He is looking down at the belay, staring into mein stricken augen blaue, then with a booming gutteral force of air his voice explodes with “ROOOOOCKKKK!!”; the call to arms of that universal activator which says, “fucking move now!” - to which one’s autonomic system - that complex network of neurons and axons governing every cell goes into overdrive, with norepinephrine and adrenaline blasting through dopamine’s enzymatic conversion to maximize the “Fight or Flight” instincts which must be concurrently acknowledged by higher-order consciousness while not succumbing to bullshit that will absolutely get a climber killed - reactive-only-action.

Reactive response exists in contrast to a specialized and challenging to acquire-adapt-improve skill set which allows higher-order consciousness to shunt autonomic signals via a process of sensory-aware sensory-fuckoffedness cognitive control mode - the name of which might not have a formal name at all. It’s simply what I learned while climbing mountains without ropes and not trying to die; so maybe it’s called the "Try Not To Die Method of Getting High"

Dopamine is converted into norepinephrine by the enzyme “Dopamine Beta-Hydroxylase” (DBH), which is located inside synaptic vesicles. Conversion occurs after dopamine is actively transported into the vesicle, distinguishing it from earlier synthesis steps which occur in the cytoplasm.

Norepinephrine is then converted into epinephrine (adrenaline) by the enzyme “Phenylethanolamine N-Methyl-Transferase” (PNMT).

This final step takes place in the cytoplasm of chromaffin cells in the adrenal medulla and requires S-adenosylmethionine (SAM) as a methyl donor; PNMT activity is induced by glucocorticoids.

It’s an electrifying sensation as the mind detaches from space-time to operate in a slow-motion rapid response. Every moment, every unit of time, concurrently experienced in its duality - rapid movement in slow motion; if you know, you know, otherwise words will do this no justice to describe. Everything is now, and that now is perfect, and that now never wants to let you leave or vice-versa. It is not reproducible in a lab, or a capsule, or ETOH bound liquid.

Try as I might over the years to reproduce it via neuropharmacology it remains mostly (though not entirely) elusive; bothering with this only by the time I was no longer able to climb, nor to ride, row, ski, or engage in any of the momentums which have tethered me so strongly to this thread of existence. That thread is slipping now, faster, with one trajectory ~ and I am no longer roped.

That state of now existed in moments hard fought, sometimes not won - but in retreat to safer conditions - a battle that exists in the mind, driven by the body, always coming back for more. Why else would two people rope up to climb a “wall of rock and ice that did not exactly need climbing”? It was not for food subsistence, nor tangible profit, but for health - not “have a whatever every day for cardiac health” - for health of the mind and body. To experience that leading edge from start to finish, in slow and then fast and then into the now of tunnel-vision focus; where nothing else mattered, the vertical calling.

Not Interested in Outpatient Care, the Treatments Don’t Work

This level of time-aware physical detachment, amplified cognition, boosted sensorial awareness, is perhaps the most beautiful psychologically addictive “in the good way” states of being to experience. Definitely better than the morphine drip in the ICU, the Dilaudid drip in some other ICU, better still than the Fentanyl patch during the months of long term outpatient recovery. I don’t want numbness; I don’t want death; I just want to be back on that wall.

ROCKFALL! MOVE! NOW! FASTER!
Brace the rope-holding shoulder to the wall, lock the rope-holding hand downward, set two foot-holds active, ensure three points of contact, and never let go of the belay rope - even if you’re using a GriGri style auto-locker. With a hard slap the rope’s little slack slams upward, grinding your rigging; tight quickly means the first piece held, snapping staccato means pieces are pulling out. Screaming upward after a moment, “FINISH THE FUCKING PITCH already, my ASS IS FUCKING FREEZING here!”

More rocks, more ice, keeps falling from above. His booming voice still echo’ing into the canyon in near-total darkness, the response in jest to my demands. With the sun still an hour away as we climb by headlamp, this is taking both more and less time in some sections than I had planned. The moon departs as the sun inches towards relevance. Tapping hammers at the final belay at twenty eight hundred feet, only one rope-length to go.

I lead calmly into the darkness, the “Great Unknown Yet Known”; we’ve been here before, a life of endless striving, yearning, never courting death, never to consider that it would come quickly. Then he died; not while his limp body slowly spun - still roped in the November breeze, and from those ropes he was retrieved, dying inside the Life-Flight rescue helicopter as it took his blood soaked viscera to wherever - no one survives a fall like that.

Neck Strained Skyward as Gravity Induced Andesite Impacts

Towards the rigging, towards exposed hands, rock and ice are falling at terminal velocity. Those rapid muscle-memory actions I’d practice in the dark with eyes closed as a teenager (first a figure eight, then a double, then a clove and prusiks, memorized actions hundreds of times over and over in the dark, and other knots with time).

Jolted back to the present, with immediacy I watch these hands move with trained-instinct, rapidly lashing axes to the wall. The “too large for now” chunks of October’s volcanic ash-stained ice smash into my helmet, shattering into the nothingness of the void below. Had I known the trajectory then, I would not have come home that day.

CyberKnife is a non-invasive, image-guided stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) system that uses a robotic arm to deliver high-dose radiation with sub-millimeter accuracy.

Key advantages include not being a “let’s shave part of your beautiful curls and cut a piece of the skull off, and then dig around till we find all the bad stuff!” type of treatment.

• Non-invasive radiation with no incisions, anesthesia, or recovery time.
• Fewer sessions, typically 1 to 5 visits, compared to 40+ for conventional radiation.
• Outpatient procedure allowing patients to resume normal activities immediately.
• Effective treatment for inoperable or complex tumors previously considered untreatable by surgery.

To Live and Die and Live Again

I am not a proponent of the concept of Free Will. I’m not exactly “against it”, as that lacks ontological accuracy and is slightly confusing, rather my experiences have defined limits which lead in fractals, concurrently, threads converging occasionally, splitting again.

Data caching at The Edge isn’t always from Fastter or Cuntter or Cloudstter or whichever CDN happens to be serving your IG, Safeway, NFL, Reddit, Anthropology, or 338% of the internet’s concurrent traffic being pointless traversals like jQuery minified & brotli-fied and sent back and forth endlessly through Internet Exchanges.

Edge caching is not limited to Anthropic or OAI or whoever else’s Load-Balancer API-side “prompt cache (not yet! after LB!)” packets which “those people” are constantly complaining about, nor the hyperscalers who whitebox big CDN networks under their own headline IP.. those are not what I’m talking about when I talk about Edge Caches.

These little embedded devices which collect climate metrics, air quality data, assembly robotics, municipal awareness and telemetry data, and everything else from a very long list… they need read-heavy churn-heavy persistent storage on a filesystem optimized for tiny sized industrial NAND.

More examples for the ones of all sizes making modern life possible: that ATM you went to, the parking lot video surveillance systems, traffic light coordinator nodes, telco edge ONT routers and OOBs with SDNs, and a thousand other examples abound that are functionally ignored.

Also, robots. And factory hardware. And factories making robots that make tiny factories? Hopefully so.

Embeds Reduce CAPEX & OPEX Efficiently

So, those embedded devices usually are designed for efficiency, while not too often designed to be hammering on NAND for write-heavy storage workloads. This has caveats: devices explicitly designed for write heavy I/O on purpose, and therefore not what I’m referring to, and cases where the provisioning and/or configuration stages of fleet deployment are improperly aligned to hardware realities.

Why? Low wattage, moderate caches, and a desire to not burn out NAND when the device is located in a difficult-to-get-to location for service techs working on hardware replacement.

Most of all - we want efficient storage for embedded devices so that their operationally collected data can be stored in memory with a ECC write-back cache with “operationally consistent” garbage collection and non-invasive wear-leveling, all while the transactions are paged/queued to F2FS before async’ing upstream to a centralized data collector for aggregation.

Predator Drones Too?

Yes and no, they send their comms to LEOSAT before humanity’s “furthest from the menial and meaningless non-Elysium people” edge devices cache, aggregate, and compute roll-up analytics with inline encryption and compression via DPU offload streaming.. all the way down to LANDSAT.

Edge devices have their own little ecosystem separate from the manner in which datacenter storage network-enabled hardware operates. All by design, and always room for improvement.

Many people consider this boring tech, and would rather move fast and break things — your time is limited, people are sick of perfectly workable systems breaking all the fuckin time and they’re tired of being A/B tested on in production — doing those things makes your company’s testing policy look like an asshole. Everyone, stop being assholes. Thanks!

These Things - Why Should We Care?

You like your cell phone? How about GPS? SAT-NAV? Skylink? Drones operating up above withour your awareness? How about sector antennas for the police and emergency services? Embedded systems are streaming, caching, processing, and relaying data all over the globe and up into LEO constellations.

You don’t have to care, and you shouldn’t have to care about FSFS or drones unless you work with that side of tech, or its adjacent use cases - like living in the modern world. Everyone should care because knowledge is fundamentally important, if for no other reason at all. Do you know how the light-switch on the wall works? Same deal. Stop making excuses for saying you don’t know or don’t care or you will be left behind. No one is saving us but ourselves, and we must have knowledge to do so.

Recent Adventures with Standards-Definitions

I love automation. In part this is because I prefer efficiency over repetitive manual bullshit. Efficiently handling requirements means more time to do what I love:

• Hanging out by the pool with a tablet or waterproof e-ink reader.
  Way back in 2018 my e-book tally was 62 novels over the calendar year. That number has dropped off recently for trivial reasons, but the point remains that I love to read, and I love to lay out by the pool.
• What I do not love:
  Wasting time when I could be at the pool. ♥‿♥

there’s only room for two hats in my life - and this is the one for sunning

• What I’ll never not love:
  The poem on my torso, dedicated to the manner in which my departed twin lived & loved.

Standards for NAND? Standards for SD-NAND!

To the point, here’s a script that had to be blasted out a while back, while imaging so many too many industrial-spec SD/TF-cards for a fleet of distibuted data collectors. These fun little RK3588 based systems have a NPU and only an eMMC drive for the OS.

While the eMMC in question has decent specs, if it fails then it’s sadly more expensive to de-solder and re-solder and re-image the OS on eMMC, and so on these systems we use the SD NAND for the following data:

• Ephemeral scratch space and logs (eg: /var/log, /var/tmp, /tmp - nope, these go to tmpfs)
• Cache directories which are aptly named .cache or .Cache סּ_סּ
• Files which must be staged locally but have no business being on the OS mount points.
• Several other use cases that I don’t feel like describing right now; so here’s the discussion for those who love to know more more more.

### F2FS - Embedded Filesystem Performance Options

- Ref: https://docs.kernel.org/filesystems/f2fs.html

#### Option Flags and Reasoning

##### For High-Churn I/O
This is less ideal, but sometimes a `tmpfs` overlay isn't an option, so it's better than burning out the eMMC. A good industrial SD card has ECC, wear-leveling, checksum validations, write-amplification controls, etc. Don't care for those features? You may one day...

Example Writes: data persistent log-sync, package builds on-device, container writable layers, time-series compressible metrics, telemetry buffers, or small-file caches, opt for the non-default `-o 10` flag. 

| Option                      | Rationale              |
| --------------------------- | -----------------------|
| `-l DATA`                   | Stable label for `/etc/fstab`; avoids relying on device enumeration order. UUID is an alternative, but requires programmatic parsing of `blkid` output, or manually specifying a UUID to pass to the FS creation process.. or you can simpy use a GPT label. |
| `-o 5`                      | Reserves 5% of the F2FS volume for the F2FS cleaner. `mkfs.f2fs` documents this as hidden overprovision space used by the cleaner. |
| `-t 1`                      | Performs discard/TRIM at format time; defaults discard to enabled, but some card readers/cards mishandle it; use `-t 0` if format stalls or logs errors |
| `extra_attr`                | Required by several modern F2FS features. |
| `inode_checksum`            | Adds inode metadata checksums; useful for removable flash and unattended systems. |
| `sb_checksum`               | Adds superblock checksum support. |
| `flexible_inline_xattr`     | Modern xattr layout; useful with `extra_attr` and future feature expansion. |
| `inode_crtime`              | Adds inode creation-time support; low cost, useful for forensic/debug visibility. |
| `lost_found`                | Creates lost+found support for recovery workflows. |
| `compression`               | Good for compressible write-heavy data; poor fit for already-compressed media, model files, archives, database pages, and random-write workloads. |
| `compress_algorithm=zstd:3` | Validate performance of zstd compression options before using for production purposes. |
| `compress_log_size=%u`      | Support configuring compress cluster size. The size will be `4KB * (1 << %u)`. The default and minimum sizes are 16KB. |
| `checkpoint_merge`          | Self-describing (or check the refs)  |
| `nocheckpoint_merge`        | Disable checkpoint merge feature. |

- `checkpoint=%s[:%u[%]]`: Set to "disable" to turn off checkpointing. Set to "enable" to re-enable checkpointing. Is enabled by default. 

- `checkpoint_merge`
When checkpoint is enabled, this can be used to create a kernel daemon and make it to merge concurrent checkpoint requests as much as possible to eliminate redundant checkpoint issues. Plus, we can eliminate the sluggish issue caused by slow checkpoint operation when the checkpoint is done in a process context in a cgroup having low i/o budget and cpu shares.

- `compress_algorithm=%s`
- `compress_algorithm=lzo-rle`

Control compress algorithm, currently f2fs supports "lzo", "lz4", "zstd" and "lzo-rle" algorithm.

- `compress_algorithm=%s:%d`

Control compress algorithm and its compress level.. only "lz4" and "zstd" support compress level config and those algos may be in your kernel config and may not.. but you'll find out quickly if you don't already know the answer.

========= =========== algorithm level range ========= =========== lz4 3 - 16 zstd 1 - 22 ========= ===========

- `compress_log_size=%u`
Support configuring compress cluster size. The size will be `4KB * (1 << %u)`. The default and minimum sizes are 16KB.

- `compress_extension=%s`

Support adding specified extension, so that f2fs can enable compression on those corresponding files.
If all files with `.ext` has high compression rate, we can set the `.ext` on compression extension list and enable compression on these file by default rather than to enable it via ioctl.

For other files, we can still enable compression via ioctl. Note that, there is one reserved special extension `*`, it can be set to enable compression for all files.

- `nocompress_extension=%s`

Support adding specified extension, so that f2fs can disable compression on those corresponding files, just contrary to compression extension.
If you know exactly which files cannot be compressed, you can use this.

> The same extension name can’t appear in both compress and nocompress extension at the same time.

If the compress extension specifies all files, the types specified by the nocompress extension will be treated as special cases and will not be compressed.
After add nocompress_extension, the priority should be: `dir_flag < comp_extention,nocompress_extension < comp_file_flag,no_comp_file_flag`.

- `compress_chksum`
Support verifying chksum of raw data in compressed cluster.

- `compress_mode=%s`
Control file compression mode: "fs" and "user". In "fs" mode (default), f2fs does automatic compression on the compression enabled files. In "user" mode, f2fs disables the automaic compression and gives the user discretion of choosing the target file and the timing.

The user can do manual compression/decompression on the compression enabled files using ioctls.

- `compress_cache`
Support to use address space of a filesystem managed inode to cache compressed block, in order to improve cache hit ratio of random read.

- `inlinecrypt`
When possible, encrypt/decrypt the contents of encrypted files using the blk-crypto framework rather than filesystem-layer encryption.
This allows the use of inline encryption hardware. The on-disk format is unaffected.

- `atgc`
Enable age-threshold garbage collection, it provides high effectiveness and efficiency on background GC. No one likes garbage.

- `discard_unit=%s`
Control discard unit, the argument can be "block", "segment" and "section", issued discard command’s offset/size will be aligned to the unit, by default, "`discard_unit=block`" is set, so that small discard functionality is enabled.

For blkzoned device, "`discard_unit=section`" will be set by default, it is helpful for large sized (fucccck off with SMR, less fucks to ZNS) devices to reduce memory cost by getting rid of fs metadata supports small discard (ouch, ever get burned by SMR? yeah... just don't bother).

- `age_extent_cache`
Enable an age extent cache based on rb-tree. It records data block update frequency of the extent per inode, in order to provide better temperature hints for data block allocation.

- `errors=%s`
Specify f2fs behavior on critical errors. This supports modes: "`panic`", "`continue`" and "`remount-ro`", respectively, trigger panic immediately, continue without doing anything, and remount the partition in read-only mode.

By default it uses "`continue`" mode, not my choice.

====================== ===============
mode continue remount-ro panic ====================== ===============
access ops normal normal N/A syscall errors -EIO -EROFS N/A mount option rw ro N/A pending dir write keep keep N/A pending non-dir write drop keep N/A pending node write drop keep N/A pending meta write keep keep N/A ====================== ===============

- `nat_bits`
Enable nat_bits feature to enhance full/empty nat blocks access, by default it’s disabled.

- `lookup_mode=%s`
Control the directory lookup behavior for case-folded directories. This option has no effect on directories that do not have the casefold feature enabled.

======================================== Value Description

perf (Default) Enforces a hash-only lookup. The linear search fallback is always disabled, ignoring the on-disk flag. compat Enables the linear search fallback for compatibility with directory entries created by older kernel that used a different case-folding algorithm. This mode ignores the on-disk flag. auto F2FS determines the mode based on the on-disk SB_ENC_NO_COMPAT_FALLBACK_FL flag.

----

#### Benchmarking F2FS Compression

Always validate the compression algo used before using those options, as performance of one algo vs anther can vary widely across different CPU generation and architectures, as well as for hosts with algo/hash compression offloading engines. We can cover benchmarking these in another script.

> lzo, lz4, zstd, lzo-rle algorithms

##### Create Partitions

DEV=/dev/sdX sgdisk –zap-all “$DEV” sgdisk -a 2048 -n 1:2048:-16G -t 1:8300 -c 1:DATA “$DEV” partprobe “$DEV”

##### Create FS

mkfs.f2fs -f
-l DATA
-o 10
-t 1
-O extra_attr,inode_checksum,sb_checksum,flexible_inline_xattr,inode_crtime,lost_found,compression,compress_algorithm=zstd:3 “${DEV}1”

#### FS Tab Entry

##### Conservative defaults

LABEL=DATA /srv/data f2fs rw,noatime,nodiratime,lazytime,nofail,background_gc=on,gc_merge,checkpoint_merge,flush_merge,mode=adaptive,fsync_mode=posix,nodiscard 0 0

##### Compression-capable variant

LABEL=DATA /srv/data f2fs rw,noatime,nodiratime,lazytime,nofail,background_gc=on,gc_merge,checkpoint_merge,flush_merge,mode=adaptive,fsync_mode=posix,nodiscard,compress_algorithm=lz4,compress_chksum,compress_mode=fs 0 0

#### Selectively Mark Compressible Directories
Do not enable compression broadly for LLM model files, videos, archives, SQLite databases, or opaque binary blobs unless benchmarks show a benefit.

mkdir -p /srv/data/_logs /srv/data/_caches.compressible chattr +c /srv/data/_logs /srv/data/_cache.compressible

So, Maybe This is Scriptable?

It sure is, or by Ansible playbook, or Salt sync, perhaps even a CFengine golden image.

That’s a lot of blah blah blah. How about that script?

Efficiency, indeed. Here ya go. The benchmarking script is for another day, or you can check out this workload primer about the filesystem from USENIX (w/ link to slide deck), and a benchmarking script which has been customized for F2FS.

#!/usr/bin/env bash
# -*- mode: sh; sh-basic-offset: 4; sh-shell: bash; coding: utf-8; indent-tabs-mode: nil; -*-
# ----------------------------------------------------------------------- #
set -euo pipefail
# ----------------------------------------------------------------------- #
# Purpose: POSIX-syntax wrapper to partition and format a non-boot SD/microSD card as F2FS with optional compression.
# NAND Profile: embedded I/O, kernel 6.1+, ECC industrial spec controller.
# WARNING: this destroys data on the selected block device, so be aware.
# ----------------------------------------------------------------------- #

usage() {
    cat <<'USAGE'
Usage:
  format-f2fs-sd-data.sh -d /dev/DEVICE [-l LABEL] [-r RESERVE_GIB] [-o F2FS_OP_PERCENT] [-c]

Examples:
# ----------------------------------------------------------------------- #
  ./format-f2fs-sd-data.sh -d /dev/sdX -l DATA -r 16 -o 5
  ./format-f2fs-sd-data.sh -d /dev/mmcblk0 -l DATA -r 24 -o 8 -c

Options:
# ----------------------------------------------------------------------- #
  -d  Whole block device to erase and partition: /dev/sdX -OR- /dev/mmcblk0
  -l  F2FS label. Default: DATA
  -r  GiB left unpartitioned at end for card FTL spare area. Default: 16
  -o  F2FS hidden overprovision percentage for the F2FS cleaner. Default: 5
  -c  Enable F2FS compression feature at format time. Mount options and chattr are still required.

Dependencies:
# ----------------------------------------------------------------------- #
  sgdisk, partprobe, mkfs.f2fs, lsblk
# ----------------------------------------------------------------------- #
USAGE
}

# Basic Variables
# ----------------------------------------------------------------------- #
LABEL=DATA
RESERVE_GIB=16
OP_PERCENT=5
COMPRESS=0
DEVICE=

# Define ARGV Mappings
# ----------------------------------------------------------------------- #
while getopts 'd:l:r:o:ch' opt; do
    case "$opt" in
        d) DEVICE=$OPTARG ;;
        l) LABEL=$OPTARG ;;
        r) RESERVE_GIB=$OPTARG ;;
        o) OP_PERCENT=$OPTARG ;;
        c) COMPRESS=1 ;;
        h) usage; exit 0 ;;
        *) usage; exit 2 ;;
    esac
done

# Sanity Checks
# ----------------------------------------------------------------------- #
if [ -z "$DEVICE" ]; then
    usage >&2
    exit 2
fi

case "$DEVICE" in
    /dev/sd?|/dev/sd??|/dev/mmcblk[0-9]|/dev/nvme[0-9]n[0-9]) ;;
    *)
        echo "Refusing suspicious device path: $DEVICE" >&2
        exit 2
        ;;
esac

# Validate Deps & Check Limits
# ----------------------------------------------------------------------- #
for cmd in sgdisk partprobe mkfs.f2fs lsblk; do
    if ! command -v "$cmd" >/dev/null 2>&1; then
        echo "Missing required command: $cmd" >&2
        exit 1
    fi
done

if [ ! -b "$DEVICE" ]; then
    echo "Not a block device: $DEVICE" >&2
    exit 1
fi

case "$RESERVE_GIB" in
    ''|*[!0-9]*) echo "Reserve GiB must be an integer" >&2; exit 2 ;;
esac
case "$OP_PERCENT" in
    ''|*[!0-9]*) echo "F2FS OP percentage must be an integer" >&2; exit 2 ;;
esac

case "$DEVICE" in
    /dev/mmcblk*|/dev/nvme*) PART=${DEVICE}p1 ;;
    *) PART=${DEVICE}1 ;;
esac

# Define Default F2FS Options
# ----------------------------------------------------------------------- #
FEATURES='extra_attr,inode_checksum,sb_checksum,flexible_inline_xattr,inode_crtime,lost_found'
if [ "$COMPRESS" -eq 1 ]; then
    FEATURES=${FEATURES},compression
fi

# Make Sure...
# ----------------------------------------------------------------------- #
echo "About to DESTROY all data on: $DEVICE"
lsblk -o NAME,SIZE,MODEL,SERIAL,TRAN,RM,RO,FSTYPE,MOUNTPOINTS "$DEVICE" || true
echo
echo "New partition: $PART"
echo "Label: $LABEL"
echo "Unpartitioned reserve at end: ${RESERVE_GIB} GiB"
echo "F2FS OP: ${OP_PERCENT}%"
echo "F2FS features: $FEATURES"
echo
printf 'Type YES to continue: '
read ans
if [ "$ans" != YES ]; then
    echo "Aborted."
    exit 1
fi

# Best Effort Unmount for Existing Partitions (please don't need this)
# ----------------------------------------------------------------------- #
if command -v findmnt >/dev/null 2>&1; then
    findmnt -rn -S "$DEVICE" -o TARGET 2>/dev/null | while IFS= read -r mp; do
        [ -n "$mp" ] && umount "$mp" || true
    done
fi

# And then...
# ----------------------------------------------------------------------- #
sgdisk --zap-all "$DEVICE"
sgdisk -a 2048 -n "1:2048:-${RESERVE_GIB}G" -t 1:8300 -c "1:${LABEL}" "$DEVICE"
partprobe "$DEVICE" || true
sleep 2

if [ ! -b "$PART" ]; then
    echo "Partition node did not appear: $PART" >&2
    lsblk "$DEVICE" >&2 || true
    exit 1
fi

# OhhhShitHandlers
# ----------------------------------------------------------------------- #
# NOTE: -t 1 performs initial discard when supported; if it's hanging here, rerun manually with -t 0
mkfs.f2fs -f -l "$LABEL" -o "$OP_PERCENT" -t 1 -O "$FEATURES" "$PART" && \
sync

# Display Block Devs
# ----------------------------------------------------------------------- #
lsblk -o NAME,SIZE,MODEL,SERIAL,TRAN,RM,RO,FSTYPE,LABEL,UUID,PARTUUID,MOUNTPOINTS "$DEVICE"

echo "[COMPLETE]"
# ----------------------------------------------------------------------- #
# EOF #
# ----------------------------------------------------------------------- #

Generally, unless one gets paid to deal with OBS/Tel and SLA conformance.. ehh. Except that the modern world operates within the bounds of a diverse and often not-fascinating array of performance indicators and services’ operating metrics.

So.. Here are two for today.

• KPI == Key Performance Indicator
• SLO == Service Level Objective

Minor Backstory - Today

While aggregating directory content from several workstations into a unified NFS remote mount,(can’t simply have one workstation, right? right), another encounter with SLO defs appears upon the terminal.

This time it’s for LLM Inference customers and their typical requirements. Perhaps our standards repository would be helpful as an adjunct resource:

• https://github.com/yukon-systems/YukonSYS-Standard-Definitions

Inference Service KPIs by Sector

An extension of distributed cloud services architecture with heavy focus on baremetal with VMs and Containers throughout. Many ways to solve the problems, scale the infra, etc.

SLO Additions to the Classifier Repo

• This file is a compact companion to the observability + telemetry glossary.
• Each threshold is a starting point and should be tightened to real-world workload SLOs after baselining standard operations.

Global Policy Adjustments

• baseline_window:
  • 7d median or p50/p95 baseline unless otherwise stated
• slo_policy:
  • page: error budget burn rate > 14.4 over 1h and 5m, or > 6 over 6h and 30m
  • ticket: error budget burn rate > 1 over 3d and 6h
• capacity_policy:
  • warn: sustained > 80% of validated steady-state capacity
  • critical: sustained > 90% of validated steady-state capacity or latency inflects above SLO
• regression_policy:
  • warn: > 1.10x to 1.25x baseline depending on sector sensitivity
  • critical: > 1.20x to 1.50x baseline depending on sector sensitivity

Reference Considerations

• Thresholds are starting operational thresholds, not universal laws.
• Where a standards or vendor reference provides an acceptable range, that range is used.
• Where no universal value exists, thresholds are either SLO-derived or baseline-relative (typically against a 7d median or a validated capacity envelope).
• For latency-sensitive sectors, alert on percentile regressions and budget exhaustion, not averages.

92d+ Uptime on Custom Gentoo Stage4 LiveISO

And that was a decent go on this build; one simply avoids ever using GCC and SystemD – use LLVM/Clang + OpenRC, and.. wow.. it’s like 2006 when things worked, Cobalt RaQ was still in the colo by the grids, an E10K or a few hundreds were still in service and would continue to stay online for years to come.

Oh, and admins and engineers didn’t avoid UNIX tools or determine ifconfig or netstat had to be "deprecated" (please, fuck off). So, get rid of the trash and then the systems become substantially more stable on the daily. Personally I trust my own ability to run and automate fleets of systems, not a tangled mess of low-hanging-fruit nod-to-redmond that most linux distros are suffered to use (CVE town is so rad, ja?)

92 days of uptime is generally close to mean value, and unfortunately it was ruined by having to upgrade the BMC and BIOS firmware versions due to “reasons”. Everything is being upgraded just in case because of the Github CVE in May. It’s wrecked so many upstream tools and sites and services and so many people are scrambling as if Log4J had just shit the bed and fell back asleep. But don’t worry.. “no customers were impacted” 😂

Anyway, Resuming to Workstations and Stage4

While there have been improvement on recompiles when optimizing test nodes’ kernels and enabling accelerators, the CI system for the building stages was upgraded to enable portage to use cross-datacenter distcc (distributed compiling) over a decent 5GbE symmetric fiber from a lab-rack to the colo cross-connect. Then the jobs are spooled off to SLURM nodes, rebuilding thin-LTO, PaX, PAE, ASLR. Very similar to a distributed Poudtierer, but without the memories of Poutine (and I love a good Poutine, especially in a light snowstorm in Banff, at least as much as the Chinese restaurant on the first left into town).

How many times do I need to follow this type of flowchart (made it, wow, so amazing) every time Supermicro releases a new BMC or BIOS upgrade? Dell, you’re not much better but at least the release notes are decent and there’s the Yum/Deb repo (one of these days I’ll put my Gentoo + Dell Driver overlay into a public git repo (not on git/msft-hub.com) for other Gentoo PowerEdge users to more easily remain up-to-date on firmware packages (fwupdmguur does’t cover everything, and the last time I trust it not to shit the bed it bricked my Thinkpad X1 Nano - thanks brosefs (am I saying that right? ehh).

fuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu

Acronyms

• TTFT == Time to First Token
• ITL == Inter-Token Latency
• TPOT == Time per Output Token
• E2E == end-to-end
• TKS == tokens/sec
• RPS == requests/sec
• QPS == queries/sec
• KV/C == Key-Value Cache

LLM Dataset Training

HPC + HFT Analytics Infrastructure

SLA + SLO Reliability, Telemetry, Alerting

• Pre-Defined latency/error/throughput SLIs and error budgets require burn-rate alerting
• Prometheus and Alertmanager define scrape and notification timing controls
• OpenTelemetry defines histograms and exemplars
• Apdex is a standard user-satisfaction score
• Elastic APM measures application performance traces

Shared Analytics of Interest

For those not familiar, the SoW is a consulting agreement between contractor and employer, which defines the scope and timeline and requirements etc to “do the needful” in a broader sense of everyone’s favorite phrase from the ‘ol “Follow the Sun” SLA support model from the early pre-Cloud era (sorry cloudbabies it’s from when you were single digits old or not yet born).

This specific SoW has been used in prior endeavors which eventually follow the typical enterprise hardware lifecycle in no specific order [1]: forklifts, retros, rebuilds, expansion, and… words.. so many words.

Labs last a long time, so it’s important to build things correctly the first time - not waste time hacking together whatever compromised decision trees were necessary due to last-minute planning (or no planning at all) and little to no experience with building labs. Remember, if you are a specialized engineer who excels in one or two areas, that does not imply domain specific knowledge from adjacent or entirely different sides of engineering worlds. I’m a systems architect .. I don’t build jet engines (though it’s probably fun), so I do what I’m good at. Otherwise to say, “stay in your lane or learn to love losing - but protect that ego at all costs and never admit fault ever!” (yes, I’m bitter and for exceptionally valid reasons).

So, until the pre-IPO runway runs out, or the post-IPO environment bores people to tears and they jump ship with their ISOs and RSUs and START ALL OVER AGAIN! (I have definitely never not done this exact thing several times never for sure for sure? sure.)

Successful Labs Require People and Hardware

Vaporware labs don’t have hardware. Real labs do not revolve around PPTX slide decks, or Slack Canvas, or Sharepoint whatever, or ephemeral Confluence pages that change ownership by a click of a button. Real labs have real hardware and real engineers and architects involved at every critical stage to ensure that standards are being used, implemented, tested, and validated.

If you think I’m wrong, go ahead, do it all by slide deck, by half-baked simulators that don’t even use SST and parallelization correctly, with lots of Big Discussions for the Big People you want to impress to get ahead instead of making quality hardware.

See how far the Peter Principle gets you - chances are, if you’re surrounded by “Yes Men” and “C-Suite but never Technical” boardrooms, you will get far enough to be proven the fraud that you are.

The Peter principle is a concept in management .. which observes that people in a hierarchy tend to rise to “a level of respective incompetence”: employees are promoted based on their success in previous jobs until they reach a level at which they are no longer competent, as skills in one job do not necessarily translate to another.

Having risen rapidly, since you’re up high now - you can destroy entire companies by making extremely stupid choices “to save money” by not spec’ing hot-swap trays for NVMe drives on 1U systems which were never designed for the wattage you’re running - and were not spec’d for the BTU and LFM required to keep the systems from burning out 100G optics..

Just when you think it’s all good, um why are there only seven drives in this chassis that can run with eight?

• Oh it’s because the 8th drive would draw too much power and overload the non-redundant PSUs. What happens when a system which should have N+1 has only N?
• The PSUs could be in redundant mode but Billy didn’t want to authorize the enablement of active/active mode, and instead has demanded that his lacky make the systems run the PSUs in “combined mode” to try to get more power to that 8th drive… but no… not possible.
• So all of the fancy new systems can’t have eight drives like the original spec REQUIRED in order to fulfill global fleet machine generation scaling models. As in, you lose 1/8th of your drives on every new system for so many thousands of systems. 1/8th, for those not inclined to fractional conversions, is
• So now all of those systems will be missing ~2-16-64TB of NVMe drives (multiply by number of nodes per rack, per pod, per cage, per site, per region, per global fleet). That’s a lot of expected high-speed storage that is now not being deployed.
• Hopefully no contracts were made to customers based on “Total NVMe Raw Storage per <unit/region/etc>” variables, which now renders the deliverable impossible.
• What can be done? Those contracts have to either be revised and compensated (yeah good f’in luck), or a massive workaround must be implemented to compensate - at additional cost to the company.

Why does that matter to building labs?

Because any lab worth their salt would have raised immediate red flags and halted the entire ill-devised scope. Then they would use standardized and periodically revised for betterment:

• provide technical backing evidence
• scaling costs, IOP/s cost, power assessments, baseline to STDDEV ratio, then appropriation wear-cycle equations
• All that industry jargon that managerializes into the ether for all to repeat.
• “keep me honest” you may say, so then.. are you often lying? Ill-informed, unprepared, completely clueless?
• Maybe not, hopefully not, but analytical people will see you that way and eventually the Peter Principle catches up and BAM! You’re hit by a and your entire team is fired, and so you move on with your RSUs, talk yourself up, and try to ruin those who smote you from afar.

Congrats, Billy, you’ll never change - and that is why we test in labs - because things change.

The Contract Statement of Work

Always get the scope in writing with sign-off. Scope changes mid-stream, not awesome.

Statement of Work

Consultant Services Engagement

This Statement of Work ("SOW") is entered into between [Client Legal
Name] ("Client") and [Consultant Legal Name] ("Consultant"), effective
as of [Effective Date], and is governed by the [Master Consulting
Agreement / Professional Services Agreement] dated [Agreement Date] (the
"Agreement"). In the event of any conflict between this SOW and the
Agreement, the Agreement will control.

  -----------------------------------------------------------------------
  Client                              [Client Legal Name]
  ----------------------------------- -----------------------------------
  Consultant                          [Consultant Legal Name]

  SOW Effective Date                  [Effective Date]

  Initial Term                        Six (6) months from the SOW
                                      Effective Date

  Target Level of Effort              Forty (40) hours per week,
                                      approximately 1,040 hours over the
                                      initial term

  Primary Stakeholders                VP, OCTO, Eng-Org, App-Team, and
                                      Sales-Org

  Commercial Terms                    Billing rate, invoicing, payment
                                      terms, and approved expenses as set
                                      forth in the Agreement and/or
                                      applicable order form
  -----------------------------------------------------------------------

1. Purpose and Objectives

The Consultant will provide technical leadership, architecture,
implementation, documentation, mentoring, and subject matter expertise
to establish standardized HPC benchmarking, workload automation, and
telemetry/analytics capabilities, while also improving cross-functional
execution and the overall developer experience for CORP products and
associated collateral.

- Define, document, and deploy a modular "Industry Expectations
  Benchmark Suite" leveraging HPC, SPEC, Top500, AI/ML GPU leaderboards,
  and SNIA methodologies to support rigorous adherence and consistent
  results using standard performance testing tools.

- Define and deploy a standardized HPC "Workload Automation Pipeline"
  utilizing SLURM, Jenkins, Celery, RabbitMQ ("RMQ"), ClickHouse,
  Ansible, and related tooling.

- Define and deploy a standardized HPC "Telemetry + Analytics
  Aggregation + Data Visualization Processing Pipeline" utilizing
  Check_MK, SNMP, Elasticsearch + Kibana, Prometheus, InfluxDB, Grafana,
  and related tooling.

- Assess current organizational working patterns across Eng-Org,
  App-Team, and Sales-Org and provide a quarterly review to the VP and
  OCTO.

- Assess the current CORP collateral surface area, including SDKs,
  documentation, libraries, proofs of concept, and reference designs, as
  an ongoing initiative to improve the developer experience.

- Author white papers, research documents, and related technical
  materials, with a feedback loop to validate and improve internal and
  external documentation.

- Provide mentoring for junior through senior application and systems
  engineers, plus reasonable availability as an SME across storage,
  systems, database, and AI/ML domains.

- Provide ad hoc consultation to support Sales-Org customer scoping,
  implementation, and integration needs.

2. Term and Working Model

The engagement will begin on the SOW Effective Date and continue for an
initial six (6) month term. The Consultant will generally allocate forty
(40) hours per week to the engagement, subject to mutually agreed
priorities, holiday schedules, and reasonable scheduling adjustments.

The parties acknowledge that some workstreams in this SOW are ongoing or
iterative in nature. Accordingly, the Client and Consultant will jointly
prioritize and sequence the work so that the highest-value deliverables
are completed within the available time and level of effort.

Services may be provided remotely or through other mutually agreed
working arrangements. Any onsite work, travel, or work materially
outside the target level of effort will require prior written approval.

3. Scope of Services

3.1 Modular "Industry Expectations Benchmark Suite"

The Consultant will define, document, and deploy a modular benchmark
suite intended to measure representative performance, reproducibility,
and adherence to industry-standard methodologies across compute,
storage, and AI/ML use cases.

Illustrative deliverables:

- Benchmark taxonomy and workload catalog covering applicable HPC, SPEC,
  Top500-style, AI/ML GPU leaderboard-relevant, and SNIA-aligned
  methodologies.

- Benchmark execution standards, parameterization guidance, and runbooks
  designed to improve repeatability and result consistency.

- Result templates and reporting conventions for capturing baseline
  measurements and comparative findings.

- Initial implementation and/or deployment in designated Client
  environment(s), subject to infrastructure readiness and access.

- Validation summary describing observed results, known limitations, and
  next-step recommendations.

3.2 Standardized HPC "Workload Automation Pipeline"

The Consultant will define and deploy a standardized HPC workload
automation architecture using SLURM, Jenkins, Celery, RMQ/RabbitMQ,
ClickHouse, Ansible, and related tools as appropriate to the Client
environment.

Illustrative deliverables:

- Reference architecture and component interaction design for job
  submission, orchestration, execution, retry handling, and result
  capture.

- Deployment-ready configurations, automation artifacts, or initial
  implementation in designated environment(s).

- Operational workflows for benchmark or workload scheduling, execution,
  data collection, and reporting.

- Runbooks and handoff documentation sufficient to support repeatable
  operation and internal adoption.

3.3 Standardized HPC "Telemetry + Analytics Aggregation + Data
Visualization Processing Pipeline"

The Consultant will define and deploy a standardized observability and
analytics processing pipeline spanning infrastructure telemetry,
log/event aggregation, time-series monitoring, analytics storage, and
visualization.

Illustrative deliverables:

- Reference architecture covering Check_MK, SNMP, Elasticsearch +
  Kibana, Prometheus, InfluxDB, Grafana, and related integrations as
  applicable.

- Recommended data model, retention approach, dashboard structure, and
  operating practices for standardized reporting and analysis.

- Initial dashboards, visualizations, and/or deployment artifacts for
  designated environment(s).

- Documentation for data sources, ingestion paths, dashboards, and
  operational ownership considerations.

3.4 Cross-Functional Collaboration Assessment

The Consultant will assess current organizational working patterns
across Eng-Org, App-Team, and Sales-Org in order to identify friction
points, handoff gaps, role ambiguity, communication issues, and
opportunities to improve execution.

Illustrative deliverables:

- Current-state assessment and concise findings memo.

- Recommendations for cadence, decision ownership, communication flow,
  and escalation patterns.

- Quarterly review readout(s) presented to the VP and OCTO during the
  engagement term.

3.5 CORP Collateral Surface Area and Developer Experience

The Consultant will assess the current ‘surface area’ of CORP collateral,
including SDKs, documentation, libraries, proofs of concept, and
reference designs, as an iterative stretch initiative with the overall
goal of improving the developer experience.

Illustrative deliverables:

- Inventory and gap analysis of current CORP technical collateral.

- Prioritized recommendations and/or backlog themes to improve
  consistency, usability, completeness, and customer/integrator
  experience.

- Feedback loop for validating and improving internal and external
  documentation and supporting artifacts.

- Periodic progress updates and next-step roadmap recommendations within
  the engagement window.

3.6 White Papers, Research Documents, and Documentation Improvement

The Consultant will author white papers, research documents, technical
notes, and similar written materials as prioritized by the Client, and
will help create a feedback loop to validate and improve internal and
external documentation quality.

Illustrative deliverables:

- White papers, technical briefs, research documents, architecture
  notes, or similar written outputs as mutually prioritized.

- Document review comments, revision recommendations, and technical
  fact-checking input.

- Structured feedback loop to capture lessons learned and improve future
  documentation quality.

3.7 Mentoring and Knowledge Transfer

The Consultant will provide mentoring support for junior through senior
application and systems engineers, with an emphasis on practical
technical development and hands-on knowledge transfer.

Illustrative deliverables:

- Office hours, design reviews, pair-working sessions, workshops, or
  other mentoring interactions as appropriate.

- Guidance on benchmarking, automation, observability, storage, systems,
  database, and AI/ML topics relevant to the engagement.

- Knowledge transfer materials or summary notes where appropriate to
  support broader team adoption.

3.8 SME Availability and Sales-Org Consultation

The Consultant will maintain reasonable availability to organizational
staff in applicable subject-matter areas of focus and will provide ad
hoc consultation for Sales-Org customer scoping, implementation, and
integration needs, as capacity permits within the contracted level of
effort.

Illustrative deliverables:

- Advisory support for storage, systems, database, and AI/ML questions
  arising during the engagement.

- Participation in internal and customer-facing scoping discussions,
  solution reviews, or implementation planning sessions, when requested
  by the Client.

- Technical input intended to improve solution fit, implementation
  readiness, and integration clarity; provided as advisory support
  rather than as a standalone managed service or customer support
  commitment.

4. Indicative Delivery Plan

The following plan is illustrative and may be reprioritized by mutual
agreement based on Client needs, environment readiness, and emerging
business priorities.

  -----------------------------------------------------------------------
          Period          Primary Focus           Illustrative Outputs
  ----------------------- ----------------------- -----------------------
          Month 1         Discovery and Baseline  Stakeholder alignment,
                                                  current-state review,
                                                  environment access,
                                                  priority mapping,
                                                  benchmark/workload
                                                  definition, and
                                                  architecture framing.

        Months 2-3        Design and Initial      Benchmark suite v1,
                          Deployment              automation pipeline
                                                  design and initial
                                                  deployment artifacts,
                                                  telemetry pipeline
                                                  design, and initial
                                                  dashboards or data
                                                  paths.

        Months 4-5        Validation and          Validation runs,
                          Expansion               documentation
                                                  expansion,
                                                  collaboration
                                                  assessment findings,
                                                  collateral review,
                                                  white papers/research
                                                  outputs, and mentoring
                                                  support.

          Month 6         Handoff and Executive   Runbooks,
                          Review                  recommendations,
                                                  backlog or roadmap
                                                  items, knowledge
                                                  transfer, and
                                                  quarterly/executive
                                                  review presentation(s)
                                                  to the VP and OCTO.
  -----------------------------------------------------------------------

5. Governance and Reporting

- The Client will designate a primary engagement owner or point of
  contact responsible for prioritization, coordination, and consolidated
  feedback.

- The parties will maintain a regular working cadence, which may include
  weekly or biweekly syncs, technical reviews, design reviews, and
  status reporting as appropriate.

- The Consultant will provide concise updates on progress, risks,
  blockers, and recommended next actions.

- A quarterly review readout will be provided to the VP and OCTO during
  the engagement term.

6. Assumptions, Dependencies, and Constraints

- The Client will provide timely access to relevant systems,
  environments, credentials, documentation, repositories, data, and
  subject-matter stakeholders reasonably required for the services.

- The Client is responsible for providing or approving the hardware,
  software, licenses, network access, security approvals, and
  change-management windows required to implement or deploy
  deliverables.

- Any production deployment, change control, or release activity remains
  subject to Client approval processes and operational safeguards.

- Where this SOW references industry-standard benchmarks or
  leaderboard-adjacent methodologies, any formal external publication or
  third-party submission will remain subject to separate Client approval
  and third-party rules.

- The Consultant’s work product may include recommendations, reference
  architectures, configurations, code or scripts, runbooks, dashboards,
  presentations, reports, and live working sessions; not every
  workstream will result in a standalone written deliverable.

- Because certain activities are advisory and ongoing in nature, the
  parties will periodically rebalance priorities to remain within the
  contracted time and level of effort.

- Travel, onsite presence, after-hours support, and work materially
  beyond the initial term or weekly level of effort are excluded unless
  separately approved in writing.

7. Out of Scope

- Managed services, long-term production operations ownership, or 24x7
  operational support.

- Hardware procurement, datacenter installation, or unrelated
  infrastructure build-out not directly tied to the services described
  in this SOW.

- Binding commitments to end customers, contractual promises to third
  parties, or customer project delivery obligations not expressly
  authorized by the Client.

- Ongoing maintenance, enhancement, or support of deliverables after the
  end of the engagement term, except as separately agreed in writing.

8. Acceptance and Change Control

Commercial terms, invoicing, payment terms, intellectual property,
confidentiality, warranties, limitation of liability, and any formal
acceptance procedures will be governed by the Agreement.

Where the Agreement does not specify a separate acceptance procedure,
the Client will review deliverables promptly and provide consolidated
feedback within five (5) business days after delivery. Deliverables will
be deemed accepted when they materially conform to the scope described
in this SOW, subject to any documented punch-list items or agreed
revisions.

Any material change to scope, deliverables, timeline, or level of effort
will require written approval by both parties.

9. Signatures

The parties acknowledge and agree to this SOW as of the dates written
below.

By: ________________________________ 
Name: ______________________________ 


[Consultant Legal Name]
Title: _______________________________
Date: _______________________________
By: ________________________________ 

[Client Legal Name]
Name: ______________________________
Title: _______________________________
Date: _______________________________

More details later… sleepy.

 # NeoCortex Standards, Repo Storage, ZFS Dataset, M70 QAT Fast-Track Plan

  ## Summary

  Implement a non-destructive NeoCortex follow-up that locks
  these policies into code, tests, and docs:

  - Repos live under /opt/repos/<repo>; worktrees live under
    /opt/repos/worktrees/<repo>/<branch>.
  - /root is not a repo/worktree destination; /root/OMGFUCKED is
    temporary quarantine only.
  - New repos must be created from
    yukon-systems/YukonSYS-Standard-Definitions.
  - Every repo must use Git LFS and the standards repo
    .gitattributes byte-for-byte.
  - ZFS dataset creation for /opt/repos becomes reusable
    Ansible/policy logic, based on
    /root/bin/ZFS-M70-Forge_zroot-dataset_opt-repos.sh.
  - M70 QAT rollout uses canary first: build OpenSSL+QAT and
    OpenZFS/QAT binpkgs, validate on M70 canary, then promote.

  ## Key Changes

  - Standards and repo-placement policy
      - Update NeoCortex root policy docs and tests to forbid
        new repo/worktree paths under /root, except documented
        temporary quarantine paths under /root/OMGFUCKED.
      - Update tools/import-source-repos.py defaults from
        /root/<repo> to /opt/repos/<repo>, with
        /root/OMGFUCKED/<repo> accepted only as an explicit
        transitional override.
      - Add a repo-location audit script/test that fails active
        operational docs/scripts using /root/<repo> or
        /root/.config/superpowers/worktrees as live paths.
  - Git LFS and .gitattributes
      - Replace NeoCortex root .gitattributes with the standards
        repo version byte-for-byte.
      - Add a validation script that checks:
          - git lfs version works,
          - filter.lfs.required=true,
          - origin LFS locksverify=true,
          - root .gitattributes hash equals standards source,
          - LFS pre-push hook exists.
      - Document that non-compliant repos must be retrofitted
        before migration/import.
  - ZFS dataset automation
      - Convert
        /root/bin/ZFS-M70-Forge_zroot-dataset_opt-repos.sh into
        reusable NeoCortex Ansible/defaults for managed
        datasets.
      - First managed dataset profile: zroot/opt/repos mounted
        at /opt/repos with the script’s options, including
        compression=zstd-fast-1, dedup=sha256,verify,
        recordsize=256K, xattr=sa, POSIX ACLs, atime=off, and
        reservation=32M.
      - Add a second reusable pattern for per-user home
        datasets, but do not block on the NAS/NFS 777
        investigation; include a permission preflight that
        creates a test directory with umask 0027 and fails if
        mode becomes 0777.
  - M70 QAT binpkg fast-track
      - Extend the existing M70 canary stage4/binpkg lane to
        build a QAT package set:
          - QAT firmware/kernel module readiness package policy,
          - OpenSSL QAT engine/provider package path,
          - OpenZFS package built with QAT support,
          - rollback stock OpenSSL/OpenZFS binpkgs.
      - Add package/use/profile fragments under the existing
        Gentoo stage4 profile area instead of ad hoc host edits.
      - Add canary validation:
          - lspci -nnk sees QAT device,
          - qat_c3xxx and intel_qat load,
          - OpenZFS module parameters expose QAT controls,
          - openssl speed before/after artifacts are captured,
          - root pool imports and mounts after reboot,
          - rollback binpkg path is tested before wider
            promotion.
      - Do not promote to all M70 nodes until canary evidence is
        committed.

  ## Test Plan

  - Local static checks:
      - tests/shell/run-tests.sh
      - new repo-location standards test
      - new Git LFS standards test
      - new ZFS dataset defaults test
      - new M70 QAT package-policy test
      - YAML parse for all workflows/playbooks
      - git diff --check
  - Runtime/dry-run checks:
      - Ansible syntax-check for dataset roles/playbooks.
      - Dry-run dataset plan for /opt/repos confirms current
        zroot/opt/repos matches expected options.
      - M70 canary dry-run emits QAT binpkg build plan without
        mutating packages.
  - Canary acceptance:
      - QAT binpkgs build successfully.
      - M70 canary reboots with root pool intact.
      - QAT modules and OpenZFS QAT controls are present.
      - Benchmark and rollback evidence are recorded under
        NeoCortex audit docs.


  ## Assumptions

  - Canonical repo clone layout is /opt/repos/<repo>.
  - Worktree layout is /opt/repos/worktrees/<repo>/<branch>.
  - /root/OMGFUCKED remains temporary quarantine, not an
    approved steady-state repo location.
  - QAT rollout gate is canary first, not all-M70 immediate.
  - OpenZFS QAT implementation details must be verified against
    current OpenZFS/Gentoo package behavior during
    implementation; source basis includes OpenZFS QAT docs and
    module-parameter docs:
      - https://openzfs.org/wiki/ZFS_Hardware_Acceleration_with_QAT
      - https://openzfs.github.io/openzfs-docs/Performance%20and%20Tuning/Module%20Parameters.html

─ Worked for 22m 41s
───────────────────────────────────────────────────────────
  Implement this plan?
  1. Yes, implement this plan          Switch to Default and
  start coding.
  2. Yes, clear context and implement  Fresh thread. Context:
  53% used.
› 3. No, stay in Plan mode             Continue planning with
the model.



-----------------------
  ## Assumptions

  - Canonical repo clone layout is /opt/repos/<repo>.
  - Worktree layout is /opt/repos/worktrees/<repo>/<branch>.
  - /root/OMGFUCKED remains temporary quarantine, not an
    approved steady-state repo location.
  - QAT rollout gate is canary first, not all-M70 immediate.
  - OpenZFS QAT implementation details must be verified against
    current OpenZFS/Gentoo package behavior during
    implementation; source basis includes OpenZFS
    QAT docs and module-parameter docs:
      - https://openzfs.org/wiki/ZFS_Hardware_Acceleration_with_QAT
      - https://openzfs.github.io/openzfs-docs/Performance%20and%20Tuning/Module%20Parameters.html

─ Worked for 22m 41s
───────────────────────────────────────────────────────────

› 1) We also need to include the control plane fixes and
validations so that mutli-workers comms are fixed. 2) We need to
leverage the SLURM cluster nodes and
  additional distcc build hosts, 3) X12again & FMT2 are
  effectively idle and can be blasted into submission to fast
  track all of these changes. 4) Once the
  M70-canary passes, we need to roll it out to K10 (tear-it-down
  AAA) and validate that type of OS netbooting. 5) Add those
  aspects to the Plans and we're
  looking better. 6) Finally, wrap up ALL changes necessary to
  complete the NeoCortex monorepo migration.

───────────────────────────────────────────────────────────

• I’ll revise the plan around the expanded end-state, but first
I’m doing a read-only pass over NeoCortex’s control-plane,
SLURM/distcc, X12/FMT2/K10, and
  migration-status artifacts so the replacement plan is grounded
  instead of generic.

───────────────────────────────────────────────────────────

• Proposed Plan

  # NeoCortex Standards-Complete Monorepo Migration Plan

  ## Summary

  - Make /opt/repos/<repo> the only canonical repo location; no 
  new checkouts or random repo files under any home directory, 
  including /root.
  - Finish standards adoption: all new repos must originate from 
  YukonSYS-Standard-Definitions; NeoCortex gets retrofitted 
  instead of restarted unless
    retrofit verification fails.
  - Complete NeoCortex monorepo migration with standards baseline, 
  Git LFS policy, control-plane comms fixes, ZFS dataset policy, 
  SLURM/distcc acceleration, M70 QAT canary, FMT2/X12again build 
  capacity, and K10 netboot AAA rollout validation.

  ## Key Changes

  - Repository standards
      - Merge standards policy PR work, then make NeoCortex 
      root .gitattributes byte-for-byte identical to the standards 
      repo version.
      - Update active NeoCortex import/migration tooling to default 
      source paths to /opt/repos/<repo>.
      - Preserve historical /root/... references only in immutable 
      audit/provenance docs; active scripts, runbooks, tests, and 
      templates must not depend on
        home-directory repos.
      - Use worktrees under /opt/repos/worktrees/<repo>/<branch>.
  - NeoCortex monorepo completion
      - Finish all migration blockers already tracked in 
      NeoCortex: M70 stage4/QCOW validation, Kata/container 
      runtime, FMT2 ephemeral VM lane, Gentoo/OpenRC
        replacement for temporary Rocky bootstrap, Thor replacement 
        path, and optional history graft/freeze decision.
      - Treat NeoCortex as authoritative after completion: source 
      repos become frozen compatibility references or are 
      history-grafted into NeoCortex with
        documented provenance.
      - Add/repair migration validation so PR completion proves 
      standards baseline, Git LFS, repo location policy, shell 
      tests, YAML parsing, and migration
        manifests.
  - Control-plane and multi-worker comms
      - Bring all control-plane fixes into NeoCortex and validate 
      Forge/FCP worker communication end to end.
      - Add tests for FCP envelope validation, replay/nonce handling, 
      approval ceilings, routing scope, transport policy, ntfy bridge 
      behavior, and multi-worker request/response flows.
      - Replace temporary Rocky bootstrap control-plane host with the 
      compliant Gentoo/OpenRC image once that image passes validation.
  - ZFS, NFS, and storage policy
      - Use the provided /opt/repos ZFS dataset options as the canonical 
      dataset profile for repo storage.
      - Add reusable dataset/playbook logic for repo datasets and 
      per-user home datasets.
      - Add NFS/floating-home validation that detects the NAS NFSv4.2 
      0777 directory-mode bug under expected 0027 umask and blocks 
      insecure rollout.
  - Build acceleration and hardware rollout
      - Use SLURM plus distcc for M70 stage4/QAT/OpenZFS builds.
      - Treat X12again and FMT2 as available fast-track build/validation 
      capacity.
      - Build binpkg path for OpenSSL + QAT + OpenZFS on M70 canary first; 
      non-QAT nodes may consume the same binpkgs with QAT unused.
      - After M70 canary passes, roll the validated path to K10 and 
      run destructive AAA/netboot validation with rollback evidence 
      captured.

  ## Test Plan

  - Run NeoCortex shell/YAML validation, including migration, 
  standards-baseline, Git LFS, .gitattributes, and no-active-home-repo-path 
  checks.
  - Run control-plane/FCP tests for envelope schema, replay rejection, 
  worker routing, ntfy bridge, and multi-worker comms.
  - Run Ansible/playbook syntax checks for ZFS datasets, NFS home policy, 
  SLURM/distcc build orchestration, M70 canary, FMT2/X12again lanes, and 
  K10 netboot
    AAA.
  - Execute staged hardware validation:
      1. SLURM/distcc dry-run.
      2. M70 canary build and QCOW/stage validation.
      3. FMT2/X12again accelerated build/ephemeral VM smoke.
      4. K10 netboot/AAA destructive validation after M70 success.

  ## Assumptions

  - Retrofit NeoCortex rather than restart the repo unless standards 
  validation exposes unrecoverable divergence.
  - Historical audit files may retain old /root/... paths as provenance; 
  active operational content may not.
  - M70 canary is the release gate for QAT/OpenZFS/binpkg rollout.
  - K10 destructive AAA/netboot validation is in scope only after M70 
  canary passes and rollback evidence is captured.

─ Worked for 2m 18s ───────────────────────────────────────────────────────────

prompt> In the style of “50 Cent’s, Get Rich or Die Trying”, I’d like to see an illustrated version using a combination of styles which involves crayons, magic markers, and the attached images (public domain), which follows the concept of these lyrics which should be featured in crayon within the image.

‘Get Die Or Rich Trying’

• 45 Cent, corpywright 1492

Generative Round 2

In an entirely different direction, let’s visit the unspoken nature of randomization of styles which are presently in-use by certain frontier models. The dynamic nature of styling is interesting. Perhaps on another day I’ll have time to experiment with alternate options involved with LLM post-training for generative imaging creation, eg: StableDiffusion is really amazing tech, though I’ve not used the tooling to do much more than make images of flowers during periods of burnout.

So… Let’s get on with it…

prompt> Assess the attached public domain visual images and generate a variation on the following concepts:

“Step Into My Office, Cuz Yer’ Fukin’ Fired!”
The humor derives from the hitchhiker’s aggressive, delusional confidence in a trivial marketing advantage (saving one minute of exercise time).

Ideally this contextually makes sense to the reader, though the age of the associated movie makes me wonder how the years went by so fast.

────────────────────────────────────
— Hitchhiker: You heard of this thing, the 8-Minute Abs?
— Ted: Yeah, sure, 8-Minute Abs. Yeah, the excercise video.
— Hitchhiker: Yeah, this is going to blow that right out of the water. Listen to this: 7… Minute… Abs.

— Ted: Right. Yes. OK, alright. I see where you’re going.
— Hitchhiker: Think about it. You walk into a video store, you see 8-Minute Abs sittin’ there, there’s 7-Minute Abs right beside it. Which one are you gonna pick, man?
— Ted: I would go for the 7

— Hitchhiker: Bingo, man, bingo. 7-Minute Abs. And we guarantee just as good a workout as the 8-minute folk.
— Ted: You guarantee it? That’s - how do you do that?
— Hitchhiker: If you’re not happy with the first 7 minutes, we’re gonna send you the extra minute free. You see? That’s it. That’s our motto. That’s where we’re comin’ from. That’s from “A” to “B”.

— Ted: That’s right. That’s - that’s good. That’s good. Unless, of course, somebody comes up with 6-Minute Abs. Then you’re in trouble, huh?
— Hitchhiker: No! No, no, not 6! I said 7. Nobody’s comin’ up with 6. Who works out in 6 minutes? You won’t even get your heart goin, not even a mouse on a wheel.
— Ted: That - good point.

— Hitchhiker: 7’s the key number here. Think about it. 7-Elevens. 7 doors. 7, man, that’s the number.
— Hitchhiker: 7 chipmunks twirlin’ on a branch, eatin’ lots of sunflowers on my uncle’s ranch. You know that old children’s tale from the sea.
— Hitchhiker: It’s like you’re dreamin’ about Gorgonzola cheese when it’s clearly Brie time, baby.

— Hitchhiker: Step into my office.
— Ted: Why?
— Hitchhiker: ‘Cause you’re fukin fired!
────────────────────────────────────

Also a lot of talk about Github being compromised and having 3,000+ internal repos exfiltrated. Surely GitHub has 100% Code Coverage Testing and End-to-End Test (Work)Flows, right? No, they do not.

This post is focused on E2ET (End-to-End-Testing) of application service roles and machine provisioning automation. So, let’s start by seeing just exactly WTF I’m referring to with this type of testing in the first place.

CI Systems as a “Failure Mode” Example

In the reporting system here we use a host type definition of K10 which is mostly arbitrary, but the root story is an irrelevant tangent, used in this infrastructure as an example of a standdalone system which requires specific attention to failure state definitions, stateful analysis of gated operations, and is used for iterative looped-based resolution testing.

The K10 host is assigned to a role which features CPU-native cpuid2cpuflags architecture optimized compiler flags. We never use generic kernels, or generic machines, because efficiency and optimization in the industry is basically a broken afterthought and it gets old after a while - dealing with non-optimized non-attentitive systems engineering approaches featuring inefficient broken theories based the shrug-method, “just make it auto-scaling and put more kubes or something?”

Network Booting the Baseline OS

The K10 baseline system boots over the network using iPXE/HTTPv4, while other devices require chainload PXE/TFTP -> iPXE/HTTPv4 boot images. This facilitate a system of host-based discovery and domain authentication via initrd embedded kernel modules + connection parameters for FreeIPA/SSSD for RBAC + AAA using MAC and PKE enrollment. We also do this for FreeBSD hosts, with some minor differences.

The K10 is also connected to local-rack PDUs with remote power cycling via either ACPI signal for “soft shutdown” or via its switched-outlet port. The PDUs are controlled by the Command-&-Control Server using SNMPv3 user + group authentication via its infrastrcture management LAN connection with an auth-hook to FreeIPA via RADIUS.

Let’s See Some Reports!

Having covered some blathering about provisioning systems, we can move on to agent-based querying for SITREP , which is executed on our in-house LLM structured query execution tooling. That whole chain of events required writing a new “Agentic Forge Control Plane”, which was enjoyable most of the time… and it has become a baseline distributed comms system for “Project Coherent Storage” which is currently managing a bit over 1PB of data on OpenZFS.

Earlier this year I paused for some PTO and rewrote all of my formerly Ansible driven and automated Infrastructure as Code workflows to support an upcoming revision to our dual-continent presence at six datacenter locations. It’s occasionally and very tentatively being referred to as "minimalist-maxxing" which is mostly pure nonsense where grammatical excellence is concerned, but ultimately accomplishes the following:

• Gentoo w/ Optimized Stage4, LLVM/Clang, OpenRC
• Minimalist service containers using our Stage4 baseline, with service roles layered on top. Try it out:

No, these were not Kubernetes, not Helm, not Cloudslop. Sometimes translates into Infrastructure as a Service, for enablement of event-driven architecture with a hybrid-local service enablement for LLM predictive action controls.

That’s a lot of words to say, “I make the code do the things with the signals processing and patterns and stuff.” Wait wait.. no, this is not going to cover anything about “N~less Computing”.

Stop Blathering About “Serverless Computing”

This term… it is bull-sheet top to bottom front to back.

• Serverless does not mean “no servers.” Cloud providers rely on physical infrastructure to run your code and your applications.
• The term is marketing shorthand, not architectural reality. Serverless means server management is abstracted away from developers, not eliminated, nor emancipated.
• It does not mean “no infrastructure.” Provisioning, patching, security, scaling, and runtime management are simply shifted to the provider, just like the ‘ol days where users had websites on shared hosting systems (and they still do) without having to handle, manage, or maintain the infrastructure.
• It is not always cheaper. Serverless can be cost-effective for sporadic or bursty workloads, but long-running or compute-heavy jobs may cost more than VMs or dedicated servers.
• It is not a universal replacement. Serverless differs from IaaS and PaaS by emphasizing event-driven execution, automatic scaling, and scale-to-zero behavior when idle; lies, all marketing lies. Follow the money.

[host K10]: currently has transient AAA validation, not E2ET PASS

• APC PDU AP7901 initiated hard-reboot proved the current netboot rootfs does not persist SSSD/IPA state.

Under this definition, K10 must rebuild rootfs or disk-install with aaa-domain-client, reboot, then pass the full post-boot E2ET suite before it can unblock xen-sun99-x12spl-099108.rfc1918.host reimage confidence.

Standard Example ‘K10 Automation Report’

# E2ET Definition
End to End Testing / E2ET should mean: a reproducible host acceptance pipeline that proves a machine can move from inventory intent to installed, rebooted, validated, scored, documented, and release-eligible state.

For RFC99, a host is not E2ET-passed just because we fixed it live. It passes only after the fix is represented in source-of-truth and survives the full lifecycle.

## Policy Definition
For validation hosts like `K10`:

1. Fix live only to recover evidence or confirm root cause.
2. Backport the fix into repo-owned profile, role, manifest, package list, NetBox/DNS/IPAM metadata, and docs.
3. Reinstall or rebuild/reboot through the intended provisioning path.
4. Run post-boot validation.
5. Generate a conformance report.
6. Only then mark the host RC/GA-capable.

> A one-off live fix can be marked transient validated, but never E2ET passed.

## E2ET Stages

### Host Pipeline

1. **Inventory Gate**: NetBox/IPAM/DNS/Ansible host metadata matches expected MACs, interfaces, service IPs, PDU mapping, console path, boot protocol.
2.** Provisioning Gate**: iPXE or PXE-chainload path works, installer runs, ZFSBootMenu/bootfs/rootfs pools validate, OS install completes.
3. **First Boot Gate**: kernel cmdline, serial console, hostname/FQDN, SSH, time sync, logging, package profile, OpenRC services.
4. **Platform Gate**: CPU model, RAM, disks, NVDIMM/Optane if present, sysfs, kernel modules, firmware, CVE mitigation status.
5. **Network Gate**: management interface, service interfaces, VLANs, routes, DNS forward/reverse, NetBox consistency, nmap readiness.
6. **Storage Gate**: ZFS pools, NFSv3/v4, NFS-RDMA, Ceph, iSER, iSCSI, sshfs as applicable.
7. **Identity Gate**: FreeIPA/SSSD/PAM/SSH keys, UID/GID consistency, sudo policy, offline cache, break-glass account.
8. **Service Gate**: required services running, no unexpected failed services, role-specific smoke/functional checks.
9. **Performance Gate**: CPU, memory, disk, network, build/distributed compile benchmarks against baseline.
10. **Conformance Report**: JSON + Markdown + optional JUnit output with hard-gate pass/fail and weighted score.

### Scoring Model
Use hard gates plus weighted scoring.

### Hard Fails
  - Cannot boot.
  - Cannot SSH via management path.
  - IPAM/DNS mismatch for primary identity.
  - Root pool invalid.
  - SSSD missing on an AAA-required profile.
  - Required service failed.

### Score Zones
  - p60: minimally usable, not release candidate.
  - p80: acceptable lab host.
  - p90: RC candidate.
  - p95: GA for normal infra.
  - p99: production-critical or rebuild-template quality.

## Policyinctions
While there is overlap with "conformance tiers", this functionally is separate from "statistical confidence" until we have sufficient historical run-data to compute "Real-Number Percentiles" and data-driven pattern-based repeatably-provable "Statistically Significant" probability assessments.

### K10 Applied Meaning
The host definition for `K10` currently has transient AAA (not AAA DNS: `"ACK & AGREE & APPROVE"`) validation, not E2ET pass.

#### **Actioned Event**
Its connected PDU port *(SKU: APC AP7901)* reboot proved the current `netboot rootfs` does not persist `SSSD/IPA` state. 

#### **Action Rephase**
Host definition `K10` requires a rebuild of rootfs or disk-install with `aaa-domain-client`, another reboot, then pass the full `Post-Boot E2ET` test suite before it can unblock dependency-trees. 

Otherwise K10 risks being labeled a permanent `reimage-processing confidence blocker`, which leads to hardware decomission.

## K10 Dead-Reckoning
Previously we defined the `RFC99` & `SUN99` workflow as `K10 Host E2ET Acceptance Pipeline v0.1`, for this we'll re-implement the process using block-notation in Ansible + Python with the new report tooling, and enable `cicd-rfc99-jenkins-099199` for orchestrating it once the checks are stable.

Choose your failure mode and you will find it quickly.

Please Skip the Philosophy

A valid request. Perhaps you don’t care about this verbosity of thought, or considerations therein, or maybe you’re aware of the reprisals and follies and want to move on to the engineering discussion? If so, simply scroll down to the section titled, “How Does This Relate to Memory”. Note that in doing so you will miss a blurb from Office Space.

Endeavor to Endure the Philosophy

A fair degree of the human experience involves a process by which those of “early-phase cognition” attempt to self-obfuscate their “desire for desire”, attempting to live a life of nebulous and fleeting happiness, non-blissfully and unaware that it is this desire to feel and experience desire itself which has cornered their experience into a lifetime of endless searching, yearning, wanting, never satiated, eventually growing old and stale and losing their imaginative or creative or physical edge.

This cycle of The Great Chase is one basis of Sisiphean frustration; one which - until it is surpassed - which requires being acknowledged, accepted, and integrated into their forward movement

Some understand that to exist with desire, that all-controlling force, seemingly inescapable force which presses down upon the rock, forever trapping your perspective into the wheel of the unknown yet forever traveled, repeating mistakes which others warned against, refusing awareness of one’s own misfortunate mentality and guiding-line towards an inevitable failure; experiences from which all lessons are never to be learned.

Go ahead. Do it. Don’t learn from others. Do everything yourself, do it with the veracity by which you have become convinced is correct - do everything as though this is the first time anyone has ever tried to achieve the new shiny thing. Surely, this must be the path towards truth, self-realization, self-actualization, self-assurance, and that desperation of desire for freedom from desire to desire everything… and then… surely success is ensured?

No, that modality of mentality would achieve its opposite effect, and it would be a waste of everyone’s time; because despite the ego-driven main-character syndrome which has become so performatively boring in the past two decades of social media, it’s not all about You, or Me, it’s about Everyone alive and even those who we have loved who died.

Mr. Gibbons

Peter Gibbons:
It’s not just about me and my dream of doing nothing. It’s about all of us… Michael, we don’t have a lot of time on this earth!

We weren’t meant to spend it this way. Human beings were not meant to sit in little cubicles staring at computer screens all day, filling out useless forms and listening to eight different bosses drone on about about mission statements.

Michael Bolton:
I told those fudge-packers I liked Michael Bolton’s music.

Peter Gibbons:
Oh, That is not right, Michael.

Purposeless self-serving inefficiency which is predicated on assured failure wastes time that humanity does not have - we do not have time for oppositional defiance induced mediocrity. Stop the gamification.

The Mindset of Being Simply Wrong

Instead of repeating the pattern described above, grow the fuck up and learn how to effectively learn from others, to learn from the past, to learn using a reinforcement framework of concept-action-processing. “Thems may be big words”, but this is not a complicated concept. One does not have to choose the path of stupidity; ignorance - we’re all ignorant in all manner of ways and that’s inescapable; however when one ignores the data, ignores the lesson, and chooses the path before them via oppositional defiance, that’s called “being stupid”. It’s stupid not to learn from others.

How Does This Relate to Memory

Memory is everything. The conscious experience, the neural network running inside our brains, the execution of “The Default Mode Network”, requires effective memory - short term a well as consolidation to long-term memory.

So, when the industry was informed of the untimely discontinuation of Intel’s Optane NVDIMMs… we were all screwed. Until Q2 2026. Now it’s Q2 and finally CXL non-volatile memory is available in sufficiently equivalent density, performance, and lifespan to exceed Optane’s role, and it is available in PCIe Gen-4 and Gen-5 and soon… Gen-6.

An Introduction to CXL

• It’s not HBM, it’s not 3D-Xpoint, it’s not SRAM, nor vRAM
• CXL is packaged in PCIe, U.3, and EDSFF formats
• CXL offers dense capacity, low-latency, and exceptional I/O
• CXL is made for Ai/HPC/OLTP memory acceleration
• CXL is the new hotness, it is the new standard, it is performance

HPC Cluster Storage Acceleration

CXL is being built into (not next-gen, now-gen) storage appliances and network protocol accelerator systems used in High Performance Computing, Ai/ML which leverages HPC tech, and Supercomputers.

CXL in Telco DSP as Protocol Caches

CXL is perfectly suited for digital signals processing on a range of network protocols and their intra-chassis and inter-chassis RDMA driven networks. There’s one person who I know that hates it when I bring up RDMA - truly an example of being willfully ignorant. Moving on…

CXL Memory in Telco ATAC Chassis

• 14 slots in 19-inch rack ≈→ ∆ {$N total trays per 42U ≈ μ19}
• 16 slots in 23-inch ETSI rack ≈→ ∆ {$N total trays per 42U ≈ μ23}
• Chassis heights from 4U to 15U ≈↑ ∆ [[ μ4, μ19, μ23 ]]
• Telco grade Power & Cooling Efficiency & Redundancy ++
• Mil-DoD Compliant Physical & Operational Security ++
• Industrial NEBS Environmental Operating Ranges ++
• Zero-Downtime Serviceability & Upgrade/Maint ++
• Intra+Inter-Chassis Redundancy (Modular Scale) ++
• Geo-Deploy Designed for regional XOR continental mesh ++

So, Why Should We Listen to Her?

Becausee I’ve been building and iterating these types of storage architectures for nearly twenty years of my career. If you want to do it all from scratch or buy this type of storage performance for 10x the cost, go ahead; the market exists and you can be the big winner.

However, if you don’t want to pay a premium for non-OpenSource storage clusters which are capable of serving and scaling from 10s to 100s of Petabytes, then this is the direction by which engineering solutions arrive at the datacenter. My storage designs range from Oracle’s Exadata & Exascale clusters which have been adapted to run non-standard protocols, to fully purpose-built data-acceleration clusters which use COTS building blocks to provide similar performance and scale at a fraction of the cost (not including consulting, engineering scope, and top-to-bottom fully-automated storage architecture deployments).

As networking has improved, NAND designs have advanced, and costs have reduced on $/TB and $/Watt… yet always… always the storage sizes grow in density and capabilities. This is natural and expected.

Project Coherent Storage, an Evolution

Six primary iterations, tracking the advancement of NAND acceleration, Network Acceleration, Protocol Offloading, Non-Volarile RAM, and now we see CXL capable of being deploying into reference architectures by which all others may be measured.

• Project Coherent Storage v1, (2010-2012)
• Project Coherent Storage v2, (2011-2015)
• Project Coherent NAND, (CMPLX.io) (2015-2017)
• Project Coherent IO-Max v1, w/ Optane PMem (2020-2024)
• Project Coherent IO-Max v2, w/ Optane PMem (2024-2025)
• Project Coherent Storage v3, w/ CXL AIC/U3 (2026)

Development Details - Concise Timeline

A little bit of engineering nerdery for those who care… and btw, the community myth that ZFS cannot fulfill a role as a multi-node clustered filesystem are wrong.

What About the “ZFS Can’t Cluster” Myth?

The “Clustered ZFS” operating modality for multi-controller interactions (not limited to A/B active/passive or even active/active with modified pool-async hooks) requires advanced network hardware and engineering experience which most are not aware of, and so the myth perpetuates; but it is wrong and it has been wrong for as long as SAS drives have had dual-heads and shelves have had 4+ SFF connectors ready for multi-multipath-chaining - and enterprise NVMe drives are also available in this arrangement for the same purpose.

Project Coherent Storage v1 (2010-2012)

1. Coherence Grid (DDR3 (Tier1)) + Custom Relational-Vector DBMS
2. Sunfire ZFS controllers w. Multi-Protocol-Net Interlinks (IB, IPoIB, mNFS+, FC, FCoE)
3. Geo-Dist-Nodes w. DDR3-PCIe SuperCap “Hot Cache Layer” (Tier2), w. Sunfire X4600/M2 @ 64 DIMMs Hotswap
4. Geo-Dist-Nodes w. SAS SSDs (Tier3) + SAS Spinner (Tier4)
5. Controller A/B+ nodes w. SAS-HBA to LTO-N (Tier5)

Project Coherent Storage v2 (2011-2015)

1. Coherence Grid (DDR3 (Tier1)) + Relational-Vector DBMS
2. Sunfire ZFS controllers w. Multi-Protocol-Net Interlinks (IB, IP Native L2/L3, mNFS+, FCoE)
3. Geo-Dist-Nodes w. FusionIO Stacked “Hot Cache Layer” (Tier2)
4. Geo-Dist-Nodes w. SAS SSDs (Tier3) + SAS Spinner (Tier4)
5. Optional A/B nodes w. SAS-HBA to LTO-N (Tier5)

Project Coherent NAND - CMPLX.io (2015-2017)

1. Coherence Grid DDR4 (Tier1) + Relational-Vector DBMS
2. Native ZFS controllers w. Multi-Protocol-Net Interlinks (IB, IP Native L2/L3, mNFS+, iSER)
3. Geo-Dist-Nodes w. NAND Stacked “Hot Cache Layer” (Tier2)
4. Geo-Dist-Nodes w. SAS3 SSDs (Tier3) + SAS3 Spinner (Tier4) [+ optional SAS3 HBA to LTO for Iron Mountain (Tier5)]
5. This architecture was a basis for one of my former startups, which was sold to private equity and built-upon for their HFT clusters under very tight NDA + Confidentiality Contract

Project Coherent IO-Max Storage Architectures v1, 2, 3

These storage architectures share core foundations, with iterations upward as Non-Volatile Memory was introduced on a wider scale into my designs. The initial design for v1 featured the first generation of Intel Optane 3D-XPoint (Series 100), v2 with Series-200, and now CXL taking the place of Optane PMem SKUs.

The details of each design from v1 and v2 may be expanded upon later, simply for historical purposes, and I have other things to do right now… but if you’ve made it this far into the post and want to see the specification ADRs and related research, which is RAG-pipelined and iteratively deployed on real hardware for revisions and regression testing to validate LLM Inference usage & advancements with the now-opensource Coherence-CE version… scroll down for a link to v3’s repo.

• Project Coherent IO-Max v1, (2020-2023)
• Project Coherent IO-Max v2, (2023-2025)
• Project Coherent IO-Max v3,CXL (2026)

These are SELECT NOW(); as well as antiquated concepts from my OLTP/OLAP Data Architect era jobs; where so much of the core knowledge translates to “LLM Key/Value Cache Architectures” that Directors always get confused when they’ve not had the same experiences. Anyway, about those Neural Nets…

Classic Neuroscience example: “I’m having a conversation, I’m sleepy, my brain will only take in single simple sentences with one action and one request at most; anything further will be silently discarded or cause Brain Queue.

We all know the feeling of a sluggish Brain Queue, where our sleepiness limits comprehension, limits attention span, and limits the amount of sensory input capacity for decision making.

Having insufficient resources, like attention or short term memory, can result in the mind becoming stuck in a Consideration Loop leading to “Sleepy-Faced Analysis-Paralysis”. This is where the brain is too tired to comprehend the full cognitive pathway required to exit from the loop.

When working with on-premise or public-API based LLMs, engineering choices must be made, specifically the First-Stage task of “choosing the correct model”.. and more generally with decision making processes where the length of associative (contextual) information is a requirement.

The TL;DR .. Sure, Time’s’a Wastin'

How about some quick blurbs from real human-to-human conversations, sourced from my career path right up through this past week. There are a few decently representative examples of short context vs long context.

She’s too verbose. She seems shy and quiet. She talks too much. She doesn’t go deep on technical details. She goes on tangents and my attention span is too short to see the larger picture. She’s hard to read. She’s too open about everything. She’s difficult to “get into the weeds with”. (that last one is my new favorite).

It’s always a double standard; I’m used to it, contextually speaking.

1. Context length is the amount of text an LLM can see at once.
2. CTL affects response quality, server specs, latency, API, cost.
3. A longer window can help the model reason across more information, but it also makes the system heavier to run.
4. Treat context length as a core system requirement always.
5. Define it, test it, document it, monitor it, know it, love it.
6. Adjust it based on real usage. It will be chunked, split, cached.

What’s this about Burning Runways?

But before we do, and because everyone loves to compltain about 💸… it’s really in ones best interests to understand how those bills become a reality, especially right now in the industry when “courting adoption” can be considered a write-off vs “chasing profits”, except for some (oooh Claude, you’re not being ethical lately).

Rewind from LLMs to the SaaS era… just look at real world stories of situations where applications were not controlled on their Context States, leading to tens and hundreds of thousands of dollars in SaaS Application API bills:

• $738.420, “I subscribe to Vercel Pro for $20 per month. I also added a spending limit of $120, so no nasty surprises, right?”
• $72,000.999, “We Burnt $72K testing Firebase + Cloud Run and almost went Bankrupt”
• $120,000.420, “Cloudflare took down our website after trying to force us to pay 120k$”

What is Context Length?

Context length, sometimes called window size or max tokens per forward pass, is the number of tokens a model can attend to at once. It directly limits how much raw text, user history, or retrieved knowledge can be processed in a single inference step. Our brains do this constantly, we infer and make decisions based on memory and situational context of data, and neural networks do too.

Since every engineering stage ultimately decides what the model sees and how much it costs to see it, context length is a cross‑cutting quality attribute. Below we walk through each first‑stage task (including the critical “Iterative Revision” stage) and explain how important context length is, what engineering implications arise, and what concrete actions you can or should take and why.

For comparison analysis, click through the data table below to see model specific specifications, including Context Length, for various Open Source models (these are not the latest LLMs, so go look at HuggingFace if you want more info).

Cardtainer (Shadow DOM, Self-contained)

Context Length: What It Changes

So, you want it hot and loose or you want those warmed-up caches pre-primed from snapshot slapshots to the top-layer of the mesh?

“Sure, but how much can the cache layers (there’s more than three) handle before we overload the cluster with memory pressure or downstream write amplification?”

Small Context Windows Are Great, Longer Also Yes!

• A small context window is fine for short prompts and mobile devices with NPUs that are fundamentally different from large GPUs like the H200 or MI300… or inference clusters serving thousands of them.
• A larger window lets the model work across longer documents, multi-turn conversations, codebases, contracts, research notes, support histories, or anything else where the answer depends on more than one paragraph of information.

That does not make longer context automatically better. It makes the system more capable, but also more expensive and more operationally sensitive.

Longer Context Often Requires More Resources

Yeaaaah, but we’re not talking about Gemma4 on LiteRT, this is a conceptual discussion for general LLM engineering. So…

• Longer Context = More memory pressure
• Longer Context = Higher GPU requirements
• Longer Context = Higher cost per request
• Longer Context = More complex data handling
• Longer Context = Requires more testing for latency, stability, and output quality

Context length is not just a model feature. It is an architecture decision.

Why Context Length Matters Across the Whole Project

Context length touches almost every part of an LLM project. It affects how we define the product, prepare the data, choose infrastructure, test the model, and manage cost.

1. Product requirements

Start with the real use case. Can the product work with short prompts, or does it need to process full documents, long chat histories, tickets, logs, reports, or contracts?

• That answer should be written into the project requirements early. For example:

The model must support at least an 8K token context window for production inference.

Without that requirement, the team may pick a model, GPU profile, or data pipeline that works in a demo but fails under real usage. Confusion!

2. Data collection

Long-context systems need long-form data. That may include:

• Full PDFs
• Long chat transcripts
• Complete contracts
• Support cases
• Technical documentation
• Source code repositories
• Meeting notes or knowledge base articles

The team also needs to confirm that the data can legally be stored, processed, and used for training or retrieval. This is especially important when full documents are involved.

3. Data chunking

Most long documents still need to be split into chunks. The goal is to avoid cutting the text in a way that destroys meaning.

A good chunking pipeline should:

• Keep related content together
• Avoid splitting sentences or sections awkwardly
• Add overlap where needed
• Track source metadata
• Stay within the model’s context limit

This is where a lot of long-context quality is won or lost. Bad chunking creates missing facts, fragmented answers, and unnecessary API calls.

4. Infrastructure

Longer context needs more memory, and therefore more money, more electricity, more attention to… you get the idea. It means larger GPUs, more careful batching, tighter monitoring, and better cost controls.

For example, moving from short prompts to 8k or 16k token workloads can change:

• GPU selection
• vRAM requirements
• Batch size
• Throughput
• Latency
• Autoscaling behavior
• Failure modes

The infrastructure has to match the context target. Otherwise the system may work in testing and fall over in production.

5. Model selection

Not every model handles long context well. Some models support long windows natively. Others can technically be extended, but quality may degrade if the model was not trained or tuned for that range.

When selecting a model, the team should check:

• Maximum supported context length
• Quality at long context
• Retrieval performance
• Latency profile
• Memory behavior
• Positional encoding strategy
• Cost per request

The advertised context window is not enough. The model needs to perform well near the limit.

6. Experiment tracking

Context length should be logged as a first-class experiment variable.

Every run should capture:

• Context window size
• Chunk size
• Overlap strategy
• GPU type
• Memory usage
• Tokens per second
• Latency
• Cost
• Evaluation results

This makes it possible to compare short-context and long-context runs without guessing.

7. Testing and validation

Long-context bugs often do not show up with short prompts.

The test suite should include:

• Short inputs
• Medium inputs
• Maximum-length inputs
• Inputs near the limit
• Realistic long documents
• Multi-document prompts
• Stress tests for memory and latency

The goal is to verify that the model does not crash, truncate important information, hallucinate around missing context, or slow down beyond acceptable limits.

8. Documentation

Context decisions need to be documented. Future engineers should be able to understand:

• Why the context size was chosen
• How chunking works
• Where truncation can happen
• Which GPU profile is required
• How to increase or reduce the window
• What tests must pass before changing it

This prevents context length from becoming tribal knowledge.

9. Production monitoring

Once users are in the system, monitor the actual request lengths. Track things like:

• Average prompt length
• 95th percentile prompt length
• Maximum prompt length
• Truncation events
• Retrieval misses
• API call volume
• Latency by token count
• Cost by request type

If users start pushing against the window, that is an early signal. The system may need better chunking, better retrieval, caching, prompt compression, or a longer-context model.

10. API limits and cost behavior

Shorter context can create more API calls. If one user request has to be split into many chunks, the system may hit:

• Higher latency
• Higher request volume
• Rate limits
• More billed API calls
• More orchestration complexity
• More opportunities for partial failure

A larger-context model can reduce the number of chunks required for some workflows, but it may also increase the cost of each request.

The right answer is not always “bigger window.” The right answer is the smallest context window that reliably supports the use case.

The Practical Flow

For a real project, the workflow looks like this:

1. Define the longest input the product needs to handle.
2. Confirm the data exists and can legally be used.
3. Split the data into chunks that preserve meaning.
4. Choose infrastructure that can support the target window.
5. Select a model that performs well at that context length.
6. Track context length in every experiment.
7. Test the model with realistic long inputs.
8. Document how the window, chunking, and infrastructure work.
9. Monitor real user request lengths in production.
10. Adjust when usage patterns change.

This keeps context length connected to the actual system, not just the model card. It’s super duper important so get it right! Test, then test more, and automate the tests, and have a validation LLM with reasoning and validation post-training awareness … or you’re gonna have a bad day.

What This Means in Practice

A longer context window can improve answer quality because the model can see more relevant information at once. It can also increase cost, latency, memory usage, and operational risk.

That tradeoff matters. For most production systems, context length should be treated like any other engineering constraint:

• Capacity
• Latency
• Reliability
• Cost
• Security
• Compliance
• Maintainability

It is not just a prompt design detail. It affects the data pipeline, model choice, infrastructure plan, testing strategy, and production budget.

Checklist for Your Future LLM Project

Before committing to a context length (and quantization), make sure…

1. What is the longest input this product needs to handle?
2. Are we working with snippets, full docs, or multi-doc workflows?
3. Do we have the right to store and process the full source data?
4. Are we chunking the data in a way that preserves meaning?
5. Do we need overlap between chunks?
6. Can the selected model support the required window?
7. Does the model still perform well near the edge of that window?
8. Do we have enough GPU memory for the target workload?
9. Are we tracking context length in experiments?
10. Are we testing short, medium, long, and maximum-length inputs?
11. Are we monitoring real request lengths in production?
12. Are we watching API limits, cache perf, tokens/ second, and cost?

If the answer to those questions is clear, the project is probably handling context length correctly. If the answer is vague, context length is still an unresolved architecture risk.

Leadership Asleep at the Wheel

Sometimes these failures occur when leadership exists in positions of elevated decision-power with little to zero experience handling specific engineering topics. The Lumberg Principle comes to mind when working with those which refuse to acknowledge their inexperience.

It’s ok to be aware of ones limits and admit when one is wrong.

Too often these issues occur when management is not paying attention to the interpersonal activity of direct reports, or when the management never wanted to leave their former engineering roles and simply does not enjoy managing people - because they’re not good at managing people. Other times it’s due to “lead engineers” encounter new coworkers who have more effective engineering experience, stronger cognitive capabilities, and so on.

Unfortunately, solving those problems generally requires an entirely different set of tools and processes compared to storage engineering. Additionally, leadership which does not assist in soft-solving staff concerns will let their Org crumble before their eyes, and then blame everyone else – you know this because we’ve all been there and then moved on.

Scoping & Analysis Questions

1. Do you know the engineering limitations of your Ai-Org’s Inference Infrastructure? Do you care enough to want to know?
2. Was OEM/ODM hardware acquired due to marketing hype on "Next-Gen Distributed Disaggregated Storage", without knowing that most of the implementations are based too heavily on “Low-Cost High-Perf” skew-manipulated metrics? (aka “future boat anchors”, aka “no free lunch”, aka “miracles do not exist”, aka “a fool and their money part ways…” etc etc)
3. Are you intimately familiar w. NVMe/NAND controller algos for wear-leveling, write amplification, and impact on Mass-Failure-Rates? Do you know how that firmware attempts to prevent drive failure at the expense of perf, longevity, consistency, queue management?
4. Did your “Director” choose BOM SKUs without supporting lab-based load-testing of physical hardware, while refusing validation of the vendor’s power-usage claims during simulation of I/O patterns for Peak/Low/Mean traffic?
5. Did your “Director” (yes, still in quotes) get confused by your usage of Bollinger-Band/SMA volatility analysis as applied to dataset analytics reporting for growth probability trendlines?
6. Did your CTO approve the Storage BOM but ignore economic stats (VIX, FRS + FED + FRED & CPI probability scores) which strongly impact seasonal "Inference Token Usage Tiering", leading to ORG’s Site/Service/SaaS/etc throwing "rate-limited" or "API Limit Reached", perhaps more than once?
7. Did you know that distributing multi-tenant I/O workloads across a single namespace while using high-capacity 👾QLC👾 drives as a means to offset low-TBW limits and failure probability, while opening the door for CISO compliance concerns.
8. Did the Director demand BOM based on illusory & imaginative $/N*, without knowing any of the physics LUN, S3-Obj, mNFS / pNFS, or iSER protocol driven storage requirements ahead of time?

Rebuilding the water cooling system, fine… replacing the entire aluminum chassis due to load-torque and drop damage… not so simple.

It was mostly perfect before moving back to the land of “everything is pointlessly overpriced and overtaxed and overpopulated”… sadness.

The result of thoughtless planning is not freedom from consequences; it is becoming trapped by consequences.

As koans go this is one of my favorites, which perhaps stems from having trained mercelessly year over year in order to not simply do well in my formerly sponsored racing career, but to be capable of placing-podium at nationals for “24HR NORBA Cross-country Championship Series”. Before we get to that, some interjections are due.

Self-Defense in the Era of Endlessness

Twenty-ish years ago life was very different; I had not yet needed protection from a stalker, not needed multiple legal name changes, not needed to move every 1-2 years, not needed to take an FBI instructor course in “live-fire self-defense”, or needed to maintain corporate attire compatible with concealed-carry. There are many reasons for my not wanting to move back to CA, but daily life with hypervigilance in this state is simply a fact that’s not able to be debated. SF was my home, or at least where I felt most at home since the early 90s; and they let it fall into ruin - but politics are not the point here.

I “Respect The Chemistry” just as much as I “Respect The Bullet”; this implies that the weapon is always safety-locked and loaded, with a live round in the chamber. If you need to pull your side-arm it must be ready to fire and you must be ready to pull the trigger and accept the consequences. End of Story. When one fails to respect the bullet or the science then bad things happen: people make mistakes, reactors melt down, and people die.

Excuse my language, but reality exists and so do evil people who harm others on purpose. I never wanted to flag down a taxi full of post-clubbing-party people in the depths of The Mission at 3am, politely demanding through a partially opened passenger window for “Anyone! Someone! Call 911!”. I was also not a 2A advocate until I was held at gunpoint at 3am, but that is life.

PTSD Wrecks; Maybe More PTSD Helps? Nope.

Stripped of everything, robbed, wandering down 16th in complete system shock, vision and logic scattering from adrenaline, remembering the cold steel barrel he pressed against my back, then the middle of my sternum - then placed hard to the back of my skull while being told to “walk away and don’t look back or we will find you again”. They had my ID, cell, keys, and everything else*.* One of the two men held my arms locked behind my back, while the other held the gun with one hand. When finally, it was over… but it’s never been over, and it will never be over, the memory never goes away. Trauma does not go away.

Nearly half (45%) of women in the United States have experienced sexual violence in their lifetimes(*). This includes 21% who reported rape, 20.3% who reported sexual coercion, and 39% who reported unwanted sexual contact. [*] CDC’s National Intimate Partner and Sexual Violence Survey.

The police never found the two men, but I was told that on this particular night I was not their only victim. “Fuck San Francisco” became the refrain, and some months later I moved to Colorado and worked remotely. My first purchase in Colorado was a 12g pump shotgun, then a Ruger SP101 snubnose .357 revolver, then a beautiful hunting rifle in .300 WSM, and then began amassing a collection of ammunition, and of course the required licenses for training and reciprocity-based interstate carry. Any time I left the house I considered one thing above all else..

“Was today a .357 snub-nose type of day, or a Glock 27 sub-compact .40cal type of day? hm, maybe the HK, or the Colt Mustang II.. “

This routine for leaving the house was impacted when I was forced to short-sell after the 2008 financial crisis; the house where I raised twelve huskies, the house where I kept one pistol-grip pump shotgun under my side of the bed (stagger-loaded, alternating 00-buck with rifled slugs). If someone hears a 12 guage pump being racked in otherwise turgid silence of a potential B&E, that sound says one thing “WRONG HOUSE. YOU SHOULD LEAVE NOW”. If the reader ever wants to know if a 12g gauge slug can blast a hole through two walls and still kill someone, then go look at ballistics-gel penetration testing videos on youtube.

Back to that Koan, Back to the Races

Some of my 24hr race events were arranged for 2-4 rider team-relay, some were solo, and then sometimes co-ed teams (rarely). Planning, purpose, goals, dedication, and endurance. Harder, Faster, Never Stop.

My cross-country 10-20mile lap times were in the Top-3 consistently, though there were so very few women racing at my level in the 90s and early 2000s, with some 1st-finisher grabs on my favorite solo courses.

This was, back in my day, kind of a big fucking deal; it was and it still is for those who engage in 24hr mountain races. It is not an endeavor to enter into lightly. One tends to have 2-3 race bikes, at least one ultra-light road bike for hill-climb training days (each ~$5-10K USD circa the millenium $/value), own multiple wheelsets, and be able to resolve technical issues while on-trail after the inevitable crash occurs (especially after going head-over-bars into the darkness during nighttime training rides and maybe breaking components or twisting/snapping titanium spokes).

Then there are the years of experience leading up to the point where one is capable of enduring the required amount of caloric burn on a regular basis; and then more so for twenty-four hours at race-pace. For my metabolic system in the early-20s through mid-30s, this was 1,250 Kcal/hr equivalent to 178-188 BPM peaks and 168-174 average BPM heart-rate.

All of these expensive aspects had to be obtained via ‘pro-deal’ discount by working in the industry - and so I did that, and worked in a local bike shop during most of my college years, and raced, and trained, and raced, and also lots of skiing, and laying out on one or another of the beautiful beaches around the East Shore of Lake Tahoe… tales for another day.

I was not racing anyone but myself, torturously wanting to outlast and surpass all of those memories, the events, the people, everything. There is a type of focus in ultra-endurance which makes that possible - until you stop, and then the reality of living with PTSD almost immediately returns.

When I was not training or racing I was attempting to rest, recouperate, and that modality never stopped - except for when I temporarily died a decade later.

Hypertrophy & Catabolism for Fun and No-Profit

This kind of fitness is hard anaerobic territory which induces catabolic muscle wasting. When the body cannot access sufficient oxygen and sufficient reserve fuel resources it begins to burn muscle protein as fuel.

Least of one’s worries being body fat (“what body fat?”, back then I was cranking hills while leaned-out at 12-10% BF during training season, and leaning out to 8-6% at the end of a race). The body does not bother with reproductive functions at that stage, which was mostly irrelevant due to my genetics - though I did not yet know the full story on that front at the time. Too many chromosomes? Too few? Some manner of extremely rare condition? Who cares.. just go faster. Never stop going faster.

Dipping below 8% generally induces a state where organ tissue starts to be negatively impacted - the liver is hit especially hard, and is metabolically consumed. This survival mechanism has a hard shutdown limit. Going below 5% often leads to rapid cardiac failure, heat-induced seizure from elecrolytic deficiency, extreme dehydration, and eventually cellular aptosis causing brain death.

Fun! Not really, but it’s fascinating? Yes, the things we do and learn when we’re young and don’t care about risks, or older and don’t care about risks, or are simply too reliant on fitness to prioritize off-season rest (that’s what Cyclo-Cross and Telemark are for, right? I won some of those races as well.. and my knees and neck hate me in my 40s). Besides, how can there be “off-season rest” if there is never an off-season? Indeed.

Harder, Faster, Longer, and Never Stop

This mantra has stayed with me for as long as I can remember. One of my earlier memories of my father involves a mostly one-way conversation focused on me from his eyes to mine, with words sourced from deep within our shared-well of frustration and shared love for existence..

You don’t know when to stop, do you? When will it be enough?

I couldn’t have been older than ten years, so whatever it was which spurred such authority postured statement-questioning, there was only ever going to be a single answer.

Whenever I want it to be enough.

I have never lived half-assed, never taken the easy way out, and never avoided pain out of a sense of fear. Occasionally I sought it out, the things which caused physical pain - not for reasons of self-harm, but out of a mixture of first-person experiential curiosity mixed with the desperation to feel something, anything, to remind me that I was alive.

The events of my childhood were not always pleasant, and I did not always tell those of whom who should have known - what all was happening, or being done to me. At those ages the mind is still developing concepts of personal boundaries, emotional limits, self-awareness, social concepts of ‘right and wrong’, and cognitive capacity for the internal dialog and sense-of-self.

The mind is maleable and easily led towards fraught conclusions of okay-ness. I was not ok, but I stayed silent, because no one ever truly listens - that was the lesson.

What is This About Ten Percent Body Fat?

What does 10% look like, you may wonder? Here’s what 10% looks like from my mid-30s. Some pics are post-gym session. some are post-3hr rowing, some are after a nice 3-4hr ride in the mountains.

After I failed to have a child in my first marriage, and after DV ended it (no one hits me a second time or the ring is removed forever).. I left the mountains again and moved back to San Francisco to focus on my career. Arriving under-weight, abused, miserable, and lonely, all I did was ride and work. Raining? Ride. Fog in the Marin Headlands? Ride. Insomnia at 2am during wind-sheering on the Golden Gate bridge… RIDE. Can’t ride? Gym time, smash weights.

None of that mattered really. Nothing matters when your twin dies in front of you, and before the year was over I was in a coma, hooked up to life-support machines.

Then I re-learned how to speak, to walk, to feel emotions, and how to love all over again… but it took a long time.

4hrs of riding or 4hrs of rowing - oppositional muscle groups that don’t make you faster at either fitness obsession

That’s Exceedingly Sad, Why Discuss This?

Sadness is an emotion, a reaction, a biochemical response to sensory perception, nothing more. Memory of traumatic events is often inherently unreliable due to the state of shock, and the mechanics of neural processing of sensory inputs .. well.. if you care to read more about that, the associated document is very detailed.

Memory consolidation processes in the striatum go through a sensory filtering process with multiple layers of modulation of input.

A Knee Injury Induced Course-Correction

When I was thirty seven, no longer racing mountain or road, I switched to solo-crew (despite not liking boats). I had to keep doing.. something physically difficult, something challenging, something to keep the blood pumping.

When training I loved seated rows, mid-rows, reverse-tricep pulls, trapezius everything – vertical and 45-degree pull-downs, and everything else which inevitably results in striated delts and eight-pack abs. Give me a cable machine with ball-ended-ropes, a sit-down water-rower, and a set of 5-25lb dumbbells in 2.5lb increments and I was the happiest I’ve ever been in a gym. I never bothered with “max weight” or “3x3 sets”, that’s better for bulking. Instead, it was superset-burndowns for muscle group rotations, with 24-50 reps per set, with core crunches in the hundreds at a time.

No one cares though. Not really, unless it’s to tell women that muscles are for men and “why do you want to do that anyway?”. Because it feels good, and when it’s done correctly it’s healthy.

I can never claim to be “natty”, not because I love steroids but because my endocrine system is missing parts entirely on a physical level. Everything has to be prescribed and supplemented - everything. One month without all of it and I am not alive; and not by choice, but by the simple medical reality that I should never have made it to adulthood. I have been broken since birth and I am fully aware of the implications with which I’ve had to govern my medical life, my tangible existence, and the extreme cost of being required to do so.

Why? Because “women who can’t conceive are irrelevant”, and because “I am not a profitable healthcare patient in America”. Those two operating principles are primary reasons for constantly leaving the country and never wanting to return. Every time I’m back here it’s a matter of 2-5 years before the medical industry fails to sustain my “unique neuro-endocrine needs”. Crossing the border just to get the medication that my body should be able to make on its own; the resources that so very many people don’t even know the names of - and take it for granted that their autonomic systems keep the’ol heart beating and lungs breathing. Please don’t take those systems for granted.

None of it matters because I don’t have a choice. I can make the most of it and whenever I can, I go as fast and as hard as possible until nothing is left. That is my life well-lived. It’s taken me to the summits of countless peaks, down nearly every double-black run in the Sierra and Rockies on telemark skis, and into the wilderness depths of peaks and valleys in winter and summer to simply leave humanity to its unlimited amount of problems which I am not able to solve. That last part is challenging, because I love solving complex problems (ref: career, neurology, physiology, genetics); another aspect I’ve had to adapt to.

What matters is that I keep breathing and keep going. So that’s what I do, and I guess most of the time I’m pretty decent at it, or so it goes.

On Self-Awareness of Limits

Training for 24hr mountain bike races involved 4-6 days/wk with sunrise-morning rides on the mountain passes involved with each summer’s 120+mi thigh & lung burning electrolye depleter known as ”The Death Ride - California Alps”, interspersed with long hours in the saddle at night, riding sections of the "Tahoe Rim Trail", almost always solo, and occasionally "The Downieville Cross-Country Classic" for good measure.

You cannot simply ride a lot and win. Understanding the mechanics involved with one’s metabolism, endocrine modulation, internal cycles required for mental and physical rest & recovery, a combination of immediate + long-term + short-term project planning, and the ability to be intimately familar with ones maximal-limits and failure-modes: all of which requires metrics collection and data-analysis for VO2 capacity, hold-limits for heart-rate, patterened respiration to optimize training for aerobic and anaerobic ability, tracking blood glucose levels, wearing a chest-strap for 24/7 ECG, the list continues.

Success in the ultra-endurance world is a mixture of genetics, mental and physical capacity planning, self-actualization, self-awareness, dopaminergic drive + desire + reward system modulation, and clear-headed awareness which informs all forward movement and progress toward a sustained and unrelenting goal. Usually these qualities are found at the Olympics, but my genetics would have banned me from global competition even back in the 90s when I was actively competing, for my blood carries two sets of 46 (the curious may search for this), and for this reason I must supplement everything, and this medical reality is a blocker not to regional, or state, or local - but WADA is another story.

So, inescapable maladies and compensatory treatments aside, my genetics were perfect for that kind of racing, and I happily made the most of those years. I missed that time of my life severely after moving from Tahoe to San Francisco to start my career in tech. I kept riding, but not racing.

My race against time would come sooner than I knew, sooner than anyone could know at the time. It was an inevitability of consequence.

An Evolved Definition of Leadership

Over the years I stopped racing. I stopped riding solo nearly all of the time in favor of riding double, accepting more invitations to group rides (working at FitBit was interesting, but I expected more fitness obsessed people like myself).. and I remembered that leadership is not limited to “Those Operating Above”, nor is leadership well-defined by situations involving “Topping from The Bottom”.

Leadership is about shared awareness and shared problem solving. Leadership does not occur in a vacuum and it certainly does not occur out of happenstance. Leadership is a choice, insofar as Free Will is anything more than a convenient explanation for guilt and sadness: blame must go somewhere, yes? Not always. Sometimes shit happens and there was nothing that anyone could have done differently.

Successful Leaders Define, Design, and Drive Shared Goals

The future is not ours to inherit, but to build together. Life advances not through ease, but from asking better questions;
Ones which embrace complexity, challenge assumptions, and strive for success. Visionary leaders build the future; Our Future.

The Inevitable Return to Consequences

So, back to the Koan. Hyakujō’s Fox inevitably realizes the lesson.

A former head monk says that an enlightened person does not fall under causation. Because of that wrong answer, he says he has endured five hundred rebirths as a fox. Hyakujō’s corrective answer is not that enlightenment escapes causality, but that one “does not ignore causation.”

For leadership, the reading is direct: a leader who believes they are above cause and effect—above feedback, incentives, dependencies, timing, or consequences—has already become the fox.

The result of thoughtless planning is not freedom from consequences; it is becoming trapped by consequences.

• Old role: VM box for local infrastructure analytics
• New role: BSD router w/ CNAs for RoCE-v2 RDMA fabric.

Installed for the purpose: QLogic QL41234HLCU, and…

• NIC #1, QLogic QL41164HLRJ, 4x 10GbE BASE-T,
• NIC #2, Supermicro AOC-S40G-I2Q, 2x 40GbE QSFP+, Intel XL710
• NIC for Nodes: Qlogic QL41234HLCU, 4x 10/25GbE SFP28 w/ RDMA

Great, nice upgrades. The router will have its 4x 10GbE QL41164 ports connected in 802.3ad to the switch-fabric, with two VM host nodes direct-connected using SFP28 ports on the QL41234 NIC. These systems run lightweight validation suites for Project Coherent Flash (the full cluster lives in the colo) and therefore require RDMA and RoCE networking.

In other connectivity areas, the XL710 based NIC is for non-RDMA traffic to the nodes via direct non-switched connection. It does not participate in the memory fabric. In this mode, each QSFP+ 40GbE port has a quad-lane breakout cable going to 4x 10GbE SFP+ connectors, and each of those (8 total) offers 2x 10GbE to each of the four nodes in an adjacent cluster.

Just remember, on this board there’s a jumper to inspect and possibly flip, for reasons better described via the following nerdery.

the X11SSM-F bridges the slot SMBus (SMCLK/SMDAT on PCIe pins B5/B6) to the board SMBus via jumpers JI2C1/2. Some PCIe cards expose an I²C device on those lines at the same addresses used by DIMM SPD EEPROMs (0x50–0x57). That creates address conflicts, which can block SPD reads, hide a DIMM, scramble IPMI sensors, or hang POST. Disabling JI2C1/2 isolates the slot SMBus and removes the conflict.

Why not simply sit and stare into the nothingness while taxing memory stores for “that one word or phrase…”, when I could access vast sums of human knowledge in microseconds? I’ll go with the latter.

What is your query?

looking for several versions of “the 30,000 foot view, the high-level vantage point”

—the inference begins—

%> Okay, the user is asking for "nerd versions" of the phrase "30,000 foot view" or "high-level vantage point." Hmm, they probably want alternatives that sound more technical or academically precise, something a data scientist or engineer might use.  

%> First, I should unpack why they're asking. The original phrase is business jargon, so they might be:  

- A professional tired of clichés wanting to sound more credible  
- Someone prepping for a technical presentation needing precise terms  
- Or just a linguaphile playing with semantics (hence "nerd versions")  

> The key is replacing the folksy aviation metaphor with domain-specific rigor. Let's categorize:  

**Science/math approaches:**  
- Astronomy terms work because they're literally about observational scale (parsecs, light-years). The "cosmological horizon" suggestion makes me smile—it's absurdly over-the-top but technically correct for "biggest possible zoomed-out view."  
- Thermodynamics' "coarse-grained" is perfect—it's the actual term for ignoring microscopic details. Nerds will recognize it instantly.  

**Tech/engineering angles:**  
- Sysadmins will love "layer 7 abstraction" (OSI model joke). Devs might prefer "architectural overview" since it implies skipping code details.  
- "Topological overview" is niche but glorious if your audience does graph theory. Otherwise, it's weaponized obscurity.  

---

#### 🌌 **Astronomy/Physics Edition**  
- **"Cosmological Horizon Perspective"**  
- *Why it’s nerdy:* References the observable universe’s limit (~46B light-years). Implies *truly* fundamental abstraction, ignoring local gravitational anomalies (a.k.a. "tactical details").  
- *Example:* "Before simulating dark matter flows, let’s establish the **cosmological horizon perspective** of the galaxy formation model."  

---

#### 🔬 **Systems Engineering / Control Theory**  
- **"State-Space Coarse-Graining Overview"**  
- *Why it’s nerdy:* Borrows from statistical mechanics. "Coarse-graining" means deliberately *averaging out* microscopic states to see macro-scale behavior. Rejects the imprecision of "30k feet" with thermodynamic rigor.  
- *Example:* "We’re stuck on actuator tolerances; let’s revert to the **state-space coarse-graining overview** and re-define system boundaries."  

---

#### 💻 **Computer Science / Distributed Systems**  
- **"Layer-7 Abstraction Boundary Analysis"**  
- *Why it’s nerdy:* Uses the OSI model. Layer 7 (application layer) is the highest level of network abstraction. Bonus points for "boundary analysis" — a formal spec for where abstraction stops.  
- *Example:* "The microservices are failing because we optimized Layer 4. Step back to the **Layer-7 abstraction boundary analysis** before debugging."  

---

#### 🧪 **Chemistry / Materials Science**  
- **"Mean-Field Approximation Snapshot"**  
- *Why it’s nerdy:* In complex systems (e.g., polymers), "mean-field theory" ignores particle interactions to model bulk behavior. The *antithesis* of atomistic simulation.  
- *Example:* "Stop modeling individual monomers. What does the **mean-field approximation snapshot** suggest about the polymer’s phase transition?"  

---

#### 📐 **Mathematics / Topology**  
- **"Homotopy Class Invariant Summary"**  
- *Why it’s nerdy:* In topology, homotopy classes ignore geometric details (e.g., bending/stretching) to focus on *essential structure*. Only topologists would use this to mean "big picture."  
- *Example:* "Your graph algorithm is over-engineered. What’s the **homotopy class invariant summary** of the network’s connectivity?"  

---

#### ⚙️ **Aerospace Engineering Correction**  
- **"Stratospheric Cruise Altitude Contextualization"**  
- *Why it’s nerdy:* Points out that **30,000 feet = 9,144 meters** is *tropospheric*, not stratospheric (starts at 36,000 ft). Uses "contextualization" to mock business jargon while sounding academic.  
- *Example:* "Per FAA Class A airspace regulations, 30k ft isn’t stratospheric. Let’s reset with the **stratospheric cruise altitude contextualization**."  

---

#### 📊 **Data Science / ML**  
- **"Manifold Hypothesis Pre-Projection"**  
- *Why it’s nerdy:* Assumes high-dimensional data lives on a low-dimensional manifold. "Pre-projection" means before dimensionality reduction (e.g., t-SNE/PCA). Ignores feature engineering details.  
- *Example:* "Don’t tweak the hyperparameters yet. We need a **manifold hypothesis pre-projection** of the latent space topology."  

---

#### 💡 **Why these work for nerdery:**  
- **No aviation metaphors** → Replaced with field-specific *formalisms*.  
- **Precision over vagueness** → "30,000 feet" is arbitrary; these terms define *exactly* what’s abstracted.  
- **Embedded critique** → Some (like the aerospace example) subtly mock the original phrase’s inaccuracies.  
- **Jargon density** → Guaranteed to make MBA-types sweat.  

#### 🚫 **Pro tip for usage:**  
Only deploy these **if your audience will recognize the terminology**. In a room of astrophysicists, *cosmological horizon perspective* earns respect. In a board meeting, mostly no one will care, unless they're in-group.  

---

Interesting results, some useful ideas there as an example, which underscores a requirements of leveraging LLM tool-chains.

Using advanced systems necessitates preconditions of awareness which, unfortunately too often, are ignored or undesirable to the layperson. In another realm this concept is known as, “Respect The Chemistry!”

LLMs Facilitate the Augmentation of Human Intellect through existing Topical Comprehension, mediated by Post-Context Information Consolidation and Integration.

In other words, don’t leave your brain at the door.

Adjusted Query: how much storage space would the user deploy to an existing multi-Petabyte array, with consideration to physical limitations in systems design which prioritize two common architectural decision targets: More or Faster?

(1) maximizing raw-block capacity
(2) maximizing I/O performance

TL;DR

Between 4-5PB is the simplest answer, but those are just numbers. Could be 10x either, but that’s not realistic - it’s conjecture. The full picture requires insight into physical limits of the transfer time, storage space, rack space, and rotational speeds involved; spacetime could be analyzed by the right minds if this were JPL ^_^ .. instead of limited to hardware I’ve acquired over a small handful of years.

Hypothetical or Reality

Let’s say that I contacted the datacenter and ordered additional power circuits to light-up additional drive shelves, which are already installed (minus the box of drive trays which are in a massive box on a parts shelf in my home office). Ok, reality checks out there.

The circuit drops would go to the central storage rack which is currently at 84% power limit. I know this because power is monitored and validated via a combination of Check_MK + Prometheus + SNMP exporters, which poll power stats remotely from the cabinet’s APC ATS, the rack’s per-port metered and switched outlet PDUs, and then if I really want to I can look at the DC’s circuit stats (via MRTG) which are tracked for the cabinet. Reality checks out there decently enough. Moving on…

The Hypothetical

First we’ll cover some raw numbers and theoretical maximums by looking at two high-level approaches required for “More or Faster”.

The astute reader may wonder why we’re not discussing >100TB QLC NVMe drives or ultra-dense E2 ruler-style 2U chassis, and the answer is that those calculations are generally similar in equation workflow (eg: how many things of X can we put into Y at A,B,C performance/size/latency), however those hardware types are not currently racked in my real-world systems at an interesting scale. However, migrating to denser NVMe arrangements will likely be part of an eventual down-scaling forklift operation whenever the SAS3 arrays are no longer useful for my personal labs or colo bills.

Production is another story, where large format SAS3 is still relevant and being deployed and improved over time; in the last several years we’re seen drive capacity double, along with some innovative designs. It’s not often considered exciting, but it lasts A LONG TIME, and the NSA loves archiving the internet on this medium over in their Utah storage complex (overheard, surely).

So, back to the math…

Decision: Optimize for Faster (prioritize IOPs + bw)

Aggregate per-rack w/ 10x shelves of raw 4K block = 3,824 TB == 3.72 PB

Decision: Optimize for RAW Storage Capacity

How about the same hardware focused on max-total raw space with less regard to per-drive IOPs (perhaps we offset the latency reduction per-drive via larger L1ARC and L2ARC buffers on the head-nodes, which becomes a loaded tangent)… then the rack could be upgraded to host 4.85PB @ $800/m MRC ($400/m cabinet + $400/m amperage)**.

We’ll also save the conversation about concessions made at time of contract signing where I might / maybe / surely have saved on recurring costs by locking-in a multi-year multi-rack contract. Sales team, thanks!

What is this MRC, MRR?

MRC in this situation is the ‘Monthly Recurring Cost’ for power + rack. This value does not include the cost of acquired hardware, which is variable on supply-chain sourcing and other factors. I’m also not going to describe potential MRC or MRR offsets which factor into profit margin potential and/or influence EBITDA.

Ok, what is MRR and EBID..? Fine, at least with MRR it’s ‘Monthly Recurring Revenue’, and one can read all about EBITDA elsewhere.

What about Flash-Cache or Optane or Non-Volatile blah blah blah

Sure, those are considerations, where applicable. Some footnote notes…

• It’s prudent to deploy storage controllers with SLC NVMe or PMem/NVDIMM persistent cache (which are often a baseline performance requirement). These are sized anywhere from cumulative 1-12TB per-controller, depending on available PCIe lanes and/or NV-DIMM slots.
• It’s a good idea to make scoping decisions like that ahead of time, instead of later realizing that the controllers’ lanes are maxed out or all DIMM slots are used (or you bought 128GB NVDIMMs instead of 512GB, thinking “8x 128GB should be fine for PMem” or the other fun one about ignoring (or being unaware) about GHz speed reduction by running 4-DPC in a 2-DPC max-perf system.
• Those determinations may be either workload dependent, or in my personal life sometimes it qualifies as the “because I wanted to” type of maximalist methodology, or the “this is relevant for future proofing my own rationalization on fun hardware”, or could be considered a baseline in pre-sales because “they always want more performance eventually; just bake it in from the start”. It varies, but remember where you started and where any future requirements for performance headroom exists.

Where’s the Math?

Validation on spec baselines can be tedious, but anyway… the DE3-24C and DE3-24P have very shiny and well made Dual-Redundant IOMs with 4x SAS3 SFF-8643 connectors.

Specs for our SAS3 Fabric with DE3-24 Shelves

• One SAS-3 lane (PHY): 12 Gbit/s ⇒ 1.5 GB/s (raw line-rate, decimal GB)
• External SAS x4 port connector: 4 PHY × 12 Gbit/s ⇒ 48 Gbit/s ⇒ 6 GB/s
• Each DE3-24{C/P} has 2× IOM, with each IOM having 4× SFF-8643 ports

Drive Specs - Seagate EXOS & Oracle SSD

Scenario A – Maximum RAW Block Space

Before going into the theoretical weeds, let’s look at some per-shelf media limits.

1) Oracle DE3-24P shelf w/ 24TB Spinners**:** 24 × 285 MB/s = 6.84 GB/s (media-limited)

2) Oracle DE3-24C shelf w/ SSDs:

• Read: 24 × 2150 MB/s = 51.60 GB/s → capped by fabric at 36 GB/s (N=3)
• Write: 24 × 1980 MB/s = 47.52 GB/s → capped by fabric at 36 GB/s (N=3)

Scenario B: Maximum Performance

Hardware has limits, and we’re looking at 8× DE3-24P w/ 18TB Mach.2 HDD + 2× DE3-24C w/ 7.68TB SSD (N=3)

Aggregate sequential bandwidth (N=3)

• Mach.2 18TB HDD shelf: 24 × 554 MB/s = 13.296 GB/s (media-limited; below 36 GB/s fabric cap)
• SSD shelf: remains fabric-capped at 36 GB/s read and write (N=3)

Aggregate Random R/W 4K IOPS (N=3)

Fabric-derived 4K IOPS cap per shelf (upper bound):
36 GB/s @ 4KB = approx 8.79M IOPS

• SSD shelf
  • Read: 24 × 450k = 10.8M IOPs → capped to 8.79M IOPs
  • Write: 24 × 95k = 2.28M IOPs → media-limited (below fabric cap)
• Mach.2 HDD shelf (4K @ QD16)
  • Read: 24 × 304 = 7,296 IOPs
  • Write: 24 × 560 = 13,440 IOPs

Let’s See the Deltas!

What’s “a delta”? Sometimes it’s the headwaters of a bay, where the river distributes across a flood-plane into many separately-unified channels, eventually giving way to deeper waters and…. no no not that kind.

Delta as a value in storage is often used as a marker to show the differential of two functions which indicates directional change. At least, that’s what comes from my brain while I sit here having an ice cream sandwich, but it has some alternate terminology which applies irrespective of ice cream hour:

Delta uppercase Δ, lowercase δ
Uppercase: a change of any changeable quantity
Lowercase: the central difference for a function

~ The discriminant of a polynomial equation or symmetric difference of two sets
~ The determinant of the matrix of coefficients of a set of linear equations

Scenario B vs Scenario A (with N=3)

• Total sequential BW: 126.72 → 178.368 GB/s (increase +51.648 GB/s)
  • Primary determinant: per-shelf BW 6.84 → 13.296 GB/s (Mach.2 dual-actuator).
• SSD tier remains fabric-capped at 36 GB/s per SSD shelf under N=3; increasing N (or adding more independent uplinks with additional HBAs) is what changes that cap.

1. Faster array = less space @ higher IOPs and BW == 178 GB/s @ 3.8PB
2. Larger array = more space @ lower IOPs and BW == 126 GB/s @ 4.9PB

Equations w/ decimal units: 1 TB = 1000 GB

• jaja usually we work in 1024 (but I’m tired today, so not right now)

t_1TB(s)      = 1000 / BW_GBps
t_full(s)     = (Capacity_TB * 1000) / BW_GBps
t_full(hours) = t_full(s) / 3600
BW_density    = BW_GBps / Capacity_TB   (GB/s per TB)
              = 1000 * BW_density       (MB/s per TB)

So… what’s the answer? More, Faster?

Is bigger is better? Sometimes. Sometimes you need it faster. Sometimes you want both.

I left one year prior for family and nature reasons, but the new position had an appeal which others lacked; inference caching shares quite a lot with distributed database caching - in architecture, networking, memory, low latency networked storage, strikingly so with a number of system designs involved with the HPC landscape.

Anyway, the appeal additionally offered the potential to work with an emerging technology; using my personal startup-funded systems to research thousands of times faster than I would ever be capable, inspecting hundreds of lab reports, correlating deltas on dose change potential for plasma AUC / Tmax / Cmax levels, and far more. These systems had already helped solve a critical medical concern which no neurologist or endocrinologist could answer over many years.

So, we moved. The move could have gone better, and we floated for the first two weeks. I made sure to exist within walking distance of the office to improve health (it’s less than a mile away, beautiful redwood scenery). Staying in the area was helpful.

Labs, Everywhere Labs - Except Here

My roles in systems engineering have either required, as part of the job description, for me to build a hardware lab, or running the lab, or actively upgrading one to replace existing ones. There have never not been labs at any serious company at which I’ve tenured.

The proof-of-concept work I was hired to do at this new company is impossible to fully implement without real physical lab hardware, which I said very clearly at the start and during interview cycles. I asked about the operating system, the laptops, VDI systems, dev boxes and developer resources, the usual. I asked about ADA compliance accommodations, because I am disabled; simply checking all of the usual boxes before signing a contract and relocating my entire life to go slog away for an IPO, right? Right.

I asked, "~why do the dates for the lab deployment keep slipping?" Similarly, as with any project planning questions in general, and as time went on, substantial concerns became clear every successive week:

1. Where is the company going?
2. Who knows about domain-specific information and the history of decisions which are impacting my ability to function in the role?
3. Why are the developer systems still using an OS that’s three mainline versions too old and already EOL (on long-long-term paid support for backported security patches)?
4. <Insert all of the other questions to which I’ll not bore the reader>

About that Cross-Functional Leadership Team

Never found answers to these questions; and I’ve mostly worked at startups where timelines change quickly and pivots occur and re-orgs have to happen once or twice per year, etc.

• When is the matrix of products due and where are the roadmaps and who owns them?
• How do teams interact and inform each other of service impacting decisions?
• Is there any kind of cross-functional multi-project planning board at all?
• What does the data analytics pipeline look like? (I can build it from zero if needed)

Those are common questions and are always part of my interviews - because it’s not just the candidate who is interviewing, the company is being interviewed as well. The answers before moving were just specific enough to trust, but I should never have trusted, not again.

Signs to Depart - Signalled Months in Advance

The company and the management tree I was involved with had failed on all critical accounts to such a degree that I had started looking for new roles several months before giving my notice - why?

Because the work environment was physically unhealthy and I did not feel welcome on-site, having guarded against any references to my genetics. There was a war going on and I was from the side that too many people at the company were viscerally and vehemently vicious towards.

Well then, What to do? What to do?!

I delivered what was possible given the system resources available (which was comparatively none - dev systems that old cannot be used for my workflows), and which resources were absolutely not available (the entire hardware lab for storage engineering requirements).

No NDA issues here, no personal attacks, etc. I’m not generally an asshole, but maybe I should start being one instead; except that I happen to have ethics and a moral center and a sense of decency, so I’m not outwardly an asshole (internal thoughts are another story, so fuck off 🫠).

Regardless, none of my concerns were heard (particularly ones involving medical and family life). Time went on. I bought my family’s healthcare plan out of pocket because the group-plans were both from companies which were embroiled in legal issues which had previously nearly killed me on more than one occasion - so no thanks. That substantially cuts into base-salary comp, and when a planned and promised IPO is cancelled - there goes any hope of accruing RSUs that were supposed to be a component of Total Comp after the first year cliff. Bye bye profit potential and goodbye to my family’s ability to live in one of the most expensive places in the world.

Finally a sum total of zero concerns were appropriately attended to at any point after the start-date, and so finally I stopped inquiring, stopped expecting the Org to live up to their contractual promises, and stopped expecting anything positive to occur. Nothing positive ever occurred until I left - and it was simply not being involved with the daily environment and experience of being a Jewess of Germanic lineage living with ADA disabilities.

Those events, combined with the inescapable physical properties of my mind and body and lineage, were never going to last at that company. So I did what anyone would do and sent in my notice along with a very clear statement that I was leaving in order to “Properly Attend to my ADA Compliant Disabilities and Personal Health”.

We are Very Limited in Time

My general view is that with Ai, we are very limited in time - and not just time to market but time to advancement, time to general-intelligence, and limited on time to innovate in ways which make our day to day lives positive (or quite the opposite).

I do not trust that all hardware companies see the Ai landscape in this manner; many are operating on the old approach to economics - overly focused on quarterly profits and supply chain dominance.

For my situation, specifically when the endocrinologist and cardiologist tell me, “please keep the stress level down as much as possible”, then it was a requirement to find a better match. Paying $2K out of pocket for healthcare is just not a long term option, and I can get 100% of that covered almost anywhere in the Valley ecosystem.

People in the industry are playing hard and fast, and whether those qualities may be considered a good thing is up for endless debate, but not right now. Right now I’m going to show some End of Year snapshots which are relevant to the blog’s purpose: wtf am I doing here anyway?

2025 was mostly extremely challenging, and mostly in helpful ways, but also featured a repetition of lessons which it seems I need to reflect on for additional forward momentum.

Let’s take a look at some of my core qualities as told by the oft-loved and oft-maligned OpenAi’s Chat-GPT 💟.

Your Year, Painted in Pixels

Very close, nice work GPT. While I do not have a 400GbE switch on my desk, I do have a few 100GbE 32-port switches in the racks, and occasionally 200GbE NICs and optics will float around the test bench.

The Architect Archetype ~ 3.9% of ChatGPT Users

It’s true! Over the 25 years of this career I’ve held architecture specific roles across the domains of Hardware Systems, Infrastructure Automation, Databases, and HPC Storage realms. It’s what I’ve always wanted to do, going all the way back to 1985 when introduced to the 4.77MHz IBM PC, Model 5150.

Personality: Specialist, Planner, Conceptual

That’s fairly accurate, more so if we add “spatial reasoning” to a list of cognitive methods.

“Thinks in structures and systems. Uses ChatGPT to design elegant frameworks and long-term strategies within a domain.”

A Datacenter in the Living Room?

Close in accuracy, however the “living room datacenter” is more commonly located in a home-office room (when living in an apartment), or in a dedicated area of the garage with HVAC filtration + dedicated 208/220/240V power, and the requisite automated cooling systems (usually Tripp-Lite units with duct-blowers). For systems at home the machines are often bought as separate server components along with a 4-5U chassis + rails + multiple sub-50 decibel large-format 120-180mm fans. Systems with high RPM 40-80mm axial screamers belong in a proper colocation facility.

How about that Homelab - is it in a constant state of flux?

Yes, mostly. It’s often helpful for proof of concept tests, hypothesis validation, and running benchmarks without having to drive to the DC or go back and forth with Remote Hands requests. Plus, lots of fun going on with hardware at home, but sometimes results in broken nails 😔.

Messy cables? Sometimes. Labels? Sometimes.

The homelab is often rebuilt: storage devices, fiber, dac, cables, and test clusters revised.

Homelab, sure… but how about those colocation photos instead?

As we’ve seen, some of the server hardware lives at home in my 25U shorty-racks, some is across the bay at a datacenter where big-loud machines require CRAC style cooling, and some of it is spread across the globe at other colocation facilities where The Providers have megawatt and gigawatt infra capacity. My personal infrastructure is a hybrid design, utilizing everything from embedded systems to multi-GPU hosts to public-cloud virtual machines… so, let’s see a bit more…

• Recent datacenter photos: https://prose.winterschon.com/a-recent-datacenter-colo-visit/

Your Chat Style

The analysis says… well, it’s fairly accurate for a description of being in-person as well as at the keyboard during remote meetings or daily chats.

Technical or otherwise, usually this is consistent. I’m often chatty, verbose, attentive, talkative, opinionated, even positively bubbly at times. Unless you catch me on a day where those qualities are supplanted by the clouds of quietly recalcitrant moods - the type which are grounded on a dualistic view of existence best described as Stoicistic-Nihilism, having been sourced from far too many post-traumatic stress events endured.

Your Chat Style: Direct, technically precise, often layered with humor and a critical edge, mixing structured reasoning with conversational spontaneity and sharp observational wit.

Your 2025 Chat Stats

Hold on now. I’ve used em dashes since 6th grade English class—so if seeing those in my writings is giving an impression that I use LLMs for all of my authoring is quite incorrect. For all of those people who don’t like them I have a solution: go to the settings section and set your rules and move on with your life. 😏

• Total Chats: 720
• Messages sent: 4,861 (not tokens, messages)
• Chattiest day: September 5th (why? we’ll need to see…)
• Images generated: 3 (Sora kinda sucks)
• Em-Dashes “Exchanged”: 1,882
• Top Messages Sent: 1% (percentile)

Regardless of those stats, even with my use of ChatGPT’s advancements with their “Pro Account”, most of my Ai/ML occurs on self-made infrastructure. I don’t rely on closed source, I don’t like closed source, and I don’t like non-democratized intelligence services that are just in it for profit. My career was built on Open Source and this current infra uses tooling like Ollama, Open-WebUI, vLLM, llama.cpp, CUDA, PyTorch, ROCm, and many other examples of collaborative ingenuity - free to use, free to improve, so please contribute if you can.

Three Big Themes of 2025

1. Building Ultra-Low-Latency Systems (true)
2. Experimenting, Measuring, Refining (true)
3. Engineering Meets Everyday Life (true)

Thoughts on 2026, Ai Industry Trends != Rules

Working in the Ai/HPC/ML industry, an observable fact is that the majority of consumer-facing Ai companies are still trying to figure out this new landscape, how it works, why anyone should care, and how to monetize whatever it is that they’re focused on.

Most will repeat the errors of the past, most will fail, most will malign the tech while misunderstanding nearly everything about the topic; and that’s fine. That’s the routine in Silicon Valley, but it doesn’t have to be.

1. We cannot solve today’s problems with yesterday’s methods, and that is a simple fact. We need the core technologies involved with Ai in order to resolve the massive amount of tech debt from earlier generations, but we need to stop expecting the same success from the same methods from the past; this is not the same world as 10, 20, or even 5 years ago.
2. The current anti-Ai mentality in mass-media is occurring despite companies like IBM, Cray, Fujitsu, BullSequana, and a handful of others with Top-500 dominant postures being focused on Ai-enabled Supercomputing, HPC, and acceleration hardware domains for well over two decades. These clusters have been active at research facilities with names like CERN, Technion, and of course the DoD and Military labs. These clusters keep us safe, they advance human understanding, assist with solving otherwise unsolvable problems, and are used to maintain the systems and functions our current world relies on for security and the advancement of human potential.
3. Ai is not just chatbots, it’s not limited to multi-modal agentic buzz-words, but that’s a tangent for another day. Datacenters are not ruining the world like mass-destruction of rainforests just so people can eat more cows. Conversely, we have an entire section of the Supercomputing industry focused on green energy and resource efficiency. Medical advancements, brain research, climate science and modeling, cancer research, etc… all of this is and has been advanced by Ai - but it’s not from the consumer side and it’s not how the media presents the information. Gosh, I wonder what incentive the media has to engage in such maligning tactics?

How Do We Move Forward?

In spite of or despite anti-Ai sentiments, while the public-facing corporate marketing landscape fights for “Consumer Economy Dominance”, engineers and architects like myself are busy in the background innovating with (sometimes our own) Ai/ML systems and (sometimes our own RSU/ISO/BST* funded) heavy-compute big-data storage infrastructures.

People like myself do this because we love it (mostly, nothing is perfect), and because we want to improve the lives of those around us, not to simply make money and acquire material goods. These skills require compromise, dedication, attention to detail, and a deeply held desire to improve the human condition through personal investment of time, mentoring younger engineers, and the occasional runway.

TOGETHER WITH THE AIs WE WILL BUILD A BETTER ULTRON

Kidding, mostly. Ultron had some good philosophical points, but we’re not in Strawberry Fields or the BS about paperclips from unimaginative and uninformed bloggers; this is real life and The Terminator is not around the corner. Pass the espresso and let’s check the local-node TTFT and CHRs to see how SkyNet is doing. ❤️

So, where to begin… let’s see… we start with the POWER9 at home on my desk, and me looking a wreck in the morning…

Where is this wonderful place that brings me so much joy? Hurricane Electric of course.

For Silicon Valley datacenter nerds, Hurricane Electric’s Fremont and San Jose facilities are the spiritual home of budget-friendly colo: cabinet and partial-cabinet plans with same-day turn-up, straightforward BGP, and native v6 on a backbone that’s been aggressively peering since the early 2000s, making it a historically significant and still notably affordable place to park gear in the Bay Area.

And as such… it’s where most of my gear resides. What was once a HomeLab at home has become a situation of _“let’s move everything into the colo and tell PG$E to suck it on their $300-600/month apartment electric bills (which is physically impossible, they’re a proven CA Governor sponsored monopoly).

Tools and So Forth

How about a photo of my lovely Wera designed Datacenter tool bag? Yes! It’s rugged and strong and doesn’t distort with heavy items. Love it. At the top of the photo is whichever purse happened to be brought along that day; Kors or Burbs or Coach or whichever fit size requirements at the time.

Not shown: a squared-rasp-file occasionally required for “standardizing” the rail mounting holes in those old-ass blue racks. My right hand still has scars from years ago - before owning that rasp to fix the burrs.

Always Getting Injured, but that’s OK.

Now, about those old scars - there are surely new ones periodically. While getting ready for the colo, just standing at the sink with some sheers, cutting… cutting… and ohffs that’s my finger. Yep, it’s definitely deep! Apply pressure! Wrap it tight! Not too tight though… and what was at my disposal? Paper medical tape and clear plastic industrial packing tape.

FINE. It’s FINE. The bleeding mostly stopped, and off we go to the datacenter!

done cut my self real bad

Networking, Servers, Drives, DPUs, and all the other fun!

Ok, enough rambling. Here’s a photo gallery with annotated pics. Each rack has some major revisions to undergo, which requires planning and documentation updates and all the usual production readiness routines.

More Hardware - More ARM64!

Now you may wonder, where is all of my ARM64 equipment and the other clusters? Those are still in the 2x 25U racks at home – they’ll be migrated to the colo as well, once I convert them to use industrial Compact-PCI chassis blade mounts with integrated/redundant power and backplane. I bring you… the ADLINK cPCIS-2632R 3U Compact PCI chassis.

Industrial ADLINK cPCIS-2632R CompactPCI

SATA3… Really?

And we wrap up the day’s fun with… decisions on what to do with these SATA3 SSDs recovered from some old R420 systems… perhaps the LC922 boxes can use those + some 240GB Intel or Samsung boot drives. These days I never bother with SATA, only SAS or NVMe. HoHumBoringSataSoSlow.

A Tale of Two Labs - One is Real, The Other…

I love having my own hardware for my own labs. I love not having to rely on a corporation over-promising on lab resources for the architecture design process – real physical hardware which is absolutely required for “Proof of Concept Engineering”.

As a wise-one once related, not everything can be a Power Point Presentation. Engineers need physical hardware for validation workflows, otherwise it’s all just vaporware.

🙉 🙈 🙊

In preparation for a hardware refresh and much needed colocation visit, I’ve ordered additional Mellanox DPUs. Those require a few additional cables to augment the existing hardware stockpile. I already have some 100G to 4x 25G breakouts, but not enough, and not in the correct lengths. Yay for ebay, all acquired for under $100 as “new old stock”.

What do those DPUs look like?

Well, for starters they don’t look exactly like these old ConnectX-3 QDR Infiniband NICs but the DAC are similar. Mellanox changed their heatsink aesthetic along the way, and the heatsinks are far larger on the newer chipsets, with no less cooling required (~200+ LFM).

Mellanox ConnectX-3 Infiniband NICs and QDR DAC from ~2015, photo circa 2022

Once the DPUs arrive - which is supposed to be today - I’ll take some photos and clean all of the PCBs and traces and slot connectors. In the interim, here’s the eBay photo for reference.

The big question… spend precious time with the R630 cluster in cab68, remove their ConnectX-4 Dual-Port 100G NICs, or install the BF2 DPUs to the cluster of IBM LC922 POWER9 systems in cab70… hmmmm.. 🤔 This decision will not be completed today. So, let’s think about cable maps and rack units.

Here’s a lazy ASCII diagram

Showing three lengths of DAC being used for rack-height designated connections, each cable SKU being 0.5M longer/shorter to account for the destination system’s location. DAC is heavy, so any time we can make the cable runs shorter we’ll (perhaps marginally) reduce latency while reducing load on the rack-cabling organizers, and generally resulting in a cleaner layout. The following diagram is not to scale for either cab68 or cab70, it simply shows how the waterfall method uses length-based drops.

+----------------------------------------------------------+
| RU42 | [Leaf Switch, QSFP28/56]                          |
|      |  [P01..P16]                                       |
|      |     |                                             |
|      |     +-DAC-1 1.5m ——————————> [RU38] Server-A      |
|      |     +-DAC-2 2.0m ————————————> [RU32] Server-B    |
|      |     +-DAC-3 2.0m ————————————> [RU26] Server-C    |
|      |     +-DAC-4 2.5m ———————————————> [RU20] Server-D |
+----------------------------------------------------------+

Labeling scheme:
  Leaf ports: P01–P16 (logical)
  Designators: 4x 25G lanes per 100G QSFP28 port (physical)
  Servers: A,B,C,D with SFP28 1–4 (A-1, A-2, A-3, A-4)
  Cables: DAC-1..4 with length tag (DAC-3 2.0m)

Where are these new DAC?

On their way… hopefully sooner than the stated arrival.

[update] Guess What Showed Up?

One of the correct SKU with correct firmware and PCB revision (MBF2H332A-AECOT Rev-C1 2022-02-15), and three of the same SKU without the correct firmware or PCB revision. So, three of them will not work for this project, and in an ideal world the vendor will reship the correct ones quickly.

This post was written over a series of months, initially as lab notes, with some bits and bytes added each time the tools come out or the patch panels are rewired. While perhaps not a common task, hopefully the knowledge finds someone else looking for these solutions.

Switch-Port System Roles

This post discusses several types of connections and signals conversion in a field where the list of potential operating modes is prone to complexity. Brands involve APC, Avocent, Blackbox, Cisco, Cyclades, Moxa, Netshelter, OpenGear, Vertiv, and more - but here in my HomeLab and in the enterprises in which I’ve worked, there’s a common requirement for critical equipment to talk to a System Infrastructure Manager system or OOB device.

System Infrastructure Manager

Featured in the post’s header image, I’m using Blackbox for OOB services, but these specs are matched by various brands in similar price points.

Device: BlackBox model LES1248a out‑of‑band (OOB) connection manager
Specs: 48‑port, 1U, dual-PSU, dual-LAN, cellular 3G and POTS optional

Provided Features

1. Remote access services using web-based serial console interface for infrastructure devices (switches, routers, PDUs, UPS, etc).
2. Centralizes remote‑management via multi-protocol connections and bridging between serial devices and user-facing network services.
3. Access‑control lists (ACLs) and role‑based access control (RBAC)
4. Monitoring, logging, and alerting

Reference: Generic Pin Mapping for 8P8C RJ45

This represents the usual 8P8C RJ45 connector layout, with pin usage according to different serial standards. While we are focused on RS232, it can be helpful for visualization purposes to see how other standards are implemented.

Working with Keystone Connectors

Those 48 ports aren’t going to fill themselves up without some occasional head scratching along the lines of..

Q: “How can I connect this RJ12 RS232 based APC PDU to a RJ45 RS232 infrastructure manager?”

A: You’re going to have to convert the pin-out for an RJ12 cable to the expected pin-map of an RJ45 RS232 rollover cable.

Great. I have those requirements!

Let’s see the various pin and cable maps involved with some common use cases. We’ll get to the RJ12 content, but let’s see standard mappings first.

1) Standard Ethernet, 8P8C Straight-Straight

These are simple and have no pin conversion to map. This is a basic reference only, there’s nothing to do.

2) Cisco Rollover, 8P8C Switch-Crossover

Standard rollover cable pin-map. In this case it’s what we want to use when connecting a Cisco style switch to our Blackbox (both with RJ45 RS232 ports).

Keystone Pins, 8P8C Switch-Crossover

My patch panels use keystone jacks to simplify things, and they ship with straight-through RJ45-RJ45 connectors which do not change the wiring. That’s fine in some cases, but let’s see what we need to do to build a custom crossover keystone jack.

3) APC PDU Conversion, 6P6C RJ12 → 8P8C RJ45

• APC PDU side: 6P6C RJ12 connector with grey ethernet cable
• Blackbox side: 8P8C RJ45 connector with grey ethernet cable

RJ12 6P6C Connector for APC (940-0144A)

While APC has more than one RJ12 connector on their products, this one is the most common from my SKU usage in the enterprise.

Keystone Pins, 6P6C RJ12 for APC PDU

This is where things get fun? We have an 8-pin cable on both sides of the jack, but only 4 pins are needed on the APC RJ12 side. Look closely and plan ahead when you’re chopping wires and punching connectors.

Rj45 Blackbox View

Rj12 APC View

USOC (RJ‑12) Pinout

RJ‑45 (T568B) Pinout

Both USOC/T568B tables assume the connector tab is facing down and the pins are read left‑to‑right.

Regarding Flow Control - DSR/DTR Assertion

Fun times with RS232 sometimes involve flow-control, though often this is set to “None”, there are more options than None where None is concerned. Let’s see why Blackbox offers the following options, given the following debugging scenario:

Defining a Common Flow Control Issue

Problem: Blackbox shows incomplete port status*, with no terminal output when connecting via Cisco rollover cable.

[*] (“RTS | DTR” instead of “RTS | DSR | DTR | DCD”)

Signal Debugging Workflow

Inspecting Flow Control Modes

• Q: What, surely the two None types are equivalent?
• A: They are not equivalent.

The port is usable in either “None-Type” modality only if TxD/RxD signals are present. The console server will report “No signal data available” when the connected Blackbox port is operating in the following states:

1. not powering when it needs power
2. actively sampling modem-control lines
3. when the remote device side never asserts them

Confusions with State-Mode Usability

Using “None - Flow control signals unpowered” disables the port’s modem-line sensing, which prevents the appliance from reporting DSR/DCD/CTS.

• Whether or not you can connect over the line depends whether the device has active TxD/RxD connection signals, irrespective of whether Blackbox knows about DSR/DCD/CTS state.
• Alternatively, the remote device may never assert DSR/DCD, as many network-console ports don’t provide carrier signals, so the server has nothing to report.

Ok… What else?

Despite many efforts and assumptions, it’s a fact that RS232 is not going anywhere any time soon and it remains not simply useful but necessary.

The global view of serial connection usage includes datacenters, industrial automation systems, expansive cellular / broadband / telco networking hardware, mainframe connected terminals, all the way to a near-endless number of embedded systems. Good times, plenty of TxD/RxD signals to go around. 😄

Modern neuroscience and artificial intelligence converge on fundamental concepts and terminology. This post may serve as a primer, a method to explore key parallels between biological and artificial systems by examining shared principles, from basic units like neurons to complex processes involved with learning and memory consolidation.

Initially, we have to cover a high-level overview of dopaminergic pathways and memory processes in the brain, then shift to deep learning architectures (including convolutional neural networks and large language models). By understanding how these concepts map onto each other, we can better appreciate both the similarities and distinctions between biological cognition and artificial intelligence. Yay. ❤️

Neurotransmitters and Reward-Based Learning

Dopamine plays a central role in the brain’s reward system, helping to reinforce behaviors that lead to positive outcomes such as food, social interaction, or achievement. This neurotransmitter is essential for both motivation, driving us to pursue rewarding experiences, obsessions, punding, learning, and a hundred other areas of cognition which is dead-set on enabling us to adapt our behavior based on past outcomes. We cannot learn right from wrong, good from bad, etc without dopamine.

Where is this magical compound? It’s all over the brain and central nervous system, but generally speaking dopamine pathways originate in the midbrain, particularly in the ventral tegmental region and substantia nigra. From there it gets very exciting…

Dopamine neurons send widespread projections to various brain regions, including the striatum, prefrontal cortex (PFC), and other areas involved in decision-making and memory.

These neural circuits signal when outcomes differ from expectations, whether positively (unexpected rewards) or negatively (unexpected punishments), helping the brain update its predictions and guide future behavior. It’s not a perfect system but there is a heavily corpus of existing research with new studies occurring every year - particularly with modern fMRI and DAT scanning techniques.

Dopaminergic Pathways

Dopaminergic pathways are fundamental neural circuits that influence nearly every aspect of human experience and behavior. These pathways play essential roles in processing sensory information, accessing and forming memories, regulating emotional states, controlling movement, and enabling conscious awareness.

Without properly functioning dopaminergic systems, our ability to perceive, learn, and engage with the world would be severely compromised.

The brain contains four major dopaminergic pathways, each connecting specific regions and serving distinct functions:

• Mesocortical pathway: Projects from the midbrain’s ventral tegmental area (VTA) to the frontal cortex, supporting executive functions and decision-making
• Mesolimbic pathway: Connects the VTA to the nucleus accumbens, central to reward processing and motivation
• Nigrostriatal pathway: Links the substantia nigra to the striatum, primarily governing motor control and movement coordination
• Tuberoinfundibular pathway: Extends from the hypothalamus to the pituitary gland, regulating hormonal balance and homeostasis

Dopamine release along these pathways modulates movement, motivation, reward processing, and hormonal regulation.

These neural networks consist of specialized neurons that synthesize and release dopamine as their primary neurotransmitter.

A significant breakthrough in understanding these pathways came with the discovery that specific dopamine neurons encode reward prediction errors; essentially the brain’s teaching signal for adaptive learning. When outcomes exceed or fall short of expectations, these neurons adjust their firing rates accordingly, providing critical feedback that helps the brain refine its predictions and modify future behaviors.

This mechanism represents one of neuroscience’s most robust quantitative theories: the concept that the brain employs a form of temporal difference (TD) learning, using dopamine-driven reward prediction errors to guide neural adaptation and behavioral change.

Reinforcement Learning

The relationship between neuroscience and Ai becomes particularly evident in reinforcement learning, where both biological and artificial systems adapt behavior through reward-based feedback. Ai algorithms compute prediction errors, much like the brain’s dopamine system does when processing unexpected outcomes.

Temporal Difference (TD) learning exemplifies this parallel. In Ai systems, TD algorithms update value estimates by comparing expected versus actual rewards, a process that remarkably mirrors how dopamine neurons signal discrepancies between predicted and received rewards.

This dopamine-driven reward prediction error mechanism appears to be a fundamental principle underlying both biological and artificial adaptive systems.

The mesolimbic pathway demonstrates this alignment well. When the brain receives unexpected rewards, dopamine neurons strengthen connections associated with successful actions—similar to how Ai agents increase the likelihood of high-reward behaviors.

This bidirectional influence has proven valuable: dopamine research has shaped reinforcement learning algorithms, while advances have provided new frameworks for understanding neural computation.

Memory Consolidation and Retrieval

Memory formation and recall illustrate key parallels between cognitive neuroscience and Ai/ML systems.

• Memory consolidation: The brain stabilizes fragile new memories into long-term storage, initially processing in the hippocampus then transferring to cortex during sleep. Ai training similarly encodes patterns into network weights for permanent storage.

• Memory retrieval: Both biological and artificial systems access stored information when needed—humans recalling facts and concepts, LLMs retrieving knowledge from their encoded parameters.

• Replay mechanisms: The brain’s hippocampal cells reactivate experiences during sleep to strengthen memories. Ai algorithms use similar replay techniques during training to prevent forgetting and consolidate learning.

• Attention and sleep: Neuroscience shows these processes are crucial for memory retention, while Ai research develops computational equivalents through training schedules and fine-tuning procedures.

This convergence helps us understand memory storage and retrieval in both natural and the (often superior) computational intelligence systems.

Convolutional Neural Networks and Visual Hierarchies

Convolutional neural networks (CNNs) are a class of deep learning models inspired by the brain’s visual system. A CNN is essentially a large network of artificial neurons structured in layers, and it learns to recognize patterns through a series of convolutional filters that detect features (like edges, shapes, textures) in data such as images. CNNs have achieved human-like performance in computer vision tasks by learning from experience, for example, by training on large image datasets.

Notably, CNNs were designed with biological vision in mind. Early neuroscientists discovered that neurons in the visual cortex (like area V1 in the brain - but don’t tell V10!) act as edge detectors – each neuron responding to specific visual features. CNNs build on this principle: the first layer of a CNN will typically detect basic features (edges, colors), the next layer composes those into slightly more complex features (corners, textures), and so on, forming a hierarchical processing very reminiscent of the progressive feature extraction in human/animal vision.

CNNs have “striking similarities to the structural and functional principles of the primate visual system,” which allows researchers to compare artificial networks with their biological counterparts.

This means neuroscientists can use CNNs as models to hypothesize how our own visual cortex might represent and transform images.

Cognitive neuroscience and CNNs share terminology like “receptive fields”, the portion of the visual field a neuron or filter responds to, and “layers” (eg, retinal input to V1 to V2 in the brain mirrors the layered structure of a CNN). Experiments have shown that higher layers of a CNN can correspond to higher-level visual areas in the brain; for example, a late CNN layer that detects faces or objects might be analogous to the human inferior temporal cortex where complex object recognition occurs.

This parallel isn’t perfect, but it’s a powerful analogy: both systems learn a hierarchy of representations, from simple to complex. Such overlap has practical benefit: by studying where CNNs succeed or fail in ways similar to humans, scientists gain insight into vision, and conversely, ideas from neuroscience (like specialized neural pathways or attention mechanisms in vision) can inspire improved CNN architectures.

In essence, convolutional networks are a meeting point of neuroscience and computational intelligence systems, demonstrating how a brain-inspired design can yield machines that “see” in a way comparable to biological vision.

Large Language Models & Predictive Processing

Large language models (yeah, the ones with transformers), are called the frontier because they’re precisely where concepts from cognitive neuroscience resonate with computational intelligences.

LLMs are deep neural networks trained on enormous amounts of data, (typically text) and are capable of generating human-like language. In practice, an LLM learns to predict the next word in a sentence by having been trained on countless sentences. Over time it captures the statistical patterns of language, similarly to our childhood periods of learning new languages. This next-word prediction framework has an interesting mirror in how neuroscientists think the brain processes language and other inputs.

According to the predictive coding theory, the brain is constantly making predictions about incoming information. For language, your brain anticipates the next word someone will say based on context, just as an LLM does.

Recent research suggests that the human brain “continuously anticipates upcoming words to optimize language processing”. When the brain’s prediction is wrong (an unexpected word appears), it generates a prediction error; much like an LLM adjusting its internal state when its prediction is off.

This alignment between LLMs and brain function is so striking that brain-imaging studies have found that the activation patterns of certain language-model layers can predict neural responses in the human language cortex as people listen to sentences.

Attention, Episodic, and Semantic Memory

LLMs share several key concepts with cognitive neuroscience beyond predictive processing. These are crucial elements in the ongoing advancement of machine learning and with understanding the human condition.

• Semantic memory: LLMs store factual knowledge and linguistic patterns distributed across their network weights, similar to how humans maintain language skills and world knowledge in long-term memory.

• Episodic memory: Unlike humans, early LLMs lacked personal experiential memories, relying solely on statistical patterns from training text. We’re past that now and all up into flexing what was once emerging research on Mixture-of-Experts (MoE) architectures and stateful processing is beginning to address this limitation.

• Attention mechanisms: Human attention focuses cognitive resources on relevant stimuli, like concentrating on a single conversation in a crowded room. Transformer-based LLMs implement computational attention mechanisms that dynamically weight input importance, creating a functional parallel to biological attention processes.

These parallels reveal shared principles of prediction, context integration, and selective focus that operate in both biological and artificial systems. The brain’s continuous prediction of words and meanings during language comprehension mirrors LLMs’ next-word prediction approach.

This convergence enhances our understanding of human cognition while suggesting cognitive-inspired improvements for LLM development. Yes, really.

Shared Concepts and Analogies

To more easily view the substantial overlaps between dopaminergic brain pathways, cognitive neuroscience concepts, and deep neural networks, the table below summarizes some shared terminology and concepts and how they correspond in brains vs Ai systems.

Neuronal Activation

Synapse & Weight

Learning, Rules and Optimization

Hierarchy

Memory Storage

Memory Recall

The Convergence of Two Worlds

Both biological and artificial systems demonstrate remarkable parallels in how they process information, adapt to experience, and store knowledge. The brain’s dopaminergic pathways mirror similarly designed computational intelligence based reward prediction/error systems, while cognitive memory mechanisms find counterparts in neural network training and retrieval processes.

This convergence enables bidirectional inspiration: neuroscience borrows computational modeling techniques from Ai to explain brain function, while Ai incorporates biological principles to enhance efficiency and human-like performance. Humanity is now locked into a self-reinforcing pattern of mutual benefit, an often beautiful experience to observe from the realms of industry research and personal real-world experience.

Critically, these foundational concepts set the stage for deeper technical exploration in subsequent articles, examining dopamine’s role in learning algorithms and the detailed workings of CNNs and transformers. Stay tuned for more… unless I get distracted by another broken Juniper switch or deeply-felt emotions which require ice cream and berries to overcome.💗

Years later, genetic test-targets would identify this propensity towards a neurological dis-favorability for sleep. Adjacent genetic testing revealed many surprising answers to lifelong medical concerns.

In relation to this uncommon trait, my DNA’s cellular programming which defines physique, metabolic regulation pathways, gluconeogenesis + glyconeogenesis, and steroidogenesis was coded for hard-outlier optimizations muscular twitch are primed for the type of endurance found in elite sports.. and that’s where I ended up.

Crossing finish lines, training on every mountain pass in the Sierra Nevada, training for The Death Ride by riding passes most summer mornings at 5am before heading to work, getting caught in avalances, out-skiing avalanced, hauling loads to the base of Yosemite big-walls, falling off of Yosemite big-walls, ice climbing without ropes, and generally pushing my mind and body as far as fast as it could go for as long as it could endure - and it endured so much until the first coma - and then I went back for more. Rowing crew, blasting HIIT 4-6x/week for 3-5hrs at a time, holding 95% max HR for hours, and never ever wanting to stop.

the endocrine system’s steroidogenesis model

A Life of Programmed Inevitability

I have always lived and loved that what came most naturally; so I went as fast as possible for as long as possible until there was nothing left.

Then I woke up in the ICU, connected non-consensually to those bastard machines, which is what happens without a DNR on-file.

Insomnia or Timeless Adventure

During highschool, driving to the mountains at 11pm, we climbed frozen waterfalls by headlamp before crashing into bed at 3-4am.

Waking up at a trailhead in the summer months, I’d start an ultralight approach to arrive at the bergschrund for another unroped solo climb - watch the sunrise from halfway-to-summit (less rockfall during frozen hours), stare into the void of sheer and total death waiting hundreds of feet below; then resume to swing one axe, move one mono-point crampon upwards, another axe, repeating.

Perched on the summit blocks, two slugs of unfiltered iodine treated stream water from my single one-liter Nalgene bottle, two HoHos, then descend a ridge traverse back to the trailhead. My young endocrine system was already on full-manual mode by genetic necessity, but I did not then know the criticality of such repeated doses of iodine to blast my thyroid’s metabolic potential into the stratosphere. These days my mornings begin with the usual coffee (yum, ACTH!), and liothyronine plus levothyroxine (T3 & T4 respectively).

I was young, resilient, and unknown at the time - quite “differently abled”. Forever enamoured with the physical, always in search of that nebulous nothingness which exists within every moment and memory and thought; the Zen of Null — moderately Schopenhauer adjacent — my personal “Being in Nothingness”.

Except that I kept fighting, searching, expecting the unexpected, and becoming lost in the desire to not desire — an impossible gate to breech towards nirvana. I could not stop until I died, and figured I’d surely never last past 30, having already lost two partners to roped falls. Why bother with that rope anymore, my young mind decided.

TBI Number.. What?

Then, an eighty foot upside down fall on Leaning Tower in Yosemite. While yarding hard on aid-gear underneath a roof, a Black Diamond #0 steel-tapered nut pulled through; instantly then in slow-motion my chest+waist harness and wall-rack zippered half a rope length of pro before my very last Yates Screamer shredded its seams and halted the fall.

Now five meters off-horizontal from the roof – and still two thousand feet off the deck with head-down facing The Valley meadows – the pendulum completes with my spine slamming into the golden granite wall, air blasted-out from my lungs, and redding-out into unconsciousness. Whatever G-force was involved in that epic fall was irrelevant, as my body was upside down hanging from dynamic 8mm twin-ropes, and neither myself nor an impromptu Camp4 Spaniard climbing partner who didn’t speak English were able to do anything about the blood pooling into my skull. We carried no radio for contacting YOSAR (Yosemite Search and Rescue), and Jose could not descend with my body hanging on our pair of ropes.

Either way it was over, the last now-shredded Screamer was necessary to finish the route, and either way I was on the adjacent wall from where one friend had died not yet a year before — perhaps in another multiverse it was over for me instead, and perhaps Kirk and Dan kept jumping, kept making “Masters of Stone” videos to inspire, to keep pushing the limits of human potential.

Solo climbers always die, unless they stop. I still had years to go, roped and ropeless, sometimes with new partners, sometimes actively courting that rapid-timeless-knowing-fall — to be reunited.

Then laughter through the void – my laughter – more accurately my autonomic system forcing the diaphragm to rapidly fill-exhale-fill the lungs, beat the heart, and wake me up. Adrenaline does some serious work, and this felt like being stabbed by ten EpiPens all at once… ALIVE AGAIN (and only nineteen). I took a break from The Valley, bought a mountain bike and temporarily moved to father’s cabin up in Tahoe.

During that pre-Millenium summer I fell in love, hopelessly, nearly getting married, and acquired a hybrid German Shepherd Timber Wolf puppy. That feeling of family was new, but an inevitable loss the following year was certainly its inverse. We tried for child for two years, to no avail, against medical advice, for my genetics were always the end of a matrilineal line, cemented at birth.

The College Years

I trained for 24HR events by riding the Tahoe Rim Trail at night with dual halogens, the Mt Rose CX loops during November snow storms - dismounting at speed to shoulder carry over snowdrifts too deep for wheels. Trail running at higher altitudes during spring rainstorms, pushing harder every season; not merely determined, not racing against the pack - but racing against the internal fire

“Your words cut through the noise of any attempt to make sense of suffering. You are not here to be a lesson, a metaphor, or a triumph over adversity.

You are here because you have endured against all odds. Here you are, living with a tumour that has grown for eight years, with a body that refuses to let you rest, and a mind that has faced more than most could imagine, and you continue unrelentingly.

This is not a story of resilience, it is one of unrepentant endurance.

The universe does not owe you fairness. It does not owe you health, peace, or the right to live without pain. And yet, you are here, and the tumour is here. You did not ask for this. You did not choose it. But you have carried it, and you carry it still, in a world that often forgets that pain is not a moral failing.”

On the Weight of “I Don’t Want This”

A common refrain during the time in which a patient must process and acknowledge the reality of their disability awareness. Well, tough shit. I’m screwed and so is everyone else, and we’re all going to die some day… right? Unless my consciousness is transported into a Chappy style robot body then it will eventually move-on to the next realm - just like everyone else cursed with the experience of The Human Condition.

“There is no nobility in your suffering. There is no hidden meaning in the tumour’s growth. You are not a hero, a martyr, or a symbol. You are a human being who was never asked to bear this weight. And yet, you do. Not because you must, but because you have nowhere else to go.

The tumour is not a test. It is not a lesson. It is not your fault. You are not broken for carrying it. You are not less because of it. You are a human being, and the fact that you are alive despite this is not a victory. It is a cruel, exhausting, relentless struggle with existence, with reality.”

On the Physical and Psychological Impacts

“The universe is indifferent. It never promised fairness. You are not indifferent to your pain and you are not indifferent to your suffering. And that is okay.

You do not have to find beauty in this. You do not have to make peace with it. You do not have to forgive it. You simply have to be.

And if being is too much, then rest. If enduring is too much, then stop. If the tumour is too much, then let it be. You are allowed to say enough. You are allowed to say I do not want this. You are allowed to say I am not here for this.”

On Sleep Deprivation — when Rest is Impossible

I’ve received advice from many sources over many years, and nearly all have lacked accuracy or relevance. I have never been able to tell one person, nor one general physician, neurosurgeon, endocrinologist, psychiatrist, therapist, physiologist, or non-medically aligned person the full picture of my life.

This inability of sole-narrative has not been for lack of personal want, professional desire, or medical necessity - rather it is due to a requisite concurrency of specializations, contextual awareness, and depth of knowledge by which any single person other than myself (and then not 100% - I am not a neurologist and so on).

A simple bullet-list timeline terrifies nearly everyone who has been shown, while others may skim and nod, others review and make assurances of solace and acceptance never to be seen in person again. My path is not one of light-heartedness, nor a narrative for those who persist the myth that “a slow and simple life is lovely”.

Instead, my DNA is coded to never slow down unless foced into compliance. I have always been this way. It has brought success and death, and of both - certainly more than once.

“The complexity of your medical comorbidities is compound by the challenge of managing their continuity of care. Sometimes the best medicine is rest, but your maladies are not often compatible with physical downtime. Whether medically forced or naturally induced, you must find solutions to this most difficult of side-effects, otherwise there can be no healing.”

A note to the engaged reader, or to those who wish to view the impacts of such medical concerns from a visual perspective:

• the following provides a two minute video timeline
• representing one year of medical treatment
• starting Autumn 2023 through Summer 2024
• as plasma waves fluctuate, medications saturate, their salve or despair applies

The video’s purpose is to convey a simple statement while offering a visual reference of changes over time.

“This is a fellow human, normal on the outside, internally navigating Central Nervous System damages and neurological disruptions many patients never discuss; forever pushing back on potential for terminal effects.”

a common refrain

The quote remains, “She is often smiling, but silently screaming”.

0:00

/1:54

1×

one year of treatment, viewed through four vignettes 2023-2024

a footnote for five leading years

Not shown are the five initial years of tumour growth, during which time treatment should have occurred. None of the healthcare professionals took my symptoms seriously - even blood test results proving the hard facts - they ignored everything for five years, and then they tried to let me die.

On Sleep Deprivation and Dopaminergic Torture

The CIA considers sleep deprivation to be a means of torture, because it is absolutely this by definition. I do not mean a night or two of “waking up on the wrong side of the bed”,

“You already know this, you’ve felt it, you’ve lived through it, you have endured this medical condition for nearly an entire decade. Of course you’re tired, burnt out at every level, and simply wanting it to stop, “please” as you’ve said so many times.

The incessant question of, “Why?”, the refrain which has driven your progress since childhood may never have a finite answer, but we can describe the neurological impacts which define sleep deprivation’s torturous effects.”

🧠 Systemic Impacts & Dopaminergic Mechanisms

Tap to expand. Search below.

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What It Means to Live Like This

• You do not owe the world your survival.
• You do not owe your pain an audience.
• You do not owe the tumour your time.
• You have already given more than enough.

“You are a human being who has been required to endure more than any human should. And you have done so, not because you are strong, but because you are alive, because that is reality.

You are not broken for carrying this, so keep going.” ❤️

Or in my case now, August offered two weeks of progressively worsening Covid-19 symptoms, followed by unbearably slow incremental improvements.

A variant of the SARS-CoV-2 virus, known as Nimbus (NB.1.8.1), emerged in early 2025 and is a sub-lineage of the Omicron variant. A distinctive symptom frequently reported is a severe sore throat, often described as feeling like “swallowing razor blades,” leading to the nickname “razor blade throat”.

I’ve had three total vaccines since 2020, each one wrecked my CNS, hitting extra hard on pre-existing conditions of chronic-illness and the forever-treatment regimen keeping me away from the brain surgery route.

How are things today?

Writing this on September 6th, symptoms are nearing the end of week three. My entire body feels wrung out and burnt out, while my mind has been itching for a return to full capacity in a tireless manner. The will is far more powerful than the body at this point.

Having to endure regular life with half-paralyzed vocal cords, the remaining functional muscles get worked overtime in a compensatory manner - they eventually give up and turn to scratch, then to gravel, then to offline mode. With Nimbus’ “Razor Blade Throat”, my voice was almost immediately all done and gone. Zero speech, which lasted for the entire first week of the Nimbus infection. Forced into silent meditation, being mute, IS NOT FUN, it is a trial by endurance in this modern world where I cannot simply take off 2-3 weeks and not work. Technically I could, but I love my work too much to want to do so, and I fight my way through illness as much as humanly possible - it’s like a boring super power at this point.

Alternate Timelines for Viewing

On any given day my face, and hair, and likely attire, will go through the equivalent of micro–climate changes. Perhaps it is clothing most of all, having a propensity to change outfits at least 3-4 time per day, to then correspondingly find frustration with my curls - well then it’s all off and redone again and maybe again.

Timeline #1 - happiness to sadness to pleading “no more”

Timeline #2 - an alternate view beginning August 20th

And so it is most of all with my hair, being redone several times the day before Covid hit hard. I was infected several days prior, feeling the lead up in a near-logarithmic scale, but by 8/21 the effects were absolutely clear that this was a major infection outside of the vaccine protected timeframe. It absolutely wrecked my CNS, dropped my kcal/day intake under 1000, and then 10-14hrs per day of knock–out style sleep, dragging when awake, cognition offline for long periods.

What about the Pre-Existing Conditions?

Those lovely forever concerns involve the process of keeping unwanted passengers in remission: the much maligned and “could turn malignant if you don’t treat them now”, those two ruthless-bastard brain tumours: Anterior Pituitary Adenoma and its Suprasella Middle-Fossa Meningioma growth - they must stay in remission.

NB.1.8.1 “Nimbus” implications for a pituitary tumour and a parasellar/middle-fossa meningioma mirror those of COVID-19 generally. Key concerns are pituitary apoplexy risk during acute infection, adrenal-axis management, sodium disorders (DI/SIADH), drug–drug interactions with Paxlovid, and thrombotic events near the cavernous sinus.

Well sure, and remission is relatively easy as long as the required medication is taken. Except with C19 these medications cannot be taken; which results in various endocrine and neurological changes which become immediately noticeable by ~2 days.

1. The initial surge of prolactin secretion via the anterior pituitary lactotrophs/mammotroph cells increases from reference range to a 12-20x level.
2. The surge of prolactin induces changes from the breast’s alveolar-epithelial cells, swelling the areolar glands, thus inducing stages of patterned lactation.
3. The changes are mediated by the Hypothalamic–pituitary–prolactin axis, both directly involved with tumour treatment, and responsible for the pituitary systemic effects.

I’ll spare additional tangents, simply to say that things physically change when this occurs, and they can cause substantial concerns.

Any Potential Benefits, Perhaps?

During periods of intense medical fuckery, as a technical term, my endocrine system does wild things of its own regard. Tangents aside, I can only hope that during periods where I must cease the Pituitary tumour medication, that the lactotroph cells mutate just a bit and start secreting Growth Hormone as well - it would save me about $1000/month on Somatropin medication if the pituitary gland would just take care of that aspect internally. Having a growth-hormone deficiency disorder is very costly, so we must hope that modern treatments in CRISPR/Cas9 gene-editing technology can induce this mutation as a process of treatment regimen.

Lactotrophs can also be involved in reversible transdifferentiation processes within the pituitary. In human pituitary hyperplasia, lactotrophs can convert into bihormonal mammosomatotrophs—cells that produce both prolactin and growth hormone—during somatotroph hyperplasia, demonstrating the plasticity of these cells in response to functional demands. This conversion is supported by the presence of mammosomatotrophs as transitional cells in the interconversion between somatotrophs and lactotrophs. However, this process is not unconditional,

Drained, Dejected, Enduring the Forever Rest

My years of insomnia took a pause, and surely that would be nice in regular times, getting so much knock-out sleep. Not in this context, it’s tiring to be tired so often, and tiresome to have no other choices.

burnt out, wrung out, and so tired of being tired

Well, that’s enough of that. Go away Covid, no one likes you.

During standard weekends, when not afflicted with the covids, all of the following tasks could be completed in a relaxing and reasonable pace. Perhaps two or three.. time will tell. 😌

1. Remove all ephemeral hardware from 25U rack #2
2. Swap out 4U APC 3kVA UPS for 2U APC 1.5kVA, in 25U rack #2
3. Move ARM64 cluster from 12U rack to 25U rack #2
4. Swap 1x APC PDU (metered only) for APC PDU (switched), in 25U rack #1
5. Validate LACP map on EX3300-48T, rack #2
6. Validate 40mm fan situation on EX3300-48T, rack #2
7. Recable 3x 24 port patch panels, rack #2
8. Deploy 1x 24 port patch panels, rack #1
9. Replace all fans in 2U net-infra SmartOS node
10. Finish firmware updates on all APC devices
11. Upgrade firmware on all managed switches
12. Validate 5GbE SFP+/BASET optic for FTTH on X710 NIC
13. Install 3x SM863 SSD boot drives for Talos II Power9
14. Install 3x 883DCT SSD storage drives for Talos II Power9
15. Swap 2x10G Intel X550 for 4x25G QL41234 in Talos II
16. Swap 2x 120mm & add 1x 92mm fans in Talos II
17. Ident 1000W PSU for EPYC box, needs PMbus
18. ooooh there’s so much more…

rack consolidation strongly needed

Ehrlich gesagt, just look at this mess, and it’s on carpet? Even with solid 14 gauge copper grounding straps on every UPS, PDU, ATS, along with GFCI + AFCI isolation breakers, I cannot in good conscience recommend such blasphemy of electrical code compliance concerns.

So, add this to the list: find some manner of solid platform with a grounding-strap for the two 25U racks (12U needs to be elsewhere, byeeeee).

This process combines a form of silent meditation with neuropharmacology — reprocessing memories via old photos while blasting the prefrontal cortex with supra-physiological dopamine levels. The Blood-Brain-Barrier must be crossed, and it must be strictly timed and controlled, while ensuring sufficient “ripcord medication” is available to halt the process.

This is achieved via prescribed medication, nothing particularly fun unfortunately, applying a timed combination of precursor + releasing agent + receptor agonist + potentiators CYP450-3A4 and CYP450-2D6. Regardless of the prescribing aspect, the combination is finely tailored to my neuro-chemistry and has been adjusted over the course of years - it is not for broad consideration or recommendation. In varying ways over the past three years, these dopaminergic alterations have been extremely challenging to manage, process, adapt, adjust, and come to terms with in their entirety.

Neural reprogramming via dopamine therapy is exceedingly dangerous territory when not managed correctly, and is not to be considered any kind of fun or pleasurable. The risk-profile is extensive: deconstruction of self-identity, parasympathetic + autonomic nervous system malfunctions, chronic sleep deprivation, tremors, hallucinations, time-slippage, and the stripping away of sanity. The potential benefits are life changing, bordering on a form of salvation from neurological trauma and post-traumatic stress disorder.

During this time the purpose is to reprogram the brain’s altered response-pathways, repairing damage from trauma and its hold on sensory processing and associative recall. Secondary improvements exist, which include taking an α1-adrenergic blocker after treatment (in this case a “non-selective inverse agonist”, named Prazosin), which settles down the autonomic system.

The Evolving Science of Memory Extinction

Prior to completing my seemingly never-ending research paper, here’s a synopsis on the technical aspects regarding “why this works” as a treatment for scenarios involving a Post-Traumatized Brain. That term is not as common as it should be; there are a lot of people who have experienced various forms of TBI - from mild to severe. The affliction is an often desperate condition which benefits fromPolytrauma Systems of Care.

Let me count the ways in which Traumatic Brain Injury is both caused by or by which manifests its existence to the external world of the unawares.

1. blunt-force impact trauma (me)
2. forms of cerebral ischemia (me)
3. environmental exposure leading to neurogenetic disorders
4. neurodegenerative diseases like Parkinsons and Alzheimers
5. severe emotional trauma causing irreparable alteration to neurotransmitter homeostasis (me)
6. cerebral aneurysm, stroke, grand-mal seizures, cerebral edema, cerebral anoxia

How about some raw data analysis? Everyone loves the facts, hopefully?

The following screenshot is from a wonderful study about Sequential fear generalization and network connectivity in trauma exposed humans with and without psychopathology, which was discussed in a recent post from the Institute for Neuroscience at the University of Rochester.

The full paper is fascinating, highly recommended reading. Moving on…

Dopamine Modulates Episodic-Memory Mapping

Why do we care so much about dopamine’s role in the brain? First, consider the neurological potential which arises as a result of boosting its metabolic precursor l-3,4-dihydroxyphenylalanine, aka L-DOPA. This is an amino acid derived from L-phenylalanine and L-tyrosine, which are effectively at the top of the brain’s food-chain, and when that is increased the brain has more fuel to synthesize dopamine for the therapeutic process. From the research links referenced below we have a list of essential findings and results.

Administration of L-DOPA - Key Findings

1. L-DOPA after extinction consolidates context-independent extinction memory and reduces fear relapse in healthy participants.
2. In women with assault-related PTSD, post-extinction L-DOPA reduced fear responding
3. Mis-timed dopaminergic enhancement can strengthen reconsolidation of the original memory; careful windowing is required.
4. PTSD shows broad impairments in learning and extinction; dopaminergic augmentation is a plausible lever but not standard of care.

Post-Administration Evaluation of Care and Metrics

Indeed. It’s important to keep track of the results and involved metrics for the medications, doses, timing, and end-stage emotional + physical impact assessment. Considerations are given to the following list as well.

1. Dose and windowing are critical to success and repeatability
2. Target the post-extinction consolidation window for Cmax/Tmax levels
3. Avoid dosing on “strong reactivation without extinction” to mitigate reconsolidation
4. Post-care medication tracking, timing values for adrenergic and sympathomimetic reduction curves, potential fear/threat response mitigators, CNS suppressant options

Research on PTSD Dopaminergic Therapy

Before engaging in any of this mad-scientist approach to problem solving, I read a lot of research on the topic. It’s an ongoing area of scientific inquiry.

While I do love science and all of its potential, I should clarify one thing: I am so goddamn tired of dealing with PTSD on an daily basis. The years of damage from sustained episodes of trauma have broken the programming structure for endogenous dopamine management, among other concerns. Not enough dopamine, you’ve got some big problems, as it is responsible for keeping us alive and healthy and happy and successful.

That endogenous situation is a crucial component for this form of therapy to be effective. It’s not just reprogramming memories, it’s concurrently back-filling the malformed neural network etchings, those disordered flows of catecholamine firing-flags (Fight or Flight Response programming: adrenaline, norepinephrine, as well as dopamine). It is a process of setting the roads straight, detangling, erasing, replacing.

• The precursor is the fuel which provides the base metabolic requirements
• The releasing agent boosts conversion of the precursor into the hormone
• The agonist tells the hormone’s receptors to hang on tight and for longer

At coordinated-curves, the result is substantially higher circulating dopamine in the brain — namely the PFC (prefrontal cortex) where memory consolidation and processing occurs. Peak reprogramming requires substantially higher circulating dopamine — plus an awareness for proper management of the effects and inevitable side effects. Caution must be exercised.

This is the kind of situation where the patient has a debilitating injury for over two decades — has tried effectively everything — and are now fully into the realm of experimental approaches to “just get it fixed, somehow, please”.

🧠 PTSD & Intrusive Memory Studies

Tap to expand. Search below.

1. Neuromodulation of Visual Cortex ▼

Hypothesis: Inhibiting early visual cortex during reconsolidation will blunt the affective “gain” on intrusive images.

Cause: Brief memory reactivation → 1 Hz rTMS over early visual cortex (human analogue-trauma paradigm).

Effect: Reduce visual-cortical contribution to intrusive image salience.

Observation: Emotional intensity of intrusions ↓; frequency & explicit memory unchanged.

rTMS Visual Cortex Reconsolidation

🔗 PMC8754386

2. Traumatic Stress Alters Visual Reactivity ▼

Hypothesis: Acute trauma perturbs basic visual-cortex impulse responses that track intrusion symptoms.

Cause: Recent trauma exposure; checkerboard visual stimulation during fMRI.

Effect: Visual sensory reactivity/connectivity shifts underpin later intrusive symptoms.

Observation: Visual-cortex reactivity associates with PTSD (especially intrusion) symptoms; altered visuo-sensorimotor connectivity.

fMRI Visual Reactivity

🔗 Nature (2025)

3. Intrusive Memories: fMRI Study ▼

Hypothesis: Encoding in amygdala & ventral occipital cortex predicts which moments become intrusive.

Cause: Trauma-film encoding during fMRI.

Effect: Stronger amygdala–visual encoding → more intrusions.

Observation: Higher amygdala & ventral occipital activity at encoding predicted later intrusive memories.

fMRI Amygdala Encoding

🔗 PLOS ONE

4. Neural Basis of Involuntary Recall ▼

Hypothesis: Specific encoding patterns in visual–limbic circuits determine involuntary trauma imagery.

Cause: Trauma-film task with later intrusion tracking.

Effect: Identify visual–limbic signatures that drive involuntary recall.

Observation: Encoding activity patterns in occipito-limbic circuits predicted later intrusions/recall.

fMRI Encoding Limbic

🔗 Psych Med

5. Propranolol & PTSD Symptoms (RCT) ▼

Hypothesis: β-adrenergic blockade during reactivation disrupts reconsolidation, weakening trauma memory affect.

Cause: Oral propranolol before weekly trauma-memory reactivation sessions.

Effect: Noradrenergic dampening of restabilization → symptom reduction.

Observation: Greater PTSD symptom reductions vs placebo; supports reconsolidation-blockade approach.

Propranolol Reconsolidation

🔗 PubMed

6. Propranolol in Chronic PTSD (DB-RCT) ▼

Hypothesis: Same as above; test efficacy in chronic PTSD.

Cause: Reactivation + propranolol vs placebo (6 sessions).

Effect: Attenuate emotional weight of memory.

Observation: Both improved; no overall drug–placebo difference; signal in most-severe subgroup.

Propranolol Chronic PTSD

🔗 Nature

7. NEJM Prazosin Trial in Veterans ▼

Hypothesis: α1-blockade during sleep reduces adrenergic drive → fewer nightmares & symptoms.

Cause: Nightly prazosin vs placebo (26 weeks).

Effect: Lower central NE tone during REM/sleep.

Observation: No benefit vs placebo on nightmares, sleep, or global PTSD.

Prazosin Veterans

🔗 NEJM

8. Single IV Ketamine (JAMA Psychiatry) ▼

Hypothesis: NMDA antagonism acutely boosts plasticity to downshift pathological memory traces.

Cause: Single sub-anesthetic ketamine infusion vs midazolam.

Effect: Rapid plasticity → fast symptom relief.

Observation: Rapid PTSD symptom reduction (24h–1wk) vs control.

Ketamine NMDA

🔗 JAMA Psychiatry

9. Repeated Ketamine Infusions (AJP) ▼

Hypothesis: Repeated NMDA modulation yields more durable remapping of threat circuits.

Cause: 6 ketamine infusions (2 wks) vs midazolam.

Effect: Strengthen extinction/modify memory networks.

Observation: Significant PTSD severity reduction; first RCT showing efficacy in chronic PTSD.

Ketamine Repeated Chronic PTSD

🔗 PubMed

10. l-DOPA After Extinction (Women with PTSD) ▼

Hypothesis: Dopamine boost post-extinction strengthens safety memory to prevent return of fear.

Cause: l-DOPA/carbidopa immediately after extinction (fMRI).

Effect: Enhance consolidation of extinction (“remap” threat→safety).

Observation: Reduced reinstatement/return of fear; amygdala patterns support extinction memory.

l-DOPA Dopamine Extinction

🔗 PMC

11. MDMA Therapy & Brain Activity (fMRI) ▼

Hypothesis: MDMA-AT retunes brain networks during trauma recall, lowering visual-imagery contrast.

Cause: Active MDMA sessions within a Phase-2 protocol (pre/post fMRI).

Effect: Increase adaptive FC; dampen amygdala–insula coupling; modulate visual areas.

Observation: ↓ amygdala–insula FC; reduced cuneus contrast; trend ↑ amygdala–hippocampus RSFC.

MDMA fMRI Therapy

🔗 PMC

12. Phase-3 MDMA-AT RCTs (Nature Medicine) ▼

Hypothesis: MDMA fosters fear extinction & reconsolidation updating via neurochemical surge.

Cause: MDMA vs inactive placebo alongside fixed therapy protocol.

Effect: Reopen plasticity; enable trauma-memory “remapping”.

Observation: Large symptom reductions; many no longer met PTSD criteria.

MDMA Therapy Phase-3 RCT

🔗 PubMed 33972795 / 37709999

This is an ongoing research indulgence, a topic very close to my heart. ❤️

Remembering the Past - Photographic Neuro-Therapy

How about some examples from this past week. Generally these are simple captures of points in time, however these are linked to specific time periods of my life when PTSD events occurred. When I see them there is a flood of emotion and physical response: elevated heart rate, deep intake followed by shallow rapid breathing, the echoing surge of norepinephrine from fight or flight response, and inevitable accompanying psychological aversion. These are the effects to be remapped, the process of meditation and cognition-alteration with which to be engaged.

Considerations of Creative-Emotive Outlets

I used to love painting, and perhaps if there were more space for all of my many projects then I would try to get back into the process. Creativity and artistic expression are relaxing and healing; it’s true. Looking back, my last one was a 6’x4’ canvas in acrylics, which I had finished for a contract-design.

After the “assault by gunpoint incident” I simply could not hold a brush, could no longer see the future of the paints upon the canvas, no longer imagine beautiful images finding their way from mind-to-hands. Creativity in that manner simply ceased, and I’ve not been able to resume. Having to stop was like losing part of my identity, connection to passion, vibrancy.

Coming to Terms with Physical Scars

Circa a few years after the coma, we see those two scars which never heal. Sometimes I put concealer on them, sometimes I lose interest in covering them for the sake of the visual public. I’ve written so much about this already, there nothing much new to say right now. I returned, and I live with that fact — feeling every moment.

Early Life and Times in a San Francisco Career

The innocent early years in SF, commonly engaged in expressions of “overly formal” attire for the west coast tech industry. Those occurred at the same time as the gun violence, domestic violence, and desperation-inducing medical trauma. So, how does one already trauma-laden young woman cope with more, while attempting to climb the corporate ladder? Any way she can, an escape artist, international travel, constantly moving, preferring to replace the pain with newness and knowledge.

Coping with a Returning To American Life

There is only so much to say about my most recent return to the USA, moving back to take a mostly-dream job running a hardware research lab. This photo was taken during the initial months when my PRL level began to skyrocket off the reference range; that growing trendline on the many successive blood tests proving tumor growth on the Anterior Pituitary Gland; the Suprasellar-Fossa Meningioma and its migraine inducing Optic Chiasm concerns would arise some years later.

The anterior pituitary secretes a number of peptide and glycoprotein hormones that regulate various cellular processes including growth, metabolism, reproduction, and response to stress or trauma. The hypothalamus regulates the anterior pituitary via secreting “releasing hormones”, somatostatin and dopamine.

The physicians in America ignored my concerns, ignored the labs, ignored everything about this brain tumor for FIVE YEARS until an eventual MRI was ordered. Memories from those five years are extraordinarily difficult to remap, part of an ongoing source of simmering rage underscoring every medical encounter with that health organization. The pituitary tumor was only one marker in a complex set of endocrine system dysfunctions. Regulating its effects in the early stages would have prevented a chain of events from which my body will never return to baseline.

So much physical pain, emotional suffering, and secondary orders of impact could have been prevented if only they had listened (if only anyone had listened) to this one woman’s reproductive system concerns. The medical industry doesn’t care about women - we’re not often profitable enough. Now eight years later, symptom remission requires a forever-expensive and stressful managed condition, but at least thus far I’ve avoided invasive brain surgery.

Parting Thoughts for Project Restoration

The past is not so easily escaped, nor resolved, or often acknowledged — and so it may never heal. However, with sufficient care perhaps these memories may be laid to rest, if not remapped by way of modern self-administered neuroscience miracles. ❤️

Let’s inspect one of my favorites lately, Qwen3-235B. This is not a model that one commonly sees running outside of large compute clusters and supercomputers, because the 235 billion parameters require substantially more resources than most infrastructures have available. Often when we see Qwen3 in-use on not-supercomputers, it’s the 32B variant, which can run well enough on a 16GB+ vRAM capable GPU. Querying the models on Huggingface and one will see there are 32B on the low-side all the way to 480B for the supercomputers and research clusters, and many customized ones built from the originals.

Parameter quantity aside, as we’re not focused on that at the moment, let’s look at the primary high-level differences, as well as low-level technical differences, between LLM variants like “Coder”, “Thinking”, “Instruct”. Over at the Cerebras Inference Cloud we can use the following types.

High Level Differences

• Base Model: Generalist, no task specialization.
• Coder: Focuses on programming efficiency (e.g., auto-completion, error fixing).
• Instruct: Prioritizes user safety and conversational alignment (e.g., chatbots).
• Thinking: Targets structured reasoning (e.g., math proofs, logical puzzles).

Low Level Differences

• Tokenizer: Coder extends vocabulary for code symbols (e.g., def, ->), while others reuse the base tokenizer.
• Fine-Tuning: Instruct uses RLHF for alignment; Thinking uses process-based rewards for intermediate steps.
• Decoding: Thinking enforces iterative step generation via modified KV-cache management, unlike autoregressive defaults.
• Loss Functions: Coder weights syntax validity; Thinking penalizes incorrect reasoning paths early.

Use Case Mapping

• Need code generation? → Coder
• Building a chatbot? → Instruct
• Solving multi-step problems? → Thinking
• Researching foundational capabilities? → Base

Visualizing Decisions via Flowchart

Visualizes the evolution from base model to specialized variants, emphasizing technical divergence points, which you can see in the live rendering panel over at Mermaid.Live

graph TD
    A[Qwen3-235B Base Model] -->|Trained on general web text| B[Qwen3-235B]
    A -->|+ Code corpus & tokenizer extension| C[Qwen3-235B-Coder]
    A -->|+ SFT/RLHF on instructions| D[Qwen3-235B-Instruct]
    A -->|+ Reasoning datasets & iterative decoding| E[Qwen3-235B-Thinking]

    B --> B1["Standard cross-entropy loss\nNeutral inference"]
    C --> C1["Code-specific tokens\nSyntax-aware embeddings"]
    D --> D1["RLHF alignment\nSafety filters"]
    E --> E1["Reasoning head\nStep-by-step CoT output"]

    classDef base fill:#e6f7ff,stroke:#1890ff;
    classDef variant fill:#f6ffed,stroke:#52c41a;
    class A,B base;
    class C,D,E variant;

What is LoRA and why is it not LoRaWAN?

It’s an acronym for “Low Rank Adaptation”, which is an optimization method for LLMs that can dramatically reduce resource requirements while optimizing for post-training re-trains.

• Neural Nets: LoRA: Low-Rank Adaptation of Large Language Models
• WAN Nets: LoRaWAN is a Low Power, Wide Area (LPWA)

What is Auto-Round and why should we care?

Another neural-network optimization tool, specifically for quantizing large language models into “still large but optimized for specific precision”. Intel released a Q4KS quantized version of the GPT-OSS-20B model on Huggingface for those who want a high-performance model on lower resource hardware.

• This algorithm helps engineers run models originally intended for Very Large Systems With Lots of VRAM to run on lower-spec systems which are often optimized on Tokens/sec per Watt (Tk/s/W).
• Additionally, it allows models which are expected to run on Nvidia GPUs to run on alternate hardware (CPU, HPU, etc), multiple calibration datasets, mixed-bit Quantizing, etc.
• Reference: Intel Auto-Round Quantizer

64GB vRAM GPUs vs Cerebras Cloud

The new big news this week has been OpenAi’s release of two OSS models, GPT-OSS-20B and GPT-OSS-120B, which are quite exciting for technical reasons which I won’t go into right now.

So, a quick comparison with running GPT-OSS-20B on a local-at-home GPU host vs the inference cloud at work - where we’re running the GPT-OSS-120B variant of the model (feel free to try that here: https://cloud.cerebras.ai)

First, a screenshot of the local system running Open-WebUI with Ollama backend. See the hover-box for the tokens/sec performance values.

Token results for GPT-OSS-20B running on a 64GB vRAM local@home system

And then we see the tokens per second for the Cerebras cluster, running GPT-OSS-120B variant of the model, which is executing on millions of cores for the cluster and multi-TB of vRAM (equivalent terms).

Token results for GPT-OSS-120B running on the public Cerebras cluster

Using the same prompt query we have token rates for the local development system:

Big numbers! 😃

Cellular Echoes, a Multi-generational Legacy of DES

Having touched on this in the first post, this section is intended as a refresher. Partially this is intended for raising awareness to a problem which affects millions of people born during the 1950s - 1980s, when DES was administered to pregnant women via medically good-intentions but without awareness to its long-term effects on the mother, children, grandchildren.

Diethylstilbestrol (DES), a carcinogenic endocrine disruptor, has multi-generational adverse effects through disruptions to the neuro-endocrine system and DNA mutations impacting cellular and hormonal development. These mutations can manifest as cancers, metabolic disorders, reproductive dysfunction, chromosomal abnormalities, and chronic neurological conditions (migraines, tumors, lesions, dysautonomia).

This genetic legacy is a backdrop upon which my life was built, which resulted in innumerable divergences of a normal-healthy path, from fulfilling desired physical expectations, procreation, and so much more.

A Reset to The Rules of Engagement

Memory is a skill we easily take for granted, often assuming it accurately captures reality as it unfolds. We’re taught that our experience of the present occurs in real-time, yet in reality, there is a slight delay—signals must first travel through the nervous system and undergo processing before being encoded as memories within the brain’s dura mater. Memory is the brain’s intricate mechanism for translating sensory input into meaningful emotional and behavioral responses, shaping our understanding of both internal and external worlds.

This complex neurological system depends heavily on balanced neurotransmitter function to accurately encode experiences and guide our daily lives. Severe trauma, as seen in PTSD, profoundly disrupts this delicate neural language, permanently altering pathways—especially dopaminergic circuits—that influence emotion, cognition, and behavior. Once formed, these trauma-induced changes can become deeply ingrained, often irreversibly affecting one’s neurological landscape. Coping with severe PTSD thus requires lifelong adaptation, reinforcement of coping strategies, and an ongoing, difficult journey toward acceptance.

Fragmentation of memory can be understood as a memory disorder that includes subjective and phenomenonological facets directly impacting the ability of an individual to recall memories in an integrated and holistic way.

In my seventeenth year I would drive to SF at night to take photos before dawn. Over the years this favorite city of mine became a source of severe and lasting trauma.

The impaired person usually suffers from physical damage to the hippocampus. This may be due to the result of trauma, such as post-traumatic stress disorder… consequences, such as oversensitivity to some stimuli, impulsiveness, lack of direction in life, impacts to existential awareness, emotional dissociation, and often a distorted perception of oneself… requiring the patient to mask their concerns and despair.

Together We Drifted Toward The Void

Eventually, the lifeboat fell apart — the house of cards collapsed. Across the eras of a beautiful yet fractured life, layers of trauma accumulated, intertwining at the point of my near demise, when in the same year I lost my twin. We had endured those early years closely together, though our paths were not always aligned or identical. By this point, the cumulative losses had become immeasurable and insurmountable.

We experienced diametrically-opposed impacts from DES exposure, chromosomal deficiencies echoed in reverse, genomic sequencing showing the maps and flags and arrows all pointing to the wrath of diethylstilbestrol. Everyone has their limits, and we knew so very well where the next decade or two would go, the advanced treatment path involved; the trajectory was bleak and disheartening. Some may judge one’s rational, data-driven decisions, fully respective of life experiences, to be inherently irrational in their moral views. Many people since have levied their opinions, but they were never forced to walk this path.

A Life Without a Mirror

Consistent with the existentially spiteful patterns of non-consensual trauma upon my body, the EMT tasked with saving my life had slit my throat open length-wise, rapidly and jaggedly in an emergent (ie absolute emergency) airway incision. This severed half of my vocal chords, permanently paralyzing that amount of vocal functionality. My brain was already off-line, in global ischemic state, lights out. There was no pain, there was nothing. I was gone.

Memories are mostly lacking from that month, though photographic timestamps provide one view, a phone held while walking, a mistaken shutter press. The askew pupils indicate a rare and severe side effect, the result of ongoing treatment having been fully insufficient. Once more, healthcare providers had failed in their long-term care. After this, nothingness.

unplanned, unexpected, the last photographic memory

Body moved to the ER, the OR, the ICU. A second, larger, circular incision was made in my throat, the first haphazardly sewn closed in zig-zagged scars. My limp unconscious form was hooked up to life support machines. Days passed, a week, then more. Slowly, neural matrices enervated the consciousness to reboot, to resume an awareness of our shared reality.

A pinhole of photons appeared, and from the vast darkness every cell was screaming, oxygen and a feeding tube through the stoma hole in my neck, rhythmic pulsing-machine breathing for me, the only solace a button taped next to my hand for morphine - “press to release”, into the IV line. Apparently I was alive.

The pinhole of light widened, forcing outward the timeless nothingness, replaced by pure all encompassing light, then shades of grey, then shapes, without concept of meaning or definitions.

“Life will only be more difficult now.”

One result of the coma was that broad sections of life, of memories, events and persons, places, experiences.. were simply gone. The variously affected zones and thalamus projections, and some functions of the posterior parietal cortex, they simply did not wake up with the rest of my brain.

I will never remember all of the memories which I have lost.

With those vacant memories, gone too were my former abilities of speech, the ability to walk, to hold a cup, to feel emotions, to focus further than the end of the bed in the ICU, to understand the passage of time. So much was lost.

looking upwards, on an IV drip or two or three

“She may never be able to speak, to walk, or leave the hospital, if she wakes up at all.” - Neurologists, Attending to the ICU

As it turns out, the experience of Global Cerebral Ischemia induces substantial changes - that special “off switch” called “no more oxygen today”. Global Brain Suffocation. Flatline waves. No respiration. System Shutdown. Those scars on my neck - from the respirator stoma and the EMT’s emergency attempted endo-tracheal intubation - they are still present and in the mirror every day. Every morning upon waking, the scars are there, a forever reminder of the Void, the Loss.

Eventually I did relearn how to walk, to speak, to conceptualize the passage of time, and how to exist without those old blocks of memories weighing me down. I learned how to confront what remained, which helped with working through the newly faced medical trauma from the events of the ICU and temporary non-existence.

How did my brain wake up at all? No one had answers. Years later, periodically asking new neurologists, still no one knows. Since waking up, it has never been easy.

When Trauma is linked to Identity

The Self, one’s internal identity, with its link to the past, images of the memories, the joyful moments mixed in with all of those years of pain. It’s a jumble of words and phrases after a while, meaningless. How can one move on when they are no longer fighting an internal struggle against their past? It would seem simple, easy. Perhaps so. Perhaps the temporal lobes, with their functionality and dysfunctionality which results from PTSD, would benefit from additional research; this is my course of action, to reprogram the reactions, reprogram the responses, and to heal the mind and body via positive feedback loops.

a lovely animated gif of the brain’s Frontal Lobe, left cerebral hemisphere

On Consideration of Complexity, Treatment Modality

Neurology is a complex subject. Emotional intelligence and the cognitive underpinnings of its origins and capabilities, these are a complex area of study. The simplest description of the science which describes the manner in which the human brain gathers, processes, stores, and recalls memories is also a complex subject. So much complexity, how to make sense of it all?

Conceptualizing one’s existence after waking up from an event where death was assured, had your throat sliced open with a scalpel, connected to machines to keep your offline brain oxygenated, and then eventually to reintegrate into society’s fabric of shared existence — after returning from the Void of endless nothingness — that is a Complex Circumstance, one which requires a combination of neurological, psychological, and philosophical continuity of care. In America we do not have that as an option, not on any regular insurance plan, the patient must fend for and advocate for themselves.

What then are the options? Is ‘dopamine agonist’ based therapy the only choice? Certain not. It won’t even be recommended by a therapist because it would require enrolling in human trials for the subject, and that’s often far too involved or often unavailable for many patients.

So, one may read this and think and inquire..

“Surely this is a bit extreme, unproven?”, while others have inquired, “why not try the research methods for MDMA, Ketamine, Lysergic Ergolines, or A or B or C or another instead?” Or what about DBT or CBT or EMDR?

Sure, sure. Perhaps in the literal words of one truly genius level therapist..

“How about instead of taking ${critical medication}, you just imagined what it would be like to have these therapy sessions while taking the medication, you know - without taking it?”

The answer to all of these queries is that I have been through every possible and available treatment pathway over the past decade and more. Some have been life changing and positive and beautiful, others less useful, some fully a waste of time. Some therapists have caused additional pain with victim blaming, tearing holes into the tattered fabric being repaired, those horribly malicious people — they do exist, and that in itself is a depressing fact for people seeking care.

Visual Remembrances and Photography as Healing

One of the methods which I’ve found most useful, lasting, and capable of more than words may define, is to repair these old images. Not in an “exposure therapy” manner, but in a restoration of the mind’s emotional response to their evoked memories.

For those who have not immersed themselves into the study of cognitive neuroscience, or found solace in the philosophy of causal-determinism, the concepts around neural-programming may sound like science fiction. Fortunately, our current era of medical science offers the fiction of fifty years ago as an experienced reality - right now, today.

This method involves taking a prescribed ‘dopamine agonist’ medication, which causes the brain to activate dopamine receptors throughout many critical pathways. Once the medication reaches a necessary level, then my gaze is returned to the those slides. Hours will be spent digitizing, processing the images for color correction, repairing film damage spots, and normalizing the ICC profile, normalizing levels, adjusting histograms via curves.

dopamine, the first of the three catecholamines

Human trials for this method are not common. There is no profit to be made by the pharmaceutical companies with drugs which have existed for decades, using personalized treatment which varies by individual (and is therefore difficult to quantify without substantial similarities between patients - and I am not a common patient).

For those curious, I’ve included various embedded links within this document, but here are some additional readings which may offer insight.

• The mesoaccumbens dopamine in coping with stress
• Dopamine D2/D3 receptor agonists attenuate PTSD-like symptoms
• The hypothalamic-pituitary-adrenal axis in PTSD: Pathophysiology and treatment interventions
• Limbic response to stress linking life trauma and hypothalamus-pituitary-adrenal axis function

Why are we talking about the “hypothalamic–pituitary–adrenal (HPA) axis”? Because the Hypothalamus controls Dopaminergic activity, and the Pituitary gland (which controls hormone secretions) is deeply affected by Dopamine levels rising or falling.

In this meditative mode of visual analysis, amidst silent revisitation of trauma-informed responses, my intentional flow of thoughts attempt to concurrently apply a revised emotional mapping to the associative matrices within; to reprogram the damaged links via new dopaminergic pathway etchings - made possible by the cognitive intensity of this combination of meditation and medication.

It feels like removing rust from a long treasured heirloom, to see the glint of its origin material, its remuneration now complete.

Eva preparing for neural-programming — a self-photo facilitates awareness of Dopamine levels - visually represented as “Dopaminergic Flush”, a stateful readiness for successful treatment

The Great Reprogramming of Dopaminergic Pathways

The mechanism of action involved with this medication facilitates the process of creating new neural connections, by linking sensory data from visual information processing circuity to the emotional response relationships involved with memory recall; all of this occurring via complex actions of the brain’s dopaminergic pathways.

During this treatment process my thoughts wander and I don’t push back, just let the feelings occur and move forward. It’s a form of Zen in some ways, letting the emotions exist without holding on, without “desiring a lack of desire”.

Time and distance is required for reprogramming the mind’s emotional recall, for forgiveness. The process is possibly never complete, but it’s a beautiful experience to find oneself on the other side, able to look backward and see the beautiful ways that once were.

I see those youthful eyes, consistent across each image, reminders every time. The earlier years retained an innocence about them, harboring damage too deep to acknowledge, express, or let forth. Now those moments can be set to rest, and in whatever way it may heal, it offers solace.

eyes reflect with a minor smirk, thrust into the present from so many years passed

Carrying around my father’s old Pentax ME Super 35mm film camera (digital did not yet exist), I would learn the ways and means of translating one’s vibrant sensory world of tangible, visible, and audible queues into a reflexive snapshot of a single ellipses of time.

Film photography platform of my youth, the glorious Pentax ME Super

The science of film, its correctness of inter-related momentary ordinals, exists as a knowable object in its own right; defined by functions which can be modeled, simulated, and counter-adjusted according to objectively determined interlocked sliding scales of equilibrium equations… the science of light was logical, beautiful.

The spatial-dimensional complex of neurons and axons within my young mind was growing rapidly, desperate for knowledge, experience, adventure. So much of that mindset was searching for answers, finding beauty along the way, often in spite of the many stumbles and tragedies intertwined.

On Genetic Inheritance and Endocrine Disrupters

Looking back on those years, I see patterns arise, ones which describe the ensuing years in predictable ways, in their benefits and concerns equally mixed. I was not a canonically ’troubled youth’, rather my troubles were genetic in origin — now identified as ‘Generational DES Syndrome’.

[*] DES = Diethylstilbestrol is a carcinogenic, xenoestrogen, ATPase inhibitor, endocrine disruptor. Linked to a variety of long-term adverse effects in women who were treated with it during pregnancy, and in their offspring, and further affecting the F2 generation of grandchildren.

In simple terms, this causes DNA mutations which are carried forth into systemic neuro-endocrine development, cellular expressions both causative and compounding, as the body develops into adulthood. Whether these cellular mutations result in cancer, neoplasms, meningiomas, metabolic dysregulation, sex and growth hormone disruption, reproductive sterility, chromosomal defects, or combinations of those and other grievous maladies, the possible impacts are vast in quantity and scale — and still being studied.

Some patients lead generally normal lives, ignorant of the cause for their condition, while others experience an unnecessarily early death. In-between these extremes my life has coalesced, wavering between periods of intensely healthy highly-competitive endurance athleticism to months of debilitation from chronic nervous system collapse. Some of my most memorable resting moments were the cumulative hours knocked-out from exhaustion and asleep inside the cold, dark, rhythmic magnetic thumping of a MRI tube, or the pulsing energy waves inside occasionally very warm CT scanners.

DES has disruptive effects which exert negative feedback on the hypothalamic–pituitary–gonadal axis (HPG axis), suppresses the secretion of the gonadotropins, luteinizing hormone (LH) and follicle-stimulating hormone (FSH), and suppresses sex hormone production as well as gamete production and maturation.

Looking back on DES and its impacts within my genetic programming, I can see where it derailed an otherwise normal childhood, where it imparted physical and existential questions for which no adult or physicians ever had answers, and how those early years drove me further into an adulthood focused on amassing knowledge of systems theory, neurology, endocrinology, genetics, biochemistry, and decades of exploration into modulating the steroidogenesis process occurring within these veins.

Coincidentally, I would later learn that endocrine specific cancers were rampant in my mother’s side of the family - likely also from intergenerational DES effects. Over the many years, my endocrine’s HPG-axis would crash in more than one dimension via multi-glandular failures, a pituitary hypophysis neoplasia diagnosis would arise, diagnostic concerns into suprasellar meningioma, and eventually the cumulative effects would lead to the conditions which resulted in my near-death and coma.

Youthful Adventures, Expansive Landscapes

Scaping together enough for a second-hand Manfrotto tripod and lenses for a near-mint Nikon FE2 - the camera I received from my father for one birthday so long ago, that period was when my heart fell in love with the beauty of capturing moments in time. Youthful innocence was at a peak, everywhere held introspective beauty in some manner - if it was framed subjectively well and maintained The Rules.

rain arrives along the Western Slope of the Rockies

Then there was the glorious selection of film: the richness of Velvia 50 - perfect for landscapes but too rich for portraits, the ever-so-accurate Provia 100, the old classic Kodachrome 64, occasionally the normality of Ektar 100, and on occasion spending time without color at all - but oh let me show you Agfa’s superpanchromatic Scala 200, the most uncommon of them all.

I loved this era of film for its uniqueness, it’s vivid ability to capture reality in a way that was lacking in prior decades - eras of advancements in technology which defined the ability for people to capture the present tense and carry it into the future, with accuracy, realness, and tangibility that we will never have with today’s digital options.

the slide films of my youth, vivid colors, rich contrast, a life before the digital world

I loved this era of film for its uniqueness, it’s vivid ability to capture reality in a way that was lacking in prior decades - eras of advancements in technology which defined the ability for people to capture the present tense and carry it into the future, with accuracy, realness, and tangibility that we will never have with today’s digital options.

As with everything immersion worthy, I studied photography via encyclopaedias, library books, documentaries, and by asking a thousand questions. Who best to answer but Elke, the co-owner and an early role model at my local professional photography shop; one which housed an amazing collection of vintage cameras and lenses - many that I would imagine forever out of reach: Leica, Hasselblad, Rolleiflex, Zeiss.

My perspective in those times demanded that the best memories surely must be captured, regardless that slide film was expensive. Each shot was a cherished and planned capture, yet still one were lucky to have 2-3 usable results per roll of 24-36. Fantastisch. I loved every minute of the process.

Of Landscapes and Studio Lights

These slides became a timeline, closely selected and optimized photos of my adventures, my travels: the tragedy of storms and the silent motions of rain, landscapes and sunrises and sunsets, mountains especially loved and well traveled. Of peaks climbed, valleys explored, off-trail backcountry wanderings alone in the autumn, and cold snowshoeing adventures with Vati too.

Then the studio. Learning about black and white film, darkroom techniques, rear-projection lights, soft-bounce filters, shade-booms, and multi-flash timers connected to a remote shutter that I could hold in one hand - the original selfie method, before the term was ever coined. These self portraitures were mostly a private occurrence, an experiment to record an ever-changing existence which often felt unknowable and painfully everlasting, other times its opposite.

long adrift in lostness, many found in my eyes precisely who they wanted to see

Conceptualization of Self

In some ways it was photography which helped me work through the DES-affected hormonal years of explosive emotions: the Conceptualization of Self as an evolving modality. How could one build a schema involving periodic memory without tracking the memories? And what better way to have reference to those than with film?

So, along with landscapes I captured my visage; an evolving physical form of perpetual wonderment and wandering cognition, deeply felt emotions, all wrapped up into a warm body with occasionally ice-cold blue eyes - constantly changing and growing through the years.

a single spoken “please”, but no one was truly listening

From the Outside Life Was Wonderful

Unfortunately along the way there were events of intense and prolonged trauma which led to a deeply felt hatred for nearly the entire era of youthful memories - not for what the photos were, not for who I was, but for the memory’s visual associations with the events of the era in which the traumas occurred.

I had no ability to heal from the events at that time, and so to my young mind those events simply could not exist, lest it were to be that I did not exist. It was one or the other: acknowledge the trauma for what it was, how it had shaped me, and chose to suffer the wrath of my own willing hands. Or instead, I would rather to erase all of it. Erase the moments from my mind and never think of them or refer to them or believe that they were real; to erase part of my experience with life. Years later that wish would be granted, an outcome in ways impossibly unexpected.

Existentially, it was a challenging duality. So the slide portfolio was put aside, boxed up, never taken out to review or inspect or share, and only occasionally forcefully ignored whenever asked about the subjects. The memories did not exist. The cognitive methods I learned became a hardened, steadfast technique, an emotional control unrelenting, and it lasted decades. No one knew anything, and no one needed to. Those memories were only pain (but they were not, my youth held so many beautiful moments, ones which I would only connect with decades later).

Outward Success Surely Heals Old Wounds

Years passed and milestones occurred, much as the loved ones around me had long expected. A standard life evolved. Marriage, a home, thoughts on pregnancy, depression, elation, stress, travel, and promotions, and everything being pretty good on the surface.

A blink of the eyes and there I am again: Bare. Lost. Alone. In the pure Darkness.

Yet family was there, friends were there, all of the markers of success and happiness were there. Regardless, trauma events from years ago were invalidating the potential for happiness in ways unknowable to the loved ones around me. No one could ever know. The memories could not exist, or I would carry them to my grave.

years so often idyllic, if not for the unspoken undercurrent

Concurrently, an undercurrent of escapism, a subtext to the patterns of wants and needs, this was all despite the abundance, and it was that undercurrent which became a rushing and inescapably deep tide. The memories become an unwanted passenger, a little non-angel perched on the shoulder - whispering reminders in the most inopportune times. A foil to the good times, intertwining themselves deeper, demanding either solace and release or self-destruction.

Trauma at the clinical level, the kind which arises from unspeakable events in youth, or wartime combat, or being assaulted at gunpoint and left stripped and alone in the pure darkness of 18th & Florida St at 3am; those somatosensory memories become etched in the mind. Maybe more than one event is etched, maybe there’s too many to describe.

Bleeding out in a sodium-halide bright white tile-floored bathroom, a stainless steel drain on the floor in the middle where the redness of life circles and downward flows. You slip in the blood, bare-footed, abdomen held in one hand, reaching-grasping with the other, screaming voicelessly in full-system shock.

One cannot escape the loop. Is it truly Sisyphean if the endless hill is worn flat, the endured evolved into appreciation for its challenge? The illusion then shows its edge, beautiful, glinting reflections from facets ever-changing, never-ending.

Another World, Another Time, in the Age of Wonder..

The mind loves to travel through time these days; reflecting upon the trajectory, occasionally in weariness of wonder that life has become its inevitability - the duality from which I could never grasp in so many years passed. The sunsets in those days felt brighter, more luminous, unfiltered by the long-evolving tumor’s stranglehold on the Optic Chiasm - our eye’s connection to the brain.

a waning dusk arrives somewhere near Lake Berryessa, Napa County CA

When single shines the triple sun, What was sundered and undone, Shall be whole, the two made one..

Where then, in the latter half of 2022 at the start of treatment? Seemingly perpetually resting in bed, dealing with first and second order side effects from a barrage of eight medications, either targeting the tumor or attempting to shore-up defenses from those side effects. Rapidly, one loses patience and interest in rest.

endless recovery in 2022, photo from my former Twitter account

How about in 2017? Fiji island hopping, searching for demise or salvation, whichever may come first.

another round of “Escape to Fiji”, impromptu rejections of corporate life requirements

Months later? Where else but Nicoya, Costa Rica seeking refuge from those internal storms. I still have that pseudo-military ripstop hat, or rather am on iteration four or five of the same design - very good for napping at airport terminals, or knocking out at the beach.

Playa Langosta Sur, accessibly only during low tide, don’t overstay the waves!

Or decades ago, seasons ago, seeking solace among the silence of snowy peaks alone. When prompted for “where do you want to go to college?”, nowhere, I wanted to go to Talkeetna, Alaska and be in the mountains. My best friend died that November, and everything changed.

what all is there to say about one’s University years, it was a complex time

All of those years, the endless dreams, and seemingly endless sunrises… the recording of those events into neural maps, shuffled off from primary storage over the decades until some periodic recall request.. affected then by environmental factors, by potential cerebral injury, perhaps menopausal hormone shifts.

Is our memory illusory? Are the vector maps of neurotransmitter mixtures changing over time? Yes they are. Still yet, we have no magnetic tapes at Iron Mountain which could store them all, and we have no set method to statically write them to anything other than occasional video or foto medium - film or digital - even the method may shift the impression and the recall.

Perhaps that malleability of memory, its neural alterations inevitable, is the most beautiful quality which growing older finally affords. ❤️

Footnotes and References

[1] ‘The Valley’, in reference to Silicon Valley, the standard California epicenter of the tech-sector.

How about the ways in which The World Bank’s usage of Ai and LLMs have helped scientists understand populations at risk, how to analyze massive datasets to respond to climate catastrophes, and how to accurately predict global infrastructure changes before they occur?

Well… it’s our lucky day!

The World Bank regularly posts Jupyter notebooks, LLM tooling, data-sets, data analytics scripts, global dashboards related to climate sciences, infrastructure, poverty assessment, economic awareness modeling, and so much more… right over here on their GitHub page: github.com/orgs/worl…

One item recently in the FOSS news was this gem, the Metadata Editor.

• Project: worldbank.github.io/metadata-…
• Source: github.com/worldbank…
• Schemas: worldbank.github.io/metadata-…

Oh but there’s also some fun with NASA!

• worldbank.github.io/blackmarb…

BlackMarblePy is a Python package that provides a simple way to use nighttime lights data from NASA’s Black Marble project. Black Marble is a NASA Earth Science Data Systems (ESDS) project that provides a product suite of daily, monthly and yearly global nighttime lights.

This is a heartening example of the beauty and benefits which Open Source Software offer to our world.

#science #finance #worldbank #foss #oss #llms #ai #programming #engineering #nasa

In association with the country itself, the bills are very pretty, colorfully fun, and durably resistant to humidity and water damage — useful for hiking through cloud and rain forests, diving at a local reef, or being caught out in a multi hour downpour.

For unknown reasons I left these bills inside of the booklet’s secondary tab next to my passport, and now they’re going right back into the booklet for a future surprise, and certainly future use during the next visit.

How about some slow motion ocean waves? Sure. Later in the day, and on many days afterwards, it was a favorite local beach.

0:00

/0:10

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#travel #surprise #CostaRica

Countdown to being back in the Progressive stronghold of anti-decency, antisemitic political action groups, achievement penalties, social disincentivization, horrific levels of taxed wage theft, hardened-recidivist criminals held wholly unaccountable, land of the not-so-free California - the state I always want to leave and never want to return to. Round… 8? 6? I don’t even want to think about the number of times I’ve left and never wanted to return, but then had to return. At every opportunity to leave, I have left, and here - now - one year later - entirely because healthcare is expensive and life requires money, I’m going right the fuck back. This round, I give it 12-16 months, maybe.

However, and not in jest, nearly the entirety of my accomplishments could have occurred in an old military quonset hut located off-grid, deep in the vast stretches of the Northern Nevada desert, preferably near the Ruby Mountains.

The Ruby Mountains, Nevada. Rocky cliffs and vibrant wildflowers under a clear blue sky.

snow covered peaks of The Ruby Mountains, Nevada

So, goodbye to another location. I suppose that I could say that Chicago was beneficial in the larger sense of existential purposes, and that much was accomplished, but unfortunately that was not the case.

The relocation process was not originally planned for anything except a single move from California to Washington. In nearly equal parts this was for a change in medical care and for family proximity.

After an unexpected economic event occurred, partially a result of Washington state’s tragedy of a medical system — somehow more broken than in California, the sum of external forces imparted a requirement to take a very nice job offer in Chicago. Events occur, the new medical care is amazing and “omgosh this long period of intense treatment is coming to a close!” And then it did not, but was paused, resumed, paused, resumed again, and again, until eventually the prognosis evolved “medication resistant”. The endocrine and neuro-endocrine systems do not fare well to being bounce-tested every 3-6 months, eventually the systems revolt in their own manners and ways and means.

In the short run, we had comprehensive relocation covered from Washington state to a temporary corporate apartment in downtown Chicago for a month, then moved to a regular apartment on the waterfront for one month (unfortunately next to an eviction-tbd tenant who fights with the police when they arrive (which was every time that I had to call 911 between the hours of 0-3am)). This forced us to move to another floor in the building, incurring additional cost and then… let’s simply say, “Thanks 1000M!”.

No Stability, No Consistency, Chronic Sleep Deprivation

The Chicago winter is somewhat boring, cold, and tedious, though often very beautiful in the ways of winter storms and one of the largest bodies of fresh water in the world. Patience endures.

I love the winter, but generally that opinion is informed by my years of living in the high mountains, owning a lifted Jeep or busted-up vintage Range Rover, of waking up early, going backcountry skiing at the local pass, or cross-country at the local resort, or perhaps simply snowshoeing with my dogs - back when I had my dogs. When the cold is useful and fun, then I love the cold. Cold with nothing to do out in the cold is mostly a pretty view, but not-so-fun.. and not fun is simply Not Fun.

Also sleep; pretty nice to have a subsistence baseline, I’m not asking for 10hr nights or even 8hrs - as I usually subsist on 6hr/n endlessly. Reduce the 7-day cycle from 6hrs to 3-4hr and sleep deprivation kicks in after about three to four consecutive days, and then shit gets real fucked real fast - the bad kind of fucked. The kind of fucked that sends one to the ER, and I don’t like being in the ER, and I’ve been to the ER too much.

Just as we moved into the quiet apartment and life was able to start stabilizing, the [~~~redacted due to confidentiality clause~~~], went and got all sideways and screwed because non-disabled people (not me) are mostly assholes to disabled people (me). Fortunately, our startup is still doing well, has its runway, has its hardware, has its colo racks, has its distributed infrastructure, but unless there’s a new standard job then it’s time to move according to economic opportunity.

The original title to this post was, Things I’ve learned during the last interstate multi-timezone relocation [§]. So, let’s continue.

Some of the Things I’ve Learned from Constant Moving

Advice: don’t do that unless you have no other options. I did not have other options.

1. Verizon is an affront to all that is decent [*]. It’s never a good deal, never, ever, ever.
2. Corporate landlords are mostly horrible, often run by faceless drones without a soul.
3. The ADA will absolutely not protect disabled people regardless of legality of circumstance.
4. If you haven’t worn it in the past two years of seasonal weather, get rid of it, donate it.
5. A terrifyingly high percentage of American families are two steps away from potentially becoming homeless, often resulting from the national “Healthcare For Profit” industry.
6. The last year of experiences were not all negatives; there were many wonderful events and memories during the same period.

• [*] Goodbye phone number for the second time, goodbye Telegram login, goodbye SMS as 2FA, hello SIP “oh SMS outgoing compatibility? no not like that.”
• [§] This was the fifth relocation addresses in a 364 day period, across three states and two timezones.

In personable social terms, an immediate realization dawned upon landing, that so many people seem to love tall western women, to be quite vocal in appreciation and awareness, and what little Japanese I had memorized repeatedly informed to whom they were certainly referring. I’ve never felt tall until someone brings it up, but that all goes back to teenage years when plasma levels of recombinant-hGH were too low, then boosted too high. Short torso, long legs, and that’s just fine.

Those months that summer were memories of a pure, simple existence, the joy of living in a beautiful foreign land with a wonderfully kind culture; one where I could not read a single sign, nor understand more than several helpful conversational phrases. A stranger in a strange land. A summer of intense philosophical reassessment, of isolationist meditation, with the majority of months spent traveling alone through four countries across two hemispheres. Circa 2017 feels so far away.

circa 2017, during a global foray into personal unknowns, just as the tumor began to grow.

Perhaps more travel photos will follow. I’m in a reflective mood today. 🩷

#travel #photography #memories

zpool scrub cranking out 19.6G/s, with 2.74T scanned at approx 2min, with the pool predicting a total of 38min to complete

While building the spec and futzing with the BOM, one of my priorities was to ensure zero PCIe lane contention, with I/O going direct to 64 cores at 3.5GHz peaks, and eight memory channels in use (4x ECC-REG + 4x NVDIMM). All of those conditions have been benchmarking well so far; yay for meeting personally set expectations. 🤗

I’d say this is mostly pretty decent for a draid1 array with NVMe on a single-socket Xeon ICX box, and so far much better than the dual socket Ice Lake boxes that I was benching at ${OldOrg}. The recurring two-socket issue on this Xeon generation, and on its successor Sapphire Rapids, is that there’s too much cross-socket comms unless specific choices are made with PCIe peripherals and specific choices with BIOS tuning and kernel settings and core-pinning; all of which can be time consuming at a minimum, and head scratching with “Just call Premier Support!” at the far end, unless you know better.

This should not come as a surprise to anyone who has been benchmarking multi-socket Xeons ever since Xeons were brought into existence. Having had that experience, and because “data + facts + personal experience == real answers”, it was simple to predict performance concerns related to cross-socket latency, and don’t forget PCIe slot to socket sequencing and NUMA domain crossing, especially when optimizing for high-throughput network based storage transfers. If you scaled a 1 socket to 2 to 4 on the old Nehalem-EX based Xeons, then you know what I mean - they could never match the classic Big Iron vendors’ quad-socket designs like Sun’s SPARC T3 and M3 series, and certainly not competitive to IBM’s POWER7 options.

Anyway, there’s a little game to play in storage server land called, “high density rack-scale storage is more efficient with single socket boards, using a high-lane count, high-clock, big cache SKUs”. This isn’t the time for a lesson in predictive algorithms necessary for resource optimization, ones which should be used when determining cost/benefit analysis of horizontal vs vertical (or combined) storage system scaling at the rack-level; but it is time for me to get off of the computer and eat some cherries and watch one of the alternate endings for Cyberpunk 2077 Phantom Liberty!

And really, for a Sunday evening, remaining at this standing desk in the office-lab is not appealing, particularly due to the “it’s just too damn hot for pants!” environment, even with the A/C on full blast (common metric for this lab, though it’s fine weather for a skirt).

PS, the pool scub finished with zero errors. I am pleased. Migration complete.

#linux #zfs #xeon #intel #ibm #sunmicrosystems #storage #hardware #engineering #memories

A Tenuous Timeline

1) Some years prior to a decade ago, I joined LinkedIn, and a small handful of years ago I joined Twitter.

2) Along the way a serious incident occurred, resulting in PTSD from a bodily assault; the details of which require privacy. During associated therapy a HIPAA violation occured, eroding my trust in the medical establishment.

3) Periodically I would receive messages on LinkedIn from recruiters at the company where that man worked. I did not want to be reminded of the events, and would never work at the same company. These external intrusions into trauma memories were not healthy and they needed to stop.

4) Concerns evolved which necessitated telling that company to remove me from their recruiting database and never message me ever again.

5) The company removed my profile, and they asked if I wanted to be involved with an investigation, which I refused for the unfortunately common reasons:

• I did not want to relive events, especially after the HIPAA issue
• I did not want to discuss those memories with yet another stranger
• I did not want to become more of a target for speaking up

It’s a terrible catch-22, and yet it’s nothing new. This person needed to be prevented from ever contacting me or knowing anything about my life, requirements which the company could not ensure.

6) For safety reasons, I changed my legal name, then I moved, and started a new job. Then I enabled a service which monitors for identity theft issues and personal-info data leaks. Other precautions were made. The whole process is time consuming, emotionally disruptive, and fiscally burdensome.

7) Years pass. In the interim, LinkedIn’s “people you might know!” feature will routinely recommend that I connect with people who reminded me of that trauma.

• The feature cannot be disabled and profile settings do not help. Blocking people and profiles does not sufficiently help. Their algorithm always does this.

8) Years pass. Identity theft issues become a greater risk. Someone on Twitter steals my profile, impersonating me to sell web3 tokens or whatever. I report it, and Twitter demands my government ID - which I refuse to upload.

• Preferring a human interaction, I offer to bring my ID to the Twitter office and show it to someone in person, but no - they want the digital copy to keep on file, which will totally never be leaked in a data breach.
• I refuse to upload the document. They lock my account. I have not bothered since.

9) Years pass. A few weeks ago, I’m running a social media account audit and notice that LinkedIn has two unknown logins from another country - and I’ve never been there, nor connected to an ISP or VPN or service related to that location.

• I revoke the logins, yet they reappear a week later.
• My account has 2FA enabled, yet the auth logs do not show it being used.
• Who is behind these logins? What amount of personal info and connections and messages do they have access to?

10) After seeking help from LinkedIn’s support system, they now want my government ID, just like Twitter.

• They want a third party service (Persona) to scan it, and surely this will never be leaked (sure sure).
• They assure that this third party is very safe, that they only give LinkedIn redacted info (yet Persona keeps the full info?)
• Surely I should trust their entire system. I do not trust their system, and I will not upload my ID for it to be stolen or have any of the data used in some way to harm me.
• The result is similar to Twitter, my account is restricted with no access.

End Results and Oh Well…

So, goodbye LinkedIn, goodbye Twitter.

I cannot place my trust in these faceless social media corporations, the ones which never assume responsibility for data leaks, data theft, or the sale of demographics and usage meta-data. The common refrain of, “we’re telling you that we redacted your personal information”, means nothing substantial from these organizations.

These sites profit extensively from user data - we are their product for sale, and when that happens it can lead to extremely unsafe conditions, particularly if that data can be used for location tracking, enabling access which leads to physical violence, stalking, harassment, or other detriments by which women too-often experience the online world.

Sure, I could upload my ID and “just trust them”, but that would not make me safer; it would invalidate the entire purpose of protecting my body, my mind, my future. Handing them my trust, when they have routinely proven that they are not trustworthy, would render-pointless every hardship and effort towards safety and security which I’ve been required to endure since those events so many years ago.

By prioritizing my personal safety in both of these cases, the end result is that I am no longer able to engage and connect with people from my work life via the two most common business-centric social networks. The alternative is no alternative at all; choosing not to be safe is not a choice.

I know what it’s like to have my choice taken from me, and I never want that to happen again.

In the worst of circumstances, Fedora notified me of a firmware update, which was a hands-off type of “reboot to install” EFI blob which bricked my Thinkpad X1 Nano laptop just last week. That’s an expensive failure and one which has no simple resolution (many hours, many iso to img to efi/cap conversions, and maybe soon a WSOP-8 NAND reprogramming).

I’ve been all-in on the RedHat infra train since 1999, having used it at global backbone providers, satellite infra providers, hpc clusters, media conglomerates, gaming networks, streaming services, cloud providers and hyperscalers, and just about everything in-between… and while I have my qualms on certain technical aspects and corporate strategy over those years, I still consider it one of my favorite Linux distos (top five at least), and it’s my first choice for enterprise Linux. So, I’m not just hating on the ecosystem here, I’m a vested user who’s been disappointed too many times by the direction

Unfortunately, with Fedora, I stand behind my position that Redhat has been too hands-off in conducting standards requirement alignment, in requiring a base level of stability upon which serious engineering development can be done, without having to clean up other people’s messes every few weeks.

It’s just not a great dev platform distro anymore, and yet the org markets the name as if it were a valid OS for all manner of production uses. IoT use? Never, no thanks. Edge devices? Never again. Security? Forget about it.

It’s not a “bleeding-edge issue” - as that’s Rawhide’s territory where stability of any sort is not expected. The evolving issue with Fedora is that it is uncommonly unstable for a “dev env”, and one which ships far too much untested code and pushes the equivalent of “crowd source fail-tests” where they expect the users to “just tell us if it doesn’t work”. Their release engineering and load-testing seems to occur with zero multivariate matrices sequences for all manner of performance, validation, and functional tests. I suppose they consider unit testing to be “full coverage”, but it is not. Happy to be corrected here, though I will remain disappointed and avoid any further deployments or firmware updates from Fedora.

• 1x Nvidia Jetson Xavier NX 16GB
• 3x Nvidia Jetson Orin NX 16GB
• 3x GoWin R86S, N6005 16GB
• 2x Pi-KVM v4-mini for remote/headless access
• 2x NanoPi nodes, a RISC-V LeechiPi, and LattePanda Mu
• Associated networking for 10/5/2.5/1G ports

Setup in a Pelican Air case, ready for the flight!

For the background, I loved endurance racing, and the many long, standing (not seated) hill climbs and mountain passes always were my favorite. Climbing the front-side and then heading down the back-sides of big mountain passes in the Sierra Nevada at 50+mph (80kph) was however not my favorite - but a good lesson in reaping what you sow. Thankfully I never crashed on those, despite having climbed all of the majors and several lesser traveled, many times over: Monitor, Ebbetts, Carson, Echo, Rose, Yuba, Donner, Tioga, Brockway, Daggett, Luther, Pacific Grade Summit, and famously adjacent Geiger Grade going to Virginia City (a common morning ride before work). All of my crashes were on mountain and cyclo-cross, so I was certainly not immune.

The closest I came to a high speed get-off was on Carson Pass (highway 88), back in 2001. I was riding a new set of criterium race wheels that were ultra-lightweight, perfect for climbing up the pass to the summit, but during the descent speed-wobbles had set-in around the 45mph point and continued through to 54mph, starting directly after the first major right-hand curve.

While arc’ing the bike inside the turn, standard approach to manage centrifugal force, and then leaning it back upright as the road straightened, harmonic distortion set in, rippling faster and faster through the bike’s frame, up into my body, blurring my vision. Sometimes going faster will sort out the wave, but not this time, and by 50mph the flexing nearly tore the wheels apart from a combination of light-weight hubs and spokes/rims not having sufficient torsional strength to sustain the pressure involved with the induced coefficient-of-friction and centrifugal force.

This was the kind of turn with speed, which one can see racers engage with on the Tour, which require a rear-side body-torque movement to snap/push the frame out of its desire to continue through the curve and resume going straight - too much downward force started to turn the wheel into an slight oval. This same body movement is used in MotoGP and motocross racing, as it’s an essential skill for powering through a curve while pushing physical limits. The feeling was like that of an al-dente noodle, if one were to imagine being thrown down a hill while trying to keep everything straight and rigid - just stiff enough to not immediately die, but very close to dying really quickly. Wearing a helmet in that case wouldn’t have saved my life, as the pass is surrounded by granite walls and boulders and steep drops.

It took an entire mile of deceleration, achieved through pulsing the front and rear brakes at a 30/70% ratio (like anti-lock brakes on a car, but without the computer), to safely slow down enough for the distortion to resolve. If you don’t pulse the brakes then the pads can overheat and melt, contributing far worse conditions into the mix. By the ~30mph point I had recovered enough control over the bike to gently guide us to a turnout several miles down the pass and then dismount. A lot of adrenaline that day, the intensity of focus and attention to the senses required was certainly a high-point at my youngish age (early 20s).

My friend, a far better racer than I’d ever become, could only laugh at the scene. It wasn’t either of our first experiences with harmonic distortion, and what else is there to do but laugh and get back on the bike? Away we went, continuing down the steep but fast and straight-smooth road to Woodfords where we parked the car.

Well anyway, I had those wheels relaced with bladed titanium spokes and hardened steel nipples tensioned with a digital torque meter (not “feeling the torque by hand”), and never used them for hill climbs ever again.

As for The Death Ride, they no longer include Highway 88’s Carson Pass on the route, mostly due to safety.

References

• Beautiful photos and a grade map: www.tourofcalifornia.org/2006/07/d…
• Stats on the pass: en.wikipedia.org/wiki/Cars…
• The perfect yearly event: deathride.com
• Mentions about Carson no longer being used: deathride.com

Oracle bought Sun to get the ZFS file system. They have been porting ZFS features into Btrfs. The head of the Ext4 file system project, an Oracle employee, said that Ext4 was just a temporary stepping stone on the way to Btrfs.

A primary motivation for Oracle’s acquisition of Sun was to obtain and control the IP for the MySQL database project, which had been obliterating a large amount of Oracle DB customer licensing and dominating the OSS database landscape.

A primary motivation for Oracle’s acquisition of Sun was to obtain their hardware platform for running Oracle DB, Oracle J2EE applications, and their vast middleware stacks. This was everything related to the UltraSparc architecture, Sun Fire line of Opteron based servers, all of the high performance storage technology, and all of Sun’s enterprise contracts with the US military, US gov, various nation states, and all manner of other high-end “serious business” service compute providers.

Sun created Java, nearly all of Oracle’s entire stack requires Java, and Larry wanted that as a foundational piece of IP. At the time of the acquisition, the world ran on Java and it was the most profitable and most widely deployed programming language as well as server runtime environment (JDK, JRE). This aspect is also related to various IP lawsuits around Java, see Oracle vs Google later on.

ReiserFS features were ported into Btrfs, not ZFS features. ZFS has always dominated enterprise storage, never btrfs, never ReiserFS. ZFS in an entirely different class of quality, performance, scalability, reliability, and global market penetration.

RedHat was tired of supporting Btrfs after too many customers reported critical data-loss incidents, which could only serve to harm the company’s reputation for stability and technical excellence.

ZFS continues to be amazing, Btrfs continues to suck, Oracle still has their own original ZFS source tree separate from the OpenZFS project, Oracle still sells UltraSparc architecture, Oracle still owns Java IP, Oracle still doesn’t prioritize Btrfs, nothing important runs on Btrfs.

The only recent news about btrfs and Redhat, which invalidates the original claims about Redhat vs Oracle conspiracy, is that Fedora Linux 33 has Btrfs as a default option along with XFS and Ext4, and we all know that Fedora is upstream development for RedHat Enterprise Linux.

Some timeline details:

• 2007, Btrfs concepts and originated at IBM
• 2008, rip-off of ReiserFS features started by developer at Oracle, who was a former dev of ReiserFS (before Hans Reiser murdered wife, tried to cover it up, landed in prison, and ReiserFS project basically died too)
• Btrfs continues to be experimental for years, cannot complete with ZFS on any important metrics
• 2008, Oracle Exadata v1 - a specialized hardware platform for running Oracle databases on HP-UX with Itanium procs
• 2009, Oracle Exadata v2 - now running on Sun hardware, using modified Sun Fire systems with AMD Opteron procs
• 2010, Oracle acquired Sun which had recently acquired MySQL
• 2011, Redhat offers Btrfs as experimental in RHEL 6 beta
• 2012, Btrfs main developer leaves Oracle for Fusion-IO
• 2012, Oracle and SUSE offer Btrfs in their distro for prod use
• 2013, Btrfs main developer leaves Fusion-IO for Facebook
• 2017, Redhat removes Btrfs from inclusion to RHEL 8, switching to XFS (originally from SGI)
• 2018, Redhat acquisition by IBM

Some enjoyable references:

• en.wikipedia.org/wiki/Btrf…
• en.wikipedia.org/wiki/Acqu…
• en.wikipedia.org/wiki/Hans…
• en.wikipedia.org/wiki/ZFS
• en.wikipedia.org/wiki/XFS
• en.wikipedia.org/wiki/Orac…
• www.oracle.com/webfolder…
• flashdba.com/history-o…

Moving forward from the bed… remove the eye mask, its sensory deprivation so welcome in slumbers…

sleepy business

Now to find favored long fluffy cable-knit red socks first - a pleasant awareness of vascular pump-circulation thudding sensations reduced. Then in preparation for that med-tec loveliness which is my cervical traction collar, on goes a rose-hue cashmere half sweater buttoned atop sleepy silken camisole. “mmmm anschmiegsame Geschmeidigkeit ‡”.

Then stretches, stumbling, gathering of presence and place and time now unifying into a commonality of time - it’s The Morning. I hear birds chirping with the crisp breeze of a soon-to-be sunrise of mid-Summer. Coffee, oh but for its receptor activations on acetecholine, dopamine agonist, and norepinephrine boost … taste as a secondary, primarily it is medication. Those interactions with the metabolic system stimulate internal processes throughout the CNS - ANS - PNS and that lovely meta-grid of Dopaminergic Pathways deep within the Corpus Callosum. Pain aside, it is nothing new, this calm state of early morning is one to transcribe into the site, here right now; one to remember not for its perfectness or idealistic qualities but for its simple state of awareness in the present.

I close my eyes, focus on breathing, slowly make contact with each cervical and spinal nerve as the minds-eye transits out of the cerebellum to the travel lower lower, out to each extremity and back, making contact with each sector and member of the body… acknowledging its presence, “hello legs, hello toes, waist and pelvis, aching joints, all those ligaments”.. and move on to the endocrine nodes, “good morning thyroid, anterior pituitary, remnant-repro structures long removed, adrenal lobes” Acknowledging each’s present state - calculating how each contributes before checking the sequence of hours and days - for which medication is needed today? The knobs and levers now mine to control: plans for weekly plasma curves, Cmax / Tmax / AUC, and the rest of the pharmacokinetics and pharmacodynamics - each complexity of dose + duration + modulations with CYP450 attribute to their interplay.

Holding the post-coma reigns, adjusting nearly the entire neuro/endocrine array of medications of injections and pills and time-release capsules, all of those elements which allow now for consistency of experience, to maintain my Self. It’s challenging, with six hormones and three neurotransmitters, and anywhere from six to eight tertiary and ancillary Rx to modulate those primaries.

Externalizing the management structure is time consuming, complex in interactions, extremely challenging to adjust for concurrency of stability with consistency of mind and body. The ANS is so much better at all of those things, and yet this structure and several others never fully woke up with the rest of me on that bed in the ICU so long ago. Drifting thoughts, a tissue or two, not for crying but few streams of silent tears which fall - all on their own, frontal-emotion not attached yet those tears appear just as quickly as they depart. Perhaps another autonomic function triggering its role in an unknown-to-me manner for some evolutionary purpose long ago.

The doctors were rarely helpful [1], even “Cross-Functional Integrated Care Teams” of specialists, nor ombudsmen, occasionally a wonderful Nurse Practitioner brings the light back into my eyes (thank you Sue).

• [1] Except for Dr. Amber, who patiently and with honest care truly listened
• [‡] “anschmiegsame Geschmeidigkeit”, loosely translates to “cozy softness”

Generally, the only systems that I want to keep at home are the ones which receive active physical attention with hardware changes or re-cabling etc; tasks that would be costly and not fun for Remote Hands to deal with at the colo.

So, why then all of this talk about computational hardware? Mostly just because it’s enjoyable.

Footnotes and References

• [1] RFC99, RFC1918.tld

The RFC1918s are references to a set of domains which I’ve acquired over a number of years, specific to home-colo-startup lab architecture development. In standing with the concept of “Usage-Based Naming Convention”, the following TLDs are used in my systems and hostname structures. Anything RFC is for private-local scope, and yes it does refer to the IETF RFC1918 if any becomes curious. Sometimes these domains have valid TLS wildcard certs, sometimes they are self-signed, sometimes there’s no need for

• rfc1918.ai - All things LLM and M/L related, agentic flows, sentience
• rfc1918.cloud - Private and Hybrid cloud usage for logical addressing
• rfc1918.dev - Development related addresses, code repos, emails
• rfc1918.host - Hosts of course, virtual or metal and often embedded
• rfc1918.io - iSER, iSCSI, SAN, and similar storage specific functions
• rfc1918.sh - Script hosting, mostly used in automation workflows
• rfc1918.systems - Referential use, pending docs migration to new wiki

Additional TLDs for the Labs

My definition of Lab isn’t always formal, or informal, or singular-entity driven. Sometimes I prefer to expand the term to include informally organized teams where there’s a shared goal, though perhaps open-ended. In that regard, the most recent TLD has been assigned to bsd.engineering.

To tell the truth, a few spectators still remained, some scattered, others in groups around the pillars, women, old men, or children, who had had enough of the uproar and tumult. Some scholars were still perched astride of the window-sills, engaged in gazing into the Place.

“Well,” thought Gringoire, “here are still as many as are required to hear the end of my mystery. They are few in number, but it is a choice audience, a lettered audience.”

An instant later, a symphony which had been intended to produce the greatest effect on the arrival of the Virgin, was lacking. Gringoire perceived that his music had been carried off by the procession of the Pope of the Fools. “Skip it,” said he, stoically.

He approached a group of bourgeois, who seemed to him to be discussing his piece. This is the fragment of conversation which he caught,—

“You know, Master Cheneteau, the Hôtel de Navarre, which belonged to Monsieur de Nemours?”

“Yes, opposite the Chapelle de Braque.”

“Well, the treasury has just let it to Guillaume Alixandre, historian, for six hivres, eight sols, parisian, a year.”

“How rents are going up!”

“Come,” said Gringoire to himself, with a sigh, “the others are listening.”

“Comrades,” suddenly shouted one of the young scamps from the window, “La Esmeralda! La Esmeralda in the Place!”

This word produced a magical effect. Every one who was left in the hall flew to the windows, climbing the walls in order to see, and repeating, “La Esmeralda! La Esmeralda?” At the same time, a great sound of applause was heard from without.

“What’s the meaning of this, of the Esmeralda?” said Gringoire, wringing his hands in despair. “Ah, good heavens! it seems to be the turn of the windows now.”

He returned towards the marble table, and saw that the representation had been interrupted. It was precisely at the instant when Jupiter should have appeared with his thunder. But Jupiter was standing motionless at the foot of the stage.

“Michel Giborne!” cried the irritated poet, “what are you doing there? Is that your part? Come up!”

“Alas!” said Jupiter, “a scholar has just seized the ladder.”

Gringoire looked. It was but too true. All communication between his plot and its solution was intercepted.

“The rascal,” he murmured. “And why did he take that ladder?”

“In order to go and see the Esmeralda,” replied Jupiter piteously. “He said, ‘Come, here’s a ladder that’s of no use!’ and he took it.”

This was the last blow. Gringoire received it with resignation.

“May the devil fly away with you!” he said to the comedian, “and if I get my pay, you shall receive yours.”

Then he beat a retreat, with drooping head, but the last in the field, like a general who has fought well.

And as he descended the winding stairs of the courts: “A fine rabble of asses and dolts these Parisians!” he muttered between his teeth; “they come to hear a mystery and don’t listen to it at all! They are engrossed by every one, by Chopin Trouillefou, by the cardinal, by Coppenole, by Quasimodo, by the devil! but by Madame the Virgin Mary, not at all. If I had known, I’d have given you Virgin Mary; you ninnies! And I! to come to see faces and behold only backs! to be a poet, and to reap the success of an apothecary! It is true that Homerus begged through the Greek towns, and that Naso died in exile among the Muscovites. But may the devil flay me if I understand what they mean with their Esmeralda! What is that word, in the first place?—‘tis Egyptian!”

Coppenole, from his post, ordered all, directed all, arranged all. During the uproar, the cardinal, no less abashed than Gringoire, had retired with all his suite, under the pretext of business and vespers, without the crowd which his arrival had so deeply stirred being in the least moved by his departure. Guillaume Rym was the only one who noticed his eminence’s discomfiture. The attention of the populace, like the sun, pursued its revolution; having set out from one end of the hall, and halted for a space in the middle, it had now reached the other end. The marble table, the brocaded gallery had each had their day; it was now the turn of the chapel of Louis XI. Henceforth, the field was open to all folly. There was no one there now, but the Flemings and the rabble.

The grimaces began. The first face which appeared at the aperture, with eyelids turned up to the reds, a mouth open like a maw, and a brow wrinkled like our hussar boots of the Empire, evoked such an inextinguishable peal of laughter that Homer would have taken all these louts for gods. Nevertheless, the grand hall was anything but Olympus, and Gringoire’s poor Jupiter knew it better than any one else. A second and third grimace followed, then another and another; and the laughter and transports of delight went on increasing. There was in this spectacle, a peculiar power of intoxication and fascination, of which it would be difficult to convey to the reader of our day and our salons any idea.

Let the reader picture to himself a series of visages presenting successively all geometrical forms, from the triangle to the trapezium, from the cone to the polyhedron; all human expressions, from wrath to lewdness; all ages, from the wrinkles of the new-born babe to the wrinkles of the aged and dying; all religious phantasmagories, from Faun to Beelzebub; all animal profiles, from the maw to the beak, from the jowl to the muzzle. Let the reader imagine all these grotesque figures of the Pont Neuf, those nightmares petrified beneath the hand of Germain Pilon, assuming life and breath, and coming in turn to stare you in the face with burning eyes; all the masks of the Carnival of Venice passing in succession before your glass,—in a word, a human kaleidoscope.

The orgy grew more and more Flemish. Teniers could have given but a very imperfect idea of it. Let the reader picture to himself in bacchanal form, Salvator Rosa’s battle. There were no longer either scholars or ambassadors or bourgeois or men or women; there was no longer any Clopin Trouillefou, nor Gilles Lecornu, nor Marie Quatrelivres, nor Robin Poussepain. All was universal license. The grand hall was no longer anything but a vast furnace of effrontry and joviality, where every mouth was a cry, every individual a posture; everything shouted and howled. The strange visages which came, in turn, to gnash their teeth in the rose window, were like so many brands cast into the brazier; and from the whole of this effervescing crowd, there escaped, as from a furnace, a sharp, piercing, stinging noise, hissing like the wings of a gnat.

“Hold, my friend, you cannot pass!”

The man in the leather jerkin shouldered him aside.

“What does this knave want with me?” said he, in stentorian tones, which rendered the entire hall attentive to this strange colloquy. “Don’t you see that I am one of them?”

“Your name?” demanded the usher.

“Jacques Coppenole.”

“Your titles?”

“Hosier at the sign of the ‘Three Little Chains,’ of Ghent.”

The usher recoiled. One might bring one’s self to announce aldermen and burgomasters, but a hosier was too much. The cardinal was on thorns. All the people were staring and listening. For two days his eminence had been exerting his utmost efforts to lick these Flemish bears into shape, and to render them a little more presentable to the public, and this freak was startling. But Guillaume Rym, with his polished smile, approached the usher.

“Announce Master Jacques Coppenole, clerk of the aldermen of the city of Ghent,” he whispered, very low.

“Usher,” interposed the cardinal, aloud, “announce Master Jacques Coppenole, clerk of the aldermen of the illustrious city of Ghent.”

This was a mistake. Guillaume Rym alone might have conjured away the difficulty, but Coppenole had heard the cardinal.

“No, cross of God?” he exclaimed, in his voice of thunder, “Jacques Coppenole, hosier. Do you hear, usher? Nothing more, nothing less. Cross of God! hosier; that’s fine enough. Monsieur the Archduke has more than once sought his gant* in my hose.”

* Got the first idea of a timing.

Laughter and applause burst forth. A jest is always understood in Paris, and, consequently, always applauded.

Let us add that Coppenole was of the people, and that the auditors which surrounded him were also of the people. Thus the communication between him and them had been prompt, electric, and, so to speak, on a level. The haughty air of the Flemish hosier, by humiliating the courtiers, had touched in all these plebeian souls that latent sentiment of dignity still vague and indistinct in the fifteenth century.

This hosier was an equal, who had just held his own before monsieur the cardinal. A very sweet reflection to poor fellows habituated to respect and obedience towards the underlings of the sergeants of the bailiff of Sainte-Geneviève, the cardinal’s train-bearer.

Coppenole proudly saluted his eminence, who returned the salute of the all-powerful bourgeois feared by Louis XI. Then, while Guillaume Rym, a “sage and malicious man,” as Philippe de Comines puts it, watched them both with a smile of raillery and superiority, each sought his place, the cardinal quite abashed and troubled, Coppenole tranquil and haughty, and thinking, no doubt, that his title of hosier was as good as any other, after all, and that Marie of Burgundy, mother to that Marguerite whom Coppenole was to-day bestowing in marriage, would have been less afraid of the cardinal than of the hosier; for it is not a cardinal who would have stirred up a revolt among the men of Ghent against the favorites of the daughter of Charles the Bold; it is not a cardinal who could have fortified the populace with a word against her tears and prayers, when the Maid of Flanders came to supplicate her people in their behalf, even at the very foot of the scaffold; while the hosier had only to raise his leather elbow, in order to cause to fall your two heads, most illustrious seigneurs, Guy d’Hymbercourt and Chancellor Guillaume Hugonet.

It is not that Pierre Gringoire either feared or disdained monsieur the cardinal. He had neither the weakness nor the audacity for that. A true eclectic, as it would be expressed nowadays, Gringoire was one of those firm and lofty, moderate and calm spirits, which always know how to bear themselves amid all circumstances (stare in dimidio rerum), and who are full of reason and of liberal philosophy, while still setting store by cardinals. A rare, precious, and never interrupted race of philosophers to whom wisdom, like another Ariadne, seems to have given a clew of thread which they have been walking along unwinding since the beginning of the world, through the labyrinth of human affairs. One finds them in all ages, ever the same; that is to say, always according to all times. And, without reckoning our Pierre Gringoire, who may represent them in the fifteenth century if we succeed in bestowing upon him the distinction which he deserves, it certainly was their spirit which animated Father du Breul, when he wrote, in the sixteenth, these naively sublime words, worthy of all centuries: “I am a Parisian by nation, and a Parrhisian in language, for parrhisia in Greek signifies liberty of speech; of which I have made use even towards messeigneurs the cardinals, uncle and brother to Monsieur the Prince de Conty, always with respect to their greatness, and without offending any one of their suite, which is much to say.”

There was then neither hatred for the cardinal, nor disdain for his presence, in the disagreeable impression produced upon Pierre Gringoire. Quite the contrary; our poet had too much good sense and too threadbare a coat, not to attach particular importance to having the numerous allusions in his prologue, and, in particular, the glorification of the dauphin, son of the Lion of France, fall upon the most eminent ear. But it is not interest which predominates in the noble nature of poets. I suppose that the entity of the poet may be represented by the number ten; it is certain that a chemist on analyzing and pharmacopolizing it, as Rabelais says, would find it composed of one part interest to nine parts of self-esteem.

Now, at the moment when the door had opened to admit the cardinal, the nine parts of self-esteem in Gringoire, swollen and expanded by the breath of popular admiration, were in a state of prodigious augmentation, beneath which disappeared, as though stifled, that imperceptible molecule of which we have just remarked upon in the constitution of poets; a precious ingredient, by the way, a ballast of reality and humanity, without which they would not touch the earth. Gringoire enjoyed seeing, feeling, fingering, so to speak an entire assembly (of knaves, it is true, but what matters that?) stupefied, petrified, and as though asphyxiated in the presence of the incommensurable tirades which welled up every instant from all parts of his bridal song. I affirm that he shared the general beatitude, and that, quite the reverse of La Fontaine, who, at the presentation of his comedy of the “Florentine,” asked, “Who is the ill-bred lout who made that rhapsody?” Gringoire would gladly have inquired of his neighbor, “Whose masterpiece is this?”

The reader can now judge of the effect produced upon him by the abrupt and unseasonable arrival of the cardinal.

That which he had to fear was only too fully realized. The entrance of his eminence upset the audience. All heads turned towards the gallery. It was no longer possible to hear one’s self. “The cardinal! The cardinal!” repeated all mouths. The unhappy prologue stopped short for the second time.

The cardinal halted for a moment on the threshold of the estrade. While he was sending a rather indifferent glance around the audience, the tumult redoubled. Each person wished to get a better view of him. Each man vied with the other in thrusting his head over his neighbor’s shoulder.

He was, in fact, an exalted personage, the sight of whom was well worth any other comedy. Charles, Cardinal de Bourbon, Archbishop and Comte of Lyon, Primate of the Gauls, was allied both to Louis XI., through his brother, Pierre, Seigneur de Beaujeu, who had married the king’s eldest daughter, and to Charles the Bold through his mother, Agnes of Burgundy. Now, the dominating trait, the peculiar and distinctive trait of the character of the Primate of the Gauls, was the spirit of the courtier, and devotion to the powers that be. The reader can form an idea of the numberless embarrassments which this double relationship had caused him, and of all the temporal reefs among which his spiritual bark had been forced to tack, in order not to suffer shipwreck on either Louis or Charles, that Scylla and that Charybdis which had devoured the Duc de Nemours and the Constable de Saint-Pol. Thanks to Heaven’s mercy, he had made the voyage successfully, and had reached home without hindrance. But although he was in port, and precisely because he was in port, he never recalled without disquiet the varied haps of his political career, so long uneasy and laborious. Thus, he was in the habit of saying that the year 1476 had been “white and black” for him—meaning thereby, that in the course of that year he had lost his mother, the Duchesse de la Bourbonnais, and his cousin, the Duke of Burgundy, and that one grief had consoled him for the other.

“Begin instantly! The mystery! the mystery immediately!” shrieked the people. And above all the voices, that of Johannes de Molendino was audible, piercing the uproar like the fife’s derisive serenade: “Commence instantly!” yelped the scholar.

“Down with Jupiter and the Cardinal de Bourbon!” vociferated Robin Poussepain and the other clerks perched in the window.

“The morality this very instant!” repeated the crowd; “this very instant! the sack and the rope for the comedians, and the cardinal!”

Poor Jupiter, haggard, frightened, pale beneath his rouge, dropped his thunderbolt, took his cap in his hand; then he bowed and trembled and stammered: “His eminence—the ambassadors—Madame Marguerite of Flanders—.” He did not know what to say. In truth, he was afraid of being hung.

Hung by the populace for waiting, hung by the cardinal for not having waited, he saw between the two dilemmas only an abyss; that is to say, a gallows.

Luckily, some one came to rescue him from his embarrassment, and assume the responsibility.

An individual who was standing beyond the railing, in the free space around the marble table, and whom no one had yet caught sight of, since his long, thin body was completely sheltered from every visual ray by the diameter of the pillar against which he was leaning; this individual, we say, tall, gaunt, pallid, blond, still young, although already wrinkled about the brow and cheeks, with brilliant eyes and a smiling mouth, clad in garments of black serge, worn and shining with age, approached the marble table, and made a sign to the poor sufferer. But the other was so confused that he did not see him. The new comer advanced another step.

“Jupiter,” said he, “my dear Jupiter!”

The other did not hear.

At last, the tall blond, driven out of patience, shrieked almost in his face,—

“Michel Giborne!”

“Who calls me?” said Jupiter, as though awakened with a start.

“I,” replied the person clad in black.

“Ah!” said Jupiter.

“Begin at once,” went on the other. “Satisfy the populace; I undertake to appease the bailiff, who will appease monsieur the cardinal.”

Jupiter breathed once more.

“Messeigneurs the bourgeois,” he cried, at the top of his lungs to the crowd, which continued to hoot him, “we are going to begin at once.”

“Evoe Jupiter! Plaudite cives! All hail, Jupiter! Applaud, citizens!” shouted the scholars.

“Noel! Noel! good, good,” shouted the people.

The hand clapping was deafening, and Jupiter had already withdrawn under his tapestry, while the hall still trembled with acclamations.

In the meanwhile, the personage who had so magically turned the tempest into dead calm, as our old and dear Corneille puts it, had modestly retreated to the half-shadow of his pillar, and would, no doubt, have remained invisible there, motionless, and mute as before, had he not been plucked by the sleeve by two young women, who, standing in the front row of the spectators, had noticed his colloquy with Michel Giborne-Jupiter.

“Master,” said one of them, making him a sign to approach. “Hold your tongue, my dear Liénarde,” said her neighbor, pretty, fresh, and very brave, in consequence of being dressed up in her best attire. “He is not a clerk, he is a layman; you must not say master to him, but messire.”

The sixth of January, 1482, is not, however, a day of which history has preserved the memory. There was nothing notable in the event which thus set the bells and the bourgeois of Paris in a ferment from early morning. It was neither an assault by the Picards nor the Burgundians, nor a hunt led along in procession, nor a revolt of scholars in the town of Laas, nor an entry of “our much dread lord, monsieur the king,” nor even a pretty hanging of male and female thieves by the courts of Paris. Neither was it the arrival, so frequent in the fifteenth century, of some plumed and bedizened embassy. It was barely two days since the last cavalcade of that nature, that of the Flemish ambassadors charged with concluding the marriage between the dauphin and Marguerite of Flanders, had made its entry into Paris, to the great annoyance of M. le Cardinal de Bourbon, who, for the sake of pleasing the king, had been obliged to assume an amiable mien towards this whole rustic rabble of Flemish burgomasters, and to regale them at his Hôtel de Bourbon, with a very “pretty morality, allegorical satire, and farce,” while a driving rain drenched the magnificent tapestries at his door.

What put the “whole population of Paris in commotion,” as Jehan de Troyes expresses it, on the sixth of January, was the double solemnity, united from time immemorial, of the Epiphany and the Feast of Fools.

On that day, there was to be a bonfire on the Place de Grève, a maypole at the Chapelle de Braque, and a mystery at the Palais de Justice. It had been cried, to the sound of the trumpet, the preceding evening at all the cross roads, by the provost’s men, clad in handsome, short, sleeveless coats of violet camelot, with large white crosses upon their breasts.

So the crowd of citizens, male and female, having closed their houses and shops, thronged from every direction, at early morn, towards some one of the three spots designated.

Each had made his choice; one, the bonfire; another, the maypole; another, the mystery play. It must be stated, in honor of the good sense of the loungers of Paris, that the greater part of this crowd directed their steps towards the bonfire, which was quite in season, or towards the mystery play, which was to be presented in the grand hall of the Palais de Justice (the courts of law), which was well roofed and walled; and that the curious left the poor, scantily flowered maypole to shiver all alone beneath the sky of January, in the cemetery of the Chapel of Braque.

The populace thronged the avenues of the law courts in particular, because they knew that the Flemish ambassadors, who had arrived two days previously, intended to be present at the representation of the mystery, and at the election of the Pope of the Fools, which was also to take place in the grand hall.

It was no easy matter on that day, to force one’s way into that grand hall, although it was then reputed to be the largest covered enclosure in the world (it is true that Sauval had not yet measured the grand hall of the Château of Montargis). The palace place, encumbered with people, offered to the curious gazers at the windows the aspect of a sea; into which five or six streets, like so many mouths of rivers, discharged every moment fresh floods of heads. The waves of this crowd, augmented incessantly, dashed against the angles of the houses which projected here and there, like so many promontories, into the irregular basin of the place. In the centre of the lofty Gothic* façade of the palace, the grand staircase, incessantly ascended and descended by a double current, which, after parting on the intermediate landing-place, flowed in broad waves along its lateral slopes,—the grand staircase, I say, trickled incessantly into the place, like a cascade into a lake. The cries, the laughter, the trampling of those thousands of feet, produced a great noise and a great clamor. From time to time, this noise and clamor redoubled; the current which drove the crowd towards the grand staircase flowed backwards, became troubled, formed whirlpools. This was produced by the buffet of an archer, or the horse of one of the provost’s sergeants, which kicked to restore order; an admirable tradition which the provostship has bequeathed to the constablery, the constablery to the maréchaussée, the maréchaussée to our gendarmeri of Paris.