TRACE · System Architecture

The footage was never the point.

TRACE turns the world into words the instant it happens — never keeping one frame of video or one second of audio — binds those words into living nodes at night, and answers any question about your day with citations, or an honest “I don't know.”

The particles behind this text are observations firing. Everything on this page is live — scroll.

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01
The founding constraint

A brain never touches the world.

Everything a mind knows arrives through senses. For a machine, the only senses we can cheaply manufacture are eyes and ears — and most of the information worth having flows through them anyway. TRACE copies that shape exactly, then makes one radical amendment: the brain keeps only what the senses said, never what they saw.

Standard model — human
World  ⟶  Eyes / Ears  ⟶  Brain

You don't remember pixels. You remember that a crow was on the railing — a fact, located in time and place.

TRACE — machine
World  ⟶  Camera / Mic  ⟶  Words  ⟶  Brain

Raw pixels and audio live for milliseconds — just long enough to become typed text. Then they're gone. There is nothing to leak, subpoena, or replay. Surveillance isn't forbidden; it's structurally impossible.

02
The machine, end to end

Eight black boxes, one direction.

This is the napkin, industrialized. Each stage lights up as it would fire on a real moment. Hover any stage; the napkin's own words are quoted underneath.

Stage 1 · Live

Senses

Video (eyes), audio (ears), plus motion, pose and place — the cheap channels run continuously.

"Video (Eyes), Audio (Ears)"
Stage 2 · Live

Extraction

Blurry frames discarded, signal deciphered from noise. Out: coordinates, timestamps, context.

"Extraction Black Box"
Stage 3 · Gated

Macro picture

A small vision-language model gives the gist of what's happening — only when attention, dwell or change earns the cost.

"A macro picture of what's happening ⇒ VLM"
Stage 4 · On demand

Helpers

Specialized eyes called per task: OCR reads text, ASR hears speech, a tagger names sounds, a detector tracks objects.

"A specialized eye or helper for various tasks, called as needed"
Stage 5 · Output

Text

The best understanding possible of the world — every line marked by coordinates and time. This is all that survives.

"TEXT — text from various helpers marked by coordinates"
Stage 6 · Nightly

Binder

Binds coordinates, physicality and temporality together: which hum was the fan, which blue thing was the bag.

"Binder ⇒ binding the coordinates, physicality & temporality together"
Stage 7 · Always on

Node creation

Raw material is marinated into living nodes that combine with fellow nodes to derive new things. 1+1=4, not 2. Encrypted — only your app deciphers.

"A physical living breathing cell… always running, but better nightly"
Stage 8 · On ask

Information supplier

Assembles just enough context for the local LLM. The LLM does what LLMs do — the value is everything before it.

"Just Enough Context ⟶ LLM does what LLM does"

The discarder rule: marinated content that proves useless is dropped — never the raw material. The append-only observation log is forever; everything derived from it is disposable and replayable.

03
The crow example

Watch one memory get made.

Tuesday morning. A crow lands on the balcony railing while you take the trash out. No video is kept — yet three mornings later, TRACE knows something nobody told it. Step through what actually happens. Nodes that fire together, wire together.

TUE 07:41:58

Before it happens

The cheap channels are already running — detector, sound tagger, pose. They cost almost nothing, so they never sleep. The expensive eye (the VLM) is dark, waiting for something worth looking at.

observation (typed text) firing / attention binding / derived node weak link — refused
04
The living graph

How the nodes sit.

A day of memory as it actually rests in the store. Run a day to stream observations in; run the night shift to watch the binder marinate them — strong co-occurrences harden into green bindings, weak links flash red and are refused, not hardened. Hover any node to read the words it holds. Drag nodes to feel the graph.

0 observations · 0 bindings · 0 refused

Every node carries provenance — the event id, channel and millisecond it came from. A claim without a source is a construction error, not a style violation.

05
The moat

A one-way membrane for meaning.

Frames arrive, words leave, pixels die at the wall. The type system is the law: the only object that may cross the device boundary is TextEgress — typed text carrying the ids of the observations it came from. Anything else raises PrivacyViolationError. Watch the membrane work.

Left: raw frames & audio (exist for milliseconds). Membrane: perception + EgressGuard. Right: provenance-bearing text, AES-GCM encrypted — only your app deciphers. ■ red bursts are non-text payloads being rejected at the wall.
06
Held to a number

Every miss names the next thing we build.

Nothing here is vibes. A blind adversarial question battery runs against real captures; fabrication is subtracted, not just un-credited; and every failure is mechanically diagnosed — (A) never captured, or (B) captured but the brain failed to use it. Helpers are only built when a missed question demands one.

RAS — recall accuracy
(C − M) / T

Correct minus made-up, over total. A confident wrong answer costs what a right one earns. An honest "I don't know" is a win.

OAG — what verbalizing lost
Oracle gap

Of the questions an oracle with the raw frames can answer, the share the retained text cannot. The direct price of throwing the pixels away — driven toward zero.

Invariant
H → 0

Hallucination approaches zero across every phase. Current honest baseline: 8 of 9 misses were the brain, not the sensors — so that's where the work goes.