- content-taxonomy: feed/avatar/volumetric marked ✅ (shipped), not ⬜. - cargo-roadmap: header notes Phases 1–5 complete (archived plan). - README: add the interactive/temporal capability table + provenance. - codecs: fix CMIC label ("Content-Adaptive Mamba", arXiv 2508.02192); drop the external BD-rate-vs-VTM comparison (self-referential copy). Co-Authored-By: Claude Opus 4.8 <[email protected]>
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WAI Cargo-Class Roadmap
Status: Phases 1–5 complete (v0.4.0). Spatial audio, haptics, state-feeds, avatars, and volumetric/4D splats all shipped, promoted to
extensions/, and live. This document is now the archived plan of record — seeCHANGELOG.mdfor current state andcontent-taxonomy.mdfor what remains white space (e.g. music-as-score).The build plan for the white-space content classes in
content-taxonomy.md. Every phase follows the same proven recipe the interactive-worlds extension established — so this is execution, not invention.
The recipe (every cargo class follows it)
- Draft the extension spec in
research/<class>-draft.md— scope, payload format, conformance criterion, fallback floor, receipt profile. - Register the capability in
wai-rs/src/codecs/mod.rs(known_capabilities+ fidelity tier). Registration freezes the payload format forever (SPEC §7) — so it lands with the drafted format. - Reference implementation in
wai-rsbehind a feature: the container, the deterministic core, and the conformance criterion. - Conformance corpus + a
gen|verifybin: vectors + expected hashes; pass = hash equality, no tolerance parameter. - Browser sink in
wai-web(wasm-bindgen) + a/worlds-style demo page; prove it on real hardware via Playwright. - JWP receipt profile — what the §8 receipt carries for this class.
- Promote the draft to
extensions/, mirror to the site, update SPEC §5/§8, CHANGELOG, deploy.
The invariants every class inherits for free: content-addressing,
fallback floor, Ed25519 seals, the JWP receipt chain, exact signed
work_steps + measured joules_micro (the native wai_world_meter
pattern), and a conformance criterion that is the class's own form of
-equivalence.
Conformance criterion per class (the load-bearing design choice)
Each class needs a deterministic, hash-checkable equivalence — the generalization of decode-equivalence:
| class | equivalence | the determinism floor |
|---|---|---|
| interactive worlds | replay-equivalence | wai.det.fixed64 (shipped) |
| spatial audio | mixdown-equivalence | fixed-point PCM mix to a declared layout |
| haptics | sample-equivalence | fixed-point actuator samples at a declared rate |
| state-feeds | replay-equivalence | reuse the worlds op-log + state hash |
| digital humans | pose-equivalence | skeletal transforms in wai.det.fixed64 |
| volumetric / 4D splats | frame-state-equivalence | per-frame Gaussian-cloud hash |
Phase 0 — shipped (baseline)
Core media codecs (image/audio/video/text + neural family) · JWP
receipts · interactive-worlds (wai.world.{scene,replay,live}, three sim
registrants, corpus, browser sink, tab + cross-device relay multiplayer,
seal-to-replay, session receipts) · wai.mesh.glb + wai.splat.spz
assets · PBR + EWA-splat renderers · native energy meter. Siblings:
map, joule-ui, Access/Lumina.
Phase 1 — Object-based spatial audio · wai.audio.scene
Why first: the cleanest technical analog to interactive-worlds.
Ship sound objects + a scene; the sink renders to its own speaker
layout. Mixdown-equivalence is the audio counterpart of
replay-equivalence, and it composes the asset path (each source is a
content-addressed wai.audio.* object) + receipts + determinism.
Payload (WSCN container, sketch):
- scene contract: sample rate, channel layout target(s), pan law id,
numeric profile (
wai.det.fixed64for the exact mix). - object table: N objects, each =
{ source_asset_hash (a wai.audio.* WAI object), gain, trajectory (keyframed position over time) }. - a deterministic render contract: given the objects + a declared
output layout (
stereo,5.1,binaural@<hrtf-id>), the mixed PCM is bit-reproducible.
Conformance: mixdown-equivalence — same scene + same declared layout → identical BLAKE3 over the canonical PCM. Reference mixer: distance attenuation + constant-power panning, fixed-point accumulate.
Reference impl: wai-rs audio_scene feature — scene container,
deterministic mixer to stereo (+ a binaural profile naming an HRTF as a
requirement-of-existence, like a neural prior). Sources decoded via the
existing audio path.
Browser sink: Web Audio API for the nice render (PannerNode/HRTF), plus the deterministic reference mixer for the hash check — same honest split as worlds (exact state vs. presentation).
Effort: medium (DSP: resample, pan, fixed-point mix). Risk: the
fixed-point mix must be exact across machines — same discipline as
Fx.
Phase 2 — Haptics · wai.haptic.signal
Why second: lowest effort, pure instructions-at-sink, trivially deterministic. A tiny event/waveform stream rendered on actuators.
Payload: a contract (sample rate, channel→actuator map) + either a keyframed envelope or a fixed-point waveform per channel. Often a few hundred bytes for an effect.
Conformance: sample-equivalence — the reconstructed actuator sample buffer hashes identically.
Reference impl: wai-rs haptic feature — container + reconstruct
to a PCM-like buffer. Browser sink: Gamepad vibrationActuator /
the Vibration API; visualize the waveform on canvas as the fallback.
Effort: low. Risk: low. Good momentum builder after Phase 1.
Phase 3 — Live state-feeds · broadcast profile + wai.feed.state
Why: the multiplayer-games precedent applied to broadcast — "ship state, not pixels" for sports/events/telemetry. Most of it already exists.
Two pieces:
- Broadcast profile of
wai.world.live— one authoritative publisher, many read-only sinks, over the existing relay. A spectator floor (an AV1 stream of a capable participant's render) per §9. wai.feed.state— a non-physics state feed (scoreboard, telemetry, market ticks): a signed op log over a declared schema with the same canonical ordering + state hash, no sim. Effectively interactive-worlds with a trivial "sim = apply the typed field updates."
Conformance: replay-equivalence (reuse the worlds machinery).
Effort: medium (mostly profiling + relay broadcast mode). Reuses relay, receipts, op log, state hash.
Phase 4 — Digital humans / avatars · skinned mesh + skeletal animation
Why: highest-bandwidth capture, most reducible to rig + stream. Composes shipped pieces.
Pieces:
- Skinned-mesh asset:
wai.mesh.glbalready carries skeletal armatures + skin weights (glTF) — decode is sink-supplied. - Skeletal sim registrant (
wai.world.sim.skeletal): nodes are bones; ops set joint transforms inwai.det.fixed64; the sink skins the mesh by the deterministic pose. - Animation / expression op stream: the existing CausalOp log drives the rig — a telepresence stream is a live world of one avatar.
Conformance: pose-equivalence (bone transforms hash identically) — a special case of replay-equivalence.
Effort: medium-high (skinning on the GPU; pose determinism).
Phase 5 — Volumetric / light-field · wai.splat.4d (temporal Gaussians)
Why last: the frontier of "video"; no clean envelope exists. Extends the splat path to time.
Payload: a base Gaussian cloud + per-frame deltas, OR per-Gaussian trajectories (position/rotation/scale/opacity keyframes). Sink interpolates and renders with the existing EWA pipeline.
Conformance: frame-state-equivalence — the Gaussian set at frame N hashes identically (presentation render stays the renderer's business).
Effort: high. Risk: size (volumetric is heavy — the win is content-addressing + dedup + receipts, not payload reduction; state that honestly, as with static splats).
Sequencing rationale
- Spatial audio — cleanest analog, highest "proves the thesis generalizes" value, composes the asset path.
- Haptics — fast win, completes the "every sense" story (sight via worlds/splats, hearing via audio-scene, touch via haptics).
- State-feeds — biggest commercial wedge, mostly already built.
- Digital humans — high value, composes worlds + mesh.
- Volumetric — frontier, heaviest, do last.
Cross-cutting, anytime: surface content-addressing + JWP receipts + measured joules on the captured-reality classes (photos, recordings, telemetry) — the lever-4 win that needs no reconstruction and applies to the content that can't be reduced to instructions.