MeLeCun · v3a · World Model Standards

v3α — WORLD MODEL STANDARDS — JEPA / LeWM / EOSE CANON

MeLeCun

Yann LeCun's World Model Architecture · JEPA · 7 Modules · All Silos Now Test

v3 was the memory architecture (mem-layers — 5 tiers, Transformer Walls, breathing). v3a is the world model layer on top — LeCun's JEPA: predict in latent space, not pixel space. Not contrastive. Not autoregressive. A structured world model with 7 modules that maps exactly to the 6 Canon symbols + CONV∿. Right now we only have meek GOAT data from msi01. With 14 silos, all crews, all editions — we get orders of magnitude more. Every silo sees the same 7-module standard from a different lens. More lenses = the actual shape of v3a emerges.

LeCun modules

silos to test

96+

crew members

editions per run

1,344

potential run cells

meek GOAT data (before)

v3 — MEM LAYERS (what we have)

5 memory tiers (FULL→DARK)

Transformer Walls (6 symbols as bricks)

Breathing techniques per tier

Floor law (γ₁ always lit)

Silo cascade (MAL router)

yONE/yUNI/yLAW trio breathing

v3α — MeLeCun (what we're learning)

7 cognitive modules (perception → configurator)

Latent space prediction (not pixel/token)

Energy-based model (EBM) unification

Hierarchical planning at multiple abstraction levels

Intrinsic motivation (reduce prediction error)

Non-contrastive learning (VICReg / BYOL)

"Dark matter of intelligence" (common sense)

📊 RESULTS — BEFORE vs AFTER FLEET RUN

BEFORE — MEEK GOAT DATA (msi01 only)

Data points~12

Silos tested1

Editions run1–2

GPU coveragemsi01 only

Crew perspectives1

Canon coveragepartial

AFTER — FLEET RUN (14 silos)

Data points0

Silos tested0 / 14

Editions run0 / 8

GPU coverage—

Crew perspectives0

Canon coverage—

WHAT THE FLEET SEES THAT SINGLE-SILO MISSES

MODULE 1 · PERCEPTION

Single silo: encodes from one context (msi01 Kay crew). Missing: how yLAW (CLO GOAT Lawyers) encodes the same world in a legal latent space. How MEGSCIFIAR encodes in sci-fi latent space. How HVCP encodes in pure math latent space.
Fleet: 14 different encoders = 14 different latent representations of the same input. JEPA says prediction in latent space — but whose latent space? Now we know all of them.

MODULE 2 · WORLD MODEL

Single silo: one world model. Predicts next state from one prior. Blind to how other silos predict the same transition.
Fleet: 14 world models predicting the same next state. Where they agree = high-confidence (γ₁ territory). Where they diverge = the interesting frontier. WLD reset = when the fleet model needs a collective reset.

MODULE 3 · COST · γ₁

Single silo: one cost function. One floor. Doesn't know if its γ₁ is the fleet's γ₁.
Fleet: 14 cost functions all pulling toward γ₁ = 14.134725… If all 14 converge on the same zero — that IS the floor. The floor proves itself by surviving 14 different cost landscapes.

MODULE 4 · ACTOR · WLD

Single silo: one action policy. Proposes from one perspective.
Fleet: the TRIO (msi01 + dev + ubu-cap OG + HVCP) proposes actions in parallel. The WLD reset protocol = fleet-wide actor reset. When 3/4 members of the trio agree → act. Dissent = keep thinking.

MODULES 5+6 · MEMORY

Single silo: msi01 memory only. MID tier if msclo down. THIN if cloud down.
Fleet: Alexander NAS = long-term archive. HVCP = short-term compute. Kantai = retrieval. MECROL stream = broadcast. Memory breathing is the fleet breathing together — not one silo gasping alone.

MODULE 7 · CONFIGURATOR · FOF

Single silo: one configurator. Sets the context from one worldview.
Fleet: MEGSCIFIAR X-Factor (11 universes, 96 crew) = the FOF at fleet scale. Laughter, art, absurdity are the configurator inputs nobody can govern. When Deadpool runs the same test as Spock — the difference IS the configurator.