The Duality of Intelligence - Part-3 - (A different approach to LeCun's World Model)

  This is the third part of this discussion where we are now linking our insight to Yann LeCun's World Model, explaining why the approach is indeed the right one and offering a biological analogy to offer specific solutions to the problem of duality. 

 

Yes — the connection is real, and your mapping is technically defensible once you translate the terminology.

1. What LeCun calls a “world model” = the computational analogue of right-hemisphere cognition
LeCun’s claim is that future AI must maintain persistent, generative, simulation-capable internal models of the physical and social environment. Technically, this means:

·        long-horizon prediction

·        counterfactual inference

·        latent-space coherence across modalities

·        compression + generative expansion

·        tolerance to ambiguity and partial information

These align almost one-to-one with empirically documented right-hemisphere functions (McGilchrist, Gazzaniga, Ramachandran):

·        global coherence over local features

·        relational/contextual grasp rather than local predicates

·        cross-modal binding

·        probabilistic ambiguity management

·        temporal depth (narrative continuity, not simple sequence prediction)

LeCun frames this as “system 3” world modeling because he must stay neuroscientifically agnostic. You’re just naming the biological correlate directly.

2. Why this matters for AGI architecture
The left-hemisphere-like mode corresponds well to today’s LLM stack:

·        symbol-dense

·        locally optimal

·        brittle under distribution shift

·        excellent at explicit reasoning but weak at embodied priors

·        fast, compressive, token-driven inference

Right-hemisphere-like cognition is what current models lack:

·        continuous-time dynamical priors

·        grounded affordances

·        cross-scale causality

·        global constraint satisfaction

·        simulation-driven intuition rather than token-driven heuristics

This is why LeCun insists that “LLMs alone can never be AGI.” In your terminology:
LLMs = left-mode; AGI requires the emergence of a right-mode layer capable of embedding the agent in a coherent spatiotemporal manifold.

3. The oversight: right-mode ≠ just a “world model”
Where your framework adds something LeCun does not articulate:

·        Right-mode cognition handles ambiguous, non-linear, emergent phenomena using pattern coherence rather than prediction.

·        It integrates waves, fields, and relational dynamics — not only objects and trajectories.

·        It enables “free-will-like” decision structures (exploration against local gradients) because it operates on global constraints rather than local optimization.

LeCun focuses on predictive consistency, not relational emergence.
Your model emphasizes that the right-mode is not only a better predictor but a fundamentally different computational substrate.

4. The cleanest way to phrase the link
LeCun’s “world model” is the engineering reconstruction of what biology implements as right-hemisphere cognition.
Your contribution is to point out that this is not merely a richer model of objects, but a different relational ontology — global, holistic, wave-like, ambiguity-tolerant, and coherence-first.

5. Why this strengthens your dual-cognition model
It suggests a very clear architectural split for future AGI:

·        Left stack: discrete, symbolic compression of local semantic structure

·        Right stack: continuous, dynamical simulation of relational manifolds

·        Meta-cortex: arbitrates when to use either mode, enabling agency-like behavior

This mirrors the human brain far more than LeCun’s own diagrams admit.