François Chollet on X: "Eventually, much of AI will converge towards intuition-guided symbolic world modeling, i.e. deep learning-guided program synthesis. It is inevitable. Symbolic modeling lets a system construct a compact, reusable, highly generalizable mental model of a problem space using minimal" / X<br>Post

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François Chollet on X: "Eventually, much of AI will converge towards intuition-guided symbolic world modeling, i.e. deep learning-guided program synthesis. It is inevitable. Symbolic modeling lets a system construct a compact, reusable, highly generalizable mental model of a problem space using minimal"

François Chollet

@fchollet

Eventually, much of AI will converge towards intuition-guided symbolic world modeling, i.e. deep learning-guided program synthesis. It is inevitable. Symbolic modeling lets a system construct a compact, reusable, highly generalizable mental model of a problem space using minimal data.<br>span:not(:empty)~span:not(:empty)]:before:content-['·'] [&>span:not(:empty)~span:not(:empty)]:before:px-1 [&>span:not(:empty)~span:not(:empty)]:before:shrink-0">8:29 PM · Jul 2, 2026124.3KViews

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span:not(:empty)~span:not(:empty)]:before:content-['·'] [&>span:not(:empty)~span:not(:empty)]:before:px-1 [&>span:not(:empty)~span:not(:empty)]:before:shrink-0 min-w-0 overflow-hidden">François Chollet

@fchollet

Jul 2

Does it mean LLMs / LRMs go away? Not at all. In the short term, they are still the best way to perform intuition guidance (codegen). In the long term, even if they become obsolete for reasoning itself, we will still need models of language in order to communicate with AI systems

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span:not(:empty)~span:not(:empty)]:before:content-['·'] [&>span:not(:empty)~span:not(:empty)]:before:px-1 [&>span:not(:empty)~span:not(:empty)]:before:shrink-0 min-w-0 overflow-hidden">François Chollet

@fchollet

Jul 2

Even right now, many workflows are morphing into LRM-guided harnessess that manipulate symbolic programs. Which is a crude, but currently-accessible form of symbolic learning.

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span:not(:empty)~span:not(:empty)]:before:content-['·'] [&>span:not(:empty)~span:not(:empty)]:before:px-1 [&>span:not(:empty)~span:not(:empty)]:before:shrink-0 min-w-0 overflow-hidden">François Chollet

@fchollet

Jul 2

Unsurprisingly, all of the strong contenders on ARC-AGI-3 so far use this type of approach.

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span:not(:empty)~span:not(:empty)]:before:content-['·'] [&>span:not(:empty)~span:not(:empty)]:before:px-1 [&>span:not(:empty)~span:not(:empty)]:before:shrink-0 min-w-0 overflow-hidden">Deniss Sīmanis

@imdsms

Jul 2

Sounds very similar to abstraction that Palantir keeps saying they already have: a layer/ontology which can translate any input to LLM without LLM knowing what it is solving

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François Chollet@fcholletFollow<br>Co-founder @ndea. Co-founder @arcprize. Creator of Keras and ARC-AGI. Author of 'Deep Learning with Python'.

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