Chollet on AI: Pattern Sponge and the Unbounded Scaling in Verifiable Domains
fchollet · x · 2026-08-28
Francois Chollet offers a perspective that current AI acts as a "sponge for patterns," absorbing and operationalizing patterns it is exposed to. He argues that once the complete space of patterns in a domain can be programmatically enumerated, saturating the domain becomes purely a matter of computational resources. Consequently, in verifiable domains, model capability scaling should remain unbounded, as models improve by absorbing more of the infinite computational universe.
Related event: Chollet: AI Shows Superhuman Skill, Not Intelligence(4 posts)→
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