François Chollet

@francois-chollet · 8 positions · 2 changes of mind

Creator of the Keras deep-learning library and the ARC-AGI benchmark.

François Chollet did not write this page. We collected these quotes from things they published elsewhere, and every quote links to where it was said. They have no account here and have not endorsed this site. Quotes are word for word; the short line under each one is our own restatement, not their wording. Their own site. Is this you? Claim it or ask us to remove it.

27 Aug 2026

Our reading
In verifiable domains model capability scaling should remain unbounded, because the space of enumerable patterns is infinite by construction.

Their wordsIn verifiable domains, model capability scaling should remain unbounded. Models will simply keep improving by "absorbing more and more of the computational universe", which is infinite by construction.

↗@fchollet on Xx.com
4 days earlier
23 Aug 2026

Our reading
A growing fraction of social media is AI slop influencers being replied to by bots — an echo of an echo of an echo.

Their wordsAn increasing fraction of social media consists of slop influencers using AI to make posts and bots replying to them. An echo of an echo of an echo

↗@fchollet on Xx.com
4 days earlier
19 Aug 2026

Our reading
Calling today's economic effects "the Singularity" waters the term down past recognition; Vinge meant an event horizon beyond which nothing is imaginable.

Their wordsIncredible watering down -- the Singularity is now redefined to mean "the rate of new firm creation has increased somewhat" Vernor Vinge described the Singularity as an event horizon past which everything (e.g. what happens tomorrow) becomes entirely unimaginable and unpredictable to human understanding

↗@fchollet on Xx.com
9 days earlier
10 Aug 2026

Our reading
Coding is not just another application domain for AI; it is the meta-skill that lets AI generate its own training material and start the recursive self-improvement loop.

Their wordsCoding isn't yet another application domain -- it's the meta-skill required for AI to automatically develop its own training material, via symbolic world models. That's how the RSI loop actually kicks off.

↗@fchollet on Xx.com
3 days earlier
7 Aug 2026

Our reading
Future AI, say in fifteen years, will not be built on the LLM stack; it will have to move to symbolic learning.

Their wordsHowever, looking ahead, I still do not believe that future AI (say, in 15 years) will be based on the LLM stack. I believe it will necessarily have to move closer to its optimal, final form -- symbolic learning. Obviously this is a risky and contrarian belief -- the safe bet would be LRMs. But let's see.

↗@fchollet on Xx.com
7 Aug 2026

Our reading
Current AI techniques are four to six orders of magnitude away from optimal in data efficiency and test-time compute efficiency.

Their wordsI believe current techniques are 4-6 orders of magnitude away from optimality in terms of data efficiency and test-time compute efficiency. But far future AI will be near-optimal.

↗@fchollet on Xx.com
20 months earlier
20 Dec 2024

Our reading
Scaling the 2019-2023 recipe — same architecture, bigger model, more data — is not enough; further progress depends on new architectural ideas.

Their wordso3's improvement over the GPT series proves that architecture is everything. You couldn't throw more compute at GPT-4 and get these results. Simply scaling up the things we were doing from 2019 to 2023 -- take the same architecture, train a bigger version on more data -- is not enough.

↗OpenAI o3 Breakthrough High Score on ARC-AGI-Pubarcprize.org
20 Dec 2024

Our reading
Passing ARC-AGI does not amount to achieving AGI: o3 still fails on some very easy tasks, indicating fundamental differences from human intelligence.

Their wordsPassing ARC-AGI does not equate to achieving AGI, and, as a matter of fact, I don't think o3 is AGI yet. o3 still fails on some very easy tasks, indicating fundamental differences with human intelligence.

↗OpenAI o3 Breakthrough High Score on ARC-AGI-Pubarcprize.org

ARC-AGI