Home Speakers Francois Chollet Quote Now LLMs have sucked the oxygen out of the room. Everyone is just doing LLMs. I see LLMs as more of an off-ramp on the path to AGI actually.
Words found on the source page on Nov 6, 2026.
More from Francois Chollet Blog OpenAI o3 Breakthrough High Score on ARC-AGI-Pub Dec 20, 2024
Passing 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. Blog OpenAI o3 Breakthrough High Score on ARC-AGI-Pub Dec 20, 2024
This is not merely incremental improvement, but a genuine breakthrough, marking a qualitative shift in AI capabilities compared to the prior limitations of LLMs. Blog OpenAI o3 Breakthrough High Score on ARC-AGI-Pub Dec 20, 2024
You'll know AGI is here when the exercise of creating tasks that are easy for regular humans but hard for AI becomes simply impossible. Podcast Dwarkesh Podcast: Why the biggest AI models can't solve simple puzzles Jun 11, 2024
I’m pretty skeptical that we’re going to see an LLM do 80% in a year. Podcast Dwarkesh Podcast: Why the biggest AI models can't solve simple puzzles Jun 11, 2024
OpenAI basically set back progress towards AGI by quite a few years, probably like 5-10 years. Podcast Dwarkesh Podcast: Why the biggest AI models can't solve simple puzzles Jun 11, 2024
The way LLMs work is that they’re basically this big interpolative memory.
On the same topics Blog The Specter Of Neuralese Sep 24, 2026
An AI with more real layers can actually be “smarter” in the conventional sense of the term. Blog The Specter Of Neuralese Sep 24, 2026
For 100 steps in a row, the AI can shoot delicate subtle ideas from layer to layer at the speed of light. Then there’s one step where it has to encode them into twenty-six glyphs invented by Phoenician turquoise miners in 1800 BC. Then it has to re-encode the Phoenician glyphs into delicate subtle lightspeed ideas before it can do anything else. Blog The Specter Of Neuralese Sep 24, 2026
The science of reading these thoughts is a subfield of AI interpretability, which is still in its infancy. Blog Mysteries Of AI Generalization Sep 23, 2026
This trains the AIs to be focused on task success, which naturally risks including things like reward-hacking, cheating, and single-minded pursuit of stated goals at the expense of ethical injunctions. Blog Why I still haven't bought into true RSI Sep 19, 2026
It is important to not confuse massive steps in inference-time scaling, a dynamic which should be fairly predictable, with being the outputs of RSI, which is highly uncertain. Podcast Dwarkesh Podcast: Agent swarms, alignment, and recursive self-improvement Sep 17, 2026
And actually the models today are far beyond what was possible even six months ago. About this quote Said by Francois Chollet, Creator of ARC-AGI, co-founder ARC Prize Where Dwarkesh Podcast: Why the biggest AI models can't solve simple puzzles Topics AGI , Research Company Source dwarkesh.com/p/francois-chollet A quote is one moment, not the whole argument. Read it in context at the source.
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