Home Speakers Ilya Sutskever Quote But now that compute is big, compute is now very big, in some sense we are back to the age of research.
Words found on the source page on Nov 6, 2026.
More from Ilya Sutskever Podcast Dwarkesh Podcast: We're moving from the age of scaling to the age of research Nov 25, 2025
All the pre-trained models are pretty much the same because they pre-train on the same data. Podcast Dwarkesh Podcast: We're moving from the age of scaling to the age of research Nov 25, 2025
I think that’s been guiding me a fair bit, thinking from multiple angles and looking for almost beauty, beauty and simplicity. Podcast Dwarkesh Podcast: We're moving from the age of scaling to the age of research Nov 25, 2025
If you think about the term “AGI”, especially in the context of pre-training, you will realize that a human being is not an AGI. Podcast Dwarkesh Podcast: We're moving from the age of scaling to the age of research Nov 25, 2025
Number three, I think it would be really materially helpful if the power of the most powerful superintelligence was somehow capped because it would address a lot of these concerns. Podcast Dwarkesh Podcast: We're moving from the age of scaling to the age of research Nov 25, 2025
One consequence of the age of scaling is that scaling sucked out all the air in the room. Because scaling sucked out all the air in the room, everyone started to do the same thing. Podcast Dwarkesh Podcast: We're moving from the age of scaling to the age of research Nov 25, 2025
So for research, you definitely need some amount of compute, but it’s far from obvious that you need the absolutely largest amount of compute ever for research. Podcast Dwarkesh Podcast: We're moving from the age of scaling to the age of research Nov 25, 2025
So it’s back to the age of research again, just with big computers. Podcast Dwarkesh Podcast: We're moving from the age of scaling to the age of research Nov 25, 2025
The thing which I think is the most fundamental is that these models somehow just generalize dramatically worse than people.
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 Banning self-recursive improvement in AI models? Sep 22, 2026
If the top U.S. labs have to give up on what is supposed to be really important, they will look very “catchable.” The policy creates a big incentive for some other parts of the world to invest a lot more in compute. Blog Frontier Overhangs Sep 21, 2026
A world with sufficient compute is one where intelligence is a commodity, and in commodity markets margin comes from a superior cost structure, which I would expect the leading model providers to have, in part because they have a meaningful lead in scaling and can apply superior AI to their infrastructure. About this quote 
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