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Ilya Sutskever

What Ilya Sutskever thinks about reinforcement learning

@ilya-sutskever · 28 positions · On ppll ↗

Co-founder and chief scientist of Safe Superintelligence Inc., and previously co-founder and chief scientist of OpenAI.

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Only Ilya Sutskever on reinforcement learning. See everyone on reinforcement learning

4 dated positions, 2025, in their own words. Our reading of what Ilya Sutskever has said — not written or endorsed by them.

4 positions so far — this page is not yet offered to search engines.

  1. Our readingModels look far better on evals than they are in the world because researchers, inadvertently, take inspiration from the evals when they build RL environments.

    Their wordsAnd one of the one thing you could do, and I think that's something that is done inadvertently, is that people take inspiration from the evals.

    ↗Ilya Sutskever – We're moving from the age of scaling to the age of researchyoutube.com 1st of 28 in this recording

  3. Our readingValue functions only make reinforcement learning faster: anything you can do with one you can also do without it, just more slowly.

    Their wordsI want to like emphasize that I think the value function is something like it's going to make RL more efficient and I think that makes a difference but I think that anything you can do with a value function you can do without just more slowly.

    ↗Ilya Sutskever – We're moving from the age of scaling to the age of researchyoutube.com 7th of 28 in this recording

  5. Our readingModels resemble each other because pre-training is the same everywhere; what differentiates labs now is RL and post-training.

    scaling laws

    Their wordsSo the reason there has been no diversity I believe is because of pre-training. All the pre-trained models are the same pretty much because the pre-train on the same data.

    ↗Ilya Sutskever – We're moving from the age of scaling to the age of researchyoutube.com 26th of 28 in this recording

  7. Our readingSelf-play as it was done in the past is too narrow: it only ever develops a small set of skills like negotiation and strategising.

    Their wordsNow the the thing is that selfplay at least the way it was done in the past when you have agents which are somehow compete with each other it's only good for developing a certain set of skills it is too narrow.

    ↗Ilya Sutskever – We're moving from the age of scaling to the age of researchyoutube.com 27th of 28 in this recording