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Ilya Sutskever

Ilya Sutskever

Co-founder

Safe Superintelligence Inc.

researchopenaisafetydeep-learning

About Ilya Sutskever

Ilya Sutskever is a co-founder of Safe Superintelligence Inc. (SSI), focused on building safe superintelligent AI. He was previously co-founder and Chief Scientist at OpenAI, where he led research from 2015-2024. He is one of the co-inventors of AlexNet, the breakthrough that launched the deep learning revolution.

Career Highlights

  • Safe Superintelligence Inc. (2024-present): Co-founder
  • OpenAI (2015-2024): Co-founder and Chief Scientist
  • Google Brain (2013-2015): Research Scientist
  • AlexNet (2012): Co-inventor with Geoffrey Hinton and Alex Krizhevsky
  • PhD under Geoffrey Hinton: University of Toronto

Notable Positions

On the Scaling Era Ending

Sutskever believes pure scaling has run its course:

"Is the belief really that if you just 100x the scale everything would be transformed? I don't think that's true."

On Eval Performance vs Reality

"Models are much more like the first student - technically brilliant but lacking the 'it factor' that makes for actual capability."

On the Research Cycle

He frames AI history as oscillating eras:

"2012-2020 was research, 2020-2025 was scaling, and now we're returning to research."

Key Quotes

  • "The real reward hacking is human researchers too focused on evals."
  • "Models generalize dramatically worse than people - it's super obvious."
  • "Value functions might short-circuit the wait-until-completion problem."

Video Appearances

Eval vs real capability gap

Eval vs real capability gap

Models are like hyper-specialized competition students - 'they practiced 10,000 hours for competitive programming but lack the it factor that makes for actual capability.'

at 00:06:00

End of scaling era

End of scaling era

Is the belief really that if you just 100x the scale everything would be transformed? I don't think that's true. We're back in the age of research.

at 00:15:00

RL training limitations

RL training limitations

The real reward hacking is human researchers who are too focused on evals.

at 00:22:00

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