A Turing Award winner says the industry’s fix for running out of data is ‘a big mistake’
Richard Sutton thinks the AI industry’s answer to running out of training data is a mistake, and he has picked a blunt word for it. “
That’s just a big mistake,” he said of the turn to synthetic data on Sequoia Capital’s Training Data podcast, published on Tuesday and hosted by Sonya Huang and Pat Grady.
The remark carries more weight than most podcast soundbites. Sutton shared the 2024 Turing Award with Andrew Barto for founding reinforcement learning, wrote the 2019 essay The Bitter Lesson that half the field now quotes at the other half, and left John Carmack’s Keen Technologies in July to start his own lab.
His objection has two specific edges rather than a blanket verdict. “There’s no way we can have synthetic data for other people’s minds,” he said, and on simulating the physical world: “The world is infinitely complex, and any simulation of it is...
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