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John Schulman Says User Data Likely Plays a Limited Role in Frontier Model Gains
What happened
John Schulman says training on user data is exceedingly unlikely to contribute much to frontier models’ math gains, which he attributes to scaling pretraining and RLVR. He says user data may instead help identify failure modes that hired annotators cannot easily recreate, and calls for stronger disclosure norms about how companies train on user data and what capabilities they aim to improve.
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