Soft label distillation entropy advantage
Distillation from soft targets provides far more bits per sample than one-hot labels because the entropy of a soft distribution is vastly higher.
Where this was said
Automated AI researchers
At 2:18:16 · chapter starts 2:16:16
Eric reports from his AlphaGo project: LLMs excel at hyperparameter tuning and executing experiments, but fail at lateral thinking — choosing the right question and recognizing dead-end research tracks. [1] — Eric Jang "LLMs can autonomously run experiments, tune hyperparameters, and optimize code. What they can't do: decide which question to investigate ne…" 2:14:00
Go as a Research Environment for AI
Go has a fast, unambiguous outer loop (win rate vs. KataGo) and contains subtasks that overlap with LLMs and robotics — distributed systems, hyperparameter search, hypothesis generation. It's a cheap, verifiable testbed for automated AI research.
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