Glossary · Term

PPO

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Definition

Plain language

The standard reinforcement-learning algorithm used to fine-tune most modern AI assistants.

As stated in the literature

Proximal Policy Optimization, a clipped-objective policy-gradient method that underlies many modern RLHF pipelines.

Why it matters: Its stability is what made large-scale RLHF practical, and most production assistants today were tuned with some PPO variant.

For example, PPO clips each update so the new policy can't drift too far from the old one in a single training step.

Heard on the show

“They use PPO — an actual, standard reinforcement learning algorithm.”
Episode 163 — Why Training Only on Perfect Solutions Cripples a Model's Reasoning

Mentioned in 6 episodes

  1. 163
    Why Training Only on Perfect Solutions Cripples a Model's Reasoning
  2. 119
    Beating Reinforcement Learning Without Ever Touching the Model's Weights
  3. 090
    How MiniMax-M2 Bets That Sparsity Plus Verifiable Rewards Can Match Frontier Agents
  4. 026
    What RL Actually Does to Language Models, at the Token Level
  5. 025
    The Missing Gradient Term That Predicts Sycophancy in RLHF
  6. 010
    When Reward Climbs But Reasoning Goes Generic: Diagnosing Template Collapse in Agentic RL

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