PPO
model-free reinforcement learning algorithm
What podcasters actually say about PPO.
6 mentions, no marketing. Save them all to a pod and ask any question.
Common Themes
Videos Mentioning PPO
Greg Brockman: OpenAI and AGI | Lex Fridman Podcast #17
Lex Fridman
Proximal Policy Optimization, a reinforcement learning algorithm developed by John Schulman, which OpenAI scaled up significantly for the Dota project, revealing emergent behaviors at larger scales.
What If We Stopped Using GPUs? | YC Paper Club
Y Combinator
A reinforcement learning algorithm used to train the AI for playing Doom with brain cells.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 15: Mid/Post-Training
Stanford Online
Proximal Policy Optimization, a reinforcement learning algorithm that aims to improve stability by using a clipping heuristic to discourage large policy changes. It's a key algorithm in RLHF.
Stanford CS329A Self-Improving AI Agents | Part 4 | Learning from Feedback with Tools/Code
Stanford Online
A reinforcement learning algorithm mentioned as being usable for the RLEF approach, particularly for updating the policy based on execution results.
Chelsea Finn: This is the State of the Art in Robotics
Y Combinator
Reinforcement learning algorithms used in language models that have scaled to enable complex reasoning.
Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 19: Model-Based RL
Stanford Online
Proximal Policy Optimization, a derivative of TRPO that simplifies implementation while maintaining policy stability and performance, widely used in reinforcement learning.