Developer Builds ChatGPT's Core Algorithm From Scratch in JAX

A developer is documenting their journey implementing reinforcement learning algorithms from scratch, with Day 8 covering PPO, the core of ChatGPT's RLHF training. The post explains PPO's clipping mechanism, which limits policy updates to 20% per step to prevent training instability. It also highlights three key additions over Actor-Critic: clipping, multiple epochs per batch, and an entropy bonus for exploration.