Get the latest tech news
Reinforcement learning, explained with a minimum of math and jargon
To create reliable agents, AI companies had to go beyond predicting the next token.
“Over the past week, developers around the world have begun building ‘autonomous agents’ that work with large language models (LLMs) such as OpenAI’s GPT-4 to solve complex problems,” Mark Sullivan wrote for Fast Company. In the process, I hope to give readers an intuitive understanding of how reinforcement learning helped to enable the new generation of agentic AI systems that began to appear in the second half of 2024. You’d need to convert every principle of good driving—including subtle considerations like following distances, taking turns at intersections, and when it’s OK to cross a double yellow line—into explicit mathematical formulas.
Or read this on Hacker News
