REINFORCEMENT LEARNING, EXPLAINED WITH A MINIMUM OF MATH AND JARGON

Summary from the TLDR AI newsletter

Reinforcement learning (RL) teaches AI models through trial and error rather than just copying human examples, allowing them to learn from mistakes and stay focused on complex tasks. Although RL has always been a part of training LLMs, companies have recently started using two new approaches to scale up the amount of data available: using AI models to grade another AI model's outputs and creating specialized environments for tasks with verifiably correct outcomes, like coding or math.