Today, Georgia Tech PhD student Alex Havrilla joins us to talk about “Teaching Large Language Models to Reason with Reinforcement Learning.” In addition to exploring the potential offered by bringing reinforcement learning algorithms to the problem of enhancing reasoning in large language models, Alex talks on the importance of creativity and exploration in problem solving. In addition, Alex discusses his studies on how noise affects language model training, emphasizing the resilience of LLM architecture. Lastly, we explore RL’s future and how merging language models with conventional techniques can lead to more reliable AI reasoning.
