Embracing Reinforcement Learning
Rishabh shares his journey through various research areas before finding his passion in reinforcement learning (RL). He highlights the unique ability of RL agents to learn from their mistakes, paralleling human problem-solving. Additionally, he reflects on his early work in disambiguation and meta learning, illustrating the evolution of his interests in the field.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Deep Reinforcement Learning at the Edge of the Statistical Precipice with Rishabh Agarwal - #559
Related Questions
Is reinforcement learning a turning point for large language models (LLMs) and artificial intelligence (AI) as discussed in the episode Towards Abstract Robotic Understanding with Raja Chatila - #118 and the clip Understanding Reinforcement Learning?
Is reinforcement learning a turning point for large language models (LLMs) and artificial intelligence (AI) as discussed in the episode Ilya Sutskever (OpenAI Chief Scientist) - Building AGI, Alignment, Spies, Microsoft, & Enlightenment and the clip Reinforcement Learning Paradigm?