Listen "Ian Osband"
Episode Synopsis
Ian Osband is a Research scientist at OpenAI (ex DeepMind, Stanford) working on decision making under uncertainty. We spoke about: - Information theory and RL - Exploration, epistemic uncertainty and joint predictions - Epistemic Neural Networks and scaling to LLMs Featured References Reinforcement Learning, Bit by Bit Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen From Predictions to Decisions: The Importance of Joint Predictive Distributions Zheng Wen, Ian Osband, Chao Qin, Xiuyuan Lu, Morteza Ibrahimi, Vikranth Dwaracherla, Mohammad Asghari, Benjamin Van Roy Epistemic Neural Networks Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy Approximate Thompson Sampling via Epistemic Neural Networks Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Morteza Ibrahimi, Xiuyuan Lu, Benjamin Van Roy Additional References Thesis defence, Ian Osband Homepage, Ian Osband Epistemic Neural Networks at Stanford RL Forum Behaviour Suite for Reinforcement Learning, Osband et al 2019 Efficient Exploration for LLMs, Dwaracherla et al 2024
More episodes of the podcast TalkRL: The Reinforcement Learning Podcast
Danijar Hafner on Dreamer v4
09/11/2025
Jake Beck, Alex Goldie, & Cornelius Braun on Sutton's OaK, Metalearning, LLMs, Squirrels @ RLC 2025
19/08/2025
Thomas Akam on Model-based RL in the Brain
03/08/2025
NeurIPS 2024 - Posters and Hallways 3
09/03/2025
NeurIPS 2024 - Posters and Hallways 2
04/03/2025
ZARZA We are Zarza, the prestigious firm behind major projects in information technology.