LLMs Empowering RL Agents
Hosted by Amir Feizpour and Matthew Taylor
Fri, Mar 21, 2025
4:00 PM UTC (45 minutes)
Virtual (Zoom)
Free to join
By continuing, you agree to Maven's Terms and Privacy Policy.
Go deeper with a course
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Fri, Mar 21, 2025
4:00 PM UTC (45 minutes)
Virtual (Zoom)
Free to join
Go deeper with a course
.jpeg&w=1536&q=75)
What you'll learn
How LLMs enhance RL agents' reasoning and adaptability.
How to build smarter agents for real-world applications.
Skills necessary to leverage RL + LLMs in use cases.
Why this topic matters
You'll learn from
Amir Feizpour
Founder @ Aggregate Intellect
Amir Feizpour is the founder, CEO, and Chief Scientist at Aggregate Intellect building a generative business brain for service and science based companies. Amir has built and grown a global community of 5000+ AI practitioners and researchers gathered around topics in AI research, engineering, product development, and responsibility. Prior to this, Amir was an NLP Product Lead at Royal Bank of Canada. Amir held a research position at University of Oxford conducting experiments on quantum computing resulting in high profile publications and patents. Amir holds a PhD in Physics from University of Toronto. Amir also serves the AI ecosystem as an advisor at MaRS Discovery District, works with several startups as fractional chief AI officer, and engages with a wide range of community audiences (business executives to hands-on developers) through training and educational programs. Amir leads Aggregate Intellect’s R&D via several academic collaborations.
Matthew Taylor
Professor of Computing Science at the University of Alberta
Dr. Matthew Taylor is a Fellow and Canada CIFAR AI Chair at Amii and a Professor of Computing Science at the University of Alberta. He is the Director of the Intelligent Robot Learning (IRL) Lab and a Principal Investigator at the Reinforcement Learning & Artificial Intelligence (RLAI) Lab, at the University of Alberta.
Taylor’s research focuses on developing intelligent agents, physical or virtual entities that interact with their environments. His main goals are to enable individual agents, and teams of agents, to learn tasks in real-world environments that are not fully known when the agents are designed. Current approaches that his teams are investigating include improving reinforcement learning through demonstrations, teaching reinforcement learning systems through action advice, and training agents with discrete human feedback.
Learn directly from Amir Feizpour and Matthew Taylor
By continuing, you agree to Maven's Terms and Privacy Policy.
By continuing, you agree to Maven's Terms and Privacy Policy.