The VII AMMCS International Conference
Waterloo, Ontario, Canada | August 17-21, 2026
AMMCS 2026 ALife Conference Plenary Speaker
Open-Ended, Quality Diversity, and AI-Generating Algorithms in the Era of Foundation Models
Jeff Clune, University of British Columbia
Tuesday, August 18, 13:30-14:30, Room: LH100
Foundation models (e.g. large language models) create exciting new opportunities in our longstanding quests to produce open-ended and AI-generating algorithms, wherein agents can truly keep innovating and learning forever. In this talk, I will introduce quality diversity, open-ended, and AI-generating algorithms and share some of our recent work harnessing the power of foundation models to unleash their potential. I will cover our recent work including OMNI (Open-endedness via Models of human Notions of Interestingness), Video Pre-Training (VPT), Automatically Designing Agentic Systems (ADAS), the Darwin G¨odel Machine, Hyperagents, and The AI Scientist.
Jeff Clune is a Professor of Computer Science at the University of British Columbia, a Canada CIFAR AI Chair at the Vector Institute, and a co-founder of Recursive. Jeff focuses on deep learning, including deep reinforcement learning. Previously he was a Senior Research Advisor to DeepMind, a research manager at OpenAI, a Senior Research Manager and founding member of Uber AI Labs (formed after Uber acquired a startup he helped lead), the Harris Associate Professor in Computer Science at the University of Wyoming, and a Research Scientist at Cornell University. He received degrees from Michigan State University (PhD, master's) and the University of Michigan (bachelor's). More on Jeff's research can be found at JeffClune.com or on Twitter (@jeffclune).
Since 2015, he won the Presidential Early Career Award for Scientists and Engineers from the White House, had two papers in Nature, one in Science, and one in PNAS, won an NSF CAREER award, received Outstanding Paper of the Decade and Distinguished Young Investigator awards, received two Test of Time awards, and had best paper awards, oral presentations, and invited talks at the top machine learning conferences (NeurIPS, CVPR, ICLR, and ICML). His research is regularly covered in the press, including the New York Times, NPR, the New Yorker, CNN, NBC, Wired, the BBC, the Economist, Science, Nature, National Geographic, the Atlantic, and the New Scientist.