All talks listed in Pacific Time. Schedule subject to change.

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Coffee and Check-In
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Opening Remarks
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What neural machinery is needed for language acquisition (Virtual Talk)
Christos Papadimitriou (Columbia University)
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Break
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Language Models as World Models?
Jacob Andreas (MIT)
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Computation with sequences of neuronal assemblies
Max Dabagia (Georgia Tech)
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Lunch (on your own)
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Bridging the data gap between LLMs and children
Michael Frank (Stanford University)
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Learning to Reason, Insights from Language Modeling
Noah Goodman (Stanford University)
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Break
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How grounded are ungrounded LLM models
Trevor Darrell (UC Berkeley)
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Discussion (Lead: Jacob Andreas)
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Reception
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Coffee and Check-In
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Lightning Talks
Mirabel Reid (Georgia Tech), Paul Liang (Carnegie Mellon University)
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The Simplest Neural Models, and Neurally Plausible Algorithms for Language
Daniel Mitropolsky (Columbia University)
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KiVA: Kid-inspired Visual Analogies for Large Multimodal Models
Eunice Yiu (UC Berkeley)
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Break
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A comparative cognition approach to evaluating AI capabilities
Lucy Cheke (Cambridge)
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Lightning Talk: The Perception Test
Viorica Patraucean (Google DeepMind)
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Lunch (on your own)
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10 AIs or 10B AIs
Joao Carreira (Google DeepMind)
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Linguistic Interaction in Humans and Machines
Yoav Artzi (Cornell University)
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Break
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What can be passively learned about causality?
Andrew Lampinen (Google DeepMind)
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Discussion (Lead: Shiry Ginosar)
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Coffee and Check-In
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Educability (Virtual Talk)
Leslie Valiant (Harvard University)
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Break
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Cultural Evolution
Alison Gopnik (UC Berkeley)
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Social Behavior Prediction from Video Observations
Shiry Ginosar (UC Berkeley)
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Lunch (on your own)
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Retrospective on multi-agent learning as a path to intelligence
Igor Mordatch (Google DeepMind)
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Emerging interactions in humans and machines: from Social Physiology to Social Neuro-AI
Guillaume Dumas (CR-CHUSJ / Mila - Quebec AI Institute, University of Montreal)
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Break
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The First 1000 Days Project: A Novel Framework for Modeling Human Development
Uri Hasson (Princeton)
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The Development of Sociality in Language and Thought
Justine Cassell (Carnegie Mellon University & Inria Paris)
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Discussion (Lead: Uri Hasson)
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Coffee and Check-In
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What does it all mean anyway? Decoding ape communication. (Remote from the Ugandan forest)
Catherine Hobaiter (University of St. Andrews)
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We are (still!) not giving Data enough credit
Alexei (Alyosha) Efros
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Break
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A compositional code for dynamic scenes across the macaque brain (Not livestreamed or recorded)
Doris Tsao (UC Berkeley)
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AI and Emotions: opportunities and challenges
Àgata Lapedriza (Northeastern University)
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Lunch (on your own)
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LLMs as a cognitive model for natural lanaguge processing in the human brain
Uri Hasson (Princeton)
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Optimal flexible inference for behavior without generative world models
Daniel McNamee (Champalimaud Research)
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Lightning Talk
Jathushan Rajasegaran (BAIR)
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Break
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The distributed conceptual network in the human brain
Jack Gallant (UC Berkeley)
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Discussion (Lead: Jack Gallant)
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Coffee and Check-In
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Talk by
David Chalmers (NYU)
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AI Consciousness is Inevitable: A Theoretical Computer Science Perspective
Lenore Blum (Carnegie Mellon University)
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Break
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On the Hard Problem of Pain
Manuel Blum (Carnegie Mellon University)
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Lunch (on your own)
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How Can We Detect Consciousness in Infants?
Claudia Passos Ferreira (NYU)
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Quantitative research programs relating metacognition and consciousness
Megan Peters (UC Irvine)
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From Simulated Subjectivity to Collective Consciousness in Large Language Models
James Evans (University of Chicago)
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Break
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Coin-Flipping in the Brain: Probabilistic Computation and Learning in the Assembly Model
Santosh Vempala (Georgia Institute of Technology)
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Discussion (Lead: Lenore Blum)
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Closing Words