Nature of Intelligence, Ep. 4: Babies vs Machines
There’s an argument to be made that if we train AI systems to learn the way babies do, we’ll get them closer to human-like intelligence. But how our own learning development functions in babyhood is still a mystery that researchers are untangling. We know that the information babies absorb is very different from how an LLM learns, and in today’s episode, with guests Linda Smith and Michael Frank we’ll attempt to look at the world through an infant’s eyes and examine why they’re able to do more with, seemingly, less information.
COMPLEXITY · Michael Frank, Linda Smith, Abha Eli Phoboo, Melanie Mitchell
Show Notes
Guests:
- Linda Smith, Distinguished Professor and Chancellor's Professor, Psychological and Brain Sciences, Department of Psychological and Brain Sciences, Indiana University Bloomington
- Michael Frank, Benjamin Scott Crocker Professor of Human Biology, Department of Psychology, Stanford University
Hosts: Abha Eli Phoboo & Melanie Mitchell
Producer: Katherine Moncure
Podcast theme music by: Mitch Mignano
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More info:
- Tutorial: Fundamentals of Machine Learning
- Lecture: Artificial Intelligence
- SFI programs: Education
Books:
- Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell
Talks:
- Why "Self-Generated Learning” May Be More Radical and Consequential Than First Appears by Linda Smith
- Children’s Early Language Learning: An Inspiration for Social AI, by Michael Frank at Stanford HAI
- The Future of Artificial Intelligence by Melanie Mitchell
Papers & Articles:
- “Curriculum Learning With Infant Egocentric Videos,” in NeurIPS 2023 (September 21)
- “The Infant’s Visual World The Everyday Statistics for Visual Learning,” by Swapnaa Jayaraman and Linda B. Smith, in The Cambridge Handbook of Infant Development: Brain, Behavior, and Cultural Context, Chapter 20, Cambridge University Press (September 26, 2020)
- “Can lessons from infants solve the problems of data-greedy AI?” in Nature (March 18, 2024), doi.org/10.1038/d41586-024-00713-5
- “Episodes of experience and generative intelligence,” in Trends in Cognitive Sciences (October 19, 2022), doi.org/10.1016/j.tics.2022.09.012
- “Baby steps in evaluating the capacities of large language models,” in Nature Reviews Psychology (June 27, 2023), doi.org/10.1038/s44159-023-00211-x
- “Auxiliary task demands mask the capabilities of smaller language models,” in COLM (July 10, 2024)
- “Learning the Meanings of Function Words From Grounded Language Using a Visual Question Answering Model,” in Cognitive Science (First published: 14 May 2024), doi.org/10.1111/cogs.13448