Episodes

  • Nature of Intelligence, Ep. 6: AI’s changing seasons
    Dec 4 2024

    Guest:

    • Melanie Mitchell, Resident Professor, Santa Fe Institute

    Hosts: Abha Eli Phoboo

    Producer: Katherine Moncure

    Podcast theme music by: Mitch Mignano

    Follow us on:
    Twitter • YouTube • Facebook • Instagram • LinkedIn • Bluesky

    More info:

    • Tutorial: Fundamentals of Machine Learning
    • Lecture: Artificial Intelligence
    • SFI programs: Education
    • Competition: ARC Prize

    Books:

    • Gödel, Escher, Bach: an Eternal Golden Braid by Douglas Hofstadter
    • Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell
    • Complexity: A Guided Tour by Melanie Mitchell

    Talks:

    • The Future of Artificial Intelligence by Melanie Mitchell
    • Introduction: AI and the Barrier of Meaning 2 by Melanie Mitchell
    • Conceptual Abstraction and Analogy in Natural and Artificial Intelligence by Melanie Mitchell

    Papers & Articles:

    • “The metaphors of artificial intelligence,” in Science (November 14, 2024), doi: 10.1126/science.adt6140
    • “Using counterfactual tasks to evaluate the generality of analogical reasoning in Large Language Models,” in arXiv (February 14, 2024), doi.org/10.48550/arXiv.2402.08955
    • “Comparing humans, GPT-4, and GPT-4V on abstraction and reasoning tasks, ” (Proceedings of the LLM-CP Workshop, AAAI 2024), arXiv (December 11, 2023), doi.org/10.48550/arXiv.2311.09247
    • “The debate over understanding in AI’s large language models,” in PNAS (March 21, 2023), doi.org/10.1073/pnas.2215907120
    • “The ConceptARC benchmark: evaluating understanding and generalization in the ARC domain,” in Transactions on Machine Learning Research (August 2023), arXiv (May 11, 2023), doi.org/10.48550/arXiv.2305.07141
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    44 mins
  • Nature of Intelligence, Ep. 5: How do we assess intelligence?
    Nov 20 2024

    Guests:

    • Erica Cartmill, Professor, Anthropology and Cognitive Science, Indiana University Bloomington
    • Ellie Pavlick, Assistant Professor, Computer Science and Linguistics, Brown University

    Hosts: Abha Eli Phoboo & Melanie Mitchell

    Producer: Katherine Moncure

    Podcast theme music by: Mitch Mignano

    Follow us on:
    Twitter • YouTube • Facebook • Instagram • LinkedIn • Bluesky

    More info:

    • Tutorial: Fundamentals of Machine Learning
    • Lecture: Artificial Intelligence
    • SFI programs: Education
    • Diverse Intelligences Summer Institute

    Books:

    • Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell

    Talks:

    • How do we know what an animal understands by Erica Cartmill
    • The Future of Artificial Intelligence by Melanie Mitchell

    Papers & Articles:

    • “Just kidding: the evolutionary roots of playful teasing,” in Biology Letters (September 23, 2020), doi.org/10.1098/rsbl.2020.0370
    • “Overcoming bias in the comparison of human language and animal communication,” in PNAS (November 13, 2023), doi.org/10.1073/pnas.22187991
    • “Using the senses in animal communication,” by Erica Cartmill, in A New Companion to Linguistic Anthropology, Chapter 20, Wiley Online Library (March 21, 2023)
    • “Symbols and grounding in large language models,” in Philosophical Transactions of the Royal Society A (June 5, 2023), doi.org/10.1098/rsta.2022.0041
    • “Emergence of abstract state representations in embodied sequence modeling,” in arXiv (November 7, 2023), doi.org/10.48550/arXiv.2311.02171
    • “How do we know how smart AI systems are,” in Science (July 13, 2023), doi: 10.1126/science.adj59
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    48 mins
  • Nature of Intelligence, Ep. 4: Babies vs Machines
    Nov 6 2024

    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

    Follow us on:
    Twitter • YouTube • Facebook • Instagram • LinkedIn • Bluesky

    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
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    39 mins
  • Nature of Intelligence, Ep. 3: What kind of intelligence is an LLM?
    Oct 23 2024

    Guests:

    • Tomer Ullman, Assistant Professor, Department of Psychology, Harvard University
    • Murray Shanahan, Professor of Cognitive Robotics, Department of Computing, Imperial College London; Principal Research Scientist, Google DeepMind

    Hosts: Abha Eli Phoboo & Melanie Mitchell

    Producer: Katherine Moncure

    Podcast theme music by: Mitch Mignano

    Follow us on:
    Twitter • YouTube • Facebook • Instagram • LinkedIn • Bluesky

    More info:

    • Tutorial: Fundamentals of Machine Learning
    • Lecture: Artificial Intelligence
    • SFI programs: Education

    Books:

    • Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell
    • The Technological Singularity by Murray Shanahan
    • Embodiment and the inner life: Cognition and Consciousness in the Space of Possible Minds by Murray Shanahan
    • Solving the Frame Problem by Murray Shanahan
    • Search, Inference and Dependencies in Artificial Intelligence by Murray Shanahan and Richard Southwick

    Talks:

    • The Future of Artificial Intelligence by Melanie Mitchell
    • Artificial intelligence: A brief introduction to AI by Murray Shanahan

    Papers & Articles:

    • “A Conversation With Bing’s Chatbot Left Me Deeply Unsettled,” in New York Times (Feb 16, 2023)
    • “Bayesian Models of Conceptual Development: Learning as Building Models of the World,” in Annual Review of Developmental Psychology Volume 2 (Oct 26, 2020), doi.org/10.1146/annurev-devpsych-121318-084833
    • “Comparing the Evaluation and Production of Loophole Behavior in Humans and Large Language Models,” in Findings of the Association for Computational Linguistics (December 2023), doi.org/10.18653/v1/2023.findings-emnlp.264
    • “Role play with large language models,” in Nature (Nov 8, 2023), doi.org/10.1038/s41586-023-06647-8
    • “Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks,” arXiv (v5, March 14, 2023), doi.org/10.48550/arXiv.2302.08399
    • “Talking about Large Language Models,” in Communications of the ACM (Feb 12, 2024),
    • “Simulacra as Conscious Exotica,” in arXiv (v2, July 11, 2024), doi.org/10.48550/arXiv.2402.12422
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    45 mins
  • Nature of Intelligence, Ep. 2: The relationship between language and thought
    Oct 9 2024
    Guests: Evelina Fedorenko, Associate Professor, Department of Brain and Cognitive Sciences, and Investigator, McGovern Institute for Brain Research, MITSteve Piantadosi, Professor of Psychology and Neuroscience, and Head of Computation and Language Lab, UC BerkeleyGary Lupyan, Professor of Psychology, University of Wisconsin-MadisonHosts: Abha Eli Phoboo & Melanie MitchellProducer: Katherine MoncurePodcast theme music by: Mitch MignanoFollow us on:Twitter • YouTube • Facebook • Instagram • LinkedIn • BlueskyMore info:Tutorial: Fundamentals of Machine LearningLecture: Artificial IntelligenceSFI programs: EducationBooks: Artificial Intelligence: A Guide for Thinking Humans by Melanie MitchellDeveloping Object Concepts in Infancy: An Associative Learning Perspective by Rakison, D.H., and G. LupyanLanguage and Mind by Noam ChomskyOn Language by Noam ChomskyTalks: The Future of Artificial Intelligence by Melanie MitchellThe language system in the human brain: Parallels & Differences with LLMs by Evelina Federenko Papers & Articles:“Dissociating language and thought in large language models,” in Trends in Cognitive Science (March 19, 2024), doi: 10.1016/j.tics.2024.01.011“The language network as a natural kind within the broader landscape of the human brain,” in Nature Reviews Neuroscience (April 12, 2024), doi.org/10.1038/s41583-024-00802-4“Visual grounding helps learn word meanings in low-data regimes,” in arXiv (v2 revised on 25 March 2024), doi.org/10.48550/arXiv.2310.13257“No evidence of theory of mind reasoning in the human language network,” in Cerebral Cortex (December 28, 2022), doi.org/10.1093/cercor/bhac505“Chapter 1: Modern language models refute Chomsky’s approach to language,” by Steve T. Piantadosi (v7, November 2023), lingbuzz/007180“Uniquely human intelligence arose from expanded information capacity,” in Nature Reviews Psychology (April 2, 2024), doi.org/10.1038/s44159-024-00283-3“Understanding the allure and pitfalls of Chomsky's acience,” Review by Gary Lupyan, in The American Journal of Psychology (Spring 2018), doi.org/10.5406/amerjpsyc.131.1.0112“Language is more abstract than you think, or, why aren’t languages more iconic?” in Philosophical Transactions of the Royal Society B (June 18, 2018), Published:18 June 2018, doi.org/10.1098/rstb.2017.0137“Does vocabulary help structure the mind?” in Minnesota Symposia on Child Psychology: Human Communication: Origins, Mechanisms, and Functions (February 27, 2021), doi.org/10.1002/9781119684527.ch6“Use of superordinate labels yields more robust and human-like visual representations in convolutional neural networks,” in Journal of Vision (December 2021), doi.org/10.1167/jov.21.13.13“Appeals to ‘Theory of Mind’ no longer explain much in language evolution,” by Justin Sulik and Gary Lupyan“Effects of language on visual perception,” in Trends in Cognitive Sciences (October 1, 2020), doi.org/10.1016/j.tics.2020.08.005“Is language-of-thought the best game in the town we live?” in Behavioral and Brain Sciences (September 28, 2023), doi:10.1017/S0140525X23001814“Can we distinguish machine learning from human learning?” in arXiv (October 8, 2019), doi.org/10.48550/arXiv.1910.03466
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    38 mins
  • Nature of Intelligence, Ep. 1: What is Intelligence
    Sep 25 2024


    Guests:

    • Alison Gopnik, SFI External Faculty; Professor of Psychology and Affiliate Professor of Philosophy at University of California, Berkeley; Member of Berkeley AI Research Group
    • John Krakauer, SFI External Faculty; John C. Malone Professor of Neurology, Neuroscience, and Physical Medicine & Rehabilitation, Johns Hopkins University

    Hosts: Abha Eli Phoboo & Melanie Mitchell

    Producer: Katherine Moncure

    Podcast theme music by: Mitch Mignano

    Podcast logo by Nicholas Graham

    Follow us on:
    Twitter • YouTube • Facebook • Instagram • LinkedIn • Bluesky

    More info:

    Complexity Explorer:

    Tutorial: Fundamentals of Machine Learning

    Lecture: Artificial Intelligence

    SFI programs: Education

    Books:

    • Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell
    • Words, Thoughts and Theories by Alison Gopnik and Andrew N. Meltzoff
    • The Scientist in the Crib: Minds, Brains, and How Children Learn by Alison Gopnik, Andrew N. Meltzoff, and Patricia K. Kuhl
    • The Philosophical Baby: What Children's Minds Tell Us About Truth, Love, and the Meaning of Life by Alison Gopnik
    • The Gardener and the Carpenter: What the New Science of Child Development Tells Us About the Relationship Between Parents and Children by Alison Gopnik

    Talks:

    • The Future of Artificial Intelligence by Melanie Mitchell
    • Imitation Versus Innovation: What Children Can Do That Large Langauge Models’ Can’t by Alison Gopnik
    • The Minds of Children by Alison Gopnik
    • What Understanding Adds to Cambrian Intelligence: A Taxonomy by John Krakauer

    Papers & Articles:

    • “Why you can’t make a computer that feels pain,” by Daniel C. Dennett
    • “Transmission versus truth, imitation versus innovation: What children can do that Large Language and Language-and-Vision models cannot (yet),” in Perspectives on Psychological Science (October 26, 2023), doi.org/10.1177/17456916231201401
    • “Empowerment as Causal Learning, Causal Learning as Empowerment: A bridge between Bayesian causal hypothesis testing and reinforcement learning,” by Alison Gopnik
    • “What can AI Learn from Human Exploration? Intrinsically-Motivated Humans and Agents in Open-World Exploration” by Yuqing Du et al, for Workshop: Agent Learning in Open-Endedness Workshop, NeurIPS 2024 conference
    • “Two views on the cognitive brain,” by David L. Barack & John W. Krakauer, Perspectives in Nature Reviews Neuroscience Vol 22 (April 15, 2021)
    • “The intelligent reflex,” by John W. Krakauer, Philosophical Psychology (May 23, 2019), doi.org/10.1080/09515089.2019.1607281
    • “Representation in Cognitive Science by Nicholas Shea: But Is It Thinking? The Philosophy of Representation Meets Systems Neuroscience” by John W. Krakauer
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    43 mins
  • Trailer for The Nature of Intelligence
    Sep 19 2024
    Right now, AI is having a moment — and it’s not the first time grand predictions about the potential of machines are being made. But, what does it really mean to say something like ChatGPT is “intelligent”? What exactly is intelligence? In this season of the Complexity podcast, The Nature of Intelligence, we'll explore this question through conversations with cognitive and neuroscientists, animal cognition researchers, and AI experts in six episodes. Together, we'll investigate the complexities of human intelligence, how it compares to that of other species, and where AI fits in. We'll dive into the relationship between language and thought, examine AI's limitations, and ask: Could machines ever truly be like us?
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    3 mins
  • Physics of Life, Ep 6: Multiple worlds, containing multitudes
    Apr 10 2024

    Guests:

    • Heather Graham, Research Associate at NASA Goddard Space Flight Center

    Hosts: Abha Eli Phoboo & Chris Kempes

    Producer: Katherine Moncure

    Podcast theme music by: Mitch Mignano

    Additional sound credits: Digifish music; “Determination of Azimuth,” written by Heather Graham, staged at the Baltimore Rock Opera Society

    Follow us on:
    Twitter • YouTube • Facebook • Instagram • LinkedIn • Bluesky

    More info:

    Apply for the 2024 Complexity Global School at Universidad de los Andes in Bogotá, Colombia

    SFI programs: Education

    • Complexity Explorer: Origins of Life: Introduction| Chris Kempes (Link to full playlist)
    • Enroll for the course: Origins of Life

    Videos:

    • Asteroids, Agnostic Biosignatures, & Experimental Rock Opera with Dr. Heather Graham
    • Heather Graham on Katherine Johnson

    Papers & Articles:

    • “Investigating the impact of x‐ray computed tomography imaging on soluble organic matter in the Murchison meteorite: Implications for Bennu sample analyses” in Meteoritics & Planetary Science (December 2023), doi.org/10.1111/maps.14111
    • “The Vacant Niche Revisited: Using Negative Results to Refine the Limits of Habitability,” in bioRxiv (Nov 8, 2023), doi.org/10.1101/2023.11.06.565904
    • “Observations of Elemental Composition of Enceladus Consistent with Generalized Models of Theoretical Ecosystems,” in bioRxiv (Oct 29, 2023), doi.org/10.1101/2023.10.29.564608
    • “Planetary Subsurface Science and Exploration: An Integrated Consortium to Understand Subsurface Sources of Energy and the Unique Energetics of Subsurface Life,” in Mars Extant Life: What’s Next? (Nov 2019), hou.usra.edu/meetings/lifeonmars2019/pdf/5047.pdf
    • “Detecting life on Earth and the limits of analogy,” in Planetary Astrobiology (June 16, 2020)
    • “Identifying molecules as biosignatures with assembly theory and mass spectrometry,” in chemRxiv (Nov 16, 202), chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/60c751e59abda27c1af8dce4/original/identifying-molecules-as-biosignatures-with-assembly-theory-and-mass-spectrometry.pdf
    • “The Grayness of the Origin of Life,” in Life (May 29, 2021) doi.org/10.3390/life11060498
    • “Generalized stoichiometry and biogeochemistry for astrobiological applications,” in Bulletin of Mathematical Biology (July 2021), link.springer.com/article/10.1007/s11538-021-00877-5
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    41 mins