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- Dec 4, 202444 min
Nature of Intelligence, Ep. 6: AI’s changing seasons
Guest: Melanie Mitchell, Resident Professor, Santa Fe InstituteHosts: Abha Eli PhobooProducer: Katherine MoncurePodcast theme music by: Mitch MignanoFollow us on:Twitter • YouTube • Facebook • Instagram • LinkedIn • BlueskyMore info:Tutorial: Fundamentals of Machine LearningLecture: Artificial IntelligenceSFI programs: EducationCompetition: ARC PrizeBooks: Gödel, Escher, Bach: an Eternal Golden Braid by Douglas HofstadterArtificial Intelligence: A Guide for Thinking Humans by Melanie MitchellComplexity: A Guided Tour by Melanie MitchellTalks: The Future of Artificial Intelligence by Melanie MitchellIntroduction: AI and the Barrier of Meaning 2 by Melanie MitchellConceptual Abstraction and Analogy in Natural and Artificial Intelligence by Melanie MitchellPapers & 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
- Nov 20, 202448 min
Nature of Intelligence, Ep. 5: How do we assess intelligence?
Guests: Erica Cartmill, Professor, Anthropology and Cognitive Science, Indiana University BloomingtonEllie Pavlick, Assistant Professor, Computer Science and Linguistics, Brown UniversityHosts: 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: EducationDiverse Intelligences Summer InstituteBooks: Artificial Intelligence: A Guide for Thinking Humans by Melanie MitchellTalks: How do we know what an animal understands by Erica CartmillThe Future of Artificial Intelligence by Melanie MitchellPapers & 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
- Nov 6, 202438 min
Nature of Intelligence, Ep. 4: Babies vs Machines
Guests: Linda Smith, Distinguished Professor and Chancellor's Professor, Psychological and Brain Sciences, Department of Psychological and Brain Sciences, Indiana University BloomingtonMichael Frank, Benjamin Scott Crocker Professor of Human Biology, Department of Psychology, Stanford UniversityHosts: 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 MitchellTalks: Why "Self-Generated Learning” May Be More Radical and Consequential Than First Appears by Linda SmithChildren’s Early Language Learning: An Inspiration for Social AI, by Michael Frank at Stanford HAIThe Future of Artificial Intelligence by Melanie MitchellPapers & 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
- Oct 23, 202445 min
Nature of Intelligence, Ep. 3: What kind of intelligence is an LLM?
Guests: Tomer Ullman, Assistant Professor, Department of Psychology, Harvard UniversityMurray Shanahan, Professor of Cognitive Robotics, Department of Computing, Imperial College London; Principal Research Scientist, Google DeepMindHosts: 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 MitchellThe Technological Singularity by Murray ShanahanEmbodiment and the inner life: Cognition and Consciousness in the Space of Possible Minds by Murray ShanahanSolving the Frame Problem by Murray ShanahanSearch, Inference and Dependencies in Artificial Intelligence by Murray Shanahan and Richard SouthwickTalks: The Future of Artificial Intelligence by Melanie MitchellArtificial intelligence: A brief introduction to AI by Murray ShanahanPapers & 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
- Oct 9, 202437 min
Nature of Intelligence, Ep. 2: The relationship between language and thought
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 Behav
- Sep 25, 202443 min
Nature of Intelligence, Ep. 1: What is Intelligence
Guests: Alison Gopnik, SFI External Faculty; Professor of Psychology and Affiliate Professor of Philosophy at University of California, Berkeley; Member of Berkeley AI Research GroupJohn Krakauer, SFI External Faculty; John C. Malone Professor of Neurology, Neuroscience, and Physical Medicine & Rehabilitation, Johns Hopkins UniversityHosts: Abha Eli Phoboo & Melanie MitchellProducer: Katherine MoncurePodcast theme music by: Mitch MignanoPodcast logo by Nicholas GrahamFollow us on:Twitter • YouTube • Facebook • Instagram • LinkedIn • BlueskyMore info:Complexity Explorer: Tutorial: Fundamentals of Machine LearningLecture: Artificial IntelligenceSFI programs: EducationBooks: Artificial Intelligence: A Guide for Thinking Humans by Melanie MitchellWords, Thoughts and Theories by Alison Gopnik and Andrew N. MeltzoffThe Scientist in the Crib: Minds, Brains, and How Children Learn by Alison Gopnik, Andrew N. Meltzoff, and Patricia K. KuhlThe Philosophical Baby: What Children's Minds Tell Us About Truth, Love, and the Meaning of Life by Alison GopnikThe Gardener and the Carpenter: What the New Science of Child Development Tells Us About the Relationship Between Parents and Children by Alison GopnikTalks: The Future of Artificial Intelligence by Melanie MitchellImitation Versus Innovation: What Children Can Do That Large Langauge Models’ Can’t by Alison GopnikThe Minds of Children by Alison GopnikWhat Understanding Adds to Cambrian Intelligence: A Taxonomy by John KrakauerPapers & 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
- Sep 19, 20243 min
Trailer for The Nature of Intelligence
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?
- Apr 10, 202440 min
Physics of Life, Ep 6: Multiple worlds, containing multitudes
Guests: Heather Graham, Research Associate at NASA Goddard Space Flight CenterHosts: Abha Eli Phoboo & Chris KempesProducer: Katherine MoncurePodcast theme music by: Mitch MignanoAdditional sound credits: Digifish music; “Determination of Azimuth,” written by Heather Graham, staged at the Baltimore Rock Opera SocietyFollow us on:Twitter • YouTube • Facebook • Instagram • LinkedIn • BlueskyMore info:Apply for the 2024 Complexity Global School at Universidad de los Andes in Bogotá, ColombiaSFI programs: EducationComplexity Explorer: Origins of Life: Introduction| Chris Kempes (Link to full playlist)Enroll for the course: Origins of LifeVideos:Asteroids, Agnostic Biosignatures, & Experimental Rock Opera with Dr. Heather GrahamHeather Graham on Katherine JohnsonPapers & 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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