Guests: <ul><li>Evelina Fedorenko, Associate Professor, Department of Brain and Cognitive Sciences, and Investigator, McGovern Institute for Brain Research, MIT</li><li>Steve Piantadosi, Professor of Psychology and Neuroscience, and Head of Computation and Language Lab, UC Berkeley</li><li>Gary Lupyan, Professor of Psychology, University of Wisconsin-Madison</li></ul>Hosts: Abha Eli Phoboo & Melanie MitchellProducer: Katherine MoncurePodcast theme music by: Mitch MignanoFollow us on:<a href="http://twitter.com/sfiscience">Twitter</a> • <a href="http://youtube.com/c/sfiscience">YouTube</a> • <a href="http://facebook.com/santafeinstitute">Facebook</a> • <a href="http://instagram.com/sfiscience">Instagram</a> • <a href="https://linkedin.com/company/20131/">LinkedIn</a>  • <a href="https://bsky.app/profile/sfiscience.bsky.social">Bluesky</a>More info:<ul><li>Tutorial: <a href="https://www.complexityexplorer.org/courses/81-fundamentals-of-machine-learning">Fundamentals of Machine Learning</a></li><li>Lecture: <a href="https://www.complexityexplorer.org/courses/108-lecture-artificial-intelligence/segments/10440?summary">Artificial Intelligence</a></li><li>SFI programs: <a href="https://www.santafe.edu/engage/learn/overview">Education</a></li></ul>Books: <ul><li>Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell</li><li>Developing Object Concepts in Infancy: An Associative Learning Perspective by Rakison, D.H., and G. Lupyan</li><li>Language and Mind by Noam Chomsky</li><li>On Language by Noam Chomsky</li></ul>Talks: <ul><li><a href="https://www.youtube.com/watch?v=GwHDAfAAKd4">The Future of Artificial Intelligence</a> by Melanie Mitchell</li><li><a href="https://www.youtube.com/watch?v=uE9AiYuCwdE">The language system in the human brain: Parallels & Differences with LLMs</a> by Evelina Federenko </li></ul>Papers & Articles:<ul><li>“<a href="https://www.cell.com/trends/cognitive-sciences/abstract/S1364-6613(24)00027-5?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1364661324000275%3Fshowall%3Dtrue">Dissociating language and thought in large language models</a>,” in Trends in Cognitive Science (March 19, 2024), doi: 10.1016/j.tics.2024.01.011</li><li>“The language network as a natural kind within the broader landscape of the human brain,” in Nature Reviews Neuroscience (April 12, 2024), <a href="https://doi.org/10.1038/s41583-024-00802-4">doi.org/10.1038/s41583-024-00802-4</a></li><li>“Visual grounding helps learn word meanings in low-data regimes,” in arXiv (v2 revised on 25 March 2024), <a href="https://doi.org/10.48550/arXiv.2310.13257">doi.org/10.48550/arXiv.2310.13257</a></li><li>“No evidence of theory of mind reasoning in the human language network,” in Cerebral Cortex (December 28, 2022), <a href="https://doi.org/10.1093/cercor/bhac505">doi.org/10.1093/cercor/bhac505</a></li><li>“Chapter 1: Modern language models refute Chomsky’s approach to language,” by Steve T. Piantadosi (v7, November 2023), <a href="https://lingbuzz.net/lingbuzz/007180">lingbuzz/007180</a></li><li>“Uniquely human intelligence arose from expanded information capacity,” in Nature Reviews Psychology (April 2, 2024), <a href="https://doi.org/10.1038/s44159-024-00283-3">doi.org/10.1038/s44159-024-00283-3</a></li><li>“Understanding the allure and pitfalls of Chomsky's acience,” Review by Gary Lupyan, in The American Journal of Psychology (Spring 2018), <a href="https://doi.org/10.5406/amerjpsyc.131.1.0112">doi.org/10.5406/amerjpsyc.131.1.0112</a></li><li>“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), </li><li>Published:18 June 2018, <a href="https://doi.org/10.1098/rstb.2017.0137">doi.org/10.1098/rstb.2017.0137</a></li><li>“Does vocabulary help structure the mind?” in <a href="https://onlinelibrary.wiley.com/doi/book/10.1002/9781119684527">Minnesota Symposia on Child Psychology: Human Communication: Origins, Mechanisms, and Functions</a> (February 27, 2021), <a href="https://doi.org/10.1002/9781119684527.ch6">doi.org/10.1002/9781119684527.ch6</a></li><li>“Use of superordinate labels yields more robust and human-like visual representations in convolutional neural networks,” in Journal of Vision (December 2021), <a href="https://doi.org/10.1167/jov.21.13.13">doi.org/10.1167/jov.21.13.13</a></li><li>“<a href="https://brussels.evolang.org/proceedings/papers/EvoLang13_paper_131.pdf">Appeals to ‘Theory of Mind’ no longer explain much in language evolution</a>,” by Justin Sulik and Gary Lupyan</li><li>“Effects of language on visual perception,” in Trends in Cognitive Sciences (October 1, 2020), <a href="https://doi.org/10.1016/j.tics.2020.08.005">doi.org/10.1016/j.tics.2020.08.005</a></li><li>“Is language-of-thought the best game in the town we live?” in Behavioral and Brain Sciences (September 28, 2023), <a href="https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/is-languageofthought-the-best-game-in-the-town-we-live/DF90CC63BBE54519FEF287401BD0A857">doi:10.1017/S0140525X23001814</a></li><li>“Can we distinguish machine learning from human learning?” in arXiv (October 8, 2019), <a href="https://doi.org/10.48550/arXiv.1910.03466">doi.org/10.48550/arXiv.1910.03466</a></li></ul>

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Nature of Intelligence, Ep. 2: The relationship between language and thought

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