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Sean Carroll | Wondery


Ever wanted to know how music affects your brain, what quantum mechanics really is, or how black holes work? Do you wonder why you get emotional each time you see a certain movie, or how on earth video games are designed? Then you’ve come to the right place. Each week, Sean Carroll will host conversations with some of the most interesting thinkers in the world. From neuroscientists and engineers to authors and television producers, Sean and his guests talk about the biggest ideas in science, philosophy, culture and much more.


Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas

The number of neurons in the human brain is comparable to the number of stars in the Milky Way galaxy. Unlike the stars, however, in the case of neurons the real action is in how they are directly connected to each other: receiving signals over synapses via their dendrites, and when appropriately triggered, sending signals down the axon to other neurons (glossing over some complications). So a major step in understanding the brain is to map its wiring diagram, or connectome: the complete map of those connections. For a human brain that's an intimidatingly complex challenge, but important advances have been made on tinier brains. We talk with Jeff Lichtman, a leader in brain mapping, to gauge the current state of progress and what it implies.

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Blog post with transcript: https://www.preposterousuniverse.com/podcast/2024/12/09/298-jeff-lichtman-on-the-wiring-diagram-of-the-brain/

Jeff Lichtman received an MD/PhD from Washington University in St. Louis. He is currently the Jeremy R. Knowles Professor of Molecular and Cellular Biology and Santiago Ramón y Cajal Professor of Arts and Sciences at Harvard University. He is co-inventor of the Brainbow system for imaging neurons. He is a member of the National Academy of Sciences.

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298 | Jeff Lichtman on the Wiring Diagram of the Brain

Living organisms seem exquisitely organized and complex, with features clearly adapted to serving certain functions needed to survive and procreate. Natural selection provides a compelling explanation for why that is so. But is there a bigger picture, a more general framework that explains the origin and evolution of functions and complexity in a world governed by uncaring laws of physics? I talk with planetary scientist and astrobiologist Michael Wong about how we can define what "functions" are and the role they play in the evolution of the universe.

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Blog post with transcript: https://www.preposterousuniverse.com/podcast/2024/12/16/299-michael-wong-on-information-function-and-the-origin-of-life/

Michael Wong received his Ph.D. in planetary science from Caltech. He is currently a Sagan Postdoctoral Fellow at the Carnegie Institution for Scienceʼs Earth & Planets Laboratory. He is in the process of co-authoring two books: A Missing Law: Evolution, Information, and the Inevitability of Cosmic Complexity with Robert M. Hazen, and a revised edition of Astrobiology: A Multidisciplinary Approach with Jonathan Lunine.

Web siteCarnegie web pageStrange New Worlds podcast • Wong et al. (2023), "
On the Roles of Function and Selection in Evolving Systems • ."
 • Wong and Prabhu (2023), "
Cells as the First Data Scientists • ."

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299 | Michael Wong on Information, Function, and the Origin of Life

It's the end of the year, and time for our annual holiday break here at Mindscape. But as usual, we wrap up with a Holiday Message. This year, inspired by Joni Mitchell's "Hits" and "Misses" albums, I go through my scientific papers and talk about some of my favorites -- some of which were hits, in terms of making an impact on subsequent research, and some of which were misses by that standard. But I love them all! It's an excuse to talk about process -- how papers come to be, from the initial informal idea to sitting down and doing the work.

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Blog post with transcript: https://www.preposterousuniverse.com/podcast/2024/12/23/holiday-message-hits-and-misses/

Here are links to the papers I discuss in the episode.

 • S.M. Carroll, G.B. Field and R. Jackiw, 1990, "Limits on A Lorentz and Parity-Violating Modification of Electrodynamics,'' 
Phys. Rev. D • 
41 • , 1231. [
pdf file • ; 
inSPIRE • ]
 • S.M. Carroll, E. Farhi and A.H. Guth, 1992, "An Obstacle to Building a Time Machine,'' 
Phys. Rev. Lett. • 
68 • , 263; Erratum: 
68 • , 3368. [
pdf file • ; 
inSPIRE • ]
 • S.M. Carroll, E. Farhi, A.H. Guth and K.D. Olum, 1994, "Energy-Momentum Restrictions on the Creation of Gott Time Machines,'' 
Phys. Rev. D • 
50 • , 6190; gr-qc/9404065. [
arXiv • ; 
pdf • ; 
inSPIRE • ]
 • S.M. Carroll, 1998, "Quintessence and the Rest of the World,'' 
Phys. Rev. Lett. • 
81 • , 3067; astro-ph/9806099. [
arXiv • ; 
pdf • ; 
inSPIRE • ]
 • S.M. Carroll, V. Duvvuri, M. Trodden, and M.S. Turner, 2003, "Is Cosmic Speed-Up Due to New Gravitational Physics?'' astro-ph/0306438. [
arXiv • ; 
pdf • ; 
inSPIRE • ]
 • S.M. Carroll and J. Chen, 2004, "Spontaneous Inflation and the Origin of the Arrow of Time'', hep-th/0410270. [
arXiv • , 
inSPIRE • ]
 • L. Ackerman, M.R. Buckley, S.M. Carroll, and M. Kamionkowski, 2008, "Dark Matter and Dark Radiation," arxiv:0807.5126. [
arXiv • ; 
pdf • ; 
inSPIRE • ]
 • S.M. Carroll, M.C. Johnson, and L. Randall, 2009, "Dynamical Compactification," arxiv:0904.3115. [
arXiv • ; 
pdf • ; 
inSPIRE • ]
 • C. Cao, S.M. Carroll, and S. Michalakis, 2016, "Space from Hilbert Space: Recovering Geometry from Bulk Entanglement," arxiv:1606.08444. [
arXiv • , 
inSPIRE • ]
 • C. Cao and S.M. Carroll, 2018, "Bulk Entanglement Gravity without a Boundary: Towards Finding Einstein's Equation in Hilbert Space," arxiv:1712.02803. [
arXiv • , 
inSPIRE • ]
 • N. Bao, S.M. Carroll, A. Chatwin-Davies, J. Pollack, and G. Remmen, 2017, “Branches of the Black Hole Wave Function Need Not Contain Firewalls," arxiv:1712.04955. [
arXiv • , 
inSPIRE • ]

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Holiday Message | Hits and Misses

A new year, and a new centennial -- 300 (regularly-numbered) episodes of Mindscape! Our tradition is to have a solo episode, and what better topic than the nature of time? Physicists and philosophers have so frequently suggested that time is some kind of illusion that it's become almost passé to believe that it might be fundamental. This is an issue where, despite the form of the question, physics has important things to say that most philosophers haven't yet caught up to. I will talk about ideas from quantum mechanics and quantum gravity that bear on the question of whether time is emergent or fundamental, and the implications of each possibility.

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Blog post with transcript: https://www.preposterousuniverse.com/podcast/2025/01/06/300-solo-does-time-exist/

Some of the papers discussed herein:

 • Carroll (2008), "
What If Time Really Exists? • "
 • Dyson, Kleban, and Susskind (2002), "
Disturbing Implications of a Cosmological Constant • ."
 • Albrecht and Sorbo (2004), "
Can the Universe Afford Inflation? • "
 • Boddy, Carroll, and Pollack (2014), "
De Sitter Space Without Dynamical Quantum Fluctuations • ."
 • Lloyd (2016), "
Decoherent Histories Approach to the Cosmological Measure Problem • ."
 • Page and Wootters (1983), "
Evolution Without Evolution: Dynamics Described by Stationary Observables • ."
 • Albrecht (1994), "
The Theory of Everything vs the Theory of Anything • ."
 • Albrecht and Iglesias (2007), "
The Clock Ambiguity and the Emergence of Physical Laws • ."

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300 | Solo: Does Time Exist?

Big data is ruling, or at least deeply infiltrating, all of modern existence. Unprecedented capacity for collecting and analyzing large amounts of data have given us a new generation of artificial intelligence models, but also everything from medical procedures to recommendation systems that guide our purchases and romantic lives. I talk with computer scientist Tina Elassi-Rad about how we can sift through all this data, make sure it is deployed in ways that align with our values, and how to deal with the political and social dangers associated with systems that are not always guided by the truth.

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Blog post with transcript: https://www.preposterousuniverse.com/podcast/2025/01/13/301-tina-eliassi-rad-on-al-networks-and-epistemic-instability/

Tina Eliassi-Rad received her Ph.D. in computer science from the University of Wisconsin-Madison. She is currently Joseph E. Aoun Chair of Computer Sciences and Core Faculty of the Network Science Institute at Northeastern University, External Faculty at the Santa Fe Institute, and External Faculty at the Vermont Complex Systems Center. She is a fellow of the Network Science Society, recipient of the Lagrange Prize, and was named one of the 100 Brilliant Women in AI Ethics.

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301 | Tina Eliassi-Rad on Al, Networks, and Epistemic Instability

Randomness plays an important role in the evolution of life (as my evil twin will tell you). But random doesn't mean arbitrary. Biological organisms are physical objects, after all, and subject to the same laws of physics as non-biological matter is. Those laws place constraints on how organisms can fulfill their basic functions of metabolism, reproduction, motility, and so on. Easy to say, but how can we turn this into quantitative understanding of actual organisms? Today I talk with physical biologist Chris Kempes about how physics can help us understand the size of organisms, their metabolisms, and features of major transitions in evolution.

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Blog post with transcript: https://www.preposterousuniverse.com/podcast/2025/01/20/302-chris-kempes-on-the-biophysics-of-evolution/

Chris Kempes received his Ph.D. in physical biology from the Massachusetts Institute of Technology. He is currently Professor and a member of the Science Steering Committee at the Santa Fe Institute. His research involves the origin of life and the constraints placed by physics on biological function and evolution.

Web siteSanta Fe Institute web pageGoogle Scholar publicationsOrigins of Life online course

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302 | Chris Kempes on the Biophysics of Evolution

A typical human lifespan is approximately three billion heartbeats in duration. Lasting that long requires not only intrinsic stability, but an impressive capacity for self-repair. Nevertheless, things do occasionally break down, and cancer is one of the most dramatic examples of such breakdown. Given that the body is generally so good at protecting itself, can we harness our internal security patrol - the immune system - to fight cancer? This is the hope of Nobel Laureate James Allison, who works on studying the structure and behavior of immune cells, and ways to coax them into fighting cancer. This approach offers hope of a way to combat cancer effectively, lastingly, and in a relatively gentle way.

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Blog post with transcript: https://www.preposterousuniverse.com/podcast/2025/01/27/303-james-p-allison-on-fighting-cancer-with-the-immune-system/

James P. Allison received his Ph.D. in biology from the University of Texas at Austin. He is currently Regental Professor and Chair of the Department of Immunology, the Olga Keith Wiess Distinguished University Chair for Cancer Research, Director of the Parker Institute for Cancer Research, and Director of the James P. Allison Institute at MD Anderson Cancer Center. He is the subject of the documentary film Jim Allison: Breakthrough. Among his numerous awards are the Breakthrough Prize in Life Sciences and the Nobel Prize in Physiology or Medicine.

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303 | James P. Allison on Fighting Cancer with the Immune System

Welcome to the February 2025 Ask Me Anything episode of Mindscape! These monthly excursions are funded by Patreon supporters (who are also the ones asking the questions). We take questions asked by Patreons, whittle them down to a more manageable number -- based primarily on whether I have anything interesting to say about them, not whether the questions themselves are good -- and sometimes group them together if they are about a similar topic. Enjoy!

Blog post with questions and transcript: https://www.preposterousuniverse.com/podcast/2025/02/03/ama-february-2025/

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303 | AMA | February 2025

It is a feature of many human activities - sports, cooking, music, interpersonal relations - that being able to do them well doesn't necessarily mean you can accurately describe how to do them well. Science is no different. Many successful scientists are not very good at explaining what goes into successful scientific practice. To understand that, it's necessary to study science in a scientific fashion. What kinds of scientists, in what kinds of collaborations, using what kinds of techniques, do well? I talk with James Evans, an expert on collective intelligence and the construction of knowledge, about how science really works.

Blog post with transcript: https://www.preposterousuniverse.com/podcast/2025/02/10/304-james-evans-on-innovation-consolidation-and-the-science-of-science/

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James Evans received his Ph.D. in Sociology from Stanford University. He is currently the Max Palevsky Professor of History and Civilizations, Director of Knowledge Lab, and Faculty Director of Computational Social Science at the University of Chicago; External Professor at the Santa Fe Institute; External Faculty at the Complexity Science Hub, Vienna; and Visiting Faculty Researcher at Google.

Knowledge Lab web siteUniversity of Chicago web pageGoogle scholar publications

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304 | James Evans on Innovation, Consolidation, and the Science of Science

The Trump administration, led by Elon Musk and his Department of Government Efficiency, has proposed sweeping cuts to spending on science research here in the US, in particular at the National Institutes of Health and the National Science Foundation. I explain a little about what is being cut and why these funds are important to scientific progress. I try, for what it's worth, to provide these explanations in a way that would be informative to those who generally favor cutting government waste in dramatic fashion.

Blog post with transcript: https://www.preposterousuniverse.com/podcast/2025/02/12/bonus-cuts-to-science-funding-and-why-they-matter/

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Indirect costs primerCuts to NIH indirect costsAppropriated funds are mandated by statuteProposed NSF cutsElon Musk doesn't understand indirect costsShrimp treadmill storyBribing foreign officialsDeleting NSA web pagesExecutive Orders are not lawsHistory of impoundments

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Bonus | Cuts to Science Funding and Why They Matter

Artificial intelligence is everywhere around us. Deep-learning algorithms are used to classify images, suggest songs to us, and even to drive cars. But the quest to build truly “human” artificial intelligence is still coming up short. Gary Marcus argues that this is not an accident: the features that make neural networks so powerful also prevent them from developing a robust common-sense view of the world. He advocates combining these techniques with a more symbolic approach to constructing AI algorithms.

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Gary Marcus received his Ph.D. in cognitive science from MIT. He is founder and CEO of Robust.AI, and was formerly a professor of psychology at NYU as well as founder of Geometric Intelligence. Among his books are Rebooting AI: Building Machines We Can Trust (with Ernest Davis).

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184 | Gary Marcus on Artificial Intelligence and Common Sense

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