632nm

Misha Shalaginov, Michael Dubrovsky, Xinghui Yin
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  • NATURAL SCIENCES
  • TWICE MONTHLY

Technical interviews with the greatest scientists in the world.

  1. 10 HR AGO

    The Real Economics of Data Centers in Space | Starcloud CEO Philip Johnston

    Are data centers in space physically possible, or just another overhyped idea? In this episode, we speak with Philip Johnston, CEO of Starcloud, about the technical and economic case for putting AI infrastructure in orbit. The idea has gone viral in recent months, drawing strong criticism from science communicators like Scott Manley, Kyle Hill, and Hank Green, but rarely with detailed engagement on the underlying assumptions. We examine whether space-based data centers can compete with terrestrial infrastructure, and what constraints actually matter: energy generation, cooling, launch costs, and manufacturing at scale. Johnston walks through the core economic model behind Starcloud, including assumptions about SpaceX’s Starship, the cost of solar power in orbit, and why removing terrestrial constraints like land use, permitting, and energy storage could fundamentally change how compute is deployed. We discuss the physics of radiative cooling in space, the challenges of operating GPUs in a radiation environment, and how orbital systems compare to Earth-based data centers in terms of efficiency and cost structure. The conversation also explores broader questions around AI’s growing energy demands, the limits of terrestrial infrastructure, and whether shifting compute off-world is a niche solution or a long-term inevitability. Whether you’re interested in space technology, AI infrastructure, energy systems, or the economics of large-scale computing, this episode offers a detailed look at one of the most debated ideas in modern engineering, and a rare opportunity to hear its strongest arguments laid out in full. Follow us for more technical interviews with the world’s greatest scientists:Twitter: https://x.com/632nmPodcastInstagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==LinkedIn: https://www.linkedin.com/company/632nm/about/Substack: https://632nmpodcast.substack.com/ Follow our hosts!Mikhail Shalaginov: https://www.linkedin.com/in/mikhail-shalaginov/Michael Dubrovsky: https://x.com/MikeDubrovskyXinghui Yin: https://x.com/XinghuiYin Subscribe:Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: https://www.632nm.com Timestamps:00:00 - Intro01:12 - What is Starcloud?02:44 - Why do data centers need to go to space?06:15 - Can’t we just build more solar panels on earth?11:10 - Economic analysis of Starcloud19:56 - How does Starcloud’s cooling work?28:26 - Training an LLM in space32:07 - Addressing critics on space Twitter34:23 - Is Starcloud overfunded?35:59 - Will demand for data centers keep going up?38:11 - GPU lifespan and disposal in space39:47 - Bus structures41:43 - Starcloud’s origin and founders49:29 - Fundraising, Competition, and Meeting Expectations53:29 - Satellite size and collisions56:29 - Manufacturing Bottlenecks1:00:20 - Starcloud 1 tests1:01:57 - Acceleration after YC1:03:43 - Testing on Earth1:05:06 - Motivations for Starcloud1:06:45 - Data centers on the Moon1:08:12 - Interacting with AI companies1:08:18 - What’s next for Starcloud?1:14:01 - Other uses for Starcloud satellites1:17:56 - Lunar hotels and space elevators1:24:28 - Complementary business ideas to Starcloud1:29:51 - Philip’s competitive twin1:32:18 - Philip and Mike’s thoughts on YC1:34:45 - Advice for young entrepreneurs #datacenter #aidatacenter #starlink #spacex #falcon9 #starcloud

    1hr 38min

  2. 5 DAYS AGO

    How To Make Quantum Algorithms Cheaper | Craig Gidney on Magic-State Factories, Resource Estimates

    How do you actually make quantum algorithms work on real hardware? Build your own quantum circuits in Crumble: https://algassert.com/crumble In this episode, we speak with Craig Gidney of Google Quantum AI, whose work focuses on the practical realities of building fault-tolerant quantum computers. Gidney explains how seemingly small implementation choices, like how you perform arithmetic, can dominate the cost of entire quantum algorithms. We explore why factoring small numbers like 15 in Shor's algorithm can be misleadingly easy, and why scaling to larger numbers requires dramatically more resources due to operations like modular multiplication. He breaks down how quantum circuits are often dominated by classical reversible logic, and why optimizing these routines is critical for making quantum computing viable. The conversation covers quantum error correction, including why T gates are especially expensive, how magic state factories works, and how different hardware architectures change what “cost” even means. Gidney also explains how resource estimates for breaking cryptography have dropped by orders of magnitude and what drove those improvements. We also dive into the tools he built, including Stim, Quirk, and Crumble, which help researchers simulate noise, visualize circuits, and track how errors propagate through complex systems. Gidney shares his unconventional path into the field, the role of intuition and tooling in discovery, and how software engineering shapes modern quantum research. Whether you’re interested in quantum computing, error correction, cryptography, or the engineering challenges behind scalable quantum systems, this episode offers a clear and grounded look at what it really takes to turn quantum algorithms into reality. Follow us for more technical interviews with the world’s greatest scientists:Twitter: https://x.com/632nmPodcastInstagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==LinkedIn: https://www.linkedin.com/company/632nm/about/Substack: https://632nmpodcast.substack.com/ Follow our hosts!Mikhail Shalaginov: https://www.linkedin.com/in/mikhail-shalaginov/Yudong Cao: https://www.linkedin.com/in/yudong-cao-25b6a929/ Subscribe:Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: https://www.632nm.com Timestamps:00:00 - Intro01:22 - Shor’s Algorithm04:02 - Why are Arithmetic Operations Important?08:35 - Why are T-Gates Important for QEC?13:47 - Motivations for Creating Crumble and STIM18:40 - Can AI Code Quantum Simulators?22:32 - Journey into Learning Quantum26:50 - How to Enter the Field of Quantum Computing31:16 - From Starcraft to Software Engineering36:05 - Crumble Demo53:18 - Quirk Demo1:00:48 - Estimating Resources for Quantum Computation1:08:58 - Optimizing Measurements for Computation1:16:40 - How Many Qubits Do We Actually Need?1:30:49 - Other Research Areas for Improving Fault Tolerance1:41:23 - Elliptic Curve Discrete Logarithm Problem1:46:55 - New Tools for Quantum Computing1:50:23 - What Would Craig Do with Unlimited Funding?1:52:28 - How Learning Has Changed for Craig with Experience1:57:31 - Riding the Wave of Innovation vs Sticking to One Idea1:59:53 - Advice for Young Scientists #quantumcomputing #quantumphysics #computerscience #googleai #googlequantum

    2h 4m

  3. 10 MAR

    How Neurons Translate Electricity into Chemistry | Tom Südhof

    How do neurons convert electrical signals into chemical messages in under a millisecond? In this episode, we speak with Thomas Südhof, Stanford neuroscientist and Nobel laureate whose discoveries revealed the molecular machinery that allows neurons to communicate at synapses. Südhof explains how an electrical impulse traveling down a neuron triggers the rapid release of neurotransmitters, transforming an electrical signal into a chemical one that can be received by the next cell. We explore the remarkable precision of synaptic transmission, including how calcium ions trigger vesicle fusion, how specialized proteins organize the release machinery, and why this entire process unfolds on the timescale of a single millisecond. Südhof walks us through the molecular components that make this possible, including the proteins that dock neurotransmitter-filled vesicles and control their release. The conversation also examines how these discoveries reshaped modern neuroscience by revealing the fundamental mechanisms underlying neuronal communication. Südhof discusses how synapses operate as highly specialized molecular machines and how disruptions in synaptic signaling are linked to neurological and psychiatric disorders. Whether you’re interested in neuroscience, synapses, brain signaling, neurotransmitters, or the molecular basis of thought, this episode offers a clear explanation of how neurons translate electricity into chemistry, and how this microscopic process makes brain communication possible Follow us for more technical interviews with the world’s greatest scientists:Twitter: https://x.com/632nmPodcastInstagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==LinkedIn: https://www.linkedin.com/company/632nm/about/Substack: https://632nmpodcast.substack.com/ Follow our hosts!Mikhail Shalaginov: https://x.com/MYShalaginovMichael Dubrovsky: https://x.com/MikeDubrovskyXinghui Yin: https://x.com/XinghuiYin Subscribe:Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: [https://www.632nm.com](https://www.632nm.com/) Timestamps:00:00 - Intro01:23 - What is a Synapse?07:01 - History of Synapse Discovery12:54 - How Electron Microscopy Helped Neuroscience15:11 - Early Electrophysiological Experiments18:31 - Why are Neurotransmitters Needed At All?21:25 - Electrical Connections Between Cells22:48 - How Signal Diversity is Created in Synapses29:04 - Why are Synapses Chemical?31:06 - How Tom Began his Neuroscience Career39:32 - Emerging Tools that Allowed for Researching Synapses44:16 - Discerning Protein Function49:36 - Discovering Mechanism through Data52:15 - Isolating Membrane Proteins55:09 - Voltage Gates57:50 - How Synapses Change Over Time1:02:14 - How are Synapses Formed?1:10:22 - The Need for New Tools1:11:53 - Implications for Drug Discovery1:17:07 - Exploring the Mouse Hippocampus1:22:35 - Tom’s Work on LDL Receptors1:26:33 - Understanding Molecular Logic #neuroscience #neuroplasticity #nobelprize #hubermanlab #neurobiology

    1hr 30min

  4. 17 FEB

    How Engineers Solve “Impossible” Problems | Dan Gelbart

    How do engineers solve problems that seem to violate the laws of physics? In this episode, we speak with Dan Gelbart, a prolific inventor and precision engineer, about what it really means to work at the limits of physical law. From lasers and optical systems to ultra-precision manufacturing and semiconductor tools, Gelbart has spent decades designing systems where nanometers, noise, and nonlinearities matter, and where small misunderstandings of physics can block real progress. We discuss the story of the first working laser, built by Theodore Maiman, and why it succeeded only after questioning widely accepted assumptions. Gelbart explains how many “impossible” engineering problems aren’t forbidden by physics at all: they’re constrained by measurement errors, incomplete models, or failure to explore edge cases like pulsed operation, material effects, and boundary conditions. We explore precision metrology, high-resolution imaging for satellite systems, the culture of engineering education, and the difference between a true physical limit and a design constraint. Gelbart reflects on why mastering fundamentals, mechanics, optics, electromagnetism, matters more than chasing trends, and how breakthroughs often come from carefully re-examining what others assume cannot be done. Whether you’re interested in physics, engineering, semiconductor manufacturing, lasers, or the philosophy of technological innovation, this conversation offers a rigorous look at how engineers operate at the edge of what nature allows, and sometimes push beyond what others think is possible. Follow us for more technical interviews with the world’s greatest scientists:Twitter: https://x.com/632nmPodcastInstagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==LinkedIn: https://www.linkedin.com/company/632nm/about/Substack: https://632nmpodcast.substack.com/ Follow our hosts!Mikhail Shalaginov: https://x.com/MYShalaginovMichael Dubrovsky: https://x.com/MikeDubrovskyXinghui Yin: https://x.com/XinghuiYin Subscribe:Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: [https://www.632nm.com](https://www.632nm.com/) Timestamps:00:00 - Intro01:35 - The World’s First Laser07:53 - Solving Impossible Problems23:37 - Underestimated Problems39:36 - Dan’s Backstory43:33 - How to Teach Yourself Anything47:03 - Shortcomings of Modern Education53:19 - Developing the Optical Tape Recorder1:01:39 - Machine Obsolescence1:08:04 - Why are Scientists Often Bad Businessmen?1:15:17 - Developing Medical Devices1:24:52 - Untapped Potential of Materials Science1:30:47 - Accidental Inventions1:35:37 - Surviving Bureaucracy1:42:27 - Humanoid Robots1:44:11 - Managing an Engineering Team1:50:06 - Developing the First Good Mobile Data Terminal1:54:15 - Building an Environment for Solving Problems2:02:18 - Why Aren’t We Inventing New Things? #machining #cnc #precisionengineering #metrology #machineshop

    2h 4m

  5. 3 FEB

    How Visual Experience Rewires the Brain | Mark Bear on Neuroplasticity

    How does experience rewire the brain—and why is vision the ideal system for understanding neuroplasticity? In this episode, we speak with Mark Bear, MIT neuroscientist and a pioneer in the study of experience-dependent plasticity. Bear explains how the visual cortex became a model system for uncovering the synaptic mechanisms that allow the brain to change, adapt, and learn, especially during early development. We explore how visual experience shapes neural circuits, why the brain undergoes critical periods of heightened plasticity, and what classic experiments in visual deprivation revealed about how connections are strengthened or lost. Bear walks us through the discovery of binocular vision in the cortex, the role of inhibition in closing critical periods, and how these ideas reshaped our understanding of learning and memory. The conversation also covers modern views of cortical plasticity, including perceptual learning, visual recognition memory, and how the brain distinguishes familiar from novel stimuli. Bear discusses how insights from vision extend to broader questions about brain development, neurological disorders such as amblyopia, and whether adult plasticity can be reopened. Whether you’re interested in neuroscience, brain development, neuroplasticity, learning and memory, or the biology of vision, this episode offers a clear and authoritative look at how experience shapes the brain at the level of neural circuits and synapses. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcastInstagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==LinkedIn: https://www.linkedin.com/company/632nm/about/Substack: https://632nmpodcast.substack.com/ Follow our hosts!Mikhail Shalaginov: https://x.com/MYShalaginovMichael Dubrovsky: https://x.com/MikeDubrovskyXinghui Yin: https://x.com/XinghuiYin Subscribe:Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: https://www.632nm.com Timestamps:00:00 - Intro00:54 - Neuroplasticity in the Visual Cortex05:45 - Critical Periods for Neuroplasticity16:50 - Brain Development in Blind People19:25 - Hallucinations and Sensory Deprivation25:36 - How Mark’s Vision Disorder Led Him to a Career in Neuroscience31:35 - Intro to the Visual System35:52 - Visual System Processing40:52 - Pop Science Neuroplasticity45:00 - Memory Enhancing Pharmaceuticals50:18 - Other Ways of Modifying the Visual Cortex1:14:50 - Declarative vs Procedural Memory1:22:36 - Neural Networks and Memory Degradation1:25:16 - Neuron Transplants and Neurogenesis1:28:58 - Brain-Machine Interfaces1:33:46 - Most Prominent Issues in the Field1:40:47 - Fragile X Syndrome1:51:10 - Advice for Young Scientists #neuroplasticity #neuroscience #hubermanlab #braindevelopment #brainplasticity

    1hr 56min

  6. 20 JAN

    Snell's Law, Metasurfaces, and Metalenses | Federico Capasso

    How can flat surfaces shape light as powerfully as bulky lenses? In this episode, we speak with Federico Capasso, Harvard physicist and pioneer of metasurfaces, metalenses, and nanophotonics. Capasso traces the path from his work at Bell Labs on quantum cascade lasers to the invention of metasurface optics, showing how a practical challenge—collimating light without traditional lenses—sparked a new way to control light. We explore the physics behind metasurfaces and generalized Snell’s law, explaining how subwavelength structures enable precise control of wavefronts, phase, and polarization beyond what conventional diffractive optics or Fresnel lenses allow. Capasso clarifies common misconceptions, contrasts metasurfaces with diffraction gratings and phased arrays, and emphasizes the importance of physical intuition and simplicity. The conversation covers metalenses, polarization optics, holography, and how these ideas moved from theory to large-scale manufacturing in semiconductor foundries, ultimately appearing in consumer devices like smartphones. Capasso also reflects on commercialization, the legacy of Bell Labs, and the blurred boundary between basic science and real-world technology. Whether you’re interested in metasurfaces, metalenses, nanophotonics, optics, or the process behind breakthrough discoveries, this episode offers a clear and insightful look at how modern optical physics becomes transformative technology. Follow us for more technical interviews with the world’s greatest scientists:Twitter: https://x.com/632nmPodcastInstagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==LinkedIn: https://www.linkedin.com/company/632nm/about/Substack: https://632nmpodcast.substack.com/ Follow our hosts!Mikhail Shalaginov: https://x.com/MYShalaginovMichael Dubrovsky: https://x.com/MikeDubrovskyXinghui Yin: https://x.com/XinghuiYin Subscribe:Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: [https://www.632nm.com](https://www.632nm.com/) Timestamps:00:00 - Intro01:53 - Transition from Bell Labs to Harvard09:45 - Generalized Snell's Law21:25 - Facing the Diffractive Optics Community31:07 - Benefits of Well-Rounded Education45:16 - Metalenses55:55 - Can AI do Physics?1:07:39 - Industry vs Academia1:11:44 - Nanophotonics1:14:44 - What Allowed for the First Metalenses?1:17:38 - 632nm and Other Lasers1:20:47 - Quantum applications of Metalenses1:30:14 - Quantum Entanglement Redefines Spacetime1:43:22 - Stokes Parameters1:48:28 - Limits of Metasurface Pixel Size1:55:20 - Advice for Young Scientists2:01:45 - Critique of the H Index #metasurface #metalenses #quantumphysics #materialscience #optics  #photonics

    2h 13m

  7. 6 JAN

    Graphene, Nanotubes, and Quantum Hall Physics | Philip Kim

    How do electrons behave when they’re confined to a single layer, and why do entirely new laws of physics emerge when dimensions shrink? Papers discussed in this episode:Experimental observation of the quantum Hall effect and Berry's phase in graphene: https://www.nature.com/articles/nature04235Tunable Fractional Quantum Hall Phases in Bilayer Graphene: https://arxiv.org/abs/1403.2112Room-Temperature Quantum Hall Effect in Graphene: https://arxiv.org/abs/cond-mat/0702408 In this episode, we speak with Philip Kim, Harvard physicist and a leading experimentalist in low-dimensional quantum materials. Kim traces the experimental path from high-temperature superconductors and charge-density waves to carbon nanotubes and the earliest graphene devices, revealing how advances in nanofabrication and quantum transport opened the door to modern 2D materials physics. We dive deep into the Hall effect and quantum Hall effect, from their 19th-century origins to the discovery of quantized and fractional conductance, and explain why these effects were found experimentally before they were fully understood theoretically. Kim shares behind-the-scenes stories of early graphene experiments, mechanical exfoliation, Shubnikov–de Haas oscillations, and what it was like to be scooped by the work that launched graphene into the spotlight. Along the way, we explore how disorder, dimensionality, and magnetic fields shape electronic behavior; why carbon nanotubes paved the way for graphene; and how many of the most important discoveries in condensed matter physics arise from intuition, timing, and new experimental tools. Whether you’re interested in graphene, quantum transport, the quantum Hall effect, nanofabrication, superconductors, or the real stories behind breakthrough discoveries, this conversation offers a rare, technically rich look at how modern quantum materials research actually unfolds. Follow us for more technical interviews with the world’s greatest scientists:Twitter: https://x.com/632nmPodcastInstagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==LinkedIn: https://www.linkedin.com/company/632nm/about/Substack: https://632nmpodcast.substack.com/ Follow our hosts!Mikhail Shalaginov: https://x.com/MYShalaginovMichael Dubrovsky: https://x.com/MikeDubrovskyXinghui Yin: https://x.com/XinghuiYin Subscribe:Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: [https://www.632nm.com](https://www.632nm.com/) Timestamps:00:00 - Intro01:15 - How Philip Began Studying Graphene20:06 - Old Methods of Creating Graphene32:33 - Hall Effect and Quantum Hall Effect48:29 - Philip's Work at Columbia52:33 - Philip's First Experiments with Graphene1:06:43 - Did Philip Get Scooped from a Discovery?1:09:40 - The Power of Scotch Tape1:24:57 - High Temperature Quantum Hall Effect1:30:18 - Fractional Quantum Hall Effect1:41:17 - Collaboration with Particle Physicists1:54:13 - Single Layer Graphene1:59:44 - Next Gen Electronics with 2D Materials2:03:23 - Graphene Twisting2:14:48 - Superconductivity in Other Materials2:20:06 - Anyons2:30:00 - Fault-Tolerant Quantum Computing2:36:05 - Can AI and Big Data Help Physicists?2:40:47 - What Would Philip Do with Unlimited Resources?2:43:44 - Optimizing the Education System #graphene #quantumphysics #materialscience #halleffect #electromagnetism

    2h 47m

  8. 23/12/2025

    Quantum Matter, Super-conductors, and Black Holes | Subir Sachdev on the SYK Model

    What makes high-temperature superconductors and “strange metals” some of the most perplexing systems in modern physics? In this episode, we speak with Dr. Subir Sachdev: Harvard physicist and one of the leading architects of today’s understanding of quantum matter. Sachdev explains why strange metals refuse to behave like ordinary conductors, how quantum entanglement reshapes the landscape of many-body physics, and why the quest to understand cuprate superconductors continues to push both theory and experiment to their limits. We explore the physics of the cuprate phase diagram, the collapse of quasiparticles, and the role of quantum criticality in creating universal, linear-in-temperature behavior. Sachdev walks us through the origins of the SYK model, its surprising connections to black-hole thermodynamics and holography, and how new lattice-based models may finally bridge the gap between solvable theory and real materials. Whether you’re curious about superconductivity, quantum criticality, black-hole analogies, emergent gauge fields, or the deep physics behind strongly correlated electrons, this conversation offers a rare, accessible look at how frontier theoretical work is redefining our picture of quantum matter—from the lab bench to the edge of spacetime. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcastInstagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==LinkedIn: https://www.linkedin.com/company/632nm/about/Substack: https://632nmpodcast.substack.com/ Follow our hosts! Mikhail Shalaginov: https://x.com/MYShalaginovMichael Dubrovsky: https://x.com/MikeDubrovskyXinghui Yin: https://x.com/XinghuiYin Subscribe:Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: https://www.632nm.com Timestamps:01:22 - Subir’s Path to Condensed Matter Physics06:24 - Challenges in Discovering Cuprates09:53 - History of Superconductivity20:07 - Subir's PhD work27:09 - Development of the SYK model41:09 - Strange Metals56:43 - Derivation of SYK Model1:03:53 - Signatures of Strange Metals1:09:58 - How Quantum Mechanics Affects Black Holes1:17:10 - What Brought Subir to Black Holes?1:19:43 - Black Hole Connections to SYK1:29:28 - ADS CFT Correspondence1:37:04 - Can Quantum Computers Help Advance the SYK Model?1:40:17 - Is AI Useful for Theoretical Physics?1:46:40 - How does Quantum Criticality Play into Superconductivity?1:49:11 - Derivation Quantum Criticality1:52:49 -  What is Holography?1:55:07 - Holography2:00:19 - Green’s Function2:08:46 - Green’s equation slides2:13:23 - Yukawa Model vs SYK2:17:30 - Can AI Brute Force Physics Discoveries?2:23:51 - What Would Subir Do With Unlimited Funding?2:36:33 - Dissecting the Hype of Superconductivity2:31:15 - Raising the Next Generation of Great Physicists #theoreticalphysics #quantummaterials #astrophysics #superconductivity #superconductor #blackhole #quantumphysics #quantummechanics

    2h 35m
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About

Technical interviews with the greatest scientists in the world.

Information

  • Creator
    Misha Shalaginov, Michael Dubrovsky, Xinghui Yin
  • Years Active
    2024 - 2026
  • Episodes
    48
  • Rating
    Clean
  • Copyright
    © 2026 Misha Shalaginov, Michael Dubrovsky, Xinghui Yin
  • Show Website
    632nm

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