632nm

Misha Shalaginov, Michael Dubrovsky, Xinghui Yin

Technical interviews with the greatest scientists in the world.

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55 episodes
Updated July 21

Episodes55

Newest first

July 21 · 3 hr 26 min
How Bacteria Evolved Rotary Motors | Michael Manson
How do bacteria power one of the most sophisticated molecular machines in nature? In this episode, we speak with Dr. Michael Manson, one of the pioneers of bacterial motility research, whose nearly 50-year career has helped uncover how the bacterial flagellar motor works. From the first experiments proving that bacterial flagella rotate to the latest breakthroughs in cryo-EM and single-molecule biology, Manson tells the story of how scientists finally solved the mechanism behind a real working biological motor. We explore how bacteria move through chemotaxis using a biased random walk, why E. coli alternates between running and tumbling, and how individual molecules can control the direction of a spinning flagellum. Manson explains the experiments that showed proton motive force powers the flagellar motor, how the motor’s rotor and stator generate torque, why it can reverse direction almost instantly, and how bacteria adapt to changing environments by dynamically adjusting their molecular machinery. We also discuss ATP synthase, proton gradients, molecular motors, bacterial genetics, cryo-electron microscopy, ion channels, self-assembling protein complexes, nanomachines, and the history of the discoveries that transformed modern microbiology. Whether you’re interested in the bacterial flagellar motor, molecular biology, biophysics, microbiology, ATP synthase, chemotaxis, molecular machines, or the fundamental physics of life, this week we go deep into one of biology’s most remarkable inventions. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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://www.linkedin.com/in/michael-dubrovsky/ Xinghui Yin: https://www.linkedin.com/in/xinghui-yin/ Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro and Reads 02:42 - Biased Random Walk 10:27 - Manson's Work with Howard Berg 13:24 - Proton Motive Force and Flagellum 29:07 - Rotors and Stators of Flagella 37:20 - Mot Proteins 57:34 - CheY and Changing Direction 1:11:48 - Biology and Intelligent Design 1:26:52 - Reversing Proton Flow 1:29:59 - Life at Low Reynolds Number 1:39:15 - Mysteries in the 90s and 2000s 1:48:34 - Applications of Understanding the Nanomotor 1:58:33 - Flagellar Motor Crash Course 2:01:46 - Bacterial Learning and Adaptation 2:05:56 - Giving Up on Birds 2:14:09 - Caltech 2:21:38 - Advice for Young Scientists 2:30:02 - Origins of Life 2:31:19 - What's Left for the Flagellar Motor? PART 2: 2:33:33 - Building the Nanomotor 2:39:29 - Other Types of Flagella 2:47:06 - MotA and MotB 3:07:17 - Reusing Motors Across Biology 3:10:13 - Benefits of Being Small 3:12:34 - CheY and Changing Direction 3:19:39 - How Physics Shapes Evolution
June 30 · 1 hr 23 min
The Atomic Physics Behind Neutral Atom Computers | Mark Saffman
Why are so many companies betting on neutral atoms to build the first useful quantum computers? In this episode, we speak with Mark Saffman, professor at the University of Wisconsin–Madison and one of the pioneers of neutral atom quantum computing. Over the past two decades, Saffman has helped transform Rydberg atoms from a theoretical idea into one of the leading architectures for scalable, fault-tolerant quantum computing. We explore the physics of optical tweezers and Rydberg blockade, how neutral atoms perform quantum logic and create entanglement, and why this platform offers unique advantages in connectivity and scalability. Saffman also discusses the engineering challenges of improving gate fidelity, implementing quantum error correction, and scaling from small laboratory experiments to processors containing millions of qubits. We also discuss the origins of companies like Infleqtion, the rapid growth of the neutral atom ecosystem, and what it will take for quantum computers to solve meaningful scientific and industrial problems. Whether you're interested in quantum computing, atomic physics, quantum error correction, computer architecture, or the future of information processing, this episode provides a deep technical look at one of the most promising paths toward practical quantum computers. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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://www.linkedin.com/in/michael-dubrovsky/ Xinghui Yin: https://www.linkedin.com/in/xinghui-yin/ Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro and Reads 02:45 - Neutral Atoms vs Superconductors and Ions 07:30 - Rydberg Atoms 12:49 - Practical Considerations for Rydberg Atoms 19:04 - From Atomic Physics to Quantum Gates 29:49 - Increasing Trap Loading 38:27 - Evolution of Rydberg Gates 45:05 - Limits of Rydberg Fidelity 49:49 - Scaling Neutral Atom Arrays 53:47 - Atomic Species and QEC 1:03:38 - History of Infleqtion 1:10:27 - Mark’s Outlook on the Future 1:15:08 - Caltech and Peter Shor 1:20:00 - Advice for Young Scientists #quantumphysics #quantumcomputing #physics #computerscience
June 16 · 1 hr 39 min
Silicon Photonics and the Future of AI Scaling | John Bowers
Why are some of the world's largest technology companies betting on silicon photonics? In this episode, we speak with John Bowers, professor at UC Santa Barbara and one of the pioneers of silicon photonics, about the technologies that are transforming AI infrastructure and modern data centers. Bowers explains why moving data has become one of the central challenges in computing, how optical communication is overcoming the limitations of traditional electrical interconnects, and why light is increasingly being used to connect processors, servers, and entire data centers. We explore the origins of silicon photonics, from early optical communications research to the development of integrated photonic devices that can be manufactured using semiconductor processes. Bowers discusses the engineering challenges of combining lasers with silicon, the breakthroughs that enabled heterogeneous integration, and how decades of research helped turn silicon photonics into a commercial technology deployed at global scale. We examine the growing demands of artificial intelligence, where the movement of information between processors has become just as important as computation itself. Bowers explains why bandwidth, power consumption, and interconnect density are emerging as critical bottlenecks for AI systems, and how optical links are enabling the next generation of large-scale computing architectures. We also discuss data center networking, optical interconnects, co-packaged optics, heterogeneous integration, semiconductor manufacturing, photonic integrated circuits, telecommunications, AI hardware, and the future of warehouse-scale computing. Throughout the episode, Bowers provides an inside look at how advances in photonics are reshaping the infrastructure that powers modern computing. Whether you're interested in silicon photonics, optical communications, semiconductor engineering, computer architecture, AI hardware, data center design, networking, integrated photonics, electrical engineering, or the future of computing, this episode provides a deep technical exploration of one of the most important technologies behind the AI revolution. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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://www.linkedin.com/in/michael-dubrovsky/ Xinghui Yin: https://www.linkedin.com/in/xinghui-yin-168b94130/ Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 01:19 - Why Data Centers Need Photonics 05:28 - Bowers's Interest in Physics 10:09 - Lessons From Bell Labs 12:58 - Semiconductor Lasers 18:31 - Teaching Entrepreneurship 23:21 - Heterogeneous Integration 29:40 - Why Silicon Photonics Needed Better Light Sources 32:00 - Heterogeneous Integration vs Direct Growth 44:04 - The Packing Problem in Photonics 47:49 - Narrow Linewidth Lasers 51:31 - Data Centers in Space 59:19 - Lessons from the Telecom Bubble 1:02:17 - Recent Breakthroughs in Photonics 1:04:32 - What is a Frequency Comb? 1:07:07 - Solitons and Microcombs 1:14:48 - Optical Computing and AI 1:19:09 - How Bowers Starts Companies 1:21:56 - Was Bowers Late to Any Trends? 1:22:51 - What would Bowers Build with Unlimited Resources? 1:24:38 - Creating Bell Labs for AI 1:26:35 - Competition, Endurance, and Personality 1:30:41 - The Best Problems for Young Scientists to Tackle 1:37:47 - Advice for Researchers Who Want to Keep Real Depth #photonics #datacenter #siliconphotonics #computerscience #artificialintelligence
June 2 · 1 hr 27 min
Bioelectricity, Morphogenesis, and Two-Headed Worms | Michael Levin
How can a flatworm regenerate a complete head after being cut in half? In this episode, we speak with Michael Levin, developmental biologist and director of the Allen Discovery Center at Tufts University, about the emerging field of developmental bioelectricity. Levin explains how voltage gradients, ion channels, and gap junctions form a layer of biological control that operates alongside genetics and biochemistry to regulate embryonic development, regeneration, and anatomical patterning. We explore the experimental foundations of bioelectricity research, including the use of voltage-sensitive dyes, ion channel manipulation, and computational models to read and write electrical information in living tissues. Levin discusses how bioelectric signals help establish left-right asymmetry in embryos, coordinate communication across developing tissues, and encode large-scale anatomical information that individual cells cannot possess on their own. The conversation examines classic and surprising experiments from the field, including the creation of two-headed planarian worms, the induction of ectopic eyes in frog embryos, and the restoration of normal development after severe genetic and environmental disruptions. Levin explains how bioelectric circuits can act as a control architecture for morphogenesis, allowing tissues to make collective decisions about growth, form, and regeneration. We also discuss voltage gradients, membrane potentials, gap junction networks, developmental pattern formation, regenerative medicine, collective cellular intelligence, and the relationship between electrophysiology and gene regulation. Throughout the episode, Levin argues that understanding development requires looking beyond genes alone to the dynamic electrical communication networks that coordinate living systems across scales. Whether you're interested in developmental biology, embryology, regeneration, electrophysiology, bioelectricity, morphogenesis, systems biology, ion channels, pattern formation, or the future of regenerative medicine, this episode provides a deep technical exploration of how electrical signals help shape living organisms. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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://www.linkedin.com/in/michael-dubrovsky/ Xinghui Yin: https://www.linkedin.com/in/xinghui-yin-168b94130/ Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 01:40 - Early Interest in Bioelectricity 05:22 - External Electric Stimulation 19:54 - Two-Headed Planarians 31:40 - Designing Bioelectric Experimental Methods 56:37 - Different Model Organisms 1:07:34 - TAME Theory 1:24:16 - Xenobots and Advice for Young Scientists #planaria #morphology #neuroscience #biology #bioelectricity
May 19 · 1 hr 59 min
Quantum Architecture, QAOA, and Cancer Biomarkers | Fred Chong
Are quantum computers changing the way we discover cancer treatments? In this episode, Misha and Yudong spoke with Fred Chong, Seymour Goodman Professor at the University of Chicago, about the future of quantum computer architecture and how quantum algorithms could eventually help solve real-world problems in medicine, optimization, and scientific computing. Chong explains the transition from the NISQ era toward fault-tolerant quantum computing, why hardware-aware software design remains essential, and how compiler architectures, error correction, and quantum system design all interact across the full computing stack. The conversation explores the challenges of building scalable quantum machines, the tradeoffs between superconducting qubits, trapped ions, and neutral atoms, and why many quantum systems may ultimately function as specialized accelerators alongside classical computers. We also discuss quantum optimization algorithms like QAOA and how Chong’s group is applying them to cancer biomarker discovery and treatment prediction. By analyzing complex multimodal biological data, including DNA, mRNA, and pathology imaging, these methods aim to uncover patterns that are difficult for conventional machine learning systems to identify without overfitting. Along the way, Fred shares stories from the early days of supercomputing at Thinking Machines, the origins of his quantum research career, the founding of Super.tech, and his perspective on where quantum computing is genuinely making progress versus where hype still dominates the conversation. Topics include quantum computing, QAOA, fault-tolerant quantum computing, quantum error correction, quantum compilers, NISQ systems, neutral atoms, superconducting qubits, quantum architecture, cancer biomarkers, biomedical optimization, hybrid quantum-classical systems, and the future of quantum software and hardware co-design. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 01:34 - From Jurassic Park to Quantum Computing 10:13 - Modernizing NISQ Research 13:45 - Designing Around Quantum Hardware 20:30 - Variational Quantum Algorithms 23:07 - Quantum Computers for Cancer Research 30:35 - How Q4Bio Began 37:20 - Will We Need QEC in the Future? 40:25 - What Quantum Computers Can Learn from Classical Architecture 43:08 - Would Fred Return to Classical Computing? 46:11 - Quantum Software and Quantum Compilers 55:19 - Starting Super.tech 1:01:43 - Classical Analogs to Quantum Hardware 1:12:21 - Advice for Young Scientists 1:17:43 - Is AI Impacting Quantum Research? 1:22:38 - Importance of Formal Verification 1:30:40 - QLDPC Codes 1:35:48 - Fred’s Beginnings in Computer Science 1:42:48 - Chicago vs Silicon Valley 1:46:27 - Do We Need More Quantum Software Companies? 1:53:17 - Future of Quantum Computing and Cryptography #quantumcomputing #quantumalgorithms #cancerresearch #computerscience
May 5 · 2 hr 1 min
How Quantum Sensors Can Measure Single Electrons | Amir Yacoby
How do you measure something as small as a single electron or map quantum behavior at the nanoscale? In this episode, Misha spoke with Amir Yacoby, professor at Harvard University, about the cutting edge of quantum sensing and the experimental tools redefining how we probe the quantum world. Yacoby explains how physicists build ultra-sensitive detectors, from single-electron transistors to quantum dots and NV centers in diamond, that can measure charge, spin, and magnetic fields with extraordinary precision. These tools make it possible to study both strongly correlated systems, like those exhibiting the fractional quantum Hall effect, and isolated quantum systems used as qubits. We explore how accidental discoveries in the lab can evolve into entirely new sensing techniques, including momentum-resolved tunneling and nanoscale imaging methods. The conversation also highlights how quantum sensors are enabling researchers to bridge two regimes: complex many-body systems and controllable quantum devices, opening the door to new insights in topological physics and quantum information processing. Whether you're interested in quantum measurement, nanoscale imaging, or the future of quantum technologies, this episode offers a detailed look at how new instruments are driving discovery at the frontiers of physics. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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/MYShalaginov Michael Dubrovsky: https://x.com/MikeDubrovsky Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 01:23 - The Process of Creating Quantum Tools 11:28 - Graduate School at Weizmann 14:51 - From Aerospace to Condensed Matter 26:53 - Starting at Harvard 39:44 - Working at Bell Labs 47:42 - Diamond NV Centers 1:00:52 - Spin Waves 1:16:10 - SQUIDs 1:29:57 - State of the Art Sensors 1:33:08 - Motivations for Building Better Sensors 1:36:52 - Fabrication Challenges 1:40:14 - New Sensors 1:45:49 - Majoranas 1:53:25 - Finding New Applications for Sensors 1:57:16 - The Use of AI in Physics 1:58:55 - Advice for Young Scientists
April 21 · 1 hr 13 min
The Physics of Un-Hackable Face Recognition | Rob Devlin on Metalenz
How do you turn a flat piece of nanostructured material into a secure biometric sensor? In this episode, we speak with Rob Devlin, co-founder and CEO of Metalenz, about how metasurfaces are transforming optics and enabling a new generation of biosecure sensing. Devlin explains how engineers can control light at the subwavelength scale to replace bulky lens stacks with a single flat surface, and why the real breakthrough isn’t just miniaturization, but the ability to mass-produce optics in semiconductor fabs. We explore how Metalenz scaled metasurfaces from academic prototypes into millions of devices, and what it takes to design optics for manufacturing. Devlin breaks down the transition from building one perfect device in a cleanroom to producing millions that all meet tight specifications. The conversation focuses on polarization imaging as a new information channel in consumer devices. Unlike traditional cameras that capture only intensity and color, polarization reveals material properties. This enables a new approach to facial recognition that is both more secure and more compact than existing systems. Rob also shares the story behind Metalenz, from its origins in a Harvard lab to partnerships with major semiconductor manufacturers, and how the company navigated the challenges of finding product-market fit, scaling fabrication, and building a new sensing stack from scratch. Whether you’re interested in optics, nanofabrication, consumer electronics, or the future of biometric security, this episode explores how controlling light at the nanoscale is opening entirely new possibilities for sensing and identity verification. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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/MYShalaginov Michael Dubrovsky: https://x.com/MikeDubrovsky Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 01:22 - Making Metalenses Mass-Producible 10:58 - Metasurfaces for Polarimetry 17:10 - Face ID Security and Pitfalls 24:47 - Polar ID Principles 29:02 - Polar ID Demo 39:58 - Meeting Federico Capasso 50:43 - Developing Metasurface Fabrication Techniques 55:58 - Founding Metalenz 1:11:44 - Future of Metalenz and Metasurfaces #photonics #faceid #biometrics #metasurface #biosecurity #optics
April 1 · 1 hr 37 min
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/632nmPodcast Instagram: 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/MikeDubrovsky Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 01:12 - 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 Starcloud 19:56 - How does Starcloud’s cooling work? 28:26 - Training an LLM in space 32:07 - Addressing critics on space Twitter 34:23 - Is Starcloud overfunded? 35:59 - Will demand for data centers keep going up? 38:11 - GPU lifespan and disposal in space 39:47 - Bus structures 41:43 - Starcloud’s origin and founders 49:29 - Fundraising, Competition, and Meeting Expectations 53:29 - Satellite size and collisions 56:29 - Manufacturing Bottlenecks 1:00:20 - Starcloud 1 tests 1:01:57 - Acceleration after YC 1:03:43 - Testing on Earth 1:05:06 - Motivations for Starcloud 1:06:45 - Data centers on the Moon 1:08:12 - Interacting with AI companies 1:08:18 - What’s next for Starcloud? 1:14:01 - Other uses for Starcloud satellites 1:17:56 - Lunar hotels and space elevators 1:24:28 - Complementary business ideas to Starcloud 1:29:51 - Philip’s competitive twin 1:32:18 - Philip and Mike’s thoughts on YC 1:34:45 - Advice for young entrepreneurs #datacenter #aidatacenter #starlink #spacex #falcon9 #starcloud
March 27 · 2 hr 3 min
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/632nmPodcast Instagram: 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/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 01:22 - Shor’s Algorithm 04:02 - Why are Arithmetic Operations Important? 08:35 - Why are T-Gates Important for QEC? 13:47 - Motivations for Creating Crumble and STIM 18:40 - Can AI Code Quantum Simulators? 22:32 - Journey into Learning Quantum 26:50 - How to Enter the Field of Quantum Computing 31:16 - From Starcraft to Software Engineering 36:05 - Crumble Demo 53:18 - Quirk Demo 1:00:48 - Estimating Resources for Quantum Computation 1:08:58 - Optimizing Measurements for Computation 1:16:40 - How Many Qubits Do We Actually Need? 1:30:49 - Other Research Areas for Improving Fault Tolerance 1:41:23 - Elliptic Curve Discrete Logarithm Problem 1:46:55 - New Tools for Quantum Computing 1:50:23 - What Would Craig Do with Unlimited Funding? 1:52:28 - How Learning Has Changed for Craig with Experience 1:57:31 - Riding the Wave of Innovation vs Sticking to One Idea 1:59:53 - Advice for Young Scientists #quantumcomputing #quantumphysics #computerscience #googleai #googlequantum
March 10 · 1 hr 30 min
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/632nmPodcast Instagram: 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/MYShalaginov Michael Dubrovsky: https://x.com/MikeDubrovsky Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: [https://www.632nm.com](https://www.632nm.com/) Timestamps: 00:00 - Intro 01:23 - What is a Synapse? 07:01 - History of Synapse Discovery 12:54 - How Electron Microscopy Helped Neuroscience 15:11 - Early Electrophysiological Experiments 18:31 - Why are Neurotransmitters Needed At All? 21:25 - Electrical Connections Between Cells 22:48 - How Signal Diversity is Created in Synapses 29:04 - Why are Synapses Chemical? 31:06 - How Tom Began his Neuroscience Career 39:32 - Emerging Tools that Allowed for Researching Synapses 44:16 - Discerning Protein Function 49:36 - Discovering Mechanism through Data 52:15 - Isolating Membrane Proteins 55:09 - Voltage Gates 57:50 - How Synapses Change Over Time 1:02:14 - How are Synapses Formed? 1:10:22 - The Need for New Tools 1:11:53 - Implications for Drug Discovery 1:17:07 - Exploring the Mouse Hippocampus 1:22:35 - Tom’s Work on LDL Receptors 1:26:33 - Understanding Molecular Logic #neuroscience #neuroplasticity #nobelprize #hubermanlab #neurobiology
February 17 · 2 hr 3 min
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/632nmPodcast Instagram: 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/MYShalaginov Michael Dubrovsky: https://x.com/MikeDubrovsky Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: [https://www.632nm.com](https://www.632nm.com/) Timestamps: 00:00 - Intro 01:35 - The World’s First Laser 07:53 - Solving Impossible Problems 23:37 - Underestimated Problems 39:36 - Dan’s Backstory 43:33 - How to Teach Yourself Anything 47:03 - Shortcomings of Modern Education 53:19 - Developing the Optical Tape Recorder 1:01:39 - Machine Obsolescence 1:08:04 - Why are Scientists Often Bad Businessmen? 1:15:17 - Developing Medical Devices 1:24:52 - Untapped Potential of Materials Science 1:30:47 - Accidental Inventions 1:35:37 - Surviving Bureaucracy 1:42:27 - Humanoid Robots 1:44:11 - Managing an Engineering Team 1:50:06 - Developing the First Good Mobile Data Terminal 1:54:15 - Building an Environment for Solving Problems 2:02:18 - Why Aren’t We Inventing New Things? #machining #cnc #precisionengineering #metrology #machineshop
February 3 · 1 hr 55 min
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/632nmPodcast Instagram: 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/MYShalaginov Michael Dubrovsky: https://x.com/MikeDubrovsky Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 00:54 - Neuroplasticity in the Visual Cortex 05:45 - Critical Periods for Neuroplasticity 16:50 - Brain Development in Blind People 19:25 - Hallucinations and Sensory Deprivation 25:36 - How Mark’s Vision Disorder Led Him to a Career in Neuroscience 31:35 - Intro to the Visual System 35:52 - Visual System Processing 40:52 - Pop Science Neuroplasticity 45:00 - Memory Enhancing Pharmaceuticals 50:18 - Other Ways of Modifying the Visual Cortex 1:14:50 - Declarative vs Procedural Memory 1:22:36 - Neural Networks and Memory Degradation 1:25:16 - Neuron Transplants and Neurogenesis 1:28:58 - Brain-Machine Interfaces 1:33:46 - Most Prominent Issues in the Field 1:40:47 - Fragile X Syndrome 1:51:10 - Advice for Young Scientists #neuroplasticity #neuroscience #hubermanlab #braindevelopment #brainplasticity
January 20 · 2 hr 13 min
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/632nmPodcast Instagram: 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/MYShalaginov Michael Dubrovsky: https://x.com/MikeDubrovsky Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: [https://www.632nm.com](https://www.632nm.com/) Timestamps: 00:00 - Intro 01:53 - Transition from Bell Labs to Harvard 09:45 - Generalized Snell's Law 21:25 - Facing the Diffractive Optics Community 31:07 - Benefits of Well-Rounded Education 45:16 - Metalenses 55:55 - Can AI do Physics? 1:07:39 - Industry vs Academia 1:11:44 - Nanophotonics 1:14:44 - What Allowed for the First Metalenses? 1:17:38 - 632nm and Other Lasers 1:20:47 - Quantum applications of Metalenses 1:30:14 - Quantum Entanglement Redefines Spacetime 1:43:22 - Stokes Parameters 1:48:28 - Limits of Metasurface Pixel Size 1:55:20 - Advice for Young Scientists 2:01:45 - Critique of the H Index #metasurface #metalenses #quantumphysics #materialscience #optics #photonics
January 6 · 2 hr 47 min
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/nature04235 Tunable Fractional Quantum Hall Phases in Bilayer Graphene: https://arxiv.org/abs/1403.2112 Room-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/632nmPodcast Instagram: 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/MYShalaginov Michael Dubrovsky: https://x.com/MikeDubrovsky Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: [https://www.632nm.com](https://www.632nm.com/) Timestamps: 00:00 - Intro 01:15 - How Philip Began Studying Graphene 20:06 - Old Methods of Creating Graphene 32:33 - Hall Effect and Quantum Hall Effect 48:29 - Philip's Work at Columbia 52:33 - Philip's First Experiments with Graphene 1:06:43 - Did Philip Get Scooped from a Discovery? 1:09:40 - The Power of Scotch Tape 1:24:57 - High Temperature Quantum Hall Effect 1:30:18 - Fractional Quantum Hall Effect 1:41:17 - Collaboration with Particle Physicists 1:54:13 - Single Layer Graphene 1:59:44 - Next Gen Electronics with 2D Materials 2:03:23 - Graphene Twisting 2:14:48 - Superconductivity in Other Materials 2:20:06 - Anyons 2:30:00 - Fault-Tolerant Quantum Computing 2:36:05 - 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
Dec 23, 2025 · 2 hr 34 min
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/632nmPodcast Instagram: 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/MYShalaginov Michael Dubrovsky: https://x.com/MikeDubrovsky Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 01:22 - Subir’s Path to Condensed Matter Physics 06:24 - Challenges in Discovering Cuprates 09:53 - History of Superconductivity 20:07 - Subir's PhD work 27:09 - Development of the SYK model 41:09 - Strange Metals 56:43 - Derivation of SYK Model 1:03:53 - Signatures of Strange Metals 1:09:58 - How Quantum Mechanics Affects Black Holes 1:17:10 - What Brought Subir to Black Holes? 1:19:43 - Black Hole Connections to SYK 1:29:28 - ADS CFT Correspondence 1:37:04 - 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 Criticality 1:52:49 - What is Holography? 1:55:07 - Holography 2:00:19 - Green’s Function 2:08:46 - Green’s equation slides 2:13:23 - Yukawa Model vs SYK 2:17:30 - Can AI Brute Force Physics Discoveries? 2:23:51 - What Would Subir Do With Unlimited Funding? 2:36:33 - Dissecting the Hype of Superconductivity 2:31:15 - Raising the Next Generation of Great Physicists #theoreticalphysics #quantummaterials #astrophysics #superconductivity #superconductor #blackhole #quantumphysics #quantummechanics
Dec 9, 2025 · 1 hr 50 min
How to Build Fault-Tolerant Quantum Computers | Austin Fowler on Surface Codes + TQEC
Would we get a quantum computer sooner if everything was open source? In this episode, we speak with Austin Fowler, one of the architects of quantum error correction and a pioneer of the surface code used in today’s leading quantum computers. Fowler helped lay the groundwork for scalable, fault-tolerant computation at Google Quantum AI, before leaving to advocate for a more open and collaborative model of research. He explains why building a useful quantum computer will require millions of reliable qubits, why no known algorithm yet clearly outperforms classical computation, and why the field’s current competitive funding model may be slowing progress instead of accelerating it. From the engineering challenges of superconducting qubits to the economics of global research, Fowler offers a candid, inside look at the state of quantum technology. We explore the history and promise of quantum error correction, the software bottlenecks that still stand in the way, and how an open-source, international approach — modeled on CERN or the International Space Station — could transform the field. Along the way, Fowler reflects on his time at Google, the importance of collaboration, and what it will really take to make quantum computing practical. Whether you’re interested in quantum hardware, physics, computer science, or research policy, this conversation reveals the technical, ethical, and economic realities behind one of today’s most ambitious scientific pursuits. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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! Michael Dubrovsky: https://x.com/MikeDubrovsky Misha Shalaginov: https://x.com/MYShalaginov Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: [https://www.632nm.com](https://www.632nm.com/) Timestamps: 00:00 - Intro 01:40 - Austin’s Longevity in Quantum 02:31 - What’s the Goal of Quantum Computing? 05:01 - Creating Fault-Tolerant Qubits 06:55 - Advantages of 2D Surface Code 08:47 - Austin’s Journey into Quantum 16:32 - Working at Google 20:14 - Alternatives to Surface Codes 22:18 - Should Quantum Computing Be Open Source? 25:20 - Quantum Computing is Eating Itself 30:52 - Open Source as a Mission 35:46 - Advice for People Getting into TQEC 39:03 - Bit Flips vs Phase Flips 45:43 - History of Surface Codes 49:05 - From Surface Code to Fault Tolerance 57:19 - What Software do Quantum Computers Need? 1:00:17 - Quantum vs Classical Error Correction 1:05:57 - Manufacturing Superconducting Qubits 1:12:02 - Noise Models in Software 1:21:21 - How do NISQ Experiments help us Build Better Computers? 1:24:01 - State of the Art Topological QEC 1:31:38 - How did the TQEC Community Begin? 1:34:46 - Future of TQEC 1:36:03 - Quantum AI 1:37:58 - Advice for Young Scientists 1:41:35 - Underrated Quantum Research 1:47:21 - What are the Most Important Upcoming Developments?
Nov 26, 2025 · 2 hr 4 min
Why Syncing Atomic Clocks is Virtually Impossible | Judah Levine on UTC
Why is syncing atomic clocks still one of the hardest problems in physics and engineering? In this episode, we speak with Judah Levine—legendary NIST physicist and one of the key architects of modern timekeeping—about the invisible systems that hold the digital world together. Levine explains why synchronizing atomic clocks across the planet is far more complex than the clocks themselves, and why seemingly simple ideas like “round-trip delay” break down in real-world media such as fiber optics and the internet. We explore how UTC is built from hundreds of atomic clocks, the difference between keeping time and *transferring* time, and the surprising challenges introduced by asymmetric delays, chromatic dispersion, and environmental noise. Levine walks us through the evolution of cesium clocks, the rise of optical clocks, and the technologies that make GPS, finance, power grids, and global communication possible. Along the way, we discuss the history of time synchronization, from railroad schedules to radio frequencies to modern satellite systems; the ongoing debate over leap seconds; and why the future of precision timing depends not just on better clocks, but on better *engineering* to deliver those clocks’ performance to the real world. Whether you’re curious about atomic clocks, relativity, fiber optics, GPS, the structure of time itself, or the hidden physics behind everyday technology, this conversation offers a rare look at how science, engineering, and careful statistical thinking keep modern civilization in sync—down to the nanosecond. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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! Michael Dubrovsky: https://x.com/MikeDubrovsky Misha Shalaginov: https://x.com/MYShalaginov Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: [https://www.632nm.com](https://www.632nm.com/) Timestamps: 00:00 – Intro 01:03 – What is UTC? 05:50 – Timekeeping for Satellites 07:08 – How Radio Created Better Clocks 18:32 – From Astronomy to Atoms 25:25 – Why are there 24 Hours in a Day? 29:55 – Why Synchronizing Clocks is so Hard 47:09 – How did Judah get into Clocks? 53:29 – Is UTC Vulnerable to Hackers? 1:06:41 – Cesium vs Optical Atomic Clocks 1:11:23 – How Cesium Clocks Work 1:23:35 – Why Cesium Clocks are Imperfect 1:26:17 – Judah’s 3 Year Experiment 1:29:30 – Statistics with Clocks 1:33:40 – Is Time Real? 1:36:29 – Is the Universe Slowing Down? 1:40:29 – Atomic Time and General Relativity 1:42:17 – What’s Left for Atomic Clocks? 1:54:34 – What would Judah do with Unlimited Funding? 1:58:57 – Judah's Past in Programming 2:02:55 – Advice for Young Scientists
Nov 4, 2025 · 1 hr 18 min
Can We Predict History Like the Weather? | Peter Turchin on Cliodynamics
Why do civilizations rise, prosper, and then collapse? Here's what the math tells us. In this episode, we sit down with Peter Turchin, complexity scientist and founder of the field of cliodynamics, which uses data and mathematical models to study the long-term cycles of history. Turchin explains his theory of elite overproduction, how societies generate too many ambitious, educated elites competing for too few positions, and why this dynamic reliably leads to polarization, inequality, and political turmoil. We explore how his structural-demographic theory maps the recurring “boom and bust” rhythms that have shaped civilizations from ancient Rome to modern America, the role of military competition in driving cooperation and social complexity, and how new tools—from AI-assisted historical databases to ancient DNA and LiDAR—are transforming the study of the past. Whether you’re drawn to history, sociology, complexity science, or the fate of modern democracies, this conversation reveals how Turchin’s quantitative approach offers a new way to understand—and maybe even forecast—the forces that make societies rise and fall. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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! Michael Dubrovsky: https://x.com/MikeDubrovsky Misha Shalaginov: https://x.com/MYShalaginov Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 01:48 - Overproduction of Elites 10:56 - Did Models Predict the Rise of Trump? 20:43 - Is Russian History Repeating in the US? 26:48 - How Competition Stabilizes Societies 32:14 - What Data Goes into Cliodynamic Models? 38:13 - How New Technologies Shaped Archaeology 43:28 - Can Historians Build Mathematical Intuitions? 47:59 - What Questions can be Answered with Cliodynamics? 52:23 - Does the NYC Mayoral Race Fit into Turchin's Theory? 56:37 - Is Fear of China Bringing Us Together? 58:29 - Do Historians Reject Turchin’s Work? 1:00:03 - Trends in Civilizations and Outliers 1:03:29 - Calvary and the Evolution of Societies 1:10:03 - Is Evolution via Natural Selection a Suitable Analog for History? 1:15:16 - Could Turchin's Ideas Be Misinterpreted Dangerously?
Oct 21, 2025 · 1 hr
Why Do Quantum Computers Make So Many Mistakes? | Mikhail Lukin on Quantum Error Correction
You can’t copy a qubit. So how do quantum computers remember anything? In this episode, we sit down with Mikhail Lukin, Harvard physicist and co-director of the Harvard Quantum Initiative, whose lab is building quantum computers from arrays of individually trapped atoms. Lukin explains the paradox of quantum error correction—how you can safeguard quantum information even though it can’t be copied or measured directly—and why this breakthrough may be the key to making large-scale quantum computers possible. We dive into the strange logic of superposition, entanglement, and “small cat states,” explore what makes quantum evolution inherently analog, and learn how Lukin’s team uses optical tweezers and Rydberg interactions to engineer stable, reconfigurable qubits—atoms literally held and moved by light. Whether you’re fascinated by quantum mechanics, computing, Schrödinger’s cat, or the future of information, this conversation reveals how physicists are turning the weirdness of quantum physics into working technology—and why building a fault-tolerant quantum computer is one of the hardest and most exciting challenges in science today. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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! Michael Dubrovsky: https://x.com/MikeDubrovsky Misha Shalaginov: https://x.com/MYShalaginov Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 01:32 - Fundamentals of Quantum Computers 04:09 - Transistors vs Quantum Gates 10:07 - What is Quantum Error Correction? 14:23 - State of the Art QEC 22:19 - Quantum Research Before Lukin 27:35 - Lukin’s Breakout Work 31:10 - From Quantum Optics to Quantum Computing 36:59 - Working with Neutral Atoms 48:17 - Funding Quantum Computers 50:00 - Transverse Gate Operations 58:22 - Is Quantum Computing All Hype? #quantumcomputing #quantumerrorcorrection #mikhaillukin #qubits #schrodingerscat #entanglement #superposition #quantumphysics
Oct 9, 2025 · 1 hr 5 min
We Interviewed the Winners of the Ig Nobel Prize | Ig Nobel 2025
The scientific stories behind this year's research that made people LAUGH, then THINK. Watch the 2025 Ig Nobel Ceremony here: https://youtu.be/z1cP4xKd_L4 In this episode, we bring together three of this year’s Ig Nobel winners whose research spans psychology, food science and human biology. You’ll hear how a team of psychologists devised a counter-intuitive way to boost a narcissist’s self-confidence; how two physicists uncovered the “mozzarella phase” of pecorino cheese while perfecting cacio e pepe; and how a group studying lactation discovered that garlic changes breast-milk’s aroma and baby behavior. We explore the playful setups, surprising results and serious science behind each project, and how curiosity, humor and a dash of persistence turned ordinary questions into prize-winning research. Follow us for more technical interviews with the world’s greatest scientists: Twitter: https://x.com/632nmPodcast Instagram: 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! Michael Dubrovsky: https://x.com/MikeDubrovsky Misha Shalaginov: https://x.com/MYShalaginov Xinghui Yin: https://x.com/XinghuiYin Subscribe: Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269 Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR Website: https://www.632nm.com Timestamps: 00:00 - Intro 01:19 - Physics Prize: Cacio e Pepe Sauce 30:40 - Pediatrics Prize: Garlic Breast Milk 44:48 - Psychology Prize: How to Boost Narcissism #ignobel2025 #cacioepepe #pastasauce #thermodynamics #psychology #dairy #pecorino