632nm

What does it actually take to build a quantum computer that can scale to millions of qubits?Learn more about Qolab here: https://qolab.ai/In this episode, we speak with John Martinis, recipient of the 2025 Nobel Prize in Physics. Martinis is a pioneer in superconducting quantum computing and led the team of engineers at Google Quantum AI during the development of their Sycamore chip, which was the first to demonstrate “Quantum Supremacy,” the outperformance of a quantum computer compared to a classical supercomputer.John is now the co-founder of Qolab, a company developing new approaches to building scalable superconducting quantum circuits. Martinis discusses why scaling quantum computers is fundamentally an engineering and manufacturing problem, and why the next generation of quantum hardware may require rethinking how the chips themselves are designed and fabricated.We explore the challenges of building superconducting qubits, from fabrication and packaging to control electronics, wiring, power dissipation, and the subtle imperfections that can determine whether a quantum chip works at all. Martinis explains why adding more qubits is not simply a matter of making existing systems larger. At the scale of hundreds of thousands or millions of qubits, every component has to work together, and improvements in one part of the system can create new problems somewhere else.Martinis describes the philosophy behind Qolab and its effort to develop a fundamentally different architecture for scalable quantum computing. Rather than simply pushing existing approaches forward, Qolab is trying to remake the individual elements of the system and integrate them in new ways. We discuss wafer-scale fabrication, the challenges of connecting and controlling large numbers of superconducting qubits, and why the manufacturing techniques used to build modern semiconductor chips could be important for the future of quantum computing.We also discuss the practical engineering lessons Martinis learned while developing superconducting quantum processors, including the difficulty of getting an entire system to work reliably. He recounts the development of the hardware behind Google's early quantum computing efforts, the unexpected failure caused by a circuit board rather than the qubit chip itself, and the many subtle fabrication and engineering issues that can become increasingly important as quantum systems grow larger.Finally, Martinis explains why he sees quantum computing as a system engineering problem involving dozens of interconnected constraints. From the physics of superconducting qubits to semiconductor fabrication, cryogenic electronics, packaging, and control, building a useful quantum computer requires solving many problems simultaneously. The goal is not simply to build a better qubit, but to develop an architecture that can ultimately support quantum computers at truly large scale.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://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/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: https://www.632nm.comTimestamps:00:00 - Intro01:06 - Secrecy of Fabrication03:24 - 2 Qubit Gate with Transmons05:18 - New Knowledge of Superconducting Quantum Computers08:53 - What are Transmons?35:56 - Lessons from Failure38:05 - The Role of Theory in Martinis’ Work44:51 - Two Level States48:15 - Engineering Tricks in Superconducting Quantum Computers53:32 - Metrics for Quantum Success1:00:11 - Scaling Quantum Computers1:08:08 - Identifying Sources of Error1:16:15 - Quantum Supremacy Experiment1:25:45 - What If Quantum Mechanics Failed?1:33:10 - Is Quantum Supremacy Holding Up?1:34:42 - Lift-off Fabrication for Superconducting Quantum Computers1:41:59 - Quantum Flexibility vs Foundries1:43:40 - Connecting Distant Qubits1:47:41 - Codesign for Fault-Tolerance1:49:16 - Martinis’ Nobel Prize2:01:55 - Advice for Young Scientists#quantumcomputing #quantumphysics #superconductor #nobelprize #fabrication

What does a cell actually look like when you can see its molecules in action?In this episode, we speak with Nobel Prize-winning scientist Eric Betzig, whose pioneering work in super-resolution microscopy transformed our ability to see inside living cells. Betzig recounts his decades-long effort to overcome the diffraction limit of light microscopy, from his early work in near-field microscopy to the development of PALM and his eventual focus on watching biological processes unfold in living cells.We explore why the familiar picture of the cell in biology textbooks may be fundamentally misleading. Much of cell biology has been built by combining observations from biochemistry, molecular biology, and structural biology to construct models of how molecules interact. But, as Betzig explains, we have historically had very little direct information about the spatial organization and dynamics of these molecules inside a living cell. When he and his colleagues used single-molecule microscopy to watch transcription factors in real time, they found that proteins believed to form stable complexes were instead binding to DNA for only a few seconds, forcing them to reconsider how transcription actually works.We discuss the diffraction limit, why conventional light microscopes cannot resolve structures at the scale of individual proteins, and how super-resolution microscopy made it possible to study molecular processes with unprecedented spatial and temporal resolution. Betzig also explains why imaging living cells can reveal dynamics that are invisible in fixed samples.Betzig describes his ambitious Cell Observatory project, which combines automated microscopy, large-scale biological experiments, and artificial intelligence to study the enormous complexity of living cells. Rather than trying to build a “virtual cell” from incomplete measurements, he argues that biology first needs to observe these systems at a much larger scale and turn the resulting data into genuine understanding.Finally, Betzig reflects on what microscopy has taught him about scientific discovery, why the cell may be the most complex form of matter we know, and why better ways of observing life could fundamentally change our understanding of biology.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://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/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: https://www.632nm.comTimestamps:00:00 - Intro01:30 - The Diffraction Limit12:30 - Imaging Cells19:04 - Betzig's Transition from Physics to Biology32:37 - Getting Fed Up with Science34:57 - Leaving Science for the Automotive Industry55:55 - 2008 and the Fall of the Automotive Industry1:09:50 - Building a Microscope in a Living Room1:34:01 - Insights from Super-Resolution Microscopy1:47:53 - AI for Analyzing Petabytes of Data2:10:35 - Improving Microscopes2:15:27 - Nuclear Energy and Politics2:23:18 - The Magic of Bell Labs2:36:17 - Is SpaceX the New Bell Labs?#microscopy #cellbiology #superresolution #fluorescence #nobelprize

Why is controlling a quantum hardware becoming one of the biggest challenges in scaling quantum computers?In this episode, we speak with Yonatan Cohen, co-founder and CTO of Quantum Machines, a company developing advanced control systems for quantum computers. Cohen explains how quantum control sits at the interface between quantum hardware and classical computing, and why this hybrid architecture will become increasingly important as quantum processors scale.We explore how quantum computers are controlled using precise microwave signals and pulse sequences, the limitations of conventional arbitrary waveform generators, and how Quantum Machines uses FPGA-based pulse processing units to generate waveforms in real time. We also discuss why low-latency classical processing and real-time feedback are essential for calibrating quantum processors, correcting errors, and implementing increasingly complex quantum algorithms. Cohen explains what changes when moving from small quantum processors to thousands or millions of qubits, including the challenges of data movement, power consumption, control-channel density, and latency. We also discuss quantum error correction, feed-forward operations, hybrid quantum-classical architectures, and the role of CPUs, GPUs, and FPGAs in stabilizing large-scale quantum systems. We also discuss the origins of Quantum Machines, the company's approach to quantum control, and why building scalable quantum computers requires much more than simply increasing the number of qubits.Whether you're interested in quantum computing, quantum control, quantum error correction, computer architecture, FPGA technology, or the future of fault-tolerant quantum computers, this episode provides a deep technical look at the control infrastructure required to make large-scale quantum computing 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://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/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: https://www.632nm.comTimestamps:00:00 - Intro and Reads02:37 - Quantum Machines and Hybrid Architecture06:04 - Why Do Classical Computers Need Quantum Processors?10:02 - State of the Art Controllers20:02 - Meeting Itamar24:01 - FPGAs for Quantum29:29 - Repurposing FPGAs35:22 - Remote Direct Memory Access (RDMA)41:29 - What If We Had Perfect Controllers?43:26 - Adaptive and Embedded Calibrations47:15 - Picks and Shovels of Quantum Computing49:14 - Progress in Different Qubits53:25 - Keeping Up with Quantum News and Research56:51 - Core Advantages of Quantum Machines1:00:06 - Managing Larger Teams1:02:12 - Discovering New Physics with Quantum Machines1:14:31 - Reinforcement Models in Quantum1:16:45 - Yonatan’s Intro to Quantum Computing1:21:24 - Realtime Correction vs Post Processing1:32:10 - Channel Numbers and Interfering Signals1:39:38 - Connecting Multiple Modules1:46:46 - Early Believers in Quantum Machines1:51:05 - What Would Yonatan Do With Unlimited Resources?#quantumcomputing #quantumphysics #computerscience #fpga #coding

How did we go from knowing almost nothing about genes to sequencing the entire human genome?In this episode, we speak with Nobel Prize-winning molecular biologist Walter Gilbert, whose discoveries helped lay the foundation for modern genomics. Gilbert recounts his remarkable journey from theoretical physics into biology, where he helped discover messenger RNA, uncovered the molecular mechanisms of gene regulation, invented one of the first practical methods for sequencing DNA, and later co-founded Biogen, one of the world's first biotechnology companies.We explore the race to understand how genes work, the search for the elusive lac repressor, how a chance experiment led to the invention of DNA sequencing, and why Gilbert believed decades in advance that sequencing the human genome would transform biology into an information science. He explains the origins of the Human Genome Project, the rise of computational biology, and why today's era of AI-driven genomics was already visible in the earliest DNA sequence databases.We also discuss the RNA World hypothesis, how life may have begun with self-replicating RNA molecules, the evolution of gene regulation, exon shuffling, the origins of protein domains, recombinant DNA technology, the birth of the biotechnology industry through Biogen, and how scientific revolutions often emerge from unexpected experiments.Finally, Gilbert reflects on creativity in both science and art, explaining why, after a lifetime of pioneering discoveries, he left the laboratory to pursue digital abstract art.Whether you're interested in DNA sequencing, the Human Genome Project, molecular biology, biotechnology, computational biology, the origin of life, RNA World, gene regulation, genomics, or the history of modern biology, this episode offers a firsthand account from one of the scientists who helped build the field.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://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/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: https://www.632nm.comTimestamps:00:00 - Intro02:34 - Jim Watson and Beginning Biology06:58 - Lac Repressor15:27 - Picking Good Problems17:57 - Developing the First Generation of Sequencing31:09 - The Birth of the Human Genome Project40:00 - Origins of Life43:35 - RNA World Hypothesis54:45 - Experiments vs Theory in Biology59:07 - Inspiration from Other Discoveries1:12:08 - Starting Biogen1:22:24 - Balancing Industry and Academia1:27:45 - Advice for CEOs1:32:48 - Perspectives on Art and Science1:37:49 - Walter’s Journey through Art1:44:55 - Walter’s Artistic Process and Inspirations1:50:32 - The Role of Theory in Biology1:55:51 - Frontiers and Guidance in Science1:59:37 - Should Everyone Get Sequenced?#biology #dnasequencing #originsoflife #genetics #humangenomeproject

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/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://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/id1751170269Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6ORWebsite: https://www.632nm.comTimestamps:00:00 - Intro and Reads02:42 - Biased Random Walk10:27 - Manson's Work with Howard Berg13:24 - Proton Motive Force and Flagellum29:07 - Rotors and Stators of Flagella37:20 - Mot Proteins57:34 - CheY and Changing Direction1:11:48 - Biology and Intelligent Design1:26:52 - Reversing Proton Flow1:29:59 - Life at Low Reynolds Number1:39:15 - Mysteries in the 90s and 2000s1:48:34 - Applications of Understanding the Nanomotor1:58:33 - Flagellar Motor Crash Course2:01:46 - Bacterial Learning and Adaptation2:05:56 - Giving Up on Birds2:14:09 - Caltech2:21:38 - Advice for Young Scientists2:30:02 - Origins of Life2:31:19 - What's Left for the Flagellar Motor?PART 2:2:33:33 - Building the Nanomotor2:39:29 - Other Types of Flagella2:47:06 - MotA and MotB3:07:17 - Reusing Motors Across Biology3:10:13 - Benefits of Being Small3:12:34 - CheY and Changing Direction3:19:39 - How Physics Shapes Evolution