『632nm』のカバーアート

632nm

632nm

著者: Misha Shalaginov Michael Dubrovsky Xinghui Yin
無料で聴く

概要

Technical interviews with the greatest scientists in the world.© 2026 Misha Shalaginov, Michael Dubrovsky, Xinghui Yin 博物学 科学 自然・生態学
エピソード
  • How Quantum Sensors Can Measure Single Electrons | Amir Yacoby
    2026/05/05

    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

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    2 時間 1 分
  • The Physics of Un-Hackable Face Recognition | Rob Devlin on Metalenz
    2026/04/21

    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

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    1 時間 14 分
  • The Real Economics of Data Centers in Space | Starcloud CEO Philip Johnston
    2026/04/01

    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

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    1 時間 38 分
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