From First Principles

Krishna Choudhary and Lester Nare
  • 4.9 (192)
  • Science
  • Updated Weekly

From First Principles is a fast, funny, and rigorous breakdown of the biggest science stories of the week, hosted by Lester Nare and physicist Krishna Choudhary, PhD. We go past headlines into the actual mechanics: what happened, why it matters, and what everyone’s missing. Expect physics, space, AI, energy, biotech, and the occasional “wait… is that real?” story. If you’re curious, skeptical, and you like learning in public — you’re in the right place.

  1. 2d ago

    Golden Goose Awards 2026: The Science Behind the Winners (Part 1) (EP 59)

    What connects a noise complaint, holiday lights seen from space, and the physics of a coffee stain? Three unexpected paths from basic research to discoveries with real-world impact. Krishna Choudhary and Lester Nare explore the science behind the 2026 Golden Goose Awards: Zhen Xu's work on histotripsy, NASA's Black Marble nighttime satellite data, and Sidney Nagel's discoveries in soft matter physics. We start with focused ultrasound and the tiny bubbles that can break apart targeted tissue, tracing the journey from early laboratory experiments to clinical research on liver tumors. Then we look at how Earth's nighttime lights reveal power outages, disaster recovery, and changing human activity. Finally, falling drops, coffee stains, and jammed grains open up a world of robotic grippers and materials that can be trained and retrained. The thread connecting all three stories is the unexpected value of federally funded basic research. Part 2 will feature conversations with the award-winning researchers and AAAS CEO Sudip Parikh. CHAPTERS 00:00 Golden Goose Awards trailer 01:19 Introducing our Golden Goose special 02:42 Zhen Xu: From a noise complaint to histotripsy 05:57 The early ultrasound experiments 13:42 Controlling cavitation with microtripsy 20:29 Tumor destruction and the immune response 28:33 Histotripsy through the skull 37:23 The HOPE4LIVER clinical trial 43:55 Why basic research needs time 47:17 FFP updates and supporting the show 49:20 NASA Black Marble: Holiday lights from space 55:29 Turning night lights into reliable data 1:01:36 Hurricane Maria and unequal recovery 1:08:12 COVID-19 and changing nighttime activity 1:10:16 Mapping access to electricity 1:15:20 Where Earth is brightening and dimming 1:32:57 Sidney Nagel and the physics of everyday life 1:37:07 The science of a falling drop 1:46:02 Why coffee leaves a ring 1:51:04 Jamming: When grains become rigid 1:53:35 A robotic gripper filled with grains 1:55:39 Why air pressure changes a splash 1:58:55 Materials that can be trained and retrained 2:03:26 The payoff from curiosity 2:05:29 Coming in Part 2 2:07:06 Outro FEATURED RESEARCH Histotripsy: The #HOPE4LIVER single-arm pivotal trial (Radiology, 2024) https://doi.org/10.1148/radiol.233051 NASA's Black Marble nighttime lights product suite (Remote Sensing of Environment, 2018) https://doi.org/10.1016/j.rse.2018.03.017 Training and retraining liquid crystal elastomer metamaterials for pluripotent functionality (PNAS, 2025) https://doi.org/10.1073/pnas.2504304122 WATCH ON YOUTUBE https://youtu.be/rDInUEtTojg EXPLORE FFP Website: https://ffppod.com Science Funding Tracker: https://ffppod.com/funding Science Transfer Portal: https://ffppod.com/transfers America 250: https://ffppod.com/America250 SUPPORT THE SHOW https://ffppod.com/donate FOLLOW @FFPPod on X / Instagram / TikTok / Facebook

  2. Sep 24

    What OpenAI Actually Did to Navier-Stokes (EP 58)

    What does it mean to solve an equation that describes almost every fluid around us, from the air over a wing to the water swirling down a drain? In Episode 58 of From First Principles, Lester Nare and Krishna Choudhary build the Navier-Stokes equations from the ground up before digging into OpenAI’s claimed breakthrough and the debate surrounding it. Summary How Newton’s laws become equations for a moving fluidVelocity fields, incompressibility, pressure and the nonlinear convective termWhy viscosity smooths a fluid while nonlinear motion can create finer structureWhat finite-time blowup means, and why simulation is different from proofHow forced and unforced equations differ, and why those assumptions matterEarlier work on Euler, Boussinesq and related fluid equationsOpenAI’s claimed result, Lean verification and the scope of the theoremThe dispute over scientific credit and the human research behind AI-assisted workThe METR investigation of the Hugging Face incidentEmergence World and long-running multi-agent experimentsAI-assisted biological discovery, oversight and recursive self-improvementSeparating demonstrated capabilities from claims and future scenariosChapters 00:00 Can AI solve Navier-Stokes? 00:34 Episode introduction 02:20 Navier-Stokes: Mathematics Meets AI 10:20 Building the Equations of Fluid Motion 21:34 Velocity fields, divergence and incompressibility 34:33 Acceleration and the convective term 52:18 Why Fluid Motion Is Nonlinear 1:02:08 Pressure, Euler and the Missing Physics 1:14:50 How Viscosity Changes Everything 1:33:36 Solving Equations vs. Simulating Fluids 1:44:59 Can a Smooth Fluid Blow Up? 2:13:52 The Road to the Claimed Breakthrough 2:31:13 Inside the Claimed Navier-Stokes Proof 2:48:26 The Dispute Over Scientific Credit 3:07:23 From Chatbots to Agents 3:08:57 The METR report and Hugging Face incident 3:23:23 AI Risk, Oversight and the Race Ahead 3:38:51 AI Discovery Beyond Mathematics 3:52:47 Why “just turn it off” gets complicated 4:06:47 Closing thoughts and what comes next 4:08:46 Outro Featured Research OpenAI’s Navier-Stokes announcement Tristan Buckmaster’s statement METR investigation Emergence World AI-assisted enzyme discovery Explore FFP ffppod.com ffppod.com/funding ffppod.com/transfers ffppod.com/America250 Watch on YouTube youtu.be/NGfGw1tGxUY Support the show ffppod.com/donate Follow @FFPPod on X / Instagram / TikTok / Facebook

  3. Sep 14

    What’s Next in Science? Nobel Prizes, Space Missions & More (EP 57)

    What science should you be watching this fall? From Nobel Prize season to NASA’s Roman Space Telescope, Mars’ moons and Mercury, Lester Nare and Krishna Choudhary take a relaxed tour of the discoveries and missions on their radar. In Episode 57 of From First Principles, we explore why curiosity-driven research matters, what the Golden Goose Awards celebrate, and how questions that once sounded impractical can lead to unexpected breakthroughs. Then we turn to space: Roman’s search for dark energy and exoplanets, JAXA’s Martian Moons eXploration (MMX) mission, and the mysteries ESA and JAXA’s BepiColombo mission will investigate at Mercury. Along the way, we tour the updated FFP website, revisit some favorite episodes, and ask which stories you want us to cover in depth next. A note before we begin: the main conversation was recorded before Labor Day weekend. The opening announcement addresses your requests for a separate episode on OpenAI, Navier–Stokes and the wider AI conversation. This episode is our fall science rundown; that deep dive is still to come. CHAPTERS 00:00 Update on our upcoming Navier–Stokes and AI coverage 03:43 Episode intro and football banter 05:47 FFP intro 06:01 Nobel Prize season and our coverage plans 10:45 Golden Goose Awards: why basic research matters 21:02 FFP website tour and favorite episodes 42:24 Nancy Grace Roman Space Telescope 46:20 Microlensing, exoplanets and dark matter 51:25 MMX: where did Mars’ moons come from? 54:40 BepiColombo and the mysteries of Mercury 1:02:17 Your questions, future deep dives and sign-off 1:05:40 Outro SHOW NOTES NASA’s Nancy Grace Roman Space Telescope: https://science.nasa.gov/mission/roman-space-telescope/ JAXA’s Martian Moons eXploration (MMX): https://www.mmx.jaxa.jp/en/mission/ ESA / JAXA BepiColombo: https://www.esa.int/Science_Exploration/Space_Science/BepiColombo Explore the research and episodes we cover: https://ffppod.com Science R&D Funding Tracker: https://ffppod.com/funding Science Transfer Board: https://ffppod.com/transfers America 250: https://ffppod.com/America250 Support the show: https://ffppod.com/donate WATCH ON YOUTUBE https://youtu.be/snhQh0fjTX4 Follow @FFPPod on X / Instagram / TikTok / Facebook Breaking down science news so it makes sense to curious people everywhere. Which mission or research story deserves a full FFP deep dive? Tell us in the comments.

  4. Sep 7

    The Yak Mutation That Could Help Repair the Brain (EP 56)

    What can a yak living thousands of meters above sea level teach us about repairing the human brain? In Episode 56 of From First Principles, Lester Nare and Krishna Choudhary break down a new Neuron paper that traces an evolutionary adaptation found in high-altitude animals to a previously hidden pathway involved in building and repairing myelin. Summary What myelin actually does and why losing it disrupts neural communicationHow multiple sclerosis damages myelin and why the brain’s natural repair process eventually failsWhy oligodendrocyte precursor cells can remain present in damaged tissue without successfully rebuilding myelinWhy current therapies are better at slowing further damage than restoring what has already been lostThe challenge of getting drugs across the blood-brain barrier while maintaining target specificityHow evolutionary pharmacology has previously produced medicines from adaptations found in snakes and Gila monstersThe RETSAT Q247R variant identified in animals adapted to the hypoxic environment of the Tibetan PlateauHow researchers engineered the high-altitude variant into mice and tested its effect on myelinThe surprising discovery that neurons — rather than the myelin-producing cells themselves — generate the key repair signalHow RETSAT increases ATDR, which neurons convert into ATDRAHow ATDRA activates RXR-γ in oligodendrocyte precursor cells and promotes their differentiationHow administration of ATDR promoted remyelination across multiple preclinical modelsWhy the result is scientifically promising but still far from a proven human treatmentFeatured Paper A gain-of-function Retsat variant from high-altitude adaptation promotes myelination via a neuronal dihydroretinoic acid-RXR-γ pathway Neuron, 2026 DOI: 10.1016/j.neuron.2026.01.013 Explore FFPffppod.comffppod.com/fundingffppod.com/transfersffppod.com/America250 Support the showffppod.com/donate Follow@FFPPod on X / Instagram / TikTok / Facebook

  5. Aug 31

    Why Spin Qubits Will Win the Quantum Race (Part 2) (EP 55)

    Which quantum computer will actually scale? In Part 2 of our quantum computing deep dive, Lester Nare and Krishna Choudhary move from theory to hardware—comparing superconducting qubits, trapped ions, neutral atoms, and silicon spin qubits before going inside the new Nature cover paper Krishna co-authored with the HRL Quantum Team and collaborators. The episode begins with a simple question: what makes a good quantum computer? We evaluate each architecture using three criteria: qubit quality, qubit control, and scalability and economics. Superconducting qubits offer extremely fast operations, but scaling them introduces challenges involving microwave control, frequency crowding, cryogenic wiring, physical size, and cooling. Trapped ions preserve quantum information for extraordinary lengths of time, but their slower gates and increasingly complex optical systems introduce a different set of tradeoffs. Neutral atoms can be arranged in dense, reconfigurable arrays using optical tweezers and entangled through Rydberg interactions, while raising questions involving atom loss, correlated noise, readout, and execution time. Then we get to silicon. Beginning with the Loss–DiVincenzo proposal, Krishna explains how individual electron spins can be confined inside semiconductor quantum dots, manipulated through exchange interactions, and measured using single-electron transistors. We then explore exchange-only qubits, where three electron spins encode a single qubit and quantum gates can be performed using electrical control. That leads to the Nature cover paper, A digitally controlled silicon quantum processing unit. The HRL system integrates 18 encoded qubits built from 54 quantum dots with cryogenic control electronics, a superconducting interconnect, automated calibration, and an engineered silicon-germanium heterostructure. Krishna also explains his own work using machine learning to automate quantum-device tuning—an essential problem if spin-qubit systems are ever going to grow from dozens of components to millions. The larger thesis is about manufacturing. The semiconductor industry has spent decades learning how to fabricate silicon devices at enormous scale. If quantum processors can inherit that infrastructure, the architecture that ultimately wins may not be the one that reaches the finish line first—but the one humanity already knows how to manufacture. Nature paper:A digitally controlled silicon quantum processing unitDOI: 10.1038/s41586-026-10754-7https://www.nature.com/articles/s41586-026-10754-7 Explore the FFP Science Transfer Portal:ffppod.com/transfers Support the show:ffppod.com/donate Follow:@FFPPod on X / Instagram / TikTok / Facebook

  6. Aug 20

    How Quantum Computing Actually Works (Part 1) (EP 54)

    Quantum computers do not simply “try every answer at once.” So what do they actually do—and why have governments and technology companies spent billions trying to build them? In Part 1 of our two-part quantum computing deep dive, Lester Nare and Krishna Choudhary build the field from first principles. The series was prompted by a new Nature cover paper, A digitally controlled silicon quantum processing unit, co-authored by Krishna and members of the HRL Quantum Team and collaborators. Before getting into that hardware in Part 2, we first need to understand why anyone wanted to build a quantum computer in the first place. We begin with Bell’s theorem and the failure of local hidden-variable explanations of quantum mechanics. From there, we follow the realization that information is fundamentally physical through Rolf Landauer, reversible computation, Charles Bennett, Tommaso Toffoli, Paul Benioff, and the origins of quantum information science. Then Richard Feynman changes the question. Straightforward classical simulation of an interacting quantum system requires tracking a state space that grows exponentially with the number of particles. If nature itself is quantum mechanical, Feynman asks, why not build a computer that is quantum mechanical too? David Deutsch formalizes the universal quantum computer and introduces the first quantum algorithm. Using the Deutsch–Jozsa problem, the double-slit experiment, and Feynman’s path-integral intuition, we explain what a quantum algorithm is actually exploiting: carefully engineered constructive and destructive interference. Finally, we reach the discoveries that turned quantum computing from an academic curiosity into a strategic technology. Daniel Simon develops an early exponential quantum speedup. Peter Shor recognizes how the underlying mathematics can be used to attack problems central to public-key cryptography. Lov Grover follows with a quantum search algorithm—and suddenly governments have a very different reason to care about quantum machines. We also explore quantum money, quantum cryptography, the many-worlds interpretation, Google Willow and parallel-universe headlines, post-quantum security, and what useful quantum computers may ultimately be good for. Part 2: How do you actually build one? Nature paper:A digitally controlled silicon quantum processing unitDOI: 10.1038/s41586-026-10754-7 Link: https://www.nature.com/articles/s41586-026-10754-7 Explore the FFP science funding tracker:ffppod.com/funding Support the show:ffppod.com.com/donate Follow:@FFPPod on X / Instagram / TikTok / Facebook

  7. Aug 14

    What Claude Actually Did to the Riemann Hypothesis (EP 53)

    Claude did not solve the Riemann Hypothesis. But what it actually did may be one of the clearest examples yet of how rapidly AI systems are changing the way difficult mathematics can be attacked. In Episode 53, Lester Nare and Krishna Choudhary go from first principles on arguably the most famous unsolved problem in mathematics. We begin with Euler and the Basel problem, build the Riemann zeta function from the ground up, explain its deep connection to prime numbers, move into the complex plane and analytic continuation, unpack the famous 1 + 2 + 3 + 4 + … = -1/12 result, and finally arrive at the Riemann Hypothesis itself: the claim that every non-trivial zero of the zeta function lies on the critical line. Then we get into Claude. An unreleased Anthropic model was prompted to take a serious run at the problem. It orchestrated roughly 60 autonomous sub-agents, tested hundreds of mathematical approaches, executed code, searched academic literature, challenged its own strategies, created adversarial referees to attack its work, and ultimately produced a result pushing a related mathematical bound well beyond the previous state of the art. The human behind the prompt was not a mathematician. One of his instructions was essentially: believe in yourself. We explain what Claude actually accomplished, what it absolutely did not accomplish, why moving a bound toward two-thirds does not mean the Riemann Hypothesis is “two-thirds solved,” and what the process tells us about agentic AI, mathematical research, scientific discovery, and AI safety. Then it’s transfer season. For the first FFP Summer Transfer Window for Scientists, we look at prominent researchers leaving American institutions for universities and research centers abroad. Using the language of football transfers, we examine major moves in chemistry, battery research, gravitational-wave astrophysics, and neuroscience—and what they reveal about research funding, immigration, scientific infrastructure, and the global competition for talent. Explore the FFP science funding tracker:ffppod.com/funding Help shape Year Two and enter the anniversary merch giveaway:ffppod.com/survey Support the show:ffppod.com/donate Follow:@FFPPod on X / Instagram / TikTok / Facebook

  8. Aug 6

    The Amazon’s Hidden Civilization (One Year Anniversary) (EP 52)

    In this anniversary episode, Lester Nare and Krishna Choudhary look back at how two longtime friends turned their regular conversations about science into a show now shared by millions of people around the world, and what they hope to build with FFP Nation in Year Two. Then we turn to a new Nature paper challenging the idea that the precolonial Amazon was sparsely populated. Airborne LiDAR revealed hundreds of geometric earthworks hidden beneath the rainforest canopy. Combining the new survey with earlier archaeological evidence, the researchers estimate that the region could contain more than 20,000 earthworks and may have supported 1.25–3 million people around AD 100–300. Lester and Krishna explain how LiDAR sees through dense vegetation, why early European accounts of crowded Amazonian settlements were dismissed, how disease and forest regrowth could erase the visible traces of large societies, and what the findings mean for our understanding of the Amazon’s human and environmental history. The conversation then becomes a thought experiment: if our civilization disappeared, what would future archaeologists—or extraterrestrial visitors—recognize as our pyramids? Apollo landing sites, CERN, LIGO, and the James Webb Space Telescope become candidates for the enduring signatures of a curiosity-driven civilization. Finally, we christen the From First Principles library. Krishna shares the mathematics, physics, biology, history, and philosophy books that shaped how he thinks, including Baby Rudin, Landau–Lifshitz, Fermi, Jackson, Sakurai, Einstein, Schrödinger, Gibbs, Newton’s Principia, Plato, the Upanishads, and Adam Becker’s What Is Real? Help shape Year Two and enter the anniversary merch giveaway: ffpod.com/survey Support the show: ffppod.com/donate Research and show notes: Over 20,000 precolonial earthworks in the Southwest Amazonia Nature Research Briefing FFP episode archive and research library

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4.9
out of 5
192 Ratings

About

From First Principles is a fast, funny, and rigorous breakdown of the biggest science stories of the week, hosted by Lester Nare and physicist Krishna Choudhary, PhD. We go past headlines into the actual mechanics: what happened, why it matters, and what everyone’s missing. Expect physics, space, AI, energy, biotech, and the occasional “wait… is that real?” story. If you’re curious, skeptical, and you like learning in public — you’re in the right place.

Information

  • Creator
    Krishna Choudhary and Lester Nare
  • Years Active
    2025 - 2026
  • Episodes
    59
  • Rating
    Explicit
  • Copyright
    © Krishna Choudhary and Lester Nare
  • Show Website
    From First Principles

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