From First Principles

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.

From First Principles is a science podcast hosted by Krishna Choudhary and Lester Nare, with 57 episodes on record and a Required Pod Score of 80.

Krishna Choudhary and Lester Nare hosts From First Principles, a science show with 57 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Episode #59

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

  Sep 29, 20262h 7mS1

  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

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  Episode #58

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

  Sep 24, 20264h 9mS1

  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 fluid Velocity fields, incompressibility, pressure and the nonlinear convective term Why viscosity smooths a fluid while nonlinear motion can create finer structure What finite-time blowup means, and why simulation is different from proof How forced and unforced equations differ, and why those assumptions matter Earlier work on Euler, Boussinesq and related fluid equations OpenAI’s claimed result, Lean verification and the scope of the theorem The dispute over scientific credit and the human research behind AI-assisted work The METR investigation of the Hugging Face incident Emergence World and long-running multi-agent experiments AI-assisted biological discovery, oversight and recursive self-improvement Separating demonstrated capabilities from claims and future scenarios Chapters 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

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  Episode #57

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

  Sep 14, 20261h 4mS1

  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.

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  Episode #56

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

  Sep 7, 20261h 36mS1

  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 communication How multiple sclerosis damages myelin and why the brain’s natural repair process eventually fails Why oligodendrocyte precursor cells can remain present in damaged tissue without successfully rebuilding myelin Why current therapies are better at slowing further damage than restoring what has already been lost The challenge of getting drugs across the blood-brain barrier while maintaining target specificity How evolutionary pharmacology has previously produced medicines from adaptations found in snakes and Gila monsters The RETSAT Q247R variant identified in animals adapted to the hypoxic environment of the Tibetan Plateau How researchers engineered the high-altitude variant into mice and tested its effect on myelin The surprising discovery that neurons — rather than the myelin-producing cells themselves — generate the key repair signal How RETSAT increases ATDR, which neurons convert into ATDRA How ATDRA activates RXR-γ in oligodendrocyte precursor cells and promotes their differentiation How administration of ATDR promoted remyelination across multiple preclinical models Why the result is scientifically promising but still far from a proven human treatment Featured 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 FFP ffppod.comffppod.com/fundingffppod.com/transfersffppod.com/America250 Support the show ffppod.com/donate Follow @FFPPod on X / Instagram / TikTok / Facebook

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  Episode #55

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

  Aug 31, 20263h 46mS1

  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

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