From First Principles – Détails, épisodes et analyse

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From First Principles

Krishna Choudhary and Lester Nare

Sciences

Fréquence : 1 épisode/7j. Total Éps: 60

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.

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2026 Nobel Prize Predictions: Medicine, Physics & Chemistry (EP 60)

Saison 1 · Épisode 60

samedi 3 octobre 2026 • Durée 40:31

Who could win the 2026 Nobel Prizes? From the science behind Ozempic to quantum interference and droplets inside living cells, Lester Nare and Krishna Choudhary make their picks for Medicine, Physics and Chemistry, and explain the discoveries behind them.

In Episode 60 of From First Principles, we explore seven research areas with a case for Nobel recognition: GLP-1, optogenetics, optical coherence tomography, the Aharonov–Bohm effect, atomic force microscopy, biomolecular condensates and Buchwald–Hartwig coupling. We also discuss Michael Berry’s geometric phase and the awkward question of how a prize limited to three people recognizes discoveries built by larger teams.

These are our predictions, recorded before the 2026 announcements. Medicine, Physics and Chemistry will be announced October 5–7. Which discovery, and which researchers, would you pick? Tell us in the comments, then join us for our Nobel week breakdowns.

CHAPTERS

00:00 The science that could win a Nobel Prize

00:57 Hello Internet: our 2026 predictions

02:03 Medicine: GLP-1 and the science behind Ozempic

07:41 Medicine: optogenetics and controlling neurons with light

13:16 Medicine: optical coherence tomography

16:28 Golden Goose Awards and FFP updates

18:39 Physics: the Aharonov–Bohm effect and geometric phase

27:37 Physics: atomic force microscopy

32:04 Chemistry: biomolecular condensates

36:36 Chemistry: Buchwald–Hartwig coupling

38:42 Your predictions and our Nobel week plans

RESEARCH & FURTHER READING

Foundational papers and background for the discoveries discussed:

GLP-1: Mojsov, Weir & Habener (1987)

https://doi.org/10.1172/JCI112855

Optogenetics: Boyden et al. (2005)

https://doi.org/10.1038/nn1525

Optical coherence tomography: Huang et al. (1991)

https://doi.org/10.1126/science.1957169

Aharonov–Bohm effect (1959)

https://doi.org/10.1103/PhysRev.115.485

Berry’s geometric phase (1984)

https://doi.org/10.1098/rspa.1984.0023

Atomic force microscopy: Binnig, Quate & Gerber (1986)

https://doi.org/10.1103/PhysRevLett.56.930

Biomolecular condensates: Brangwynne et al. (2009); Li et al. (2012)

https://doi.org/10.1126/science.1172046

https://doi.org/10.1038/nature10879

Buchwald–Hartwig coupling: Paul et al. (1994); Guram et al. (1995)

https://doi.org/10.1021/ja00092a058

https://doi.org/10.1002/anie.199513481

Official Nobel announcement schedule:

https://www.nobelprize.org/prizes/about/prize-announcement-dates/

EDITORIAL NOTES

19:30 David Bohm later held a professorship at Birkbeck, University of London (1961–1987); he did not spend the rest of his career in Brazil.

33:23 The ribosome-producing compartment discussed is the nucleolus, not the nucleosome. These corrections also appear on screen.

WATCH & EXPLORE

YouTube: https://youtu.be/MgOpbh5VUGE

Episode page and research library: https://ffppod.com/episodes/ep60

Support: https://ffppod.com/donate

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Breaking down science news so it makes sense to curious people everywhere.

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

Saison 1 · Épisode 59

mardi 29 septembre 2026 • Durée 02:07:22

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

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

Saison 1 · Épisode 58

jeudi 24 septembre 2026 • Durée 04:09:02

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 Agents3:08:57 The METR report and Hugging Face incident3:23:23 AI Risk, Oversight and the Race Ahead3:38:51 AI Discovery Beyond Mathematics3:52:47 Why “just turn it off” gets complicated4:06:47 Closing thoughts and what comes next4:08:46 Outro

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

Saison 1 · Épisode 57

lundi 14 septembre 2026 • Durée 01:03:30

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

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

Saison 1 · Épisode 56

lundi 7 septembre 2026 • Durée 01:35:37

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

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

Saison 1 · Épisode 55

lundi 31 août 2026 • Durée 03:46:20

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.

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

Saison 1 · Épisode 54

jeudi 20 août 2026 • Durée 02:11:10

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.

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

Saison 1 · Épisode 53

vendredi 14 août 2026 • Durée 01:47:25

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.

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

Saison 1 · Épisode 52

jeudi 6 août 2026 • Durée 01:47:13

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:

The Tech Elon Has Been Waiting For (EP 51)

Saison 1 · Épisode 51

vendredi 31 juillet 2026 • Durée 01:44:27

What happens when electronics can operate at temperatures hot enough to melt aluminum?

In this deep-dive episode, Lester Nare and Krishna Choudhary examine a new high-temperature memory device developed by researchers at USC, the Air Force Research Laboratory, Kumamoto University, and their collaborators.

Published in Science, the experimental memristor combines tungsten, hafnium oxide, and graphene. It operated reliably at 700°C—roughly 1,300°F—retained data for more than 50 hours, and survived more than one billion switching cycles.

We begin by explaining why conventional electronics and flash memory fail when temperatures rise. From deep-earth drilling and hypersonic aircraft to nuclear systems and the surface of Venus, many environments where intelligent electronics would be useful remain inaccessible to today’s hardware.

Krishna then builds the memristor from first principles. We explore the history of the “missing” fourth circuit element, how oxygen vacancies create low- and high-resistance memory states, why conventional platinum electrodes fail under extreme heat, and how graphene prevents tungsten atoms from diffusing through the device.

Finally, we examine the implications for artificial intelligence. Memristors can potentially store neural-network weights and perform matrix multiplication in the same physical location, reducing the energy wasted moving information between processors and memory.

Could that combination of heat tolerance and energy efficiency make AI data centers in space more practical? Lester and Krishna work through thermal radiation, radiator size, power consumption, radiation resilience, and the considerable engineering challenges that remain.

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Research and Show Notes

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