64 avsnitt
- 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
High-temperature memristors enabled by interfacial engineering
USC: A memory device that operates at 700°C
The development of carbon-neutral data centres in space
NASA Venus facts AI Breaks a 90-Year Math Problem, Life’s Alphabet in Space, and Science Funding (EP 50)
2026-07-23 | 1 h 52 min.Hosted by Lester Nare and Krishna Choudhary, this episode moves from astrobiology to science policy to the rapidly changing frontier of artificial intelligence and mathematics.
First, researchers analyzing pristine samples returned from asteroid Ryugu report all five canonical nucleobases used by DNA and RNA. We explain what that does—and does not—mean for the origin of life, how JAXA’s Hayabusa2 mission collected uncontaminated asteroid material, and why comparisons with NASA’s Bennu samples strengthen the case that prebiotic chemistry may be widespread across the Solar System.
Next, we examine the fight over who controls federal research funding. A proposed overhaul of the rules governing federal grants would give political appointees greater influence over awards, reduce the controlling role of expert peer review, and expand the government’s power to stop grants that no longer align with an administration’s priorities. We break down the roles of Congress, OMB, federal agencies, universities, and the courts—and why this dispute could reshape the American research ecosystem.
Finally, we go deep on an AI-assisted counterexample to the Jacobian conjecture, a major open problem in mathematics. Krishna explains coordinate transformations, Jacobian determinants, invertibility, special relativity, and why this result appears fundamentally different from simple brute force. We close with the growing debate over AI-generated mathematics, human verification, open science, attribution, and the future role of mathematicians.
Summary
All five canonical nucleobases found in pristine asteroid Ryugu samples
Hayabusa2, Bennu, and the possibility of widespread prebiotic chemistry
The fight over political control of federal research grants
Congress, OMB, peer review, and the American science-funding system
The Jacobian conjecture and an AI-assisted counterexample
Special relativity, coordinate transformations, and invertibility
AI-generated mathematics, open science, attribution, and verification
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Show Notes
A complete set of canonical nucleobases in asteroid Ryugu
OMB proposed federal-grant rule
Association of American Universities response
Levent Alpöge’s Jacobian counterexample announcement
Leiden Declaration on Artificial Intelligence and Mathematics
Human-verified remarks on the OpenAI-generated Erdős result- In this special interview episode, Lester Nare speaks with Juan Busso, Senior Football Data Scientist at FIFA, and Arron Ackerman, FIFA’s Team Lead for Football Performance Analysis, about the data science behind the Match Momentum visualization featured throughout the 2026 World Cup.
What does “momentum” actually mean in football—and how can it be measured without reducing the game to possession or shots? Juan and Arron explain how FIFA translates football principles into mathematical models, validates those models with coaches and technical experts, and turns complex tracking data into a graphic that fans can understand at a glance.
We break down the underlying “threat” model, including kinetic pitch control, player speed and acceleration, ball trajectories, defensive spacing, distance to goal, sight lines, and the creation of space. Match Momentum is calculated from player-tracking data captured 50 times per second, allowing the model to recognize when a team is becoming dangerous even without dominating possession.
The conversation also covers FIFA’s wider data ecosystem—including event data, skeletal tracking, and the connected match ball—why offside positioning can still create threat, whether hydration breaks alter momentum, and the next generation of football analytics focused on player energy and physical effort.
Guests
Juan Busso — Senior Football Data Scientist, FIFA
Arron Ackerman — Team Lead, Football Performance Analysis, FIFA
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Follow: @FFPod on X / Instagram / TikTok / Facebook - Hosted by Lester Nare and Krishna Choudhary, this episode returns to the FFP science rundown with stories spanning astrophysics, precision medicine, medical imaging, artificial intelligence, and World Cup technology.
We begin with the Event Horizon Telescope and its evolving view of M87*, the supermassive black hole 55 million light-years away. How do you image something that appears about as small as a donut on the Moon? Krishna explains angular resolution, the Rayleigh limit, radio interferometry, and how telescopes across Earth can function like one planet-sized instrument. We then look at new observations showing the magnetic field around M87* changing over time—and why that may help explain black-hole jets and the mysterious shutdown of star formation in giant elliptical galaxies.
Next, we turn to medicine. Researchers at Johns Hopkins have built personalized digital twins of patients’ hearts, allowing doctors to simulate ventricular-tachycardia treatments before entering the operating room. We break down how MRI data, electrical modeling, and virtual ablation could reduce procedures from hours to roughly 30 minutes. We also examine Midjourney Medical’s proposed whole-body ultrasound scanner: what the prototype appears to do, what its creators are claiming, and why it should be viewed as a potential addition to the medical-imaging toolbox rather than a replacement for MRI.
Finally, we return to the World Cup. Krishna takes on “Are You Smarter Than a Scientist?” by guessing the most common injuries in professional football. Then we investigate the Norway–England Skycam controversy: did the ball strike a cable, and why did its internal sensor appear not to detect it? We close with the data behind home-field advantage, referee bias, and the natural experiment created by crowdless matches during the COVID-19 pandemic.
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Follow: @FFPod on X / Instagram / TikTok / Facebook - Hosted by Lester Nare and Krishna Choudhary, this episode is part two of our July 4th America 250 special: a celebration of the scientific, technological, institutional, and cultural breakthroughs that helped shape the United States into one of the most important scientific nations in human history.
In part one, we traced American science from Benjamin Franklin and the founding documents through Sputnik, NASA, DARPA, Bell Labs, the transistor, information theory, nuclear physics, molecular biology, and the birth of the modern American science state. In part two, we pick up after Sputnik and follow the explosion of American science from 1958 to today.
This episode covers the visual system, solar wind, perceptrons, impact cratering, pacemakers, neurotransmitter reuptake, cochlear implants, the genetic code, quarks, Bell’s theorem, density functional theory, the fast Fourier transform, immigration policy, electroweak unification, ARPANET, Apollo 11, dark matter, MRI, GPS, Unix, gravitational waves, ozone depletion, lithium batteries, Voyager, RNA splicing, recombinant insulin, quantum computing, the Space Shuttle, prions, PCR, cellular networks, telomeres, laser cooling, backpropagation, the Hubble Deep Field, Deep Blue, Sagittarius A*, cosmic acceleration, the Human Genome Project, CRISPR, mRNA vaccines, reusable rockets, LIGO, transformer models, black hole imaging, quantum supremacy, and the James Webb Space Telescope.
The larger story is not just that America produced extraordinary discoveries. It is that those discoveries came from an ecosystem: universities, national labs, government agencies, industrial research labs, immigrant scientists, public investment, basic research, private enterprise, and a culture that repeatedly turned curiosity-driven science into civilization-changing technology.
The episode closes by connecting that 250-year legacy to the current debate over federal science funding and the future of American scientific leadership.
Explore the interactive timeline
ffppod.com/America250
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Om 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.
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