FFP EP. 12 | From Princeton to the Nobel Prizes — How FFP Started + 2025 Nobel Recap
After a packed week of Nobel Prize coverage, Lester and Krishna look back on how From First Principles began and why they built it as an “ESPN for Science.” They revisit 2025’s Medicine, Physics and Chemistry winners and discuss why fundamental research and immigration policy are core to America’s scientific edge.Quick note: this week’s episode is in vertical format because of a technical hiccup during recording — back to widescreen next week!SummaryOrigin Story — Two Princeton friends from different continents unite around a shared love of science and storytelling.The Mission — Creating an “ESPN for Science” that celebrates research and the people behind it.Nobel Follow-ups — Medicine (Tregs and non-immune roles), Physics (macroscopic quantum tunneling and quantum supremacy), Chemistry (MOFs and industrial scaling).Funding + Immigration — Why public research grants and curating global talent are vital to scientific leadership.Show NotesNobel Prize Press Release (2025 Medicine)Nobel Prize Press Release (2025 Physics)Nobel Prize Press Release (2025 Chemistry)Nature Genetics (2001) — FOXP3 Mutation Causes DysregulationNature (1999) — MOF-5 Discovery (Omar Yaghi et al.)Google Quantum AI Lab — Quantum Supremacy (Nature, 2019)
--------
1:12:17
--------
1:12:17
FFP EP. 11 | From Cells to Circuits to Crystals — 2025 Nobel Prizes Unpacked
Hosted by Lester Nare and Krishna Choudhary, this one-episode special brings all three 2025 Nobel Prizes in the sciences into a single listen: Medicine (immune tolerance and FOXP3), Physics (macroscopic quantum tunneling in superconducting circuits), and Chemistry (metal–organic frameworks and “new rooms for chemistry”).SummaryMedicine: Regulatory T cells and the FOXP3 gene that prevent autoimmune disease.Physics: Macroscopic quantum tunneling and energy quantization in electrical circuits — the bridge to today’s qubits.Chemistry: Metal–Organic Frameworks (MOFs) — modular porous crystals enabling CO₂ capture, water harvesting, and hydrogen storage.Show Notes Nobel Prize Press Release (2025 Medicine) Nature Genetics (2001) — FOXP3 mutation and IPEX link Nature Genetics (2001) — FOXP3 Mutation Causes Dysregulation Nature Genetics (2001) — FOXP3 Gene Cause IPEX Syndrome Science (2003) — FOXP3 function in regulatory T cells German Journal of Immunology (1995) — Sakaguchi’s first Treg paper Nobel Prize Press Release (2025 Physics) Physical Review Letters (1980s) — Macroscopic Quantum Tunneling Experiments (UC Berkeley) BCS Theory (1972 Nobel) — Bardeen, Cooper & Schrieffer, University of Illinois Josephson Effect (1973 Nobel) — Brian D. Josephson Google Quantum AI Lab — Quantum Supremacy Paper (Nature, 2019) Nobel Prize Press Release (2025 Chemistry) Nature (1999) — MOF-5 Discovery (Omar Yaghi et al.) Science (2003) — Reticular Chemistry Foundations Journal of the American Chemical Society (1989, 1990) — Richard Robson’s Early Frameworks Lawrence Berkeley National Laboratory — ChatMOF and AI-Assisted Materials Discovery
Hosted by Lester Nare and Krishna Choudhary, this two-story, 2.5-hour special sets the table for Nobel Prize Week with deep dives into two recent Nobel-winning domains—gene editing (CRISPR) and gravitational waves (LIGO)—and how AI is accelerating both. We trace CRISPR from bacterial immunity to Stanford’s new “CRISPR-GPT” lab co-pilot, then pivot to how machine learning upgrades are pushing LIGO past its noise limits to capture new classes of gravitational waves.Summary• CRISPR, from bacterial immune memory to RNA-programmable genome editing• The 2012 Science breakthrough: guide RNAs unlock programmable editing• The patent saga and the 2020 Nobel Prize in Chemistry• Stanford’s CRISPR-GPT: an AI “co-pilot” trained on expert lab threads and papers• Experiment planning, guide design, and safety guardrails for CRISPR-GPT• Biosecurity and ethical guardrails around AI in biology• LIGO’s foundations: Einstein’s equations, binary pulsars, and interferometer engineering• The “noise budget”: seismic, environmental, and quantum limits• AI-driven denoising and template generation: unlocking earlier inspirals and tougher detections• Funding, leadership, and the global policy race to keep LIGO competitive• Big picture: AI as an amplifier of discovery in both medicine and physicsShow NotesStanford Medicine — AI + CRISPR BreakthroughNature Biomedical Engineering — AI-CRISPR Original PaperCaltech — AI Helps LIGOScience — LIGO Machine Learning Paper
--------
2:36:24
--------
2:36:24
FFP Story — Scientists Build a Time Crystal You Can Actually See (EP. 9)
Hosted by Lester Nare and Krishna Choudhary, this story explains the first-ever time crystal that humans can actually see, built from liquid crystals at the University of Colorado Boulder. Unlike earlier quantum time crystals that required lasers and extreme cold, this room-temperature, macroscopic version uses simple light to generate a self-sustaining, periodic motion.Summary• UC Boulder team builds the first visible time crystal using liquid crystals• Time crystals explained: symmetry breaking in time vs. space• Historical context: Frank Wilczek’s 2012 idea and the “no-go theorem”• Classical vs. quantum systems: why this matters for scalability• How solitons in liquid crystals act like quasi-particles• Potential applications: secure currency, dynamic QR codes, photonic devices• Why room temperature + macroscopic scale make this breakthrough differentShow Notes• Nature Materials: Visible Time Crystal Study
--------
25:10
--------
25:10
FFP Story — The $294K AI Model That Shocked the World (EP. 9)
Hosted by Lester Nare and Krishna Choudhary, this story unpacks China’s DeepSeek R1 — a large language model trained for just $294,000 using restricted H800 GPUs. Published in Nature, DeepSeek shocked the AI community by matching frontier-level performance at a fraction of the cost, and by releasing peer-reviewed papers and open weights. We explore how reinforcement learning without human labels, mixture-of-experts efficiency, and geopolitical strategy made this possible — and why it matters for the global AI race.Summary• DeepSeek trained a frontier-scale LLM for only $294K• First peer-reviewed AI model at this scale (published in Nature)• U.S.–China AI rivalry: Chips Act, export controls, and geopolitics• How hardware choke points forced algorithmic innovation• DeepSeek’s open-weights release vs. OpenAI’s closed approach• Training strategies: pure reinforcement learning + mixture-of-experts• Global ripple effects on Meta, OpenAI, and future AI policyShow Notes• Reuters: China’s DeepSeek AI paper• Nature: DeepSeek peer-reviewed paper (1)• Nature: DeepSeek peer-reviewed paper (2)
Netherlands