Raffaele Mauro (@Rafr) header
Raffaele Mauro (@Rafr) profile picture

Partner at Primo Capital - Deep Tech VC | Kauffman Fellow | Karman Fellow | EYL40 | Ph.D. | Previously Endeavor & Harvard

Milano, Italy
Joined March 2009
Photo by Raffaele Mauro (@Rafr)Photo by Raffaele Mauro (@Rafr)Photo by Raffaele Mauro (@Rafr)Photo by Raffaele Mauro (@Rafr)Photo by Raffaele Mauro (@Rafr)Photo by Raffaele Mauro (@Rafr)Photo by Raffaele Mauro (@Rafr)Photo by Raffaele Mauro (@Rafr)Photo by Raffaele Mauro (@Rafr)Photo by Raffaele Mauro (@Rafr)
“I have made a ceaseless effort not to ridicule, not to bewail, not to scorn human actions, but to understand them.” (Baruch Spinoza)
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Astral Codex Ten meetup in Milan this Tuesday, November 10, at 7:00 PM at Iurio! Looking forward to great conversations, fresh ideas, and curious minds. DM me for details
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Today Physical Superintelligence PBC is announcing a proof of the Aaronson-Ambainis conjecture, one of the central open problems in quantum complexity, with major implications for quantum computing speedup. psi.inc/research/aaronson-am… Thread 👇
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Raffaele Mauro retweeted
Big math breakthrough today: Researchers (with heavy AI help) just showed you can spot the whole numbers among the fractions using one giant polynomial equation. The polynomial has 292,890,231,905 variables! Info: Elliot Glazer, github.com/elliotglazer/diop…
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🔜 🧠 “We are about to enter the era of interventional psychiatry, transforming the field of psychiatry.” — Tom Insel, former NIMH Director, at a recent psychedelic science conference. We have invested in many of these new modalities: transcranial focused ultrasound (Sanmai), minimally invasive deep brain stimulation and vagus nerve stimulation (Neurobionics), brain-computer-interfaces (Neuralink), auditory dream engineering (Dust), psychedelic-assisted therapy (atai/Lilly), and real-world-data collection for all (Osmind). Insel also co-authored a Nature paper with Osmind defining the field: nature.com/articles/s44220-0… + summary: osmind.org/interventional-ps… Interventional psychiatry companies: •  tFUS: Sanm.ai/technology • Endovascular DBS: Neurobionics.io •  BCI: Neuralink.com •  Dream engineering: DUST.systems •  Psychedelics: ataibeckley.com P.S. Underfunded: “From 2002-2013, the NIMH did not receive any funding applications for psychedelics. It was all funded and legitimized by philanthropy.” P.S.S. Needed: “The World Health Organization (WHO) predicts that without significant changes, mental illness will cost the world economy $16t by 2030, making it the largest disease burden globally." — UBS: flic.kr/p/2jcRcoS We need significant changes.
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Raffaele Mauro retweeted
Fascinating finding! Astra can interpret the function of smaller models just by looking at the weights. And it can fix flaws in smaller models. Positive update both for mechanistic interpretability / AI monitoring, and for RSI. Caveat: The models Astra improved were 1,000 - 58 milllion times smaller than itself.
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math. It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training. We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵 Blog: rikiyat.github.io/blog/weigh…
Readers added context they thought people might want to know
LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math. rikiyat.github.io/blog/weight-sp… github.com/RikiyaT/lm_und… huggingface.co/Qwen/Qwen3.5-0… huggingface.co/RikiyaT/Qwen3.…
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Raffaele Mauro retweeted
Scientists have created one of the most detailed 3D reconstructions of a human cell (eukaryotic cell) ever produced. This groundbreaking model, often termed a "Cellular Landscape Cross-Section Through a Eukaryotic Cell," combines data from X-ray tomography, nuclear magnetic resonance (NMR), and cryo-electron microscopy to map molecular structures in extreme detail.
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I joined @GoogleDeepMind to develop a research program on the economics of AGI. Today, together with Andrew Koh (@andrewjkoh) and Shane Legg (@ShaneLegg), we are incredibly excited to release The Economics of Intelligence, the first in a series of projects from our group on how AGI will change the economy. How do capability improvements transform the economy, and when? In this project, we define thresholds of economic capabilities, e.g., minimal AGI, based on how they transform the economy. We then track how the economy–market structure, employment, and wages–changes during the transition across capability regimes. We have seen exponential increases in what AI agents can do but the broader economy seems almost remarkably unchanged. Part of the reason is that the solo AI agent is the wrong economic object; economic transformation is an equilibrium outcome where organizations compete. Looking at how intelligence functions within organizations, transformation will depend on when two key capability thresholds are crossed: competence (gains on individual skills, e.g., coding, math) and coordination (gains on ability of agents to cooperate and work together). We show that what economic transformation looks like depends on whether AI becomes supercompetent, supercooperative, or both—the regime of artificial superintelligence (ASI). Tracking this transition shows why the real visible transformation may come from improvements in coordination—a capability most benchmarks don’t yet track. Past a certain threshold, AI capabilities can break the Coasian ceiling on firm size and lead to an economy that looks drastically different than the one we see today. Two main takeaways: 1. To understand the path of transformation, we should be tracking agentic coordination more closely. 2. The impact of AI will likely show up in wages before market structure or employment. We are really excited about this paper. Excited to hear people’s thoughts. Link: institute.deepmind.com/essay…
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Why I'm almost certain that AI is about to usher in a golden age of rapid scientific discovery: noahpinion.blog/p/a-golden-a…
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Da oggi si può firmare la proposta di legge “PMA per tutte”: accesso alla PMA anche per donne single e coppie di donne. Bastano pochi minuti con SPID o CIE. Firma anche tu: firmereferendum.giustizia.it…
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Bacteria should have shared the 2025 chemistry Nobel Prize for metal-organic frameworks! It’s been known for a while that there are “cable bacteria” that extrude conductive filaments up to 1 cm long, which penetrate sediments on the sea floor and allow them to draw electrons …
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Mathematics of the Future Pavel Etingof and Slava Gerovitch math.mit.edu/~etingof/future…
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Gameto my sixth unicorn was just sold to Ferring for $1.38bn here is the story. In 2020 I endowed a fellowship at Harvard in my father's name, Carlos M. Varsavsky, in the lab of George Church, one of the world's leading geneticists. Its goal: to make human eggs in the lab. Gameto grew out of it. My father was an astrophysicist and built the Instituto Argentino de Radioastronomía, Argentina's radio astronomy institute. He was a great teacher, at the university and at home. In a time without artificial intelligence, he was the artificial intelligence for me: he knew about everything. He died young. The fellowship carries his name. The fellowship paid for the PhD of Christian Kramme, a Californian geneticist who worked out how to make in the lab the cells that surround an egg in the ovary and help it mature. He is now Gameto's chief scientific officer. Ferring Pharmaceuticals, the Swiss fertility drug maker, is acquiring Gameto for up to $1.3825 billion. I am a co-founder, and this is the story of a company that set out to do one thing and was bought for another. I came to fertility in 2016 with Prelude Fertility, a network of US clinics I built, now part of Inception, the largest fertility network in North America. Inside those clinics I learned that IVF works, but it is brutal. For two weeks a woman injects herself with hormones so her ovaries release many eggs at once: around 28 shots, ultrasounds, blood tests, bloating and mood swings. Many women go through it once and never again. Every one who stops is a pregnancy that never happens. One question obsessed me: what if the treatment took three days instead of two weeks. I brought in Dina Radenkovic Turner as co-founder and CEO. She was 26, a physician trained at University College London and one of the brightest people I have ever worked with. Many questioned the bet on someone that young. Time proved us right. I had a moonshot and a fellowship. Dina turned them into a company. She looked at Christian's cells and saw a product: if the egg was out of reach, we would do the ovary's work in the lab. That became Fertilo. With Fertilo a woman takes hormones for two or three days, about 80% fewer shots. Her eggs are collected immature and spend a day in the lab with those cells, which do the ovary's job. Then they are fertilized as in any IVF cycle. The cells never enter her body. On December 16, 2024, the first baby conceived this way was born in Lima. By August there were five babies and more than twenty pregnancies. Three gentle cycles beat one brutal cycle nobody wants to repeat. With Dina at the helm, Gameto raised about $127 million in total from Overwater Ventures, Insight Partners, RA Capital, Two Sigma Ventures, BOLD Capital Partners, Future Ventures, Olivia Walton's Ingeborg Investments, Arcadia Investment Partners, PAGS Group, Pontiva Healthcare Partners and Portfolia, and from Anne Wojcicki of 23andMe, Bob Nelsen of ARCH Venture Partners, Stacey Bendet Eisner of Alice + Olivia and Chelsea Hirschhorn of Frida. Gameto is the sixth company I have built to pass a billion dollars, after Viatel, Yacom, Jazztel, Eolia Renovables, sold in 2017, and Inception/Prelude Fertility, Telecoms, internet, clean energy, clinics, biotech: nothing in common, and in every one the team mattered more than me.
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The largest math proof in human history is now computer-verified. Today, Axiom announces a complete Lean auto-formalization of the Classification of Finite Simple Groups, the "periodic table of symmetry." About 15,000 pages, built by over 100 mathematicians across generations.
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MIND-BENDING FACT: OpenAI announced Monday that its AI proved the Exponential Time Hypothesis (ETH) is false — a foundational pillar of theoretical computer science since the 1970s. The ETH holds that NP-complete problems cannot be solved faster than exponential time; cryptographic security, algorithm complexity bounds, and the theoretical ceiling on AI planning have all been calibrated against it being true. One model, running in collaboration with academic partners, disproved it. Simultaneously, OpenAI disclosed it finalized a proof of Yang-Mills existence on October 16 — one of the seven Millennium Prize Problems, each carrying a $1 million Clay Mathematics Institute award. Navier-Stokes was solved September 8. Two Millennium Prize Problems in 49 days. Five remain.
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OpenAI has announced to three new discoveries in mathematics, computer science, and physics: - Local smoothing and the Kakeya conjecture - The Exponential Time Hypothesis is false - Existence of quantum chromodynamics and completions of the Standard Model
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Major breakthrough: OpenAI says its AI has cracked decades-old problems across mathematics, computer science, and physics, with key proofs formally verified in Lean. These are original discoveries that could reshape entire fields, from the limits of computation to the mathematical foundations of particle physics. Independent experts are now examining the work; if it holds up, this is a major milestone for AI making new science.
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