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“I have made a ceaseless effort not to ridicule, not to bewail, not to scorn human actions, but to understand them.”
(Baruch Spinoza)
Raffaele Mauro retweeted
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…
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…
Raffaele Mauro retweeted
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 …
Raffaele Mauro retweeted
Mathematics of the Future
Pavel Etingof and Slava Gerovitch
math.mit.edu/~etingof/future…
Raffaele Mauro retweeted
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.
Raffaele Mauro retweeted
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.
Raffaele Mauro retweeted
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.
Raffaele Mauro retweeted
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
Raffaele Mauro retweeted
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.
We are announcing three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.
openai.com/index/building-sc…
Raffaele Mauro retweeted
We are announcing three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.
openai.com/index/building-sc…
Raffaele Mauro retweeted
# Black October
For anyone who knows me even somewhat well, it's clear that I am a 99th percentile tech optimist. However, the vibes have shifted for me quite a bit in the last 18 hours, and I feel a moral imperative to share what I'm thinking and feeling with my circles so that everyone can understand, and hopefully take seriously, what's happening right now. I think October 2026 will have many chapters written about it in the history books.
You know those scenes in financial movies like Margin Call where someone realizes that they're all fucked, and no one else sees it yet? And that person feels like they're crazy, and then suddenly everyone is pulling an all-nighter in a boardroom and freaking out? Yeah, that's kind of how this is feeling right now in the SF/Bay Area/AI circles.
We're 48 hours into what is being called Black October. In the last 2 days there have been several dozen cyber attacks which, in isolation, would each have been the worst to happen in an entire calendar year. Every sector from government to education to big tech and banks is being massively affected, and people are starting to freak out.
In a nutshell, what's happened is that frontier AI models have gotten to a point where they are as advanced as the most sophisticated programmers, with one critical difference: they can work 24/7, and you can spin up 10,000 of them with a single command and they'll work together tirelessly until they accomplish their task. The most advanced models today are from companies like Anthropic and OpenAI, whose current best technology is so good that they haven't been able to roll it out to everyone yet because of the national security risks it poses.
Meanwhile, the best open source models (where anyone can just download the model weights and do whatever they want with them, uncensored) are slightly behind the frontier but still 90-95% as capable. These models, developed primarily in China, are being used by black hat hackers to wreak havoc on the Western capitalist structure. Presumably, this has been part of China's plan the entire time, and we're seeing its implications fall out in real time.
In red-pilled AI circles, we've been sharing and reading papers called things like "Situational Awareness" and "AI 2027" for the last year or so, which at the time felt a bit like near-term speculative fiction. They laid out the case for why Artificial General Intelligence (AI smarter than any human at any knowledge task) and Recursive Self-Improvement (models that are able to use themselves to get better) weren't half-baked future ideas anymore, but instead an inevitable outcome of the linear progress that's happening.
These papers would then talk about things like "takeoff scenarios," trying to envision how that moment would come to be and what it would be like when it happened. It would either be a "slow takeoff" that would play out over the course of months and quarters, happening subtly and only obvious to a few. Or, it would be a "fast takeoff" where it would pretty much happen instantly, like a bit flipping from 0 to 1.
From everything that I can see and am feeling, we are currently experiencing the fast takeoff scenario. Beyond the crazy security vulnerabilities that have come out recently, there have also been massive breakthroughs in life sciences, fundamental computer science, materials science, and pure mathematics that have all landed in the same time frame. While I still firmly believe that AI will be a net positive for humanity, it's more clear to me than ever that the societal and individual risk is very real, and is playing out NOW.
For as much conviction as I have that this is happening, the thing that's caused me to lose sleep is that I don't really know what to do about it, or more importantly, what to tell you, reader, to do about it. So, the best I can do is make a few suggestions that have always been a good idea but are more timely now than ever:
Set up 2-factor authentication for everything. I use Duo.
Use a password manager across your devices. I use 1Password.
Get an identity protection app set up. I use Alta.
Move your IoT devices to their own network. Claude helped me do this.
And last, but certainly not least, if you've been avoiding leaning into AI, see this as a catalyst to wake up and start using it. Don't just use the chat mode version of ChatGPT/Claude; click that Code/Work button and see how easily you can have AI write code to help you with your job. One of the biggest vulnerabilities was in a massively popular programming language called PHP, and the prompt that set it off was literally, "Find vulnerabilities in php."
This is an unprecedented time for humanity, but as we've done with many things before, we will prevail so long as we are kind, loving, and open-minded to the world.
Much love.
What is AI really capable of in bio?
To separate hype from reality, we spent 3 months working firsthand with @AnthropicAI's internal research model to see if it could create an experimental scorpion antivenom.
Introducing Citrini Therapeutics.
citriniresearch.com/p/citrin…
Raffaele Mauro retweeted
Some of humanity’s oldest myths contain the same warning: not to look back. Lot’s wife looks back at the world she was leaving and turns into a pillar of salt. Orpheus looks back for Eurydice before they have completely escaped the underworld and loses her. In Japanese mythology Izanagi looks back at Izanami in the land of the dead and discovers that the woman he remembers no longer exists. Different cultures, different stories, but all have the same message….that there are thresholds in life that can only be crossed by accepting that what was behind you is gone.
This doesn’t mean we have to forget the past. But it does mean refusing to live there. The past can teach you, shape you, and become material for the Great Work, but it cannot be inhabited again. We become frozen when we keep trying to resurrect an old relationship, an old life, an old identity, or an old version of ourselves. Transformation requires something to die so that something else can be born. Sometimes the final test of an initiation is simply this: can you keep walking without turning around?
Raffaele Mauro retweeted
New from our STEM Fellows Program: Designing more efficient quantum circuits with Claude.
Given plain-language instructions, Claude Mythos 5 designed quantum circuits that improve on the best published ones, sometimes by an order of magnitude or more.
More efficient circuits reduce the resources needed by quantum algorithms, which could bring quantum computing applications in chemistry and materials science within reach sooner.
Read more: anthropic.com/research/desig…
Raffaele Mauro retweeted
Claude figured out how the curve parameters for ECDSA were chosen
ECDSA is an algorithm for creating and verifying digital signatures using elliptic curves. You might know its older more well known sibling DSA.
In the late 1990s, the NSA supplied the seeds behind these curves used for ECDSA with no explanation of where they came from
turns out they're just output from a basic random number generator, seeded with a timestamp
anthropic.com/research/ecdsa…
Raffaele Mauro retweeted
What can large-scale AI models bring to the growing complexity of particle physics?
@CERN and Mistral join forces to explore this question.
The ambition: a single Large Physics Model, trained on billions of simulated collisions.
Raffaele Mauro retweeted
The singularity has already begun for math:
Scott Aaronson is one of the world's leading quantum computing researchers and spent two years at OpenAI working on AI safety.
We talked about why he thinks the singularity has already begun for math, who gets credit when AI writes the proof, and whether intelligence will still matter once machines do the thinking.
In this episode:
• Why the singularity has already begun for math
• Who gets credit when AI writes the proof
• What a proof that P = NP would be worth
• Why he turned down getting rich to keep blogging
• Whether intelligence will still matter
Where to watch:
• YouTube - youtube.com/watch?v=ORlscppG…
• Spotify - open.spotify.com/episode/0qn…
• Apple Podcasts - podcasts.apple.com/us/podcas…
• Transcript - developing.dev/p/e070-scott-…
Thank you to the sponsor of this episode for supporting my work:
• WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at workos.com/
Chapters:
00:00 Intro
00:34 Why he updated so hard on AI
01:14 The people still denying AI progress
03:53 The singularity has already begun for math
08:30 Will human-driven math research survive
13:12 Who gets credit for AI-written papers
15:55 OpenAI's $15M Navier-Stokes proof
19:20 What if AI proved P = NP
23:07 Why AI is so good at finding counterexamples
26:13 The goalposts keep moving
28:52 Why AI disclosure matters in research
32:59 The fake Monet experiment
35:23 Why he blogs instead of getting rich
39:45 Are AI labs racing too fast
42:01 Will intelligence still matter
47:12 Book recommendations
52:27 Advice for students today
57:23 Reacting live to a new AI result
59:58 Outro
Raffaele Mauro retweeted
Another big AI math drop. This time from Google DeepMind
Google DeepMind’s AlphaProof Nexus AI solved mathematical questions that had resisted progress for decades.
The system autonomously resolved 9 of 353 open Erdős problems, including 2 that had remained unsolved for 56 years, and also proved 44👀 of 492 open conjectures from the Online Encyclopedia of Integer Sequences.
It also resolved an open question in algebraic geometry and improved a known bound in min-max optimization.
The key: pairing an LLM’s ability to generate proofs with Lean’s formal verification. The AI proposes a proof, the checker tests every logical step, and failed attempts produce feedback for another try. Proofs must pass the checker to be accepted.
Researchers also tested a simpler approach. Repeatedly generating candidate proofs with an LLM and checking them in Lean, alongside their more sophisticated search framework.




























