This morning we are releasing the largest proof in the history of mathematics: A formalization of the Classification of Finite Simple Groups (CFSG)! Over 43 million lines of Lean, 715 papers and books, and 100 substantive fixes to the literature, this is truly an enormous theorem. Well done team!

This is Genie 4, our most realistic and interactive world model yet. 🌐 Explore dynamic environments in real time to see how the scene responds, sounds, and how the people in it move, react, and speak.

Mathematicians: How do you dare releasing such terrible AI-written proofs before humans checked them! Also mathematicians: Release the proofs immediately!

Sweden opts for coronavirus protein vaccine instead of mRNA From the 2027/2028 season onwards, Sweden will use only a protein-based coronavirus vaccine for its national vaccination campaign. It is the first country in the world to say goodbye to the mRNA vaccines. Difference in technology Nuvaxovid is a classic protein vaccine. It contains a ready-made piece of the virus (the spike protein), produced using recombinant technology (a molecular method in which DNA from different organisms is combined in the laboratory and placed into a host cell (such as a bacterium or yeast) to allow it to multiply or produce proteins) and provided with an adjuvant (an excipient that stimulates and strengthens the body's immune response to the antigen, so that the vaccine works better). The body is presented with this protein directly to build an immune response. This differs from mRNA vaccines (such as Comirnaty from Pfizer/BioNTech), where the body's cells must produce the spike protein themselves after receiving the mRNA instruction. This process carries the risk of autoimmune reactions, especially because these products do not remain at the injection site but can spread throughout the body. Furthermore, the quantity and duration of spike protein production are not defined in the mRNA technique. In addition, the lipid coating of the mRNA vaccines is very reactive. All in all, this leads to a disproportionate number of side effects, some very serious and resulting in death (1-3). Sweden chose its own path during the coronavirus years by not enforcing lockdowns or school closures. Although there was much criticism of this at the time, the Swedish approach was later appreciated ( De Morgen, 25 December 2023 ). With the decision to phase out coronavirus mRNA vaccines, Sweden appears set to play a pioneering role once again. The Doctors' Collective, together with European partners, has been advocating for the cessation of mRNA vaccinations for quite some time. Sources: Sanofi press release (April 21, 2026), LäkemedelsVärlden report and Läkemedelsmarknaden report regarding the tender. References Cappelletti-Montano B, Demuru G, Laconi E and Musio M (2023) A comparative analysis on serious adverse events reported for COVID-19 vaccines in adolescents and young adults. Front. Public Health 11:1145645. doi: 10.3389/fpubh.2023.1145645 Szebeni, J. Expanded Spectrum and Increased Incidence of Adverse Events Linked to COVID-19 Genetic Vaccines: New Concepts on Prophylactic Immuno-Gene Therapy, Iatrogenic Orphan Disease, and Platform-Inherent Challenges. Pharmaceutics 2025, 17, 450. Fraiman J, Erviti J, Jones M, Greenland S, Whelan P, Kaplan RM, Doshi P. Serious adverse events of special interest following mRNA COVID-19 vaccination in randomized trials in adults. Vaccine. 2022 Sep 22;40(40):5798-5805. doi: 10.1016/j.vaccine.2022.08.036. Epub 2022 Aug 31. PMID: 36055877; PMCID: PMC9428332. artsencollectief.nl/zweden-k…

New Anthropic research: How AI agents shape experts' judgment calls When experts delegate work to an agent, do they still make the key decisions? We tested this in a randomized trial with 50 professional data analysts.

We interrupt our usual programming to inform you that I was never hired by Facebook to do a hit job on Jonathan Haidt. statmodeling.stat.columbia.e…

Meta had an internal PR plan to try and discredit Jon Haidt because he was a critic of social media. Meta was going to recruit academics, like Andrew Gelman, to write take down pieces. They were trying to turn academics against one another through a "whisper strategy". This is a very serious problem for open academic debate. If academics who share negative evidence about a platform are targeted by campaigns to smear our credibility, we are in deep, deep trouble. This creates a very serious conflict of interest for anyone who is paid to do this. law360.com/articles/2542517/…

Turns out seeing sounds is really fun

Statement of Yang-Mills Working Group, a scientific collaboration to interpret AI result related to the existence of quantum chromodynamics & completions of the Standard Model, including a subproblem proving the existence of the Quantum Yang-Mills theory. buff.ly/BwV89Tk

If you start reading this, read it to the end.

Driving a truck requires physical work. Physical changes -- products, manufacture, and the inevitable regulation -- take time. Pure intelligence jobs are easier to replace by software, hence coding and maths are among the first to have AI as serious competitors. Next up will be a lot of academic disciplines, from theoretical physics to economics. We can already see this beginning now. There must be a lot of scientific discoveries hidden in the scientific literature, conclusions that have not been drawn simply because no human has been able to read everything that has been published. AI is about to pick those fruits in the coming year ringing in what might be akin a second scientific revolution. This is going to keep the stock market excited for some time. I also expect, unfortunately, that the models which are most capable at scientific discovery will be increasingly restricted to members of institutions that have made deals with the leading companies. (Which isn't going to end well for the EU.) As usual, you shouldn't believe a word I say because as everyone will tell you, I don't know anything about nothing. But at least I have consistently said the same thing for a few years now. nitter.siddz.com/Icebergy/status/211488…

In fact, it's time to carefully revisit what OpenAI predicted on job market impact in early 2023. Mathematicians were #1 on their list. arxiv.org/abs/2303.10130

Today Physical Superintelligence PBC is announcing solutions to five long-standing problems in quantum information theory. psi.inc/research/oqp-batch-2… Thread 👇

He has a point. To me the OpenAI announcement seems to be about mathematical physics. To most people "mathematical physics" and "theoretical physics" sound interchangeable but they are different disciplines. Theoretical physics is solidly part of physics. In this area, researchers develop either theories that explain observations already made, or they improve existing theories to make predictions for observations. (At least that's what they should be doing.) Mathematical physics on the other hand is usually part of the department of mathematics, not physics. It is concerned, loosely speaking, with cleaning up the mess that physicists have made of their theories of nature. Or in some cases studying the properties of theories that have nothing to do with nature. (Like physics in lower or higher dimensions, fields that don't exist in nature, etc.) People in these two disciplines work closely together of course. But mathematical physics is more maths than physics. I would not consider it part of the natural sciences as it is not itself concerned with describing nature. I don't know exactly what the OpenAI discovery is about, but it sounds like it is more in the area of mathematical physics rather than theoretical physics. I am not saying this makes it irrelevant, but as Andreas points out, it is of limited interest for applications. nitter.siddz.com/karch_andreas/status/2…

Many of you don't understand how serious this is, so let me break it down. In computer science there is a famous kind of puzzle called 3-SAT. You are given a long list of yes-or-no switches and a set of rules about how they must be arranged, and you have to find a combination that satisfies every rule. The obvious way to solve it is to try every combination, but each new switch doubles the number of possibilities, so a puzzle with a few hundred switches would take longer than the age of the universe to brute force. For decades, the smartest people in the field found clever tricks that made this a little faster, but every trick still hit the same wall: the time required kept exploding as the puzzle grew. About 25 years ago, two computer scientists, Russell Impagliazzo and Ramamohan Paturi, working with Francis Zane, turned that wall into a formal idea. They proposed the Exponential Time Hypothesis, which says this explosion is not a failure of human cleverness but a law of nature. No algorithm, however brilliant, will ever solve 3-SAT without the time blowing up exponentially. Nobody could prove it, but almost everyone believed it, and it became one of the foundations of modern computer science. Researchers used it as a measuring stick. If you could show that solving some other problem quickly would also crack 3-SAT quickly, you had shown that problem was hopelessly hard too. Hundreds of papers, across scheduling, graphs, logic and much more, rest on this one assumption. Now an internal AI model at OpenAI claims to have broken it. It says it found an algorithm that solves these puzzles meaningfully faster than the hypothesis allows, and it has checked the proof in a computer verification system called Lean. And here is the remarkable part: the very people who proposed the hypothesis, Impagliazzo and Paturi, along with MIT's Ryan Williams, are now leading the public review of whether a machine has disproved their own idea. So what happens next? If the disproof holds, a large part of theoretical computer science has to be revisited. Every result that said "this problem cannot be solved faster, assuming ETH" loses its foundation, and researchers will have to work out which of those walls were real and which were simply where we stopped looking. It does not mean everything becomes easy. The new algorithm is still slow in absolute terms and this is not the famous P versus NP problem being solved. But it means our map of what is possible was wrong in a place we were very confident about, and it was an AI that redrew it. If the disproof fails, the hypothesis survives and the field breathes out, but we will still have watched an AI produce serious, checkable work on one of the deepest questions in the discipline, closely enough that the founders of the idea had to take it seriously. Either way, something has shifted.

Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory). AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…

Plastic pollution is a problem... but the problem is not what we thought it was piped.video/watch?v=JJste2I_…

Scientists are rethinking free will. I have a brief summary.