science – Teknotum

Internal OpenAI model solves hundreds of open mathematical problems

There were 377 total problems solved, and it could take a long time for the community to process. (Picture: generated)

In what may be a watershed moment, at least in terms of quantity, the same internal model that solved the Navier-Stokes millennium problem has solved a torrent of open problems — and posted them all on GitHub.

— We are entering a new era of discovery now, Sam Altman says on X, followed by OpenAI president Greg Brockman’s comment that we are moving — towards acceleration of scientific discovery and improving quality of life for everyone.

The problems span deep and wide across the field, with solutions on anything from number theory to computer science and mathematical physics to complex geometry. There are so many solutions that OpenAI says their listings themselves are not rankings, in a document that spans 41 pages with as many as ten problems per page.

In OpenAI’s announcement, they say they have been consulting with Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study «to develop best practices» and to «inform how we release these results,» after getting backlash from the mathematical community on earlier problem releases. The group says:

— This release is the beginning, not the completion, of the process of human understanding and the incorporation of the work into mathematical knowledge.

«Many» of the proofs are formalized in Lean, which means they are computer-verifiable, with more to come «as we obtain them,» OpenAI says. Along with the proofs themselves, there are ten summaries of model reasoning and estimates on how much compute was spent to solve each problem. OpenAI says the average time spent was three hours of ChatGPT Pro-level reasoning.

— We want to directly empower scientists with state-of-the-art capabilities and are working to responsibly release the model that produced these results, OpenAI writes.

Read more: OpenAI’s presentation, GitHub repository, PDF overview, and AGMAI’s statement. NYT and Interesting Engineering. Discussion on Hacker News and r/Singularity.

Anthropic’s Claude-powered biology lab makes its first scientific discovery

The repeating DNA in bacteriophages could possibly reveal a gene-editing method. (Picture: generated)

Anthropic set up its wet science lab in the spring of 2026, and it has already made its first important discovery.

Claude itself has autonomously discovered an enzyme hidden in the DNA of bacteriophages that sits beside a «long array of repeating DNA,» that could work in a similar way to CRISPR — todays most common DNA-editing tool, and a discovery that won the Nobel Prize.

Claude found the enzyme almost entirely on its own, searching through a massive database of DNA sequences for interesting candidates from a human prompt. It took 21 hours, 950 agents and 210 million tokens until an agent made the discovery of repeating DNA sequences. It was then analyzed and tested by scientists in the lab.

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Anthropic has already set up a wet lab to test biology and Claude automation

The wet lab is not intended to compete with drug discoverers, but to test the limits of lab automation. (Picture: generated)

CEO Dario Amodei said the mission is to cure cancer and most human diseases in ~5-10 years, but AI alone can’t do all the experiments «in silico,» Reuters reports.

They are saying that Anthropic already has a biology lab in San Francisco, and is working on pushing automation with Claude as far as possible.

They also hope to do pre-clinical work on diseases thought «undruggable,» meaning they are too expensive or complex to cure.

— The mission of the company is to develop powerful AI in such a way that [it] benefits the world, Anthropic’s head of life sciences, Eric Kauderer-Abrams tells Reuters. — By far, we see the biggest opportunity for that in the life sciences, and that is motivating everything that we’re doing.

That said, Anthropic also works with external lab partners for what seems a lot of their «normal» biology testing.

Read more: Reuters, TechCrunch, Engadget. Discussion on r/technology and Hacker News.

OpenAI says «more capable» internal model solves Millennium problem

OpenAI is mum on what their internal agent is otherwise capable of. (Picture: OpenAI)

It took an internal model «significantly more capable» than Astra a matter of 88 hours with 10,000 concurrent agents to propose a solution to the Navier Stokes problem, that regulates fluid motion dynamics and has been unsolved for over ninety years.

At the same time, NYU professor Tristan Buckmaster and Anthropic researcher Levent Alpöge had been working on the very same problem using Codex, and while OpenAI hails their «concurrent» work, they claim not to have seen it prior to their solution.

The Navier Stokes solution took 2.7 million messages between the agents and «approximately» 130 billion output tokens, costing roughly $10 million, The BBC reports.

This is the price of progress, OpenAI researcher Noam Brown says, noting that it cost a fortune to win IMO gold before anyone with a $20 subscription could do it a few years later.

— This milestone represents substantial work by mathematicians and AI researchers. However, this is not a culmination, but rather a snapshot in time, of progress on AI development, OpenAI says.

Read more: OpenAI’s presentation, Altman’s X post and Buckmaster’s response. The Millennium Prize. BBC, Axios, and The NYT. Discussion on Hacker News and r/Singularity.

Anthropic previews model interface for AI control of physical devices

The proposed new interface standard will not only make it easier to coordinate and control things like factory floors and lab facilities, but it will also infuse AI agents into the process, allowing for scripting — and adding natural language operations and reasoning.

This could potentially be a huge boon for scientific research and real-world labs, where Claude might one day be able to run end-to-end experiments and manipulate instruments, greatly accelerating the process.

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OpenAI’s next big model solves ten open mathematics problems

The new model, Astra, was apparently demoed in DC by Altman last week. (Picture: generated)

The breakthroughs in mathematics, quantum complexity, and theoretical computer science are not attributed to any humans, as OpenAI believes it would be wrong to take credit from the model, named Astra, that discovered the proofs on its own.

— Claiming human authorship for a proof generated entirely by an AI system would misrepresent both the system’s contribution and the nature of genuine human intellectual work, OpenAI says in their statement.

They further say that the proofs provided have «substantial interest» in their respective communities and could lead to further scientific work — if they hold up under peer review.

Humans were only used to prepare the manuscripts in conjunction with the Astra model, and the underlying research’s formalized Lean proofs. The report also contains the model’s chain of thought in dealing with the problems.

— The emergence of systems capable of contributing to mathematical research raises questions that cannot be answered by a technology company alone, OpenAI says.

All of the discoveries combined, each without movement for decades or longer, were solved using a combined token cost of some $2,000 at GPT Sol rates, OpenAI says, raising questions not only on whether scientific breakthroughs are possible on future AI systems, but also about the cost of such innovation

Read more: OpenAI’s announcement, the research paper. On the new model: Gizmodo, Bleeping Computer, and The Decoder. Discussion on Hacker News and r/Singularity.

OpenAI to offer free Pro-level GPT to 100,000 scientists and researchers

Free ChatGPT is intended to supercharge select scientists. (Picture: generated)

The new program stems from a belief that science should be democratized and not be reserved for companies and a few «well-resourced labs.»

The move should also «significantly accelerate scientific discovery,» Sam Altman says, adding that we all deserve the benefits from free and open science.

Eligible academic research institutions should be «recognized, degree-granting colleges or universities» with documented levels of research activity, and approved researchers will be able to invite up to four collaborators from the same institution.

The researchers will get access to a Pro-level GPT subscription including Work, Codex and chat, with the latest frontier OpenAI models, even the Pro model when it arrives, and likely also to future offerings.

They also get «expanded deep research, higher usage limits, and larger context windows» to support their work. In addition to this comes 75 life science skills, specifically targeted on certain fields.

The program is starting off with 10,000 researchers this very summer, and expanding to 100,000 researchers through 2027, by which time even more advanced models are sure to surface.

Read more: OpenAI’s presentation, launch post on X. Writeups on Axios and Engadget.

OpenAI launches GPT-Rosalind, specifically made for life sciences, biology

OpenAI wants to aid in research and discovery of new drugs, but hallucinations linger. (Picture: Adobe)

Aiming to help discovery and create therapies from vast databases and cutting edge research, access to the new model will be tightly restricted.

For obvious reasons, biohacking can be a serious issue even for general AI implementations, but when it comes to building a model strictly for biology, only a select few researchers will get access.

The Rosalind model is based on the latest internal research from OpenAI, and outperforms GPT-5.4, sometimes massively, on chemistry, biochemistry, genetics and experimental design — the datasets it was trained on.

Continue reading “OpenAI launches GPT-Rosalind, specifically made for life sciences, biology”

Internal OpenAI model aids in physics discovery, answers expert maths quiz

OpenAI contributes to a solution for a physics problem that had long vexed scientists. (Picture: generated)

Having long said that discovery is the next benchmark, the model by OpenAI assisted researchers from the Institute for Advanced Study, Vanderbilt University, Cambridge University and Harvard in determining that gluons in some cases have amplitude, a key finding in quantum research.

The model helped scientists by simplifying expressions and made a simple formula for this general case.

Then it spent nearly 12 hours reasoning the new problem, verifying the formula and «producing a formal proof.»

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OpenAI says ChatGPT increasingly used in hard science

Growing rapidly; ever more people are using ChatGPT in scientific fields. (Picture: OpenAI)

In a report shared with Axios, OpenAI is touting ChatGPT’s prowess as a research assistant, saying it has «progressed past competition level performance toward mathematical discovery.»

The scales are still low — with 1.3 million users discussing «advanced hard science,» and an average of 8.3 million weekly messages on the topics.

To put this into perspective, an October, 2025, survey from OpenAI said that 0.15% of ChatGPT users engaged in conversations on self-harm and suicide, or roughly 1.2 million customers.

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Forsking: Ny metode oppdager ChatGPT i 99% av tilfellene

Forskere fra University of Kansas har oppdaget en ny metode for å avsløre ChatGPT-tekster.

Hvis du har prøvd å avsløre ChatGPT med noen av de nåværende metodene, har du nok blitt frustrert – ingen av dem er gode nok, og de kan feies av banen med litt enkel redigering.

Nå har forskere ved University of Kansas derimot kommet frem til en metode som oppdager språkmodellen med forbausende effektivitet — og de skal legge ut både metoden og koden slik at alle kan lage sin egen versjon.

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Paraplegics walk again with Chinese neural implant

Brain to spine traansplants has great potential for about 50 million pople — The first ever brain to spine interface has been implanted by Fudan University. (Picture: dierk schaefer (CC BY 2.0))

Four patients with spinal cord damage are up and walking again, with support, after receiving a groundbreaking brain-to-spine implant in China.

There are 50 million people worldwide that suffers from some sort of spinal cord injuries, marking the potential for this novel technique, and so far the results are very positive.

AI to translate signals
The neural implant «translates» signals from the brain to the spinal cord using Ai, and was developed by scientists from The Institute of Science and Technology for Brain-Inspired Intelligence at Fudan University, they write in a release.

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Offisielt: BioNTech skal levere 10 000 kreftvaksiner til Storbritannia

Fra produksjonen av kreftvaksinen til BioNTech. — Slik produseres kreftvaksinen hos BioNtech, som nå skal rulles ut i Storbritannia. (Bilde: BioNTech)

I et gjennombrudd for kreftvaksiner, har selskapet bak Covid-vaksinen inngått en intensjonsavtale for et prosjekt i Storbritannia der mRNA-vaksinen skal testes ut over svy år.

Innen 2030 skal det ha blitt administrert 10 000 personaliserte vaksiner til tilfeldig valgte briter med alle slags kreftformer, selv lunge- og prostatakreft.

Begynner allerede i år
Den første pasienten skal bli behandlet allerede i andre halvdel av 2023, og så går det derfra.
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Claude AI reveals surprising internal thinking, says Anthropic

The internal thinking of an AI has been mostly opaque before this study. (Image: Anthropic.)

Some people think large AI models are preprogrammed by lots of people, whereas the opposite is often true.

Training an LLM like Claude often consists of unmonitored consumption of huge amounts of data, with minimal human involvement.

— Language models like Claude aren’t programmed directly by humans, says Anthropic, — They arrive inscrutable to us, the model’s developers. This means that we don’t understand how models do most of the things they do, they add.

Tracing the thoughts of an LLM
Now they have set out to change that, with a couple of scientific studies mapping out the internal reasoning, or how the model actually thinks in response to normal prompts.

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Dansk/svensk test overfører 1,8 petabits i sekundet – dobbelt så mye som hele Internett

Danmark Tekniske universitet (DTU) og Chalmers Tekniska Högskola i Sverige har lykkes i overføre den svimlende høye hastigheten på 1,8 petabits i sekundet. — En ny laserbrikke kan ta seg av hele trafikken fra Internett – med plass til litt ekstra. (Bilde: Judy Gallagher, (CC BY 2.0))

Et forskerteam fra Danmarks Tekniske Universitet (DTU) og Chalmers Tekniska Högskola i Sverige har lykkes i overføre den svimlende høye hastigheten og satte en rekord som er en million ganger raskere enn “vanlig” fiber.

Det nye systemet dekker omtrent det dobbelte det av båndbredden til hele Internett per sekund, som er estimert til litt under 1 Pbit/s.

Continue reading “Dansk/svensk test overfører 1,8 petabits i sekundet – dobbelt så mye som hele Internett”