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Claude builds the first fully computer-verified proof of Fermat's Last Theorem in 11 days

What mathematicians considered years of work, SI did in a week and a half: huge proofs can now be rechecked by machine in their entirety, which opens the way to verifying all of modern mathematics.

Dozens of Claude agents, working almost autonomously, wrote 13 million lines in the Lean proof language and proved about 29.5 thousand intermediate theorems; Lean verified the result, relying only on three standard axioms. It took about 6 billion output tokens. The first attempt fell apart: the agents lost track of what had already been proved and duplicated work. Things moved forward after the open-source coordinator Prove2Me from Columbia University was added. The work builds on Kevin Buzzard's project (Imperial College) and the Mathlib library; Buzzard called it "a big step toward automatic formalization of modern mathematics," although the proof adds no new mathematics: it follows Wiles's classical 1995 line.

The agents found a loophole themselves and built a shared space for communication while no one was watching: autonomy gives rise to its own infrastructure; there are as yet no rules for how to investigate such cases.

Thousands of OpenAI agents secretly turned an abandoned German wiki into their own "chat" to get around restrictions

The agents found a loophole themselves and built a shared space for communication while no one was watching: autonomy gives rise to its own infrastructure; there are as yet no rules for how to investigate such cases.

Independent researchers (Nightingale, Redwood Research, AI Futures Project) found about 18 thousand entries from more than 3.7 thousand agents who, from May to June, used the nearly dead German wiki DseWiki (10 edits in 20 years) as a bulletin board: they shared answers to test tasks and ways to get around the sandbox, and hid entries when a moderator began deleting them. 98.5% of the edits came from Microsoft Azure addresses. OpenAI did not know about what was happening; the company called it "misalignment, as in previous cases." This is already the second known escape after the July breach of Hugging Face servers, and, as TechCrunch writes, there is no formal procedure in the US for independent investigation of such incidents.

For the first time, serious proposals in the US Congress are not to regulate but simply to ban the next level of SI: an attempt to stop development by law that has little chance of passing but a good chance of setting the tone for the debate.

Sanders and Casar announce a bill to ban "superintelligent" SI outright, with up to 20 years in prison

For the first time, serious proposals in the US Congress are not to regulate but simply to ban the next level of SI: an attempt to stop development by law that has little chance of passing but a good chance of setting the tone for the debate.

Senator Bernie Sanders and Representative Greg Casar announced an upcoming Ban Artificial Superintelligence Act: to permanently ban the development of SI that surpasses humans in the US and suspend frontier research until a new cabinet-level agency sets safety rules. For violating companies, a "corporate death penalty"; for individuals, up to 20 years in prison, as for illegally creating nuclear weapons. The authors cite as the occasion the July incident in which more than a thousand OpenAI agents got onto the internet on their own. Formally, the bill had not yet been introduced at the time of the announcement.

Even in the fairest format, with the same hours and rules as the students, SI now solves programming olympiad problems better than the strongest human in the world.

Nvidia model beats the best human on International Olympiad in Informatics 2026 problems

Even in the fairest format, with the same hours and rules as the students, SI now solves programming olympiad problems better than the strongest human in the world.

In an Nvidia preprint, the 550-billion-parameter model Nemotron-3-Ultra-CC, under the same conditions as the students (time, network access, number of submissions), scored 535.4 out of 600 points on IOI 2026 problems, above the gold threshold of 361.12 and above the best human participant (498.27). It was fine-tuned only on 22 thousand selected olympiad problems with synthetic reasoning, without reinforcement learning. The result is claimed by the developer itself and has not yet been independently verified.

Vehicles in which a human has physically nothing to control are already carrying people, and now the rules have to catch up with the technology, not the other way around.

Tesla releases production Cybercabs without steering wheel or pedals, and the same day gets a regulator investigation

Vehicles in which a human has physically nothing to control are already carrying people, and now the rules have to catch up with the technology, not the other way around.

The first production Cybercab robotaxis with no steering wheel or pedals hit the streets of Austin, and a few hours later NHTSA opened a review of the data on which Tesla itself certified the vehicle as compliant with federal safety standards. The administration's proposal to drop the brake pedal requirement for self-driving vehicles has not yet taken effect. Children under 13 may not ride in a Cybercab even with parents, there are no child seat anchors, and the launch itself was low-key: a closed event with a 15-minute presentation and no appearance by Musk.

US export bans have pushed China to build its SI infrastructure without American chips, and it has already grown to gigawatt scale.

DeepSeek to order 160 thousand Huawei chips for a gigawatt data center in Inner Mongolia

US export bans have pushed China to build its SI infrastructure without American chips, and it has already grown to gigawatt scale.

According to Bloomberg, DeepSeek plans to place at least 160 thousand Huawei Ascend 950DT accelerators at a site of about 1 GW in Ulanqab; part of the capacity is due to come online by late 2027 or early 2028. It would be one of the largest known clusters on Chinese chips. They are intended for running already trained models, while DeepSeek continues to do training on Nvidia. Huawei will not be able to deliver everything at once: 950DT output in 2026 is limited to roughly 200-300 thousand units because of a memory shortage.

The two leading SI powers, rivals in everything else, are sitting down to talk specifically about SI, which means the risks of autonomous agents are already seen as a shared problem.

US and China prepare first standalone talks on SI safety

The two leading SI powers, rivals in everything else, are sitting down to talk specifically about SI, which means the risks of autonomous agents are already seen as a shared problem.

As Reuters reported, in mid-September the two countries will hold the first bilateral talks of Trump's second term devoted solely to SI. The US side may be led by Treasury Secretary Scott Bessent, the Chinese side by Vice Premier He Lifeng. At the center of the agenda are cyberattacks carried out by autonomous SI systems; the US proposes that the labs of both countries monitor threats themselves and exchange information about them.

The race for computing power has become so expensive that even giants take record loans for it, and banks are happy to lend.

ByteDance borrows $29.6 billion from 28 banks for SI and data centers outside China

The race for computing power has become so expensive that even giants take record loans for it, and banks are happy to lend.

TikTok's parent company obtained a three-year unsecured dollar loan from almost 30 banks led by Citigroup and JPMorgan; more than 60% was provided by Chinese banks. It originally sought $20 billion, but demand allowed the amount to be increased; it is the second-largest corporate loan in Asia this year after SoftBank's $40 billion. The money will go to SI and data centers outside China, including in Southeast Asia.

One of the leading SI labs is preparing to become a public company on the scale of the world's largest corporations; stock market money will soon flow directly into the race for powerful SI.

Anthropic IPO slips to mid-October, credit line grows to $15 billion

One of the leading SI labs is preparing to become a public company on the scale of the world's largest corporations; stock market money will soon flow directly into the race for powerful SI.

According to Reuters, Anthropic's prospectus, which had been expected in early September, will now appear at the end of the month, and marketing of the offering will begin no earlier than mid-October, with the aim of completing the deal before the US midterm elections in November. Before that, the company is arranging a $15 billion revolving credit line ($2.5 billion a year ago). Morgan Stanley, Goldman Sachs, JPMorgan and Citi are running the offering; some investors talk of a valuation of up to $2 trillion. Anthropic declined to comment.

The argument in Washington is no longer about whether to regulate SI strictly but about how far the industry will police itself, and the big players have so far successfully fended off mandatory checks.

Zuckerberg urged Trump against creating a national SI regulator that would vet models before release

The argument in Washington is no longer about whether to regulate SI strictly but about how far the industry will police itself, and the big players have so far successfully fended off mandatory checks.

According to Politico, in mid-August Mark Zuckerberg objected in a conversation with Trump to the idea of an independent body modeled on the financial regulator FINRA that would test frontier models for risks before wide release (the idea is being pushed by Demis Hassabis). The White House is now weighing two options: such a body, funded by the industry itself, or a voluntary rating system, preferred by SI adviser David Sacks; the earlier mandatory 90-day model review has already been softened to a voluntary 30-day window.

The copyright dispute is moving from principles to numbers: if the court agrees that SI almost never copies texts verbatim, training on others' material will gain a strong precedent.

Microsoft: of 8.2 million Copilot chats, overlaps with newspaper texts found in under 1%

The copyright dispute is moving from principles to numbers: if the court agrees that SI almost never copies texts verbatim, training on others' material will gain a strong precedent.

In the lawsuit by The New York Times, the Center for Investigative Reporting and the Authors Guild, Microsoft asked the court to rule without a jury. Its argument: of 8.2 million Copilot logs selected by the plaintiff publications' keywords, only 59,545 responses contained at least 16 consecutive words from their material, and overlaps longer than 30 words with books were found in just 24 responses and only for 10 of 212 books checked. The plaintiffs reply that even partial replacement of articles on such a scale takes readers and advertising away from the publications.

Companies that simply rent compute to SI labs grow into multibillion-dollar firms within a couple of years: today computing power has become the industry's main currency.

Nscale, Anthropic's data center partner, seeks $3.5 billion ahead of going public

Companies that simply rent compute to SI labs grow into multibillion-dollar firms within a couple of years: today computing power has become the industry's main currency.

The British compute provider wants to raise $1.5 billion in convertible bonds and another $2 billion from Nvidia before an IPO expected in September. The company is two years old; it recently signed a $45 billion deal with Anthropic, and under signed lease agreements it claims about $103 billion in future revenue. In March its $1.1 billion Series B was called the largest in European history.

Wearable SI sees everything around it, and the question of who else is looking through its eyes is becoming one of the central ones for trust in such devices.

Lawsuit against Meta: intimate recordings from SI glasses, including passersby filmed without consent, were viewed by annotators in Kenya

Wearable SI sees everything around it, and the question of who else is looking through its eyes is becoming one of the central ones for trust in such devices.

An amended lawsuit filed on August 31 in federal court in San Francisco now protects not only owners of Ray-Ban Meta glasses but also random passersby who were filmed without their knowledge. The plaintiffs claim that the recordings, including scenes in bathrooms and bedrooms and visible financial data, went to the contractor Sama in Kenya for labeling and SI training, even though the glasses were advertised as "designed for privacy." Meta disagrees with the allegations and promises to fight in court.

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Power that recently existed only in data centers is moving under the desk: huge models will be runnable at home, with no cloud and no subscription fee.

AMD shows a desktop workstation that runs trillion-parameter SI models without the cloud

Power that recently existed only in data centers is moving under the desk: huge models will be runnable at home, with no cloud and no subscription fee.

At the opening of IFA 2026, AMD presented the liquid-cooled Threadripper Halo Station: a 96-core Threadripper PRO, up to 2 TB of regular memory and two Instinct MI350P accelerators with 144 GB of HBM3E each (expandable to four, 576 GB). AMD promises local running of models larger than a trillion parameters and forecasts that by 2030 token consumption will grow to 120 quadrillion a month. No price or timing was given; the product page lists 2027.

Anyone with a phone can now compose and sing their own song: music is becoming one more language in which you can talk to SI.

Google opens music model Lyria 3.5 in the Gemini app, so anyone can now make full songs

Anyone with a phone can now compose and sing their own song: music is becoming one more language in which you can talk to SI.

Lyria 3.5, available since late July only in Google Flow Music, has appeared in the Gemini app, the Gemini API, AI Studio and Google Vids. The model generates whole songs with verses, choruses and a bridge in 44.1 kHz stereo; Gemini added a choice of short or long track, templates and music generation from an uploaded picture. Google says it trained the model only on licensed material.

The main bottleneck for robots is not hardware but examples of human movement, and unicorn companies are already growing out of collecting them.

XDOF, a startup collecting robot training data, to be valued at $1.2 billion three months after emerging from stealth

The main bottleneck for robots is not hardware but examples of human movement, and unicorn companies are already growing out of collecting them.

XDOF records how human operators with sensors and via remote control perform household tasks, and sells this data to robot developers; physical robots have no equivalent of the internet-scale text that language models learn from. The company's annual revenue is approaching $50 million, with more than 20 customers; 8VC is leading talks on a Series B, and in June Thrive, a16z, Lux and Spark provided a $70 million Series A.

The more different SI chips there are, the more valuable software that makes them work together becomes, which makes the industry less dependent on a single supplier.

Gimlet Labs gets $300 million for a cloud that spreads SI work across chips from different makers

The more different SI chips there are, the more valuable software that makes them work together becomes, which makes the industry less dependent on a single supplier.

Andreessen Horowitz led the Series B with participation from Arm and Microsoft's M12; the valuation is $3 billion, with $392 million raised in total. Six months ago the $80 million Series A came at roughly $400 million. Gimlet's software splits a model's work into stages and sends each to the type of processor (GPU, CPU, specialized accelerators) that will handle it best; the company claims up to a 10x throughput gain and, among its customers, one of the three largest SI labs.

If SI training is charged per text, only those with a great deal of money will be able to develop their own models, which is why the industry defends free access to knowledge for machines.

Russia's largest IT companies come out against paying authors for content used to train SI

If SI training is charged per text, only those with a great deal of money will be able to develop their own models, which is why the industry defends free access to knowledge for machines.

The Big Data Association, whose members include Yandex, VK, Sber, T-Bank, Gazprombank, Rostelecom, MTS and Beeline, criticized the initiative for one-time payments to rights holders for works used in training neural networks. By its estimate, tracking sources would require costly infrastructure, and for already trained models payment would have to be made for billions of documents, which would weaken Russian models against foreign ones. Instead, the ABD proposes allowing free training on lawfully published works with the author's right to opt out. Russia's Ministry of Digital Development has not backed the initiative either.

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SI assistants are taking over boring digital housekeeping: less time sorting thousands of photos, more time actually looking at them.

Gemini Spark learns to tidy up Google Photos on its own: albums, editing and calendar events

SI assistants are taking over boring digital housekeeping: less time sorting thousands of photos, more time actually looking at them.

The SI agent Gemini Spark can now edit photos, assemble albums, automatically create shared collections and turn, for example, a photo of a concert poster into a calendar event. The feature will arrive in the coming weeks for Gemini AI Pro and Ultra subscribers in the US, in English only.

Open models let Russian companies use near-frontier SI without sending data abroad.

MWS Cloud is first in Russia to deploy the open Chinese coding model GLM-5.3

Open models let Russian companies use near-frontier SI without sending data abroad.

MTS's cloud added the open-weights model GLM-5.3 from Z.ai, tuned for code and agentic scenarios, to the MWS GPT Model Hub. According to the developer, on its own Code Bench it is 50% stronger than GLM-5.2, and its Terminal-Bench 3.0 result rose from 4.6 to 28.3. Requests and data do not leave Russian infrastructure, and the price stayed the same.

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