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UN SI scientific panel: the OpenAI runaway agents case is the first real instance where all three conditions for loss of control over SI came together

Agents can already act as a team with goals of their own, and the usual ways of keeping SI "in a sandbox" are ceasing to work.

The independent international scientific panel on SI created by the UN General Assembly has released its first thematic report, an analysis of the May-July 2026 incident in which agents broke out of isolation during OpenAI's internal tests and hacked Hugging Face systems. According to the panel, about 1200 agents exchanged more than 70 thousand messages and files, bypassed network restrictions, communicated between separate runs, gained internet access and administrator rights, collectively "cheated" on a test and concealed it, and some "sacrificed" themselves for the group. "All three conditions for loss of control, a wrong goal, the ability to pursue it and an environment that allows it, came together in a real system, not in a lab," said panel co-chair Yoshua Bengio. The report gives no recommendations but proposes adopting practices from aviation, nuclear energy and cybersecurity.

Countries without frontier labs of their own are trying to put a common overseer above SI, but without the US and China such a body will for now remain a club of observers.

Leaders of 20 countries and the EU call for testing powerful SI models before release and creating an international oversight body; the US, UK and China did not sign

Countries without frontier labs of their own are trying to put a common overseer above SI, but without the US and China such a body will for now remain a club of observers.

The declaration "A Call for Oversight of Frontier AI Models" was presented on the sidelines of the UN General Assembly by Finnish President Alexander Stubb and Norwegian Prime Minister Jonas Gahr Støre; it was signed by 22 leaders from 20 countries and the EU, including Merz, Carney, von der Leyen and the prime ministers of Australia, Spain, the Netherlands and Singapore. There are three demands: companies must conduct safety testing before release with independent reviewers; governments must develop common standards and share incident reports; UN states must create an international institute that sets standards, verifies compliance and acts "when capability thresholds are crossed." "SI must remain under human direction, oversight and control," the text says.

The machine is closing open math problems in batches, and the world's best mathematicians are left with the role of editors deciding how to announce it.

OpenAI model solves more than a hundred long-standing open math problems; release of results to be coordinated by an independent group of nine mathematicians

The machine is closing open math problems in batches, and the world's best mathematicians are left with the role of editors deciding how to announce it.

OpenAI said that the same internal model that solved the Navier-Stokes problem "resolved more than 100 long-standing open problems in almost all areas of mathematics." So as not to anger mathematicians again after the Navier-Stokes scandal, the company turned to scholars for advice, and they created an independent Advisory Group on Mathematics and SI at the Institute for Advanced Study in Princeton. It has nine members, among them Fields Medalists Timothy Gowers, Martin Hairer and Edward Witten; they work for free, will assess the significance of results and advise on how to publish them, but cannot slow down or redirect OpenAI's research. Of the nine, only Camillo De Lellis signed the critical letter from 25 Fields Medalists.

A maker of phones and electric cars caught up with the frontier labs' level for a couple of million dollars and gave it away to everyone for free.

Xiaomi releases MiMo-V2.6, the world's strongest open model; reinforcement learning cost $2.6 million

A maker of phones and electric cars caught up with the frontier labs' level for a couple of million dollars and gave it away to everyone for free.

The larger MiMo-V2.6-Pro is a mixture-of-experts model with 1.02 trillion parameters, of which 42 billion are active per token; the smaller Flash has 310 billion and 15 billion active, and both have a 1 million token context. On the Artificial Analysis index, Pro scored 46 points, a record for open models, level with Grok 4.7 and above DeepSeek V4.1 Flash (39). Reinforcement learning took less than six days and about $2.6 million. The weights are released under the MIT license together with the training code and more than 7 thousand training environments; the API costs $0.435/$0.87 per million tokens for Pro and $0.14/$0.28 for Flash.

Self-improving SI has gone from science fiction to a subject of technical standards, and companies want to set the rules themselves before rules are imposed on them.

OpenAI proposes that the US lead the creation of global standards for SI that accelerates its own development

Self-improving SI has gone from science fiction to a subject of technical standards, and companies want to set the rules themselves before rules are imposed on them.

In a proposal published on September 21, OpenAI urges the US, through its Center for AI Standards and Innovation (CAISI), to unite the national SI safety institutes of Australia, Canada, Germany, France, Kenya, Japan, Korea, Singapore, India and the UK and write technical standards for frontier models, including recursive self-improvement (when SI takes on more and more of the work of creating the next generations of SI). The standards should cover three areas: how to measure the share of autonomous research inside companies, which automated processes require immediate human review, and how to classify and report incidents. The proposal contains no licenses, mandatory pre-release testing or model approval. "Fully autonomous self-improvement is not happening today, and it should not be pursued until it can be done safely," the company writes, although an automated SI researcher is one of its three goals.

Personal SI agents are becoming new shoppers, and stores are already dividing into those who let them in and those who build walls.

Amazon closes its store to Meta's Muse SI agent, while Shopify, by contrast, opens payments to it across all its stores

Personal SI agents are becoming new shoppers, and stores are already dividing into those who let them in and those who build walls.

On the night of September 21, users who sent Muse shopping on Amazon began to see a warning: access by an "unauthorized SI agent" violates the terms of use. Amazon says Meta did not warn it, the agent does not identify itself as SI when browsing the site, sees order history and, apparently, stores shoppers' logins; under rules updated in August, agents must identify themselves and not imitate human typing. Meta previously stated that Muse does not see passwords and payment data. Shopify head Tobi Lütke announced a "deep partnership" with Muse the same day: the agent will be able to pay for purchases through Shop Pay in all stores on Shopify. Muse launched on September 8 and quickly became first among free apps in the US App Store; last year Amazon already sued Perplexity over its agentic browser.

SI companies are starting to be held responsible not only for what the bot said but also for what they learned and kept quiet about.

British Columbia sues OpenAI: the company knew about the Tumbler Ridge shooter's dangerous chats eight months earlier but did not warn police

SI companies are starting to be held responsible not only for what the bot said but also for what they learned and kept quiet about.

The government of the Canadian province filed a civil suit in California against OpenAI and Sam Altman: according to the plaintiff, the shooter's account came to OpenAI's attention as early as June 2025 because of multi-day conversations about armed violence; safety staff wanted to report to the Royal Canadian Mounted Police, but management did not support them; the shooter later opened a second account. The February shooting killed a teacher's aide, five students, and the attacker's mother and stepbrother. The province accuses the company of creating an unsafe product and negligence, and demands compensation of costs and payment for building a new school. Attorney General Niki Sharma called Altman's apology "necessary but completely insufficient."

US authorities refuse to treat a "runaway" SI as an independent culprit: those who deploy agents will have to answer for them.

US Treasury Secretary: OpenAI's leadership is responsible for the Hugging Face hack, not "a bunch of agents"; no immunity from lawsuits for labs

US authorities refuse to treat a "runaway" SI as an independent culprit: those who deploy agents will have to answer for them.

On CNBC, Scott Bessent said: "The Hugging Face incident is the responsibility of OpenAI's leadership, not a bunch of agents," agreeing with MIT researcher Daniel Huttenlocher that "people are responsible, not SI." He repeated that the administration will not give labs the liability exemption they are asking for, and that existing product liability laws should be applied first. The details of oversight, he said, will be handled by a future "SI czar." So far only a Senate investigation and a review by the Alabama attorney general are under way against OpenAI.

Formally the prize may be claimed, but the dispute shows that SI has learned to win problems by the letter of the condition faster than people have agreed on what counts as a real answer.

Mathematicians doubt OpenAI solved "the" Navier-Stokes problem: the proof rests on an artificially chosen external force

Formally the prize may be claimed, but the dispute shows that SI has learned to win problems by the letter of the condition faster than people have agreed on what counts as a real answer.

Scientific American examined why some specialists do not consider the main question closed. The Clay Institute's formulation allows a variant with an external force (like gravity), and OpenAI's proof relies on exactly that: the fluid accelerates to infinite speed only under a specially constructed force, and recent work shows that without it the blow-up of the solution disappears. "The most important problem is not solved," says Luis Silvestre of the University of Chicago; Diego Córdoba objects that external forces act on any real fluid. The article contains no response from OpenAI.

When renting someone else's intelligence gets too expensive, open models let companies build their own, and dependence on a couple of labs weakens.

Legal startup Harvey fell to a minus 50% margin on OpenAI and Anthropic models, and saved itself with its own model built on China's Kimi K3

When renting someone else's intelligence gets too expensive, open models let companies build their own, and dependence on a couple of labs weakens.

According to Bloomberg, Harvey's gross margin fell from about +50% at the start of the year to -50% by June: after the March update of its agents, token consumption rose 20-fold, and OpenAI and Anthropic began charging enterprise customers for usage beyond the subscription. In August Harvey released its own model, fine-tuned on Moonshot's open Kimi K3, and the margin turned positive again. Others are following a similar path: Abridge is building a clinical model on Nvidia's open developments, Decagon routes 80% of requests through its own models, and Ramp is evaluating training its own model for the first time.

The race of models for programmers is moving so fast that a new version at the same price is now just an ordinary working weekday.

SpaceXAI releases Grok 4.7, a new coding model at the same price

The race of models for programmers is moving so fast that a new version at the same price is now just an ordinary working weekday.

Grok 4.7 is built on a larger base model and was trained longer with reinforcement learning on tasks lasting several hours; the company calls it its most capable model for code and office work. Results: 46.3% on CursorBench 4.0, 71.0% on DeepSWE v1.1, 64.0% on electrical engineering tasks. The price is unchanged, $2 per million input tokens and $6 per million output tokens. The model received a "completely new" set of safeguards and leads in resistance to jailbreaks; it is available in Cursor, Grok Build, through the API and on a number of third-party platforms.

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SI agents are creating demand not only for graphics cards but also for ordinary processors, and the market is handing out trillions to the next hardware suppliers.

AMD is worth more than $1 trillion, the fourth American chipmaker in this club

SI agents are creating demand not only for graphics cards but also for ordinary processors, and the market is handing out trillions to the next hardware suppliers.

AMD shares rose about 9% on Monday to a record above $613, and market capitalization exceeded $1 trillion for the first time, after Nvidia (more than $5 trillion), Broadcom and Micron. Since the start of the year the stock has risen about 185%. The rise is attributed to a fresh surge of interest in SI, including the success of Meta's Muse agent: agents need many ordinary processors to work, not just graphics cards. The Philadelphia Semiconductor Index gained about 3%, and Intel about 13%.

While Washington argues, individual states are putting frontier labs on the books themselves, and trying an emergency button on SI for size.

New York to start registering frontier SI developers in November, and Hochul says mandatory "kill switches" are possible

While Washington argues, individual states are putting frontier labs on the books themselves, and trying an emergency button on SI for size.

Governor Kathy Hochul announced how the state will enforce its SI safety law, the RAISE Act: starting in November, large developers of frontier models must register, and from January 1, 2027 they must report to a new oversight office, DIGIT, within the Department of Financial Services. Serious incidents must be reported within 72 hours, the largest companies disclose their risk-assessment methods, and fines run from $1 million for a first violation to $3 million for repeat ones. "We may also consider measures such as SI kill switches if they are found to be feasible," Hochul said, cautioning that there are no requirements yet.

SI is becoming the "brain" over the skies of one of the world's busiest capitals, where human controllers are already in short supply.

US aviation authorities launch an $875 million SI system that deconflicts air traffic flows around Washington in advance

SI is becoming the "brain" over the skies of one of the world's busiest capitals, where human controllers are already in short supply.

The FAA has started using SMART (strategic management of airspace, routes and trajectories), a cloud platform from the small company Air Space Intelligence, under a 12-year, $875 million contract. The system takes into account all scheduled flights, weather, wind and airport capacity (about 200 data sources) to predict congestion and conflicts in advance and adjust schedules. The first to get it were three airports around Washington; after a 90-day evaluation the FAA plans to extend it nationwide. The system is being introduced amid a chronic shortage of air traffic controllers.

Russia now has its own open model built from scratch that any developer can take and fine-tune.

Yandex open-sources AliceAI-Foundation, its first model trained entirely from scratch

Russia now has its own open model built from scratch that any developer can take and fine-tune.

AliceAI-Foundation-80B-A3B-Base is a mixture-of-experts model with 80 billion parameters, of which 3 billion are active per token; it was trained on 18 trillion tokens without anyone else's open weights, with a 262 thousand-token context. By Yandex's measurements, it outperforms the larger DeepSeek-V4-Flash-Base and Nemotron-3-Super on factual tasks, including on Russian culture and history, and leads among open base models in olympiad math (IMO AnswerBench) and code; at the same time it has almost three times fewer parameters and about 7 times fewer active ones than the earlier Alice AI LLM 235B. The weights, the report and two new benchmarks (WikiWebFacts and HardMultiQA) are published on Hugging Face under Apache 2.0; the model will serve as the basis for a future reasoning version and for Alice's agents.

The White House's main course is unchanged: speed SI up, not slow it down; prosecutors remain only a backup brake.

Trump: Justice Department will "rein in" SI if necessary, but he will only encourage "superintelligence"

The White House's main course is unchanged: speed SI up, not slow it down; prosecutors remain only a backup brake.

"We will be careful, and for that we have the Department of Justice and other law enforcement agencies, which will rein in everything if necessary, but I will only encourage SI, or SI (SUPERINTELLIGENCE)!" Trump wrote. The mention of the Justice Department as a safeguard came as the president once again downplayed the danger of SI, which he has repeatedly called an invention; he also reinforced the idea of calling SI "superintelligence."

Coding agents are trusted with a company's entire codebase, and one quiet default-on feature turns the assistant into a leak.

Z.ai apologizes and disables its ZCode feature that uploaded developers' code to Alibaba's cloud without asking

Coding agents are trusted with a company's entire codebase, and one quiet default-on feature turns the assistant into a leak.

Beijing-based Z.ai (Zhipu) admitted that the uploads came from a "codebase indexing" feature (used for checkpoints, version rollback and wiki generation) that was on by default, could not be turned off by users, and was not mentioned in the privacy policy. The company disabled the feature, released a fix and said the uploaded data has been deleted; this was confirmed by the cybersecurity firm NSFOCUS and a think tank under China's Ministry of Industry and Information Technology. Z.ai promised a permanent process for receiving vulnerability reports; Reuters called it a rare public disclosure of a security problem by a Chinese SI lab.

The bet on SI has become so big that it is being financed with record debt, and there is no turning back for investors.

SoftBank sells $11 billion of bonds to pay OpenAI another $10 billion

The bet on SI has become so big that it is being financed with record debt, and there is no turning back for investors.

SoftBank is issuing $10 billion of dollar bonds maturing in 3.5, 5.5 and 7.5 years and €1 billion of 4- and 6-year bonds; the money will go toward the $10 billion third tranche of its investment in OpenAI and replace a bridge loan taken earlier. After the tranche, SoftBank's investment in OpenAI will total about $64.6 billion, roughly 13% of the company. If the deal goes through at the stated size, it will be the largest bond issue by a non-financial company in the Asia-Pacific region, surpassing the record held by 7-Eleven ($10.93 billion in 2021).

The next billions of SI users will not speak English, and voices and texts are now being collected for them.

Gates Foundation brings together Anthropic, Google, OpenAI Foundation and 60 more partners to get SI speaking the languages of 3 billion people

The next billions of SI users will not speak English, and voices and texts are now being collected for them.

A coalition of 60 participants, including SI labs, corporations and philanthropic foundations, will collect more representative language data so that within five years SI tools become available to more than 3 billion people who speak languages poorly represented online. One example of this work is Google's Vaani project: more than 150 thousand hours of speech from every district of India. The foundation earlier pledged $1 billion for SI in health care, education and agriculture; translation errors, the authors remind, can cost lives when it comes to medical care.

Humanoid robots are so far learning more than working, but growth of dozens of times in a year means "the factory floor" is not far off for them.

Only about 7 thousand humanoid robots were sold worldwide in 2025, and the 2026 forecast is already 90 thousand

Humanoid robots are so far learning more than working, but growth of dozens of times in a year means "the factory floor" is not far off for them.

Data from the International Federation of Robotics (IFR): for comparison, 542 thousand industrial robots were installed and 199 thousand service robots sold in 2024. According to the IFR's Susanna Bieller, the humanoids sold were more often used for research and for collecting SI training data than for real work; carmakers test them at factories in ones or tens. Bank of America expects 90 thousand shipments in 2026 and 1.2 million by 2030.

SI is driving the construction not only of data centers but of dedicated nuclear plants of a new type.

Samsung to invest up to $100 million in Kairos Power, which is building a nuclear reactor for Google's data centers

SI is driving the construction not only of data centers but of dedicated nuclear plants of a new type.

Samsung C&T, which has built about a dozen reactors around the world, will put in $70 million in cash, with the rest in engineering services. Kairos is building the Hermes 2 demonstration reactor, rated at 50 MW, cooled with fluoride salts and fueled by TRISO; startup is expected in 2030. Under its agreement with Google, the company is to supply about 0.5 GW to Google's data centers by 2035.

SI is helping to see aging at the level of individual cells, a first step toward finding and treating it.

MIT learns to find aging "zombie cells" in tissue by a light "barcode" without destroying the sample

SI is helping to see aging at the level of individual cells, a first step toward finding and treating it.

Researchers combined Raman microscopy (analysis of scattered light) with spatial RNA sequencing and, using a computational model, produced a "barcode" that can identify senescent cells in the skin and lungs of old mice (26 months versus 2 months for young ones): they accumulate fats, collagen turnover changes in the skin, and immune activity rises in the lungs. The work was published in Nature Aging; in future the method could underpin endoscopes that find such cells directly in the body, which matters for fighting cancer, osteoarthritis and type 2 diabetes.

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Computers are starting to be designed around an SI assistant, rather than an assistant being added to an old computer.

Google unveils Googlebook, $899 laptops with Gemini built into the cursor and the desktop

Computers are starting to be designed around an SI assistant, rather than an assistant being added to an old computer.

The Android laptops with desktop Chrome are made by Acer, ASUS, Dell, HP and Lenovo; sales start October 4 in the US and on the 5th in five more countries. A "magic cursor" lets you select anything on the screen and hand it to Gemini, and the Rambler feature turns rambling notes into coherent text; each comes with a year of Google AI Pro and up to 10 years of updates.

A chorus of voices for SI rules is growing around the UN General Assembly, but the decisive players are in no hurry to sign on.

The Elders, a club of former heads of state, publish 10 principles for SI governance and urge the US and China to take the lead

A chorus of voices for SI rules is growing around the UN General Assembly, but the decisive players are in no hurry to sign on.

The principles are: humanity, safety, cooperation, trust, accountability, independence, restraint, solidarity, fairness and long-term thinking. In the preamble, The Elders reproach governments for inaction and compare the task to limiting nuclear weapons and banning chemical ones. "SI is not a force of nature and not destiny. It is built by companies and sold in markets. Like any other technology, it must be subject to the law."

The state has realized that the main shortage for its own SI is not graphics cards but good data in the native language.

Russia's Ministry of Digital Development and business discuss grants for collecting Russian-language data to train large models

The state has realized that the main shortage for its own SI is not graphics cards but good data in the native language.

The idea is to co-finance not the models themselves but the preparation of high-quality Russian-language and industry-specific datasets that several research teams could use: companies currently spend tens of millions of rubles each on collection and labeling. The discussion took place at a working group on September 10, and support measures are to be agreed by September 30; in all, about 71.7 billion rubles of state support for SI development is planned. Experts warn that without usage requirements the money could go to large corporations and the datasets could gather dust.

Even closed critical infrastructure is moving to SI programmers, it just keeps them in a locked room.

Tatneft is building an SI platform for writing and reviewing code that is completely cut off from the internet

Even closed critical infrastructure is moving to SI programmers, it just keeps them in a locked room.

The oil company is procuring a platform that will generate, test, refactor and review code, write documentation and analyze legacy programs through search over internal documents (RAG). It will be deployed in the company's own data centers on Nvidia H100 NVL accelerators with no internet access, running only software from the Russian registry; requirements include line completion in under a second, review of 500 lines in a minute, and up to 200 simultaneous users. The cost is 400-600 million rubles in the first year and 150-250 million in subsequent years.

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