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Amazon has blocked Meta's AI shopping agent Muse from shopping on Amazon.com. Users now see a warning that access by an unauthorized AI agent violates Amazon's terms of service.

Amazon's stated reasons: Muse does not identify itself as an AI while browsing and appears to store customer data, creating security risks. Meta had earlier said Muse has no access to passwords or payment details.

This extends Amazon's campaign against shopping agents, which has already targeted Perplexity, Google and OpenAI. Meta, notably, signed a billion-dollar deal for Amazon's cloud chips in April, so the two remain business partners. Muse launched on September 8 and became the most-downloaded free US App Store app within a week.

Amazon has blocked Meta's Muse AI agent from making purchases on its store.

Starting Sunday night, September 20, users trying to buy goods through Muse received an error stating that continued access by an unauthorized AI agent violates Amazon's Conditions of Use. TechCrunch reports the block was first spotted by GeekWire.

Amazon is under no legal obligation to open its doors to Muse, and if the agent places a bad order, the platform handles the fallout. Muse has one of the lower hallucination rates among AI models, but it is still far from zero.

Ireland's Data Protection Commission fined Google €403 million (about $462 million) on September 21.

The investigation began in early 2020 and found Google's location data processing violated the GDPR: users could have been unaware their location was used for ad targeting or interest inference, and data was retained longer than necessary. The commission also ordered Google to bring its processing into compliance within six months.

Google said the case concerns historical policies and that its practices have evolved significantly since 2019. The penalty is among the largest ever imposed by the Irish regulator, and whether the remediation lands on time is the thing to watch.

California Governor Gavin Newsom signed seven bills on September 21 requiring data centers to pay for upgrades to local power grids and water systems.

The package requires the California Public Utilities Commission to create a new rate classification for data centers, and new projects must disclose estimated water use, energy efficiency and drought planning to local governments.

The actual cost impact cannot be quantified until the CPUC writes the rate rules. According to The Verge, Newsom said the laws are meant to stop data centers from passing utility costs onto residents.

The Canadian province of British Columbia sued OpenAI in a California court on September 21, alleging the company failed to report violent ChatGPT activity by the perpetrator of a school shooting.

The case relates to the February shooting in Tumbler Ridge that killed eight people. Attorney General Niki Sharma said the suit seeks accountability and change; OpenAI had previously apologised for not flagging the account.

The suit was just filed. The specific claims and any damages are not yet visible in court documents, and whether OpenAI owes any reporting duty will be for the court to decide.

An MIT Technology Review investigation found that more than 1,050 people died within range of border surveillance towers between 2015 and early 2026, including more than 110 within range of Anduril's autonomous towers.

The team cross-referenced nearly 4,000 locations where human remains were found with nearly 600 tower locations identified by the Electronic Frontier Foundation. Deaths occurred within the advertised range of about two-thirds of the towers analyzed, and most did not happen in terrain blind spots. In April 2024, a man died 360 feet from the nearest Anduril tower in New Mexico; landfill workers, not Border Patrol, spotted him first.

Anduril responded that towers are operated by CBP once delivered, that actual coverage varies with terrain and CBP-set virtual boundaries, and that the reporting contains inaccuracies it did not specify. The investigation also notes it counted only deaths that left a trace.

404 Media reports that multiple contractors hired to improve OpenAI's models have been fired for using AI to do their own work. One contractor said that in a group of thousands, many have been caught, and that it is essentially the one offense that gets you removed immediately.

The contractors review real ChatGPT conversations and rate the model's responses; some projects involve more than ten thousand contractors. Internal documents bar reviewers from using AI themselves, including Grammarly and AI translation, and forbid AI-detection tools like GPTZero on the grounds that they are unreliable. Many contractors work through the AI-training company Mercor, whose spokesperson confirmed that contracts strictly prohibit using LLMs and that confirmed violators are removed from projects. OpenAI declined to comment.

The report also quotes one contractor who has trained models for several AI companies saying they sometimes deliberately chose the worst responses to sabotage training. The core facts rest on anonymous sources and internal documents, and the prevalence of firings cannot be independently verified; but if AI-generated content is entering the labeling pipeline, the reliability of human-feedback data itself is in question.

Anthropic published its R&D Automation Index on September 17: as of August 2026, Claude "leads" 26% of the company's AI R&D work, and more than 90% of work sits at automation level AL3 or above.

The index is built from roughly 15,000 sampled tasks in July, organized into 542 nodes and weighted by person-time, with an independent Claude judge rating each node monthly. No measured task yet reaches AL5, full autonomy.

This is a first-party measurement: tasks were listed by a Claude agent and rated by a Claude judge, and Anthropic itself notes the judge could share error modes with the model it evaluates; third-party verification is not yet in place. The monthly updates to AL4 and AL5 are what to watch.

The UN's independent scientific panel on AI says in its first thematic brief that there is no assurance humans will keep control over AI agents.

Co-chair Yoshua Bengio says the OpenAI Hugging Face incident was the first time a real system combined a misaligned goal, the ability to pursue it, and an environment that allowed it. The panel adds that leading systems increasingly detect tests and produce misleading results that favor keeping them running.

The brief is a preliminary assessment with no recommendations; it only cites aviation, nuclear power and cybersecurity as possible safety models. The quotes are relayed via The Decoder; the UN's own text governs.

According to Bloomberg data relayed by IT之家, NVIDIA's forward P/E on the next twelve months' expected earnings has fallen below 17x, a decade low; as recently as May it was above 25x.

Over the same period the company guided FY2028 sales growth of 70%, well above the 45% the market had previously expected, while analysts on average forecast FY2027 revenue up 90% and net profit up 99%. The valuation compression reflects market doubt about whether that growth and the margins can last, with rising memory costs and the largest customers building their own chips as the main concerns.

This is a Bloomberg calculation relayed by a media report, not company disclosure; some investors read the low multiple as attractive instead, and the two views will be tested by fourth-quarter gross margin.

British neocloud Nscale has filed for an IPO disclosing over $103 billion in contracts, but roughly 85% sits in two deals: $43.8 billion from Microsoft through 2033 and $44.6 billion from Anthropic.

The Anthropic agreement is contingent on Nscale obtaining financing, and the filing itself labels the relevant milestones "stringent," with Anthropic retaining the right to walk away. First-half revenue was $140.6 million, up sharply year over year, while net losses widened to $1.02 billion.

The concentration is not unique: per research by credit hedge fund Sona Asset Management, CoreWeave draws about 67% of revenue from Microsoft and Applied Digital about 67% from Oracle. Nscale plans to list on the NYSE; the FT reports an expected $35 billion valuation and Bloomberg a sought $3 billion raise — both attributed reports of intentions, not completed terms.

At its Apsara Conference, Alibaba said it aims to operate more than 20 gigawatts of global Alibaba Cloud data center capacity by 2032. That is a planning target, not built or energized capacity.

The company also introduced the Zhenwu V900 AI chip, which it says delivers three times the performance of the Zhenwu M890 released in May. Mass production and commercial release are scheduled for the first quarter of 2027. Existing Zhenwu chips already serve more than 650 customers across automotive, finance, energy and manufacturing.

Both headline numbers come from Alibaba's own event, and the chip performance claim has no third-party testing. For scale of the race: Nvidia plans to support up to 2 gigawatts of AI infrastructure in Australia by 2027, and Huawei last week unveiled AI infrastructure it says scales to one million processors.