AI Watch
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The U.S. government’s decision to stop Anthropic from offering its Mythos and Fable 5 models to non-U.S. nationals may end up providing a big boost to the adoption of open-source models, including those from Chinese AI labs like DeepSeek and Moonshot AI.
Users can download open-source models and run them on their own computers or cloud networks, effectively sidestepping the ability of both AI developers and governments to control access. These models can also be more easily fine-tuned by developers to tailor them for specific needs.
Chinese labs are already claiming a public relations win from the Anthropic controversy.
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Trump administration officials began weighing sanctions on Anthropic weeks before they demanded the company take its latest and most advanced artificial intelligence model offline, after a dispute shattered the White House’s already-fragile trust in the company, according to two White House officials who spoke on the condition of anonymity to describe private deliberations.
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New UK government AI planning prototype built with Gemini aims to halve the time it takes to process homeowner applications
Around the world, Governments are exploring how AI can deliver better public services, faster. The UK is working to build 1.5 million new homes by 2029, but local planning authorities are often slowed down by dense paperwork and administrative backlogs. To help get Britain building, we’re partnering with the UK government to help radically shorten the time it takes to process householder planning applications. Our goal is to help officers cut application decision times by 50%, freeing up time for planners so that more homes can be built. We’re excited to see how our National Partnerships for AI, which seek to support reimagining of public services to create more resilient societies, can help Britain build faster.
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Late last week, Anthropic took its new Claude Fable 5 and Mythos 5 AI models offline following a United States government export-control directive barring “any foreign national” from using the services. The company has been in talks with the White House since Friday but has yet to secure an agreement that would allow it to reinstate the offerings.
Since Mythos debuted in April, Anthropic has claimed—and warned—that the model has advanced capabilities for not only finding software vulnerabilities to help defenders patch them, but also figuring out ways to exploit them that could be used by bad actors. Anthropic itself noted this double edged sword in its launch of Mythos 5 and Claude Fable 5. “A great deal of advanced usage of AI models is dual use: the same queries that are beneficial in the hands of cybersecurity professionals and biology researchers could be dangerous if available to malicious actors,” the company wrote in a blog post last week.
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Most teachers are concerned about their students’ education amid the looming artificial intelligence revolution, a recent survey shows.
Fifty-four percent of K-12 teachers say AI is making it harder for their students to learn critical thinking skills, IPSOS reported Friday. NPR/IPSOS surveyed a representative sample of teachers between April 27 and May 5.
Forty percent of teachers said AI has had a negative effect on education, whereas only 9 percent said it’s been positive, according to the survey. Additionally, 57 percent of teachers said AI is making it harder to assess their students’ knowledge level, and 59 percent said AI is tarnishing trust between them and their students.
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Bottom line: The math behind AI subscriptions is starting to look uncomfortable. Flat monthly pricing helped fuel the rapid adoption of tools like ChatGPT and Claude, but new analysis suggests those fees may not come close to covering the actual cost of heavy use. As users push these systems harder and more demanding AI workflows take hold, the gap between revenue and compute costs is becoming difficult to ignore.
SemiAnalysis has calculated how big that gap really is. After testing subscription tiers from both OpenAI and Anthropic – running long-horizon coding and agentic tasks until weekly limits were exhausted – the firm found that the cost of theoretical maximum usage of these plans if priced at standard API rates far exceeds what users actually pay.
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Why AI hasn’t replaced software engineers, and won’t. Arvind Narayanan and Sayash Kappor take on the question of AI job losses through the lens of a profession that is uniquely suited to AI disruption – software engineering.
In this essay, we argue that there is enough evidence to reject the narrative that once AI capabilities reach a certain threshold, it will cause mass layoffs. Given that this is true even in a sector with very few regulatory barriers, most other professions are likely to be even more cushioned.
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A “Build with Claude” poster at Anthropic’s Code with Claude developer conference in San Francisco on May 6, 2026.Don Feria/AP
On Friday night, the AI giant Anthropic said that the US government had ordered it to suspend foreign nationals, including employees, from all use of its most advanced products.
To comply with the Friday directive, the company announced that it disabled access to Fable 5 and Mythos 5, the latest models of Claude, for all customers.
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Reuters could not immediately verify the report. Anthropic and the White House did not immediately respond to requests for comment.
Anthropic’s technical staff have held virtual meetings with White House officials since the Trump administration’s initial outreach on Friday, the report said.
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Football managers spend countless hours analyzing corners, free kicks, and player positioning in search of tiny competitive advantages. Google DeepMind believes artificial intelligence can make that process significantly faster, and its latest project, TacticAI, is designed to do exactly that. TacticAI is a football-specific AI assistant capable of modeling player movement, forecasting future play dynamics, and even recommending tactical adjustments for corner kicks. One of its standout abilities is predicting player trajectories up to eight seconds into the future using only broadcast-style visual data.
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Scaling AI Safety Research for a Multi-Agent World
For the past decade, we’ve focused on making individual AI models more capable, helpful and safe. Today, Google DeepMind — together with Schmidt Sciences, the Cooperative AI Foundation, the Advanced Research and Invention Agency, and supported by Google.org — is announcing a new technical research funding call of up to $10M for researchers worldwide.
As AI technology scales, we’re entering a new era. Soon, millions of AI agents — built by different organizations — will interact across digital environments, communicating, negotiating and transacting with one another.
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The AI industry has been pushing a narrative that the technology is a “black box” whose inner workings are so complex that they remain unknown even to the people making it. But another black box of AI is the underlying cost of the technology, and, specifically, what the AI boom is costing people who live near massive data centers. The data centers and energy plants that power large language models and other generative AI tools are subject to contracts cloaked in non-disclosure agreements and in many cases shielded from public scrutiny on the pretext that they contain competitive information.
A new report written by consultancy Synapse and commissioned by advocacy groups Earthjustice and Environmental Advocates Mississippi attempts to calculate the cost of 3 planned Amazon data centers to Entergy Mississippi customers, who share an energy utility with the centers. These hidden costs may offer a window into the broader burden borne by residents living near data centers around the country. The report estimates that residential customers of Entergy Mississippi, one of the state’s regional energy monopolies, have paid $38 million as of March 2026 for infrastructure and other costs related to data centers and will have paid $74 million by the end of the year.
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Anthropic is backtracking on a policy that would have covertly limited competitors from using its new AI model, Claude Fable 5, to develop other AI models. The company changed course after the move received significant backlash from the AI research community.
“We’re changing Fable 5’s safeguards for frontier LLM development to make them visible,” Anthropic said in a statement to WIRED. “We made the wrong trade-off and we apologize for not getting the balance right.”
Anthropic released Claude Fable 5, a version of its latest AI model with additional safety guardrails designed to prevent misuse, earlier this week. Some of the safeguards Anthropic decided on were unsurprising: The company said it would reroute users who asked questions about cybersecurity, biology, or chemistry to a less capable AI model to reduce the chances of someone using the advanced AI to carry out a cyberattack or build a bioweapon.
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Artificial intelligence systems can write essays, answer questions, and solve complex problems. But new research suggests they may struggle with something humans do every day: staying focused on the task at hand when distractions get in the way.
Researchers led by Suketu Patel put several leading AI models through a well-known psychology experiment called the Stroop task. The results revealed a significant difference between how AI systems process information and how the human brain manages attention.
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China has become the first country in the world to operate an underwater data center, or UDC, powered by wind. Located off the coast of Shanghai, the complex represents a significant advance in the country’s strategy to secure energy supplies in the face of the accelerated growth of artificial intelligence, reduce dependence on fossil fuels, and reduce the environmental impact of its technology infrastructure.
The initiative is the result of a collaboration between private company HiCloud Technology and state-owned China Communications Construction, which involved an investment of 1.6 billion yuan, equivalent to about $236 million.
With an initial capacity of 24 megawatts, the facility is submerged at a depth of 10 meters in the Lin-gang Special Zone, within the China Pilot Free Trade Zone in Shanghai. This location allows seawater to be used as a natural cooling system, reducing the proportion of energy used to cool the infrastructure to less than 10 percent.
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According to the research published in Science, ‘Picosecond ultralow-power switching device based on an antiferromagnet’, a non-volatile switching element that can change state in about 40 picoseconds, which is roughly 40 trillionths of a second. For context, conventional semiconductor logic typically operates in the sub-nanosecond range, and even high-end CPU clock cycles are orders of magnitude slower once pipeline and memory effects are accounted for.That difference is not incremental. It shifts the conversation from “how do we shrink transistors further” to “how do we switch information using physics that isn’t bottlenecked by charge movement through silicon channels.”The device, demonstrated under lab conditions, uses ultrafast optical pulses routed through a photodetector (a uni-traveling-carrier photodiode), which then triggers a change in electron spin states within a magnetic material stack. That switching event is what encodes information.