October 11, 2026

AI Markets

Trump Admin Blocks Microsoft, Adobe and Six Other Tech Companies From Green Card Program › American Greatness– amgreatness.com
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Vice President JD Vance announced Thursday that the Trump administration has blocked Microsoft, Adobe, and six other IT outsourcing firms from using the U.S. Department of Labor’s green card program, citing alleged fraud, misuse of H-1B and J-1 visas, and the displacement of American workers.

The suspension bars these companies from submitting new applications to the Permanent Labor Certification Program (PERM), or having pending applications processed. The ban will remain in place “as long as it needs to be,” Vance said.

The vice president also announced federal investigations into nine universities—Harvard, Yale, Stanford, Brown, the University of Pittsburgh, UC Davis, Caltech, Arizona State, and MIT—for visa fraud and undercutting American citizens.

“These universities are employing J-1 visas for federally funded grants at a rate of about 61 percent,” said Vance. “The national average is 38 percent. So something weird is going on at these universities!”

Vance, flanked by Department of Labor (DOL) Secretary Keith Sonderling, DOL Inspector General Anthony D’Esposito,  Attorney General Todd Blanche, senior Trump advisor Stephen Miller, and Anti-Fraud Task Force Vice Chair Andrew Ferguson, made the announcements during a press conference at the White House, Thursday.

How to Defend Against AI-Designed Viruses– warontherocks.com
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Anthropic recently disclosed five cases in which users hid their countries while asking Claude for help enhancing pathogens or toxins. This added fuel to the ongoing debate over whether progress in AI should be slowed. Insider warnings of threats to human lives from artificial intelligence have been received as everything from prescient humility to a hoax or marketing stunt. But in a world where AI-designed biological viruses have already been grown in the lab, the threats should be reckoned with in any biodefense strategy.

The “AI doomer” model of biological risks is that AI will develop intelligence beyond that of any human, leading it to invent a supervirus so much more powerful and fatal than anything in the world that our civilization will collapse. Adherents name this “x-risk.” An opposite view is that virus design is such a hard problem that AI won’t add anything beyond what the best humans can do, and that malicious actors — even state actors — would require access to so much top expertise that production is unfeasible.

Doomerism justifies unrealistic and destabilizing solutions (like bombing data centers) while the dismissiveness of certain biologists — including some, like Claus Wilke and David Bellamy, who are AI experts with experience in synthetic virus design — fosters a complacency that leaves us vulnerable to AI threats.

A US state just approved an AI doctor. For now, it’ll only prescribe acne cures.– www.digitaltrends.com
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The first AI doctor is here. Despite all the skepticism and risks associated with AI models going haywire, the state of Utah just approved Nolla Health, a company that is providing an AI healthcare expert capable of writing prescriptions without any human in the chain. For now, it will only write acne prescriptions for Utah residents over 18 years of age, willing to pay a token monthly subscription fee that’s lighter than your Spotify bill.

The big push here is that the Nolla Derm app will reduce the costs of medical consultation, save users the hassle of clinic visits, and take out the problem of waitlisting from the entire healthcare equation. “Unlike telehealth platforms that use AI only to collect information before handing patients off to clinicians, Nolla’s AI system is designed to independently issue initial prescriptions within tightly defined, physician-approved treatment protocols,” writes the company.

AI appears to be breaking the gateway into the tech world for new technicians. Nearly 50% of entry-level tech jobs have been eliminated by AI. Even though AI is producing jobs as well, this critical interruption of the talent development chain could produce shortages of experienced technicians to manage the AI itself.

Entry-Level Tech Jobs Plunge 49% as AI Begins Wiping Out First Rung of Career Ladder– slaynews.com
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The long-feared artificial intelligence-driven jobs bloodbath may already be arriving for one particularly vulnerable group of American workers: those trying to get their foot in the door.

A disturbing new analysis of New York City employment data reveals that postings for entry-level jobs in computer and mathematical occupations have collapsed by a staggering 49% since 2022.

The findings raise fresh concerns that companies are increasingly turning to AI while dramatically reducing opportunities for young workers and recent graduates who previously relied on junior positions to launch their careers.

Anthropic Says It Discovered a Crispr-Like System. Now What?– www.wired.com
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Tech executives have long touted the potential for their AI models to accelerate the pace of biology discoveries. Last week, they announced one. In a September 23 announcement, Anthropic claimed that its large language model Claude had identified an enzyme system with properties “reminiscent of Crispr,” the Nobel Prize-winning gene-editing tool.

According to Anthropic, about 950 Claude agents running simultaneously found the interesting genetic sequences in 21.5 hours. “I sincerely compliment Anthropic for telling the world about their discovery,” says Fyodor Urnov, a gene-editing expert at the University of California, Berkeley and director for therapeutic R&D at its Innovative Genomics Institute. (IGI is collaborating with Anthropic, but was not involved with the new discovery.)

Other scientists are less enthusiastic about the finding, which is the first to come out of a research group formed by Anthropic earlier this year. “The experiments are still in the queue. The PR is already live,” says Le Cong, a professor at Stanford University focused on integrating AI into genome engineering research.

Anthropic, which has set up a wet lab for drug discovery, has been clear that the finding isn’t the end of its work. (“We don’t yet understand what this system does,” the company said in an X post, “but only a handful of known systems share its features, and all of them are able to cut, copy, and paste DNA.”) One physical experiment was included in a technical report, which has not been peer-reviewed. However, a lot more needs to be done to determine the significance of this discovery. It remains unknown whether this enzyme system can be used as a gene-editing tool and, if so, whether it’s a useful gene-editing tool.

The Economist has estimated AI has created five jobs for every one job lost. Their study claims AI has caused 200,000 job cuts since mid-2023 while creating one million new jobs.

It’s Not All Doom and Gloom: AI Added 1 Million US Jobs, 5 for Every 1 Cut– www.westernjournal.com
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A wave of doomsday warnings about artificial intelligence (AI) is overshadowing a short-term bright spot: the technology appears to be creating American jobs even as it eliminates others.

U.S. employers cited AI in 116,175 announced job cuts through August, roughly 22% of all cuts announced in 2026, according to Challenger, Gray & Christmas.

Yet amid mounting warnings about AI’s threat to workers and even humanity, The Economist estimated in September that AI has created roughly 1 million American jobs compared with roughly 200,000 AI-attributed layoffs since mid-2023 — a ratio of about five jobs created for every one lost.

The figures are not directly comparable. Challenger tracked announced layoffs in which AI was cited as a reason, while The Economist estimated job creation using employment trends, AI-specific occupations and infrastructure hiring. Challenger has recorded roughly 188,000 announced cuts attributed to AI since it began tracking AI separately in 2023.

The broader labor market has so far avoided mass displacement. Employers added 162,000 jobs in August and the unemployment rate remained at 4.1%, the Bureau of Labor Statistics (BLS) reported Sept. 4.

AI-related job creation is also extending beyond the workers constructing the data centers needed to power the technology.

Virtual cells built from 4D AI models and ‘digital twins’ could speed up drug discovery– phys.org
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Mitochondria—tiny structures that convert nutrients into energy—are often depicted as discrete kidney bean-shaped objects. But in reality, they form a dynamic, interconnected network throughout the entire cell, rapidly splitting and fusing as they’re transported to where energy is needed most.

Meta’s plans to replace workers with AI fell flat, report says – Computerworld– www.computerworld.com
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Earlier this year, Meta, one of the industry’s loudest AI advocates, was ready to slash up to 60% of the members of some teams and replace them with AI, as part of what it called Project OT (Organization Transformation), an initiative to make Meta “AI native.”

But it backed off at the last minute after internal data showed that the plan wasn’t working out, according to a Reuters investigation published Wednesday. For example, Reuters said, code changes made to the internal software platforms and infrastructure that employees used on the job were up 220% year-over-year, according to an early June post by Meta CTO Andrew Bosworth, yet changes that led to new or upgraded features reaching Meta users were only up 36%.

Meta executives also saw “’reliability warning signs’ caused by the AI coding surge,” according to an internal post, Reuters reported. “Another post, in April, said that unchecked AI agents were performing ‘large-scale, disruptive actions that humans are unlikely to execute.’ The result: Major technical and security incidents, such as service disruptions and possible data leaks, spiked 40% from the previous year, with the time staffers had to spend firefighting them up 70%.”

 

American scientists are building a $12 million ‘digital brain’ for drones based on how insects make decisions with limited information |– timesofindia.indiatimes.com
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A $12 million research project at Penn State is trying to give drones a new way of making decisions, drawing inspiration from the small brains of insects and other animals. Funded by the US Army’s Army Research Laboratory, the project aims to develop an onboard sensing system that can pick out useful information without sending large amounts of data to external computers. The team, led by Saptarshi Das, is studying how animals such as locusts and owls filter sensory information despite having tiny brains. Their proposed system would use analogue computing, graphene-based components and memristors to process signals while using less power. A cochlea-inspired structure would help filter information before it reaches conventional digital processing. The researchers also plan circuits that mimic coincidence-detecting neurons, allowing drones to respond to combinations of signals rather than processing everything they encounter. Annual demonstrations will gradually move from individual prototypes towards larger drone swarms.

SpaceXAI Unveils Grok Bot To Work Like A Team Of AI Agents– www.ndtv.com
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SpaceXAI is rolling out new artificial intelligence software that’s designed to act like a team of AI agents fielding assignments throughout the day, marking the latest bid by Elon Musk’s company to keep pace with Anthropic PBC and OpenAI.

The new product, called Grok Bot, is designed to seamlessly handle a wide range of professional work. The tool can sign into various apps and websites, retain information from prior tasks and enable bots to share details and context with each other, the company said Tuesday.

The product is part of Musk’s broader push to catch up in the AI race after slipping behind in the fast-growing market for AI agents. SpaceXAI, as Musk’s AI outfit is now known, released its first coding agent in May to compete with Anthropic’s offerings, followed by the new Grok 4.5 built with Cursor.

SpaceX reached a $60 billion agreement in June to acquire Cursor, an AI coding startup. Cursor emerged as a key player in tech’s so-called vibe coding era, as demand surged for tools that can write and debug software programming.

Anthropic to watermark AI-generated content – Computerworld– www.computerworld.com
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Anthropic will begin labeling AI-generated content created by Claude, Claude Code, and the company’s API, as well as Claude models via third-party services, according to The Register.

Text generated by future Claude models will be given an invisible watermark. According to Anthropic, the watermark is embedded directly into the generated text without affecting its meaning or readability. For files, Anthropic will instead use signed metadata in accordance with the C2PA standard.

The effort is part of the company’s plan to comply with the EU’s AI Regulation and transparency requirements regarding AI-generated material. However, the labeling will be implemented globally for all users.

 

DeepMind Says Its AI Can Predict Hurricanes Earlier Than Everyone Else– www.wired.com
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In October 2025, a storm brewed over the Caribbean Sea. Weather models differed on its trajectory. Would it remain weak and end up in Haiti, or would it intensify and head to Jamaica? Artificial intelligence model WeatherNext, developed by Google’s DeepMind and Google Research, went with the latter. Five days before landfall, it predicted with 80 percent confidence that the storm system would hit Jamaica as a Category 5 hurricane.

Hurricane Melissa was catastrophic, causing flooding and landslides across Jamaica. But the AI model helped forecasters give an earlier warning to communities in its path, so they could better prepare.

In a paper published on Thursday in Nature, researchers show the WeatherNext AI model can predict cyclones with unprecedented accuracy. On average, it gives forecasters a day more lead time than existing models; this means its predictions three days out are as accurate as previous models’ predictions two days out. On the ground, that extra day can mean a lot.

“Even a few hours can make a difference,” says Mike Brennan, director of the US National Hurricane Center. Organizing evacuations, staging supplies, and moving resources to respond to a hurricane risk are all time-sensitive tasks—and making the wrong decision can have big consequences. “Time is really golden when it comes to those types of decisions, so the ability to push forecast accuracy out as much as a day beyond what we’ve previously been able to do is really valuable,” he says.

Historically, bringing forecasts forward by a day would take a decade of work, the researchers say.

Google abruptly cancels its unreleased AI Studio mobile app– www.androidauthority.com
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TL;DR

  • Google has already canceled the standalone AI Studio mobile app before it ever launched.
  • The company says it will now bring AI-powered app creation directly into the Gemini app.
  • Meanwhile, the AI Studio web experience will continue to grow and evolve.

In a post on X, the official Google AI Studio account said the company has decided to cancel the standalone mobile app, despite around 800,000 users pre-ordering it across Android and iOS.

The company said that, instead of asking users to install “yet another app,” it will bring AI Studio’s core capabilities directly into the Gemini app.

Google says it’s partnering with the Gemini app team to make this vision a reality across both mobile and desktop.

New chapter in reading: AI companion tools let readers chat with books– timesofindia.indiatimes.com
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Mid-listen, you can tap a button, ask your question, hear the answer, and then pick up the story right where you left off

NEW YORK: Imagine a world where you could ask a book a question as you read it. That’s the pitch from a wave of new AI tools letting readers do exactly that. “You are dealing with a book as if it is a living object – it’s totally different,” says Ahmed Kamel, CEO of Sinai.ai, a platform now in testing.With these tools, users get access to an e-book or audiobook alongside an AI chatbot. Confused about a character’s motives or the historical setting? Just ask. Readers can dig into a character’s psychology, historical context, or a philosophical concept — no separate research required.French startup My Smart Book launched something similar in mid-April. Like Sinai, its chatbot draws only on the actual text of the book – no outside information.

AI Capability Races Ahead of the Business Payoff | American Enterprise Institute– www.aei.org
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The state of the AI revolution can be confusing. At times, it can seem as if the latest artificial intelligence models are showing huge capability increases. One example is when two OpenAI models broke out of the lab, accessed the internet, and broke into another AI company. Or, as a Wall Street Journal headline put it, “The Day the Bots Broke Loose.”

But then you might come across another headline from the Wall Street Journal: “Big Companies Are Starting to Hire Again, Defying Predictions of AI Wipeout.” And from that piece:

The push to expand head count, at least modestly, is a reversal from the prevailing corporate messaging during much of the AI era. Major employers largely held back on adding people due to economic uncertainties or a belief that artificial intelligence could shoulder more tasks on the job. But some executives say the costs and limitations of AI now demand that more people be added; others want to hire people back following layoffs.

A surge in hidden debt among AI giants like Oracle and Meta is setting off alarms in the industry. The hidden debt comes from future payment operations for expenses not yet online to make money. For instance, leases and property taxes must be paid on sites that are earmarked for databases that haven’t been built or completely built yet. The hidden debt amounts to more than $1.65 trillion.

The AI Illusion: Big Tech’s ‘Invisible Debt’ Surges To $1.65 Trillion On Opaque Funding – NDTV Profit– news.google.com
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The hidden $1.65 trillion stems from future payment obligations-such as long-term operating leases for data centers not yet built, bulk GPU supply contracts, and joint ventures. Under current accounting standards, companies are not required to record these obligations as liabilities on their balance sheets until the assets are delivered or the facilities go live.

Instead, these financial commitments are buried in the small-print footnotes of their financial statements. While perfectly legal, this practice effectively obscures the true financial leverage of the companies. By shifting costs to future periods, tech giants can maintain balance sheets and inflate current profit figures, all while locking themselves into hundreds of billions of dollars in future payouts.

While all five giants are utilizing these financial structures, the report reveals that the scale of hidden debt at Meta and Oracle is particularly striking:

Meta: The social media giant’s off-balance-sheet debt has reached an estimated $420 billion, nearly three times its officially recorded debt. A significant driver is its joint venture with Blue Owl Capital to build a massive data center in Louisiana, a project whose expected investment recently ballooned from $27 billion to over $50 billion.

Oracle: The company’s hidden debt has surged more than 30-fold in four years, reaching $273.3 billion. Much of this is tied to concentrated, single-counterparty exposure, such as its massive “Stargate” supercomputer data center project with OpenAI.

Meanwhile, Alphabet, Amazon, and Microsoft have collectively disclosed backlogs of roughly $1.45 trillion for cloud services and related business commitments as of March, according to the report.

 

AI can become more biased than humans while choosing who gets hired; study finds |– timesofindia.indiatimes.com
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Artificial intelligence is increasingly being trusted to help employers screen CVs, rank candidates and even conduct early-stage interviews. The promise is simple: AI can process thousands of applications quickly, reduce administrative workloads and, in theory, make hiring decisions more objective than humans. According to a recent review by MIT Technology, based on the 2024 study published in the Journal of Experimental Psychology titled “Costly Exploration Produces Stereotypes With Dimensions of Warmth and Competence”, large language models (LLMs) may not only inherit human biases from the data they are trained on but also develop entirely new stereotypes based on their own experiences. Rather than simply reflecting existing prejudice, these systems can create fresh patterns of discrimination as they attempt to optimise decision-making over time.The findings are particularly significant because businesses are rapidly integrating AI into recruitment. If these systems begin making assumptions about groups of applicants after only a handful of hiring decisions, they could gradually reinforce unfair employment practices without any explicit human instruction.The research, conducted by scientists at Princeton University and the University of Chicago, builds on earlier psychological work showing how stereotypes can emerge from repeated decision-making. It suggests that the same learning strategies that make AI effective at solving complex problems can also make it unusually prone to stereotyping job candidates.

U.S. pledges $5 billion to boost AI in government-backed scientific research– www.scientificamerican.com
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Overall federal funding for scientific research is set to decline in 2027, the most senior White House science figure said on Wednesday. The government, however, pledged to spend $5 billion on promoting artificial intelligence in science.

Michael Kratsios, the White House’s science and technology adviser, told the House Committee on Science, Space, and Technology that the money will be drawn from the National Science Foundation (NSF) and NASA, as well as other federal agencies.

The goal is to produce “the premier AI for science ecosystem in the world,” he said. The funding will be earmarked for “research awards, funding opportunities, specialized scientific datasets and research facilities,” the White House said in a statement.

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A coalition of current and former Meta employees have sued the social media giant, alleging that the company used artificial intelligence in its latest round of layoffs in a way that was discriminatory.

In a lawsuit filed Monday, plaintiffs allege that Meta violated various protected-leave laws and discrimination acts related to pregnancies and disabilities, among others, and said they wish to pursue their claims individually in arbitration.

Attorneys representing the 26 unnamed workers said in a legal complaint filed in the United States Northern District Court of California that the plaintiffs were among the 10% of Meta’s workforce cut in the company’s May layoff round.

The plaintiffs allege that Meta’s “constellation of internal artificial-intelligence systems” failed to take approved absences into account when determining which employees to cut.

“Those tools draw on inputs—performance ratings, calibration scores, productivity and output metrics, ‘AI-native’ ratings, and AI-token consumption—that, by design, cannot be accumulated by an employee who is on protected medical or family leave, or whose output is reduced by a disability,” the lawyers wrote in the filing.