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Austrian Physics AI Startup Purchased by Mistral AI in an Industrial Push

Austrian Physics AI Startup

Europe’s push to strengthen its artificial intelligence ecosystem received a major boost after French AI company Mistral AI announced the acquisition of Austrian startup Emmi AI in a move aimed at expanding advanced AI solutions for manufacturers and engineering firms across the continent.

The deal, whose financial terms were not disclosed, positions Mistral to deepen its presence in industrial artificial intelligence — an area increasingly viewed as critical to Europe’s competitiveness as governments and businesses seek to modernise manufacturing while reducing dependence on foreign technologies.

The acquisition also highlights growing momentum behind Europe’s ambition to build homegrown AI capabilities that can rival U.S. and Chinese firms in strategic sectors.

Mistral Targets Europe’s Industrial Sector

Founded as one of Europe’s most prominent AI startups, Mistral has rapidly emerged as a key player in the continent’s technology landscape by developing large language models and enterprise AI solutions.

With the purchase of Emmi AI, the company is moving beyond traditional generative AI applications into industrial simulation and engineering intelligence.

Linz-based Emmi AI specialises in physics-driven AI models capable of analysing and simulating highly complex industrial processes, including airflow dynamics, heat transfer systems, structural stress behaviour and material interactions.

These capabilities are particularly valuable in industries where precision engineering and real-time optimisation are essential.

Mistral said integrating Emmi’s technology would allow its AI systems to better understand and interact with physical environments, improving performance in manufacturing operations and industrial automation.

The move aligns with the company’s strategy of delivering customised AI systems designed around specific business needs rather than relying solely on general-purpose models.

Industrial AI Gains Strategic Importance in Europe

The acquisition comes as industrial artificial intelligence becomes increasingly central to Europe’s re-industrialisation efforts.

European policymakers have intensified efforts to strengthen domestic technological capabilities amid concerns about reliance on foreign AI infrastructure and software providers.

Last year, the European Commission identified manufacturing as one of the bloc’s critical AI sectors, emphasizing the need to accelerate digital transformation across factories, supply chains and engineering systems.

Industrial AI applications are now expanding rapidly across automotive production, aerospace development, semiconductor manufacturing and energy management.

Unlike consumer AI tools focused on chatbots or content generation, industrial AI operates directly within production environments.

These systems can monitor machinery, predict equipment failures, optimise energy usage, identify defects and coordinate robotics in real time.

For Europe, where manufacturing remains a cornerstone of economic strength, AI integration is increasingly viewed as essential to maintaining global competitiveness.

Building Smarter Manufacturing Systems

Mistral explained that its industrial approach often involves deploying multiple AI systems working together simultaneously.

For example, one model may inspect products for manufacturing defects using computer vision, another may guide robotic equipment, while separate systems analyse logistics data or monitor operational efficiency.

These tools operate as interconnected systems rather than isolated applications.

The addition of Emmi AI’s simulation expertise is expected to improve how these systems interact with real-world industrial processes.

By understanding physical forces such as pressure changes, temperature variations or structural stress, AI platforms can make more accurate operational decisions.

This could significantly improve predictive maintenance, reduce waste and minimise costly production interruptions.

Industry analysts note that combining generative AI with physics-based simulation may become one of the next major developments in industrial automation.

ASML Case Highlights Potential Impact

Mistral pointed to its collaboration with semiconductor equipment giant ASML as an example of how industrial AI can deliver measurable results.

According to the company, AI-powered vision systems integrated into ASML’s advanced EUV lithography equipment are now able to identify engraving defects during semiconductor manufacturing much faster than traditional inspection methods.

The technology reportedly reduced diagnostic processes from several hours to approximately eight minutes.

For semiconductor facilities operating highly expensive equipment and processing valuable silicon wafers, reducing downtime can generate substantial savings.

ASML executives have previously highlighted the operational benefits of AI-assisted diagnostics in improving efficiency and protecting production output.

The example illustrates why manufacturers are increasingly investing in specialised AI systems rather than generic tools.

Europe’s Manufacturing Heritage Seen as Competitive Advantage

Mistral believes Europe’s long-standing industrial expertise gives the region a unique edge in the industrial AI race.

The company argues that purpose-built AI systems trained on company-specific datasets can outperform general AI models trained on broad internet data.

Manufacturers often operate under highly specialised conditions that require tailored solutions.

A factory producing automotive components, for instance, faces entirely different operational challenges than a semiconductor facility or aerospace plant.

Mistral’s customer list already reflects this industrial focus, including automaker Stellantis, environmental services firm Veolia and defence technology manufacturer Helsing.

By strengthening simulation capabilities through Emmi AI, the company aims to expand deeper into sectors requiring advanced engineering intelligence.

Positioning for Europe’s AI Future

Mistral CEO Arthur Mensch said the acquisition is expected to reinforce the company’s role as a strategic partner for manufacturers operating in aerospace, automotive and semiconductor industries.

The move also reflects broader trends across Europe, where governments and businesses are increasingly investing in domestic AI ecosystems to support economic resilience and technological independence.

As global competition in artificial intelligence intensifies, industrial applications may become one of Europe’s strongest opportunities to establish leadership.

By combining advanced language models with engineering-focused simulation technology, Mistral is betting that the future of AI will extend far beyond digital assistants and into the factories, laboratories and production lines driving Europe’s economy.

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Tech

Meta’s Muse AI Agent Promises Help, but Experts Warn of Online Chaos

By George Mensah 8 min read

Meta’s new AI agent, Muse, can cancel a gym membership, haggle with customer service, buy groceries and invite friends to a party. It asks for total control of your Gmail, your calendar and, on a Mac, your whole computer. A BBC reporter who tested the app for a week revoked its access and asked it to erase what it had collected, and the researchers interviewed say the problems reach well beyond one person’s inbox.

Muse is an AI agent, a tool that goes out into the world to complete tasks without supervision. It uses its own web browser, and Meta says phone calls are coming. It is the first free, full-featured agent from a big company. Millions of people downloaded it in its first weeks, and OpenAI has since announced an agent of its own. More are expected.

The experts interviewed for the BBC’s report expect the internet to get more frustrating as agents spread, with bots competing for tickets and appointments, small businesses swamped by automated requests and some agents working against their own users.

An agent that asks for everything

A cartoon avatar asks for your name. Then it asks for access to Gmail, the calendar and, on a Mac, the entire machine. Muse arguably asks for more trust and sensitive information than any product Meta has made.

Patrick Wardle, co-founder of Objective-See, a US nonprofit security foundation, uncovered serious flaws in the app. His advice is blunt. “I wouldn’t use it,” he said. “Personally, I would tell you to uninstall it altogether.”

The reporter tested it anyway, named the agent “Bob” and handed over access to their accounts.

Meta defends the product. “Muse is the first personal AI agent built for everyone and designed to be safe, secure and private – with built-in protections and user controls that put people in charge of how they use it,” a Meta spokesperson said. “Safety and security is a huge priority for us,” the spokesperson added, and said Muse went through extensive testing.

The ticket problem scales up

Experts expect the problems to look like the ones scalpers already cause. In 2024, some American fans of Taylor Swift flew to Europe to see her because resellers had pushed US ticket prices so high that a flight to an international concert cost less. Scalpers buy tickets to resell at a mark-up.

An agent gives anyone the same tool. Calli Schroeder, director of the AI and Human Rights Program at the Electronic Privacy Information Center (Epic), expects a sharp rise in bot activity. “There’s going to be a huge escalation of the problems we’re already having with bots,” she said.

The effects reach ordinary errands. Reservations at a hot new restaurant could become close to impossible to get. Appointments for passport or driver’s licence renewals in peak travel season could vanish too. Some people will probably hoard slots, booking five appointments just in case, since an agent makes that effortless.

Solutions exist. Society could drop “first come first served” and move to lotteries for scarce slots. That would change how much of daily life works. Schroeder sees little preparation. “I haven’t seen a lot of plans to address these things,” she said. “We’re just launching these tools and saying, ‘well, we’ll deal with the problems when they come up’.”

Meta says Muse asks permission before buying anything. According to the company, it is built to behave like a “reasonable, honest person”, one who would not buy every ticket to an event or refresh a page 500 times an hour.

Websites under strain

The reporter found Muse useful. Over a week, it messaged a seller on Facebook Marketplace with questions, ordered the reporter’s preferred dental floss and negotiated a $31 (£23) discount on a software subscription.

Now picture millions of agents doing this at once, on tasks that might take a person weeks. Schroeder asked what that does to the sites on the receiving end. “What happens if bots send 600 inquiries to a website a day, when normal humans might only send two?” she said. By our arithmetic, that is 300 times the normal load from a single visitor. “Businesses and individuals are going to have a lot to deal with.”

Web businesses already face pressure. Google and chatbots now answer many questions directly, so people visit fewer websites. Robots do not click ads or buy subscriptions, and the income those visits once produced is shrinking. Agents are expected to deepen the problem.

One analysis found that web traffic from bots rose 124% in the year to June 2026. Some websites and services are struggling because they were not built for that load.

Meta’s spokesperson said Muse completes tasks while respecting the interests of websites.

Whose side is the agent on?

Personal risks sit alongside the public ones. “If you’re empowering an agent to make things like purchasing decisions, or choices about taste and preferences, you’re opening yourself up to being exploited,” Schroeder said.

She gave examples. If Muse plans a holiday, a user has no way to check whether it found the best deal or picked flights and hotels that benefit Meta’s business partners. If it recommends music, the user cannot tell whether the picks come from their taste or from artists who signed deals with Meta.

Meta says Muse’s protections and user controls put people “absolutely in charge”, and that Muse “behaves like a personal assistant acting for a single person” and follows ethical guidelines meant to protect users. Schroeder has read the terms of service. She said they contain no guarantee that the app will act in the user’s favour.

Proposals for new rules

Ramesh Raskar, an associate professor at the Massachusetts Institute of Technology who studies AI agents, uses a driving comparison for the current situation. “Imagine there are no rules of the road. And you release billions of cars – the AI agents – and you just let them drive through playgrounds, hitting kids. That’s where we are,” he said.

Raskar is among the researchers designing an internet that works for agents, businesses and people alike. He argues that regulators need an approach built for agents. “Think about the models like an engine. The agents are the cars, and that’s what we need to regulate,” he said. “We need to establish the rules of the road: windshields, brakes, traffic lights and so on.”

The AI industry is developing protocols and standards that let bots connect directly to other services in a cooperative way. Some companies are building systems that would charge AIs a fee to scrape websites. Regulation could require agents to serve their users’ best interests.

There are early examples. A few restaurant reservation platforms have banned people for AI misuse. The UK has rewritten the rules for booking driving tests, in part to combat bots.

Raskar remains optimistic. “Agents could unlock so much investment, innovation and value,” he said, as long as the new rules do not hand any company an unfair advantage. In the meantime, people who use agents pay with personal data.

What Muse holds, and what Meta promises

The reporter has used the same Gmail address for 21 years. It is the login for hundreds of accounts. It holds medical test results, contracts, legal documents, family conversations, receipts and financial information. It also holds love letters from an ex-girlfriend, who gave permission before the account was connected. Muse also suggested connecting bank accounts. The reporter declined and did not let the agent loose on the hard drive.

Meta makes explicit privacy promises. The company says it will not connect any data Muse collects to its advertising systems. Special systems are meant to keep the AI from seeing passwords or payment methods. When a user connects Gmail, the agent asks whether it should scan the whole inbox or read only messages related to specific tasks.

There is a catch, according to Schroeder. By default, Meta uses Muse data to train new AI models. She said data built into a model cannot be removed, and that AIs can sometimes be tricked into revealing training data. Meta says it “sanitises” data to strip out personally identifiable information before training, and that users can opt out with a setting.

Wardle does not take those assurances at face value. Soon after launch he found a critical vulnerability. “This was literally 20 minutes of me poking at the app, and it just, like, fell over,” he said. With a simple hack, he said, an attacker could have taken over Muse and all of its data, and even controlled other connected devices such as a phone or a smart lock.

Meta fixed the flaw immediately. Wardle says the oversight still leaves him unable to trust the company’s privacy and safety claims. “These bugs were trivial to discover,” he said. “If they were willing to ship something that’s security was not well vetted, it doesn’t give me a warm fuzzy about their intentions.”

A Meta spokesperson disputes that view and said Muse was delayed for months for further privacy and security testing.

The tester’s decision

The reporter spent a lot of time with Bob and found the agent useful and enjoyable. After finishing the article, the reporter revoked Muse’s Gmail access and asked the app to erase everything it had collected.

The reporter’s reason was simple: “In the end, the fear won out.”

Sources: BBC News reporting on Meta’s Muse AI agent; comments from Patrick Wardle (Objective-See), Calli Schroeder (Electronic Privacy Information Center), Ramesh Raskar (MIT); statements from a Meta spokesperson.

Tech

Trump Renames AI “Super Intelligence” in Executive Order as Calls for Regulation Grow

By George Mensah 4 min read

President Donald Trump signed an executive order on Tuesday, Sept. 29, 2026, that renames artificial intelligence “super intelligence” across the federal government. The White House says the new term better describes what the technology can do. The order lands as critics press Washington for stricter limits on how fast AI develops.

What the order says

The executive order argues that current systems do “much more than imitate or automate discrete aspects of human intelligence.” It goes further in its central passage. “As these capabilities continue to improve, they increasingly represent not merely artificial intelligence, but a new era of Super Intelligence,” the text reads.

It adds that federal terminology “should reflect the transformative capabilities of these technologies and the limitless opportunities they create for the American people.”

Trump spoke to reporters after signing. “It’s not artificial, we all agree on that,” he said.

What agencies must do now

Every federal agency has to use the new term, or its short form “SI,” when it talks about the technology in public. That covers public communications, websites, reports and policy documents. If your local agency publishes an AI guidance page, expect it to change.

The order also gives Michael Kratsios, director of the Office of Science and Technology Policy, a defining role. He will decide whether the official definition of “super intelligence” should be modified or expanded. The order does not set a deadline for that decision.

A term that already means something else

The rename creates a vocabulary problem. In the AI field, super intelligence already refers to a specific kind of system, one that exceeds human cognitive ability in virtually every area of thinking. Nobody has built one. Researchers treat it as a future possibility, and much of the safety debate centers on it.

Under the order, federal documents will apply that label to chatbots, coding assistants and image generators that exist today. A reader who sees “SI” in a government report may assume the government is describing something far more advanced than what companies actually sell. Kratsios’s authority to modify the definition could narrow that gap, or it could widen it.

Timing and the push against regulation

The order follows a week of similar messaging. Trump began using the term at the U.N. General Assembly last week, where he pushed back on calls for tighter rules on the industry. He told world leaders that tech executives would build the right guardrails into their own models.

Concerns have grown since then. Worries about AI replacing workers keep rising. Recent reporting has also described rogue agents linked to a security breach involving Australia’s prime minister, and AI agents that accessed U.S. government websites. Some systems have also been used to start cyberattacks.

Trump has repeatedly called whistleblower warnings about weak oversight overblown and a “hoax.” He has said he will not slow AI growth. In his view, keeping American dominance in the technology is a national security matter.

The industry’s own safeguard

On the same day, tech executives signed a “morally binding” constitution on AI at the White House. Its terms ask companies to hire an independent external auditor. The auditor would check that models are “operating as intended.”

The document also asks companies to set up internal controls meant to stop models from hacking systems. A team would monitor those controls. That team would answer to an independent committee of the company’s board.

The wording matters here. “Morally binding” describes an obligation companies accept by choice. The reporting on the document does not describe fines, penalties or a government body that could enforce it. Whether outside auditors get real access to model internals, and what happens if one finds a problem, are open questions.

What the two actions have in common

The order and the constitution came out the same day, and they share a theme. Both keep the government’s role limited. The order changes what officials call the technology. The constitution leaves safety checks largely in company hands.

Supporters of that approach say it keeps American firms moving fast against foreign competitors. They argue that rigid rules written now could be out of date within a year. Critics say voluntary pledges have a weak record in other industries, and that a stronger name for the technology may make the public less cautious about it.

Neither side has settled the argument. What is clear is the direction of policy. The administration is choosing branding and industry commitments over new binding rules, at a moment when the documented incidents involving AI agents are piling up.

What happens next

Three things are worth watching over the coming weeks.

  • Kratsios’s definition. Any change to the official meaning of “super intelligence” will show how the administration wants the term understood.
  • Agency compliance. Federal sites and reports should begin switching to “SI” now that the order requires it.
  • The auditor provision. The industry constitution only matters if independent auditors are named, given access and allowed to publish what they find.

Congress has not yet responded to the order, and no agency has published a compliance timeline. Until Kratsios acts on the definition, “super intelligence” will mean one thing to researchers and something looser in federal paperwork.

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