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TSMC ups US investment on AI mega-trend

TSMC raised its investment budget in the US by a further $100 billion, driven by strong demand for AI technology through to 2030.

In an announcement tied to its quarterly results, the Taiwanese chipmaker revealed it would spend the sum in the US state of Arizona, adding to an investment of $165 billion which it has already committed.

TSMC has pledged to build eight manufacturing sites in Arizona, and with the additional investment, could now set up another four focused on manufacturing advanced 2nm chips, in addition to facilities for advanced packaging.

CEO CC Wei stated its raised outlook was based on demand mainly from cloud service providers, which provide a “strong signal and positive outlook”.

“Thus, our conviction in the multi-year AI mega-trend remains very high.”

He added the investment “will help further foster the development of the US semiconductor ecosystem, strengthen the supply chain and support an increasing number of high-tech, high-paying jobs” in the country.

In Q2 2026 the company reported a year-on-year revenue increase of 36% to TWD1.3 trillion ($40.4 billion), with net income increasing 77% to TWD706.6 billion.

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Thinking Machines releases first AI model

Thinking Machines Lab unveiled its first AI model more than a year after former OpenAI executive Mira Murati (pictured) founded the start-up, moving it from research previews to a full launch.

The Inkling model is designed to reason natively across text, images and audio, while balancing cost against performance through variable, adjustable effort.

Thinking Machines stated the model is trained to exhibit safe behaviour across all modalities.

The company noted Inkling is a mixture-of-experts transformer with 975 billion total parameters and 41 billion active parameters, supporting a context window of up to 1 million tokens.

Thinking Machines described it as the first in a family of models of varying sizes.

Rather than chasing state-of-the-art performance in a single domain, Thinking Machines said it trained Inkling for solid capabilities across agentic tasks, reasoning, coding, instruction-following, factuality, vision and audio, positioning it as a foundation model for future releases.

The company acknowledged Inkling is not the most performant model available today, closed or open.

Inkling is open-weight, meaning developers can download and customise the model without access to training data or source code.

It is available for fine-tuning on Tinker, Thinking Machines’ developer platform, alongside a so-called Inkling Playground for testing the model directly.

Bloomberg reported Thinking Machines is not aiming to monetise the model itself; the company currently generates revenue through Tinker, which it sells to customers including hedge fund Bridgewater Associates for financial-task fine-tuning.

The news outlet noted Murati’s company raised $2 billion at a $12 billion valuation last year and was reportedly in talks over a larger subsequent round, though it added several employees have since departed for firms including Meta Platforms and OpenAI.

Bloomberg also reported the launch could help fill a gap in the US open model market, as Meta shifts focus on proprietary offerings and rising AI spending pushes some users toward freely available Chinese models.

Thinking Machines was founded in early 2025 by Murati and a host of other former OpenAI employees, with the company initially focused on collaboration between the technology and people.

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Anthropic plans investor meetings as IPO looms

Anthropic is reportedly seeking to meet with investors ahead of a potential mega-IPO, as the company prepares to join a wave of AI-driven stock market debuts.

Bloomberg reported the banks leading the offering are scheduling meetings between investors and the Claude chatbot maker in the coming weeks, citing people familiar with the matter. The news outlet previously stated Anthropic is considering an IPO as soon as October.

Deliberations remain ongoing and details including timing could still change, Bloomberg stated.

Moving ahead on the timeline would put Anthropic ahead of rival OpenAI, which is now eyeing a debut in 2027 after earlier targeting 2026.

The news site noted an IPO in October would also see Anthropic list before DeepSeek, the Chinese AI company which has been steadily gaining market share.

DeepSeek is reportedly preparing its own IPO and could file this year.

Bloomberg stated Anthropic is working with Morgan Stanley, Goldman Sachs and JPMorgan Chase on its IPO.

The AI player is also navigating uncertainty tied to its relationship with the Trump administration, which briefly imposed foreign access restrictions on two of Anthropic’s top models.

Anthropic separately sued the US Department of War after it declared the company posed a risk to the nation’s supply chain.

The company was valued at $965 billion following a funding round in May, making it one of the world’s largest private companies and pushing its valuation past OpenAI’s for the first time.

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Ingram Micro avança para a versão 2.0 da empresa com aposta reforçada em Portugal

A reorganização da operação da Ingram Micro em Portugal já está em marcha e Jaime Soler descreve as mudanças como uma evolução que traz benefícios aos clientes no mercado português.

The post Ingram Micro avança para a versão 2.0 da empresa com aposta reforçada em Portugal appeared first on Tek Notícias.

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Trump sets up AI threat coordination group

The US government launched a cybersecurity coordination group allowing AI developers and service providers a formal way to work together to respond to threats emerging from the technology.

The White House stated it, along with the Department of the Treasury, Homeland Security, Department of War and the Cybersecurity and Infrastructure Security Agency worked closely with industry partners to detect threats faster and develop a rapid and prioritised response to cyber vulnerabilities across critical infrastructure sectors.

The group, called Gold Eagle, has been spearheaded by President Donald Trump as part of his vision to secure and accelerate American AI innovation.

It was first revealed as part of Trump’s executive order in June to promote advanced AI innovation and security, which includes plans for the release of a new operational model for cyber defence.

The model aims to tap into frontier AI capabilities to continue advancing faster than adversaries, reduce duplicative scanning efforts and “deliver prioritised and actionable threat and remediation information to defenders” across the government and private sector.

The White House statement explained Gold Eagle will help government and industry collectively identify risks, prioritise action and strengthen the resilience of systems that power the economy, national security and daily life.

Companies involved in the coordination group were not disclosed.

Trump’s administration has taken a hands-on approach to AI regulation.

In May it unveiled a legislative framework to create uniform security and safety guardrails. This followed another executive order at the end of 2025 to secure control of AI regulation away from individual states.

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OpenAI plots AI speaker launch in hardware push

OpenAI is reportedly preparing to enter the consumer hardware market with a portable, screen-free smart speaker designed to serve as an AI companion in the home.

Sources told Bloomberg the device will access ChatGPT’s AI capabilities to control smart home appliances, play media, answer questions and respond to messages. It will utilise OpenAI’s GPT-Live voice technology to listen and adaptively respond at the same time to support more natural conversations and incorporate AI models beyond those used in existing smart speakers.

In addition, the hardware will apparently feature a camera and sensors to enable the AI to read its surroundings. Unlike conventional smart speakers, the rechargeable device will be portable and feature moving mechanical elements.

It will also draw on user data such as emails to become increasingly personalised over time. OpenAI envisions the speaker developing a humanlike personality, proactively surfacing information, anticipating users’ needs and acting as a physical embodiment of ChatGPT.

OpenAI’s hardware unit is reportedly developing around five products in total, with the speaker set to be the first to market.

Last year, the company splashed $6.5 billion to acquire io Products, the device startup co-founded by former Apple design chief Jony Ive. Ive’s creative design studio LoveFrom is also working on the hardware line.

A hardware launch would put the ChatGPT-maker in direct competition with Apple, Amazon and Google in consumer devices.

Trade secrets
Last week, Apple filed a lawsuit against OpenAI and io Products, alleging “theft of trade secrets” obtained through former employees during hiring to accelerate the development of its AI devices. According to its lawsuit, more than 400 former Apple employees have joined OpenAI’s hardware effort.

Drew Pusateri, a spokesman for OpenAI, told the BBC OpenAI has “no interest in other companies’ trade secrets” and is “focused on building innovative technology that empowers people everywhere”.

Apple is seeking an injunction that could delay the AI giant’s device sales. According to Bloomberg, OpenAI is aiming to unveil the speaker later this year, with release targeted for 2027, subject to the lawsuit.

Meanwhile, Apple is reportedly developing its own AI-focused home devices including a smart home hub with a 7-inch display and facial recognition tied to the upcoming AI-powered Siri revamp in iOS 27.

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DeepMind CEO seeks US standards body for frontier AI

Google DeepMind CEO Demis Hassabis called for the establishment of a new US-led regulatory framework to govern frontier AI, proposing a self-regulatory structure which could bypass political opposition.

In a post on X, Hassabis warned the breakneck pace of commercial and geopolitical competition is currently outstripping the industry’s understanding of the technology.

He noted the arrival of Artificial General Intelligence (AGI) is likely only a few short years away.

To address looming technical, biological, and cybersecurity risks without stifling innovation, Hassabis proposed creating a new US standards body.

He modelled it after a self-regulatory organisation like the Financial Industry Regulatory Authority (FINRA), rather than a traditional government agency.

The structural choice comes amid heavy resistance to AI regulation from the tech industry and shifting policies from the Trump administration.

The FINRA-style blueprint would be staffed by leading technical experts and open-source representatives but primarily funded by the industry to secure the massive compute resources needed for testing.

TechCrunch reported the proposed system would replace the current, highly criticised ad hoc government reviews previously used for models like Anthropic’s Mythos and OpenAI’s Sol.

Those reviews drew fire from industry onlookers for a distinct lack of technical expertise and opaque decision-making, according to the news outlet.

Under Hassabis’s framework, the independent body would define thresholds to classify models as Frontier-Class. Organisations behind them, dubbed Frontier Labs, would eventually be required to pass the independent assessments to deploy in the US market.

Hassabis stated assessments would check for advanced threats, deception, and guardrail bypass attempts. The standards body could also outsource specific evaluations to a growing ecosystem of independent, third-party AI safety groups.

He argued the approach is designed to keep up with AI’s acceleration, allowing the industry to safely steer toward an era of scientific abundance while addressing the Trump administration’s concern over state-mandated red tape.

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New York puts mega data centres on ice

New York made history by becoming the first US state to halt the construction of massive new data centres, imposing a one-year moratorium as concerns escalate over the environmental and financial toll of the AI boom.

The moratorium, outlined in an executive order signed by Governor Kathy Hochul (pictured), targets hyperscale operations by halting discretionary environmental permits for new facilities requiring 50 megawatts or more of power.

The rapid expansion of facilities housing thousands of computer servers has triggered intense community and political backlash across the US.

“This pause will remain in place for up to one year while New York establishes the strongest possible framework to protect our community’s guardrails to reduce the risk to our energy grid, minimize land disruption, noise pollution, and protect our natural resources, especially our water supply,” Hochul stated during a press conference. “We’re going to explore having hyperscale data centres pay into a larger fund to support our grid statewide.

“We need to invest in this, help defray costs, reduce bills for our rate payers,” she added. “We expect this process, which we already launched, to be completed within the year.

Once the policy is in place, the freeze will be reviewed and lifted, Hochul stated.

She also said the data centres should only be built in areas which want them and “they will never be exempt from local zoning, local approvals”.

Local populations are increasingly concerned the energy-hungry centres by companies including Alphabet, Microsoft, Meta, Amazon, and Oracle are inflating residential utility bills, straining electricity grids and consuming millions of gallons of water for cooling.

Hochul framed the aggressive intervention as a necessary protective measure for state residents, stating as data centre development threatens to hike utility bills and deplete natural resources, it is her responsibility to act.

She noted labour organisations will have a seat at the AI data centre discussions “so projects can include wage standards and labour agreements and prioritise local hiring”.

To further rein in the sector, Hochul announced plans to pursue legislation to repeal lucrative sales tax exemptions currently enjoyed by hyperscale data centre operators.

“New Yorkers work hard and, on my watch, their tax dollars will not be used to benefit these large firms, these centres.”

Reuters reported Hochul directed state officials to develop a Generic Environmental Impact Statement. The comprehensive assessment will establish consistent operating and environmental standards for new facilities while examining the overall footprint of data centre construction and operation across the state.

The construction ban will be lifted once the rigorous regulatory guidelines are finalised.

The news outlet reported state lawmakers recently passed a bill targeting data centres consuming 20 megawatts or more of power, representing a wider scope than the governor’s executive order.

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Feature: Experts offer top tips for enterprise AI deployments

Experts speaking at the inaugural AMR Technology Forum offered a picture of the road to deploying AI in enterprise which is not unlike the early days of Formula One and other motor racing series.

The core message from Aston Martin Aramco technology partners is the best way to employ AI is to use it.

It is an ethos which is arguably the very basis on which Formula One racing is built. Want to try a different valve configuration on your engine? Do it. Is the car better with the power unit behind the driver than in front? Let’s find out. Are six wheels better than four and so on.

AI strategy
Speakers from the AMR Network of technology partners essentially said the strategy for deploying AI is no different to those shifts and trials in car design. Devise a clear plan about what you want to achieve and just do it. Do not be fearful, go all in and make sure what you do helps the people with the real expertise to do their jobs better.

David Ingham, digital partner in media and entertainment with Cognizant (pictured, third from right), said any AI deployment needs “to be solving a problem”, so it makes sense the first step would be to identify what that is, then the rest “falls in line”.

Ingham explained Cognizant’s approach is born of its position as a company which brings “all the layers of the AI stack” together. He referred to chips, infrastructure and software as the elements in mind, explaining the primary goal is to combine them into “a coherent workflow”, a “process that adds value”.

He argued Aston Martin Aramco’s racing cars are a great example, because individual components “don’t add value, they don’t win a race” until they are brought together.

An obvious use for AI in any organisation is coping with vast amounts of data, an element Ryan Lewis, head of Cohere’s operation in the UK and Ireland (pictured, second from right), said is another in which Formula One is a fitting example due to the volume of information teams generate and rely on.

He pointed to telemetry, diagnostic and simulation data as examples from the sport which emphasise the challenges any organisation faces in making the most of their information.

Data is “sometimes really hard to access” due to being stored in different systems, modalities or even languages.

Lewis believes “making sense of the data wherever it’s sitting” to enable rapid decision making “in high-stakes environments” presents a “really exciting opportunity for AI just to take that off the table”.

He envisions a set-up where individual AI agents communicate directly to synthesise the insights, “reports and responses” staff can use to work more effectively.

For Lewis, the watchword of deploying AI in a business is empowerment.

Cohere is not inherently seeking to use AI to “replace the things that are high value in organisations”, instead it is driving to “give the people the power to do the things that are mundane and routine” more easily, in turn accelerating the decision-making process.

A green Aston Martin Aramco Formula One car sits in a brightly lit garage or simulator facility, positioned centrally on a polished floor. Overhead equipment and gantries display the Aston Martin Aramco and Arm logos, while workstations and technical equipment are visible in the background. The image highlights the front and side profile of the race car in a clean, modern engineering environment.

Teamwork
Aston Martin Aramco technology ambassador Eric Ernst (pictured, second from left) elaborated on the empowerment theme, explaining it is the experienced staff within the team which drive the value of AI usage.

He noted machine learning is well-established, meaning AI deployment strategies today are more about how best to employ generative iterations.

Aston Martin Aramco is deriving benefits by using AI to create and assess several possible strategies, which knowledgeable engineers can then pick from based on their real-world experience.

Ernst’s advice is humans must remain the foremost element in use of AI, interpreting recommendations and conclusions the technology produces to derive the smartest outcomes.

For a Formula One team like Aston Martin Aramco, this could be as simple as when drivers should go flat out and when they should be more conservative during a race.

The point about the human element was picked up in a later session by Jonathan Armstrong, senior director of Brand and Creative at Arm, who noted AI is good at deconstructing “complex problems” but argued the full benefits of the technology can only be reaped when it is combined with the vision, ingenuity and creativity of people.

“When you have technology and AI and human insight altogether, that’s a powerful weapon.”

He said Formula One teams are working to optimise the combination of AI and human abilities, an “exciting” period for the engineering sector.

Simon Cox, chief transformation officer at ServiceNow (pictured, far right), urged organisations not to be paralysed by worries over the accuracy of their operational data. He explained the companies making the most of their AI strategies “are the ones that embrace” the chaos of current information sources and adopt a “fix it as we go” mindset.

He argued the iterations of AI involved in the latest dawn of the technology deliver the capabilities to correct data anomalies on the fly and so make a success of the very approach which embodies the ethos of Formula One racing.

The technology today can “find those gaps and see through the noise” in a company’s data. The volume of information and challenges of employing it should not hinder companies, instead Cox believes the secret to success is to “just start, get going”.

Cox’s advice to take the plunge was echoed by Ben Richardson, head of CoreWeave International (pictured, third from left), who urged companies not to wait for the perfect AI or deployment strategy.

“Like anything, if you really want to use it you’ve got to take risks, you can’t sit there and you can’t just wait”, because rivals are not.

“People have to be brave and you have to be able to say this is happening, it is here, how can I start to capture it”?

Richardson’s view is cracking on and using AI holds the potential to create a virtuous circle, where the technology becomes more valuable based on how much it is employed. Or, as he more succinctly put it: “the more people that use it the more you get out of it”.

Restrictions
With the experts’ broadly agreeing the best strategy is to learn about AI by using it, what do they think is holding most organisations back?

Lewis believes many large organisations are simply not clear enough about what they want to achieve and so are struggling to develop a “cohesive enterprise AI strategy”.

Companies must consider the result of their AI deployments and doing so requires “a top-down perspective”, one which ties every element together.

Rushing headlong into deploying any technology is, of course, inherently risky. Richardson acknowledged as much and advised companies to build protections into their strategy “if that’s what you need” to deliver the confidence required to reap the AI benefits he outlined.

Cox noted governance is a decidedly unsexy element in any discussion of AI, but explained it is still necessary.

Experience from using data, cloud computing and more has taught ServiceNow the importance of installing controls “from the beginning”.

“Resilience by design can give you the control tower for your AI and then you’re able to fly.”

Governance “sounds dull” in any discussion of enterprise AI strategy best-practice, but is an element Cox argues is absolutely necessary.

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Intel pumps €5B into EU AI fab capacity

Intel outlined a €5 billion capital investment in its Republic of Ireland campus to expand ‌European output to meet the increased demand for AI and high-performance computing.

The chipmaker stated the expansion at its facility in Leixlip, County Kildare, began earlier in the year and involves upgrading fabrication facilities and installing leading-edge manufacturing equipment to boost production of its Intel Xeon 6 and next-generation Xeon processors built on the advanced Intel 3 process node.

Intel stated the chips are increasingly critical to power AI factories.

As part of the infrastructure overhaul, Intel is expanding its “automated track system to integrate disparate campus modules” into a single, “high-velocity production environment”.

Intel explained the investment programme would create permanent high-tech jobs alongside engaging specialised building and equipment installation tradespeople.

Naga Chandrasekaran, EVP and GM of Intel Foundry, said the investment is a “definitive commitment to maximising capacity” for foundry customers.

Upgrading the site “with state-of-the-art technology and installing cutting-edge tools” would help keep the Republic of Ireland “at the forefront of the world’s most advance manufacturing ecosystems while strengthening” Europe’s position in “the global technology landscape”, he said.

The move aligns with broader European Union tech-sovereignty goals to establish a resilient, domestic supply chain for leading-edge processors.

Intel invested more than €30 billion in the Republic of Ireland since establishing operations in 1989. The Leixlip site currently employs 4,900 people.

The company is trying to revitalise its chip manufacturing business and become a serious player in the booming foundry industry.

In April, it signed up to Elon Musk’s Terafab AI chip project to create processors for orbital data centres and robots.

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Astronomers Detect Sugar in Interstellar Space for First Time

This composite image of the Milky Way’s central region shows the location of the molecular cloud G+0.693-0.027. Image credit: Ashley Barnes / Izaskun Jiménez-Serra / Juan García de la Concepción.

Using the Yebes 40-m and IRAM 30-m radio telescopes, astronomers have discovered erythrulose, a four-carbon sugar commonly found in raspberries and sunless tanning cosmetics, in the molecular cloud G+0.693-0.027.

The post Astronomers Detect Sugar in Interstellar Space for First Time appeared first on Sci.News: Breaking Science News.

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