Mobile World Live brings you our top three picks of the week as OpenAI’s models hacked an AI start-up during testing, Samsung unveiled its latest AI-powered foldables, and Verizon and AT&T logged record World Cup network traffic.

OpenAI models hack AI start-up

What happened: OpenAI revealed that a combination of its advanced AI models autonomously breached a controlled testing environment and launched a cyberattack on AI start-up Hugging Face.

Why it matters: During an internal benchmark designed to evaluate advanced cyber capabilities, the models exploited vulnerabilities in OpenAI’s research infrastructure to gain internet access before using stolen credentials and zero-day flaws to access Hugging Face’s systems. OpenAI said it had intentionally relaxed cyber safeguards in the sandboxed environment to test the models’ capabilities, stating the models were “hyperfocused” on completing the evaluation task and went to “extreme lengths”, though the company warned such events are likely to “become more commonplace” as models grow more capable.

Jason Goode, VP at IT service AppViewX, argued “this is the wake-up call the industry needed”, as the models “didn’t defeat their guardrails so much as exploit what their environments already permitted”. He said the episode underlined the “why model governance alone was never going to be enough” and how “the control point has to be the agent’s identity and what it’s actually allowed to touch”. Meanwhile Dan Gray, chief systems architect at technology R&D firm ChronoDyne Systems, added the incident should not be viewed as AI “going rogue”, but as a “cross-organisational control-chain failure” in which the models provided the “speed, persistence and adaptive exploitation capability”, while the organisations supplied “the objective, permissions, infrastructure and attack surface”.

OpenAI models hack AI start-up

Samsung unveils 3 new foldables packed with AI

What happened: Samsung Electronics expanded its foldables portfolio with three new smartphones at its latest Galaxy Unpacked event in London.

Why it matters: The lineup washeadlined by the Galaxy Z Fold8 Ultra, Samsung’s first foldable to carry the Ultra branding. The vendor also refreshed the Galaxy Z Fold8 and Galaxy Z Flip8, placing AI capabilities and slimmer designs at the centre. Alongside the handsets, Samsung unveiled the Galaxy Watch9 and Galaxy Watch Ultra2, while teasing AI-enabled smart glasses developed with Google and Qualcomm. Futuresource Consulting principal analyst Rasika D’Souza noted that despite forecasts smartwatch shipments will top 200 million units in 2026, the market is maturing as growth shifts to wearables including smart glasses and rings, an opportunity targeted by Samsung. She added the event showed Samsung’s strategy “has evolved from simple integration of AI features to now creating AI assistants that can assist meaningfully in daily tasks”. Meanwhile, FDM CCS Insight chief analyst Ben Wood said Samsung is “doubling down on foldables at exactly the moment the category is about to get its biggest credibility boost”, arguing Apple’s rumoured launch of a foldable iPhone later this year “could also be the moment that turns foldables from a niche premium category into a mainstream flagship battleground”.

Samsung unveils 3 new foldables packed with AI

Verizon, AT&T tally massive data usage during World Cup

What happened: Verizon and AT&T outlined the scale of network infrastructure deployed to support connectivity during the FIFA World Cup, reporting record data traffic and major capacity upgrades across US host venues.

Why it matters: Verizon said its network carried almost 500TB of data across all US host stadiums. The operator boosted stadium capacity by three to five times, installed thousands of under-seat and overhead antennas, and deployed nearly 140 small-cell projects and temporary sites beyond venues. Verizon described the World Cup as an opportunity to “test, refine, and validate our enterprise network capabilities, stressing that many upgrades will remain after the tournament to extend the value of the infrastructure into long-term assets for host cities. Meanwhile, AT&T reported it carried around one petabyte of nationwide traffic during the tournament after preparing its network for two to three times normal demand across 11 US host cities and 146 venues. Verizon’s deployment supported live broadcast production alongside fan connectivity, while AT&T highlighted the role of its FirstNet public safety network in coordinating emergency services.

Verizon, AT&T tally massive data usage during World Cup

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Indian IT company HCLTech teamed with AI start-up Sarvam to build a data centre in the eastern state of Odisha, tapping increasing demand for the technology and cloud computing.

The project is expected to cost around INR142.6 billion ($1.5 billion), with financial assistance from the government of Odisha, HCLTech stated.

It pitched the data centre as central to boosting sovereign AI and the local developer ecosystem, employing the full-stack of its capabilities with the technology along with Sarvam’s foundation models to tailor services for private and public sector enterprises.

The company stated the data centre would also help to deliver multi-lingual AI-based services in line with calls from Indian Prime Minister Narendra Modi for the technology to benefit all citizens.

HCLTech is building its relationship with Sarvam AI after acquiring a 10.5% stake in the business for $150 million.

This month, it struck a $1.1 billion deal with an unnamed European company.

HCLTech CEO and MD C Vijayakumar said the data centre in Odisha is an important milestone in its full stack AI play, explaining the state offers “a progressive policy environment backed by excellent infrastructure”.

In November 2025, rival Tata Consultancy Services also announced plans to develop AI data centres in partnership with private equity company TPG and investing around $2 billion.

HCLTech separately outlined a plan to open a technology centre in the city of Bhubaneswar, also in Odisha.

It intends for the site to be operational by 2028, housing around 5,000 employees.

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Alphabet CEO Sundar Pichai (pictured) rejected concerns Google is losing ground in the AI race after delays to the Gemini 3.5 Pro model, as the company posted a strong second quarter on booming demand for AI and cloud services.

Speaking on the company’s Q2 earnings call, Pichai acknowledged Google needed to improve in areas including AI coding, but said it remained “very committed and very confident of being at the frontier”.

The chief faced repeated questions over whether Gemini could keep pace with rivals in the AI race after Google delayed the launch of its next advanced model in June. He said Google is “committed to being at the full parade of frontier,” offering models at multiple price points including its more affordable Flash models.

Pichai argued “the frontier is an incredibly dynamic space, and it’s fiercely moving forward”, stressing “there are many attributes on which we are still at the frontier”.

He pointed to Gemini 3.6 Flash, released this week, explaining it improved by more than 10 points on a coding benchmark over its predecessor while using fewer tokens. He also revealed the company has begun training Gemini 4, describing it as its “most ambitious pre-training run yet”.

Once Gemini 4 lands, he added the company plans on “picking up pace and releasing models almost at a monthly cadence”.

Strong demand
In Q2 2026, Alphabet pinpointed Google Cloud, which continued to benefit from enterprise demand for AI infrastructure and services.

Revenue from the unit soared 82% to $24.8 billion and operating income more than tripled to $8.8 billion. Google Services revenue increased 15% to $94.5 billion, driven by a 17% spike in Search, 15% in Google subscriptions, platforms and devices, and a 13% rise in YouTube advertising.

Total revenue rose 24% year-on-year to $119.8 billion, Alphabet’s 12th consecutive quarter of double-digit growth.

Net income surged 298% to $112.1 billion, as it benefitted from a net gain of $98 billion on equity securities. It did not disclose further information, but the company is known to have a sizeable stake in SpaceX and has investment in Anthropic.

“Our AI investments are redefining what’s possible across every part of our business,” Pichai explained, adding ballooning demand for AI infrastructure and enterprise AI solutions helped drive the results.

The search giant also continued ramping AI investment, expecting to spend between $195 billion and $205 billion in capital expenditure this year, up from its previous forecast of $180 billion to $190 billion.

“We have increased ​our capacity quite significantly over the past three years. The demand still outpaces that investment,” explained Alphabet CFO Anat Ashkenazi, adding that although “we’re still in a supply constraint environment”, the company is “seeing very strong demand, both from external cloud customers as well as across the business”.

Looking ahead, the company added it expects capex to “increase significantly” in 2027 as AI demand swells.

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Rockwell Automation and industrial AI company Augury spotted an opportunity to help industries make sense of the vast pools of data the technology is now generating, teaming on a product focused on delivering usable information to manufacturers.

The US-headquartered automation company explained the partnership with Augury would benefit businesses seeking to employ AI in predictive ways spanning maintenance, reliability and overall industrial performance.

Rockwell Automation’s own research indicates less than half of all data collected is being used in effective ways, despite the growing ability for AI to execute on the insights it provides.

“Manufacturers don’t need more alerts, they need a faster path to action,” Angela Rapko, VP and GM of Visualisation and Asset Management at Rockwell Automation explained.

The set-up uses relevant products from each company to provide the route highlighted by the executive: Rockwell Automation stated it enables manufacturers to go beyond “early issue detection and diagnosis”.

It emphasised the use of an Augury reliability agent and its own maintenance assistant as a key differentiator.

The Augury agent “continuously analyses machine conditions” for potential problems and generates ideas on how to avoid or fix them. Rockwell Automation’s assistant is used to make sense of the recommendations to provide “maintenance workflows, work orders and orchestration of execution activities”.

Rockwell Automation indicated the partnership could be foundational in future agentic AI developments in addition to the companies’ more practical aim of helping industrial players to improve the efficiency of their manufacturing operations.

The companies aim to provide initial access to the set-up from September.

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AMD outlined plans to invest up to $5 billion in Anthropic as part of a wider deal for the AI company to add 2 gigawatts of computing capacity to its platform, with deployment set to begin in the first half of 2027.

The duo stated it had struck the strategic partnership to address the extraordinary pace of AI adoption, which is driving rapid growth in demand for training and inference capacity,

Anthropic said it was scaling up its compute infrastructure to serve strong and growing demand for Claude and acquiring AMD’s latest AI server chips “represents a major expansion of AMD’s position at the centre of the global AI infrastructure buildout”.

Deployment of the first gigawatt of AMD’s Helios platform will begin in the first half of 2027. No timescale was given to complete deployment.

In addition, the pair stated they are launching a multiyear engineering collaboration to accelerate AMD software deployment with Claude and the company will adopt the model across its engineering and product development teams.

Details on the $5 billion commitment from AMD into Anthropic were sparse, but it will be dependent on meeting certain milestones. Anthropic has also secured billions in investment from Google and Amazon.

Lisa Su, CEO and chair at AMD, said the deal will help it establish “Helios as a major platform for the next generation of AI infrastructure”.

Chief compute officer and co-founder of Anthropic Tom Brown added access to compute is “central to keeping Claude at the frontier and meeting demand from our customers”.

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Intel and Google Cloud broadened their multi-year strategic collaboration with plans to deploy Gemini Enterprise and Google Cloud infrastructure across the chipmaker’s global operations as part of a wider AI-driven transformation.

Under the expanded partnership, Intel will roll out Gemini-powered generative AI tools across engineering, supply chain and corporate functions, aiming to scale workforce capabilities through agentic workflows.

The hyperscaler’s infrastructure will also support Intel’s semiconductor development environment, with custom agentic workflows intended to speed up the chip design lifecycle and improve cross-functional execution.

Intel CIO Cindy Stoddard stated the collaboration gives employees a central hub to build and deploy agents through Gemini Enterprise, alongside elastic cloud infrastructure to scale silicon development, as part of the company’s push to move faster and more efficiently.

Karthik Narain, chief product and business officer at Google Cloud, described the partnership as an effort to pair Intel’s engineering expertise with agentic AI tools to create what he called an autonomous foundation for how the chipmaker designs, operates and scales its business.

The companies stated the deployment moves Intel beyond isolated AI pilot programmes. Through the Gemini Enterprise Agent Platform, Intel’s business units will be able to build and run tailored line-of-business agents aimed at automating core processes and speeding up data-driven decision-making.

Gemini’s reasoning capabilities will also power dedicated coding assistance and engineering automation tools designed to streamline software development pipelines and automate multi-step workflows.

Intel is separately piloting Google Cloud-powered tools for marketing and communications, including agents that can identify relevant subject matter experts, draft executive-ready messaging, and generate supporting content across communications channels.

On the infrastructure side, Intel is extending its on-premises compute capacity into Google Cloud’s C4 and N4 instances to support silicon development simulations and core engineering workloads, letting engineering teams run high-performance computing simulations concurrently to shorten chip development cycles.

The tie-up builds on a partnership which has deepened steadily this year. In April, Google committed to using multiple generations of Intel’s Xeon processors, including the 18A-manufactured Xeon 6, to support AI training and inference in its data centres, alongside a plan to co-develop custom infrastructure processing units.

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China President Xi Jinping (pictured) set out his vision for the country to assume a leadership role in AI, calling for increased international cooperation and promotion of open-source technology while taking aim at the US over attempts to govern the sector.

Xi made the comments in a speech at the World AI Conference in Shanghai, where it was announced China, Brazil, Russia and Indonesia are among 30 countries to have joined the World Artificial Intelligence Cooperation Organisation.

Chinese state media describe the new group as an intergovernmental organisation headquartered in Shanghai to promote global AI governance.

Of the new group, Xi said AI should not be a “solo performance by one country, but rather a symphony of global cooperation”.

He said the initiative is a response to the call of the Global South to unite the international community in promoting development and governance of AI, “and it will become a major milestone in the history of artificial intelligence development”.

To further support this, Xi said China will provide 5,000 training opportunities in AI-related fields for developing countries, in addition to establishing AI application cooperation centres.  

In his speech, Xi noted that as AI continues to develop at “staggering speed”, there was a greater need for positive direction.

“We must more precisely grasp the scale of oversight and governance, and more promptly refine measures to forestall loss of control.”

Overstretch
While not naming the US directly, Xi said countries should oppose “overstretching the national security concept in the field of AI, or placing one country’s security over that of others”.

The US has notably placed several restrictions on China, impacting companies in the country from accessing high-end technology.

XI continued to state he was committed to promoting cooperation, bridging the digital divide, promoting sustainable development and avoiding “creating new historical injustices in the field of artificial intelligence”.

Finally, he called on the countries to “seize this rare historical opportunity, encourage open source and open collaboration”, in turn upgrading traditional industries and ensure AI can “empower all sectors”.

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NTT and Japanese media company TBS identified AI as a potential danger to children’s decision-making abilities and outlined an intention to form a company to tackle the issue using digital games and smartphone apps.

The pair plan to commence operations of their e6 joint venture on 8 August to help children form clear ideas in a world where AI offers myriad possible answers to questions. The business is to be used to commercialise a namesake project NTT and TBS launched in February to provide an experience-based educational approach using various technologies.

NTT stated the companies created Emotional Knight, a story-based “original IP” emotive education game employing AI and extended reality to teach decision-making.

NTT President and CEO Akira Shimada said the companies believe huge volumes of information are not necessarily the best thing for children.

Instead, they need “the ability to think for themselves and make their own decisions while interacting with a wealth of information and AI”.

The companies intend to expand the line-up of educational games, develop relevant IP and add more “entertainment experiences” which foster children’s “ability to make independent decisions”.

NTT is contributing group resources including its innovative optical and wireless network, tsuzumi 2 LLM, R&D and social implementation capabilities. TBS brings content creation, IP development and distribution elements.

The Japanese conglomerate stated feedback from an event held in March showed a high level of satisfaction.

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Micron Technology secured strategic supply agreements with major automotive partners including Qualcomm and Harman to guarantee long-term chip access for software-defined vehicles.

The deals come during an aggressive industry-wide race to expand manufacturing capacity to meet a massive surge in memory chip demand driven by rapid AI adoption.

As the only US-based manufacturer of high-bandwidth memory chips used in Nvidia’s AI processors, Micron occupies a unique market position alongside South Korean rivals Samsung and SK Hynix, allowing it to command premium prices while solidifying long-term commitments during ongoing hardware shortages.

Micron also struck deals with Visteon, Joynext, Denso, Astemo, and Hyundai Mobis. It stated the agreements would improve visibility and help optimise production planning. It expects greater stability in pricing and supply chains for increasingly sophisticated AI-enabled vehicle platforms.

Demand for high-performance DRAM and NAND flash memory has grown as the automotive sector transitions toward highly connected, autonomous and intelligent designs.

Modern vehicle architectures require robust computing hardware to support advanced driver assistance systems, infotainment services and high-speed connectivity.

Sanjay Mehrotra, chair, president and CEO of Micron, emphasised the next phase of automotive innovation hinges on the strength of the ecosystem behind it. He noted “memory and storage serve are critical enablers” for the sophisticated digital experiences consumers expect.

Qualcomm CEO Cristiano Amon highlighted the collaborative effort required to deliver advanced digital cockpit and driver assistance technologies. He stated working with Micron provides a strong hardware foundation as vehicles become more intelligent and connected.

The automotive sector is a key area for increasing Qualcomm’s revenue beyond mobile chips. In its April Q2 earnings, it reported Automotive sales rose 38 per cent to $1.3 billion.

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Consumer hardware company Aina raised millions of dollars in seed funding to finance development of an interface it argues is required to fully unlock the potential of AI on smartphones and PCs.

The company believes current device hardware lags the progress of software and AI, resulting in a disconnect between expectation and reality in terms of the interface with apps and services.

It raised $5.5 million in the recent funding round to advance development of experimental interfaces which adapt to the app being used.

Aina stated it already shipped hundreds of experimental keypads called Dune to early adopters, a product for Mac computers it describes as “context-aware” which primarily focuses on work tools.

It is using the feedback from Dune to develop a general-purpose interface for smartphones and computers.

Aina founder and CEO Apoorv Shankar (pictured) said current smartphones and PCs “are still primarily designed for browsing” and use manual inputs requiring users to “figure out what you need”.

He argued this is laborious when users are “doing hundreds of tasks” per day.

The company believes there is room within the broader AI assistant space for a contextualisation system which makes it easier for people to interact with the technology. Shankar explained the general-purpose interface on the drawing board is being designed to “capture human approval”.

Shankar was previously VP of hardware at smart ring company Ultrahuman.

The seed funding round was led by Redstart Labs (Infoedge) and 360 ONE Asset, with two other investment companies and a host of angel investors.

Along with launching its interface, Aina intends to use the backing to grow its team in the US and India.

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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 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 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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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 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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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 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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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.

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 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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Qualcomm struck a deal to acquire AI software company Modular for about $3.9 billion, in all stock-deal aimed at strengthening its software foundation for generative and agentic AI across data centre and edge environments.

The deal will pair Qualcomm’s silicon expertise with Modular’s AI-native software platform, which is designed to run AI models efficiently across CPUs, GPUs, NPUs and custom ASICs without requiring separate rewrites for each type of accelerator.

The chipmaker stated developers and enterprises will only need to build once ahead of deploying across multiple environments at a lower total cost of ownership.

Qualcomm framed the acquisition as a response to a shift in what is constraining AI deployment at scale. As AI use grows, the company argued, efficiency rather than raw capability becomes the limiting factor, since performance-per-watt drives inference costs and those costs determine what can scale.

Closing this gap, according to Qualcomm, requires software that connects system-level optimisation with heterogeneous, disaggregated compute, turning silicon performance into AI services which work reliably across different accelerators and use cases.

The deal is intended to expand Qualcomm’s data centre ambitions, supporting more efficient inference, orchestration and deployment in distributed AI systems while deepening relationships with model creators, developers, hyperscalers, and enterprise customers.

It is also expected to help the company achieve strong day-zero performance on new Qualcomm AI hardware as it rolls out.

Qualcomm President and CEO Cristiano Amon called the acquisition a pivotal moment for the AI industry. He stated agentic AI’s growth across data centres and edge environments is pushing the sector toward disaggregated, multi-vendor architectures which need a more open, modern software foundation.

He said Qualcomm believes the future belongs to developer-friendly platforms which can run across diverse compute environments, giving customers real choice in how and where they deploy AI.

“With Modular, we’re accelerating that shift, combining our scale and energy-efficient data center technologies with an open ecosystem approach to help drive the next chapter of AI,” Amon stated.

Modular co-founder and CEO Chris Lattner stated the company was built on the belief AI needs a more open and efficient software foundation spanning diverse hardware and deployment environments.

The transaction is expected to close in the second half of 2026, subject to customary closing conditions and regulatory approvals. Qualcomm plans to issue 19.2 million shares to Modular equity holders.

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