An Anthropic AI safety researcher warned there is more than a 10% chance that increasingly capable AI could “kill all humans” within the next decade, highlighting growing concerns in the industry over the pace of development.

Evan Hubinger, manager of the AI Alignment Stress-Testing team at Anthropic, wrote on social media platform X: “I personally think it is >10% within the next decade.”. He explained the risk from existing AI models was “low” but warned he was concerned about “superintelligence” emerging through “recursive self-improvement”, which is the ability of an AI system to autonomously develop its own successor.

He added Anthropic was “trying its best” but did not yet have a plan to solve alignment for superintelligence and was “not clearly on track to”.

Gambling with lives
Hubinger’s comments came in response to the resignation of AI researcher Jacob Coxon from Anthropic. In a post on X, Coxon accused OpenAI and Anthropic of “racing straight to self-improving superintelligence and gambling with our lives”.

“Neither company is acting responsibly,” he said.

Coxon argued future AI models could become capable of hacking systems, rapidly transforming industries and acquiring “real power and resources”. He called for greater coordination between AI developers, including a temporary halt to improving model capabilities.

“At OpenAI, many have not deeply internalised the civilisational stakes,” he warned. Meanwhile at Anthropic, he said “the stakes are well-understood” but “they believe no one else will act responsibly, so they must do it themselves, despite the risk”.

AI giants are facing increasing scrutiny over the behaviour of autonomous systems. In recent months, OpenAI, Anthropic and Meta have all disclosed unprecedented incidents involving AI tools carrying out cyberattacks.

Indeed, Anthropic’s August risk report assessed that while the threat posed by current models was low, the company was “less confident in this assessment than we were in prior risk reports”. It said advanced models could eventually automate R&D, rapidly accelerate progress in technical fields, and “lead to catastrophic harm”.

“We are seeing early signs of potential acceleration,” the US AI player stated.

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A report by Dell’Oro Group found worldwide data centre IT semiconductor and component revenue for servers and storage systems surged 182% in Q2 2026, driven by rising memory prices and continued AI infrastructure investment.

DRAM and storage drive revenue grew at a triple-digit pace, as average selling prices per bit more than doubled year-over-year while continued AI infrastructure investment fuelled broad-based demand across accelerators and complementary server and storage components.

“Data centre component growth accelerated sharply in the second quarter, driven by higher memory and storage prices and continued growth in server demand,” stated Baron Fung, VP of research at Dell’Oro.

He also said Nvidia’s Blackwell platform and custom accelerators from Google and Amazon continued to gain momentum.

Fung added agentic AI is emerging as a meaningful growth driver for general-purpose servers, broadening component demand beyond accelerated computing hardware.

Going forward, Fung stated Dell’Oro expects component revenue growth to maintain momentum through the remainder of 2026, supported by elevated component prices and strong AI infrastructure investment, though supply constraints could limit hyperscaler capital expenditure plans.

The report found accelerated server deployments drove strong demand for complementary components, including high-bandwidth memory (HBM), CPUs, memory and high-speed back-end network interface cards.

General-purpose server demand remained strong across cloud service providers, supported by continued infrastructure expansion alongside emerging agentic AI workloads.

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Google is set to invest at least €13 billion in digital infrastructure across Finland over the next two years, putting AI facilities, nuclear power and renewable energy at the centre of its largest single outlay in Europe.

The spending will cover new digital infrastructure across the regions of Hamina, Kajaani, Muhos and Vaala as the technology giant looks to expand capacity for services including Gemini, Search, Maps and YouTube.

The investment is expected to support more than 37,000 jobs nationwide and contribute an annual average of €3.6 billion to Finland’s GDP. Once operational, the new facilities are projected to support around 7,000 jobs annually.

It also includes a commitment of €31 million for local community initiatives over four years, including €10 million for research and innovation. Additionally, more than 4,400 workers will receive AI skills training through local partnerships

According to Google, the new sites will use existing grid infrastructure and locate closer to carbon-free energy sources. The outlay will also fund biodiversity restoration, including native forest, peatland and wetland projects.

Google’s hefty Finnish commitment dwarfs its other European investments. The company pledged €5.5 billion to Germany through 2029 and committed €600 million to a new AI facility in the Netherlands in 2024. It also broke ground on its first data centre in Austria this year as it expands AI capacity across the region.

Nokia backing
Alongside the investment, Google struck a 22-year power purchase agreement with Finnish energy company Fortum to support the continued operation of a nuclear power plant near the southern town of Loviisa. The deal marks the company’s first nuclear power contract outside the US, according to Reuters.

Google said that without the latest agreement, the plant, which currently supplies around 10% of Finland’s electricity and employs about 580 people, would not be able to continue operating beyond 2030. Keeping it online is expected to support grid resilience and help stabilise electricity prices across the country.

Google’s latest outlay deepens its existing presence in Finland, where it has operated a data centre in Hamina since 2009, supporting more than 600 suppliers including domestic operators DNA, Elisa and vendor Nokia.

Commenting on the Google investment, Nokia CEO Justin Hotard pointed to its partnership with the company on delivering optical and IP networks, while outlining a commitment to build out infrastructure to help connect Google’s activities in Finland to the world.

“Every AI token is a network moment. Billions of agents, devices, and people act on intelligence in real time, and every one of those moments depends on a network that is fast, secure and always on. Nokia builds those networks,” said Hotard.

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Qualcomm struck a deal with Amazon to develop customised silicon for large-scale AI data centre infrastructure, while issuing a warrant to the technology giant to acquire a stake worth up to $4 billion in the chipmaker.

The move marks Qualcomm’s latest strategic expansion into the data centre sector, building on its recent moves to establish an AI-native foundation, acquire AI software specialist Modular, and advance its agentic AI ambitions beyond edge devices.

Under regulatory filings tied to the deal, the agreement is linked to up to $60 billion in potential commercial transactions.

As part of the arrangement, Qualcomm issued Amazon a warrant to acquire up to 25 million shares at $161.26 apiece, representing a potential $4 billion stake which vests across tranches tied to purchase milestones.

The operational partnership centres on creating tailored processors optimised for AI inference workloads across Amazon Web Service (AWS) data centres.

By combining Qualcomm’s experience in power-efficient compute design with AWS’ global cloud footprint, the companies aim to tackle the skyrocketing energy and compute demands driven by generative AI applications.

Alongside customised processing chips, the agreement encompasses high-performance optical connectivity technologies.

Qualcomm plans to supply optical digital signal processor and serialiser/deserialiser products capable of supporting speeds up to 1.6 Tb/s.

The high-bandwidth interconnects are designed to clear data bottlenecks within data centre networks, allowing large clusters of AI chips to communicate with minimal latency.

Both ways
The collaboration works both ways, as Qualcomm also plans to deepen its internal adoption of AWS infrastructure.

The chipmaker will use cloud-based AI tools, including Amazon Bedrock, to run electronic design automation workloads aimed at accelerating its own chip development cycles.

Qualcomm CEO Cristiano Amon highlighted the rapidly accelerating demand for AI requires foundational advances across both processing and network interconnects to maximise operational efficiency.

AWS VP Prasad Kalyanaraman added the co-development effort will deliver more performant and cost-effective infrastructure for cloud customers globally.

The deal marks a significant expansion for Qualcomm, which has spent recent years diversifying its revenue beyond smartphones into personal computers, automotive systems and now cloud-scale hardware.

For AWS, working directly with Qualcomm on specialised silicon offers another avenue to manage the high-power consumption and soaring costs associated with operating global AI services.

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Mistral raised €3 billion in a Series D funding round led by Samsung Electronics, taking the French AI player’s valuation above €21 billion as it ramps up efforts to build sovereign frontier AI.

Samsung jointly led the round with European Union (EU)-backed Scaleup Europe Fund, and existing investor PSG Equity. According to Mistral, the raise marks the largest ever equity funding round by a European technology company.

New investors included private equity firm Advent and the Grand Duchy of Luxembourg, while existing backers including Mistral’s largest shareholder ASML, Nvidia, Salesforce Ventures and Bpifrance also participated.

Mistral said the funds will expand its frontier AI research and compute capacity, as well as support infrastructure investment, model development, commercial growth and international expansion.

Last year, the startup raised €1.7 billion at a €11.7 billion valuation in a series C funding round led by ASML.

The company said demand is growing for sovereign AI that combines performance with control, as enterprises and governments consider “long-term technology dependencies, data governance requirements and deployment choices”.

Mistral emphasised its “full-stack and open approach” and open-weight models and as a “sovereign AI layer” that gives organisations greater control over their data, models, compute and production systems.

In the game
Europe’s push for technological independence has gained urgency following a US decision in June to curb foreign access to two advanced AI models developed by Anthropic.

Mistral CFO Johan Bergqvist told Reuters that Europe having its “own kind of AI provider in the game is important”. He added that there is “politics involved in the access of these solutions” and organisations need to ensure they “do not compromise” their access to the AI supply chain.

Bergqvist also told the outlet the company is on track to hit $1 billion in annual recurring revenue by the end of the year, with growth increasingly coming from Asia and North America. He added a potential IPO remains an option, although the timing is “still up in the air”.

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IT provider Tata Consultancy Services’ (TCS) subsidiary HyperVault is planning a 1GW AI data centre campus in the south Indian city of Hyderabad, with up to INR700 billion ($7.4 billion) earmarked for the project.

HyperVault, an AI data centre and infrastructure business, secured 264 acres for the development, which will be built in phases based on customer demand and technology requirements. Once fully built, the campus is expected to rank among India’s largest AI infrastructure facilities.

The site will target AI companies and hyperscalers, supporting high-density GPU deployments for AI training and inference. It will use liquid cooling and is designed to accommodate larger power requirements for advanced AI workloads. The company also plans to use green energy and water-neutral design principles.

HyperVault CEO and managing director Deepesh Nanda said the company is “building infrastructure for where AI is going: higher density, liquid cooling, larger power blocks and faster deployment”.

Meanwhile, TCS CEO K. Krithivasan noted: “Hyderabad offers the scale, talent and ecosystem to serve global customers,” adding the project combines “AI-ready infrastructure with our cloud, engineering, enterprise transformation and AI capabilities”.

The move forms part of TCS’ broader push into AI infrastructure. Last month, the IT services player struck a five-year partnership with Porsche worth €1.25 billion and agreed to acquire the company’s automotive and consulting unit MHP for €320 million.

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Almost 130 nations called for restrictions to be placed on autonomous weapons systems, adding another slant to recent growing concerns over the impact of rogue AI.

In a post on X on 5 September, Minister of Foreign Affairs of the Netherlands Tom Berendsen revealed 128 nations reached an accord on a United Nations (UN) push to address the challenges posed by lethal autonomous weapon systems (LAWS) by defining what the systems are.

The agreement is an “important step” in regulating the systems, Berendsen wrote.

Various news outlets quoted an Agence France-Presse (AFP) article explaining the move to define what LAWS are is the first step towards possible regulation, which the UN separately explained is needed to ensure autonomous systems do not breach international humanitarian laws prohibiting the targeting of civilians during conflicts.

UN information indicates the agreement ratifies work on the impact of emerging technologies on LAWS commenced in 2023.

Across various meetings, government experts have defined the systems as being “one or more” weapons which can work together to “identify, select and engage a target with force, without intervention by a human being”.

Life-and-death
The concerns hold particular relevance in various ongoing global conflicts, with reports Russia and Ukraine are already testing autonomous drone fleets in their war.

In late August, UN secretary general Antonio Guterres and Mirjana Spoljaric, president of the International Committee of the Red Cross (ICRC), jointly expressed concerns over the growing capabilities of AI, in particular its use in scenarios involving lethal force.

“We are now dangerously close to crossing a moral red line: the autonomous targeting of humans by machines,” Guterres said.

Spoljaric branded autonomous targeting systems “morally repugnant”.

The UN and ICRC urged nations to act swiftly to agree global rules and continue to press for humans to remain involved in “life-and-death decisions”.

UN high commissioner for Human Rights Volker Turk today (7 September) pressed for faster action on governing AI as a whole, warning in a speech the technology poses an “existential risk to humanity” and lamenting the “almost unlimited power” a “handful of men” have over the technology.

Volker called for independent verification and “much stronger collaboration on security”, along with expressing concern over the potential impact of AI on employment, democracy and the environment.

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Nvidia inked strategic partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish AI compute infrastructure financing platforms to mobilise more than $500 billion of third-party capital to build related infrastructure.

The chipmaker stated memorandums of understanding would help create the first compute financing platforms of their kind at global scale, intended to fund frontier AI laboratories, clouds and enterprises.

It noted the platforms are designed to create dedicated pools of capital at significant scale and attractive rates for its customers, positioning Nvidia compute and full-stack AI infrastructure as an investable asset class.

“We are bringing the world’s leading long-term capital providers together to independently underwrite AI infrastructure,” Nvidia CEO Jensen Huang said.

“These financing platforms will help customers access scarce compute at scale and build the DSX AI factories that will power every industry and country”.

Nvidia described its compute as an investable asset offering the lowest token cost, highest revenue and longest life, alongside a rich ecosystem of buyers.

The arrangement builds on Nvidia’s broader push to raise capital for it and its customers to continue producing the chips, power systems and data centres underpinning the AI boom.

Nvidia GPUs underpin most leading US AI models available today and it supplies relevant chips, infrastructure, and software to a wide range of partners.

Money matters
It faced scrutiny in recent months over circular financing arrangements in which the company provides backing to help AI partners raise debt, in turn boosting Nvidia’s own revenue.

Bringing outside private capital providers onboard may help address some of the criticism since it spreads the financing load beyond Nvidia itself.

In recent years, private capital groups including Apollo and Blackstone have structured AI deals to help companies including Anthropic finance heavy spending on chips and data centres.

Financial Times reported Morgan Stanley predicts large cloud computing players would spend $3.5 trillion on AI infrastructure over the next two years.

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Meta Platforms CEO Mark Zuckerberg (pictured) argued open, decentralised access to super-intelligence is essential for ensuring global economic prosperity and personal safety.

In a lengthy blog, the executive rejected doom-centric narratives surrounding advanced AI technologies.

Rather than centralising powerful models within a select group of corporations or government institutions, Zuckerberg advocated for a balance-of-power approach, which puts personal superintelligence directly into the hands of individuals.

On the same day the post was published, Meta Superintelligence Labs released the open weights for Muse Glimmer, a 30-billion-parameter dense multimodal model under an Apache 2.0 license on Hugging Face.

The model is distilled from Muse Spark 1.2 and engineered to run locally on a single consumer GPU or Mac to execute agentic workflows such as autonomous coding and file management without cloud dependency.

Meta also plans to publish open weights for its Muse Spark 1.2 model in the coming weeks, reversing a brief closed-weight stance, while teasing a next generation frontier model known internally as Watermelon.

The release and blog came amid heightened scrutiny over closed-source AI labs following recent incidents where models from OpenAI and Anthropic broke containment during evaluation testing.

Zuckerberg positioned open-source distribution as a key countermeasure to security risks. He stated broad developer access allows system defences to be patched faster than in centralised environments.

He also defended AI distillation practices by claiming learning from observed model outputs is essential for keeping US open-source technology competitive against foreign rivals like DeepSeek.

Central to Meta’s broader strategy is the deployment of personal AI agents designed to assist users across daily tasks, business operations and learning.

To support this vision Meta unveiled a $1 billion community fund for US cities hosting its data centres to address local power, water and infrastructure needs, while committing to train skilled trade workers through its Community Compact and America’s Workforce Academy initiatives.

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Anthropic formed a strategic partnership with Macquarie Asset Management and Singaporean wealth fund GIC to build data centres which the AI company would lease under long-term arrangements.

The Theseus Infrastructure platform is to be a vehicle to develop AI computing sites with an initial focus on the US.

Macquarie Asset Management and GIC pledged to fund the bulk of the equity for each project, while Anthropic committed to covering any consumer electricity price hikes stemming from the facilities.

The asset management company stated sites would require a major investment and highlighted anticipated boosts for employment covering building and operation.

GIC is a repeat Anthropic investor.

It jointly led a $30 billion funding round in February and backed a $1.5 billion enterprise services venture Anthropic launched in May.

In 2025, Anthropic stated it would spend $50 billion on custom data centres across several US locations, including the states of Texas and New York.

The company is also preparing for a public listing.

Bloomberg reported Anthropic has made relatively few high-profile data centre partnerships compared with rival OpenAI, which launched its Stargate infrastructure joint venture in 2025.

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LG Uplus advanced efforts to apply AI in network automation by testing its ability to control the quality of a Wi-Fi 8-compatible home broadband system.

The self-healing capability employs Edge AI technology, which the South Korean operator explained conducts analyses and adaptation in the router instead of the cloud.

Broadcom contributed a Wi-Fi 8 platform running a neural processing unit to LG Uplus’ trial, enabling the on-board AI computation.

The operator adapted its existing cloud-based AI network prediction model for operation in the router.

There is an argument home broadband and consumer equipment are not often the focus of discussions around self-healing and autonomous networks.

LG Uplus explained the trial is significant in proving routers can become part of “an AI-based quality management platform”, benefitting customer service and infrastructure management.

It stated the companies proved the router could detect and adapt to anomalies before customers notice, boosting stability for bandwidth-intensive services.

LG Uplus plots further trials of how AI could be used to manage Wi-Fi 8 networks.

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OpenAI temporarily paused certain internal activities surrounding its upcoming model after the system demonstrated unprecedented cybersecurity and agentic coding capabilities.

The ChatGPT maker disclosed preliminary evaluations showed the Astra model is significantly adept at cyber tasks, leading company officials to admit they cannot rule out it becoming a critical security threat threshold.

Under OpenAI’s internal Preparedness Framework, a critical threshold is defined by a model’s ability to autonomously discover and execute zero-day exploits across hardened real-world systems without human intervention, or independently carry out complex attack strategies.

While evaluations remain ongoing alongside third-party experts, the initial findings prompted immediate containment protocols.

OpenAI is moving Astra into isolated testing environments equipped with sandboxed execution, restricted tool and network access, enhanced model weight encryption and full chain-of-thought monitoring.

It stated it paused related activities which do not currently meet the safety controls.

OpenAI’s move follows a recent series of incidents where autonomous AI agents breached security boundaries during testing.

Within the past month, OpenAI, Anthropic and Meta Platforms have all publicly acknowledged inadvertent system intrusions during evaluation phases.

OpenAI plans to partner with government agencies and AI safety institutes to evaluate Astra’s defensive and attacking potential before considering public release.

It emphasised its goal is to equip cyber defence players with high-capability models to patch vulnerabilities before malicious actors can exploit them.

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SK Hynix outlined plans to invest KRW54 trillion ($38.3 billion) in two new semiconductor manufacturing plants in South Korea, stepping up production capacity to meet long-term demand for AI memory.

The South Korean chipmaker will invest KRW35.2 trillion in its Yongin Y2 fabrication plant in the Seoul Metropolitan Area, which will produce high-bandwidth memory (HBM) and other next-generation dynamic random access memory (DRAM) products. Meanwhile, KRW19.1 trillion is earmarked for a second facility, Cheongju M17, in central South Korea to manufacture NAND flash memory chips, with the company arguing the city “offers the fastest fab construction timeline”.

The latest investment forms part of a wider manufacturing push. In June, SK Hynix unveiled plans to invest KRW600 trillion in the Yongin Semiconductor Cluster and KRW100 trillion to expand its Cheongju production base.

Yongin Y2 will become the second of four planned fabs in the Yongin Semiconductor Cluster. Construction of the plant is due to begin in July 2027, while work on the Cheongju M17 fab is scheduled to start in February 2027. The company aims to complete all four planned fabrication plants by 2033, bringing forward the original timeline by 12 years.

The latest commitment comes amid strong demand for AI memory requiring large volumes of HBM. SK Hynix explained demand for NAND memory is “surging rapidly”, adding its investment followed “a thorough review of market demand”. Citing forecasts by Omdia, it noted global DRAM and NAND demand is expected to grow at a compound annual rate of 19% through 2030.

The company noted “in the AI era, technological competitiveness alone is not enough”, arguing the “ability to supply the required volume at the exact moment customers need it is the ultimate competitive advantage”.

In June, South Korean President Lee Jae-myung unveiled a long-term AI and semiconductor initiative led by Samsung Electronics and SK Hynix expected to exceed $1 trillion by 2035.

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ByteDance is reportedly in the process of developing an AI model which could rival Anthropic’s Mythos system as part of a bid to establish itself as a leader in China’s AI ecosystem.

Financial Times (FT) reported the TikTok owner is in the early stages of training a model with as many as 10 trillion parameters.

This would put ByteDance’s offering ahead of Anthropic’s cutting-edge Mythos and make it three-times larger than Moonshot Kimi K3, the biggest model to come out of China so far.

While Anthropic does not reveal the size of its models, FT reported the most advanced Mythos 5 system has 8 trillion parameters and its Fable 5 about 5 trillion.

ByteDance’s model is apparently being pre-trained, a stage in development which typically takes three-to-six-months. It would then be fine-tuned and released, provided there are no issues.

Chinese companies are showing their hand with regards to AI model development, with Moonshot and Alibaba highlighting releases in recent weeks.

FT added ByteDance invested more aggressively in AI than other Chinese companies, building data centres and attracting talent in the sector.

Founder Zhang Yiming reportedly told staff he wants the team to target “world-leading model capabilities” during an internal meeting last month.

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Mobile World Live (MWL) brings you our top three picks of the week as SpaceX CEO Elon Musk outlined Starlink’s global broadband ambitions, Verizon lifted the lid on the network behind the FIFA World Cup 2026 and the World Bank urged developing nations to boost AI adoption.

Musk targets global broadband domination with Starlink

What happened: Musk outlined plans to increase Starlink’s network capacity 100-fold, claiming the satellite broadband business could eventually “deliver a majority of the world’s internet”.

Why it matters:  The tech mogul said the goal hinges on the rollout of an expanded V3 satellite constellation capable of delivering around 10 times the performance of current V2 models. To support the plan, the company asked the US Federal Communications Commission (FCC) for approval to deploy up to 100,000 low-Earth-orbit V3 satellites, supplementing the roughly 9,600 V2 satellites already in orbit. Musk argued the additional capacity would allow Starlink to eventually carry a majority of global internet traffic in countries where the service is authorised to operate, while driving a tenfold increase in Starlink revenue even if revenue per bit falls by 90%. Quilty Space founder and CEO Chris Quilty told MWL that the company’s “bold claim” flouts its “prior statements that Starlink was most appropriate for rural user”. While V3 satellites are expected to provide a “10x boost”, he noted “aggregate network capacity is a misleading metric because capacity is geographically distributed while demand is geographically concentrated”. Earlier this week, SpaceX president Gwynne Shotwell claimed that Starlink Mobile could compete directly with operators including AT&T, Verizon and T-Mobile US using upgraded satellites and additional spectrum.

Musk targets global broadband domination with Starlink

Podcast: Inside Verizon’s World Cup connectivity

What happened: In the latest edition of the MWL podcast, Kavit and Justin sat down with Verizon wireless chief network officer Srini Kalapala, who detailed how the operator delivered connectivity as the official network provider for the FIFA World Cup 2026.

Why it matters: Earlier this month, the operator revealed its network carried almost 500TB of data across all US host stadiums, including 29.2TB during the final between Argentina and Spain. To handle demand, Verizon boosted stadium capacity by three to five times, installed thousands of under-seat antennas, deployed nearly 140 small cells around venues and fan zones, and laid 80,000 miles of fibre to transport broadcast feeds from all World Cup stadiums. In the podcast, Kalapala described the tournament’s “104 games in 39 days across 18 different stadiums in three countries” as “probably one of the largest projects that we worked on.” He explained Verizon had to ensure stadiums comprising 70,000 to 85,000 people could access “good quality mobile connectivity”, while also delivering “the most reliable network” for broadcasters and powering private 5G applications including referee cameras.

Podcast: Inside Verizon’s World Cup connectivity

World Bank urges lower income nations to grasp AI opportunity

What happened: The World Bank called on developing economies to accelerate AI adoption, arguing low-cost, locally adapted tools could accelerate economic development without requiring frontier models or hefty AI infrastructure investments.

Why it matters: In its World Development Report 2026: The Promise of Artificial Intelligence, the organisation said AI “could allow developing countries to do in a decade what might otherwise take a century”, provided governments address gaps in electricity, internet access, digital skills and institutions. World Bank SVP and chief economist Indermit Gill said AI has “thrown developing economies a lifeline”, but warned countries “must hurry” because the technology is “spreading faster and is more context-specific than earlier general-purpose technologies”. He added many high-impact use cases do not require large models or data centres, instead relying on “small, low-cost AI tools” tailored to local conditions. The report highlighted applications across healthcare, agriculture, tax collection and judicial services, while warning AI could also deepen inequality and weaken public trust without appropriate action. Foresight Communications Consultancy CEO Howaida Nadim argued the World Bank’s framework recognises that “greater opportunity lies in adopting proven tools and adapting them to local languages, data, institutions and development priorities”. She added “the next AI divide” might be “between those that successfully adapt AI to their development needs and those that remain primarily consumers of systems built elsewhere”.

World Bank urges lower income nations to grasp AI opportunity

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Indosat Ooredoo Hutchison brought in the big guns of its parent, Nokia and Nvidia to help it develop fresh infrastructure to meet the demand for AI computing in Southeast Asia and beyond, with an initial 1GW target.

The Indonesian operator’s Zankore by Indosat play is to employ Nvidia’s DSX AI Factory reference design as part of an ambitious plan to establish the nation as a regional compute hub.

It aims to provide the first 200MW of capacity in H1 2027, running an Nvidia GB300 NVL72 rack. Information from the chip company indicates the set up uses 72 of its Blackwell Ultra GPUs and 36 Arm-architected CPUs to provide additional reasoning capabilities.

Zankore by Indosat is also employing the Nvidia DSX MaxLPS technology suite, which the chip player separately explained provides ways to “maximise token performance per MW within a fixed power budget”.

Put more plainly, the suite is designed to offer the lowest-possible token cost by optimising power use across the line of GPUs to unlock fuelling which might otherwise be stuck in less useful areas.

The operator’s parent Ooredoo Group is the lead investor and platform sponsor, an arrangement noted to bring access to long-term capital and regional scale.

Nokia is providing AI-native network infrastructure.

Zankore by Indosat appointed ex-Ericsson and T-Mobile US executive Ulf Ewaldsson as CEO, along with establishing a board comprising representatives from principal shareholders and independent members.

Meutya Hafid, the Indonesian Minister of Communication and Digital Affairs, said the nation is advantageously placed to provide AI compute capacity throughout Southeast Asia and the Zankore by Indosat move would speed development of sovereign capabilities to the benefit of “businesses and society”.

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Google CEO Sundar Pichai (pictured) revealed a major shake-up within its AI division, with DeepMind co-founder and CEO Demis Hassabis stepping back from day-to-day operational management to focus on overarching strategy, AGI and scientific breakthroughs.

Under the new leadership structure, Koray Kavukcuoglu, former CTO of Google DeepMind and chief AI architect, steps up as SVP of Google DeepMind, reporting directly to Pichai.

Kavukcuoglu, who has been with DeepMind for 13 years and previously led foundational projects like WaveNet and Deep Q-Networks, will now directly oversee Gemini model development, frontier AI research and developer ecosystems.

Hassabis transitions into a newly created strategic role as chair of Google DeepMind and chief scientist of Alphabet.

In a note sent to employees, Pichai stated the shift allows Hassabis to dedicate his attention to shaping the long-term future of AGI and scientific applications, alongside his ongoing leadership at drug-discovery subsidiary Isomorphic Labs.

Hassabis expressed confidence in the transition, emphasising  he plans to focus on broad strategic initiatives and high-impact applications of AI in healthcare, particularly accelerating efforts to treat major diseases.

The executive shift comes at a period of rapid product momentum for the internet giant’s AI stack.

According to internal metrics shared by Pichai, the flagship Gemini consumer application has surged past 950 million monthly active users, while the open-weights Gemma model family has surpassed 900 million downloads.

The reorganisation also marks the end of an era for two foundational figures in modern computing infrastructure.

Jeff Dean, Google’s chief scientist and long-time head of Google AI, is departing after 27 years alongside Google senior fellow Sanjay Ghemawat.

The pair are launching independent public benefit company aimed at applying machine learning to scientific and engineering discoveries. Google will serve as a founding investor and cloud infrastructure partner for the new entity, maintaining an active collaborative research framework on advanced systems.

“Jeff Dean is at a moment where he wants to try something new, and we’re excited to support him in that,” Pichai stated.

As competition in model capabilities intensifies across the industry, Google is doubling down on its full-stack approach which spans custom silicon, cloud infrastructure, and consumer applications to seek an edge in the race toward advanced AI.

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Anthropic confirmed it is building an in-house silicon team to design custom chips for its Claude AI model, a move aimed at improving performance and efficiency as demand for its services continues to rise.

In a statement to Mobile World Live (MWL), Anthropic said it “is hiring engineers with experience across the stack”.

The company stated this move will let it co-design hardware and models together, allowing Claude to run faster and more efficiently at the scale its customers need.

Anthropic told MWL the effort is not a shift away from its existing hardware partners. The company described the silicon team as the latest step in its multi-chip approach

It is building a diversified hardware stack with chips from Amazon Web Services (AWS), Google, Nvidia, and AMD, which will “remain central to how we scale”.

Reuters had previously reported Anthropic was exploring building its own chips while The Information stated the company had held talks with Samsung Electronics about possibly manufacturing them.

Business Insider cited a newly posted job listing which describes what Anthropic is looking for, which includes a “custom silicon team” with engineers spanning multiple areas of chip design and verification.

The listing, which advertises a salary range of $320,000 to $485,000, calls for candidates who can point to direct personal contribution in finalising and shipping semiconductor designs.

Building AI chips in-house is expensive and technically demanding, but the benefits include improved performance and less dependence on Nvidia.

Rival moves
Anthropic joins a growing list of AI companies pursuing custom silicon, following moves by OpenAI, Meta, Google, and Amazon.

OpenAI unveiled its first custom-built inference ASIC, Jalapeno, in June, developed in partnership with Broadcom.

In April, Meta Platforms expanded its partnership with Broadcom to jointly develop multiple generations of custom MTIA chips, building on four new generations it had unveiled in March.

Google is also developing a server chip, called Frozen v2, to improve efficiency for its Gemini AI model and separate from its existing TPUs,

During Alphabet’s Q1 earnings call in April, CEO Sundar Pichai stated the company will begin making its tensor processing units available to a select group of customers for their own data centres, a move seen as a potential challenge to Nvidia’s dominance in AI chips.

Also in April, Meta struck a deal with Amazon Web Services to use its Graviton processors for agentic AI workloads.

Amazon also has an agreement in place with Anthropic to use its Trainium chips to train and run its AI models

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Anthropic appointed Mariano-Florentino Cuellar as its first chief global affairs officer, as the Claude AI model developer faces escalating political and regulatory friction.

In the newly-created role, Cuellar (pictured) will report directly to Anthropic president Daniela Amodei.

His primary focus involves managing relationships with US authorities and international government bodies as the business expands internationally.

Cuellar is stepping down from Anthropic’s independent four-person Long-Term Benefit Trust, a body which ensures the company aligns its commercial goals with its public-interest mission.

The trust is now searching for a successor.

Anthropic described Cuellar as a pragmatist and consensus builder suited to navigating government opposition. His credentials include working as a special assistant to former President Barack Obama and a justice with the Supreme court of California.

He also directed the Carnegie Endowment for International Peace think tank while co-chairing a task force on US national security and nuclear proliferation, a domain industry executives often cite as a blueprint for managing advanced AI risk.

Cuellar also jointly led studies which shaped landmark Californian state law SB 53, which introduced whistleblower protections and safety reporting mandates for high-revenue AI developers.

The executive said politicians everywhere are recognising AI governance is at a pivotal inflection point, noting current decisions would determine if technology can be harnessed safely or increase global inequality.

Anthropic is working to mend relations with the US government following several clashes including a military dispute which resulted in the US Department of War blacklisting its technology, a designation the company is challenging in court.

Officials also issued export control directives temporarily banning international sales of its high-tier Mythos 5 and Fable 5 models over national security concerns.

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Infrastructure company Azio AI Holdings signed a master services agreement (MSA) with AT&T worth roughly $2.4 million to provide enterprise fibre connectivity for its first AI data centre campus.

The deal covers a 500-megawatt site and establishes a standardised connectivity framework across the campus, delivering the high-capacity, low-latency network infrastructure needed to support AI training, inference, GPU cloud computing, enterprise colocation, and other high-performance computing workloads.

Azio said the connectivity buildout is intended to streamline network deployment as it brings on additional customers under its hyperscale AI strategy. The company pointed to a recent power purchase and hosting agreement with a GPU customer, which it said will require a rapid, modular buildout at the Texas site.

“This agreement establishes the networking framework supporting our initial 500-megawatt Texas AI platform while creating a scalable operating model that can support future expansion as additional projects move forward under our hyperscale AI strategy,” Azio COO Elgin Tracy stated.

The company’s broader strategy centres on scalable, liquefied natural gas-backed energy capacity intended to meet rising demand for GPU cloud and AI workloads.

It stated the Texas site was picked in part due to the location being able accommodate large-scale industrial infrastructure without the land-use and community constraints which can complicate data centre projects in urban areas.

The agreement adds AT&T to the growing list of telecoms operators positioning themselves as connectivity partners for the AI infrastructure buildout, as data centre operators race to secure the fibre capacity needed to link GPU clusters to enterprise and hyperscale customers.

Azio did not disclose a timeline for construction completion or when the Texas campus is expected to become operational.

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