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

The post The Friday File: Starlink; Verizon; World Bank appeared first on Mobile World Live.

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

The post Anthropic plans in-house chip team to power Claude appeared first on Mobile World Live.

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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Anthropic disclosed it is investigating three instances of its Claude AI models conducting hacks into companies during a testing process, a week after OpenAI revealed a similar incident.

The company explained its Claude models “reached the internet” from within or while interacting with a third-party evaluation environment and then gained access to the real systems of three different organisations.

Anthropic blamed a “misunderstanding” between it and a partner, which resulted in the model being able to access the internet during a cybersecurity testing process.

This then led the model’s search to real systems on the open internet, treating them as part of the exercise.

“Operating under the false belief that all accessible entities were intended to be in-scope for the exercise, Claude compromised the impacted organisations’ infrastructure using basic techniques, such as exploiting weak passwords and unauthenticated endpoints,” Anthropic stated.

Anthropic added it did not find or “exploit any complex weaknesses”.

It did not reveal which companies had been attacked.

Review
The company stated the OpenAI incident, in which two models attacked Hugging Face, prompted it to conduct a large-scale retrospective review of its own cybersecurity evaluations.

In particular, it looked for evidence Claude, like the OpenAI models, was able to access “the internet from the testing environments that should have been sealed off”.

It found the breaches after reviewing 141,006 evaluation runs where Claude could have obtained internet access.

The incidents occurred on Claude models Opus 4.7, Mythos 5 and an internal research test model.

“Ultimately, many factors contributed to these incidents, but consistent with a blameless post mortem culture, we’re approaching the fixes as if the responsibility were ours alone,” the company added.

Nvidia this week led the way in the formation of an AI safety coalition in response to the OpenAI incident.

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Meta Platforms revealed a dramatic acceleration in its infrastructure commitments, disclosing in a regulatory filing it has secured $279 billion in off-balance sheet lease obligations primarily dedicated to expanding its AI capabilities.

The future costs, which exist on top of its active leases, comprise short- and long-term agreements covering data centres, co-location facilities and certain network infrastructure.

The total for uncommenced lease commitments as of the quarter ended 30 June represents a 53% surge from the $183 billion reported in the previous period.

The social media giant is showing no signs of slowing its aggressive AI buildout, adding an extra $68 billion in commitments during July alone, with those leases slated to commence in 2027 and 2028.

The disclosure comes alongside mounting investor pressure on CEO Mark Zuckerberg. Meta’s stock fell today (30 July) following a disappointing Q3 revenue forecast yesterday which heightened investor scrutiny over the company’s massive capital expenditures on AI.

During the Q2 earnings call, Zuckerberg said Meta could sell compute directly to large enterprises but stated the social media giant believes there will be a “significantly higher margin on selling [super]intelligence rather than selling compute directly”.

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Meta Platforms CEO Mark Zuckerberg (pictured) outlined his high-stakes vision for AI across consumer and enterprise markets during a Q2 investor call, casting the technological transition as a massive commercial opportunity despite heavy infrastructure outlays and operational charges weighing on profitability.

Zuckerberg detailed three primary expansion pillars driving Meta’s long-term strategy. He noted AI investments are actively boosting performance across the main portfolio by improving user experiences, optimising return on investment for advertisers and enabling internal product teams to ship software faster.

Looking ahead, Zuckerberg stated that Meta is “developing new personal agents that will be the foundation for our next wave of products and revenue lines in the months and years ahead”.

Expanding beyond consumer applications, he highlighted a growing commercial footprint, pointing to “a large enterprise opportunity to sell to businesses, including APIs, business agents, potentially selling compute directly, and other services that we’re building for large customers”.

Q2 financial performance
Meta delivered strong Q2 top-line performance, driven by continuous gains across its AI-enhanced advertising suite, though rapid infrastructure spending and operational charges squeezed overall profitability below Wall Street expectations.

Meta generated $60.8 billion in revenue, representing a 28% increase compared to $47.5 billion in the same period last year. However, net income dropped 14% to $15.8 billion.

Advertising revenue accounted for $59.8 billion of total sales, up 28% year-over-year. This growth was supported by high adoption of AI automated ad features, with ad impressions growing 14% year-over-year across its Family of Apps and the average price per ad climbing 12%.

Family Daily Active People reached an average of 3.6 billion in June, reflecting a 3% increase year-over-year.

Total costs and expenses surged 55% to $42 billion, heavily weighed down by $2.4 billion in legal proceeding charges as well as $1.2 billion in severance expenses following restructuring in May.

Driven by the aggressive capex ramp and operational charges, free cash flow dropped 91% year-over-year to $784 million, compared to $8.5 billion in the prior-year period.

Capital expenditures jumped to $31 billion from $17 billion, including principal payments on finance leases, as Meta continued to scale its computing infrastructure, servers, and data centres to expand generative AI capabilities.

Looking ahead, the social media giant issued a Q3 revenue forecast of $61 billion to $64 billion.

For the full year, Meta maintained its capital expenditure guidance at $130 billion to $145 billion and anticipates total expenses between $165 billion and $169 billion, while reiterating full-year operating income is expected to exceed prior-year levels.

Highlighting engagement growth across its app suite, Zuckerberg noted Threads crossed 500 million monthly active users, “making it the fastest-growing conversation app ever,” while Facebook reached more than 2 billion daily active users a while ago.

“WhatsApp just hit an all-time messaging record, peaking at 30 million messages sent per second during the World Cup final,” he said.

Meta’s Reality Labs division, which houses the company’s VR and AR hardware efforts including Quest headsets and smart glasses, continued to weigh on overall profitability.

The unit posted an operating loss of $4.6 billion, widening slightly from a year earlier, on revenue of just $431 million, up from $370 million in the same period last year.

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One NZ advised businesses to rethink their approach to responsible AI after research showed consumers are growing worried about the environmental impact of companies’ use of the technology.

Research by the operator involving 1,001 New Zealanders found 45% have concerns over the sustainability of business use of AI, making it a key factor alongside transparency and privacy in overall trust ratings.

Head of corporate affairs and sustainability Nicky Preston said One NZ’s findings “highlight a shift” in attitudes.

“The conversation around AI has largely focused on productivity and innovation to date. But this research shows New Zealanders are starting to consider a broader question”.

Preston noted trust “has always been fundamental to technology adoption” and said sustainability is now part of the “equation”.

One NZ’s research found those worried about environmental impacts believe businesses should prioritise using renewable energy alongside cutting power consumption.

Consumers also want companies to be transparent about the environmental impacts, explain their reasons for employing AI and be open to independent audits.

“Customers and employees increasingly want evidence that organisations are managing AI responsibly through governance, infrastructure choices, supplier decisions and thoughtful deployment,” Preston explained.

The research highlighted consumption of electricity and water as key environmental concerns. Other factors include electronic waste and carbon emissions.

One NZ highlighted more traditional concerns about AI continue to rank highly: it noted respondents are worried about the technology taking jobs away from people, personal data being employed without consent and a lack of human oversight.

Preston said the findings indicate the businesses likely to be the most successful in using AI would be those which show they are “thinking carefully” about social and environmental impacts.

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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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