OpenAI set to spend $10bn on Broadcom AI chips

OpenAI has reportedly placed a $10bn order with Broadcom to mass-produce custom AI chips, due for shipment in 2026. Sources told the Financial Times that the move would help reduce OpenAI’s dependence on Nvidia, its primary supplier.

Sam Altman recently said OpenAI will use ‘well over 1m GPUs’ by the end of 2025, highlighting the company’s accelerating demand for computing power. In contrast, Elon Musk’s xAI is expected to double its Nvidia Hopper GPUs to around 200,000.

Broadcom confirmed a large custom chip order during its latest earnings call, without naming the buyer. The company’s AI revenue rose 63 percent to $5.2bn, chip sales grew 57 percent to $9.1bn, and shares gained nearly 5 percent.

The new order is expected to be for internal use rather than external customers. Industry observers suggest that OpenAI’s decision signals a strategic shift, allowing the ChatGPT maker to secure supply for its AI expansion while diversifying beyond Nvidia.

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EU Parliament challenges US-EU Trade deal while rallying around digital autonomy

During a special hearing, the EU Parliament Trade Committee scrutinised the US-EU ‘Framework on an Agreement on Reciprocal, Fair, and Balanced Trade’, from July 2025. Brussels expected that the deal would put an end to the transatlantic ‘tariff war’, but members of the European Parliament (MEPs) criticised the allegedly lopsided nature of the proposed agreement. Among other things, they argued that it would endanger Europe’s pursuit of strategic autonomy. 

Their perception has been strengthened by post-agreement declarations from US President, Donald Trump, who threatened to impose tariffs and export controls on countries whose taxes, rules or laws on tech companies “discriminate” against the US. This indicates that, from the US perspective, the agreement does not seem to put an end to the quarrel over European regulation. 

Central to the deal is a 15% tariff ceiling on most EU exports to the US – such as cars, semiconductors, and pharmaceuticals –  replacing a patchwork of higher and less predictable duties. Without an agreement, the EU was set to get a tariff level of 30%, plus the ordinary Most-Favoured Nation (MFN) tariff level in place before Trump. 

Alongside that, other commitments touch directly on the EU digital policy agenda. The European Union pledged to buy $40 billion worth of American AI chips for its computing centres (while blocking any leakage of semiconductors to ‘destinations of concern’), to engage in closer coordination with the US in technical standards, and to cooperate on economic security by, for example, coordinating on export controls to enhance supply chain resilience. 

The European Commission needs to have a majority in the Parliament to be able to enact the US-EU deal, raising uncertainty about the future of the Framework. Among MEPs, the digital sovereignty agenda is gaining strength. This week, S&D – the second largest political group in the EU Parliament – sponsored the launch of the policy brief ‘A progressive roadmap for strengthening Europe’s digital sovereignty’, by Cecilia Rikap, in a display of the growing support for strengthening Europe’s autonomy in this area.  

MEPs also expressed concern that the US-EU deal may violate the laws of the World Trade Organization (WTO). The US is raising tariffs beyond its WTO commitments, while the EU is offering tariff cuts that discriminate against its other international partners, violating the Most-Favoured Nation principle.

In spite of the resistance, MEPs are expected to propose amendments to the text of the deal, rather than halting the agreement.

Quantum and supercomputing converge in IBM-AMD initiative

IBM has announced plans to develop next-generation computing architectures by integrating quantum computers with high-performance computing, a concept it calls quantum-centric supercomputing.

The company is working with AMD to build scalable, open-source platforms that combine IBM’s quantum expertise with AMD’s strength in HPC and AI accelerators. The aim is to move beyond the limits of traditional computing and explore solutions to problems that classical systems cannot address alone.

Quantum computing uses qubits governed by quantum mechanics, offering a far richer computational space than binary bits. In a hybrid model, quantum machines could simulate atoms and molecules, while supercomputers powered by CPUs, GPUs, and AI manage large-scale data analysis.

Arvind Krishna, IBM’s CEO, said the approach represents a new way of simulating the natural world. AMD’s Lisa Su described high-performance computing as foundational to tackling global challenges, noting the partnership could accelerate discovery and innovation.

An initial demonstration is planned for later this year, showing IBM quantum computers working with AMD technologies. Both companies say open-source ecosystems like Qiskit will be crucial to building new algorithms and advancing fault-tolerant quantum systems.

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Alibaba shares soar on AI and cloud growth

Alibaba’s Hong Kong shares rose over 15%, their most significant single-day gain since early 2023, following strong AI revenue growth. AI-related sales surged triple digits, and the cloud division grew 26% to 33.4 billion yuan ($4.7 billion), exceeding expectations and driving expansion.

The results underline Alibaba’s transformation from a retail-heavy company into a diversified technology player. Analysts say AI is now a central growth driver, with cloud and AI offerings boosting investor confidence despite price war pressures from JD.com and Meituan.

Alibaba is investing in AI hardware and developing proprietary chips to reduce reliance on foreign semiconductors. The strategy aims to build faster, cheaper, and more secure AI systems for domestic and international markets, including Lazada and AliExpress.

Experts view this calculated self-reliance and strong cloud and AI services as a long-term growth driver.

While retail rivals continue to struggle with profit pressure, Alibaba’s leadership has emphasised AI as a core strategic focus.

CEO Eddie Wu emphasised ambitions in artificial general intelligence, with analysts noting AI could protect Alibaba from price wars and support growth across multiple business areas.

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IBM and AMD unite to build quantum-classical supercomputers

IBM and AMD have launched a strategic collaboration to pioneer quantum-centric supercomputing architectures, blending IBM’s quantum computing capabilities with AMD’s strengths in high-performance computing (HPC), AI acceleration, CPUs, GPUs and FPGAs.

Their vision involves creating hybrid systems where quantum components handle atomic-scale or highly complex tasks, such as molecular simulation or optimization, while classical and infrastructure powered by AI processes large datasets efficiently.

The approach aims to unlock new levels of computational power. A demonstration of these hybrid workflows is scheduled for later this year.

Additionally, AMD’s technology may facilitate real-time error correction, a vital step toward achieving IBM’s goal of fault-tolerant quantum computing by the end of this decade.

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NVIDIA’s sales grow as the market questions AI momentum

Sales of AI chips by Nvidia rose strongly in its latest quarter, though the growth was less intense than in previous periods, raising questions about the sustainability of demand.

The company’s data centre division reported revenue of 41.1 billion USD between May and July, a 56% rise from last year but slightly below analyst forecasts.

Overall revenue reached 46.7 billion USD, while profit climbed to 26.4 billion USD, both higher than expected.

Nvidia forecasts sales of $54 billion USD for the current quarter.

CEO Jensen Huang said the company remains at the ‘beginning of the buildout’, with trillions expected to be spent on AI by the decade’s end.

However, investors pushed shares down 3% in extended trading, reflecting concerns that rapid growth is becoming harder to maintain as annual sales expand.

Nvidia’s performance was also affected by earlier restrictions on chip sales to China, although the removal of limits in exchange for a sales levy is expected to support future revenue.

Analysts noted that while AI continues to fuel stock market optimism, the pace of growth is slowing compared with the company’s earlier surge.

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US pushes chip manufacturing to boost AI dominance

Donald Trump’s AI Action Plan, released in July 2025, places domestic semiconductor manufacturing at the heart of US efforts to dominate global AI. The plan supports deregulation, domestic production and export of full-stack technology, positioning chips as critical to national power.

Lawmakers and tech leaders have previously flagged tracking chips post-sale as viable, with companies like Google already using such methods. Trump’s plan suggests adopting location tracking and enhanced end-use monitoring to ensure chips avoid blacklisted destinations.

Trump has pressed for more private sector investment in US fabs, reportedly using tariff threats to extract pledges from chipmakers like TSMC. The cost of building and running chip plants in the US remains significantly higher than in Asia, raising questions about sustainability.

America’s success in AI and semiconductors will likely depend on how well it balances domestic goals with global collaboration. Overregulation risks slowing innovation, while unilateral restrictions may alienate allies and reduce long-term influence.

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Jetson AGX Thor brings Blackwell-powered compute to robots and autonomous vehicles

Nvidia has introduced Jetson AGX Thor, its Blackwell-powered robotics platform that succeeds the 2022 Jetson Orin. Designed for autonomous driving, factory robots, and humanoid machines, it comes in multiple models, with a DRIVE OS kit for vehicles scheduled for release in September.

Thor delivers 7.5 times more AI compute, 3.1 times greater CPU performance, and double the memory of Orin. The flagship Thor T5000 offers up to 2,070 teraflops of AI compute, paired with 128 GB of memory, enabling the execution of generative AI models and robotics workloads at the edge.

The platform supports Nvidia’s Isaac, Metropolis, and Holoscan systems, and features multi-instance GPU capabilities that enable the simultaneous execution of multiple AI models. It is compatible with Hugging Face, PyTorch, and leading AI models from OpenAI, Google, and other sources.

Adoption has begun, with Boston Dynamics utilising Thor for Atlas and firms such as Volvo, Aurora, and Gatik deploying DRIVE AGX Thor in their vehicles. Nvidia stresses it supports robot-makers rather than building robots, with robotics still a small but growing part of its business.

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NVIDIA eyes recovery in China after export deal ahead of Q2 report

NVIDIA is due to report its Q2 2026 financial results after the US market closes on 27 August, and analysts are expecting strong performance.

Consensus forecasts place revenue at around US $45.9 billion, up about 50 percent year-on-year, driven by ongoing demand for Blackwell GPUs, data centre expansion and redistribution of AI infrastructure investments globally.

Export changes are also pivotal. After entering a deal to resume H20 chip sales to China, despite revenue-sharing conditions, NVIDIA could reclaim as much as US$8 billion during Q2, mitigating past losses caused by restrictions.

Beyond geopolitical shifts, the Blackwell Ultra GPU is central to growth. Offering up to 50 times faster AI inference than earlier models, it is increasingly stocked by cloud providers and hyperscalers. Markets view this as a strategic advantage, fueling long-term AI momentum.

Risks remain. Gross margins may recover from prior pressure due to licensing charges, but margin expansion depends on supply and TAM realisation. China’s policy environment is also uncertain, making future guidance cautious for some analysts.

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Arm to build its own chips with AI focus

Arm Holdings has hired Amazon’s AI chip lead, Rami Sinno, to design its own complete chips. Known for Amazon’s Trainium and Inferentia processors, Sinno brings key expertise to Arm’s new direction in chip manufacturing.

Arm has traditionally licensed chip designs to companies like Apple and Nvidia, but now aims to build chips and complete systems. The firm is expanding teams with experience from HPE, Intel and Qualcomm, signalling a significant shift in its business model.

Backed by SoftBank, Arm plans to invest profits in chip development to rival Nvidia and reduce reliance on traditional licensing.

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