Oxford Quantum Circuits (OQC) and Digital Realty have launched the first quantum-AI data centre in New York City at the JFK10 facility, powered by Nvidia GH200 Grace Hopper Superchips. The project combines superconducting quantum computers with AI supercomputing under one roof.
OQC’s GENESIS quantum computer is the first to be deployed in a New York data centre, designed to support hybrid workloads and enterprise adoption. Future GENESIS systems will ship with Nvidia accelerated computing and CUDA-Q integration as standard.
OQC CEO Gerald Mullally said the centre will drive the AI revolution securely and at scale, strengthening the UK–US technology alliance. Digital Realty CEO Andy Power called it a milestone for making quantum-AI accessible to enterprises and governments.
UK Science Minister Patrick Vallance highlighted the £212 billion economic potential of quantum by 2045, citing applications from drug discovery to clean energy. He said the launch puts British innovation at the heart of next-generation computing.
The centre, embedded in Digital Realty’s PlatformDIGITAL, will support applications in finance, security, and AI, including quantum machine learning and accelerated model training. OQC Chair Jack Boyer said it demonstrates UK–US collaboration in leading frontier technologies.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
China’s State Administration for Market Regulation (SAMR) has issued a preliminary finding that Nvidia violated antitrust lawlinked to its 2020 acquisition of Mellanox Technologies. The deal was approved with restrictions, including a ban on bundling and ‘unreasonable trading conditions’ in China.
SAMR now alleges that Nvidia breached those terms. A full investigation is underway. Nvidia shares fell 2.4% in pre-market trading after the announcement. According to the Financial Times, SAMR delayed releasing the findings to gain leverage in trade talks with the USA, currently taking place in Madrid.
At the same time, US export controls on advanced chips remain a challenge for Nvidia. Licensing for its China-specific H20 chips is still under review, affecting Nvidia’s access to the Chinese market.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
Arm Holdings has unveiled Lumex, its next-generation chip designs built to bring advanced AI performance directly to mobile devices.
The new designs range from highly energy-efficient chips for wearables to high-performance versions capable of running large AI models on smartphones without cloud support.
Lumex forms part of Arm’s Compute Subsystems business, offering handset makers pre-integrated designs, while also strengthening Arm’s broader strategy to expand smartphone and data centre revenues.
The chips are tailored for 3-nanometre manufacturing processes provided by suppliers such as TSMC, whose technology is also used in Apple’s latest iPhone chips. Arm has indicated further investment in its own chip development to capitalise on demand.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
The selection means Google will work with DARPA’s technical experts, who will be independent validators for its quantum computing roadmap. The evaluation aims to provide rigorous third-party benchmarking, a critical capability for the broader quantum industry.
DARPA’s QBI is not only about validation. It aims to compare different quantum technologies, superconducting qubits, photonic systems, trapped ions and other modalities under shared metrics.
Google’s involvement underscores its ongoing mission to build quantum infrastructure capable of addressing problems such as new medicine design, energy innovation and machine-learning optimisation.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
Chinese scientists have unveiled SpikingBrain1.0, the world’s first large-scale AI language model to replicate the human brain. The model reduces energy use and runs independently of Nvidia chips, departing from conventional AI architectures.
Developed by the Chinese Academy of Sciences, SpikingBrain1.0 uses spiking neural networks to activate only the required neurons for each task, rather than processing all information simultaneously.
Instead of evaluating every word in parallel, it focuses on the most recent and relevant context, enabling faster and more efficient processing. Researchers claim the model operates 25 to 100 times faster than traditional AI systems while keeping accuracy competitive.
A significant innovation is hardware independence. SpikingBrain1.0 runs on China’s MetaX chip platform, reducing reliance on Nvidia GPUs. It also requires less than 2% of the data typically needed for pre-training large language models, making it more sustainable and accessible.
SpikingBrain1.0 could power low-energy, real-time applications such as autonomous drones, wearable devices, and edge computing. The model highlights a shift toward biologically-inspired AI prioritising efficiency and adaptability over brute-force computation.
Would you like to learn more aboutAI, tech and digital diplomacy? If so, ask our Diplo chatbot!
Broadcom has secured a $10 billion agreement to supply custom AI chips, with analysts pointing to OpenAI as the likely customer.
The US semiconductor firm announced the deal alongside better-than-expected third-quarter earnings, driven by growing demand for its ASICs. It forecast a strong fourth quarter as cloud providers seek alternatives to Nvidia, whose GPUs remain costly and supply-constrained.
Chief executive Hock Tan said Broadcom is collaborating with four potential new clients on chip development, adding to existing partnerships with major players such as Google and Meta.
The company recently introduced the Tomahawk Ultra and next-generation Jericho networking chips, further strengthening its position in the AI computing sector.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
A team of international researchers has shown how training neural networks directly with light on photonic chips could make AI faster and more sustainable.
A breakthrough study, published in Nature, involved collaboration between the Politecnico di Milano, EPFL Lausanne, Stanford University, the University of Cambridge, and the Max Planck Institute.
The research highlights how physical neural networks, which use analogue circuits that exploit the laws of physics, can process information in new ways.
Photonic chips developed at the Politecnico di Milano perform mathematical operations such as addition and multiplication through light interference on silicon microchips only a few millimetres in size.
By eliminating the need to digitise information, these chips dramatically cut both processing time and energy use. Researchers have also pioneered an ‘in-situ’ training technique that enables photonic neural networks to learn tasks entirely through light signals, instead of relying on digital models.
The result is a training process that is faster, more efficient and more robust.
Such advances could lead to more powerful AI models capable of running directly on devices instead of being dependent on energy-hungry data centres.
An approach that paves the way for technologies such as autonomous vehicles, portable intelligent sensors and real-time data processing systems that are both greener and quicker.
Would you like to learn more aboutAI, tech and digital diplomacy? If so, ask our Diplo chatbot!
Apple is rolling out Memory Integrity Enforcement on the iPhone 17 line and iPhone Air, an always-on set of protections aimed at blocking memory-safety exploits used by mercenary spyware.
MIE builds on ARM’s Enhanced Memory Tagging Extension in Apple’s A19 chips, alongside secure allocators and tag-confidentiality measures.
Older devices without the new tagging hardware also receive memory-safety upgrades. Apple says new Spectre V1 leak mitigations arrive with virtually no CPU penalty.
Comparable ideas exist elsewhere, such as Windows 11’s memory integrity (HVCI) and Android’s MTE support on Pixel 8, but Apple’s approach is enabled by default across key attack surfaces. Security reporters note the move significantly complicates spyware operations.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
At a forum in Taipei, SEMI’s Terry Tsao said Taiwan’s chip design and fabrication expertise complements Japan’s materials and manufacturing equipment strengths. He noted that TSMC’s Kumamoto expansion creates opportunities for talent development in partnership with local schools.
Tsao described Taiwanese growth as a golden semiconductor era, emphasising its success closely tied to Japanese collaboration. He argued that TSMC’s achievements in Japan also represent progress for Japan’s industry.
Kazuhito Hashimoto, head of the Japan Science and Technology Agency, said joint projects with Taiwan’s National Science and Technology Council are underway. He pledged support for expanded research exchanges between the two partners.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
Meta has plans to spend at least $600 billion on US data centres and AI infrastructure by 2028. The forecast, reported by The Information, was shared by CEO Mark Zuckerberg during a dinner with President Donald Trump and other technology leaders.
Capital expenditure is set to rise sharply over the next three years. Meta projects spending of $66–72 billion in 2025, nearly 70% higher than 2024, with another significant increase expected in 2026.
The company said the surge in investment will be driven primarily by the need to expand AI computing power.
Zuckerberg confirmed that Meta aims to deploy more than one million GPUs to train its next generation of AI models.
The company is also investing heavily in talent and infrastructure as it builds a dedicated team focused on developing artificial super intelligence, a concept referring to AI systems with capabilities beyond those of humans.
The spending commitment highlights how major US technology companies are racing to secure computing capacity for AI. Meta is pledging ‘hundreds of billions of dollars’ towards expanding its data centre footprint in the years ahead.
Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!
