Semiconductors

Intel unveils next-gen 18A processors with high performance and efficiency

Intel has revealed its next-gen client and server processors using Intel 18A, the most advanced US-made semiconductor node. The new Intel Core Ultra 3 (Panther Lake) and Xeon 6+ (Clearwater Forest) promise major performance and efficiency gains, with production already underway at Fab 52 in Arizona.

Panther Lake introduces a scalable multi-chiplet architecture for consumer and commercial AI PCs, gaming devices, and edge applications. It offers over 50% faster CPU and GPU performance, up to 180 TOPS for AI, and new robotics AI capabilities.

High-volume production begins later this year, with broad availability expected in January 2026.

Clearwater Forest is designed for hyperscale data centres, cloud providers, and telcos. Built entirely on Intel 18A, the Xeon 6+ processor offers up to 288 E-cores, a 17% IPC uplift, and improved density, throughput, and power efficiency.

It is set to launch in the first half of 2026.

Intel 18A underpins at least three upcoming generations of client and server products, with key innovations including RibbonFET transistors, PowerVia backside power delivery, and Foveros advanced packaging.

Fab 52 further strengthens the company’s US manufacturing leadership, supporting domestic production and strategic supply chain resilience.

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Microsoft boosts AI leadership with NVIDIA GB300 NVL72 supercomputer

Microsoft Azure has launched the world’s first NVIDIA GB300 NVL72 supercomputing cluster, explicitly designed for OpenAI’s large-scale AI workloads.

The new NDv6 GB300 VM series integrates over 4,600 NVIDIA Blackwell Ultra GPUs, representing a significant step forward in US AI infrastructure and innovation leadership.

Each rack-scale system combines 72 GPUs and 36 Grace CPUs, offering 37 terabytes of fast memory and 1.44 exaflops of FP4 performance.

A configuration that supports complex reasoning and multimodal AI systems, achieving up to five times the throughput of the previous NVIDIA Hopper architecture in MLPerf benchmarks.

The cluster is built on NVIDIA’s Quantum-X800 InfiniBand network, delivering 800 Gb/s of bandwidth per GPU for unified, high-speed performance.

Microsoft and NVIDIA’s long-standing collaboration has enabled a system capable of powering trillion-parameter models, positioning Azure at the forefront of the next generation of AI training and deployment.

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US greenlights Nvidia chip exports to UAE under new AI pact

The US has approved its first export licences for Nvidia’s advanced AI chips destined for the United Arab Emirates, marking a concrete step in the bilateral AI partnership announced earlier in 2025.

These licences come under the oversight of the US Commerce Department’s Bureau of Industry and Security, aligned with a formal agreement between the two nations signed in May.

In return, the UAE has committed to investing in the United States, making this a two-way deal. The licences do not cover every project yet: some entities, such as the AI firm G42, are currently excluded from the approved shipments.

The UAE sees the move as crucial to its AI push under Vision 2031, particularly for funding data centre expansion and advancing research in robotics and intelligent systems. Nvidia already collaborates with Abu Dhabi’s Technology Innovation Institute (TII) in a joint AI and robotics lab.

Challenges remain. Some US officials cite national security risks, especially given the UAE’s ties and potential technology pathways to third countries.

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Bulgaria eyes AI gigafactory partnership with IBM

Bulgaria is considering building an AI gigafactory in partnership with IBM and the European Commission, Prime Minister Rosen Zhelyazkov announced after meeting with IBM executives in Sofia. The project aims to attract large-scale high-tech investment and strengthen Europe’s AI infrastructure.

The proposed facility would feature over 100,000 advanced GPU chips and require up to 500 megawatts of power. The initial phase alone is expected to need around 70 megawatts, highlighting the scale of the planned operation.

Funding could come through a public-private partnership, with the European Commission covering up to 17 percent of capital costs and EU member states contributing additional support for this Bulgarian project.

IBM is considered a strategic technology partner, bringing expertise in cloud computing, cybersecurity, and AI systems. The first gigafactories across Europe are expected to begin operations between 2027 and 2028, aligning with the EU’s plan to mobilise €200 billion for AI development.

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OpenAI and AMD strike 6GW GPU deal to power next-generation AI infrastructure

AMD and OpenAI have announced a strategic partnership to deploy up to six gigawatts of AMD GPUs, marking one of the largest AI compute collaborations.

The multi-year agreement will begin with the rollout of one gigawatt of AMD Instinct MI450 GPUs in the second half of 2026, with further deployments planned across future AMD generations.

A deal that deepens a long-standing relationship between the two companies began with AMD’s MI300X and MI350X series.

OpenAI will adopt AMD as a core strategic compute partner, integrating its technology into large-scale AI systems and jointly optimising product roadmaps to support next-generation AI workloads.

To strengthen alignment, AMD has issued OpenAI a warrant for up to 160 million shares, with tranches vesting as the partnership achieves deployment and share-price milestones. AMD expects the collaboration to deliver tens of billions in revenue and boost its non-GAAP earnings per share.

AMD CEO Dr Lisa Su called the deal ‘a true win-win’ for both companies, while OpenAI’s Sam Altman said the partnership will ‘accelerate progress and bring advanced AI benefits to everyone faster’.

The collaboration positions AMD as a leading hardware supplier in the race to build global-scale AI infrastructure.

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Bezos predicts gigantic gains from the current AI investment bubble

Jeff Bezos has acknowledged that an ‘AI bubble’ is underway but believes its long-term impact will be overwhelmingly positive.

Speaking at Italian Tech Week in Turin, the Amazon founder described it as an ‘industrial bubble’ rather than a purely financial.

He argued that the intense competition and heavy investment will ultimately leave society better off, even if many projects fail. ‘When the dust settles and you see who the winners are, societies benefit from those investors,’ he said, adding that the benefits of AI will be ‘gigantic’.

Bezos’s comments come amid surging spending by Big Tech on AI chips and data centres. Citigroup forecasts that investment will exceed $2.8 trillion by 2029.

OpenAI, Meta, Microsoft, Google and others are pouring billions into infrastructure, with projects like OpenAI’s $500 billion Stargate initiative and Meta’s $29 billion capital raise for AI data centres.

Industry leaders, including Sam Altman of OpenAI, warned of an AI bubble. Yet many argue that, unlike the dot-com era, today’s market is anchored by Nvidia and OpenAI, whose products form the backbone of AI development.

The challenge for tech giants will be finding ways to recover vast investments while sustaining rapid growth.

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Japan targets AI leadership through new Nvidia–Fujitsu collaboration

Nvidia and Fujitsu have partnered to build an AI infrastructure in Japan, focusing on robotics and advanced computing. The project will utilise Nvidia’s GPUs and Fujitsu’s expertise to support healthcare, manufacturing, environmental work, and customer services, with completion targeted for 2030.

Speaking in Tokyo, Nvidia CEO Jensen Huang said Japan could lead the world in AI and robotics. He described the initiative as part of the ongoing AI industrial revolution, calling infrastructure development essential in Japan and globally.

The infrastructure will initially target the Japanese market but may later expand internationally. Although specific projects and investment figures were not disclosed, collaboration with robotics firm Yaskawa Electric was mentioned as a possible example.

Fujitsu and Nvidia have previously collaborated on digital twins and robotics to address Japan’s labour shortages. Both companies state that AI systems will continually evolve and adapt over time.

Fujitsu CEO Takahito Tokita said the partnership takes a humancentric approach to keep Japan competitive. He added that the companies aim to create unprecedented technologies and tackle serious societal challenges.

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Atlantic Quantum joins Google Quantum AI to advance scalable quantum hardware

Google Quantum AI has taken a major step in its pursuit of error-corrected quantum computing by integrating Atlantic Quantum, an MIT spin-out focused on superconducting hardware.

The move, while not formally labelled an acquisition, effectively brings the startup’s technology and talent into Google’s programme, strengthening its roadmap toward scalable quantum systems.

Atlantic Quantum, founded in 2021, has worked on integrating qubits with superconducting control electronics in the same cold stage.

A modular chip stack that promises to simplify design, reduce noise, and make scaling more efficient. Everything is equally important to build machines capable of solving problems beyond the reach of classical computers.

Google’s Hartmut Neven highlighted the approach as a way to accelerate progress toward large, fault-tolerant devices.

The startup’s journey, from MIT research labs to Google integration, has been rapid and marked by what CEO Bharath Kannan called ‘managed chaos’.

The founding team and investors were credited with pushing superconducting design forward despite the immense challenges of commercialising such cutting-edge technology.

Beyond hardware, Google gains a strong pool of engineers and researchers, enhancing its competitive edge in a field where rivals include IBM and several well-funded scale-ups.

A move that reflects a broader industry trend where research-heavy startups are increasingly folded into major technology firms to advance long-term quantum ambitions. With governments and corporations pouring resources into the race, consolidation is becoming common.

For Atlantic Quantum, joining Google ensures both technological momentum and access to resources needed for the next phase. As co-founder Simon Gustavsson put it, the work ‘does not stop here’ but continues within Google Quantum AI’s effort to deliver real-world quantum applications.

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Taiwan rejects US proposal on semiconductor production split

Taiwan has dismissed reports of a US plan to divide global semiconductor production evenly between the two sides. Vice Premier Cheng Li-chiun, returning from tariff talks in Washington, said her negotiating team had never discussed or agreed to a 50-50 split on chipmaking.

‘Rest assured, we did not discuss this issue during this round of talks, nor would we agree to such conditions,’ Cheng told reporters.

The clarification followed comments by US Commerce Secretary Howard Lutnick, who suggested Washington was seeking such an arrangement. Neither the US Department of Commerce nor the Office of the Trade Representative commented on the reports.

Taiwan, home to leading chipmaker TSMC, currently faces a 20% tariff on exports to the United States but hopes negotiations will lead to more favourable trade terms.

TSMC is already expanding production abroad with a $165 billion investment in factories in Arizona, though the majority of its output will remain in Taiwan. The government has emphasised that the ongoing trade talks with Washington have achieved ‘certain progress’ but remain focused on tariffs, not production quotas.

Separately, President Lai Ching-te met with US officials to discuss agricultural trade. Taiwan pledged to purchase $10 billion worth of American agricultural products, including soybeans, wheat, corn, and beef, over the next four years, signalling broader economic cooperation despite tensions over chips.

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Samsung joins OpenAI for AI data centre push

Samsung Electronics, alongside OpenAI, has signed a letter of intent to collaborate on AI data centre infrastructure. The partnership leverages Samsung’s expertise in semiconductors, cloud services, and shipbuilding. Combining these strengths aims to accelerate advancements in global AI technology.

Samsung Electronics will provide energy-efficient DRAM for OpenAI’s Stargate, meeting a projected demand of 900,000 wafers monthly. Advanced chip packaging and heterogeneous integration further enhance Samsung’s ability to deliver tailored semiconductor solutions for AI workflows.

Samsung SDS will design and operate Stargate AI data centres while offering enterprise AI services, including ChatGPT integration for Korean businesses. Meanwhile, Samsung C&T and Samsung Heavy Industries will explore floating data centres to address land scarcity and reduce emissions.

Signed in Seoul, the agreement positions Samsung to support Korea’s ambition to rank among the top three AI nations globally. Broader adoption of ChatGPT within Samsung’s operations will also drive workplace AI transformation.

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