Huawei has unveiled its most powerful AI server, the CloudMatrix 384, to challenge Nvidia’s grip on the high-performance AI infrastructure market.
The system, launched at the World AI Conference in Shanghai, uses 384 Ascend 910C chips, significantly outnumbering Nvidia’s 72 B200 GPUs in the GB200 NVL72.
Although Nvidia’s GPUs remain more powerful individually, Huawei’s design relies on stacking and high-speed chip interconnection to boost overall performance.
The company claims the CloudMatrix 384 can deliver 300 petaflops of computing power, well above Nvidia’s 180 petaflops, though it consumes nearly four times more energy.
The US recently reversed its ban on Nvidia’s H20 chip exports to China, seeking to curb Huawei’s momentum. However, ongoing reports of smuggled Nvidia GPUs raise doubts over the effectiveness of these restrictions.
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The long-term agreement, slated to extend through 2033, was confirmed on Monday, 28 July and highlights rising confidence in Samsung’s cutting-edge chip technology, especially its 2-nanometer production line.
Although Samsung declined to name Tesla as the client, insiders familiar with the deal identified the electric vehicle leader as the buyer.
News of the pact propelled Samsung’s shares upward by 3.5%, its sharpest intraday rise in nearly a month; a clear indicator of investor optimism following a lull in the semiconductor foundry sector.
In recent quarters, Samsung has grappled to hold its ground in the cutthroat chip manufacturing market, seeing its global foundry share dip to 7.7% from 8.1%.
By contrast, market leader Taiwan Semiconductor Manufacturing Co. (TSMC) commands a 67.6% share, operating at full capacity, while Samsung struggles to fill its production lines, straining its foundry revenue.
Analysts estimate the Tesla deal could lift Samsung’s foundry sales by 10% annually, injecting fresh vigour into a faltering business segment.
Furthermore, this breakthrough may pave the way for new contracts with other fabless chipmakers, broadening Samsung’s client portfolio and securing steady growth in an unsteady industry.
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Amazon’s quiet wind-down of its Shanghai AI lab underscores a broader shift in global research dynamics, as escalating tensions between the US and China reshape how tech giants operate across borders.
Instead of expanding innovation hubs in China, major American firms are increasingly dismantling them.
The AWS lab, once central to Amazon’s AI research, produced tools said to have generated nearly $1bn in revenue and over 100 academic papers.
Yet its dissolution reflects a growing push from Washington to curb China’s access to cutting-edge technology, including restrictions on advanced chips and cloud services.
As IBM and Microsoft have also scaled back operations or relocated talent away from mainland China, a pattern is emerging: strategic retreat. Rather than risking compliance issues or regulatory scrutiny, US tech companies are choosing to restructure globally and reduce local presence in China altogether.
With Amazon already having exited its Chinese ebook and ecommerce markets, the shuttering of its AI lab signals more than a single closure — it reflects a retreat from joint innovation and a widening technological divide that may shape the future of AI competition.
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A joint statement committed to signing an administrative agreement on AI, aligned with principles from the Hiroshima AI Process. Shared initiatives include a €4 million EU-supported quantum R&D project named Q‑NEKO and the 6G MIRAI‑HARMONY research effort.
Both parties pledge to enhance data governance, digital identity interoperability, regulatory coordination across platforms, and secure connectivity via submarine cables and Arctic routes. The accord builds on the Strategic Partnership Agreement activated in January 2025, reinforcing their mutual platform for rules-based, value-driven digital and innovation cooperation.
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North Korea is dispatching AI researchers, interns and students to countries such as Russia in an effort to strengthen its domestic tech sector, according to a report by NK News.
The move comes despite strict UN sanctions that restrict technological exchange, particularly in high-priority areas like AI.
Kim Kwang Hyok, head of the AI Institute at Kim Il Sung University, confirmed the strategy in an interview with a pro-Pyongyang outlet in Japan. He admitted that international restrictions remain a major hurdle but noted that researchers continue developing AI applications within North Korea regardless.
Among the projects cited is ‘Ryongma’, a multilingual translation app supporting English, Russian, and Chinese, which has been available on mobile devices since 2021.
Kim also mentioned efforts to develop an AI-driven platform for a hospital under construction in Pyongyang. However, technical limitations remain considerable, with just three known semiconductor plants operating in the country.
While Russia may seem like a natural partner, its own dependence on imported hardware limits how much it can help.
A former South Korean diplomat told NK News that Moscow lacks the domestic capacity to provide high-performance chips essential for advanced AI work, making large-scale collaboration difficult.
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Deputy Minister Nezar Patria says the roadmap aims to clarify the country’s AI market potential, particularly in sectors like health and agriculture, and provide guidance on infrastructure, regulation, and investment pathways.
Already, global tech firms are demonstrating confidence in the country’s potential. Microsoft has pledged $1.7 billion to expand cloud and AI capabilities, while Nvidia partnered on a $200 million AI centre project. These investments align with Jakarta’s efforts to build skill pipelines and computational capacity.
In parallel, Indonesia is pitching into critical minerals extraction to strengthen its semiconductor and AI hardware supply chains, and has invited foreign partners, including from the United States, to invest. These initiatives aim to align resource security with its AI ambitions.
However, analysts caution that Indonesia must still address significant gaps: limited AI-ready infrastructure, a shortfall in skilled tech talent, and governance concerns such as data privacy and IP protection.
The new AI roadmap will bridge these deficits and streamline regulation without stifling innovation.
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GCT Semiconductor Holding, Inc. has begun delivering samples of its latest 5G chipsets to lead customers, including Airspan Networks and Orbic. The company offers chip and module formats to meet specific testing needs.
Initial shipments aim to fulfil early demand, after which GCT will work with clients to assess performance and establish production requirements. The firm is well positioned to scale with a robust supply chain and deep experience in high-speed connectivity.
The fabless semiconductor designer targets mid-tier 5G applications and plans to introduce a Verizon-certified module. GCT has said it remains focused on accelerating its role in the global 5G market.
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Recent debates on AI’s environmental impact have overwhelmingly focused on energy use, particularly in powering massive data centres and training large language models.
However, a Forbes analysis by Saleem H. Ali warns that the material inputs for AI, such as phosphorus, copper, lithium, rare earths, and uranium, are being neglected, despite presenting similarly severe constraints to scaling and sustainability.
While major companies like Google and Blackstone invest heavily in data centre construction and hydroelectric power in places like Pennsylvania, these energy-focused solutions do not address looming material bottlenecks.
Many raw minerals essential for AI hardware are finite, regionally concentrated, and environmentally taxing to extract. However, this raises risks ranging from supply chain fragility to ecological damage and geopolitical tension.
Experts now say that sustainable AI development demands a dual focus, not only on low-carbon energy, but on keeping critical mineral supply chains resilient.
Without a coordinated approach, AI growth may stall or drive unsustainable resource extraction with long-term global consequences.
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Former Google chief executive Eric Schmidt has warned that electricity, rather than semiconductors, will limit the future growth of AI.
Speaking on the Moonshots podcast, Schmidt said the push towards artificial superintelligence—AI that exceeds human cognitive ability in almost all domains—will depend on securing sufficient power instead of just developing more advanced chips.
Schmidt noted the US alone may require an extra 92 gigawatts of electricity to support AI growth, equivalent to dozens of nuclear power stations.
Instead of waiting for new plants, companies such as Microsoft are seeking to retrofit closed facilities, including the Three Mile Island plant targeted for relaunch in 2028.
Schmidt highlighted growing environmental pressures, citing Microsoft’s 34% increase in water use within a year, a trend experts link directly to rising AI workloads.
Major AI developers like OpenAI’s Sam Altman also acknowledge energy as a key constraint. Altman has invested in nuclear fusion through Helion, while firms such as Microsoft and AMD are pressing US policymakers to fast-track energy permits.
Environmental groups, including Greenpeace, warn that unchecked AI expansion risks undermining climate goals instead of supporting them.
Schmidt believes superintelligence is inevitable and approaching rapidly, predicting specialised AI tools across all fields within five years. Rather than focusing solely on AI’s capabilities, he stressed the urgent need for planning energy infrastructure today to match tomorrow’s AI demands.
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NVIDIA’s CEO has praised China’s open-source AI work during a high-profile visit to Beijing, spotlighting DeepSeek as an example of world-class science and engineering.
At the International Supply Chain Expo, Huang highlighted the global value of Chinese contributions to AI research.
He told former Alibaba executive Wang Jian that Chinese researchers publish more AI papers than any other nation, calling their output A-plus in both science and engineering. Huang named DeepSeek, Alibaba, Tencent, MiniMax, and Baidu’s Ernie Bot globally significant AI leaders.
The visit coincides with a policy shift by the US government allowing Nvidia to resume H20 chip exports to China. Huang confirmed that export licenses are expected soon, potentially unlocking billions in lost revenue.
Industry watchers see this development as pivotal for Nvidia, which had paused shipments under earlier restrictions. The chipmaker’s renewed access to China’s semiconductor market could reshape global AI infrastructure over the next year.
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