Semiconductors

Sam Altman reverses his stance on AI hardware as current computers can’t meet the demands

Sam Altman, CEO of OpenAI, has returned from his earlier position, saying that AGI would not need new hardware.

Speaking on a podcast with his brother, Altman said current computers are no longer suited for the fast-evolving demands of AI. Instead of relying on standard hardware, he now believes new solutions are necessary.

OpenAI has already started developing dedicated AI hardware, including potential custom chips, marking a shift from using general-purpose GPUs and servers.

Altman also hinted at a new device — not a wearable, nor a phone — that could serve as an AI companion. Designed to be screen-free and aware of its surroundings, the product is being co-developed with former Apple design chief Jony Ive.

The collaboration, however, has run into legal trouble. A federal judge recently ordered OpenAI and Ive to pause the promotion of the new venture after a trademark dispute with a startup named IYO, which had previously pitched similar ideas to Altman’s investment firm.

OpenAI’s recent $6.5 billion acquisition of io Products, co-founded by Ive, reflects the company’s more profound commitment to reshaping how people interact with AI.

Altman’s revised stance on hardware suggests the era of purpose-built AI devices is no longer a vision but a necessary reality.

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SoftBank shifts focus to AI and next-generation chips

Masayoshi Son, founder and CEO of SoftBank, has indicated his readiness to pass the leadership baton after decades at the helm. Speaking to shareholders in Tokyo, the 67-year-old entrepreneur said he had mentally prepared to step aside and had already identified internal candidates.

However, he noted that revealing a successor prematurely could affect dynamics within the company.
While succession planning is underway, Son focuses on positioning SoftBank as a global leader in artificial superintelligence (ASI).

The company is pursuing aggressive investments, including a proposed $30 billion stake in OpenAI, the acquisition of UK-based Graphcore, and a potential purchase of US firm Ampere Computing.

Plans are also in motion to build a central tech hub in Arizona, modelled on Shenzhen, featuring advanced chip infrastructure and a possible partnership with TSMC.

SoftBank’s reach extends well beyond the US and Japan. India has invested over $10 billion across 24 companies, including Paytm, Ola Electric, and Swiggy. These ventures have spurred rapid growth and successful IPOs, reinforcing SoftBank’s influence over the country’s digital economy.

Shareholder confidence plays a crucial role in sustaining SoftBank’s bold innovation strategy. Many Japanese retail investors have remained loyal for decades, drawn by Son’s enduring vision and the promise of future breakthroughs.

With AI now firmly at the centre of SoftBank’s roadmap, the company is betting big on a future it hopes to shape.

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DeepSeek struggles to launch R2 amid NVIDIA chip shortage

The launch of DeepSeek’s next-generation AI model, R2, is expected to face delays due to a shortage of NVIDIA H20 chips in China.

These chips, designed specifically for the Chinese market following US export restrictions, are essential for running DeepSeek’s highly optimised models.

The ban on H20 shipments in April has triggered widespread concern among cloud providers about the scalability of R2, especially if it outperforms existing open-source models.

CEO Liang Wenfeng has reportedly held back the model’s release, expressing dissatisfaction with its current performance.

Engineers continue refining R2, but the lack of compatible hardware poses a deeper challenge. DeepSeek’s reliance on NVIDIA architecture makes switching to Chinese chips inefficient, as the models are tightly built for NVIDIA’s software and hardware ecosystem.

Some Chinese firms have begun using workarounds by flying engineers to Malaysia, where NVIDIA chips are still available in local data centres.

After training their models abroad, teams return to China with trained systems. Others rely on gaming GPUs like the RTX 5090, which are easier to access via grey markets despite restrictions.

While Chinese tech giants ordered 1.2 million H20 chips earlier in 2025 to meet demand sparked by R1’s success, inventory is still unlikely to support a full R2 rollout.

Companies outside China may launch R2 more easily without facing the same export hurdles.

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Nvidia becomes world’s most valuable company after stock surge

Nvidia shares hit an all-time high on 25 June, rising 4.3 percent to US$154.31. The stock has surged 63 percent since April, adding another US$1.5 trillion to its market value.

With a total market capitalisation of about US$3.77 trillion, Nvidia has overtaken Microsoft to become the world’s most valuable listed company.

Strong earnings and growing AI infrastructure spending by major clients — including Microsoft, Meta, Alphabet and Amazon — have reinforced investor confidence.

Nvidia’s CEO, Jensen Huang, told shareholders that demand remains strong and that the computer industry is still in the early stages of a major AI upgrade cycle.

Despite gaining 15 percent in 2025, following a 170 percent rise in 2024 and a 240 percent surge in 2023, Nvidia still appears reasonably valued. It trades at 31.5 times forward earnings, below its 10-year average and close to the Nasdaq 100 multiple, even though its projected growth rate is higher.

Analyst sentiment remains firmly bullish. Nearly 90 percent of analysts tracked by Bloomberg recommend buying the stock, which trades below their average price target.

Yet, Nvidia is less widely held among institutional investors than peers like Microsoft and Apple, indicating further room for buying as AI momentum continues into 2026.

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SoftBank plans $1 trillion AI and robotics park in Arizona

SoftBank founder Masayoshi Son is planning what could become his most audacious venture yet: a $1 trillion AI and robotics industrial park in Arizona.

Dubbed ‘Project Crystal Land’, the initiative aims to recreate a high-tech manufacturing hub reminiscent of China’s Shenzhen, focused on AI-powered robots and next-gen automation.

Son is courting global tech giants — including Taiwan Semiconductor Manufacturing Co. (TSMC) and Samsung — to join the vision, though none have formally committed.

The plan hinges on support from federal and state governments, with SoftBank already discussing possible tax breaks with US officials, including Commerce Secretary Howard Lutnick.

While TSMC is already investing $165 billion in Arizona facilities, sources suggest Son’s project has not altered the chipmaker’s current roadmap. SoftBank hopes to attract semiconductor and AI hardware leaders to power the park’s infrastructure.

Son has also approached SoftBank Vision Fund portfolio companies to participate, including robotics startup Agile Robots.

The park may serve as a production hub for emerging tech firms, complementing SoftBank’s broader investments, such as a potential $30 billion stake in OpenAI, a $6.5 billion acquisition of Ampere Computing, and funding for Stargate, a global data centre venture with OpenAI, Oracle, and MGX.

While the vision is still early, Project Crystal Land could radically shift US high-tech manufacturing. Son’s strategy relies heavily on project-based financing, allowing extensive infrastructure builds with minimal upfront capital.

As SoftBank eyes long-term AI growth and increased investor confidence, whether this futuristic park will become a reality — or another of Son’s high-stakes dreams remains to be seen.

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Pasqal opens Canada factory, sells quantum computer to Distriq

French quantum computing firm Pasqal has deepened its North American presence by selling a 100-qubit quantum processor and opening a significant manufacturing facility in Sherbrooke, Québec.

The processor was sold to Distriq, a quantum innovation hub in Sherbrooke, which aims to strengthen Québec’s growing quantum technology ecosystem.

The deal was backed by a CA$9.6 million (US$7.1m) loan from the Québec Ministry of Economy, Innovation and Energy and Investissement Québec, alongside CA$2.4 million (US$1.8m) from the National Bank of Canada and CA$1.2 million (US$883,000) from Canada Economic Development for Québec Regions.

Pasqal confirmed that the system would be manufactured and installed in Sherbrooke and made available to Canadian researchers and industries.

The firm also inaugurated its first North American manufacturing site—its second globally—in Sherbrooke’s 50,000 sq ft Espace Quantique 1 building. The facility will focus on producing Pasqal’s next-generation quantum processors.

The factory was supported by a CA$15 million (US$11m) loan from Investissement Québec, positioning Pasqal among Canada’s most significant quantum players.

‘These achievements signal that quantum computing is no longer a future promise—it has become a reality today,’ said Wasiq Bokhari, Pasqal’s executive chairman.

Distriq VP Mehdi Bozzo-Rey called the acquisition a ‘major milestone’ in supplying Québec with industrial quantum capabilities.

Founded in 2019, Pasqal counts Nobel Laureate Alain Aspect among its co-founders. The company has installed systems in Saudi Arabia and Germany, and in early June 2025, it acquired Canadian photonics company Aeponyx to bolster its hardware capabilities.

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Oxford physicists set new qubit accuracy record

Physicists at the University of Oxford have achieved a ground‑breaking error rate in quantum logic operations, reducing it to just 0.000015 percent, one mistake in 6.7 million operations. The result marks nearly a ten‑fold improvement over their previous record set in 2014.

The team used a trapped calcium ion qubit controlled by microwave signals instead of lasers to achieve high stability at room temperature and eliminate the need for magnetic shielding. However, this method offers cheaper, more robust control that fits with ion‑trap chip technology.

Reducing the error rate helps shrink the infrastructure needed for error correction, meaning future quantum computers could be smaller, faster and more efficient. They still lag, with around one in 2,000 error rates, highlighting further challenges for full‑scale quantum systems.

The findings, published in Physical Review Letters, bring practical quantum computing a significant step closer. The Oxford researchers involved include Professor David Lucas, Molly Smith, Aaron Leu and Dr Mario Gely.

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Taiwan tightens rules on chip shipments to China

Taiwan has officially banned the export of chips and chiplets to China’s Huawei and SMIC, joining the US in tightening restrictions on advanced semiconductor transfers.

The decision follows reports that TSMC, the world’s largest contract chipmaker, was unknowingly misled into supplying chiplets used in Huawei’s Ascend 910B AI accelerator. The US Commerce Department had reportedly considered a fine of over $1 billion against TSMC for that incident.

Taiwan’s new rules aim to prevent further breaches by requiring export permits for any transactions with Huawei or SMIC.

The distinction between chips and chiplets is key to the case. Traditional chips are built as single-die monoliths using the same process node, while chiplets are modular and can combine various specialised components, such as CPU or AI cores.

Huawei allegedly used shell companies to acquire chiplets from TSMC, bypassing existing US restrictions. If TSMC had known the true customer, it likely would have withheld the order. Taiwan’s new export controls are designed to ensure stricter oversight of future transactions and prevent repeat deceptions.

The broader geopolitical stakes are clear. Taiwan views the transfer of advanced chips to China as a national security threat, given Beijing’s ambitions to reunify with Taiwan and the potential militarisation of high-end semiconductors.

With Huawei claiming its processors are nearly on par with Western chips—though analysts argue they lag two to three generations behind—the export ban could further isolate China’s chipmakers.

Speculation persists that Taiwan’s move was partly influenced by negotiations with the US to avoid the proposed fine on TSMC, bringing both countries into closer alignment on chip sanctions.

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New ion trap chip paves way for scalable quantum systems

Researchers at the Quantum Systems Accelerator have announced significant progress in building scalable, stable quantum computers focusing on trapped-ion technology.

Their work marks a series of engineering milestones pushing quantum computing toward practical use.

A new ion trap chip can store up to 200 ions and significantly reduces power loss by redesigning its internal layout.

Developed and tested with collaborators at Duke and Cornell in the US, this design allows for the future creation of far larger qubit systems without overheating or energy waste.

At the University of Maryland, a team achieved parallel quantum gate operations using different spatial directions, overcoming prior interference issues.

However, this innovation boosts processing speed and accuracy, offering more efficient handling of time-sensitive quantum tasks.

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Nvidia announces new AI lab in UK and supercomputing wins in Europe

What began as a company powering 3D games in the 1990s has evolved into the backbone of the global AI revolution. Nvidia, once best known for its Riva TNT2 chips in consumer graphics cards like the Elsa Erazor III, now sits at the centre of scientific computing, defence, and national-scale innovation.

While gaming remains part of its identity—with record revenue of $3.8 billion in Q1 FY2026—it now accounts for less than 9% of Nvidia’s $44.1 billion total revenue. The company’s trajectory reflects its founder Jensen Huang’s ambition to lead beyond the gaming space, targeting AI, supercomputing, and global infrastructure.

Recent announcements reinforce this shift. Huang joined UK Prime Minister Sir Keir Starmer to open London Tech Week, affirming Nvidia’s commitment to launch an AI lab in the UK, as the government commits £1 billion to AI compute by 2030.

Nvidia also revealed its Rubin-Vera superchip will power Germany’s ‘Blue Lion’ supercomputer, and its Grace Hopper platform is at the heart of Jupiter—Europe’s first exascale AI system, located at the Jülich Supercomputing Centre.

Nvidia’s presence now spans continents and disciplines, from powering national research to driving breakthroughs in climate modelling, quantum computing, and structural biology.

‘AI will supercharge scientific discovery and industrial innovation,’ said Huang. And with systems like Jupiter poised to run a quintillion operations per second, the company’s growth story is far from over.

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