Semiconductors

IBM sets 2029 target for quantum breakthrough

IBM has set out a detailed roadmap to deliver a practical quantum computer by 2029, marking a major milestone in its long-term strategy.

The company plans to build its ‘Starling’ quantum system at a new data centre in Poughkeepsie, New York, targeting around 200 logical qubits—enough to begin outperforming classical computers in specific tasks instead of lagging due to error correction limitations.

Quantum computers rely on qubits to perform complex calculations, but high error rates have held back their potential. IBM shifted its approach in 2019, designing error-correction algorithms based on real, manufacturable chips instead of theoretical models.

The change, as the company says, will significantly reduce the qubits needed to fix errors.

With confidence in its new method, IBM will build a series of quantum systems until 2027, each advancing toward a larger, more capable machine.

Vice President Jay Gambetta stated the key scientific questions have already been resolved, meaning what remains is primarily an engineering challenge instead of a scientific one.

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AI chip boom fuels TSMC revenue surge

Taiwan Semiconductor Manufacturing Co. (TSMC), the world’s leading contract chipmaker, reported a significant 39.6% year-over-year surge in May revenue, reaching NT$320.52 billion ($10.70 billion).

This robust growth is primarily attributed to sustained high demand for its AI chips. The company, a key supplier to tech giants like Apple and Nvidia, has seen its US-listed shares rise over 2% in premarket trading, extending their 5% gain so far this year.

Despite May’s revenue being down 8% from April’s figure, the chipmaker’s January-to-May revenue climbed nearly 43% compared to the same period last year, reaching NT$1.51 trillion.

This strong performance underpins TSMC’s ambitious expansion plans, including a previously announced intent to invest $100 billion in U.S.-based chip-manufacturing facilities.

TSMC CEO C.C. Wei reiterated the company’s full-year 2025 revenue projection in April, anticipating an increase of ‘close to mid-20s percent in US dollar terms.’

The continued strong demand for AI chips is expected to be a major driver in achieving these financial targets, solidifying TSMC’s critical role in the global technology landscape.

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Qualcomm to acquire Alphawave for $2.4 billion

Qualcomm has agreed to acquire London-listed semiconductor firm Alphawave for approximately $2.4 billion in cash, aiming to strengthen its position in AI and data centre technologies. Alphawave shares surged 23% in London trading following the announcement.

The deal, offering 183 pence per share, represents a 96% premium over Alphawave’s share price at the end of March. Regulatory and shareholder approvals are still required, with the transaction expected to close in early 2026.

Qualcomm is diversifying beyond smartphones as CEO Cristiano Amon targets growth sectors such as AI hardware. Alphawave, known for high-speed chip connectivity, has gained momentum, especially among US AI customers.

Alphawave’s board unanimously supports the offer, and shareholders representing half the company have already agreed to the deal. In addition to the cash option, Qualcomm is offering stock and security exchange alternatives.

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Quantum light beats AI at its own game in surprise photonic experiment

A small-scale quantum device developed by researchers at the University of Vienna has outperformed advanced classical machine learning algorithms—including some used in today’s leading AI systems—using just two photons and a glass chip.

The experiment suggests that useful quantum advantage could arrive far sooner than previously thought, not in massive future machines but in today’s modest photonic setups.

The team’s six-mode processor doesn’t rely on raw speed to beat traditional systems. Instead, it harnesses a uniquely quantum property: the way identical particles interfere. This interference naturally computes mathematical structures known as permanents, which are computationally expensive for classical systems.

By embedding these quantum calculations into a pattern-recognition task, the researchers consistently achieved higher classification accuracy across multiple datasets.

Crucially, the device operates with extreme energy efficiency, offering a promising route to sustainable AI. Co-author Iris Agresti highlighted the growing energy costs of modern machine learning and pointed to photonic quantum systems as a potential solution.

These early results could pave the way for new applications in areas where training data is limited and classical methods fall short—redefining the future of AI and quantum computing alike.

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SoftBank and Intel develop low-power memory for AI data centres

SoftBank and Intel are collaborating on a new memory technology designed to halve power consumption compared to current high-bandwidth memory (HBM), which is critical for AI systems.

The project includes the University of Tokyo, research institute Riken, and Shinco Electric Industries, among others, and aims to address cost, efficiency, and supply issues in today’s HBM market.

The initiative will be led by a newly established SoftBank subsidiary, Cy Memory, which is tasked with IP management and developing prototype memory chips that reconfigure wiring structures in stacked DRAMs.

The goal is to mass-produce more energy-efficient and cost-effective memory than existing HBM, with applications in data centres running AI workloads.

SoftBank plans to invest 3 billion yen in Cy Memory, becoming its largest shareholder, and may seek government funding.

As AI data centre demand skyrockets, the new memory could offer Japan a strategic edge in semiconductor development—particularly as domestic DRAM production has largely disappeared. Japan has pledged over 10 trillion yen in semiconductor investments by 2030 to revive its chip industry.

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Broadcom beats estimates but stock dips after-hours

Broadcom reported strong second-quarter earnings and revenue driven by robust AI demand and solid networking performance.

Despite beating expectations and raising its outlook, the stock fell 3.47% in after-hours trading on Thursday — likely due to profit-taking instead of concern about fundamentals. Shares had previously rallied over 75% since April.

Revenue for the quarter ending May 5 reached US$15 billion, up 20% year-on-year. Adjusted earnings per share were US$1.58, exceeding estimates by two cents.

Net income more than doubled to US$4.97 billion. CEO Hock Tan attributed the strength to growing demand for AI infrastructure and contributions from VMware, which Broadcom acquired in late 2023.

Broadcom forecasted Q3 revenue of approximately US$15.8 billion, slightly above analyst expectations. AI-related revenue is set to increase to US$5.1 billion, up from US$4.4 billion in Q2, fuelled by custom AI accelerators and high-speed networking chips used in hyperscale data centres.

Tan said that the trend should continue through fiscal 2026.

Semiconductor solutions brought in US$8.4 billion in Q2, up 17% from last year, while software revenue rose 25% to US$6.6 billion, with VMware as a key contributor.

About 30% of Broadcom’s AI-related revenue now comes from its switching business, reflecting increasing demand for AI chip clusters. Despite the slight dip in share price, analysts continue to view Broadcom as a key player in AI infrastructure.

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Semiconductor innovation drives AI chip boom

The global AI chip design market is set for explosive growth, with its value projected to rise from USD 73.87 billion in 2024 to USD 468.9 billion by 2032.

This rapid expansion, driven by a 25.98% compound annual growth rate, reflects rising demand for AI in everyday devices, cloud computing, and industrial automation.

Surging adoption of AI-powered technologies across sectors—from smartphones and autonomous vehicles to manufacturing and healthcare—is fuelling the need for advanced, energy-efficient chips.

Companies are investing in smaller, faster processors and real-time edge computing solutions, while governments in countries like the US, China, and South Korea are backing local AI chip development through funding and research initiatives.

North America currently leads the market thanks to tech giants like NVIDIA, Google, and Intel, but Asia-Pacific is growing fastest, particularly as China and South Korea accelerate efforts toward self-reliance in AI hardware.

Industry leaders such as Arm, Intel, and Qualcomm are racing to optimise performance while managing power demands, placing AI chip design at the heart of the next digital transformation wave.

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EU launches global digital strategy

The European Union has launched a sweeping international digital strategy to bolster its global tech leadership and secure a human-centric digital transformation. With the digital and AI revolution reshaping economies and societies worldwide, the EU is positioning itself as a reliable partner in building resilient, open, and secure digital ecosystems.

The strategy prioritises collaboration with international partners to scale digital infrastructure, strengthen cybersecurity, and support emerging technologies like AI, quantum computing, and semiconductors while promoting democratic values and human rights in digital governance. The EU will deepen and expand its global network of Digital Partnerships and Dialogues to remain competitive and secure in a fast-changing geopolitical landscape.

These collaborations focus on research, industrial innovation, regulatory cooperation, and secure supply chains, while engaging countries across Africa, Latin America, Asia, and the EU’s own neighbourhood. The strategy also leverages trade instruments and investment frameworks such as the Global Gateway to support secure 5G and 6G networks, submarine cables, and digital public infrastructure, helping partner countries improve connectivity, resilience, and sustainability.

To enhance global digital governance, the EU is pushing for international standards that uphold privacy, security, and openness, and opposing efforts to fragment the internet. It supports inclusive multilateralism, working through institutions like the UN, G7, and OECD to shape rules for the digital age.

With initiatives ranging from AI safety cooperation and e-signature mutual recognition to safeguarding children online and combating disinformation, the EU aims to set the benchmark for ethical and secure digital transformation. At the heart of this vision is the EU Tech Business Offer—a modular, cross-border platform combining technology, capacity-building, and financing.

Through Team Europe and partnerships with industry, the EU seeks to bridge the digital divide, export trusted digital solutions, and foster an interconnected world aligned with European democratic principles. The strategy underscores that in today’s interconnected world, the EU’s prosperity and security hinge on shaping a digital future that is competitive, inclusive, and values-driven.

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Chinese tech firms thrive amid US curbs

Nvidia CEO Jensen Huang has raised concerns that US export restrictions are accelerating the growth of Chinese AI firms, making them more competitive. In a recent interview, Huang highlighted that companies like Huawei — long blacklisted by the US — have become ‘formidable’ rivals.

The restrictions have hit Nvidia hard, with the company projecting an $8 billion revenue loss this quarter due to the limited access to the Chinese market, historically its largest for chips. The Biden administration’s AI diffusion rule, aimed at controlling the spread of advanced AI technologies, had already drawn criticism from Huang before being partially rolled back by the Trump administration in May.

Yet, Nvidia still faces tough restrictions, including a ban on selling even its downgraded H20 chip to China. The company was recently notified that it would need a special license to export the chip, leaving it with no viable alternative for the Chinese market.

Huang warned that efforts to keep cutting-edge AI tech out of China have largely backfired, as Chinese firms are finding workarounds and quickly catching up.

‘They’re doubling or quadrupling capabilities every year,’ he noted, stressing that the performance of Huawei’s latest AI chip now rivals Nvidia’s once-leading H200.

Despite Nvidia’s strong recent performance, Huang emphasised the long-term importance of re-engaging with China, home to the world’s largest community of AI researchers. He urged US policymakers to reconsider their approach, advocating for broader access to American AI technology to maintain leadership and influence in the global AI ecosystem.

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PREVAIL to offer advanced Edge AI chip design tools across Europe

The European Union’s PREVAIL project is preparing to open its Edge AI services to external users in June 2025.

Coordinated by Europe’s top research and technology organisations, the initiative offers a shared, multi-hub infrastructure designed to speed up the development and commercialisation of next-generation Edge AI technologies.

Through its platform, European designers will gain access to advanced chip prototyping capabilities and full design support using standard commercial tools.

PREVAIL combines commercial foundry processes with advanced technology modules developed in partner clean rooms. These include embedded non-volatile memories (eNVM), silicon photonics, and 3D integration technologies such as silicon interposers and packaging innovations.

Initial demonstrators, already in development with industry partners, will serve as test cases to ensure compatibility with a broad range of applications and future scalability.

From July 2025, a €20 million EU-funded call under the ‘Low Power Edge AI’ initiative will help selected customers co-finance their access to the platform. Whether supported by EU funds or independently financed, users will be able to design chips using one of four shared platforms.

The consortium has also set up a user interface team to manage technical support and provide access to Process Design Kits and Design Rule Manuals.

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