Semiconductors

Malaysia under scrutiny over semiconductor exports to China

Malaysia plans to tighten regulations on semiconductor shipments following US concerns over the potential transfer of high-end Nvidia chips to China.

Trade Minister Zafrul Aziz stated that the United States has urged Malaysia to closely monitor shipments, ensuring that advanced AI chips do not end up in unauthorised locations.

The move comes amid increasing global scrutiny over AI-related technology exports.

Authorities in Malaysia are also investigating whether local laws were breached in a case involving servers linked to a Singapore fraud investigation.

The case involves transactions worth $390 million, and reports suggest that some servers may have contained Nvidia chips subject to US export controls. Singapore media have linked the matter to potential transfers to Chinese AI company DeepSeek.

The United States has been tightening restrictions on advanced semiconductor exports to China, particularly chips crucial to AI development.

Malaysia’s role as a key semiconductor hub has drawn greater attention, with US officials pushing for stricter oversight.

The government is expected to introduce measures to ensure compliance with international regulations while maintaining its position in the global chip supply chain.

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FuriosaAI rejects $800m acquisition offer from Meta

FuriosaAI, a South Korean startup specialising in AI chips, has reportedly turned down an $800 million acquisition offer from Meta.

Instead of selling, FuriosaAI plans to continue developing its AI chips. Disagreements over post-acquisition business strategy and organisational structure were reportedly the cause of the breakdown in negotiations, rather than issues over price.

Meta, which has been trying to reduce its reliance on Nvidia for chips specialised in training large language models (LLMs), unveiled its custom AI chips last year. The company also announced plans to invest up to $65 billion this year to support its AI initiatives.

FuriosaAI, founded in 2017 by June Paik, who previously worked at Samsung Electronics and AMD, has developed two AI chips—Warboy and Renegade (RNGD).

The startup is also in talks to raise approximately $48 million and is planning to launch the RNGD chips later this year, with LG AI Research already testing them for use in its AI infrastructure.

FuriosaAI’s decision to focus on expanding its chip production signals its confidence in competing with giants like Nvidia and AMD in the rapidly growing AI hardware market.

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AMD vs Intel in the CPU market battle

The competition between AMD and Intel remains intense, despite Intel’s larger market share. In recent years, AMD has emerged as the preferred choice for gamers, often topping sales charts, including Amazon’s CPU best-sellers list.

Just yesterday, AMD dominated the top 15 spots instead of Intel. Surprisingly, the top processor was AMD’s Ryzen 7 9800X3D, a high-end gaming chip, priced at $480, despite its occasional stock shortages.

The top 15 list featured a mix of older and newer AMD processors, such as the Ryzen 5 5500 and Ryzen 5 5600X, indicating that AMD has successfully kept older hardware relevant and in demand.

However, today’s best-seller list paints a slightly different picture, as Intel has managed to secure several spots, with older models like the Alder Lake chips offering more affordable alternatives to current AMD processors.

Interestingly, Intel’s latest Arrow Lake processors did not make it to the top 50 best-sellers on Amazon. This suggests that many customers prefer the more affordable Intel options or turn to AMD, which has shifted the market dynamics significantly in recent years.

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Semiconductor design set for AI revolution with new Synopsys tool

Synopsys has introduced AgentEngineer, an AI-powered technology designed to streamline semiconductor design by automating complex engineering tasks.

The company, which provides software for chip design, aims to help engineers cope with increasing demands as semiconductor firms like Nvidia build advanced AI server systems with thousands of chips.

CEO Sassine Ghazi highlighted the growing pressure on engineers to manage complexity, meet tight deadlines, and control costs.

The AI-driven tool will initially assist human engineers by handling specific tasks, such as verifying circuit designs. Over time, it is expected to coordinate the development of intricate systems comprising multiple chips and components, ensuring efficient project delivery.

The company’s technology and development lead, Shankar Krishnamoorthy, emphasised that AI will be crucial in expanding research and development capacity without requiring larger engineering teams.

With the pace of AI computing accelerating, semiconductor companies face mounting challenges in chip design. Synopsys believes AI will play a critical role in overcoming these difficulties, making the process faster and more efficient.

The new technology is part of a broader industry shift toward AI-driven automation in engineering.

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Ampere Computing joins SoftBank in AI-focused expansion

SoftBank has announced a $6.5 billion acquisition of US chip startup Ampere Computing, marking a major step in its investment in AI infrastructure.

The deal, paid entirely in cash, reflects founder Masayoshi Son’s growing focus on AI as a transformative technology. Ampere produces data centre CPUs based on an architecture from SoftBank’s majority-owned Arm Holdings, with customers including Oracle.

The acquisition follows a series of multi-billion-dollar AI investments by SoftBank, including funding for OpenAI, the Stargate AI data centre project, and Cristal, an AI services joint venture in Japan.

Ampere, founded in 2018 by former Intel president Renee James, developed its own custom CPU cores—an approach typically seen in larger firms like Apple and Qualcomm.

Under SoftBank’s ownership, the company will operate alongside Arm, strengthening SoftBank’s growing collection of AI-focused chip technology firms.

Masayoshi Son described the move as part of his vision for ‘artificial super intelligence,’ highlighting the need for advanced computing power.

While SoftBank has seen mixed results in past investments, such as its troubled backing of WeWork, the company continues to place high-stakes bets on emerging technologies.

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Nvidia introduces high-performance AI machines for the future

At GTC 2025, Nvidia CEO Jensen Huang unveiled a new generation of AI-focused personal supercomputers designed to redefine computing in the era of AI. The two new machines, DGX Spark and DGX Station, are powered by Nvidia’s Grace Blackwell chip platform and promise to deliver unprecedented AI computing power at the edge.

DGX Spark, available immediately, features the GB10 Grace Blackwell Superchip, capable of up to 1,000 trillion operations per second. Meanwhile, the DGX Station, set for release later this year, is built with the GB300 Grace Blackwell Ultra Desktop Superchip and 784GB of memory. According to Nvidia, these supercomputers will allow users to prototype, fine-tune, and deploy AI models with greater efficiency.

Huang described the devices as the future of computing, highlighting their role in supporting AI applications across enterprises. Nvidia has partnered with major manufacturers, including Asus, Dell, HP, and Lenovo, to bring these machines to market. As AI adoption continues to surge, these systems could become essential tools for developers and businesses looking to stay ahead in an increasingly AI-driven world.

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Nvidia holds back on optical technology for GPUs

Nvidia’s CEO, Jensen Huang, has stated that a promising new chip technology, co-packaged optics, is not yet reliable enough for use in the company’s flagship GPUs.

The technology, which uses laser beams to transfer data via fiber optic cables instead of traditional copper, is more energy-efficient and faster.

However, Huang emphasized that copper connections remain ‘orders of magnitude’ more reliable than today’s optical alternatives, making them the preferred choice for now.

Speaking at Nvidia’s annual developer conference in San Jose, Huang announced that the company will use co-packaged optics in two upcoming networking chips designed for server switches, increasing their energy efficiency by three and a half times.

These switch chips will be released later this year and into 2026, marking a gradual technological step forward. However, Huang clarified that Nvidia currently has no plans to implement optical connections between GPUs, as reliability remains a key priority for its AI-focused customers like OpenAI and Oracle.

Silicon Valley startups such as Ayar Labs, Lightmatter, and Celestial AI have invested heavily in co-packaged optics, seeing it as essential for building more powerful AI systems. Nvidia itself has backed some of these ventures, despite Huang’s cautious approach.

While optical connections could eventually help AI models process complex tasks more efficiently, Nvidia is prioritizing proven technology for its near-term roadmap, ensuring stability in an industry preparing to invest hundreds of billions in AI infrastructure.

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Google reduces costs with MediaTek in AI chip development

Google is set to collaborate with Taiwan’s MediaTek on the next generation of its Tensor Processing Unit (TPU) chips, which are expected to be produced next year.

The partnership is partly driven by cost considerations, as MediaTek offers Google a lower price per chip than its long-time partner Broadcom. MediaTek’s close ties with Taiwan Semiconductor Manufacturing Company (TSMC) also played a role in Google’s decision.

Despite the new partnership, Google has not severed ties with Broadcom, which has exclusively worked on its AI chips for several years.

Broadcom remains involved in the project, and an employee at the company confirmed that the relationship with Google is still intact. Google has been developing its own AI server chips, allowing it to reduce reliance on Nvidia, whose processors dominate the industry.

Google introduced its sixth-generation TPU last year to provide itself and its cloud customers with an alternative to Nvidia’s highly sought-after chips. The company reportedly spent between $6 billion and $9 billion on TPUs in 2023, based on revenue targets from Broadcom.

By bringing MediaTek into the fold, Google aims to strengthen its AI chip strategy while managing production costs more efficiently.

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Intel’s new CEO plans major changes to revive the company

Intel’s incoming CEO Lip-Bu Tan is considering major changes to the company’s chip manufacturing and AI strategies to revive the struggling tech giant.

Sources revealed that Tan aims to restructure Intel’s approach to AI and implement staff cuts to streamline operations, focusing on addressing slow-moving middle management.

One of Tan’s core priorities is revamping Intel’s manufacturing operations, which have expanded to include producing semiconductors for external clients like Nvidia.

The changes come as Intel looks to regain its competitive edge after a decade of missed opportunities in smartphone chips and AI processors, allowing competitors such as Arm Holdings and Nvidia to dominate.

At a recent town hall, Tan told employees that the company would need to make ‘tough decisions’ to improve performance. Intel’s shares rose over 8% following his appointment, as investors await further details on his plans.

Tan’s immediate focus includes bolstering Intel Foundry’s performance and attracting new customers in sectors such as AI and robotics.

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Samsung faces tough shareholder meeting over AI struggles

Samsung Electronics faces a challenging annual general meeting as shareholders express frustration over its failure to capitalise on the AI boom.

Despite being South Korea’s most valuable company, Samsung’s stock tumbled nearly a third last year, making it one of the worst-performing tech firms.

Executives, including Co-CEO Han Jong-hee, will address concerns over lagging innovation, competition in semiconductor technology, and strategies to counter US tariffs.

Internal discussions at Samsung have revealed concerns about losing its technological edge, particularly in high bandwidth memory (HBM) chips, where it trails rival SK Hynix.

Chairman Jay Y. Lee reportedly criticised the company for focusing on maintaining the status quo rather than driving major innovation.

A stagnation like this has contributed to Samsung losing market share to competitors like TSMC in chip manufacturing and Apple in smartphones.

Adding to its challenges, Samsung has warned of sluggish AI chip sales due to US export restrictions to China, its biggest market. This puts the company at greater risk from potential US tariffs on Chinese trade.

In an attempt to regain investor confidence, Samsung launched a $7.2 billion share buyback plan in November, which has helped its stock recover slightly. However, shareholders remain sceptical about its future growth strategy.

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