China's Chip Challenge: The Race to Match US Tech

Ramping up its chip industry is a way for Beijing to beat restrictions imposed by Washington on exports of the most advanced chips -- used to power AI systems -- to China. STR / AFP/File
Ramping up its chip industry is a way for Beijing to beat restrictions imposed by Washington on exports of the most advanced chips -- used to power AI systems -- to China. STR / AFP/File
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China's Chip Challenge: The Race to Match US Tech

Ramping up its chip industry is a way for Beijing to beat restrictions imposed by Washington on exports of the most advanced chips -- used to power AI systems -- to China. STR / AFP/File
Ramping up its chip industry is a way for Beijing to beat restrictions imposed by Washington on exports of the most advanced chips -- used to power AI systems -- to China. STR / AFP/File

China's push to develop top-end artificial intelligence microchips is gaining momentum, but analysts say it will struggle to match the technical might of US powerhouse Nvidia within the current decade.

Ramping up its chip industry is a way for Beijing to beat restrictions imposed by Washington on exports of the most advanced chips -- used to power AI systems -- to China.

The United States cites national security concerns, such as the risk of giving China a military advantage, for the block, a geopolitical bind that shows no sign of easing.

"China wants chips that policy cannot take away," said Stephen Wu, a former AI software engineer and founder of the Carthage Capital investment fund.

However, "full end-to-end parity with Nvidia's best chips, memory packaging, networking and software is not guaranteed" by 2030 or even beyond, Wu told AFP.

Announcements of computing upgrades by Chinese companies and reports of plans to dramatically increase output of advanced semiconductors have driven up chip-related shares in the country.

But to catch up with Nvidia, China needs to make fast progress on high-bandwidth memory and packaging -- "the hardest and most complex parts of the chip", Wu said.

Other challenges include building the right software to harness the chips' power, and upgrading manufacturing tools.

"These chips are extremely advanced and tiny, so imagine carving a stone sculpture with a hammer instead of a chisel," Wu said.

'Only way' to succeed

"The industry consensus is China at least needs five to ten years to catch up," said George Chen of The Asia Group, a view reflected by Dilin Wu, research strategist at Pepperstone.

"The future is bright, but not yet," she told AFP.

"It's maybe a 2030 story", as "significant gaps remain in terms of performance, and also in terms of energy efficiency and ecosystem maturity".

Public demand for AI services is booming in China, and while government support for new chips is "substantial", the investment required is "immense", she added.

Shares in Alibaba, the e-commerce titan ploughing billions of dollars into AI tech, have more than doubled since January.

And Chinese chip industry leader Huawei will reportedly double output of its top Ascend 910C chip in the next year.

The hype has also sharply driven up stocks in the smaller chipmaker Cambricon, sometimes dubbed "China's Nvidia".

"I think this rally can be sustained", partly because it is driven by Chinese government policy, Pepperstone's Wu said.

Even Xiaomi, whose 2014 venture into chip design was a self-confessed flop, is turning back to semiconductors.

"Chips are the only way for Xiaomi to succeed," the company's CEO Lei Jun said in Beijing last month, referring to the production of high-end smartphone chips.

'Best in China'

China, the world's biggest consumer of semiconductors, is a huge market for California-based Nvidia.

Nvidia chips are still "the best... to train large language models", the systems behind generative AI, said Chen Cheng, general manager for AI translation software at tech firm iFLYTEK.

Faced with US restrictions, "we overcame that difficulty" by shifting to Chinese-made tech, she said in a group interview.

"Now our model is trained on Huawei chips" -- currently the best in China, Cheng said.

Meanwhile Nvidia, the world's largest company by market capitalization, is under pressure from both sides.

The Financial Times reported last month that Beijing had barred major Chinese firms from buying a state-of-the-art Nvidia processor made especially for the country.

And the company must now pay the US government 15 percent of revenue from certain AI chip sales in China.

Nvidia boss Jensen Huang has warned that restrictions on exporting his most cutting-edge semiconductors to China will only fuel the country's rise.

"They're nanoseconds behind us," the leather jacket-clad Huang said on a tech business podcast.

"So we've got to go compete."



India Eyes $200B in Data Center Investments as It Ramps Up Its AI Hub Ambitions

FILE -Google CEO Sundar Pichai, right, interacts with India's Minister for Information and Technology Ashwini Vaishnaw during Google for India 2022 event in New Delhi, Dec. 19, 2022. (AP Photo/Manish Swarup), File)
FILE -Google CEO Sundar Pichai, right, interacts with India's Minister for Information and Technology Ashwini Vaishnaw during Google for India 2022 event in New Delhi, Dec. 19, 2022. (AP Photo/Manish Swarup), File)
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India Eyes $200B in Data Center Investments as It Ramps Up Its AI Hub Ambitions

FILE -Google CEO Sundar Pichai, right, interacts with India's Minister for Information and Technology Ashwini Vaishnaw during Google for India 2022 event in New Delhi, Dec. 19, 2022. (AP Photo/Manish Swarup), File)
FILE -Google CEO Sundar Pichai, right, interacts with India's Minister for Information and Technology Ashwini Vaishnaw during Google for India 2022 event in New Delhi, Dec. 19, 2022. (AP Photo/Manish Swarup), File)

India is hoping to garner as much as $200 billion in investments for data centers over the next few years as it scales up its ambitions to become a hub for artificial intelligence, the country’s minister for electronics and information technology said Tuesday.

The investments underscore the reliance of tech titans on India as a key technology and talent base in the global race for AI dominance. For New Delhi, they bring in high-value infrastructure and foreign capital at a scale that can accelerate its digital transformation ambitions.

The push comes as governments worldwide race to harness AI's economic potential while grappling with job disruption, regulation and the growing concentration of computing power in a few rich countries and companies.

“Today, India is being seen as a trusted AI partner to the Global South nations seeking open, affordable and development-focused solutions,” Ashwini Vaishnaw told The Associated Press in an email interview, as New Delhi hosts a major AI Impact Summit this week drawing participation from at least 20 global leaders and a who’s who of the tech industry.

In October, Google announced a $15 billion investment plan in India over the next five years to establish its first artificial intelligence hub in the South Asian country. Microsoft followed two months later with its biggest-ever Asia investment announcement of $17.5 billion to advance India’s cloud and artificial intelligence infrastructure over the next four years.

Amazon too has committed $35 billion investment in India by 2030 to expand its business, specifically targeting AI-driven digitization. The cumulative investments are part of $200 billion in investments that are in the pipeline and New Delhi hopes would flow in.

Vaishnaw said India’s pitch is that artificial intelligence must deliver measurable impacts at scale rather than remain an elite technology.

“A trusted AI ecosystem will attract investment and accelerate adoption,” he said, adding that a central pillar of India’s strategy to capitalize on the use of AI is building infrastructure.

The government recently announced a long-term tax holiday for data centers as it hopes to provide policy certainty and attract global capital.

Vaishnaw said the government has already operationalized a shared computing facility with more than 38,000 graphics processing units, or GPUs, allowing startups, researchers and public institutions to access high-end computing without heavy upfront costs.

“AI must not become exclusive. It must remain widely accessible,” he said.

Alongside the infrastructure drive, India is backing the development of sovereign foundational AI models trained on Indian languages and local contexts. Some of these models meet global benchmarks and in certain tasks rival widely used large language models, Vaishnaw said.

India is also seeking a larger role in shaping how AI is built and deployed globally as the country doesn’t see itself strictly as a “rule maker or rule taker,” according to Vaishnaw, but an active participant in setting practical, workable norms while expanding its AI services footprint worldwide.

“India will become a major provider of AI services in the near future,” he said, describing a strategy that is “self-reliant yet globally integrated” across applications, models, chips, infrastructure and energy.

Investor confidence is another focus area for New Delhi as global tech funding becomes more cautious.

Vaishnaw said the technology’s push is backed by execution, pointing to the Indian government's AI Mission program which emphasizes sector specific solutions through public-private partnerships.

The government is also betting on reskilling its workforce as global concerns grow that AI could disrupt white collar and technology jobs. New Delhi is scaling AI education across universities, skilling programs and online platforms to build a large AI-ready talent pool, the minister said.

Widespread 5G connectivity across the country and a young, tech-savvy population are expected to help with the adoption of AI at a faster pace, he added.

Balancing innovation with safeguards remains a challenge though, as AI expands into sensitive sectors such as governance, health care and finance.

Vaishnaw outlined a fourfold strategy that includes implementable global frameworks, trusted AI infrastructure, regulation of harmful misinformation and stronger human and technical capacity to hedge the impact.

“The future of AI should be inclusive, distributed and development-focused,” he said.


Report: SpaceX Competing to Produce Autonomous Drone Tech for Pentagon 

The SpaceX logo is seen in this illustration taken, March 10, 2025. (Reuters)
The SpaceX logo is seen in this illustration taken, March 10, 2025. (Reuters)
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Report: SpaceX Competing to Produce Autonomous Drone Tech for Pentagon 

The SpaceX logo is seen in this illustration taken, March 10, 2025. (Reuters)
The SpaceX logo is seen in this illustration taken, March 10, 2025. (Reuters)

Elon Musk's SpaceX and its wholly-owned subsidiary xAI are competing in a secret new Pentagon contest to produce voice-controlled, autonomous drone swarming technology, Bloomberg News reported on Monday, citing people familiar with the matter.

SpaceX, xAI and the Pentagon's defense innovation unit did not immediately respond to requests for comment. Reuters could not independently verify the report.

Texas-based SpaceX recently acquired xAI in a deal that combined Musk's major space and defense contractor with the billionaire entrepreneur's artificial intelligence startup. It occurred ahead of SpaceX's planned initial public offering this year.

Musk's companies are reportedly among a select few chosen to participate in the $100 million prize challenge initiated in January, according to the Bloomberg report.

The six-month competition aims to produce advanced swarming technology that can translate voice commands into digital instructions and run multiple drones, the report said.

Musk was among a group of AI and robotics researchers who wrote an open letter in 2015 that advocated a global ban on “offensive autonomous weapons,” arguing against making “new tools for killing people.”

The US also has been seeking safe and cost-effective ways to neutralize drones, particularly around airports and large sporting events - a concern that has become more urgent ahead of the FIFA World Cup and America250 anniversary celebrations this summer.

The US military, along with its allies, is now racing to deploy the so-called “loyal wingman” drones, an AI-powered aircraft designed to integrate with manned aircraft and anti-drone systems to neutralize enemy drones.

In June 2025, US President Donald Trump issued the Executive Order (EO) “Unleashing American Drone Dominance” which accelerated the development and commercialization of drone and AI technologies.


SVC Develops AI Intelligence Platform to Strengthen Private Capital Ecosystem

The platform offers customizable analytical dashboards that deliver frequent updates and predictive insights- SPA
The platform offers customizable analytical dashboards that deliver frequent updates and predictive insights- SPA
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SVC Develops AI Intelligence Platform to Strengthen Private Capital Ecosystem

The platform offers customizable analytical dashboards that deliver frequent updates and predictive insights- SPA
The platform offers customizable analytical dashboards that deliver frequent updates and predictive insights- SPA

Saudi Venture Capital Company (SVC) announced the launch of its proprietary intelligence platform, Aian, developed in-house using Saudi national expertise to enhance its institutional role in developing the Kingdom’s private capital ecosystem and supporting its mandate as a market maker guided by data-driven growth principles.

According to a press release issued by the SVC today, Aian is a custom-built AI-powered market intelligence capability that transforms SVC’s accumulated institutional expertise and detailed private market data into structured, actionable insights on market dynamics, sector evolution, and capital formation. The platform converts institutional memory into compounding intelligence, enabling decisions that integrate both current market signals and long-term historical trends, SPA reported.

Deputy CEO and Chief Investment Officer Nora Alsarhan stated that as Saudi Arabia’s private capital market expands, clarity, transparency, and data integrity become as critical as capital itself. She noted that Aian represents a new layer of national market infrastructure, strengthening institutional confidence, enabling evidence-based decision-making, and supporting sustainable growth.

By transforming data into actionable intelligence, she said, the platform reinforces the Kingdom’s position as a leading regional private capital hub under Vision 2030.

She added that market making extends beyond capital deployment to shaping the conditions under which capital flows efficiently, emphasizing that the next phase of market development will be driven by intelligence and analytical insight alongside investment.

Through Aian, SVC is building the knowledge backbone of Saudi Arabia’s private capital ecosystem, enabling clearer visibility, greater precision in decision-making, and capital formation guided by insight rather than assumption.

Chief Strategy Officer Athary Almubarak said that in private capital markets, access to reliable insight increasingly represents the primary constraint, particularly in emerging and fast-scaling markets where disclosures vary and institutional knowledge is fragmented.

She explained that for development-focused investment institutions, inconsistent data presents a structural challenge that directly impacts capital allocation efficiency and the ability to crowd in private investment at scale.

She noted that SVC was established to address such market frictions and that, as a government-backed investor with an explicit market-making mandate, its role extends beyond financing to building the enabling environment in which private capital can grow sustainably.

By integrating SVC’s proprietary portfolio data with selected external market sources, Aian enables continuous consolidation and validation of market activity, producing a dynamic representation of capital deployment over time rather than relying solely on static reporting.

The platform offers customizable analytical dashboards that deliver frequent updates and predictive insights, enabling SVC to identify priority market gaps, recalibrate capital allocation, design targeted ecosystem interventions, and anchor policy dialogue in evidence.

The release added that Aian also features predictive analytics capabilities that anticipate upcoming funding activity, including projected investment rounds and estimated ticket sizes. In addition, it incorporates institutional benchmarking tools that enable structured comparisons across peers, sectors, and interventions, supporting more precise, data-driven ecosystem development.