Nvidia chief executive Jensen Huang says the company’s share of China’s artificial intelligence accelerator market has effectively collapsed to zero, delivering one of the starkest warnings yet about the consequences of Washington’s escalating semiconductor export restrictions.

“In China, we have now dropped to zero,” Huang said during an interview with the Special Competitive Studies Project.

The remarks mark one of the clearest acknowledgements yet of how severely U.S. export controls have disrupted Nvidia’s once-dominant position in China, previously one of its most strategically important markets.

Just two years ago, Nvidia controlled the overwhelming majority of China’s AI accelerator market, supplying the advanced GPUs used by Chinese cloud giants, research institutions, and AI startups to train large language models and power hyperscale computing infrastructure.

Now, Huang says Washington’s restrictions have effectively erased Nvidia’s direct commercial foothold in the country.

“Conceding an entire market the size of China probably does not make a lot of strategic sense, so I think that has already largely backfired,” Huang said. “Maybe it made sense at the time, but I think the policy really needs to be dynamic and needs to stay with the times.”

His comments amount to a pointed critique of the increasingly aggressive semiconductor export controls imposed by successive U.S. administrations to curb China’s AI ambitions. Washington has argued the restrictions are necessary to prevent advanced American chips from supporting Chinese military modernization and strategic AI capabilities. But Huang suggested the policy may instead be accelerating China’s technological independence while weakening the global reach of American AI platforms.

The Nvidia chief’s frustration also comes after Washington recently softened parts of its hardline position and signaled willingness to permit exports of some downgraded Nvidia AI chips to China. The Trump administration moved earlier this year to allow shipments of Nvidia’s H20 AI chips to proceed, with White House economic adviser Kevin Hassett saying the decision was intended to preserve America’s technological edge and prevent China from fully replacing U.S. suppliers. The deal includes 15% revenue sharing with the U.S. government.

Washington later began issuing export licenses for some H20 shipments after Nvidia said it had received assurances that approvals would move forward. The H20 chip was specifically designed by Nvidia for the Chinese market after earlier export restrictions blocked sales of its more advanced processors.

But even those efforts to partially reopen the market appear to have run into growing resistance from Beijing itself. Chinese regulators later summoned Nvidia over alleged security concerns tied to the H20 chips, including fears around potential tracking, remote access, and so-called “backdoor” vulnerabilities.

The scrutiny highlighted a new layer of distrust emerging in the technology confrontation between the world’s two largest economies.

Beijing’s concerns are believed to have significantly complicated Nvidia’s efforts to rebuild its China business, even after Washington relaxed some licensing restrictions. The Cyberspace Administration of China reportedly questioned whether U.S.-designed chips could expose Chinese data or critical systems to surveillance or remote intervention capabilities. Nvidia denied the allegations and insisted its chips contain no “backdoors” that would allow remote control or unauthorized access.

For Beijing, the U.S. sanctions appear to have reinforced long-standing concerns that reliance on American technology creates strategic vulnerabilities. Chinese officials have repeatedly warned they would not bow to Washington’s pressure and instead would accelerate domestic innovation and semiconductor self-sufficiency.

The rapid rise of Chinese AI hardware firms now increasingly reflects that strategy. Companies such as Huawei, Cambricon, Moore Threads, and MetaX are aggressively expanding production as China attempts to reduce dependence on Nvidia and other U.S. suppliers.

Research firm Bernstein previously estimated Nvidia’s China AI GPU market share could collapse from 66% in 2024 to roughly 8% over time as domestic Chinese vendors move to satisfy as much as 80% of local demand.

Huang’s latest comments suggest the deterioration may have been even faster. The Nvidia chief argued that China retains formidable structural advantages in artificial intelligence regardless of hardware restrictions.

“American companies win around the world,” Huang said. “The argument there is that across the five-layer cake, there’s one particular layer that is too important because in the others, China can get ahead. They have cheaper energy. They have incredible talent.”

He pointed specifically to China’s deep engineering and research base.

“So, they have the number of science and math experts, and as a result of that, the number of AI researchers in China is quite extraordinary, it’s one of their national treasures,” Huang said.

The comments reflect growing concern inside parts of the U.S. technology sector that export controls may ultimately strengthen Chinese competitors rather than weaken them. Huang has increasingly argued that the real strategic advantage for the United States lies not merely in hardware leadership but in maintaining global dominance of software ecosystems such as Nvidia’s CUDA platform, which remains deeply embedded in AI development worldwide.

But the longer Chinese companies are shut out from American hardware, analysts say, the stronger the incentive becomes for Beijing to build parallel semiconductor and software ecosystems insulated from U.S. influence.

That fragmentation could eventually weaken the global dominance of American AI standards and reduce the international reach of U.S. technology companies. The geopolitical tensions are already reshaping supply chains and investment flows across the semiconductor sector.

The United States has tightened restrictions on advanced AI chip exports, while China has intensified efforts to localize semiconductor production and reduce dependence on foreign suppliers. At the same time, Washington’s own policy shifts have shown growing unease about completely surrendering the Chinese market to domestic competitors.

U.S. officials acknowledged that preventing China from buying American chips entirely could accelerate indigenous Chinese innovation and erode U.S. influence over global AI infrastructure.

That policy dilemma now sits at the center of the AI cold war.

Origin Quantum said Saturday that its fourth-generation superconducting quantum computer, the “Origin Wukong-180,” has officially gone online and is now accepting computing tasks from users worldwide, marking another major step in China’s accelerating race to build advanced domestic quantum technology.

The company described the system as China’s first large-scale attempt to systematically integrate independently developed quantum computing infrastructure into the broader artificial intelligence ecosystem, signaling Beijing’s ambition to compete more aggressively with the United States in next-generation computing technologies.

The new machine is powered by a 180-qubit superconducting quantum chip under a single-chip architecture, more than doubling the scale of its predecessor, the 72-qubit “Origin Wukong” system launched in January 2024.

According to the company, the upgrade represents a substantial leap in both computing power and system integration capability. Origin Quantum said all four major components of the system were independently developed inside China, including the quantum chip system, measurement and control infrastructure, environmental support system, and operating system.

That claim carries strategic significance as China continues seeking to reduce reliance on Western semiconductor and advanced-computing technologies amid intensifying geopolitical and technology tensions with the United States.

Quantum computing has become one of the most fiercely contested technological frontiers globally because of its potential to revolutionize industries ranging from artificial intelligence and cybersecurity to drug discovery, financial modeling, and military simulations. Unlike conventional computers, quantum machines process information using quantum bits, or qubits, which can exist in multiple states simultaneously.

In theory, sufficiently advanced quantum systems could solve certain classes of problems exponentially faster than classical supercomputers.

The launch of Origin Wukong-180, therefore, reflects more than a technical milestone. It is part of China’s broader strategy to establish technological leadership in strategic industries that Beijing considers essential for economic security and geopolitical influence. Chinese authorities have poured billions of dollars into quantum research over the past decade, viewing the field as critical to future military, industrial, and AI competitiveness.

The announcement also highlights how the boundaries between artificial intelligence and quantum computing are beginning to converge. Origin Quantum said the latest system is designed to support AI applications and has already begun integrating quantum-powered AI tools, including its “Origin Brain” quantum large model and the QPanda3 Runtime MCP platform.

Globally, technology companies and governments are increasingly exploring whether quantum systems can eventually accelerate AI training, optimization, and inference tasks that currently require enormous computing resources and electricity consumption.

Although practical large-scale quantum advantage remains years away in many areas, firms are racing to establish early ecosystems and developer networks before the technology matures. Origin Quantum’s earlier 72-qubit system, also called “Origin Wukong,” has reportedly handled more than 900,000 quantum computing tasks from users in over 160 countries and generated approximately 50 million remote visits since launch.

The company also said it achieved China’s first overseas export sale of independently developed quantum computing power in 2025, an achievement Beijing is likely to frame as evidence of growing global competitiveness in advanced computing.

The rollout comes as the global quantum race intensifies dramatically. In the United States, companies including IBM, Google, Microsoft, and startups such as IonQ and Rigetti Computing are competing to build increasingly powerful quantum systems.

Meanwhile, governments across Europe and Asia are rapidly increasing investments amid concerns that quantum breakthroughs could reshape economic and military power balances.

China’s emphasis on fully independent development is particularly notable. Washington has tightened restrictions on advanced semiconductor exports and AI-related technologies to China in recent years, pushing Beijing to accelerate domestic alternatives across critical computing sectors.

Quantum computing is viewed as one area where China believes it still has an opportunity to narrow or potentially surpass parts of the Western technological lead. Still, experts caution that qubit counts alone do not determine practical capability.

Quantum systems remain highly unstable and error-prone, and many researchers argue that the true challenge lies in improving error correction, coherence, and reliability rather than merely increasing qubit numbers. Even so, the launch of Origin Wukong-180 signals that China is moving aggressively from experimental research toward commercial deployment and ecosystem-building.

The development also underpins how the AI boom is now spilling into adjacent advanced-computing sectors. As artificial intelligence models become larger and more computationally demanding, governments and companies are increasingly searching for entirely new computing paradigms capable of handling future workloads.

Quantum computing, once viewed largely as a distant scientific pursuit, is increasingly being positioned as part of the long-term infrastructure underpinning the next era of AI competition.

Apple is preparing to deepen ties with Intel in a move that could alter the balance of power in the global chip industry, strengthen Washington’s push for domestic semiconductor production, and give Intel its biggest external manufacturing endorsement in years.

The two companies have reached a preliminary agreement for Intel to manufacture some of the chips used in Apple devices, according to people familiar with the matter cited by WSJ, capping more than a year of negotiations that increasingly drew in the White House and senior U.S. economic officials.

The arrangement remains in its early stages, and it is still unclear which Apple products will ultimately rely on Intel-made chips, according to the report. But the implications stretch far beyond a normal supplier agreement.

The deal represents an attempt for Apple to reduce dependence on Asia-centered semiconductor manufacturing at a time when artificial intelligence demand is consuming advanced chip capacity at unprecedented levels. It is also seen as a high-stakes opportunity for Intel to prove it can once again compete with industry leaders after years of technological decline.

In addition, the deal is seen as a validation of Washington’s aggressive industrial strategy designed to pull critical semiconductor production back onto U.S. soil.

The agreement arrives at a pivotal moment for the semiconductor industry, where AI infrastructure spending has transformed chip manufacturing from a largely commercial business into a geopolitical priority.

For years, Apple relied almost exclusively on Taiwan Semiconductor Manufacturing Company to produce the custom chips powering the iPhone, iPad, and Mac ecosystem. That partnership became one of the most successful relationships in modern technology, helping Apple develop increasingly powerful processors after abandoning Intel-designed Mac chips in 2020 in favor of its own Arm-based silicon.

But the AI boom has fundamentally changed the economics of chip production. Explosive demand from companies such as Nvidia, cloud providers, and AI startups has overwhelmed advanced semiconductor fabrication and packaging capacity worldwide. AI accelerators and high-performance GPUs now command priority access to the most sophisticated manufacturing nodes, forcing even giants like Apple to compete more aggressively for supply.

Apple executives have recently acknowledged the growing strain. CEO Tim Cook said supply shortages involving advanced chips were constraining production of some Mac products.

“We think, looking forward, that the Mac Mini and the Mac Studio may take several months to reach supply-demand balance,” Cook said during a recent earnings call.

AI infrastructure is beginning to crowd out traditional consumer electronics demand, reflecting a shift in the industry. In effect, Apple is now operating in a semiconductor market increasingly shaped by AI capital expenditure cycles rather than smartphone refresh patterns.

That has elevated the strategic importance of manufacturing diversification. The Intel deal gives Apple a potential secondary source for advanced chip production while aligning the company more closely with Washington’s effort to rebuild domestic semiconductor capabilities amid rising geopolitical concerns surrounding Taiwan.

Boosting Trump’s Domestic Manufacturing Push

The political dimension surrounding the agreement is unusually significant. The Trump administration spent the past year actively encouraging major U.S. technology firms to support Intel’s foundry ambitions as part of a wider effort to restore American leadership in chip manufacturing.

Last summer, the administration converted nearly US$9 billion in federal support into Intel equity, giving the U.S. government a 10% stake in the company. The investment transformed Intel from a struggling chipmaker into a centerpiece of America’s industrial and national security strategy.

Commerce Secretary Howard Lutnick reportedly met repeatedly with Apple executives, Nvidia leadership, and Elon Musk to encourage partnerships with Intel.

President Donald Trump also personally pressed Cook during White House discussions.

“I like Intel,” Trump said in January. “As soon as we went in, Apple went in, Nvidia went in, a lot of smart people went in.”

The administration increasingly views semiconductor manufacturing not merely as an economic issue but as a national security imperative, especially as tensions between Washington and Beijing continue reshaping technology supply chains.

Intel’s revival, therefore, carries political significance well beyond Wall Street. The company had spent much of the last decade losing technological leadership after repeated manufacturing delays allowed TSMC and Samsung Electronics to dominate advanced fabrication.

A series of failed transitions, executive turnover, and engineering setbacks badly damaged Intel’s reputation among major customers. The company’s foundry division struggled to attract external business as customers questioned whether Intel could reliably produce cutting-edge chips at scale.

That trajectory began changing after Intel appointed Lip-Bu Tan as CEO in 2025. Tan launched an aggressive restructuring campaign focused on rebuilding Intel’s engineering culture, streamlining management, and restoring confidence in its manufacturing roadmap. He invested heavily in Intel’s next-generation 14A process technology while reshaping the company’s leadership ranks, including recruiting former TSMC executive Wei-Jen Lo, a move that reportedly triggered legal action from TSMC. Intel also reorganized its data center, client computing, and custom silicon operations in an effort to become more responsive to outside customers.

The Apple agreement may now become the strongest indication yet that Intel’s turnaround is gaining credibility. Importantly, Intel has already secured support from several major AI-era players.

Nvidia invested US$5 billion in Intel last year and partnered with the company on custom data center processors. Elon Musk’s businesses also announced a manufacturing partnership with Intel tied to Musk’s Texas-based Terafab initiative, which is expected to support chip production for Tesla, SpaceX, and xAI.

With Apple now joining that ecosystem, Intel is gradually positioning itself as the manufacturing backbone of a broader American AI and technology alliance.

However, TSMC continues to hold a commanding technological lead in several advanced manufacturing areas, particularly in process maturity, yield consistency, and large-scale production execution.

Manufacturing chips for Apple also represents one of the most demanding assignments in the semiconductor industry. Apple’s performance, efficiency, and reliability requirements are among the strictest globally, meaning Intel will face intense scrutiny if the partnership moves forward.

Analysts say the deal is less about Intel immediately replacing TSMC and more about Apple building optionality in an increasingly constrained and politically sensitive supply environment.

The agreement also underscores how AI is redrawing corporate alliances across Silicon Valley. Companies that once competed primarily in consumer products are now increasingly linked by a shared need for computing infrastructure, access to semiconductors, and energy-intensive AI systems.

In that environment, chip manufacturing capacity has become as strategically important as software innovation – and the Apple-Intel partnership reflects that new reality.