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Malaysia’s long-debated dual network strategy has entered its most important phase, as UMobile accelerates its 5G network rollout and plans for up to 7,000 new sites by mid-2026, While two years of industry discourse have centred on whether the country needs two 5G networks, the question is: with DNB already covering 80% of populated areas, how does building parallel infrastructure serve Malaysia’s digital ambitions?

Gayan Koralage has shaped Edotco Group’s strategy since its formation in 2013 and helped establish the company as Asia’s leading tower company in eight markets with 55,000 towers, and says Malaysia’s 5G infrastructure development must prioritise network resilience over immediate cost savings.

“The design objective is single network failure,” Koralage explained during an exclusive interview with Tech Wire Asia, amid mounting industry concerns about UMobile’s plan to deploy 5,000-7,000 new 5G sites alongside DNB’s existing 80% population coverage. “If you have only one network running the country’s 5G network, then the whole nation risks not having any if there should be a failure with the single network.”

This defence comes at a time when Malaysia’s 5G adoption reveals significant untapped potential. With only 20% of what industry estimates suggest is approximately 33 GB of monthly per-customer data consumption migrated to 5G networks, the vast majority of digital transformation remains ahead. The government’s vision for building parallel networks with substantial capacity addresses this opportunity, positioning Malaysia to accelerate digital adoption and support the projected surge to 50-75 GB per customer by 2030 as AI and machine-to-machine communications drive demand.

The numbers tell the story of Malaysia’s digital trajectory. Current data consumption of 33GB per customer monthly is projected to rise to 50-75GB over the next decade, driven not just by human-to-human communications but also artificial intelligence applications and machine-to-machine interactions.

“The incremental data growth for Malaysia’s 35-40 million population – the data manufacturing capacity we need to build in the country, predominantly AI-based – cannot be handled by a single operator,” Koralage argued.

The 2025 reality: Beyond theoretical debates

Two years after Malaysia announced its dual 5G network strategy, the debate has moved from boardrooms to construction sites. UMobile’s aggressive deployment timeline targets 7,500 sites with 80% coverage by July 2026 and is the largest network rollout in Malaysian telecommunications history. This isn’t theoretical anymore; it’s happening on the ground.

That is why the current moment represents a shift in Malaysia’s telecommunications narrative. Early 2023 discussions focused on whether dual networks made economic sense, yet this year sees operational realities: spectrum allocation is finalised, TM has secured major fibre deals with both networks, and construction crews are building infrastructure nationwide.

Koralage’s strategic oversight helped attract Japanese and Malaysian sovereign wealth fund investments into Edotco in 2017. He views the transition as validation not vindication. “The question is no longer whether we should have two networks,” he said. “The question is how we execute two networks efficiently.”

“Having two networks is not new. It’s something very well tested,” Koralage said when pressed about infrastructure overlap concerns. “You have to have an overlap to have redundancy in this location. Otherwise, if 5G fails, what’s my backup plan?”

Yet redundancy comes with costs. UMobile’s rollout plan includes 2,000 new locations alongside 5,000 tower upgrades, creating the infrastructure duplication that tower sharing principles were designed to eliminate. The irony isn’t lost on industry observers: Malaysia promotes sharing and mandates separation.

Market balance complexities

The current network distribution reveals structural imbalances that the dual strategy attempts to address. “Right now there are three MNOs – CelcomDigi, Maxis, YTL – in one shared 5 G network, while UMobile operates essentially alone,” Koralage said. “The industry could potentially create traffic balance by selectively sharing networks – for example, with indoor coverage, operators can choose which buildings to serve rather than duplicating infrastructure in the same location.”

The rebalancing exercise suggests the dual network strategy serves broader competitive objectives beyond technical redundancy. The government appears to be engineering market dynamics that prevent any single network from achieving monopolistic control, even if its approach contradicts immediate efficiency gains.

The rural connectivity reality check

Beneath the 5G deployment debate lies an economic reality that exposes Malaysia’s digital divide in financial terms. The JENDELA initiative, designed to connect the remaining 4% of Malaysia’s unconnected population, reveals why market forces alone cannot achieve universal coverage.

“The cost to build a tower in a rural area is three times [higher],” Koralage said, outlining the brutal mathematics of rural connectivity. “Off-grid sites require specialised solutions – backup power, satellite backhauling, full macro towers rather than simple poles. The total cost of ownership becomes three times higher, while the revenue you can generate is only one-third of urban levels.”

This creates what Koralage describes as a “10 times problem” – three times the cost multiplied by one-third the revenue equals a nine-fold economic disadvantage, rounded to ten for practical purposes. The maths explain why government intervention through revenue sharing becomes necessary for rural deployment.

The bureaucratic challenges reveal a fundamental disconnect between urban and rural infrastructure development processes. “The site acquisition permitting process is taking much longer than we expected, because in urban cities, the process is well-known. In those rural locations, the landlords would have to visit government agencies. The process is not quite there, and to top it off, the council doesn’t meet often,” Koralage explained, describing what he characterises as “inherent, intrinsic issues” that complicate rural deployment.

The contrast is stark: urban tower deployment benefits from established relationships between municipal councils, landlords, and telecommunications companies. Rural areas lack this institutional knowledge and infrastructure. Local councils convene less frequently than their urban counterparts, landowners are unfamiliar with telecommunications infrastructure requirements, and government agencies haven’t developed standardised approval processes for remote locations.

Koralage describes Edotco as Malaysia’s “National Tower company. It’s delivered 257 towers in seven states for JENDELA Phase One, but these delays represent more than operational challenges – they undermine universal connectivity objectives. The company has committed to 90-day delivery timelines, down from previous 180-day standards, but rural permitting processes often extend beyond targets.

“The government has an ambitious plan with JENDELA: to get it done in six months. The approval process is something which we have to work on,” Koralage said, suggesting that regulatory reform may be necessary to achieve JENDELA’s connectivity goals.

The company advocates for a single-window approval system in all states, which could standardise rural deployment processes and reduce bureaucratic friction that currently hampers national connectivity initiatives.

State-backed competition and industry fragmentation

The proliferation of state-backed tower companies adds another layer of complexity to Malaysia’s infrastructure landscape. The entities emerged partly as a response to what Koralage terms “indisciplined rollout by mobile operators” – situations where multiple towers were constructed in proximity of one another without coordination.

“You’d see situations where we have two towers on the same rooftop, or two towers on the same hilltop – parallel towers built without coordination. That’s the history where the state found that the city’s aesthetic appeal was being compromised. It doesn’t look good, and some towers were built without proper approvals,” he said, defending the rationale behind state-backed companies as a response to industry indiscipline.

Today, Malaysia’s tower industry includes approximately 150 companies, with 40-plus remaining active. Edotco controls 6,000 towers out of 20,000 owned by independent tower companies: significant market fragmentation that enables competition yet complicates coordination.

The company advocates for a single-window approval system in all states to streamline deployment timelines. Edotco has already improved its delivery commitments from 180 days to 90 days, but regulatory bottlenecks remain problematic.

“Right now, we are committed to 90-day delivery. It used to be 180 days, but when network traffic grows in a location and operators decide to add infill sites, they cannot wait 180 days. The network traffic has already increased, calls are losing quality, and by the time 180 days pass, the situation has changed completely. Operators need a faster, more rapid approval process,” Koralage said.

Technology evolution beyond traditional infrastructure

Malaysia’s infrastructure development extends beyond conventional tower deployment into emerging technologies that may reshape rural connectivity economics. Edotco is exploring low-earth orbit (LEO) satellite integration for areas where terrestrial infrastructure proves economically unviable, particularly in Sabah and Sarawak, where point-of-presence locations may be 50 kilometres apart.

The company is also diversifying into adjacent services, including electric vehicle charging infrastructure through its ChargeSini partnership, which targets 200-plus locations using existing tower footprints. Out of the 100 EV charging stations deployed so far, Edotco uses its in-building locations, taking parking lots for ChargeSini charging through revenue-sharing arrangements.

Beyond Malaysia, Edotco’s influence extends to eight Asian markets with 47,000-plus towers, though Koralage acknowledges political instabilities in markets like Myanmar create operational challenges. The company’s RM1 billion annual revenue demonstrates the scale of infrastructure operations, with government projects representing less than 5% of total revenue – contradicting perceptions of heavy government dependency.

“We consider ourselves as the national tower company,” Koralage said, pointing to Edotco’s delivery of 1,200 tenancies in Malaysia last year and projections of around 800 this year. “[That’s] the largest rollout ever conducted by any Malaysian company in the history of the Malaysian tower or telecom industry.”

Edotco’s positioning reflects broader infrastructure responsibilities. The company owns 400 out of Malaysia’s 1,000 IBS-capable buildings, including shopping malls, universities, and iconic locations like the Kuala Lumpur International Airport. UMobile has selected 200 of these for 5G upgrades, representing approximately RM200 million in new business and highlighting how indoor coverage – which handles 70% of Malaysia’s cellular traffic – becomes crucial for network quality.

Critical industry assessment

While Koralage presents a technically sound defence of Malaysia’s dual network strategy, several challenges warrant scrutiny. The economic justification relies heavily on projected data consumption growth and AI adoption – assumptions that remain unproven at scale. Singapore’s successful dual network model may not translate directly to Malaysia’s more complex geography and economic structure.

The regulatory environment appears fragmented, with multiple approval processes creating deployment inefficiencies that undermine the speed advantages 5G networks are supposed to provide. The persistence of 42% operator-owned towers suggests that commercial incentives for infrastructure sharing may be less compelling than theoretical models indicate.

The rural connectivity economics expose uncomfortable truths about market-driven universal access. If remote towers require three times the investment for a third of the revenue, the business case for private investment disappears without government subsidies. This reality challenges assumptions about telecommunications market efficiency.

Malaysia’s approach to 5G infrastructure development reflects a broader tension between market efficiency and strategic resilience. The dual network strategy may indeed provide redundancy benefits, but at costs that extend beyond immediate financial calculations. Success will depend on whether the nation can justify redundancy premiums and deliver the connectivity foundation necessary for the country’s digitally-based economic aspirations.

As Malaysia navigates between efficiency and resilience, the telecommunications industry watches closely. The outcome may determine whether other ASEAN nations follow Malaysia’s redundancy-first approach or pursue more traditional efficiency-focused strategies. Either way, the experiment will provide valuable data points for regional digital infrastructure development.

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Why legacy networks are holding innovation back

Enterprise IT leaders face a complex and evolving digital landscape. Traditional networks can be rigid and fragmented, and struggle to support the real-time demands of AI, IoT, and data analytics. Legacy systems can delay the adoption of emerging technologies, creating bottlenecks that stifle innovation. When data flows in multiple systems, borders, and cloud environments without robust security controls, it increases exposure to security and compliance risks. Enterprises operating in the APAC region grapple with a lack of harmonisation in international regulatory requirements. The fragmented landscape makes it important to have a trusted security partner to help navigate compliance obligations without slowing innovation.

The Verizon Deploying AI at Scale research report, produced in partnership with S&P Global, shows that early AI adopters often underestimated infrastructure demands, leading to delays in scaling initiatives. In a region where regulatory complexity compounds infrastructure challenges, organisations need a modern, flexible network approach to stay competitive; one that lets them innovate quickly and at scale while maintaining resilience, performance, and security.

Verizon’s network solutions: Built for AI, edge and automation

Verizon’s enterprise-grade network capabilities are built for the digital-first world. Offering a flexible architecture that supports hybrid environments, Verizon’s network solutions let businesses modernise infrastructure without disrupting operations. Whether integrating legacy systems or deploying next-gen applications, Verizon’s modular design enables phased upgrades that align with business priorities. Deploying AI at Scale finds modular networks are key as AI projects shift from pilots to multi-environment deployments requiring data movement between on-premises, edge, and cloud systems.

Security needs to be embedded from core to edge. Verizon’s networks are built on zero-trust architecture, with features like data loss prevention (DLP) and intrusion detection systems (IDS) providing protection. Deploying AI at Scale [PDF] highlights security gaps in AI setups, where models like RAG may expose more data than intended. Control over network routing and data sovereignty strengthens compliance with regional regulations – an essential feature for APAC enterprises navigating the different legal frameworks.

Performance and reliability are also important. Verizon uses real-time visibility and AI-driven analytics to optimise network performance and enable predictive maintenance. Its high-capacity private IP backbones and fibre connections are capable of handling hundreds of GB per second, and ensure AI workloads run efficiently in distributed environments, tackling the infrastructure concerns flagged in the study.

Scalability for real-time technologies

As AI, machine learning, and automation become central to business operations, networks must scale to support these technologies. Verizon’s infrastructure is designed to handle high-throughput, low-latency workloads, including video analytics, connected devices, and industrial automation. AI projects often fail due to cost issues, the Deploying AI at Scale research report notes, emphasising the need for scalable, efficient networks.

Edge computing is another area where Verizon provides value to the modern enterprise network. By bringing compute power closer to where data is generated, edge solutions reduce latency and enable faster decision-making. This is particularly valuable in sectors like manufacturing, logistics, and healthcare, where real-time insights can drive operational efficiency and innovation. With only 2% of enterprises using edge AI, the report points to strong potential in sectors like healthcare and manufacturing, areas Verizon supports with its real-time, scalable solutions.

Verizon also provides private 5G solutions that give businesses the flexibility to deploy secure, resilient networks and support applications. The private 5G and edge solutions are designed to move large AI workloads locally, enabling rapid model inferencing and retraining without routing traffic through distant cloud environments.

Turning infrastructure into innovation

For enterprises in APAC, Verizon’s solutions help innovation by removing the need to manage disparate systems, so organisations can focus on delivering value to customers. Businesses can launch AI and automation initiatives, confident that Verizon’s network solutions will accommodate the workloads. They can deploy edge computing to enable smarter operations and integrate cloud services securely and efficiently. Verizon’s hybrid-ready architecture simplifies AI workload orchestration in the cloud and on-prem by managing interconnectivity, bandwidth, and latency constraints, identified as key risks in the study.

Verizon’s approach to scaling AI is grounded in strategic, ethical, and sustainable practices. The company outlines three key steps to enterprise AI success: setting high strategic standards, implementing a responsible AI framework, and embedding human oversight into AI systems. The principles align with Deploying AI at Scale‘s call for better communication between leadership and implementers, to reduce risks and enhance project success. The principles help businesses build trust, reduce risk and unlock long-term value from AI investments. For more information, visit 3 steps to scale enterprise AI.

Why APAC enterprises choose Verizon

Verizon’s strength lies in its ability to combine global scale with deep regional experience. With infrastructure and operations in Australia, Singapore, Japan and beyond, Verizon is well-positioned to support organisations navigating the region’s complex and fast-evolving digital landscape. Deploying AI at Scale highlights the fact that APAC’s diverse regulatory environment can present challenges for businesses seeking to implement and scale AI solutions. In such an environment, a trusted partner with proven experience in markets is essential to help enterprises stay compliant and competitive.

“Our customers in APAC need networks that do more than connect – they need networks that are adaptive, secure and intelligent enough to support evolving AI, edge and hybrid environments,” said Rob Le Busque, Regional Vice President, Verizon Asia Pacific. “We work closely with enterprises in the region to deliver future-ready infrastructure that aligns with their digital transformation goals.”

Verizon’s expertise spans highly-regulated sectors like finance, public services, and healthcare, where compliance and security are of paramount importance. It offers co-managed services and support to extend internal IT teams, along with strategic partnerships that accelerate implementation and reduce risk. Verizon’s services support edge AI by providing robust network segmentation, monitoring, and routing strategies that help enterprises deploy and maintain AI workloads in geographically-distributed environments.

Security and compliance are built into every layer of Verizon’s architecture. From governance controls to region-specific data handling, Verizon helps businesses meet evolving APAC regulations with confidence. Its security framework addresses new AI threats like data leaks and prompt attacks – which are part of the expanded threat model outlined in Deploying AI at Scale.

The network behind innovation

In today’s innovation economy, your network isn’t just a utility – it’s your advantage. Verizon’s next-generation solutions lets APAC businesses harness AI and edge computing, providing the flexibility, security, and intelligence required to thrive with a competitive advantage.

To discover how Verizon can help your business remove constraints and realise digital opportunities, visit https://www.verizon.com/business/en-au/solutions/adaptive-networks/

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Just three years ago, Cambricon Technologies was bleeding money, blacklisted by Washington, and fighting for survival in the shadow of Nvidia’s dominance. Today, the Chinese AI chipmaker has done something that seemed impossible: it turned a stunning US$144 million profit while US sanctions intended to cripple China’s tech ambitions appear to be backfiring spectacularly.

Record-breaking financial performance

The numbers tell the story of a company—and a country—defying expectations. Cambricon posted a 1.03 billion yuan profit versus a year-earlier loss of 533 million yuan, driven by a staggering 44-fold surge in revenue to 2.9 billion yuan for the first half of 2025. More than just a corporate comeback, this represents China’s most concrete proof yet that its domestic AI ecosystem can not only survive American restrictions—it can thrive because of them.

Cambricon Technologies, which competes directly with Huawei Technologies in providing AI accelerators for developing and hosting AI models, has achieved what many analysts thought was impossible under US restrictions. The company’s earnings per share (EPS) of 2.48 yuan and a sustained profitability trajectory, which began with its first-ever quarterly profit in late 2024, signal a fundamental shift in China’s semiconductor capabilities.

The transformation is all the more remarkable given the company’s recent struggles. Just months ago, Cambricon was grappling with years of persistent losses, while US sanctions severely limited its access to advanced manufacturing processes and cutting-edge technologies.

Market euphoria and valuation surge

The market’s response to Cambricon Technologies has been nothing short of euphoric. As of Aug 26, 2025, Cambricon Technologies was trading at 1,329.00 yuan, with a previous close of 1,384.93 yuan, representing an 11.6% jump on Monday alone. Cambricon’s stock closed up 11.4% on Monday at 1,384.93 yuan ($191.07) per share, just shy of the fiery liquor-maker Kweichow Moutai, which closed at 1,490.33 yuan.

Investors are paying an extraordinary premium for a piece of China’s AI future—Cambricon’s price-to-earnings ratio has ballooned to 4,463 times, making Kweichow Moutai’s 20 times multiple look conservative by comparison. The rally shows no signs of slowing: after rising 383% in 2024 to become China’s best-performing stock, shares have more than doubled since mid-July, delivering a spectacular 562% return since September.

The DeepSeek effect and China’s AI renaissance

Behind Cambricon’s meteoric rise lies a game-changing development: DeepSeek, the Chinese AI startup that shocked Silicon Valley with its cost-effective approach to artificial intelligence. When DeepSeek revealed it could achieve a “theoretical” profit margin of 545%—more than five times its costs—it didn’t just demonstrate Chinese AI prowess, it created a gold rush for the domestic chips powering these breakthroughs.

The ripple effect was immediate. As DeepSeek optimised its models for the “next generation of domestic chips,” investors suddenly grasped the full potential of China’s homegrown AI ecosystem. Beijing’s push for technological self-reliance wasn’t just about politics anymore—it was about profits, and companies like Cambricon were perfectly positioned to capitalise

When sanctions backfire

The irony is impossible to ignore: the very restrictions designed to kneecap China’s AI ambitions have become Cambricon’s greatest competitive advantage. When Washington added the company to its Entity List in December 2022, cutting off access to advanced US technologies, it seemed like a death sentence. Instead, it became a business opportunity.

Nvidia’s China-specific H20 chips—already a watered-down version designed to comply with export controls—were further restricted under the Trump administration’s latest regulations. The result? Chinese companies had no choice but to look inward, and Cambricon was ready with domestic alternatives. 

In September 2024, when Beijing ramped up pressure on local firms to ditch American processors, Cambricon’s shares hit the 20% daily trading limit.

The technical reality check

But can Cambricon actually compete with Nvidia’s technological prowess? The company, founded by brothers Chen Yunji and Chen Tianshi from China’s elite “genius youth class,” is betting its future on the Siyuan 690 processor—a chip designed to rival Nvidia’s H100. 

While specifications remain closely guarded, the China Academy of Information and Communications Technology has validated Cambricon as one of eight suppliers with DeepSeek-compatible hardware.

The real test isn’t just raw performance, but ecosystem compatibility. Chinese AI companies increasingly need chips optimised for their specific algorithms and cost structures—something Nvidia’s export-restricted chips struggle to deliver.

The $5 billion bet

Cambricon isn’t just riding the wave—it’s doubling down with a massive 5 billion yuan capital raise to fund large language model chip development. The allocation tells the story: 2.9 billion yuan for LLM chips, 1.6 billion yuan for software, and the rest for working capital. This isn’t incremental improvement; it’s an attempt to leapfrog generations of chip development.

Goldman Sachs’ bullish 1,835 yuan price target (50% above current levels) reflects growing confidence that Chinese cloud giants like Tencent will fuel sustained demand. But with a 4,463x P/E ratio, there’s little room for execution missteps.

The uncomfortable truth

The sustainability question looms large, and it’s not just about valuation bubbles. Cambricon’s explosive growth masks dangerous client concentration risks—a few large customers departing could crater revenues overnight. More fundamentally, while China can design competitive AI chips, manufacturing them at scale without access to cutting-edge Western equipment remains an open question.

The company likely relies on domestic foundries like SMIC or Hua Hong Semiconductor, which lag TSMC by several process generations. Physics doesn’t care about geopolitics, and advanced AI workloads demand the most efficient chips available.

The new semiconductor reality

Cambricon’s remarkable turnaround isn’t just a corporate success story—it’s a preview of the technology cold war’s next phase. For decades, the semiconductor industry thrived on global integration: American designs, Taiwanese manufacturing, Chinese assembly. That era is ending.

What we’re witnessing isn’t just market fragmentation, but the birth of parallel technological universes. Chinese AI companies will increasingly optimise for domestic chips, while American firms double down on Western hardware. The result won’t be healthy competition—it will be technological tribalism that ultimately slows innovation for everyone.

The real winners may not be the companies or countries involved, but the geopolitical rivals watching from the sidelines. While the US and China spend hundreds of billions building duplicate semiconductor ecosystems, Europe, India, and others are quietly developing their own capabilities without the baggage of a tech cold war.

Overall, Cambricon’s success proves that China can build a domestically powered AI ecosystem. But success and optimality are different things. The world is about to find out how much innovation we’re willing to sacrifice on the altar of technological sovereignty. Based on Cambricon’s soaring stock price, investors think the answer is: quite a lot.

The question isn’t whether China can build its own AI chip champions—Cambricon has already answered that. The question is whether a bifurcated global technology system will ultimately serve anyone’s interests, including China’s. On that, the jury is very much still out.

The post The Chinese chip company that’s making Nvidia sweat: Inside Cambricon’s meteoric rise appeared first on TechWire Asia.

Apple manufacturing in India has reached unprecedented heights, but the narrative of India becoming “the next China” oversimplifies a far more nuanced strategic reality. Apple assembled US$22 billion worth of iPhones in India in the 12 months ended March, increasing production by nearly 60% over the previous year, marking a pivotal moment in global supply chain dynamics.

The transformation is remarkable by any measure. In the first half of 2025, iPhone production in India rose by 53% compared to the same timeframe in 2024, reaching nearly 23.9 million units. Exports from India surged as well, totalling US$22.56 billion, a substantial increase from US$14.71 billion the previous year.

For the first time in history, India overtook China to become the top exporter of smartphones to the US, with smartphones assembled in India accounting for 44% of US imports of those devices in the second quarter.

The geopolitical catalyst behind the shift

Apple’s accelerated pivot stems from mounting geopolitical pressures and market realities in China. Apple’s smartphone shipments in China fell 17% year-over-year, dropping from 51.8 million units in 2023 to 42.9 million in 2024.

The company’s Chinese market share has contracted dramatically, falling to 15% in China, behind Huawei’s 16% and top-ranking Vivo’s 17%. The decline isn’t merely cyclical. Local manufacturers have emerged as the primary beneficiaries, with government support through nationwide smartphone subsidy policies providing additional momentum for domestic brands.

Notably, Apple’s premium-priced iPhones were reportedly ineligible under the new subsidy scheme. The resurgence of Huawei, previously hampered by US sanctions, has particularly impacted Apple’s premium market position.

Patrick McGee, author of “Apple in China: The Capture of the World’s Greatest Company,” provides context to this shift. McGee argues that Apple is still far from withdrawing from China, having invested billions of dollars in talent and equipment in China, with the country’s authoritarian government now having more influence over Apple’s fate than any other country. His analysis reveals a fundamental dependency that extends beyond simple manufacturing.

India’s manufacturing momentum and limitations

India’s rise as an Apple manufacturing hub has been swift but faces inherent constraints. Apple and its suppliers are aiming for a significant shift in global iPhone production, with plans to assemble 32% of global output and 26% of its value in India by 2026-27. The ambitious target could see India’s iPhone production value rise beyond US$34 billion.

However, the reality on the ground reveals some challenges. India’s manufacturing ecosystem is less mature than China’s, with supply chain inefficiencies and a less experienced workforce combining to slow scalability. Indian factories still face many problems, including low iPhone yield rates (only about 50%) and hygiene issues.

Manufacturing executives acknowledge the limitations, and the infrastructure gap remains substantial. While iPhone assembly lines in China work on two 12-hour shifts, Indian labour laws force Apple supply chain partners to have three eight-hour shifts, requiring them to employ more workers.

Quality control presents another hurdle, with Apple having to reject almost half the production out of one partner in India as it failed to meet standards.

The supplement strategy: Why complete replacement isn’t feasible

The evidence suggests India serves as a strategic supplement rather than a wholesale replacement for China. While Apple has been able to build iPhones in India, it’s only a tiny percentage of its needs; it’s only final assembly processes for now, and it will take years to reach any significance in numbers. Surprisingly, many of Apple’s factories in India are Chinese subsidiaries that followed Apple to the continent.

Apple’s dependency on China extends beyond final assembly. Ten years ago, Apple relied on China primarily for final assembly, while today, Apple not only assembles devices in China, but it also sources many components from the country. This deep integration means that even Indian-assembled iPhones rely heavily on Chinese components and expertise.

The scale disparity is telling. India could reach about 15%-20% of overall iPhone production by the end of 2025, while China still accounts for the majority of Apple iPhone production. Even Apple’s most ambitious projections suggest India will handle approximately 25% of global iPhone production by 2027 – significant, but hardly a complete replacement.

Market dynamics and strategic positioning

Apple’s India strategy represents sophisticated risk management rather than abandoning China. As of late 2024, 15% of iPhones are now produced in India, up from just 5% two years prior. Its measured approach reflects practical constraints and strategic thinking.

The geopolitical environment continues to shape decisions. President Donald Trump laid out US “reciprocal tariff” rates on more than 180 countries, with China facing a 34% tariff and India pegged at 26%. However, the tariff differentials don’t eliminate the fundamental challenges of replicating China’s manufacturing ecosystem elsewhere.

Apple’s approach mirrors broader industry trends. Samsung Electronics and Motorola have also been striving to move assembly for US-bound smartphones to India, though their shift has been significantly slower and is limited in scale compared with Apple, indicating systemic challenges in scaling alternative manufacturing hubs.

The path forward: Coexistence, not replacement

The most realistic scenario involves sustained coexistence rather than replacement. The end goal for Apple is to have about half of iPhone production in India and half in China, according to industry analysis. A balance recognises the strategic necessity of diversification and the practical impossibility of complete disengagement from China.

Apple’s investment trajectory supports this interpretation. Apple announced a US$500 billion investment in US facilities and is establishing new production lines in Vietnam for AirPods, Apple Watch, and MacBook parts: a multi-hub strategy rather than a simple China-to-India migration.

The company’s approach to component sourcing reinforces this complexity. Assembly is the final stage of iPhone production, with hundreds of components sourced from China. As final assembly shifts geographically, the underlying supply chain remains integrated with Chinese manufacturers.

Conclusion: Redefining the narrative

Apple’s manufacturing shift to India represents neither the wholesale replacement of China nor a simple geographical arbitrage. Instead, it reflects a sophisticated strategy of supply chain resilience, market access optimisation, and geopolitical risk management.

The success of Apple’s diversification strategy shouldn’t be measured by India’s ability to completely replace China, but rather by its capacity to provide strategic alternatives, serve specific market demands, and contribute to overall supply chain resilience. In this context, India’s emergence as an Apple manufacturing hub represents a strategic success.

The India-China dynamic in Apple’s supply chain will likely remain complementary rather than competitive, with each region serving distinct strategic purposes in the company’s broader manufacturing ecosystem.

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Chinese internet conglomerate Tencent has dismissed concerns over US GPU export restrictions, with executives stating the company’s AI infrastructure possesses adequate processing power for ongoing operations. This comes as Washington and Beijing continue negotiations over semiconductor trade policies.

During Tencent’s Q2 2024 earnings call, company president Martin Lau addressed questions about potential consequences of recent US decisions that allow Nvidia and AMD to resume limited GPU sales to China. Lau’s response suggested the policy changes hold minimal significance for the company’s immediate operations.

“We do not have a definite answer on the import situation yet. There are a lot of discussions between the two governments,” Lau stated, according to The Register. However, he emphasised the company’s current position: “From our perspective, we do have enough chips for training and continuous upgrade of our existing models. We also have many options for inference chips.”

Strategic shift toward software optimisation

Tencent’s approach extends beyond developing stockpiles. “We are executing a lot of software improvements to drive efficiency in inference so we can put more workloads on the same number of chips,” Lau said during the earnings call.

The optimisation-first strategy represents a shift in how Chinese technology companies respond to ongoing US export controls. Rather than scrambling for alternative hardware sources, Tencent appears to be focusing on extracting maximum performance from current resources.

Implications for US semiconductor giants

The company’s self-sufficiency claims present challenges for American chip manufacturers hoping to capitalise on renewed access to Chinese markets. Both Nvidia and AMD had anticipated revenue increases from resuming sales to China, particularly given the massive scale of Chinese AI development projects.

Lau’s remarks suggest Tencent may not contribute to the expected purchasing surge, potentially dampening revenue projections for US semiconductor companies. The situation becomes more complex when considering the Trump administration’s reported plans to claim a percentage of GPU sales to China.

Moreover, Tencent has indicated flexibility in sourcing inference chips from non-US suppliers, suggesting the company has developed alternative supply chains that could reduce American market share in Chinese AI infrastructure.

Financial performance amid AI investment concerns

Despite robust financial results, Tencent’s earnings call revealed challenges it’s facing recouping AI investments. The company reported Q2 revenue of RMB 184.5 billion (US$25.7 billion), representing 15% annual growth, while net profit reached RMB 64.8 billion (US$9 billion), up 11%.

However, Lau acknowledged persistent difficulties in balancing AI infrastructure costs with revenue generation. “Depreciation costs from AI will continue to go up,” he noted. “But we continue to reap the benefits of AI. The issue is these two may not match each other completely, but both are moving in the same general direction.”

The comments suggest Tencent, like many technology companies globally, continues struggling to translate substantial AI investments into proportional revenue streams.

Diversification beyond GPU-dependent services

Tencent’s cloud division has adapted its strategy to reduce dependence on GPU availability, according to Lau’s statements. The company is actively pursuing opportunities in CPU-based computing and database services, areas less affected by current US export restrictions.

“Our cloud strategy is not dependent on GPU,” Lau emphasised, adding, “We are also growing in CPU and database.” The tendency to diversification allows Tencent to maintain growth in cloud services regardless of semiconductor supply chain disruptions, and potentially reduce exposure to future trade policy changes.

Consistent messaging on hardware independence

This is the third consecutive quarter where Tencent has communicated to investors that additional GPU purchases are unnecessary for current operations, which suggests the company’s position on hardware sufficiency is not reactive to recent US policy developments.

The company’s core social media platforms continue showing strong user engagement, with numbers of Weixin and WeChat monthly active users reaching 1.411 billion, an annual growth of 40 million users or a 3% increase.

As US-China technology trade relationships remain in flux, Tencent’s stated hardware independence and optimisation focus may serve as a template for other Chinese technology companies navigating similar export control challenges. The long-term effectiveness of its approach to maintain competitive AI capabilities will likely influence industry-wide strategies in China’s technology sector.

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For decades, US export controls have operated on a simple principle: companies either get licences to sell restricted technology abroad, or they don’t. But reports of a new deal between semiconductor giants Nvidia and AMD and the Trump administration suggest this binary approach may be changing, with the companies reportedly agreeing to pay 15% of their revenues from Chinese AI chip sales to the US government.

The reported revenue-sharing deal between both chip giants, if confirmed, would represent a shift in how Washington approaches technology export controls and could set a new precedent for US-China trade relations.

What the reports say

According to multiple media reports citing sources familiar with the matter, Nvidia plans to share 15% of the revenue from sales of its H20 AI accelerator in China. AMD would deliver the same share from MI308 revenues. The two chip companies reportedly agreed to the fee structure last week, following months of lobbying efforts by industry leaders.

The reported revenue-sharing arrangement specifically targets Nvidia’s H20 chip and AMD’s MI308, both important for AI applications. The chips were developed after the Biden administration imposed export restrictions in 2023, with the H20 designed specifically for the Chinese market to comply with those limitations.

The path to this deal has been marked by shifting policies and intense lobbying. US President Donald Trump’s administration halted sales of H20 chips to China in April, but Nvidia last month announced that the administration said it would allow the company to resume sales, and it hoped to start deliveries soon.

It followed a separate report from the Financial Times that the US Commerce Department started issuing H20 licenses on Friday, two days after Nvidia Chief Executive Officer Jensen Huang met President Donald Trump. The timing suggests the personal involvement of industry executives in securing the arrangement.

Why these reports matter

While export controls for sensitive products are nothing new, reports of charging a company 15% of its revenue to sell a particular product to a particular country would be unprecedented if confirmed. The reported arrangement would represent a shift from traditional export control mechanisms, which typically involve licensing fees or outright bans, to a revenue-based approach.

For the companies involved, China represents a massive market opportunity. Despite export restrictions, Chinese demand for AI chips remains robust as the country continues to invest heavily in artificial intelligence capabilities. The 15% payment allows these companies to maintain market access while demonstrating compliance with US national security concerns.

The reported deal has already attracted significant criticism from legal experts who question its constitutional validity if implemented. “In addition to the policy problems with just charging Nvidia and AMD a 15% share of revenues to sell advanced chips in China, the US Constitution flatly forbids export taxes,” Peter Harrell, the White House senior director for international economics under the Biden administration, said in a Sunday post social media.

Christopher Padilla, a top export control official in the George W. Bush administration who is now a senior adviser with the Brunswick Group consulting firm, echoed those fears, describing the deal as “unprecedented and dangerous.”

The constitutional prohibition referenced stems from Article I, Section 9, Clause 5 of the US Constitution, which states, “No Tax or Duty shall be laid on Articles exported from any State.” The clause was designed to prevent the federal government from imposing taxes specifically on exported goods.

Industry response and market impact

“We follow the rules the US government sets for our participation in worldwide markets,” a Nvidia spokesperson said in a statement. The company added: “While we haven’t shipped H20 to China for months, we hope export control rules will let America compete in China and worldwide.”

AMD has not yet responded to requests for comment regarding the reported arrangement. It was not immediately clear how the government would deploy the presumed billions of dollars in fees collected if the reports prove accurate.

From a business perspective, the revenue-sharing model allows both companies to maintain their competitive positions in the crucial Chinese market. For Nvidia, especially, which has seen explosive demand for its AI chips globally, maintaining access to China’s market – even with a 15% revenue reduction – is likely preferable to being shut out entirely.

Broader trade implications

The arrangement comes amid a broader context of evolving US-China trade relations. The semiconductor industry has become a key battleground in technological competition between the world’s two largest economies. The US has progressively tightened export controls on advanced chips since 2022, citing national security concerns about their potential use in military applications and AI development.

The reported revenue-sharing approach could represent a new model for managing technology exports to strategic competitors if implemented. Rather than implementing outright bans, which can harm US companies’ competitiveness, this reported arrangement would allow for continued market access while extracting value for the US government.

What happens next?

The constitutional challenges to the reported arrangement are likely to continue if it’s confirmed, potentially leading to legal challenges that could test the boundaries of executive authority over export controls.

Even without the revenue-sharing provision, Donald Trump’s decision to ease the chip-sale restrictions on Nvidia was controversial, with officials from both parties expressing concern that the flip-flopping policy would erode further any trust in US export controls.

The precedent that could be set by this reported deal might influence how other technology exports are managed, particularly for companies seeking to maintain access to strategically important markets while complying with national security restrictions.

The bottom line

While neither the US government nor the companies involved have officially confirmed these reports, the potential implications are far-reaching. If true, the revenue-sharing model between Nvidia and AMD could reshape how American technology companies access overseas markets under national security restrictions.

For China, such an arrangement might accelerate its push toward semiconductor self-sufficiency, as Beijing has been investing heavily in domestic chip manufacturing precisely to reduce dependence on foreign suppliers. The prospect of US companies paying their government a premium to sell in China could provide additional motivation for Chinese firms to develop competitive alternatives.

Other US technology companies will be watching, as the model could extend beyond semiconductors to other strategic technologies like quantum computing, advanced software, or telecommunications equipment. Companies in sectors deemed critical to national security might face similar revenue-sharing requirements when seeking to operate in sensitive markets.

The broader tech industry could also see fragmentation accelerate, with American companies paying premiums to access certain markets while competitors from other countries operate without constraint. This could reshape global supply chains and partnerships in ways that extend far beyond the current US-China technology rivalry.

Until official confirmation emerges, however, these remain speculative scenarios based on unverified reports. What’s clear is that any such arrangement would mark a significant evolution in how economic statecraft intersects with private enterprise.

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As financial regulators worldwide grapple with the challenge of overseeing artificial intelligence deployment in banking and finance, Malaysia has taken a step forward with Bank Negara Malaysia’s publication of a discussion paper on AI governance, initiating a ten-week consultation period that will shape how banks, insurers, and fintech companies deploy machine learning technologies.

The regulatory framework addresses a global challenge facing central banks from Singapore to the European Union, where policymakers balance innovation with financial stability as AI adoption accelerates in the sector.

Governor Abdul Rasheed Ghaffour used the MyFintech Week event to outline a broader regulatory roadmap extending through to the end of 2025, including forthcoming exposure drafts on open finance and asset tokenisation that represent Malaysia’s collected approach to emerging financial technology oversight.

Three-pronged regulatory approach

Speaking at Sasana Kijang on August 5, 2025, Governor Ghaffour outlined BNM’s immediate regulatory priorities. “We have released a Discussion Paper on Artificial Intelligence today, outlining our regulatory and developmental approach, including priority areas for industry-led collaboration and responsible adoption of AI in financial services,” he said, during the opening ceremony of MyFintech Week.

The regulatory roadmap extends beyond AI. By year-end 2025, BNM will issue an Exposure Draft on Open Finance, establishing a framework for customer-permissioned data sharing in Malaysia’s financial ecosystem. And, a discussion paper on Asset Tokenisation will follow, addressing potential use cases and safeguards for the adoption of tokenisation.

The coordinated approach reflects what Minister of Finance II Amir Hamzah Azizan described as the “F-I-N-D agenda” – Foster, Invest, Nurture, and Democratise – emphasising responsible innovation and shared infrastructure development in Malaysia’s financial sector.

AI adoption momentum in Malaysian finance

The timing of Malaysia’s AI financial regulation discussions aligns with industry adoption trends. According to BNM’s AI Survey 2024, 71% of banking institutions and development financial institutions had implemented at least one AI application by the end of 2024, up 56% on the previous year. Insurance and takaful operators showed similar growth, with AI adoption rising from 58% to 77% of companies.

According to the discussion paper unveiled at MyFintech Week, “Most AI applications currently in development or expected to be deployed in the near-term are designed to augment rather than replace human decision-making.” Simply put, financial service providers are primarily focusing on customer analytics, internal operational improvements, and fraud detection rather than core financial risk functions.

The AI survey also revealed that over 60% of banking institutions and insurance operators view AI as a strategic priority for the next one to three years, with particular interest in generative AI applications for internal process improvements.

Regulatory philosophy: Technology-neutral yet targeted

BNM’s approach to Malaysia’s AI financial regulation emphasises parity, proportionality, and neutrality. “Activities bearing the same types of risks will be regulated the same way, while regulatory expectations and supervisory rigour are calibrated to be commensurate with the materiality and likelihood of risks,” the discussion paper states.

The central bank maintains that existing technology-agnostic, outcome-focused regulatory requirements remain broadly adequate for current AI applications. However, BNM acknowledges that emerging AI use cases may require specific regulatory attention as the technology evolves. “As AI technologies and state of adoption in FSPs continue to grow and evolve, we recognise that AI use may introduce new risks that are not adequately addressed by the existing regulatory framework,” the paper states.

Industry collaboration and responsible innovation

The discussion paper emphasises “win-win-win” use cases – AI applications that benefit consumers, enhance outcomes for service providers, and align with regulatory objectives.

Examples include AI-driven fraud detection systems that reduce false positives and protect consumers, and personal financial management tools that improve financial litreacy through consumer-permissioned data analysis.

Leading financial institutions are already implementing specialised governance structures for AI projects. The survey found that institutions with more AI projects demonstrate greater confidence in managing concerns around staff expertise, model interpretability, and regulatory uncertainty.

BNM encourages industry-led collaboration through the Chief Risk Officers’ Forum, which developed an AI Governance Framework outlining responsible AI principles, including fairness, accountability, transparency, and reliability for Malaysian financial institutions.

Economic context and digital infrastructure

Malaysia’s economic fundamentals support this regulatory advancement. BNM has revised GDP growth projections to 4%-4.8% for 2025, while inflation is expected to remain moderate at 1.5%-2.3%. The ringgit has appreciated 5.55% against USD as of August 4, 2025, reflecting improved investor confidence in Malaysia’s structural reforms.

The country’s digital infrastructure foundation strengthens the case for comprehensive Malaysia AI financial regulation. With 97% of Malaysian households having internet access and 98% with smartphones, the financial sector considers itself well-positioned for AI adoption.

Malaysia currently ranks second globally in QR payment adoption, with DuitNow becoming integral in many daily transactions. Digital banks, digital insurers, and takaful operators are expected to accelerate digital-native model adoption in the industry.

Feedback timeline and implementation

BNM seeks comprehensive industry feedback on the AI discussion paper through to October 17, 2025. Responses should be submitted to aipolicy@bnm.gov.my with the subject line “AI in the Malaysian Financial Sector: Feedback from [name of institution/individual].”

The central bank specifically requests input on whether formal sector-specific AI definitions would benefit the industry, regulatory clarity, and AI trends that could shape the sector over the next 3-5 years.

Balancing innovation with systemic risk

The discussion paper’s most sobering assessment concerns the potential for AI to create new forms of systemic risk. “Convergence by the financial sector on the use of the same foundation models and/or the same datasets may introduce or amplify interconnections among FSPs,” the document says, highlighting how widespread adoption of similar AI systems could trigger synchronised market reactions during periods of volatility.

The concern reflects a deeper regulatory philosophy emerging in global financial centres: that AI’s promise of enhanced fraud detection, improved financial inclusion, and operational efficiency must be weighed against the possibility of creating more interconnected and potentially fragile financial networks.

BNM’s approach appears calibrated to navigate the tension through a regulatory sandbox. The central bank’s emphasis on “win-win-win” use cases – those benefiting consumers, financial institutions, and regulatory objectives simultaneously – suggests a pragmatic framework that prioritises demonstrable value over technological novelty.

The October 17 consultation deadline will test whether Malaysia’s financial industry shares this approach or wants to push for a more aggressive AI deployment.

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The race to dominate Europe’s emerging autonomous vehicle market has taken an unexpected turn, with Chinese driverless cars poised to become a common sight on roads in Germany and the UK by 2026. While European markets have largely expected American firms like Waymo to lead the rollout of autonomous vehicles, Lyft has partnered with Beijing-based tech giant Baidu to deploy thousands of Apollo Go vehicles in European cities.

The cross-Pacific collaboration represents a corporate partnership and signals the first incursion of Chinese autonomous vehicle technology into Western markets, potentially disrupting established players and challenging European perceptions about the global leadership in self-driving.

The deployment will begin in Germany and the United Kingdom, where Baidu’s sixth-generation Apollo Go vehicles will integrate into Lyft’s ride-hailing platform, pending regulatory approval. Both companies project scaling to “thousands of vehicles” in multiple European markets in a few years of the initial launch.

Strategic timing and market entry

The announcement comes alongside Lyft’s recent acquisition of European ride-hailing app FREENOW from BMW and Mercedes-Benz for approximately $200 million. The acquisition provided Lyft with immediate access to operations in 180 cities in nine European countries, creating the infrastructure necessary for the robotaxi deployment.

Lyft, which has had very little presence in Europe so far, said it will prioritise Germany and the UK due in part to FREENOW’s existing presence in these countries, and keep “deep relationships with local regulators and taxi operators,” according to the company’s press release.

The timing aligns with regulatory developments in Europe. The UK has already enacted legislation that could allow autonomous vehicles on public roads by 2026, while Germany’s autonomous vehicle framework targets commercial operations in the same timeframe.

Germany’s roadmap includes plans for autonomous public transport services by 2027 and fully integrated autonomous mobility systems by 2030.

Chinese driverless cars enter European markets

For Beijing-based Baidu, the Lyft partnership represents the latest phase in bringing Chinese driverless cars to international markets through an aggressive global expansion strategy. Last month, Baidu partnered with Uber to deploy its autonomous cars on the ride-hailing giant’s platform outside the US and mainland China, with a focus on the Middle East and Asia.

Baidu’s Apollo Go platform brings operational experience to the partnership. In the fourth quarter of 2024, Apollo Go completed 1.1 million rides, a 36% increase from the previous year, and covering 130 million autonomous kilometres in multiple Chinese cities.

The technology foundation appears robust for international deployment. Baidu’s sixth-generation Chinese driverless cars, specifically the RT6 model, cost less than US$30,000 to manufacture – letting Baidu scale operations and maintain cost efficiency. The cost structure could prove important for competitive pricing in European markets.

Operational scale and technical capabilities

Baidu’s domestic operations demonstrate the scale potential for European deployment. The fleet of 500 vehicles operating in the city belongs to Apollo Go, a unit of Chinese tech giant Baidu. They serve an area that covers roughly half of Wuhan’s population, showcasing the service’s ability to handle large metropolitan areas.

The pricing strategy has proven effective in Chinese markets, where base fares start as low as 4 yuan (55 cents), compared with 18 yuan ($2.48) for a taxi driven by a human. However, European pricing strategies remain undisclosed as regulatory frameworks and market conditions differ significantly from China.

Baidu’s Apollo Go platform currently operates over 1,000 autonomous vehicles in 15 cities in China, having completed more than 11 million rides.

Competitive landscape and industry context

The Lyft-Baidu partnership enters an evolving competitive landscape in Europe. Uber has formed partnerships with companies like Waymo, Pony.ai, WeRide, and Momenta to prepare for robotaxi deployment in Europe, with its services expected to launch around the same time in 2026.

The autonomous vehicle market represents substantial economic potential. Analysts project that by 2030, Europe’s autonomous vehicle market could reach $50 billion in value, according to industry consulting estimates. The projected growth has attracted significant investment and partnership activity in the sector.

For Lyft specifically, the partnership addresses a gap in autonomous vehicle technology. Lyft hasn’t had the same pace of deals as Uber, but has made several partnerships in the past year, including a plan to add autonomous shuttles made by Austrian manufacturer Benteler Group to its network in late 2026.

Technical implementation and safety considerations

The deployment will use Baidu’s advanced autonomous driving technology stack developed for Chinese driverless cars. Baidu’s Apollo platform integrates lidar, radar, and cameras for urban navigation, complemented by Lyft’s app ecosystem for user booking and payments.

Safety protocols developed through Chinese operations will inform the European deployment. Baidu also received permits to test autonomous vehicles in Hong Kong in November 2024, marking its first entry into a right-hand drive market.

The partnership structure allocates responsibilities strategically. Lyft will retain ownership of the operational marketplace, and Baidu will provide vehicle supply, technology validation and technical support, according to company statements.

Regulatory hurdles and market challenges

Despite the ambitious timeline, regulatory challenges remain. European authorities maintain stringent standards for data privacy and vehicle safety that could impact deployment schedules. The regulatory approval process in both Germany and the UK will likely require extensive documentation of safety protocols and operational procedures.

Operational challenges specific to European markets may also emerge. Previous analysis has highlighted how English country lanes, cobbled Paris streets, or the chaos of Neapolitan traffic will present similar challenges to those faced by autonomous vehicle operators in complex Asian urban environments.

The partnership could also reshape urban transportation economics in Europe. The alliance could disrupt urban transport with lower costs and enhanced efficiency, potentially affecting traditional taxi services and public transport use.

For both companies, the collaboration represents a strategic response to market pressures. Baidu faces increasing domestic competition and seeks international revenue diversification, while Lyft requires autonomous technology to compete with Uber’s expanding autonomous vehicle partnerships.

The deployment timeline of 2026 places both companies in direct competition with other major autonomous vehicle initiatives in Europe, setting the stage for what industry observers expect to be a transformative period for urban mobility.

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The dramatic reversal of Nvidia’s AI chip export restrictions against China signals a fundamental shift in US technology trade policy, revealing how both superpowers have weaponized their technological advantages in an escalating economic standoff.

While the US has restricted China’s access to advanced semiconductors to limit AI capabilities, China has retaliated by restricting the supply of rare earth materials that American manufacturers desperately need for everything from fighter jets to smartphones. 

Now, after months of economic brinkmanship, both nations are stepping back from the precipice—trading AI chips for access to rare earths in a deal that underscores how deeply intertwined their technological futures remain, despite growing geopolitical tensions.

High-stakes reversal after months of restrictions

Nvidia, the world’s most valuable company with a $4 trillion valuation, announced Monday that it has received government assurances to resume sales of its H20 artificial intelligence chip to Chinese customers after a four-month embargo. 

The move follows a pivotal meeting between Nvidia CEO Jensen Huang and President Donald Trump at the White House, where the chipmaker’s leadership argued that continued restrictions could undermine America’s global AI dominance.

“We were recently informed by the Department of Commerce that license applications to export MI308 products to China will be moving forward for review,” AMD stated Tuesday, confirming it would also resume AI chip shipments once licenses are approved. 

The policy reversal represents one of the most significant developments in US-China technology relations since export controls were first implemented, affecting billions of dollars in trade and potentially reshaping the global AI competitive landscape.

Rare earth materials drive strategic calculations

Commerce Secretary Howard Lutnick revealed that the resumption of semiconductor exports is directly tied to broader negotiations over rare earth materials. “We put that in the trade deal with the magnets,” Lutnick told Reuters, referencing an agreement to restart rare earth shipments to US manufacturers.

China’s dominance over rare earth production—controlling approximately 85% of global processing capacity for the 17 metals essential to smartphones, military equipment, and electric vehicles—has provided Beijing with significant leverage in trade negotiations. 

The country had halted rare earth exports in March following escalating trade tensions with the Trump administration. Treasury Secretary Scott Bessent characterized the Nvidia export controls as a “negotiating chip” in larger US-China trade discussions, according to Bloomberg, highlighting how semiconductor policy has become intertwined with broader economic and strategic considerations.

Massive financial stakes for industry leaders

The export restrictions have imposed substantial costs on American technology companies. Nvidia estimated a US$2.5 billion shortfall in H2 sales during the first quarter of 2025, with projected losses of US$8 billion in the second quarter. Overall, the company calculated that export curbs would reduce annual revenue by US$15 billion.

For Nvidia, China represents a critical market generating US$17 billion in revenue during fiscal 2024—approximately 13% of total sales. The company’s stock surged 4% following the resumption announcement, while AMD shares gained 7%, reflecting investor relief over restored market access.

“The Chinese market is massive, dynamic, and highly innovative, and it’s also home to many AI researchers,” Huang told Chinese state broadcaster CCTV Tuesday, emphasizing the strategic importance of Chinese partnerships for Nvidia’s continued growth.

Congressional opposition highlights bipartisan concerns

The decision has encountered sharp criticism from US legislators across party lines, who express concern about potential national security implications. Democratic Representative Raja Krishnamoorthi described the move as “dangerously inconsistent” with previous administration positions on China export controls.

Republican John Moolenaar, chair of the House Select Committee on China, demanded clarification from the Commerce Department. “The H20 is a powerful chip that, according to our bipartisan investigation, played a significant role in the rise of PRC AI companies like DeepSeek,” Moolenaar stated, referencing a Chinese startup claiming to build AI models at significantly lower costs than US competitors like OpenAI.

The congressional pushback underscores ongoing tensions between economic interests and national security considerations that have characterized US technology policy toward China.

Chinese companies scramble for chip access

News of the resumption has triggered an immediate scramble among Chinese technology companies to secure H20 chip allocations, according to Reuters sources familiar with the procurement process. Internet giants ByteDance and Tencent are reportedly submitting applications through an approved vendor list system managed by Nvidia.

While H20 chips lack the full computing power of unrestricted Nvidia processors due to previous export limitations, they remain compatible with Nvidia’s CUDA software platform—considered the industry standard for AI development globally. This compatibility provides Chinese developers with access to established development tools and frameworks essential for competitive AI research.

The volume of chips ultimately approved for export will determine the strategic significance of this policy shift. AI expert Divyansh Kaushik from Beacon Global Strategies warned that substantial access could dramatically alter competitive dynamics. “If China can get a million H20 chips, it could significantly narrow, if not overtake, the US lead in AI,” he said.

Huang has consistently argued that restricting American technology access to Chinese developers ultimately undermines US leadership by encouraging domestic alternatives. Chinese companies like Huawei have accelerated the development of indigenous chip designs, potentially reducing long-term dependence on American technology.

“For America to be the world leader, just like we want the world to be built on the American dollar, using the American dollar as a global standard, we want the American tech stack to be the global standard,” Huang told CNN’s Fareed Zakaria, articulating Nvidia’s strategic vision for maintaining technological influence.

Regional impact and future outlook

For Asian technology companies and governments, the resumption of Nvidia China AI chip sales represents both opportunity and uncertainty. Regional partners have watched closely as US-China technology tensions have disrupted global supply chains and forced difficult choices between competing technological ecosystems.

The rapid reversal of export restrictions demonstrates how quickly geopolitical and economic pressures can reshape technology trade policy, creating ongoing uncertainty for companies planning long-term AI investments and partnerships across the region.

As Huang prepares for a media briefing in Beijing Wednesday during his second visit to China this year, the technology industry continues adapting to an increasingly complex landscape where AI advancement, national security concerns, and economic leverage intersect in unprecedented ways.

The post US lifts Nvidia AI chip export ban to China in rare earth trade deal appeared first on TechWire Asia.

Yet many organisations are constrained by legacy infrastructure that stifles innovation, introduces risk, and slows response times. Complex architectures, performance bottlenecks and security gaps can turn opportunity into operational burden.

Verizon Business helps enterprises overcome their limitations with a future-ready network approach – flexible, secure, and intelligently adaptive to business needs in near real-time.

Why traditional networks fall short

Conventional network infrastructure was not designed for the complexities of today’s digital environment. As organisations pursue cloud migration, adopt AI tools, and connect distributed teams and devices, legacy systems can struggle to provide the required scalability, visibility and control.

The challenges are technical and commercial. Delayed insights, degraded user experience, and exposure to cyber threats each have bottom-line impact.

“Digital transformation in APAC isn’t just accelerating – it’s diversifying. Businesses are adopting AI, cloud and IoT at different speeds and in different ways, but a common bottleneck is the rigidity of legacy networks,” says Duncan Kenwright, Managing Director, Global Solutions, APAC, Verizon Business.

“Systems were not designed to support dynamic, data-driven ecosystems. That’s where many enterprises are hitting limits – not just in performance, but in their ability to respond to opportunity.”

The adaptive network approach

Verizon’s network solutions reflect a change in philosophy, from static infrastructure to dynamic, intelligent connectivity. At the core is a fully converged, private IP backbone supported by one of the world’s few Tier 1 networks, which gives Verizon control over traffic routing, performance, and resilience.

Key capabilities include:

• Software-defined networking (SDN) for intelligent traffic management and policy enforcement,
• Network-as-a-Service (NaaS) for scalable, use-based consumption,
• Managed Network Services (MNS) that reduce operational overhead for IT teams,
• Secure Access Service Edge (SASE) to protect data and applications in distributed environments,
• Private 5G and edge computing for ultra-low-latency applications in manufacturing, healthcare, logistics and other industries.

With modular components, enterprises can tailor their networks for what they need now and in the future. This could be expanding a secure remote workforce, using AI for quality control in factories, or meeting compliance rules in different regions.

Turning infrastructure into advantage

By aligning network architecture with business objectives, Verizon can help organisations unlock measurable gains in agility, efficiency and customer experience.

• Improved agility: With programmable networks, businesses can respond quickly to changing market conditions, spin up services, or scale capacity with minimal disruption.
• Enhanced security: Verizon’s private backbone and embedded security controls reduce exposure to threats and help support zero-trust frameworks.
• Performance at scale: High-speed, low-latency connectivity supports mission-critical systems, from real-time analytics to robotic process automation.

“We’re helping our customers move from thinking of networks as infrastructure to seeing them as business enablers,” says Kenwright. “The right architecture gives enterprises the agility to pivot quickly, the security to operate confidently and the visibility to make informed decisions. In the AI era, that kind of adaptability is not a nice-to-have – it’s mission-critical.”

Built for APAC complexity

Asia Pacific enterprises face unique network demands, like multi-market operations, complex regulatory environments, and a range of infrastructure maturity. Verizon’s solutions are designed to overcome those challenges.

With operations in Australia, Singapore, Japan and beyond, Verizon provides:

• Regionally distributed infrastructure with global reach,
• Localised support for compliance, data sovereignty, and language,
• Sector-specific expertise in public sector, healthcare, financial services, and industrial operations.

For example, manufacturers deploying machine vision and AI need real-time feedback loops from production line to cloud platform. Verizon’s private 5G and edge solutions ensure data is processed where it’s generated to deliver precision, speed and quality control.

Supporting seamless transformation

Modernisation is usually a process, not a clean break with the past. Many businesses operate hybrid environments where legacy and modern systems need to coexist. Verizon’s network services are built with that reality in mind.

• Phased transformation: Verizon supports incremental upgrades, ensuring operational continuity while new technologies are integrated,
• Co-managed services: Organisations can rely on Verizon to maintain, monitor, and optimise networks while retaining strategic oversight,
• Cloud-native orchestration: Verizon’s platform simplifies network provisioning, scaling, and visibility, giving businesses more control and less complexity.

Flexibility lets enterprises evolve at their own pace, without compromising on performance or security.

Built-in security, end-to-end

Security is central to Verizon’s approach. With its private IP backbone, Verizon can isolate enterprise traffic from the public internet and maintain consistent performance even under pressure.

Core security features include:

• Near real-time threat detection and prevention
• Data loss prevention (DLP) and intrusion detection systems (IDS),
• Support for zero-trust network access and identity-based controls,
• Visibility into cross-border data flows to support compliance and reduce risk.

In a threat landscape where cyberattacks are automated and targeted, having security embedded in the network is essential, not optional.

Infrastructure that moves with you

Today’s business environment requires networks that are more than just fast. They have to be agile, intelligent and secure. Verizon’s adaptive approach lets enterprises establish a network backbone that evolves with their needs, turning challenges into opportunities, and fostering sustainable growth.

Whether your goals include scaling AI workloads, enabling edge analytics, or securing a hybrid workforce, Verizon provides the infrastructure to make it possible.

In an era when milliseconds are critical, your network should not merely keep pace – it should lead the way.

Learn how Verizon can help your business build an adaptive, future-ready network at: Verizon.com/business/en-au/solutions/adaptive-networks.

The post How Verizon helps APAC enterprises build adaptive digital networks appeared first on TechWire Asia.

Beijing has escalated tensions with Taiwan by threatening retaliation following the island’s decision to blacklist Chinese tech giants Huawei Technologies and Semiconductor Manufacturing International Corp (SMIC), marking a significant deterioration in cross-strait technology relations as both sides dig in for a prolonged economic confrontation.

According to Bloomberg, Taiwan Affairs Office spokeswoman Zhu Fenglian delivered a stern warning during a regular briefing in Beijing on Wednesday, declaring that China would “take forceful measures to resolutely safeguard the normal order of cross-strait economic and trade exchange.” The threat of Chinese retaliation comes in direct response to Taiwan’s unprecedented move to add major Chinese technology companies to its Strategic High-Tech Commodities Entity List.

Beijing’s response signals escalation

Zhu condemned Taiwan’s decision as “despicable” and claimed it displayed President Lai Ching-te’s loyalty to the US government, framing the export restrictions as evidence of Taiwan’s subordination to American strategic interests.

The spokeswoman’s comments represent the strongest official Chinese retaliation threat since Taiwan implemented the export controls over the weekend.

“Attempts to decouple will not delay the progress of industrial upgrading on the mainland,” Zhu said, adding that such actions will only damage the competitiveness of Taiwanese enterprises and the island’s economy.

However, she did not elaborate on specific measures Beijing might take in response to Taiwan’s actions. The Chinese retaliation warning reflects Beijing’s growing frustration with what it perceives as Taiwan’s alignment with US technology containment strategies.

Taiwan last week joined a yearslong US campaign to curtail China’s technological ascent by adding the country’s AI and chipmaking champions to its entity list, marking the first time Taipei has used the blacklist on major Chinese companies.

Strategic stakes in a cross-strait technology war

The new restrictions are likely to, at least partially, cut off Huawei and SMIC’s access to Taiwan’s plant construction technologies, materials and equipment essential to build AI chips, like those made by Taiwan Semiconductor Manufacturing Co for the likes of Nvidia Corp.

The represents a significant escalation in the technology dimension of cross-strait tensions. Taiwan’s decision bars the island’s firms from doing business with Huawei and SMIC without a licence, creating substantial new barriers for Chinese companies seeking to access Taiwan’s advanced semiconductor ecosystem.

For Beijing, this represents another layer of technological isolation that compounds existing US export controls. The timing of China’s retaliation threat also coincides with broader geopolitical tensions.

President Donald Trump’s administration has urged Taipei to take more ownership over chip restrictions on China, Bloomberg News previously reported, suggesting coordinated pressure on Taiwan to align more closely with US strategic objectives.

Economic vulnerabilities on both sides

While Beijing threatens forceful measures, both sides face significant economic vulnerabilities in any escalated confrontation. Taiwan’s semiconductor industry, dominated by companies like TSMC, has historically maintained complex relationships with Chinese customers despite political tensions.

Chinese retaliation could potentially target these commercial relationships, affecting Taiwan’s economic interests. However, China also faces constraints in its response options. Beijing’s own technology companies depend heavily on access to global supply chains, including components and equipment from Taiwan and other allied nations.

Aggressive retaliation could further isolate Chinese firms and accelerate the technological decoupling that Beijing claims to oppose. The mutual economic dependencies suggest that while both sides may engage in escalatory rhetoric, the practical scope for damaging retaliation remains limited by shared commercial interests.

Broader implications for the regional technology ecosystem

China’s retaliation threat underscores the broader transformation of the regional technology ecosystem along geopolitical lines. As Taiwan increasingly aligns its export control policies with US strategic objectives, Beijing faces growing pressure to develop alternative technological pathways that reduce dependence on democratic allies.

The confrontation also highlights the central role that Taiwan’s semiconductor industry plays in global technology competition. Beijing’s frustrated response to Taiwan’s export controls demonstrates the continued importance of Taiwanese technology capabilities for Chinese advancement in artificial intelligence and advanced semiconductors.

For regional technology companies and supply chains, the escalating tensions signal an environment of increasing uncertainty where commercial relationships become subject to political calculations. The threat of Chinese retaliation adds another layer of complexity for businesses navigating an already fragmented global technology landscape.

As both sides prepare for what appears to be a prolonged technology confrontation, the stakes extend beyond bilateral relations to encompass the broader question of how technological innovation and competition will be shaped by geopolitical rivalry in the years ahead.

Beijing’s retaliation threat suggests that neither side is prepared to back down from what has become a defining contest over the future of global technology leadership.

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