The United Arab Emirates has announced plans to introduce AI education in curriculum in all government schools, making AI a mandatory subject from kindergarten through to grade 12, starting next academic year.

The initiative, announced by Sheikh Mohammed bin Rashid, Vice President and Ruler of Dubai, aims to provide children as young as four with understanding of AI technologies, principles, and ethical considerations.

“Our goal is to teach our children a deep understanding of AI from a technical perspective, while also fostering their awareness of the ethics of this new technology, enhancing their understanding of its data, algorithms, applications, risks, and its connection to society and life,” Sheikh Mohammed stated on May 4.

Global context: A competitive landscape

The UAE’s announcement comes amid a global rush by multiple nations to integrate AI education into their curricula, with each country adopting distinctive approaches based on their educational priorities and technological aspirations.

In Beijing, China, primary and secondary school pupils will receive a minimum of eight hours of AI-focused lessons each academic year beginning this autumn. Children as young as six will learn how to engage with AI-powered tools, gain a foundational understanding of the technology, and explore ethical considerations surrounding its use.

The Beijing Municipal Education Commission recently announced that schools may integrate these lessons into existing subjects like information technology and science or offer them as standalone courses.

Its plan includes developing a multi-year AI curriculum, establishing a structured education and training system, introducing support initiatives, and promoting awareness of the program. China’s approach is particularly notable as it has already taken concrete steps toward implementation.

Last December, China’s Ministry of Education selected 184 schools to trial AI-focused curricula, forming the basis for future expansion. According to Minister Huai Jinpeng, AI represents a crucial component of China’s educational strategy.

Estonia, with its already strong digital education foundation, is taking a different path. Estonia’s government recently partnered with OpenAI to introduce AI-driven education tools to secondary school pupils and teachers. From September, students in Years 10 and 11 will gain access to customised AI learning platforms, with additional support for educators in lesson planning and administrative tasks.

Comparing approaches

While the UAE curriculum appears comprehensive on paper, with 7 key areas spanning from foundational concepts to community engagement, it’s important to note that there has been no announcement yet on whether private schools, which are regulated separately, will be instructed to roll out AI classes.

This contrasts with China’s approach which appears to be moving toward broader implementation beyond pilot programmes. The UAE’s plan is ambitious in its age range, starting with four-year-olds, which is younger than many other programmes globally.

The curriculum is broken into three cycles, with tailored units for each age group. Four-year-olds will engage in visual and interactive activities to discover AI through play, while older students progress to comparing machines to humans, designing their own AI systems, andtually learning command engineering with real-world scenarios.

South Korea and Canada have taken different approaches, incorporating AI into existing school curricula, offering AI-powered learning materials and classroom tools for teachers rather than creating entirely new subject areas. The integration model may prove more practical for educational systems that face challenges in adding new subjects to already crowded curricula.

Critical assessment

What distinguishes the various approaches is not necessarily which country is “leading,” but rather how each nation’s AI education strategy aligns with its broader technological and economic goals.

For the UAE, the emphasis appears to be on creating a framework that starts from the earliest years of education. Sarah Al Amiri, Minister of Education, described the integration of AI in education as a “national imperative” that “supports economic growth, fosters sustainable development and significantly enhances individual capabilities.”

However, experts might question whether starting AI education at age four is developmentally appropriate, or if the UAE’s education system has the necessary infrastructure and teacher training to deliver such an ambitious curriculum effectively. The practical considerations will determine the program’s success beyond the ambitious announcement.

China’s approach benefits from the country’s established technological infrastructure and its significant investments in AI research and development, potentially giving it advantages in implementation. The selection of 184 schools for trial programmes demonstrates a methodical approach focused on gathering data before broader implementation.

In the UK, the approach has been more fragmented with at least one private school launching an experimental learning space where students use virtual reality headsets and AI platforms instead of traditional teaching methods. This reflects a more market-driven approach compared to the centralised government initiatives seen in the UAE, China, and Estonia.

Balancing technology and pedagogy

All these initiatives face similar challenges regarding the balance between technological innovation and sound pedagogical approaches. While AI can transform education by making learning more accessible and personalised, education authorities worldwide remain cautious.

The United Nations has highlighted the importance of responsible AI implementation, recommending clear guidelines, inclusivity, and a focus on human-centred learning.

The rush to implement AI education also raises questions about equity and access. Will these programmes exacerbate existing digital divides between well-resourced and under-resourced schools? Will all teachers receive adequate training to deliver these curricula effectively?

Looking forward

Rather than crowning any nation as the definitive leader in AI education, it’s more accurate to observe that there is something of a global recognition of AI litreacy as a component of future education. Each country’s approach reflects its unique educational philosophy, technological capabilities, and strategic priorities.

The UAE’s ambitious programme, China’s methodical implementation, Estonia’s partnership model, and other nations’ varying approaches will provide data on the results of AI education strategies. The true test will be in implementation, teacher training, curriculum quality, and ultimately, student outcomes.

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For years, American consumers have enjoyed a steady stream of incredibly cheap Chinese goods flowing directly to their doorsteps. The $10 t-shirts, $15 electronics, and $5 household items that populated platforms like Temu and Shein seemed almost too good to be true. And in a way, they were – propped up by a little-known trade provision called the “de minimis exemption” that allowed packages valued under $800 to enter the United States completely duty-free.

But as of May 2, 2025, that era of Chinese import tariff-free bargain hunting has abruptly ended. President Donald Trump has officially closed this loophole, meaning those same goods could now cost more than double as they face tariffs of up to 145%. The $10 t-shirt you ordered last month might now cost $24.50. The household gadget that was once $20 could balloon to nearly $50. The seismic shift has sent e-commerce giants scrambling to adapt their business models and left American consumers facing a new reality: the days of ultra-cheap Chinese imports are over. As Temu blocks US shoppers from seeing Chinese import products and Shein quietly incorporates the cost from tariffs into its pricing, we’re witnessing nothing less than a fundamental restructuring of global e-commerce dynamics.

What was the de minimis exemption?

The de minimis exemption, introduced in 1938 as Section 321 of the Tariff Act of 1930, allowed packages valued under $800 to enter the United States duty-free. The provision was originally designed to facilitate trade by eliminating the administrative burden of collecting negligible duties on low-value goods at a high cost to the government. Over time, this exemption became what a Congressional Research Service report called the “primary path” for Chinese exports to enter the US market From 2018 to 2023, the value of low-value e-commerce exports from China ballooned from $5.3 billion to $66 billion, according to a February report from the Congressional Research Service. US Customs and Border Protection processed a billion such packages in 2023, the average value of which was $54.

Why did Trump end the exemption?

In a cabinet meeting at the White House on Wednesday, Trump referred to the loophole as “a big scam going on against our country, against really small businesses,” he said. “And we’ve ended, we put an end to it.” The Trump administration cited multiple reasons for eliminating the exemption:

• Fentanyl concerns: President Trump in February said he would eliminate the loophole because he didn’t believe China was taking sufficient action to stem the flow of fentanyl into the US The administration said drug traffickers were “exploiting” the loophole by sending precursor chemicals and other materials used to manufacture fentanyl into the United States without having to provide shipping details.
• Protecting American businesses and jobs: The growing use of the loophole also threatened US jobs in warehousing and logistics. It encouraged major American retailers to ship more products directly from China to consumers’ doorsteps, avoiding larger shipments that were subject to tariffs and then distributed through US warehouses and delivery networks.
• Supporting domestic manufacturers: Kim Glas, the president of the National Council of Textile Organisations, which represents American textile makers and fought to eliminate the loophole, said it had “devastated the US textile industry.” Glas said it had allowed unsafe and illegal products to flood the US market duty-free for years.

How are retailers responding?

Major Chinese e-commerce platforms are already adapting their business models:

• Temu announced a dramatic shift to its business model. “All sales in the USare now handled by locally based sellers, with orders fulfilled from in the country,” the company said in a statement to CBS MoneyWatch. The company said on Friday that it would no longer ship products from China into the United States. Temu saidthat it “has been actively recruiting USsellers to join the platform,” and that “all sales in the USare now handled by locally based sellers, with orders fulfilled from in the country.”
• Shein announced it would begin adjusting prices on April 25. The company’s website tells shoppers that tariffs are “included in the price you pay.”
• Other retailers have started displaying tariff surcharges in their online shopping carts to help consumers understand where added fees are coming from.

Impact on consumers and markets

The end of the de minimis exemption will have far-reaching consequences:

• Higher prices: According to The New York Times, Gabriel Wildau, a China analyst at Teneo, an advisory firm, said the change would “take a bite out of Chinese exports” and “force online retailers whose main selling point is dirt cheap prices to raise their prices dramatically.” Wildau warned, “It’s a price shock for price-sensitive US consumers who really enjoyed access to cheap goods.” The same article notes that goods coming into the United States from China via private carriers like DHL or FedEx will be subject to tariffs of at least 145% – for example, adding $14.50 of duties to a $10 T-shirt.
• Potential product availability issues: Mary Lovely, an international trade expert and senior fellow at the Peterson Institute for International Economics, told CBS News “You’ll see a much-diminished market and at some point, it won’t be worth it to import to a small market,” so you’ll see products disappearing. As reported by Wired, Temu is currently blocking US shoppers from seeing products shipped from China, effectively narrowing the number of goods for Americans to choose from.
• Shipping delays: Ryan Young, a trade policy expert at the Competitive Enterprise Institute, explained to CBS MoneyWatch that “It will be an administrative nightmare, so you will see a lot of delays.”
• Changing consumer behaviours: According to CBS News, PwC consumer markets industry leader Ali Furman expects to see consumers start “trading down” by swapping name brands for store labels or even turning to resale platforms to stretch budgets.

Potential loopholes and enforcement challenges

Despite the administration’s intentions, several potential issues remain: Goods that come into the US from China via private carriers like DHL or FedEx will be subject to tariffs of at least 145%. But shipments that come in through the Postal Service face either a tariff of 120% of the value of the goods or a fee of $100 per package, which increases to $200 in June. The Postal Service appears to face less scrutiny for collecting tariffs on goods shipped from China to other countries and then into the US through foreign postal services. However the Postal Service has not been legally required to collect information on where products originate, and neither are foreign postal services. That could lead to an increase in schemes that try to bypass China tariffs by using the post office. Experts also question whether the government has enough CBP agents to efficiently inspect packages and enforce policies. Ram Ben Tzion, CEO of Publican, a company that authenticates shipment documentation, told CBS MoneyWatch: “As these adjustments are made, a key question remains, which is the ability of CBP to effectively regulate and enforce these measures. As of today. CBP does not have that ability.”

Who benefits?

While consumers may face higher prices and delays, certain groups stand to benefit from this policy change: Companies that sell goods made in the US could face less competition as previously cheap China-made goods rise to new price highs. Larger corporations with bigger profit margins, or more diversified businesses, will likely fare better than smaller retailers that operate on thin profit margins, making it difficult to re-jigger supply chains.

The future of e-commerce

As both retailers and consumers adjust to this new reality, the landscape of online shopping is fundamentally changing. Ben Tzion said to CBS MoneyWatch, “the way we shop online will never be the same.” Specifically, “everything will take more time, cost more money, and everything that’s price-sensitive won’t be available,” he said. For Asian businesses exporting to the US, this represents a significant shift in the economics of cross-border e-commerce. Companies will need to reassess their supply chains, and pricing strategies, and possibly even consider establishing US-based operations to remain competitive in this new environment where the days of duty-free Chinese imports under $800 are now firmly in the past. The Chinese import tariffs policy change marks not just the end of an era of ultra-cheap online shopping, but also signals a broader realignment of global e-commerce dynamics that will continue to unfold in the coming months and years.

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China’s gaming and animation industries are no longer just local success stories. With titles like Black Myth: Wukong and Ne Zha 2 drawing attention from global audiences, the country has shown its ability to produce content that travels well beyond its borders. At the same time, rapid adoption of artificial intelligence is reshaping how stories are made, blending machine efficiency with human creativity.

Tech Wire Asia spoke with Cheng Lu, President and CEO of CreateAI, about how Chinese studios are redefining entertainment, the role of AI in production, and what the future holds for immersive storytelling.

China’s growing influence in global gaming and animation

Asked about China’s role in shaping global entertainment over the next decade, Cheng points to the momentum already visible in the market. “China’s gaming and animation industries are gaining global dominance. Blockbusters like Black Myth: Wukong and Ne Zha 2 are showcasing our ability to captivate audiences worldwide,” he said.

That influence is backed by strong numbers. According to the “2025 H1 China Game Industry Report” from the Game Publishing Committee, the industry generated RMB 168 billion (USD 23 billion) in sales revenue in the first half of 2025 – a 14% year-on-year increase. Chinese self-developed games earned USD 9.5 billion overseas, underscoring their reach in a global market worth around USD 250 billion.

Cheng sees the next decade as one where Chinese studios can lead in immersive, AI-enhanced storytelling. “Fueled by rapid AI adoption and investment in creative production, Chinese studios are redefining entertainment with innovative technology and cultural storytelling,” he explains. “Over the next decade, China is likely to lead in immersive, AI-enhanced storytelling and cross-platform experiences, shaping global trends by blending technology with cultural heritage.”

Balancing AI efficiency and human artistry

AI has become more visible in creative production pipelines, raising the question of how to balance machine efficiency with human artistry. Cheng notes that animation, especially 2D, has long been labour-intensive. Scriptwriting, keyframing, and colouring often slow production, particularly when there’s a shortage of skilled animators.

Here, AI can make a difference without displacing artists. “AI can help studios produce higher-quality content more efficiently without sidelining human creators,” Cheng says. Tools like Animon.ai can turn simple images into anime videos, reducing repetitive tasks and giving artists more time to focus on storytelling.

The idea of synergy – AI handling technical tasks while humans guide the creative heart – runs through Cheng’s perspective. He points to the company’s recent release for example: “Our Animon.ai Studio Version, launched in July, exemplifies this approach by providing creators with tools like high-quality 2K visual generation and consistent keyframe editing, enabling both professionals and beginners to streamline workflows while retaining full creative control.”

Making local stories travel

Chinese titles often draw from local myths and traditions but still manage to resonate with audiences around the world. Cheng sees lessons here for other markets.

He highlights CreateAI’s game Heroes of Jin Yong, which reflects the role of chivalry in Chinese wuxia culture. “Chivalry is something that resonates in the world, but manifests uniquely in China with wuxia culture,” he explains. The broader lesson, he says, is to take cultural dynamics rooted in one place and show how they reflect universal human experience.

“All markets can consider cultural dynamics inherent to themselves that are shared in the human experience, and show how those come to fruition in their unique culture,” Cheng says. Done well, this approach lets people outside the culture connect to familiar values while sparking curiosity about a new one.

The future of immersive entertainment

Advances in motion capture, real-time rendering, and AI animation are already changing the entertainment industry. Cheng expects those shifts to accelerate. He outlines two big trends:

1. The gamification of everything. “Top content is becoming more immersive and interactive,” Cheng says.
2. Cross-media synergies. “Blending between what is a video game and TV show, and video game IP are being made into anime shows, and vice versa.”

At CreateAI, the team is exploring both directions. With the Three-Body Problem franchise, they are working on an anime feature film and a AAA video game, based on the second book of the series. The goal is to launch them side by side. “The generates maximum consumer exposure and greatly enhances fan experience,” Cheng says.

As AI gains the ability to generate characters, voices, and entire worlds, questions about authenticity and ethics are unavoidable. Cheng is clear on this point: “We believe in ‘safe AI’ and will do our part to promote the generative AI industry to grow according to high ethical values and local regulations.”

Asked to compare how AI and gaming innovation differ in regions, Cheng avoids making sweeping claims. “AI and gaming are truly global industries facing global competition,” he says. Still, he notes that companies succeed by excelling in three areas: creating compelling intellectual property, applying new technology for efficiency or storytelling, and using effective distribution channels.

Skills the next generation of China’s gaming creators will need

Looking ahead, Cheng sees a need for a new mix of skills among animators, developers, and storytellers. “The next generation of animators, game developers, and storytellers will need to blend technical proficiency with creative adaptability to thrive in an AI-driven industry,” he says.

A key mindset is to see AI as a tool for expansion rather than replacement. “Viewing AI as an opportunity to create more content, rather than a replacement, is key,” Cheng stresses. He also underlines the importance of cultural sensitivity and narrative innovation – qualities that make stories resonate beyond their home market.

Opportunities in China’s gaming and animation with AI

When asked what excites him most about the future, Cheng points to AI’s potential to open creation to more people. “At CreateAI, what excites us most is AI’s potential to democratise creation and deliver deeply personalised, immersive experiences,” he says.

“Our tools allow any fan to become a creator, freeing new opportunities in the creative economy, while adaptive narratives create immersive experiences,” Cheng explains. He sees breakthroughs coming from cross-platform projects, using global IPs like Heroes of Jin Yong and The Three-Body Problem to build both anime and AAA games.

That approach, he says, creates communities of fans and creators who help redefine how stories are consumed. “We have a full pipeline of projects currently, but we are always opportunistic to work with strong IP holders, using our technology and development know-how to innovate and bring immersive content to a global audience.”

Closing thoughts

From China’s expanding influence in the global gaming market to the role of AI in reshaping production, Cheng Lu’s perspective underscores how technology and cultural storytelling are increasingly intertwined. The future of entertainment, he suggests, won’t be about choosing between AI or human creativity but about finding new ways for them to work together.

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“When the chips are down, you can bet on India,” Prime Minister Narendra Modi declared as he received the country’s first indigenous 32-bit microprocessor this week. The Vikram processor, developed by ISRO’s Semiconductor Lab, marks India’s entry into domestic chip production – a journey that began just four years ago and faces its first commercial test by year-end.

Modi announced Tuesday that commercial chip manufacturing will begin by the end of 2025, transitioning India from a semiconductor importer to a producer. The statement came as industry leaders gathered for Semicon India 2025, where the scale of the country’s ambitions became clear.

The numbers behind the push

India has committed US$18 billion in 10 semiconductor projects, representing one of the largest industrial investments in the country’s recent history. The government allocated ₹76,000 crore (US$9.1 billion) through the Production Linked Incentive scheme, with ₹65,000 crore already committed to approved projects, according to the Press Information Bureau.

The market trajectory shows rapid growth: from US$38 billion in 2023 to an estimated $45 – 50 billion in 2024 – 25. The government targets a projected US$100 – 110 billion by 2030, though achieving this would require sustaining growth rates that few countries have managed in semiconductor manufacturing.

The financial scale reflects both opportunity and risk. Semiconductor manufacturing requires sustained capital investment over many years, with no guarantee of commercial success. Historical attempts by countries, including Malaysia, Thailand, and others, have demonstrated the difficulty of building competitive chip industries from scratch.

From test chips to commercial reality

The CG Power facility in Sanand, Gujarat, launched in August 2024, represents India’s first operational semiconductor assembly and test capability. The facility currently handles 0.5 million units per day, with plans to scale to 14.5 million units daily. CG-Semi expects to produce the first commercial “Made in India” chips from the facility.

The Vikram processor demonstrates existing capabilities but also limitations. Fabricated using 180-nanometer CMOS technology, it functions in space applications but represents older technology compared to the 3-nanometer processes that define current leading-edge manufacturing.

Major international partnerships include Micron Technology’s ₹22,516 crore investment in Gujarat and Tata Electronics’₹91,000 crore partnership with Taiwan’s Powerchip Semiconductor Manufacturing Corp. The partnerships provide technology transfer and expertise, though they also highlight India’s current dependence on foreign knowledge and equipment.

Technology gap: 25-year-old manufacturing process

The Vikram processor demonstrates both capabilities and limitations of India’s current semiconductor manufacturing. Fabricated using 180-nanometer CMOS technology – state-of-the-art in 2000 but now 25 years behind leading-edge processes – it functions reliably in space applications but highlights the technological gap India faces.

For context, today’s advanced smartphones use 3-nanometer chips, while even mid-range consumer electronics typically employ 7-14 nanometer processes. The 180nm technology, while proven and suitable for specific applications, represents a significant technological lag compared to current commercial standards.

Major international partnerships include Micron Technology’s ₹22,516 crore investment in Gujarat and Tata Electronics’ ₹91,000 crore partnership with Taiwan’s Powerchip Semiconductor Manufacturing Corp. The partnerships provide technology transfer and expertise, though they also highlight India’s current dependence on foreign knowledge and equipment.

Design capabilities and talent

India contributes approximately 20% of global semiconductor design, according to industry estimates. The Design Linked Incentive scheme has approved 23 chip design projects, supporting both startups and established companies.

Two 3-nanometer design facilities in Noida and Bengaluru position India among countries with advanced design capabilities. However, design capabilities differ significantly from manufacturing expertise. While India has demonstrated strong software and design skills, semiconductor manufacturing requires different competencies, including process engineering, yield optimisation, and supply chain management.

The government also reports training over 60,000 students in semiconductor-related skills, though industry sources suggest the sector will need significantly more specialised talent to achieve stated production goals.

Geopolitical context

India’s semiconductor push occurs amid global supply chain diversification efforts. Taiwan produces over 60% of global semiconductors and 90% of advanced chips, creating concentration risks that governments worldwide seek to address.

Japan’s commitment to invest 10 trillion yen (US$68 billion) in India, including semiconductor cooperation, reflects international interest in alternative manufacturing locations. However, these partnerships often come with technology transfer limitations and competitive constraints.

The US CHIPS Act, European Chips Act, and similar initiatives worldwide demonstrate how governments are subsidising domestic semiconductor capabilities. This creates both opportunities and challenges for India, as it competes for investment and talent in an increasingly crowded field.

Technical and economic challenges

The semiconductor industry presents formidable barriers to entry. Advanced chip manufacturing requires:

• Capital investments of US$10-20 billion per leading-edge facility
• Highly specialised equipment from a limited number of suppliers
• Process expertise that typically takes years to develop
• Consistent yields and quality that meet global standards

India’s current projects focus on assembly, testing, and older-generation manufacturing rather than cutting-edge production. While this provides a foundation, competing with established manufacturers in Taiwan, South Korea, and China requires capabilities that India is still developing.

Supply chain complexity adds another layer of difficulty. Semiconductor manufacturing depends on hundreds of specialised materials, chemicals, and components. Building reliable domestic suppliers for these inputs requires time and sustained investment.

Market realities

Industry observers note the gap between policy announcements and commercial execution. Producing test chips differs significantly from achieving commercial-scale manufacturing with competitive costs and yields.

Delta Electronics India’s Sanjeev Srivastava stated that “the semiconductor industry has started in India over the last 1-2 years,” acknowledging the sector’s early stage. Emerson’s Shitendra Bhattacharya noted that while semiconductors produced in India will target global markets, domestic demand is also rising, providing a potential foundation for the industry.

The economic multiplier effects remain theoretical until commercial production begins. Each semiconductor job typically supports additional positions in related industries, but these benefits depend on achieving sustainable production volumes.

Execution risks

Several factors could impact India’s semiconductor ambitions:

Technology access: Advanced semiconductor manufacturing depends on equipment from companies including ASML and Applied Materials. Export controls and technology restrictions could limit access to the latest capabilities.

Talent development: While India has engineering capabilities, semiconductor manufacturing requires specialised skills that differ from software development or design work.

Global competition: Established manufacturers benefit from decades of established supply chains, talent, and have gained economies of scale that new entrants find difficult to match.

Capital requirements: Semiconductor technology evolves, requiring continuous investment. The industry’s capital intensity has, historically, challenged even well-funded government initiatives.

Assessment

India’s semiconductor initiative shows early progress, with operational facilities and international partnerships providing a foundation for expansion. The country’s design capabilities and engineering talent offer advantages, while government financial support addresses some traditional barriers.

However, the transition from current capabilities to competitive semiconductor manufacturing remains unproven. The industry’s technical complexity, capital requirements, and competitive dynamics present challenges that policy support alone cannot address.

The next 12-18 months will provide crucial evidence of India’s execution capabilities as commercial production begins and facilities scale operations. Success will depend on factors including yield rates, production costs, and quality standards that meet global market requirements.

Modi’s declaration that “when the chips are down, you can bet on India” will face its first real test as the country attempts to transform semiconductor ambitions into commercial reality. The outcome will influence not only India’s technology sector but global supply chain dynamics in one of the world’s most strategic industries.

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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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Nvidia shares slipped on Wednesday as uncertainty grew around its business in China, caught in the middle of the trade fight between Washington and Beijing.

CEO Jensen Huang said he expects approval to restart sales of Nvidia chips in China after striking a deal with US President Donald Trump to pay commissions to the government. But with no formal rules yet, and doubts about whether Chinese regulators might discourage purchases, Nvidia left potential China sales out of its forecast for the current quarter.

That decision led to an outlook that looked steady but less than what investors have come to expect. Nvidia projected revenue of about US$54 billion for the third quarter, just above Wall Street estimates of US$53.14 billion, according to LSEG data. The forecast was enough to beat analyst targets but fell short of the “blowout” growth the market has grown used to, pushing the stock down 3.2 per cent in after-hours trading. That drop cut about US$110 billion from Nvidia’s US$4.4 trillion valuation.

As reported by Reuters, Huang downplayed concerns that the AI spending surge could be cooling, telling investors the opportunity could expand into a multi-trillion-dollar market over the next five years. “A new industrial revolution has started. The AI race is on,” he said, adding that Nvidia sees $3 trillion to $4 trillion in AI infrastructure spending by the end of the decade.

“Nvidia’s biggest bottleneck isn’t silicon, it’s diplomacy,” said Michael Ashley Schulman, chief investment officer at Running Point Capital. He added the company’s growth is “still impressive, but not as exponential.”

Second-quarter revenue reached US$46.74 billion, above the US$46.06 billion analysts expected. But the data centre segment, a key driver of Nvidia’s growth, missed some estimates. Analysts suggested that big cloud providers may be spending more carefully. Nvidia said around half of its US$41 billion in data centre revenue came from major cloud companies, slightly below Visible Alpha’s estimates of US$41.42 billion.

The company’s forecast also assumed no shipments of its H20 chips to China, even though some licenses to sell them have already been granted. Nvidia said that if geopolitical hurdles ease and orders come in, H20 sales to China could add between US$2 billion and US$5 billion in the third quarter.

“That is a big question mark to watch,” said Ben Bajarin, CEO of consulting firm Creative Strategies.

Analysts also pointed out that Nvidia’s share price, which has risen by about one-third this year, may have created lofty expectations that are hard to meet. “The mega caps are the ones propelling a lot of the capex that Nvidia is benefiting from. But obviously Nvidia still is growing, is able to sell,” said Matt Orton of Raymond James Investment Management, who argued the durability of the AI trade remains intact.

Even so, demand for Nvidia’s chips remains strong. Businesses racing to build generative AI systems continue to buy the company’s processors, which are designed to handle huge amounts of data quickly. CFO Colette Kress said Nvidia’s “sovereign AI” push — aimed at selling AI hardware and software to governments, including outside China — is on track to bring in US$20 billion this year. She added that cloud and enterprise customers could spend as much as US$600 billion on AI in 2025 alone, with total infrastructure spending tied to AI reaching US$3 trillion to US$4 trillion by the end of the decade.

Huang said much of this growth will come from hyperscalers like Microsoft and Amazon, which are expected to spend about US$600 billion on data centres this year. He added that for a US$60 billion data centre, Nvidia can capture roughly US$35 billion in revenue.

Big Tech firms including Meta and Microsoft are spending heavily on AI, much of it flowing toward Nvidia chips. For the current quarter, Nvidia forecast adjusted gross margins of 73.5 per cent, a touch above analyst estimates of 73.3 per cent.

“The data centre results, while massive, showed hints that hyperscaler spending could tighten at the margins if near-term returns from AI applications remain difficult to quantify,” said Jacob Bourne, an analyst at eMarketer.

Shares of rival Advanced Micro Devices, which is developing competing AI servers, also fell 1.4 per cent after Nvidia’s results.

AI enthusiasm, with Nvidia at the centre, has been one of the main drivers of the S&P 500’s rally over the past two years. But the company’s latest report drew a more muted response.

“This is the smallest reaction to an earnings report in Nvidia’s AI incarnation,” said Jake Behan, head of capital markets at Direxion in New York. “While it may not have been a blowout, it’s not a miss.”

Outside China, Nvidia is still seeing strong demand for its H20 chips. Kress said one customer alone bought US$650 million worth during the second quarter.

Huang also said the company’s high-end Blackwell chips are already largely booked through 2026, while its older Hopper processors remain in demand. “The buzz is: everything sold out,” Huang told analysts, describing the pace of orders.

The company also said its board had approved an additional US$60 billion in share buybacks.

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Bangkok has quickly become one of Southeast Asia’s largest data centre hubs, according to a report from DC Byte. With IT capacity now above 2.5GW, it sits just behind Johor in regional capacity ranking. Growth is powered by specific advantages: available land, steady power supply, and a location that connects East and West. The factors are drawing in major operators and global cloud companies.

Until recently, Thailand’s data centre market was made up of smaller, retail-style sites. Over the past two years, that has shifted toward full-scale campuses and large, multi-building projects. New development is also spreading outside central Bangkok into the Eastern Economic Corridor, especially in Chonburi, which is emerging as a strategic zone for hyperscale builds.

Global players and big investments

Amazon Web Services, Google, Microsoft, and Chinese providers including Huawei, Alibaba, and Tencent have committed to major projects in Thailand. Examples include Bytedance’s $8.8 billion investment, AWS’s $5 billion expansion, Google’s $1 billion site in Chonburi, and Microsoft’s first Thailand cloud region.

Operators like STT GDC, Equinix, DAMAC Digital, and Evolution Data Centres are also expanding. Between 2019 and 2024, Bangkok’s total IT capacity grew more than twenty-fold, with pipeline capacity rising at an average of about 40% each year.

At present, Bangkok has around 120MW of live capacity, with more expected before year-end as sites under construction come online. The next two years is expected to see another surge, with large projects from Google, DayOne, and Edgnex Data Centres by DAMAC among those set to launch.

Eastern Economic Corridor becomes Thailand’s data centre hub

The Eastern Economic Corridor (EEC) is fast becoming Thailand’s centre for large-scale deployments. Chonburi and Rayong are attractive for hyperscalers because of cheaper land, existing infrastructure, and easy access to ports and industrial zones.

Chonburi is now home to some of the country’s biggest upcoming builds. Projects like DayOne’s 120MW Tech Park and Bridge Data Centres’ planned 200MW campus will increase local capacity. Demand is so strong that both local and global operators are already locking in space before builds are complete.

One of the biggest announcements came in 2024, when Doma Infrastructure Group revealed plans for 1.5GW of green data centre campuses in the EEC. That accounted for most of the 1.7GW increase in early-stage capacity during the year, marking the shift from smaller facilities to large, multi-site campuses.

Cloud and AI power Thailand’s data centre demand

Cloud services remain the main source of growth, making up about 38% of Thailand’s total capacity in early 2025. AI is quickly catching up, rising from 20% of demand in 2024 to 28% just a year later. Growth is being fueled by AI training, large language models, and other data-heavy applications.

To meet the need, operators are working with partners like Siam AI Corporation, an NVIDIA cloud partner, to design facilities built for high-density AI workloads. The efforts could help Thailand develop into both a regional cloud hub and a centre for AI innovation.

Public and private efforts align

Government support is also shaping the market. Partnerships with NVIDIA aim to build sovereign AI capabilities, while major operators like True IDC, Edgnex Data Centres by DAMAC, and GSA Data Center Company are teaming up with Siam AI Corporation on AI-focused cloud services.

The mix of public and private investment is establishing the groundwork for next-generation infrastructure. With rising demand for AI and cloud services, Thailand is positioning itself to meet regional needs and strengthen its role in the wider Southeast Asian market.

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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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Storage cards keep getting smaller, but faster speeds usually mean bigger hardware. MicroSD cards are tiny, easy to slip into almost any device, but they can’t keep up with the pace of modern gaming or high-resolution video. At the other end, M.2 SSDs deliver blistering speed but take up far more room. Now, a new format from China promises to combine both traits – small enough to rival MicroSD, but fast enough to compete with much larger drives, as reported by The Verge.

The format is being called the Mini SSD, and the first devices using it have already been revealed. Biwin, a Chinese storage company, is leading the move with its 15mm x 17mm design, also referred to as the “1517” after its dimensions. At just 1.4mm thick, it’s only slightly bigger than a MicroSD card and smaller than a US penny. Despite that, Biwin says it can reach sequential read speeds of 3,700MB/s and write speeds of 3,400MB/s, connecting over PCIe 4.0 x2. It’s being offered in 512GB, 1TB, and 2TB capacities – a range that would normally require a much larger form factor.

Speed in perspective

To understand what that means, it helps to compare it with current options. MicroSD Express cards, which are used in the Nintendo Switch 2, can only manage around 985MB/s, at best, making the Mini SSD more than three times faster. Standard SD Express cards can in theory beat it at 3,940MB/s, but they’re nearly double the size. M.2 drives, which dominate PC gaming setups, are still far ahead, with some models hitting 8,000MB/s or even 14,000MB/s. But those are much bigger devices designed for desktops or laptops.

Here’s how it stacks up against other storage cards and SIM cards commonly found in phones and handhelds:

Designed like a SIM card

The Mini SSD uses a tray system similar to smartphone SIM cards. You poke in a pin, slide the tray out, and swap storage the same way you’d change a SIM. The design could make it easy to add or replace storage in devices that normally don’t leave room for bulky drives.

Biwin is pitching the form factor for laptops, tablets, cameras, and phones. It’s also rated IP68 for water and dust resistance and can survive a three-metre drop, making it a fit for outdoor devices and action cameras. But since it’s not an official JEDEC standard yet, there’s no guarantee other manufacturers will adopt it. For now, it’s an experimental format backed by a single company.

First adopters: gaming handhelds

Handheld gaming systems seem to be among the first to try the format. At the ChinaJoy expo, two upcoming devices showed off support for the Mini SSD. GPD’s Win 5, which runs AMD’s Strix Halo chip, also demonstrates the new storage slot. OneNetbook’s OneXPlayer Super X, a hybrid laptop and tablet using the same chip, also advertised its own Mini SSD slot. Both systems are designed to run high-end PC games on the go, making fast storage a priority.

The comparison with Nintendo is clear: while the Switch 2 is sticking with microSD Express, these Chinese handhelds are pushing a faster, albeit less tested, alternative. If it works as promised, players could see shorter load times and smoother performance without sacrificing portability.

What comes next

The biggest question is whether Mini SSD can become a true standard or if it will remain limited to a few niche devices. Without wider adoption, it risks being another short-lived format. There’s also no word on pricing yet, or when cards and readers will be available for purchase.

Still, the idea is appealing: a storage card that combines the size of a MicroSD with the performance of at least an SSD. If it spreads beyond gaming into laptops, phones, or cameras, it could change how devices handle expandable storage. For now, though, it’s a glimpse of what could be the next step in compact, high-speed storage.

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The Huawei Cloud AI Ecosystem Summit APAC 2025 brought together government leaders, industry experts, and technology partners to discuss how artificial intelligence is already changing the way people work, learn, and live in Malaysia and ASEAN. The gathering highlighted not only new technologies but also the partnerships and governance needed to make AI effective and trustworthy.

The summit is part of the Huawei Cloud APAC AI Ecosystem Initiative, a programme aimed at building an inclusive AI community by developing local skills, encouraging cooperation between sectors, and ensuring AI benefits are shared widely.

Government support for AI development

At the ASEAN AI Summit’s opening day, Huawei Technologies (Malaysia) CEO Simon Sun announced new AI initiatives. Malaysia’s Prime Minister, YAB Dato’ Seri Anwar Ibrahim, was present to witness the launch, underscoring the government’s view that AI is central to the country’s economic growth. The commitment is reflected in strategies that link public and private sectors and aim to prepare the country for a future where AI shapes every major industry.

Huawei Cloud’s three core capabilities

Huawei Cloud has built its AI approach around three capabilities. First, a global network of 34 regions and 101 availability zones (AZs) – including five regions and 17 AZs in ASEAN – provides the infrastructure for low-latency access. Second, an AI cloud service that supports more than 160 open-source models, allowing flexibility for development in different industries. Third, the Pangu multimodal models form the backbone of the company’s “AI for Industries” strategy; tailored solutions for manufacturing, healthcare, transport, among others.

On day two, the AI Ecosystem Summit drew about 300 delegates from the region. Li Yin, CTO of Huawei Cloud Enterprise Intelligence, led a session titled Leap to Cloud, Heading to AI, in which she shared examples of how Huawei Cloud has worked with customers in more than 30 industries and applied AI to over 500 scenarios worldwide.

See also: Huawei to unveil tech to cut China’s reliance on foreign AI memory chips

Li explained that with the Pangu foundational large model, ModelArts AI toolchain, and proven engineering methods, organisations can use own data to develop and refine models quickly. She pointed to three areas where Huawei Cloud will continue to invest: strengthening secure AI computing infrastructure, building industry-focused solutions like enterprise AI assistants and AI video applications, and expanding the partner ecosystem to speed adoption.

Malaysia’s focus on ethical and sustainable AI

Minister of Digital, YB Gobind Singh Deo, used his keynote to make clear that Malaysia’s AI journey is about more than just technology. Ethical use, sustainability, and shared benefit are all priorities.

“Our National AI Office (NAIO) has been speeding up the completion of the AI Technology Action Plan 2026 – 2030 and relevant regulatory frameworks to ensure the adoption of AI technology in key sectors in the country are ethical, sustainable and of high value,” he said.

He linked the goals to the Malaysia Digital Economy Blueprint and the Malaysia Digital (MD) initiative, saying both are strengthened through close cooperation with technology partners. Every step we take is action-driven, grounded in strong public-private collaborations, to shape Malaysia’s digital economy,” he said.

Building Malaysia’s AI talent pipeline

Simon Sun highlighted Huawei’s investment in local expertise through the Huawei Malaysia AI Talent Programme.

“We have set the goal of nurturing 30,000 Malaysian AI talents, comprising students, government officials, industry leaders, think tanks, associations, and others under this initiative in the coming three years,” he said.

He said AI is already making an impact in areas like fraud detection in banking, predictive maintenance in factories, supply chain management, and personalised learning in schools. Huawei’s localised partnerships, he said, ensure global expertise is applied in ways that suit ASEAN’s needs.

Real-world applications from Huawei partners

The summit also gave the stage to Huawei customers, who shared how they use AI in their own sectors.

William Zhou, Vice President of IFLYTEK Open Platform, said that while computing power and platforms form the base of AI systems, the real value comes from the application layer – where solutions are integrated into daily work. He said that Knowledge Q&A systems are among the most requested features from customers in government, telecom, and finance, but said successful deployment depends on close collaboration.

“The key is not the technology alone, but working closely with the customer to fine-tune the model and increase efficiency,” Zhou said, pointing to a Middle Eastern project that improved performance significantly in just two months.

He also described how subtitling and translation tools are vital in multilingual regions, with IFLYTEK solutions optimised for English, Malay, and Cantonese, which enable fast turnaround for media companies in Southeast Asia. In sectors where data must stay on-site, he said the ‘Spark’ all-in-one on-premise AI solution allows organisations to train and run models securely.

Dato Fadzli Shah, Co-Founder of Zetrix, discussed the link between AI, blockchain, and self-sovereign identity. He said these technologies could allow data from separate systems to be referenced securely without forcing organisations to adopt a single standard. Blockchain-backed digital identities, he added, could be used in education, finance, and trade to help ensure credentials remain verifiable.

He said Malaysia should develop specialist AI models trained on local data to ensure accurate interpretation of laws, policies, and cultural contexts. “We believe no single AI will dominate globally; instead, there will be natural product-market fit for specific stacks serving specific solutions.”

Henry Li Nan, Managing Director of TrustDecision Malaysia, shared how AI-powered decision intelligence is helping the finance industry tackle fraud. His company processes more than 130 million interception events a year, protects over seven billion devices, and prevents an estimated USD$10 billion in potential losses annually.

Working with Huawei, TrustDecision uses cloud-native infrastructure to deliver real-time detection, compliance, and risk management services.

“The result is faster detection, smarter prevention, and greater confidence for financial institutions to stay ahead of threats,” Li said.

National AI Office: Matching the speed of change

Shamsul Izhan Abdul Majid, Head of the NAIO, warned that the speed of AI development is unlike anything seen before, with new versions emerging every few weeks. This, he said, means that plans and standards must be developed quickly and in cooperation with industry.

He called data “the most important asset” and said that in sensitive fields like healthcare or defence, Malaysia’s approach is to bring AI to the data rather than move the data to the AI.

See also: Huawei tries to push AI chips abroad as US pressure grows

Since its formation in December last year, the NAIO has worked with six sectors and identified 55 AI potential use cases, with more expected as engagement expands to state and local levels. The office is also promoting the creation of locally-trained models with strong cybersecurity safeguards and a focus on making AI understandable for everyone, not just technical experts.

“Doing AI for everyone requires collaboration,” he said. “The AI Office brings together experts and companies to plan Malaysia’s AI journey for the next five years… We must stay ready, responsible, and innovative.”

Closing call to action

In closing, Simon Sun encouraged all participants to take the ideas shared at the summit and turn them into practical projects. He described the event as “the starting point for more actions and ideas to shape a smarter and stronger ASEAN, powered by AI and driving digital economies.”

The summit’s discussions made one thing clear: AI’s future in Malaysia and ASEAN will depend not only on powerful technology, but on how well it is adapted to real-world needs, governed responsibly, and supported by a skilled and informed community.

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Chinese AI start-up Z.ai, formerly known as Zhipu AI, has made its GLM models compatible with Huawei Technologies’ processors, adding momentum to China’s efforts to build up its own technology supply chain, according to the South China Morning Post.

The Beijing-based company said its models now work with Huawei’s Ascend chips, used in AI servers, and Kirin processors, which power smartphones and laptops.

“The tie-up marks a major breakthrough in cloud-device collaboration between home-grown large [language] models and computational architecture, highlighting the deeper integration of a domestic AI ecosystem,” Z.ai said.

The move comes shortly after Huawei announced it would open-source its Compute Architecture for Neural Networks (CANN) – the software toolkit for its Ascend processors. Opening the code lets developers build, adapt, and scale applications for domestic chips without relying on foreign platforms.

CANN competes with Nvidia’s proprietary CUDA toolkit, long used by Chinese AI developers who depend on the US company’s GPUs in many data centres. Working with Z.ai helps Huawei push wider use of its own processors in AI projects.

Last month, Huawei’s Ascend division became a founding member of the Model-Chips Ecosystem Innovation Alliance, alongside Chinese AI companies like StepFun, Infinegence AI, SiliconFlow, MetaX, Biren Technology, Enflame, Iluvatar Corex, Cambricon Technologies, and Moore Threads.

Z.ai said it will use CANN to fine-tune its GLM models on Huawei’s Ascend-powered cloud, showing the open-source toolkit in action.

In June, OpenAI described Zhipu – before its rebranding – as making “notable progress” in delivering AI infrastructure to governments and state-owned firms in non-Western markets. Backed by more than 10 billion yuan (US$1.4 billion) in funding, Z.ai filed pre-IPO documents in April, with plans to go public as early as 2026.

China’s response to GPT-5

OpenAI’s latest flagship model, GPT-5, debuted last week with claims of being “smarter, faster, and more useful,” offering improved abilities in coding, maths, writing, health, and visual perception. It also includes a “thinking” function that switches between standard and deep reasoning modes depending on the task.

“It’s like a PhD-level expert in anything, any area,” said OpenAI CEO Sam Altman.

In China, where OpenAI services like ChatGPT are unavailable, experts were unconcerned about falling behind.

“GPT-5 is not significantly ahead of Chinese models, so it won’t put substantial pressure on Chinese researchers and developers,” said Zhang Linfeng, assistant professor at Shanghai Jiao Tong University. He added the model “doesn’t come with revolutionary breakthroughs; it lacks memorable characteristics.”

Zhang noted that the “thinking” feature is already in some Chinese systems, including Alibaba’s AI products. Still, he credited OpenAI with reducing hallucinations – incorrect AI outputs – and improving coding and general intelligence.

Despite the muted reaction, interest was high. A GPT-5 discussion on Zhihu drew more than 3.2 million views, with some users praising the upgrades. GPT-5 is now the default model on ChatGPT for both free and paid users, and Microsoft is adding it to products like GitHub Copilot and Visual Studio Code.

AI talent in high demand

Competition for AI experts in China is also heating up where Alibaba’s Tongyi Lab, creator of the Qwen open-source models, has lost senior staff to rivals.

Yan Zhijie, who joined Alibaba in 2015 and led Tongyi’s speech lab, left in February. He joined JD.com’s Explore Academy but later moved to Tencent, leaving soon after an internal restructuring. His role was filled by Li Xiangang, co-founder of 01.AI.

Bo Liefeng, former head of Tongyi’s applied vision division, has also moved to Tencent’s Hunyuan AI team. Tencent and Alibaba did not comment.

Alibaba says its Qwen models have been downloaded over 400 million times worldwide, leading to the creation of 140,000 derivative models.

The flow of talent mirrors trends in the US, where firms like Meta have hired away AI experts from Google, OpenAI, and Apple. In China, ByteDance, Alibaba, and Tencent have all launched fresh recruitment drives, many aimed at AI research roles.

ByteDance’s “Top Seed Talent Programme” lists 65 AI-related openings, while Alibaba’s “Star Top Talent” campaign is targeting researchers in foundational models, infrastructure, and AI applications. Tencent recently opened internal applications for roles tied to its Yuanbao chatbot, Hunyuan model, and WeChat e-commerce.

As China pushes to build its AI ecosystem with home-grown chips and models, the fight for top talent is becoming as important as the technology itself.

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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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