NVIDIA has introduced the Rubin CPX, a new type of GPU designed for long-context AI processing. The chip is built to handle workloads that require models to process millions of tokens at once – whether that’s generating code in entire software projects or working with video content an hour in length.

Rubin CPX works alongside NVIDIA’s Vera CPUs and Rubin GPUs inside the Vera Rubin NVL144 CPX platform. A single rack delivers 8 exaflops of AI compute, with 7.5 times the performance of NVIDIA’s GB300 NVL72 system, along with 100 terabytes of fast memory and bandwidth of 1.7 petabytes per second. Customers can also adopt Rubin CPX in other system configurations, including options that reuse existing infrastructure.

Jensen Huang, NVIDIA’s founder and CEO, described the launch as a turning point: “The Vera Rubin platform will mark another leap in the frontier of AI computing – introducing both the next-generation Rubin GPU and a new category of processors called CPX. Just as RTX revolutionised graphics and physical AI, Rubin CPX is the first CUDA GPU purpose-built for massive-context AI, where models reason in millions of tokens of knowledge at once.”

From coding to video generation

The demand for long-context processing is growing fast. Today’s AI coding assistants are limited to smaller code blocks, but Rubin CPX is designed to manage far larger projects, with the ability to scan and optimise entire repositories. In video, where an hour of content can take up to one million tokens, Rubin CPX combines video encoding, decoding, and inference processing in a single chip, making tasks like video search and generative editing more practical.

The GPU uses a monolithic die design based on the Rubin architecture, packed with NVFP4 compute resources for high efficiency. It delivers up to 30 petaflops of compute with NVFP4 precision and comes with 128GB of GDDR7 memory. Compared to NVIDIA’s GB300 NVL72 system, it provides triple the speed for attention mechanisms, helping models handle longer sequences without slowing down.

Rubin CPX can be deployed with NVIDIA’s InfiniBand fabric or Spectrum-X Ethernet networking for scale-out computing. In the flagship NVL144 CPX system, NVIDIA says customers could generate $5 billion in token revenue for every $100 million invested.

Beyond Rubin CPX itself, NVIDIA also highlighted results from the latest MLPerf Inference benchmarks. Blackwell Ultra set records on new reasoning benchmarks like DeepSeek R1 and Llama 3.1 405B, with NVIDIA being the only platform to submit results for the most demanding interactive scenarios.

The company also set records on the new Llama 3.8B tests, Whisper speech-to-text, and graph neural networks. NVIDIA credited these wins partly to a technique called disaggregated serving, which separates the compute-heavy context phase of inference from the bandwidth-heavy generation phase. By optimising them independently, throughput per GPU rose by nearly 50%.

NVIDIA tied these results directly to AI economics. For example, a free GPU with a quarter of Blackwell’s performance could generate about $8 million in token revenue over three years, while a $3 million investment in GV200 infrastructure could generate around $30 million. The company framed performance as the key lever for AI factory ROI.

Rubin CPX is positioned as the first of a new class of “context GPUs” in NVIDIA’s roadmap. The company is also advancing the Rubin Ultra GPU, Vera CPUs, NVLink Switch, Spectrum-X Ethernet, and CX9 SuperNICs – all designed to work together in a one-year upgrade cycle. The roadmap emphasises NVIDIA’s push for full-stack solutions, not just standalone chips.

Industry adoption

Several AI companies are preparing to use Rubin CPX. The company behind Cursor, the AI-powered code editor, expects the GPU to support faster code generation and developer collaboration. “With NVIDIA Rubin CPX, Cursor will be able to deliver lightning-fast code generation and developer insights, transforming software creation,” said Michael Truell, CEO of Cursor.

Runway, a generative AI company focused on video, sees Rubin CPX as central to its work on creative workflows. “Video generation is rapidly advancing toward longer context and more flexible, agent-driven creative workflows,” said Cristóbal Valenzuela, CEO of Runway. “We see Rubin CPX as a major leap in performance, supporting these demanding workloads to build more general, intelligent creative tools.”

Magic, an AI company building foundation models for software agents, highlighted the ability to process larger contexts. “With a 100-million-token context window, our models can see a codebase, years of interaction history, documentation and libraries in context without fine-tuning,” said Eric Steinberger, CEO of Magic.

Supported by NVIDIA’s AI stack

Rubin CPX is integrated into NVIDIA’s broader AI ecosystem, including its software stack and developer tools. The GPU will support the company’s Nemotron multimodal models, delivered through NVIDIA AI Enterprise. It also connects with the Dynamo platform, which helps improve inference efficiency and reduce costs for production AI.

Backed by CUDA-X libraries and NVIDIA’s community of millions of developers, Rubin CPX extends the company’s push into large-scale AI, offering new tools for industries where context size and performance define what’s possible.

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Apple’s latest event introduced the new iPhone 17 lineup, the ultra-thin iPhone Air, major iOS 26 updates, and fresh AirPods. The launch gives Apple fans a look at what’s next for iPhone 17 models and other devices arriving this fall.

The iPhone Air: Apple’s thinnest phone yet

Apple introduced the iPhone Air, a device that’s 5.6mm thick and weighs 165 grammes. Tim Cook described it as offering “pro performance in a thin and light design.”

The Air features a 6.5-inch ProMotion display with a refresh rate that reaches 120Hz and up to 3,000 nits of peak brightness. Apple says the body is its “most durable” design to date, built with a ceramic shield and titanium frame.

Under the hood, the Air runs on Apple’s new A19 Pro chip, the fastest in the iPhone lineup so far. It also comes with the C1x modem, which the company claims doubles the speed of the previous C1, and the all-new N1 chip for Wi-Fi 7, Bluetooth 6, and Thread support.

Battery life is designed to last through the day, with up to 27 hours of video playback. There’s also a $99 MagSafe battery pack built exclusively for the Air that stretches that time to 40 hours. To make room for more battery capacity, Apple dropped physical SIMs – the Air supports eSIM only. iOS 26 will also bring a new adaptive power mode to help stretch battery performance.

The Air introduces a 48MP “dual fusion” rear camera system, paired with a 12MP telephoto lens. A new capture mode allows both the front and back cameras to record at the same time. The 18MP front camera supports Center Stage, a feature that frames everyone in view without requiring the phone to be rotated.

The iPhone Air will be available in black, white, beige, and light blue, starting at $999 for 256GB of storage. Preorders open September 12th, with sales beginning September 19th.

iPhone 17: A larger display and camera upgrades

The iPhone 17 no longer has a Plus version. Instead, it comes in a single size with a slightly larger 6.3-inch OLED display, slimmer bezels, and ProMotion support at up to 120Hz. The screen can reach 3,000 nits of peak brightness and has a new protective coating, Ceramic Shield 2, that Apple says is three times more resistant to scratches.

Camera improvements headline the update. The rear system includes a 48MP main camera that can act as a 2x telephoto lens by cropping, alongside a 48MP ultrawide lens with macro capabilities. The front camera has also been upgraded to 18MP with a larger, square sensor, allowing for high-quality landscape selfies without rotating the phone.

Internally, the iPhone 17 is powered by Apple’s new A19 chip with a six-core CPU and five-core GPU. Apple says this enables better performance for on-device AI tasks while still delivering all-day battery life – up to 30 hours of video playback.

The phone also introduces Apple’s new in-house N1 networking chip, which replaces Broadcom components. It supports Wi-Fi 7, Bluetooth 6, and Thread, improving the reliability of features like AirDrop and hotspot sharing. The faster C1x modem also ships with the device.

The iPhone 17 starts at $799 for 256GB of storage. Preorders begin September 12th, and it launches September 19th in black, lavender, blue, green, and white.

iPhone 17 Pro and Pro Max: New design and big battery

The iPhone 17 Pro lineup sees the biggest visual change in Apple’s new phones. The rear camera system now sits on what Apple calls a “full-width camera plateau,” a bar that spans the back of the phone. The design recalls the Pixel’s wide camera bar and is expected to appear on Samsung’s next S series as well.

For the first time, all three rear cameras feature 48MP sensors. The telephoto lens is the most improved, offering 56% more sensor space and up to 8x optical quality zoom. Like the other models, the front camera has been upgraded to 18MP with Centre Stage support.

Video tools get a boost too, including Dual Capture – which records from both front and rear cameras at once – and support for formats like ProRes RAW and Log 2.

The Pro models keep the same display sizes: 6.3 inches for the Pro and 6.9 inches for the Pro Max, with ProMotion at up to 120Hz and peak brightness of 3,000 nits. The body returns to aluminium, paired with second-generation Ceramic Shield on the front.

Performance comes from the A19 Pro chip, a 3nm processor with a six-core CPU and GPU. But the standout is battery capacity. Apple says the Pro Max offers up to 39 hours of video playback, the longest ever for an iPhone. Models sold in the US are eSIM-only, leaving space for larger batteries. Versions with physical SIMs may get slightly less runtime.

Apple’s iPhone 17 Pro line supports faster charging too – up to 25W through MagSafe wireless charging using the Qi2.2 standard. Colour options include silver, blue, and a bright orange.

Pricing starts at $1,099 for the Pro and $1,199 for the Pro Max, both at 256GB of storage. The Pro Max can be configured with up to 2TB, priced at $1,999.

Security upgrades in iOS 26

Beyond hardware, Apple is stressing new security changes in iOS 26. The company says it’s delivering “the most significant upgrade to memory safety in the history of consumer operating systems.”

The feature, called Memory Integrity Enforcement (MIE), targets spyware that exploits memory bugs, like those used in Pegasus. Built into the A19 and A19 Pro chips, MIE protects memory by default without slowing performance. Apple says this makes it more costly for attackers to build spyware.

The open-source GrapheneOS project praised the improvements while pointing out differences between Apple’s approach and Android’s Memory Tagging Extension, which is already active on Pixel phones.

iOS 26 launches September 15th, bringing the new “Liquid Glass” design language, which gives apps and system elements a glossy, transparent look. The update also includes new features like Live Translation, a refreshed Phone app, call screening, polls in Messages, and a new Games app.

MagSafe battery and accessories

Apple also revealed a new MagSafe battery pack, but it only works with the iPhone Air. The $99 add-on attaches to the slim phone, but its size doesn’t fit the camera layout of other models. Apple ended support for its previous MagSafe Battery Pack in 2023, though third-party options remain available.

Other accessories include a reinforced polycarbonate bumper case, a standard MagSafe case, and a crossbody strap option.

Apple Watch and new health features

Apple’s latest software update for its watches, watchOS 26, arrives September 15th. It brings new features to existing models, not just the upcoming Series 11.

Hypertension notifications are the highlight. Using the heart sensor, the watch can track vascular responses over 30 days and alert users if it detects signs of high blood pressure. Apple is seeking FDA approval for the feature, with plans to roll it out in more than 150 regions.

Other updates include Sleep Score, which combines heart rate, temperature, blood oxygen, and breathing data to grade sleep quality. The will be available on Series 6 and later, along with Watch Ultra and SE models.

AirPods Pro 3: Better health tracking

The AirPods Pro 3 are Apple’s first major update to the line in three years. They introduce a heart rate sensor, stronger noise cancellation, and live translation features.

Apple says the redesigned earbuds are smaller and shaped to fit better after analysing more than 10,000 ear scans. They come with five tip sizes and are rated IP57 for water and sweat resistance.

The new heart rate sensor uses infrared light to measure blood flow and, paired with iPhone sensors and AI, can track calories burned and activity. A new workout feature called Workout Buddy links this data with fitness history.

Noise cancellation has also been improved, with Apple claiming twice the performance of the previous model. Live Translation lowers outside volume and provides spoken or text translations through the earbuds or paired iPhone.

The AirPods Pro 3 will cost $249, with preorders starting today and shipping September 19th.

iPadOS 26: New windowing system

Apple confirmed iPadOS 26 will be released on September 15th. The update adds the Liquid Glass design seen in iOS 26 but also introduces a new way to manage apps.

Users will be able to resize, minimise, and move app windows – similar to the multitasking system on Macs. A new Files app and a tablet version of Preview also arrive, alongside support for AI-powered Live Translation in the Phone app.

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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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Apple’s thinnest iPhone may take longer to reach Chinese consumers as the country’s eSIM system is not yet ready for nationwide launch. The setback could delay availability of the iPhone 17 Air, a model expected to debut this month alongside the rest of the iPhone 17 lineup, according to the South China Morning Post.

At two Apple-authorised resellers in Foshan, Guangdong province, shop assistants said they had not received training on how to support eSIM. By comparison, Apple resellers in the European Union were asked to complete an eSIM training course by last week, MacRumors reported. The difference highlights how China may not be ready to match the iPhone’s global rollout schedule.

On Chinese social media, concerns about delays are gaining traction. Tech influencer Fixed Focus Digital, who has 2.3 million Weibo followers, said Wednesday that eSIM services in mainland China were “unlikely” to go live this month. He pointed out that mass production of the slimmer model, thought to be called the iPhone 17 Air, began later than the standard iPhone 17, the iPhone 17 Pro, and the iPhone 17 Pro Max. He also downplayed the impact, saying that later availability “isn’t problematic.”

Apple is still expected to reveal the iPhone 17 series on September 9, an event that typically draws global attention and sets the tone for the company’s holiday season sales.

China carriers send mixed signals on iPhone eSIM rollout

Hints of preparation have emerged from China Unicom, one of the country’s three state-owned telecom operators. Weibo user ChillsYaya wrote last week that the carrier had told staff to offer eSIM support for Apple devices. But it was unclear if the directive covered smartphones, since China Unicom already supports eSIM for iPads and Apple Watches. Neither Apple nor China Unicom responded to requests for comment on Wednesday.

In July, China Unicom updated its “5G AI terminal white paper” with eSIM phone specifications, a move seen as preparation for future iPhone support in China. Around the same time, users discovered a beta webpage for eSIM activation, though it only pointed customers to offline stores and gave no clear details on locations.

China’s three major carriers – China Unicom, China Telecom, and China Mobile – have been cautious about smartphone eSIM services. According to a July report from the state-backed China Business Journal, the operators have focused their eSIM development on wearables for now, while smartphone integration remains on hold.

Broader competition on thin designs

The eSIM issue in China extends beyond Apple’s iPhone. Rival smartphone makers are also working on thinner devices that rely on eSIM technology. Xiaomi, for example, lists 16 smartphones with eSIM support in overseas markets, suggesting that competition around slimmer hardware is already under way.

Apple’s September event will not just be about this year’s lineup. The company is beginning a three-year refresh cycle for its most important product. Reports suggest that next year may bring Apple’s first foldable iPhone, a move that would follow similar launches by Samsung Electronics and Google.

Siri’s next upgrade

Alongside hardware, Apple is also preparing major software changes.

Bloomberg‘s Mark Gurman reported that Apple is building an AI-powered search feature for Siri, internally known as “World Knowledge Answers,” a change that will affect how future iPhones function in China and elsewhere. The feature would pull information from the web and deliver AI-generated summaries, presented with text, photos, videos, and location details.

To make this work, Apple may have to rely on third-party services. Google is currently the front-runner to provide an AI model – likely from its Gemini family – that would run on Apple’s servers. The two companies reached a “formal agreement” this week for Apple to test Google’s model for Siri summaries, according to the publication.

The planned Siri upgrade is part of Apple’s broader but delayed effort to expand the voice assistant’s functions. The new system is expected to rely on three parts: a planner that interprets user prompts, a search engine that can scan personal data or the internet, and a ‘summariser’ that packages the results in a usable format.

Apple is still considering other partners. While its own AI models are expected to handle personal data searches, the company is evaluating Google’s Gemini and Anthropic’s Claude for tasks like planning.

What’s next for the iPhone in China

Even with the iPhone 17 launch scheduled for next week, the AI-enhanced Siri is not expected to arrive immediately. Bloomberg reported the new features will roll out with iOS 26.4, which could be released as early as March next year.

For Apple, the timing matters. The iPhone remains its most important product in China, where competition from local brands is intense and regulatory conditions are complex. A delay in eSIM readiness may slow adoption of its thinnest model to date, but the company’s long-term plans – including new form factors and AI-powered software – show that it is preparing for more than just one launch cycle.

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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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OpenAI is considering a plan to set up a massive new data centre in India, a project that could become one of its largest investments in Asia under the US government’s Stargate initiative.

As reported by Bloomberg, people familiar with the matter say the ChatGPT-maker is in talks with local partners about building a facility with at least a gigawatt of capacity. If completed, it would rank among the biggest in India, where Microsoft, Google, and billionaire Mukesh Ambani have already poured billions into similar sites to support cloud and AI growth.

The exact location has not been finalised, and the timeline remains uncertain. Some sources suggest CEO Sam Altman may announce the project during an upcoming visit to India, though those plans are still shifting.

OpenAI’s possible expansion in India comes as trade friction between Washington and New Delhi deepens. US President Donald Trump recently imposed a 50% tariff on Indian goods, saying it was a response to India’s trade barriers and purchases of Russian oil. The move disrupted years of US diplomacy aimed at strengthening ties with the South Asian nation. OpenAI declined to comment on whether its India plans might be affected by these tensions.

Building AI infrastructure worldwide

The company has embarked on an aggressive push to expand its infrastructure both in the US and overseas. The signature $500 billion Stargate project in the US is being developed with backing from SoftBank and Oracle. OpenAI recently raised its US capacity commitment by 4.5 gigawatts – a figure that rivals the energy demand of several million households. Trump has publicly praised the project, framing it as a win for US technology.

Beyond its home market, OpenAI has also launched “OpenAI for Countries,” a global programme aimed at building AI infrastructure alongside governments that share what the US terms its own ‘democratic values.’ OpenAI has pitched the plan as a way for the US and its partners to guide AI development in a way that balances China’s growing influence.

More than 30 countries have expressed interest in joining, with OpenAI pursuing about 10 partnerships to date. Confirmed projects include a facility in Norway that could grow to provide 520 megawatts capacity, and a five gigawatt complex in Abu Dhabi. In the latter case, OpenAI will use about 1 gigawatt of computing power itself, leaving the rest available for other customers.

Security questions abroad

The Abu Dhabi venture has triggered debate in Washington. Some officials argue such projects are necessary to counter China’s global AI ambitions, while others worry about security risks tied to shipping thousands of Nvidia chips to countries with historic links to Beijing.

Since 2023, the US has required approval for any AI chip exports to the UAE. India, however, is not subject to those restrictions. The Trump administration dropped a plan recently that would have expanded AI chip export controls worldwide, leaving India in a stronger position to attract high-performance computing investments.

Why India is key for OpenAI’s AI strategy

For OpenAI, India offers more than just market size. A large-scale data centre in the country could allow it to train and deploy models locally, easing concerns about sending users’ data abroad. It would also align with New Delhi’s $1.2 billion IndiaAI Mission, which aims to develop large and small language models tailored to Indian languages and contexts. OpenAI has already pledged support for the initiative.

India is also OpenAI’s second-largest market by users. To strengthen its presence, the company plans to open an office in New Delhi, expand its hiring, and has launched a $5 monthly subscription plan designed for local customers. The moves suggest India is becoming central to OpenAI’s AI strategy.

If the data centre plan goes ahead, it would mark one of the company’s most ambitious steps yet in its global buildout – and a sign of how AI is becoming deeply tied to trade policy, energy infrastructure, and geopolitics.

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Microsoft has introduced its first in-house AI models, a move that could reshape its position in the AI race. The company rolled out MAI-Voice-1, a speech model, and MAI-1-preview, a text-based model it calls a glimpse of what’s coming next inside Copilot.

The MAI-Voice-1 model is built for speed. According to Microsoft, it can generate a full minute of audio in less than a second using just a single GPU. The model is already in use inside some of the company’s tools. For example, Copilot Daily uses it to deliver short news summaries through an AI voice host. It also helps produce podcast-style conversations that break down complex topics into easier explanations.

The second release, MAI-1-preview, is designed for text tasks. Microsoft trained the model on roughly 15,000 Nvidia H100 GPUs, giving it the scale to handle instruction-following and natural Q&A. Users can already try it on Copilot Labs, where they can test its ability to respond to everyday queries. Microsoft says the model will soon support text-based use cases inside its Copilot assistant.

Competition with OpenAI

These launches come while Microsoft is still heavily tied to OpenAI, the maker of ChatGPT. Microsoft has invested more than $13 billion into the startup, which now has a valuation of about $500 billion. OpenAI continues to rely on Microsoft’s cloud infrastructure to run its own models, while Microsoft uses OpenAI’s systems inside Bing, Windows, and other products.

At the same time, the two companies are drifting into competition. Last year, Microsoft added OpenAI to the list of rivals it names in its annual report, alongside Amazon, Apple, Google, and Meta. OpenAI has also been spreading its infrastructure needs across other providers such as CoreWeave, Google, and Oracle, as demand for ChatGPT climbs. The chatbot now draws about 700 million weekly users.

Early results and rankings

Performance comparisons show Microsoft’s work still trails some of its peers. On Thursday, the new MAI-1-preview ranked 13th for text workloads on LMArena, behind models from Anthropic, DeepSeek, Google, Mistral, OpenAI, and Elon Musk’s xAI. While not at the top, Microsoft has positioned MAI-1-preview as its first foundation model built entirely in-house.

“MAI-1-preview represents our first foundation model trained end to end in house,” Mustafa Suleyman, Microsoft AI chief, wrote on X.

A consumer focus

Suleyman has been clear about the group’s direction. In an interview last year, he explained that Microsoft’s AI models are aimed at consumer use rather than the enterprise market. “My logic is that we have to create something that works extremely well for the consumer and really optimise for our use case,” he said. He pointed to Microsoft’s access to large amounts of consumer data—such as ad performance and telemetry—as a strength in training models for everyday companions.

The company has also said that it does not plan to rely on one general-purpose model. Instead, it sees potential in offering multiple specialised models designed for different types of requests. “We believe that orchestrating a range of specialised models serving different user intents and use cases will unlock immense value,” Microsoft AI wrote in a blog post.

Building an AI division

MAI-1-preview builds on earlier small-scale models released under the Phi name. But this marks the first time Microsoft has trained a foundation model of this size from start to finish. The effort reflects how the company has been building out its AI group since hiring Suleyman and many of his former colleagues from the startup Inflection.

Suleyman previously co-founded DeepMind, the research lab Google bought in 2014. In the past year, Microsoft has brought on about two dozen former DeepMind researchers to expand its internal team. The hires show how the company is drawing on talent with long experience in AI development to accelerate its own projects.

For now, Microsoft is positioning its new models as additions to its Copilot ecosystem while it continues to rely on OpenAI for many core features. But the release of MAI-Voice-1 and MAI-1-preview signals a step toward more independence in model development. Analysts say it could also set up a new phase of competition between Microsoft and the company it helped make into an AI giant.

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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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