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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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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• Data centre demand outstripping supply.
• APAC offers alternatives in a saturated market.
• Massive growth and investment, especially in secondary locations.

Over much of the world, demand for data centre capacity is rising faster than it can be satisfied by data centre (DC) operators, driving up prices and forcing users to look outside the popular hubs for facilities.

Power availability is the main cause of the brakes being applied to growth in data centres in the US (especially North Virginia and Atlanta) and Europe (Frankfurt, London, Amsterdam, Paris – FLAP). That shortage is driving new opportunities in several hotspots in the Asia-Pacific region, including in India, Indonesia, and Malaysia, and to ‘secondary’ cities in Australia such as Melbourne.

Globally, average vacancy rates (the amount of resources unused in data centres) dropped by 2.1% in Q1 2025, falling to 6.6%, according to the CBRE’s Global Data Center Trends report.

The growth in demand for data centre facilities is driven largely by AI, with large hyperscalers committing billions of dollars to new projects, and snapping up space – increasing prices and lowering available capacity. Data centres in Singapore, Tokyo, Hong Kong, and Sydney saw a rise in inventory of 4.4%, but high demand and rising prices have shifted new DC developments out of ‘traditional’ hubs.

Hitting limits in the capitals

The primary APAC data centre hubs are limited by the price and availability of power, with Hong Kong and Singapore adding infrastructure but not significantly lowering vacancy rates due to naturally higher costs being passed on to users. Hong Kong’s data centre vacancy rates remain at 28% due to high costs. While Singapore has only 2% of total DC capacity unused, that’s down to government limits on greenfield development for new facilities, according to the CBRE.

Overall, India’s data centre capacity is forecast to rise to around 1.8 gigawatts (from 0.95 gigawatts in 2024) by 2026, driven by AI and growing digitisation of the local economy. Mumbai ranks sixth globally in places where capacity is under construction – much more than in European hubs like London and Dublin, Ireland.

Off the beaten track

Spill-over from the main centres of DC operation means areas previously considered secondary are gaining popularity. Yet outside the main APAC data centre hubs, it’s a lack of local skilled professional talent that is seen as the main limit to growth. Areas like Kolkata, India, and Iskandar Puteri and Selangor, Malaysia are the targets of significant investment in new builds, for example.

That’s a trend not limited to Asia: in Europe, Scandinavian countries are absorbing demand for compute and storage that can’t be satisfied by the FLAP cities.

At an international level, Malaysia and Indonesian are set to be the region’s fastest-growing places for companies needing to source co-location facilities, with growth rates projected [PDF] of between 32% and 56% CAGR in capacity, compared to 8% in Singapore.

The booming market

According to the commercial real estate company Cushman & Wakefield, the APAC co-location market is expected to bring in revenues of around US$44 billion by 2040, divided among Japan, mainland China, Australia, Malaysia, and India, and the region will overtake the US in data centre capacity before 2030. That’s a statistic confirmed by the CBRE Trends report, which states that in the country’s most popular DC hub in North Virginia, availability remains currently at less than a single percentage point of capacity.

The challenge in creating new facilities includes sourcing their associated infrastructure, allocating necessary resources such as water for equipment cooling, and sourcing local, skilled staff. Whether the region can succeed in grabbing a significant market share globally remains to be seen.

(Image source: “Old chinese temple in Klang, Selangor, Malaysia. Balance body and mind.” by Conny Sandland is licensed under CC BY 2.0.)

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Meta CEO Mark Zuckerberg has outlined what he calls “personal superintelligence,” marking a shift in the company’s AI strategy. Technology journalist Alex Heath from The Verge, who has interviewed Zuckerberg several times, believes the plan signals that Meta is stepping back from trying to directly compete with ChatGPT in productivity tools. Instead, the focus is shifting to Meta’s core motive: to keep people engaged on its platforms.

Over the past year, Zuckerberg promoted Meta’s AI assistant heavily in Facebook, Instagram, and WhatsApp in an attempt to slow ChatGPT’s momentum. But ChatGPT’s strong early lead, reputation as a productivity tool, and ability to help users complete tasks efficiently have kept it ahead. Heath says Zuckerberg appears to have realised that copying that approach isn’t working.

In his “Personal Superintelligence Manifesto,” Zuckerberg predicts that as AI boosts productivity, people will spend less time using productivity software and more time on creative and social activities. He envisions an AI that understands each user, their goals, and how to help them achieve them. While companies like OpenAI, Google, and Anthropic aim to build AI systems that take over more work, Meta wants to use AI to help fill the extra time people gain from increased productivity.

Chris Cox, Meta’s chief product officer, told employees at an all-hands meeting last month that the company will concentrate its AI efforts on entertainment, social connections, and lifestyle features rather than productivity. Heath expects this could lead to AI-powered changes to Meta’s content recommendations, ad targeting, and Reels video generation, along with interactive AI characters designed to keep users engaged longer.

The idea of “personal superintelligence” was first coined by Noam Shazeer, co-founder of Character.AI, who had considered joining Meta before returning to Google last year.

Billions for superintelligence

Zuckerberg says “superintelligence is now in sight” and claims Meta’s AI systems have started improving themselves, though progress is still slow. He did not explain what would distinguish superintelligence from standard AI but acknowledged that it will bring new safety risks. He emphasised that Meta will need to be cautious, especially with open-source releases.

Meta’s spending on AI is massive. For months, the company has been building data centres, acquiring AI startups, and recruiting top researchers, often from competitors. In the second quarter of 2025, total costs reached $27.07 billion, up 12% from the same period last year, with $17.01 billion going toward capital expenditures.

The company now expects total expenses in 2025 to be between $114 billion and $118 billion, with $66 billion to $72 billion in capital spending – higher than earlier forecasts. Infrastructure growth will account for the largest increase, followed by hiring more technical staff. Plans for 2026 point to even higher spending.

Despite the scale of investment, Wall Street has responded positively. Meta reported $7.14 in earnings per share on $47.52 billion in revenue for the second quarter, beating expectations of $5.92 and $44.8 billion, respectively. Stock jumped 10% after the results, another quarter where Meta has exceeded financial forecasts despite heavy AI spending.

Zuckerberg said Meta’s goal is to bring personal superintelligence to everyone, in contrast to rivals that focus on automating as much work as possible. He described the rest of this decade as a decisive period for shaping AI’s future – whether it will empower individuals or replace human roles.

Recruiting and infrastructure

Meta has been building its new superintelligence labs team by attracting talent from Apple, GitHub, and AI startups, often with large pay packages. One reported offer exceeded $200 million. The company also invested $14.3 billion in Scale AI for a 49% stake, bringing its CEO, Alexandr Wang, on board as chief AI officer.

Mike Proulx, research director at Forrester, says Meta’s willingness to spend heavily is giving it an edge in recruiting top AI experts and building the infrastructure to support its ambitions. “Money talks and Meta has plenty of it,” he said.

Reality Labs, Meta’s division for hardware like AI glasses, remains a small part of the business, with $370 million in revenue last quarter. But Zuckerberg compared AI glasses to contact lenses, saying people without them could be at a “cognitive disadvantage.”

Advertising remains Meta’s largest revenue source, bringing in $46.6 billion in the second quarter, up from $38.3 billion a year earlier. CFO Susan Li said WhatsApp ads are unlikely to contribute meaningfully to ad revenue growth for several years, as the platform targets lower-monetising markets and offers less data for ad targeting than Facebook or Instagram.

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Data centres are a core part of how countries manage and protect information today. Without local infrastructure, governments and businesses must rely on services from abroad – raising concerns around data privacy, performance, and national control. For countries like Malaysia, building out a strong data centre industry supports domestic needs and opens the way to becoming a regional hub for digital exports, including AI model training and cloud services.

A new report [PDF] from the Asia Pacific Data Centre Association (APDCA), prepared by KPMG, lays out how important the sector has become for Malaysia. The study found that in 2024 alone, data centres contributed around USD 1.4 billion to the national economy and supported more than 4,400 jobs. By 2030, those numbers are expected to grow significantly – reaching roughly USD 34 billion in output and supporting over 30,000 jobs.

A key piece of digital infrastructure

Data centres are essential for running everything from AI and fintech to e-commerce and public services. They help businesses run smoothly, make government operations more efficient, and give Malaysia a competitive edge in the global digital economy. Reliable infrastructure is no longer just a nice-to-have – it’s central to long-term growth and sovereignty.

Malaysia’s push to lead in digital services depends heavily on data centres. Beyond the construction and maintenance work involved, they unlock broader productivity gains in multiple industries – from cloud computing to artificial intelligence. The makes them a crucial part of Malaysia’s strategy to grow its knowledge economy and reduce brain drain.

The sector creates high-skilled jobs in areas like cloud infrastructure, network security, and data engineering. The are roles that help retain local talent and attract tech-focused foreign investment. According to LinkedIn data, over 357,000 professionals in Malaysia already work in digital-related roles – a sign that the workforce is well-positioned to support continued growth in this space.

Johor takes the lead

Much of Malaysia’s data centre capacity is concentrated in Johor, which in 2024 accounted for nearly 80% of the country’s total. The region has become a top destination for hyperscale and enterprise data centres, with a very low vacancy rate and strong interest from global tech players.

Johor’s location in the Johor-Singapore Special Economic Zone (JS-SEZ) gives it a strategic edge. Combined with solid infrastructure and available land, it’s become a natural choice for developers. As demand grows, new investments are also flowing into other parts of the country, like Selangor and the Klang Valley, helping to distribute benefits more widely.

Malaysia’s capacity is expected to rise from around 505MW in 2024 to roughly 3,600MW by 2030. That growth is being driven by demand for colocation, edge computing, and large-scale cloud operations.

Supporting broader economic goals

The impact of data centres goes well beyond the facilities themselves. They support jobs in construction, electrical work, HVAC systems, and more. They also create demand for digital services – everything from software engineering to customer support – that extend in industries.

The data centres serve as the foundation for high-growth sectors like AI, advanced manufacturing, and smart logistics. They enable better public services, rural internet access, and digital tools in education and healthcare. All of this contributes to better living standards and a more connected society.

The government sees this potential and has backed the sector through major infrastructure plans, including the Malaysia Digital Economy Blueprint and the Twelfth Malaysia Plan. A number of regulatory and incentive programs have also helped draw in investment, including tax breaks and energy supply improvements.

A fast-growing, competitive market

Malaysia is one of the fastest-growing data centre markets in Asia Pacific. Between 2025 and 2030, total data centre capacity is projected to double from 1.26GW to 2.53GW. At the same time, colocation revenue is expected to jump from $710 million to $1.87 billion. That growth is being driven by demand from hyperscale cloud providers and enterprise customers looking for reliable, cost-effective infrastructure in the region.

Compared to mature but capacity-limited markets like Singapore, Malaysia offers available land, lower costs, and growing government support. These factors make it a strong option for global providers looking to expand in Southeast Asia.

Supporting AI growth

The rise of AI has pushed global demand for data centre services even higher. Since the launch of tools like ChatGPT, companies have been racing to build infrastructure capable of training and deploying large models.

Malaysia is seen as well-positioned to meet this demand. The government has established the National AI Office (NAIO) to guide AI development and has set targets for inclusive AI growth and talent development. AI is expected to contribute around $115 billion to Malaysia’s economy between 2025 and 2030.

Local infrastructure is a big part of that. Owning and operating AI-ready data centres gives Malaysia more control over how data is handled, offers national security benefits, and strengthens its position in areas like renewable energy and sustainable facility design.

A broader supply chain opportunity

The growth of data centres also creates export potential for related industries. Malaysia could become a provider of AI and cloud services to nearby countries in ASEAN. It could also export technologies like cooling systems, develop expertise in managing electronic waste, and grow local capabilities in building GPU infrastructure.

This kind of industrial diversification supports long-term job creation and helps Malaysia build a more complex, tech-focused economy.

The policy environment matters

The government has already approved over $24 billion in data centre projects, most of it coming from foreign investors. To keep that momentum going, clear and consistent policy will be important.

Initiatives like the Green Lane Pathway – developed by Tenaga Nasional Berhad (TNB) – have helped speed up infrastructure setup. It now takes around 12 months to get power access, compared to the usual 36 – 48 months.

Other frameworks, like the Corporate Renewable Energy Support Scheme (CRESS), help providers tap into clean energy. At the same time, the new Planning Guidelines for Data Centres and upcoming rules around energy and water use show that Malaysia is also trying to manage sustainability more seriously.

Still, some areas need improvement. Unclear tax and energy tariff changes could reduce Malaysia’s appeal compared to other countries. Engaging with data centre operators and offering better regulatory certainty could help address this.

Building the workforce

Malaysia has made strong progress in growing its digital talent pool, but there’s still a gap when compared to other mature markets like Singapore, South Korea, and Japan. Lower attrition rates in Thailand and Vietnam also point to the need for better talent retention strategies.

Closer partnerships between government, industry, and education providers could help bridge these gaps and ensure that Malaysia remains competitive.

A strong outlook

Malaysia’s data centre market is set to expand quickly and play a key role in supporting national digital goals. The combination of strong government support, demand from global providers, and available resources gives the country a clear opportunity to become a major player in Southeast Asia’s digital infrastructure story.

As Jeremy Deutsch, Chair of the APDCA, put it: “Data centres are the foundational infrastructure that powers and enables AI, cloud adoption, and digital transformation in sectors. The report provides compelling evidence of the sector’s tangible benefits and broad-based impact on the Malaysian economy, rakyat, and nation.”

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Oracle is in talks to sign a large software deal with Skydance Media, a move contingent on Skydance completing its planned purchase of Paramount Global.

According to Bloomberg, sources familiar with the matter say the deal would be worth about US$100 million a year. If it goes through, Paramount and its group of media companies would begin using Oracle’s cloud software to run parts of their business. The discussions are private, and the companies haven’t confirmed any details.

Skydance already uses Oracle’s products with the media company spending US$2.2 million on Oracle’s cloud services in the year ending May 2024, according to public filings. Skydance was founded by David Ellison, whose father, Larry Ellison, is Oracle’s chairman and a major shareholder. Larry Ellison is also backing Skydance’s US$8 billion bid to take over Paramount, providing cash and investment support.

None of Oracle, Skydance or Paramount responded to requests for comment.

If the merger is approved and the Oracle deal is finalised, the combined Skydance-Paramount group would become one of Oracle’s larger cloud clients. It would also deepen the existing relationship between the two companies. A person familiar with the discussions said moving Paramount’s operations to Oracle’s cloud could lead to major cost savings – possibly in the hundreds of millions – as outdated systems are replaced with newer tools.

Paramount owns a number of high-profile media brands, including CBS, MTV, and Nickelodeon. The networks generate huge amounts of video and audio data needing a lot of storage and computing power. By shifting to Oracle’s cloud, the company could centralise much of that work, making it easier to manage and potentially offering cost savings.

David Ellison has said he wants to run Paramount more efficiently if the deal goes through. A big part of that plan involves updating its technology systems. While talks with Oracle are still ongoing, the deal isn’t finalised and could still change, according to sources.

The merger between Paramount and Skydance was first announced last year but still needs approval from US regulators. The final major hurdle is the Federal Communications Commission (FCC). Last week, Ellison met with FCC chair Brendan Carr and other officials to discuss the proposal and try to move things forward.

Meanwhile, Paramount has been facing scrutiny. Earlier in July, the company reached a legal settlement in a case brought by US President Donald Trump, who accused CBS News of media bias. On Monday (Jul 21), a group of US senators sent a letter to Ellison asking whether the timing of that settlement was tied to efforts to close the merger.

Oracle has been expanding its cloud business beyond its traditional database software. The company has been picking up customers that need large-scale computing and storage, particularly those working with artificial intelligence. Oracle already counts TikTok, Uber, and Zoom among its major clients.

The cloud deal with Skydance-Paramount comes shortly after Oracle announced a new round of spending in Europe. The company said it plans to invest US$3 billion over the next five years to expand its data centre capacity in Germany and the Netherlands. Oracle has earmarked US$2 billion for Germany and US$1 billion for Dutch operations.

According to Oracle, this investment will help local companies, governments, and organisations shift their workloads to the cloud and make use of newer AI tools. The announcement didn’t tie the spending directly to the Skydance talks, but it highlights the growing demand for AI computing infrastructure.

Big names in tech – including Microsoft, Amazon, Google, Meta, OpenAI, and xAI – have also committed large amounts of money to data centres that can power AI models. Oracle is part of the US-based group, Stargate, that includes OpenAI and others. The project plans to pour hundreds of billions into new infrastructure to support AI.

Oracle’s stock rose about 1% in early trading on the day the Skydance talks were reported. Shares are up more than 37% this year and are just below their highest point to date.

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The Trump administration is apparently preparing new AI chip export restrictions targeting Malaysia and Thailand over concerns about semiconductor smuggling to China, according to Bloomberg’s sources familiar with the matter. The proposed measures would add the two Southeast Asian nations to existing export control frameworks amid ongoing investigations into potential chip diversion schemes.

A draft rule from the Commerce Department seeks to prevent China — to which the US has effectively banned sales of Nvidia’s advanced AI processors — from obtaining those components through intermediaries in the two Southeast Asian nations, people familiar with the matter told Bloomberg. 

If proven true, the proposed AI chip export restrictions would mark the first formal step in Trump’s promised overhaul of his predecessor’s semiconductor trade policies. The timing of these potential restrictions comes as Malaysia has emerged as a critical hub for global technology investments. 

The timing of these potential restrictions comes as Malaysia has emerged as a critical hub for global technology investments. Oracle, Google, Microsoft, and Amazon have committed a combined investment of $16.9 billion through 2038 in the country’s digital infrastructure, with Oracle alone pledging $6.5 billion for its first public cloud region in the country.

Trade data also shows that chip shipments to Malaysia have surged in recent months, according to Trendforce’s report. This increase has drawn the attention of US officials who worry about the potential diversion of advanced semiconductors to China.

What ignited the concerns?

The proposed restrictions gain additional context from ongoing investigations in neighbouring Singapore. Singapore charged three men with fraud in a case domestic media have linked to the movement of Nvidia’s advanced chips from the city-state to Chinese artificial intelligence firm DeepSeek.

The servers involved in the case were supplied by Dell Technologies and Super Micro Computer to Singapore-based companies before they were sent to Malaysia, according to Singapore’s Law and Home Affairs Minister K Shanmugam. Malaysia said it will take “necessary action” against Malaysian companies if they are found to be involved in a fraud case linked to the alleged movement of Nvidia chips.

It is also worth noting that the draft measure represents a significant departure from the Biden administration’s approach. Officials plan to pair Malaysia and Thailand controls with a formal rescission of global curbs from the so-called AI diffusion rule, which had drawn objections from US allies and tech companies, including Nvidia.

Commerce Secretary Howard Lutnick has outlined the administration’s vision, stating that the US will “allow our allies to buy AI chips, provided they’re run by an approved American data centre operator, and the cloud that touches that data centre is an approved American operator”.

However, the draft measure is far from a comprehensive replacement and doesn’t answer questions about security conditions for the use of US chips in overseas data centres — a debate with particularly high stakes for the Middle East.

Mitigation Measures for Industry

Recognizing the potential disruption to legitimate business operations, the proposed AI chip export restrictions would include several measures to ease pressure on companies with significant operations in the region. 

One provision would allow firms headquartered in the US and a few dozen friendly nations to continue shipping AI chips to both countries, without seeking a licence, for a few months after the rule is published.

The licence requirements also would still include certain exemptions to prevent supply chain disruptions. Many semiconductor companies rely on Southeast Asian facilities for crucial manufacturing steps like packaging, and the process of encasing chips for use in devices.

Regional response and uncertainty

Government responses from the targeted nations have been measured. In response to earlier Bloomberg queries about curbs focused on smuggling risks, Thailand said it’s awaiting details, while Malaysia’s Ministry of Investment, trade and industry said clear and consistent policies are essential for the tech sector.

Nvidia, the dominant maker of AI chips, declined to comment, while spokespeople for the Thai and Malaysian governments didn’t respond to Bloomberg’s requests for comment. Nvidia chief executive officer Jensen Huang has previously said there’s “no evidence” of AI chip diversion, in general remarks that didn’t touch on any particular country.

Strategic implications for Southeast Asia

The proposed measures highlight the broader geopolitical tensions surrounding AI technology and export controls. Washington officials for years have debated which countries should be able to import American AI chips — and under what conditions. 

On one hand, the world wants Nvidia hardware, and US policymakers want the world to build AI systems using American technology — before China can offer a compelling alternative.

Singapore is Nvidia’s second-biggest market after the United States, accounting for 18% of its total revenue in its latest fiscal year.  Actual shipments to the Asian trading hub, however, contributed less than 2% of total revenue, as customers use it as a centre for invoicing sales to other countries.

What’s next?

The draft regulation remains subject to change, and it’s unclear whether Trump officials may ultimately regulate AI chip export restrictions to a wider swath of countries, beyond the Malaysia and Thailand additions. The Commerce Department did not respond to Bloomberg’s request for comment on the proposed measures.

The proposed restrictions underscore a fundamental tension in US technology policy: how to contain China’s AI capabilities without undermining America’s technological influence. By potentially restricting two countries that have become key destinations for US tech investment, Washington risks creating the very fragmentation it seeks to avoid – pushing regional partners toward alternative suppliers and technologies.

For Malaysia and Thailand, the challenge extends beyond compliance. These nations must now prove they can serve as trusted AI infrastructure hubs while managing the reality that their strategic location makes them attractive conduits for circumventing sanctions. 

The outcome will likely shape how other Southeast Asian countries approach their own AI development strategies.

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Alibaba Cloud is expanding its presence in Southeast Asia with new data centres in Malaysia and the Philippines, part of a broader push to meet rising demand for AI services in the region.

The company recently launched its third data centre in Malaysia and plans to open a second in the Philippines by October. These follow similar investments in Thailand, Mexico, and South Korea earlier this year.

Alibaba has committed to spending US$53 billion on AI infrastructure over the next three years. It’s also positioning Southeast Asia as a key market, even after shutting down data centres in Sydney and Mumbai last year, as reported by South China Morning Post.

AI hub and talent development in Singapore

As part of its 10-year anniversary in Singapore, Alibaba Cloud announced a new AI Global Competency Center (AIGCC) in the country. The centre is intended to support over 5,000 businesses and 100,000 developers, offering tools for building and deploying AI systems.

It also includes an AI Innovation Lab that will provide curated datasets, usage credits, and support services. The AIGCC is expected to work with more than 1,000 companies and startups, with plans to introduce over 10 AI agents for industries like healthcare, logistics, and finance.

To build a larger talent pool, Alibaba Cloud says it will partner with over 120 institutions to train 100,000 AI professionals annually.

New AI tools and system upgrades

Alibaba Cloud also rolled out upgrades to its AI infrastructure and software tools.

Its real-time data service, Data Transmission Service (DTS), now supports an “One Channel for AI” feature that can convert various types of data—text, images, audio, video—into formats that can be used for AI training and Retrieval-Augmented Generation (RAG) applications. The goal is to reduce technical complexity and speed up deployment.

On the AI inference side, Alibaba’s Platform for AI (PAI) introduced updates to support large models and complex architectures like Mixture of Experts. A new Model Weights Service is also available to cut cold start times and improve scaling, with test results showing up to 90% faster performance in some cases.

The company’s ninth-generation Intel-based Elastic Compute Service (ECS) instance is also expanding to more markets, including Japan, the UAE, and the UK. Since its April launch, nearly 10,000 businesses have adopted the new instance, which offers better computing efficiency and faster networking for AI, HPC, and database workloads.

Green AI research and challenges

A new study released during Alibaba Cloud’s global summit looked at how businesses are approaching “green AI”—AI systems designed to reduce environmental impact. Conducted by Forrester and commissioned by Alibaba, the study surveyed more than 460 IT and business leaders globally.

While most respondents agreed that green AI is important, many said they’re still in early stages. Some of the top challenges include sourcing sustainable hardware (80%) and improving data centre energy efficiency (73%).

Capability gaps were also common. Around three-quarters of respondents said their organisations lack the knowledge or skills to build and operate green AI systems. The study recommended several steps to close the gap, including using renewable energy in data centres, building smaller models, and improving collaboration on standards and open-source tools.

AI in practice: Customer examples

Alibaba Cloud’s AI offerings are being used by a growing number of customers across Asia and beyond.

Indonesia’s GoTo Group migrated its core business intelligence data platform to Alibaba Cloud’s MaxCompute. The company says the migration, which moved tens of petabytes of data over six months, helped improve cost efficiency and system performance with no downtime. GoTo Financial has also moved its lending systems to Alibaba Cloud, using PolarDB and Tair to support over 500 microservices with low latency.

VisionTech, a generative AI startup in Singapore, uses Alibaba Cloud infrastructure to scale its multilingual AI bots across Southeast Asia. The company says it cut infrastructure costs by more than 25% and now uses Alibaba’s Qwen model to manage real-time translation across English, Chinese, Malay, and Japanese.

Japanese tech provider FLUX is also working with Alibaba Cloud to bring the Qwen model to local businesses. FLUX plans to build its own LLM product using Alibaba’s tools and apply it to core operations for clients across industries.

In the Middle East, Alibaba Cloud signed an agreement with Al-Futtaim, a diversified business group based in Dubai, to support AI development across its business units. The deal includes access to Alibaba’s cloud and AI infrastructure, as well as open-source frameworks and training support.

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IBM has updated its quantum computing roadmap, with plans to roll out a new system called Starling by the end of the decade. If all goes as planned, Starling could handle far more operations than current machines and push quantum computing closer to real-world use.

Starling is designed to carry out 100 million quantum operations using 200 logical qubits. It is to be hosted in a new IBM data centre under construction in Poughkeepsie, New York. Renders of the facility suggest it will hold four of IBM’s Quantum System Two machines – each using a hexagonal layout that fits three quantum processors – and sit alongside rows of standard server racks.

Another machine, Blue Jay, is intended to follow Starling. It is said to be able to support 2,000 logical qubits and perform 1 billion operations, according to IBM. Both Starling and Blue Jay would mark a shift from earlier designs which are based on single, monolithic processors.

IBM has spent years trying to scale up quantum systems. But researchers have found that simply packing more qubits on one chip wasn’t enough to build fault-tolerant machines. To reach better levels of reliability, IBM is now focusing on modularity – a design approach that links smaller quantum units into one system. The setup could help avoid some of the limits of older surface code methods.

The company also says fault tolerance isn’t just about qubits. The whole system – including gates, connections, operations, control electronics, memory, and how errors are measured – has to be reworked from the ground up.

IBM says Starling’s performance would be beyond what classical supercomputers can achieve. The company says the computational state of Starling would require more memory than all of the world’s most powerful supercomputers combined – although no technical breakdown was shared to support this.

CEO Arvind Krishna says the company’s focus is now on building machines that can take on real-world problems. That means reaching a point where quantum computers can run tasks that classical computers simply can’t handle, even with massive amounts of time or power.

The isn’t IBM’s first quantum computing roadmap. Back in 2020, it laid out a plan that included the Falcon processor (27 qubits), and later the 1,121-qubit Condor chip, which was aimed at research use but was never released to the public. Since then, it has become clear that bigger chips alone won’t solve the problem of making quantum systems stable and usable.

IBM’s new approach includes a series of processors with different features. Nighthawk, expected this year, will offer 133 error-corrected qubits. Multiple Nighthawk units can be connected to reach over 1,000 qubits total. IBM plans to launch Loon in 2025, Kookaburra in 2026, and Cockatoo in 2027. Each step adds new features: longer qubit connections, combined logic and memory, and a way to link chips together like nodes in a larger system.

Error correction remains one of the toughest problems in quantum computing. IBM says it’s made some headway with quantum low-density parity check (qLDPC) codes. The technique may cut down how many physical qubits are needed to support each logical qubit, and IBM claims it could lower the overhead by up to 90 per cent.

The company is also working on ways to catch and fix errors in real time, saying this can be done with standard computing hardware like FPGAs or ASICs. This too would mark a shift from current methods, which often require complex workarounds after errors occur.

Jay Gambetta, a longtime IBM researcher and VP of IBM Quantum, told reporters the company has “cracked the code” for error correction, but the rest of the engineering still needs work.

IBM started its quantum research in the late 1990s, teaming with universities to build early test systems. In 2016, it launched a five-qubit machine online through IBM Quantum Experience. Since then, the field has seen steady improvements, but no system yet has crossed into fully fault-tolerant territory.

Whether IBM can meet its 2029 target remains to be seen. But the company’s new roadmap shows a shift in focus – from adding more qubits to a single to making quantum systems stable, connected, and useful via modularity.

The post IBM plans to build working modular quantum system by 2029 appeared first on TechWire Asia.

Microsoft has opened its first cloud regions in Malaysia and Indonesia, giving the countries local access to data storage, AI tools, and cloud services. The move supports public and private sector efforts to improve infrastructure, strengthen security, and build digital skills.

Malaysia West, based in Greater Kuala Lumpur, and Indonesia Central, located in Jakarta, each include three availability zones, with zones offering separate power, cooling, and networking to reduce service disruptions. Both regions are now live and available to customers.

The two launches are part of larger investment plans. In Malaysia, Microsoft committed US$2.2 billion between 2024 and 2028 to support cloud and AI growth. In Indonesia, the company is investing US$1.7 billion over the same period. The funds are going toward infrastructure, training programs, and partnerships.

Meeting local rules and performance needs

Each region offers data residency, allowing organisations to keep their data inside national borders. This helps with compliance and privacy concerns, and reduces latency for users.

The cloud regions are built with the same security measures as Microsoft’s global network. These include physical safeguards, encryption, and access controls. Microsoft also reports that the centres are intended to meet environmental goals like reducing carbon emissions and improving water use.

For example, the Indonesia Central region was developed in line with Microsoft’s environmental targets which include becoming carbon negative by 2030, water positive by 2030, and reaching zero waste in the same decade. The facility is connected to Microsoft’s global wide area network, giving users in Indonesia access to high-bandwidth, low-latency connections in other regions.

Economic projections and job growth

Research from IDC suggests that these regions could create new economic value for both countries. In Malaysia, the new cloud region is projected to help generate US$10.9 billion in revenue and more than 37,000 jobs by 2028. In Indonesia, the estimate is US$15.2 billion in value and more than 106,000 jobs in the same time period.

The jobs are expected to cover both tech and non-tech roles, like cloud operations, software development, support services, and training. Many of the positions will require AI and digital skills, which ties into local workforce development efforts.

Working with local groups and businesses

Several organisations are already using the new cloud infrastructure. In Malaysia, early users include PETRONAS, TNG Digital, and SCICOM Berhad. In Indonesia, the list includes BCA, Pertamina, Telkom Indonesia, Astra, and Binus University.

Public agencies are also involved. In Indonesia, the Ministry of Communications and Digital Affairs said the cloud region shows trust in the country’s digital direction. The ministry said cloud and AI could play a role in both national development and regulation.

In Malaysia, the government sees the launch of a cloud region as part of its effort to improve digital services and support job creation. Officials believe the new infrastructure will assist firms in updating existing systems and exploring more efficient ways of working.

Focus on training and AI skills

To support these changes, Microsoft is running several skills programmes. In Malaysia, AIForMYFuture aims to train 800,000 people by the end of 2025. So far, 400,000 people have taken part. The programme includes public servants, students, and people from underserved groups.

In Indonesia, elevAIte was launched with help from the Ministry of Communications and Digital Affairs. The target is to train a million people by 2025. More than 20 organisations are involved, including schools, businesses, and local groups.

Microsoft also started a vocational programme called the Nusantara Data Centre Academy. It trains students for roles in data centre operations. Some students are already doing on-the-job training with others in classroom sessions.

In addition, a Community Empowerment Fund is helping schools near data centres improve their digital tools. Funds are used to buy equipment and run training programmes for teachers and students.

As of mid-2025, the Fund has supported over 3,200 students and teachers in Indonesia. Schools in areas like Cikarang and Karawang have received hardware and software tools to support digital learning.

AI projects and local solutions

Both countries are working to use AI to solve local problems. In Malaysia, Microsoft is part of discussions around a National AI Innovation Centre. The goal is to build tools that can support national goals and public services.

A plan for an AI Centre of Excellence in Indonesia was announced during Microsoft’s AI Tour Jakarta. The idea is to bring together stakeholders from government, education, and business to collaborate on real-world AI solutions.

Some groups have already put AI into use. Astra in Indonesia has developed a dealer management system using AI and Microsoft tools, helping with planning, inventory, and service tracking.

The Ministry of Finance in Indonesia is also assessing how to use cloud services for institutional needs. Officials said that reliable and compliant cloud infrastructure could help lower latency and improve efficiency in public sector operations.

A long-term bet on digital growth

The cloud regions are part of Microsoft’s long-term involvement in Southeast Asia. Demand for secure, local digital tools continues to rise, and governments and businesses are exploring cloud adoption as part of their digital plans.

Microsoft’s cloud regions are now one of several factors shaping how Southeast Asia uses technology. While more firms may enter this space, the current focus remains on building infrastructure that can support both long-term national strategies and daily operational needs in sectors like education, healthcare, energy, and finance.

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Grab has opened its first Artificial Intelligence Centre of Excellence (AI COE) at its Singapore headquarters, which is backed by Digital Industry Singapore (DISG). The centre will develop AI solutions to improve access to digital services, boost productivity, and support public projects across Southeast Asia.

Grab will use the new facility to train local talent, build tech tools for everyday use, and address regional social and business concerns. By 2025, the company expects to create at least 50 roles in engineering, product, data science, and analytics. These jobs are aimed at helping Singaporeans work on real AI problems with regional impact.

One major focus is making technology easier to use, especially for people who have trouble with standard apps or services. Grab is working with the Singapore Association of the Visually Handicapped (SAVH) to test a new voice assistant that helps visually-impaired users book rides using spoken commands. SAVH members helped test the tool and gave feedback to make sure it fits their needs.

Lyn Loh, who leads accessibility services at SAVH, said they were glad to support this effort. She said the voice assistant could help more people travel on their own and use digital services more easily.

Grab built the voice feature using models based on OpenAI’s technology, but with a local twist. The team trained the system on 80,000 voice samples that reflect Singaporean speech and building names. That helped the model improve its ability to recognise local accents and landmarks—from 46% to 89%. Starting in June, users in Singapore can donate voice samples through the app to further improve accuracy.

For now, the voice assistant is being tested in Singapore. Grab plans to expand its use in the future and is also exploring similar tools to support elderly users and others less familiar with smartphones.

The AI COE will also work on boosting productivity. That includes assisting drivers, delivery workers, and small businesses in using AI to make better decisions and improve how they work.

Grab is building its own AI model, trained on its own data, to better understand user behaviour and how partners use the app. This custom model is expected to improve the way Grab recommends rides, routes, and services to users and partners. It can help provide suggestions that are more relevant to each individual.

The company is also creating tools that let its employees test AI ideas more quickly. A new internal kit includes code and resources that make it easier to set up safe environments for AI testing. What used to take more than a week can now be done in half a day.

For Grab’s partners, the AI COE is rolling out tools like the Driver AI Companion and the Merchant AI Assistant. The driver tool offers tips on where to go for more ride requests, how to plan routes more efficiently, and what rewards are available based on driving patterns. The merchant tool assists businesses in understanding trends, getting suggestions on improving sales, and managing daily tasks more easily.

Another area of focus is public infrastructure and smart city tools. Grab collects a lot of data from its driver network, which it plans to use to support local government work. Its existing devices, such as KartaDongle and KartaDashcam, are being updated with new features to detect road hazards, monitor weather, and track traffic in real time.

One example is its collaboration with Singapore’s national water authority, PUB. By merging Grab’s data with PUB’s flood monitoring systems, the two teams can deliver real-time flood notifications to drivers and assist officials respond more quickly to storm-related situations. This reduces traffic interruptions and improves emergency response times.

Grab describes the AI COE as a way to use technology to improve daily life across Southeast Asia. The centre brings together data, tools, and people to build useful solutions for drivers, merchants, users, and cities. By focusing on real problems like accessibility, small business support, and urban planning, the company hopes to make AI more practical and inclusive across the region.

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