According to Counterpoint Research data, SK Hynix captured 36% of the DRAM market in Q1 2025, compared to Samsung’s 34% share.

HBM chips drive market shift

The company’s achievement ends Samsung’s three-decade dominance in DRAM manufacturing and comes shortly after SK Hynix’s operating profit passed Samsung’s in Q4 2024.

The company’s strategic focus on high-bandwidth memory (HBM) chips, essential components for artificial intelligence applications, has proven to be the decisive factor in the market shift.

“The is a milestone for SK Hynix which is successfully delivering on DRAM to a market that continues to show unfettered demand for HBM memory,” said Jeongku Choi, senior analyst at Counterpoint Research.

“The manufacturing of specialised HBM DRAM chips has been notoriously tricky and those that got it right early on have reaped dividends.”

SK Hynix has taken the overall DRAM market lead and has established its dominance in the HBM sector, occupying 70% of this high-value market segment, according to Counterpoint Research.

HBM chips, which stack multiple DRAM dies to dramatically increase data processing capabilities, have become fundamental components for training AI models.

“It’s another wake-up call for Samsung,” said MS Hwang, research director at Counterpoint Research in Seoul, as quoted by Bloomberg. Hwang noted that SK Hynix’s leadership in HBM chips likely comprised a larger portion of the company’s operating income.

Financial performance and industry outlook

The company is expected to report positive financial results on Thursday, with analysts projecting a 38% quarterly rise in sales and a 129% increase in operating profit for the March quarter, according to Bloomberg data.

The shift in market leadership reflects broader changes in the semiconductor industry as AI applications drive demand for specialised memory solutions.

While traditional DRAM remains essential for computing devices, HBM chips that can handle the enormous data requirements of generative AI systems are becoming increasingly valuable.

Market research firm TrendForce forecasts that SK Hynix will maintain its leadership position throughout 2025, coming to control over 50% of the HBM market in gigabit shipments.

Samsung’s share is expected to decline to under 30%, while Micron Technology is said to gain ground to take close to 20% of the market.

Counterpoint Research expects the overall DRAM market in Q2 2025 to maintain similar patterns across segment growth and vendor share, suggesting SK Hynix’s newfound leadership position may be sustainable in the near term.

Navigating potential AI memory demand headwinds

Despite the current AI memory demand boom, industry analysts identify several challenges on the horizon. “Right now the world is focused on the impact of tariffs, so the question is: what’s going to happen with HBM DRAM?” said MS Hwang.

“At least in the short term, the segment is less likely to be affected by any trade shock as AI demand should remain strong. More significantly, the end product for HBM is AI servers, which – by definition – can be borderless.”

However, longer-term risks remain significant. Counterpoint Research sees potential threats to HBM DRAM market growth “stemming from structural challenges brought on by trade shock that could trigger a recession or even a depression.”

Morgan Stanley analysts, led by Shawn Kim, expressed similar sentiment in a note to investors cited by Bloomberg: “The real tariff impact on memory resembles an iceberg, with most danger unseen below the surface and still approaching.”

The analysts cautioned that earnings reports might be overshadowed by these larger macroeconomic forces. Interestingly, despite SK Hynix’s current advantage, Morgan Stanley still favours Samsung as their top pick in the memory sector.

“It can better withstand a macro slowdown, is priced at trough multiples, has optionality of future growth via HBM, and is buying back shares every day,” analysts wrote.

Samsung is scheduled to provide its complete financial statement with net income and divisional breakdowns on April 30, after reporting preliminary operating profit of 6.6 trillion won ($6 billion) on revenue of 79 trillion won earlier this month.

The shift in competitive positioning between the two South Korean memory giants underscores how specialised AI components are reshaping the semiconductor industry.

SK Hynix’s early and aggressive investment in HBM technology has paid off, though Samsung’s considerable resources ensure the rivalry will continue.

For the broader technology ecosystem, the change in DRAM market leadership signals the growing importance of AI-specific hardware components.

As data centres worldwide continue expanding to support increasingly-sophisticated AI models, AI memory demand should remain robust despite potential macroeconomic headwinds.

(Image credit: SK Hynix)

See also: Samsung aims to boost on-device AI with LPDDR5X DRAM

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“As America’s world-leading AI sector approaches AGI, with a Chinese Communist Party (CCP) determined to overtake us by 2030, the Trump Administration’s new AI Action Plan can ensure that American-led AI built on democratic principles continues to prevail over CCP-built autocratic, authoritarian AI,” wrote OpenAI, in a letter to the Office of Science and Technology Policy.

In a separate letter, Google echoed this sentiment by stating, “While America currently leads the world in AI – and is home to the most capable and widely adopted AI models and tools – our lead is not assured.”    

A plan for the AI Action Plan

OpenAI highlighted AI’s potential to “scale human ingenuity,” driving productivity, prosperity, and freedom.  The company likened the current advancements in AI to historical leaps in innovation, such as the domestication of the horse, the invention of the printing press, and the advent of the computer.

We are at “the doorstep of the next leap in prosperity,” according to OpenAI CEO Sam Altman. The company stresses the importance of “freedom of intelligence,” advocating for open access to AGI while safeguarding against autocratic control and bureaucratic barriers.

OpenAI also outlined three scaling principles:

1. The intelligence of an AI model roughly equals the log of the resources used to train and run it.

2. The cost to use a given level of AI capability falls by about 10x every 12 months.

3. The amount of calendar time it takes to improve an AI model keeps decreasing.

Google also has a three-point plan for the US to focus on:

1. Invest in AI: Google called for coordinated action to address the surging energy needs of AI infrastructure, balanced export controls, continued funding for R&D, and pro-innovation federal policy frameworks.

2. Accelerate and modernise government AI adoption: Google urged the federal government to lead by example through AI adoption and deployment, including implementing multi-vendor, interoperable AI solutions and streamlining procurement processes.

3. Promote pro-innovation approaches internationally: Google advocated for an active international economic policy to support AI innovation, championing market-driven technical standards, working with aligned countries to address national security risks, and combating restrictive foreign AI barriers.

AI policy recommendations for the US government

Both companies provided detailed policy recommendations to the US government.

OpenAI’s proposals include:

• A regulatory strategy that ensures the freedom to innovate through voluntary partnership between the federal government and the private sector.    

• An export control strategy that promotes the global adoption of American AI systems while protecting America’s AI lead.    

• A copyright strategy that protects the rights of content creators while preserving American AI models’ ability to learn from copyrighted material.    

• An infrastructure opportunity strategy to drive growth, including policies to support a thriving AI-ready workforce and ecosystems of labs, start-ups, and larger companies.    

• An ambitious government adoption strategy to ensure the US government itself sets an example of using AI to benefit its citizens.    

Google’s recommendations include:

• Advancing energy policies to power domestic data centres, including transmission and permitting reform.    

• Adopting balanced export control policies that support market access while targeting pertinent risks.    

• Accelerating AI R&D, streamlining access to computational resources, and incentivising public-private partnerships.    

• Crafting a pro-innovation federal framework for AI, including federal legislation that prevents a patchwork of state laws, ensuring industry has access to data that enables fair learning, emphasising sector-specific and risk-based AI governance, and supporting workforce initiatives to develop AI skills.    

Both OpenAI and Google emphasise the need for swift and decisive action. OpenAI warned that America’s lead in AI is narrowing, while Google stressed that policy decisions will determine the outcome of the global AI competition.

“We are in a global AI competition, and policy decisions will determine the outcome,” Google explained. “A pro-innovation approach that protects national security and ensures that everyone benefits from AI is essential to realising AI’s transformative potential and ensuring that America’s lead endures.”

(Photo by Nils Huenerfuerst) 

See also: Gemma 3: Google launches its latest open AI models

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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The monumental project, led by Fir Hills – a division of California-based Stock Farm Road, Inc. (SFR) – is expected to commence construction in winter 2025 and aims to generate an initial annual revenue of $3.5 billion.  

The facility, located in the Jeollanam-do Province, is the result of a strategic collaboration between seasoned innovators. SFR was co-founded by LG heir Brian Koo and Dr Amin Badr-El-Din, a veteran of successful ventures in technology, energy, and global public-private partnerships.

“This is more than just a technological milestone; it’s a strategic leap forward for Korea’s global technological leadership,” said Dr Badr-El-Din.

“We are incredibly proud to partner with Stock Farm Road and the Jeollanam-do government to build this crucial infrastructure, creating an unprecedented opportunity to build the foundation for next-generation AI.”

The initial project is valued at over $10 billion, with the potential to grow to $35 billion. Upon completion in 2028, the centre will boast a 3-gigawatt capacity, making it the largest AI data facility in the world.

The centre is designed to meet the sophisticated requirements of next-generation AI, featuring advanced cooling infrastructure, cutting-edge fibre bandwidth for regional and global connectivity, and the capability to manage significant and sudden energy load variations.  

This level of infrastructural sophistication not only promises bolstered AI innovation but is also a boon for South Korea’s economy. With projections suggesting that the burgeoning data centre services market will grow to $438.3 billion by 2030, South Korea’s 3GW behemoth positions itself as a pivotal player in the industry.

“Having witnessed firsthand the immense technological capabilities of large Asian enterprises, I recognise the potential of this project to elevate Korea and the region to a new level of technological advancement and economic prosperity,” commented Koo.

“This data centre is not merely an infrastructure project, but the launchpad for a new digital industrial revolution.”

A data centre for the future of South Korea

The scale of the project translates into major economic gains for the Jeollanam-do Province and beyond.

The initiative is expected to create over 10,000 jobs spanning various sectors, including energy supply and storage (ESS), renewable energy production, equipment manufacturing, and research and development (R&D).  

Moreover, the data centre’s services will benefit millions, catering to the needs of hundreds of large corporations—hyperscalers and developers among them.  

The centre’s development is only the first step in a broader strategy by SFR. Future projects are already on the horizon, as the company plans to establish AI infrastructure partnerships across Asia, Europe, and the US in the next 18 months.  

SFR’s expertise in Energy-to-Intelligence (e2i²) forms the backbone of this push, transforming traditional energy infrastructure into platforms for advanced AI innovation.

With access to significant financial resources and a robust network extending across both Asian and Western markets, SFR could lead the next generation of global intelligent infrastructure.  

In just over a decade, South Korea has transformed into a technological powerhouse. With companies like Samsung, LG, and Hyundai leading in their respective sectors, the nation is now solidifying its standing in AI and data infrastructure.

The massive Jeollanam-do AI data centre underscores how strategically aligned public-private partnerships can foster innovation on a monumental scale. By establishing such a colossal infrastructure project, South Korea is furthering its ambitions to catalyse a true digital industrial revolution.  

See also: UK must act to secure its semiconductor industry leadership

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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The company harnessed an immense data centre equipped with approximately 200,000 GPUs to develop Grok 3. According to xAI owner Elon Musk, this project utilised “10x” more computing power than its predecessor, Grok 2, with an expanded dataset that reportedly includes information from legal case filings.

Musk claimed that Grok 3 is a “maximally truth-seeking AI, even if that truth is sometimes at odds with what is politically-correct.”

The Grok 3 rollout includes a family of models designed for different needs. Grok 3 mini, for example, prioritises faster response times over absolute accuracy. However, particularly noteworthy are the new reasoning-focused Grok 3 models.

Dubbed Grok 3 Reasoning and Grok 3 mini Reasoning, these variants aim to emulate human-like cognitive processes by “thinking through” problems. Comparable to models like OpenAI’s o3-mini and DeepSeek’s R1, these reasoning systems attempt to fact-check their responses—reducing the likelihood of errors or missteps.

Grok 3: The benchmark results

xAI asserts that Grok 3 surpasses OpenAI’s GPT-4o in certain benchmarks, including AIME and GPQA, which assess the model’s proficiency in tackling complex problems across mathematics, physics, biology, and chemistry.

The early version of Grok 3 is also currently leading on Chatbot Arena, a crowdsourced evaluation platform where users pit AI models against one another and rank their outputs. The model is the first to break the Arena’s 1400 score.

According to xAI, Grok 3 Reasoning outperforms its rivals on a variety of prominent benchmarks:

These reasoning models are already integrated into features available via the Grok app. Users can select commands like “Think” or activate the more computationally-intensive “Big Brain” mode for tackling particularly challenging questions.

xAI has positioned the reasoning models as ideal tools for STEM (science, technology, engineering, and mathematics) applications, including mathematics, science, and coding challenges.

Guarding against AI distillation

Interestingly, not all of Grok 3’s internal processes are laid bare to users. Musk explained that some of the reasoning models’ “thoughts” are intentionally obscured to prevent distillation—a controversial practice where competing AI developers extract knowledge from proprietary models.

The practice was thrust into the spotlight in recent weeks after Chinese AI firm DeepSeek faced allegations of distilling OpenAI’s models to develop its latest model, R-1.

xAI’s new reasoning models serve as the foundation for a new Grok app feature called DeepSearch. The feature uses Grok models to scan the internet and Musk’s social platform, X, for relevant information before synthesising a detailed abstract in answer to user queries.

Accessing Grok 3 and committing to open-source

Access to the latest Grok model is currently tied to X’s subscription tiers. Premium+ subscribers, who pay $50 (~£41) per month, will receive priority access to the latest functionalities. 

xAI is also introducing a SuperGrok subscription plan, reportedly priced at either $30 per month or $300 annually. SuperGrok subscribers will benefit from enhanced reasoning capabilities, more DeepSearch queries, and unlimited image generation features.

The company also teased upcoming features. Within a week, the Grok app is expected to introduce a voice mode—enabling users to interact with the AI through a synthesised voice similar to Gemini Live.

Musk further revealed plans to release Grok 3 models via an enterprise-ready API in the coming weeks, with DeepSearch functionality included.

Although Grok 3 is still fresh, xAI intends to open-source its predecessor in the coming months. Musk claims that xAI will continue to open-source the last version of Grok.

“When Grok 3 is mature and stable, which is probably within a few months, then we’ll open-source Grok 2,” explains Musk.

The ‘anti-woke’ AI model

Grok has long been marketed as unfiltered, bold, and willing to engage with queries that competitors might avoid. Musk previously described the AI as “anti-woke,” presenting it as a model unafraid to touch on controversial topics. 

True to its promise, early models like Grok and Grok 2 embraced politically-charged queries, even veering into colourful language when prompted. Yet, these versions also revealed some biases when delving deep into political discourse.

“We’re working to shift Grok closer to politically-neutral,” said Musk.

However, whether Grok 3 achieves this goal remains to be seen. With such changes at play, analysts are already highlighting the potential societal impacts of introducing increasingly “truth-seeking” yet politically-sensitive AI systems.

With Grok 3, Musk and xAI have made a bold statement, pushing their technology forward while potentially fuelling debates around bias, transparency, and the ethics of AI deployment.

As competitors like OpenAI, Google, and DeepSeek refine their offerings, Grok 3’s success will hinge on its ability to balance accuracy, user demand, and societal responsibility.

See also: AI in 2025: Purpose-driven models, human integration, and more

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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Laura Foster, Associate Director of Technology and Innovation at techUK, said: “The UK has a unique opportunity to lead in the global semiconductor landscape, but success will require bold action and sustained commitment.

“By accelerating the implementation of the National Semiconductor Strategy, we can unlock investment, foster innovation, and strengthen our position in this critical industry.  

Semiconductors are the backbone of modern technology, powering everything from consumer electronics to AI data centres. With the global semiconductor market projected to reach $1 trillion by 2030, the UK must act to secure its historic leadership in this lucrative and strategically vital industry.

“We must act at pace to secure the UK’s semiconductor future and as such our technological and economic resilience,” explains Foster.

UK semiconductor industry strengths and challenges

The UK has long been a leader in semiconductor design and intellectual property (IP), with Cambridge in particular serving as a global hub for innovation.

Companies like Arm, which designs chips used in 99% of the world’s smartphones, exemplify the UK’s strengths in this area. However, a techUK report warns that these strengths are under threat due to insufficient investment, skills shortages, and a lack of tailored support for the sector.

“The UK is not starting from zero,” the report states. “We have globally competitive capabilities in design and IP, but we must double down on these strengths to compete internationally.”

The UK’s semiconductor industry contributed £12 billion in turnover in 2021, with 90% of companies expecting growth in the coming years. However, the sector faces significant challenges, including high costs, limited access to private capital, and a reliance on international talent.

The report highlights that only 5% of funding for UK semiconductor startups originates domestically, with many companies struggling to find qualified investors.

A fundamental need for strategic investment and innovation

The report makes 27 recommendations across six key areas, including design and IP, R&D, manufacturing, skills, and global partnerships.

Some of the key proposals include:

• Turn current strengths into leadership: The UK must leverage its existing capabilities in design, IP, and compound semiconductors. This includes supporting regional clusters like Cambridge and South Wales, which have proven track records of innovation.

• Establishing a National Semiconductor Centre: This would act as a central hub for the industry, providing support for businesses, coordinating R&D efforts, and fostering collaboration between academia and industry.

• Expanding R&D tax credits: The report calls for the inclusion of capital expenditure in R&D tax credits to incentivise investment in new facilities and equipment.

• Creating a Design Competence Centre: This would provide shared facilities for chip designers, reducing the financial risk of innovation and supporting the development of advanced designs.

• Nurturing skills: The UK must address the skills shortage in the semiconductor sector by upskilling workers, attracting international talent, and promoting STEM education.

• Capitalise on global partnerships: The UK must strengthen its position in the global semiconductor supply chain by forming strategic partnerships with allied countries. This includes collaborating on R&D, securing access to critical materials, and navigating export controls.

Urgent action is required to secure the UK semiconductor industry

The report warns that the UK risks falling behind other nations if it does not act quickly. Countries like the US, China, and the EU have already announced significant investments in their domestic semiconductor industries.

The European Chips Act, for example, has committed €43 billion to support semiconductor infrastructure, skills, and startups.

“Governments across the world are acting quickly to attract semiconductor companies while also building domestic capability,” the report states. “The UK must use its existing resources tactically, playing to its globally recognised strengths within the semiconductor value chain.”

The UK’s semiconductor industry has the potential to be a global leader, but this will require sustained investment, strategic planning, and collaboration between government, industry, and academia.

“The UK Government should look to its semiconductor ambitions as an essential part of delivering the wider Industrial Strategy and securing not just the fastest growth in the G7, but also secure and resilient economic growth,” the report concludes.

(Photo by Rocco Dipoppa)

See also: AI in 2025: Purpose-driven models, human integration, and more

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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While the US and China are often seen as frontrunners, von der Leyen emphasised that the AI race “is far from over” and that Europe has distinct strengths to carve a leading role for itself.

“This is the third summit on AI safety in just over one year,” von der Leyen remarked. “In the same period, three new generations of ever more powerful AI models have been released. Some expect models that will approach human reasoning within a year’s time.”

The European Commission President set the tone of the event by contrasting the groundwork laid in previous summits with the urgency of this one.

“Past summits focused on laying the groundwork for AI safety. Together, we built a shared consensus that AI will be safe, that it will promote our values and benefit humanity. But this Summit is focused on action. And that is exactly what we need right now.”

As the world witnesses AI’s disruptive power, von der Leyen urged Europe to “formulate a vision of where we want AI to take us, as society and as humanity.” Growing adoption, “in the key sectors of our economy, and for the key challenges of our times,” provides a golden opportunity for the continent to lead, she argued.

The case for a European approach to the AI race 

Von der Leyen rejected notions that Europe has fallen behind its global competitors.

“Too often, I hear that Europe is late to the race – while the US and China have already got ahead. I disagree,” she stated. “The frontier is constantly moving. And global leadership is still up for grabs.”

Instead of replicating what other regions are doing, she called for doubling down on Europe’s unique strengths to define the continent’s distinct approach to AI.

“Too often, I have heard that we should replicate what others are doing and run after their strengths,” she said. “I think that instead, we should invest in what we can do best and build on our strengths here in Europe, which are our science and technology mastery that we have given to the world.”

Von der Leyen defined three pillars of the so-called “European brand of AI” that sets it apart: 1) focusing on high-complexity, industry-specific applications, 2) taking a cooperative, collaborative approach to innovation, and 3) embracing open-source principles.

“This summit shows there is a distinct European brand of AI,” she asserted. “It is already driving innovation and adoption. And it is picking up speed.”

Accelerating innovation: AI factories and gigafactories  

To maintain its competitive edge, Europe must supercharge its AI innovation, von der Leyen stressed.

A key component of this strategy lies in its computational infrastructure. Europe already boasts some of the world’s fastest supercomputers, which are now being leveraged through the creation of “AI factories.”

“In just a few months, we have set up a record of 12 AI factories,” von der Leyen revealed. “And we are investing €10 billion in them. This is not a promise—it is happening right now, and it is the largest public investment for AI in the world, which will unlock over ten times more private investment.”

Beyond these initial steps, von der Leyen unveiled an even more ambitious initiative. AI gigafactories, built on the scale of CERN’s Large Hadron Collider, will provide the infrastructure needed for training AI systems at unprecedented scales. They aim to foster collaboration between researchers, entrepreneurs, and industry leaders.

“We provide the infrastructure for large computational power,” von der Leyen explained. “Talents of the world are welcome. Industries will be able to collaborate and federate their data.”

The cooperative ethos underpinning AI gigafactories is part of a broader European push to balance competition with collaboration.

“AI needs competition but also collaboration,” she emphasised, highlighting that the initiative will serve as a “safe space” for these cooperative efforts.

Building trust with the AI Act

Crucially, von der Leyen reiterated Europe’s commitment to making AI safe and trustworthy. She pointed to the EU AI Act as the cornerstone of this strategy, framing it as a harmonised framework to replace fragmented national regulations across member states.

“The AI Act [will] provide one single set of safety rules across the European Union – 450 million people – instead of 27 different national regulations,” she said, before acknowledging businesses’ concerns about regulatory complexities.

“At the same time, I know, we have to make it easier, we have to cut red tape. And we will.”

€200 billion to remain in the AI race

Financing such ambitious plans naturally requires significant resources. Von der Leyen praised the recently launched EU AI Champions Initiative, which has already pledged €150 billion from providers, investors, and industry.

During her speech at the summit, von der Leyen announced the Commission’s complementary InvestAI initiative that will bring in an additional €50 billion. Altogether, the result is mobilising a massive €200 billion in public-private AI investments.

“We will have a focus on industrial and mission-critical applications,” she said. “It will be the largest public-private partnership in the world for the development of trustworthy AI.”

Ethical AI is a global responsibility

Von der Leyen closed her address by framing Europe’s AI ambitions within a broader, humanitarian perspective, arguing that ethical AI is a global responsibility.

“Cooperative AI can be attractive well beyond Europe, including for our partners in the Global South,” she proclaimed, extending a message of inclusivity.

Von der Leyen expressed full support for the AI Foundation launched at the summit, highlighting its mission to ensure widespread access to AI’s benefits.

“AI can be a gift to humanity. But we must make sure that benefits are widespread and accessible to all,” she remarked.

“We want AI to be a force for good. We want an AI where everyone collaborates and everyone benefits. That is our path – our European way.”

See also: AI Action Summit: Leaders call for unity and equitable development

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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A report published today by the National Engineering Policy Centre (NEPC) highlights the urgent need for data centres to adopt greener practices, particularly as the government’s AI Opportunities Action Plan gains traction.

The report, Engineering Responsible AI: Foundations for Environmentally Sustainable AI, was developed in collaboration with the Royal Academy of Engineering, the Institution of Engineering and Technology, and BCS, the Chartered Institute of IT.

While stressing that data centres enabling AI systems can be built to consume fewer resources like energy and water, the report highlights that infrastructure and regulatory conditions must align for these efficiencies to materialise.

Unlocking the potential of AI while minimising environmental risks  

AI is heralded as capable of driving economic growth, creating jobs, and improving livelihoods. Launched as a central pillar of the UK’s tech strategy, the AI Opportunities Action Plan is intended to “boost economic growth, provide jobs for the future and improve people’s everyday lives.”  

Use cases for AI that are already generating public benefits include accelerating drug discovery, forecasting weather events, optimising energy systems, and even aiding climate science and improving sustainability efforts. However, this growing reliance on AI also poses environmental risks from the infrastructure required to power these systems.  

Data centres, which serve as the foundation of AI technologies, consume vast amounts of energy and water. Increasing demand has raised concerns about global competition for limited resources, such as sustainable energy and drinking water. Google and Microsoft, for instance, have recorded rising water usage by their data centres each year since 2020. Much of this water comes from drinking sources, sparking fears about resource depletion.  

With plans already in place to reform the UK’s planning system to facilitate the construction of data centres, the report calls for urgent policies to manage their environmental impact. Accurate and transparent data on resource consumption is currently lacking, which hampers policymakers’ ability to assess the true scale of these impacts and act accordingly.

Five steps to sustainable AI  

The NEPC is urging the government to spearhead change by prioritising sustainable AI development. The report outlines five key steps policymakers can act upon immediately to position the UK as a leader in resource-efficient AI:  

1. Expand environmental reporting mandates
2. Communicate the sector’s environmental impacts
3. Set sustainability requirements for data centres
4. Reconsider data collection, storage, and management practices
5. Lead by example with government investment

Mandatory environmental reporting forms a cornerstone of the recommendations. This involves measuring data centres’ energy sources, water consumption, carbon emissions, and e-waste recycling practices to provide the resource use data necessary for policymaking.  

Raising public awareness is also vital. Communicating the environmental costs of AI can encourage developers to optimise AI tools, use smaller datasets, and adopt more efficient approaches. Notably, the report recommends embedding environmental design and sustainability topics into computer science and AI education at both school and university levels.  

Smarter, greener data centres  

One of the most urgent calls to action involves redesigning data centres to reduce their environmental footprint. The report advocates for innovations like waste heat recovery systems, zero drinking water use for cooling, and the exclusive use of 100% carbon-free energy certificates.  

Efforts like those at Queen Mary University of London, where residual heat from a campus data centre is repurposed to provide heating and hot water, offer a glimpse into the possibilities of greener tech infrastructure.  

In addition, the report suggests revising legislation on mandatory data retention to reduce the unnecessary environmental costs of storing vast amounts of data long-term. Proposals for a National Data Library could drive best practices by centralising and streamlining data storage.  

Professor Tom Rodden, Pro-Vice-Chancellor at the University of Nottingham and Chair of the working group behind the report, urged swift action:  

“In recent years, advances in AI systems and services have largely been driven by a race for size and scale, demanding increasing amounts of computational power. As a result, AI systems and services are growing at a rate unparalleled by other high-energy systems—generally without much regard for resource efficiency.  

“This is a dangerous trend, and we face a real risk that our development, deployment, and use of AI could do irreparable damage to the environment.”  

Rodden added that reliable data on these impacts is critical. “To build systems and services that effectively use resources, we first need to effectively monitor their environmental cost. Once we have access to trustworthy data… we can begin to effectively target efficiency in development, deployment, and use – and plan a sustainable AI future for the UK.”

Dame Dawn Childs, CEO of Pure Data Centres Group, underscored the role of engineering in improving efficiency. “Some of this will come from improvements to AI models and hardware, making them less energy-intensive. But we must also ensure that the data centres housing AI’s computing power and storage are as sustainable as possible.  

“That means prioritising renewable energy, minimising water use, and reducing carbon emissions – both directly and indirectly. Using low-carbon building materials is also essential.”  

Childs emphasised the importance of a coordinated approach from the start of projects. “As the UK government accelerates AI adoption – through AI Growth Zones and streamlined planning for data centres – sustainability must be a priority at every step.”  

For Alex Bardell, Chair of BCS’ Green IT Specialist Group, the focus is on optimising AI processes. “Our report has discussed optimising models for efficiency. Previous attempts to limit the drive toward increased computational power and larger models have faced significant resistance, with concerns that the UK may fall behind in the AI arena; this may not necessarily be true.  

“It is crucial to reevaluate our approach to developing sustainable AI in the future.”  

Time for transparency around AI environmental risks

Public awareness of AI’s environmental toll remains low. Recent research by the Institution of Engineering and Technology (IET) found that fewer than one in six UK residents are aware of the significant environmental costs associated with AI systems.  

“AI providers must be transparent about these effects,” said Professor Sarvapali Ramchurn, CEO of Responsible AI UK and a Fellow of the IET. “If we cannot measure it, we cannot manage it, nor ensure benefits for all. This report’s recommendations will aid national discussions on the sustainability of AI systems and the trade-offs involved.”  

As the UK pushes forward with ambitious plans to lead in AI development, ensuring environmental sustainability must take centre stage. By adopting policies and practices outlined in the NEPC report, the government can support AI growth while safeguarding finite resources for future generations.

(Photo by Braden Collum)

See also: Sustainability is key in 2025 for businesses to advance AI efforts

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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Regardless of whether this is being powered via a supercomputer, edge computing methods, or a traditional data centre, society is truly feeling the positive effect of advances in the AI industry.

However, with fresh innovation has always come questions around environmental impact. These concerns are gaining momentum, especially around the energy consumption associated with the increased processing power required to run increasingly large systems.

The United Nations Environment Programme recently expressed concerns about the rising levels of e-waste and cooling considerations for data centres more specifically. This also follows on from similar concerns from academia, who have flagged that a larger carbon footprint might be the price we are paying for innovation.

Add on top of this the fact that governments globally are implementing new regulations and reporting requirements as part of initiatives to curb the impact of climate change, such as the EU’s Circular Economy Action Plan (CEAP), and it becomes clear this issue is coming to the forefront of the AI agenda.

Analysts around the globe are also beginning to focus on this, with Gartner naming energy-efficient computing as a top technology trend for 2025, as organisations come under pressure to show they are considering the impact AI is having on the environment.

Businesses that are not considering sustainability as part of core AI infrastructure and expansion or technology strategies are at risk of hindering their own progress. Failing to keep pace with sustainable practices can cause reputational damage, as organisations may be seen as behind the curve in an increasingly sustainability-focused world, alongside risking non-compliance with regulation.

When looking at the previously mentioned example of e-waste, if organisations are found to be not properly recycling devices (such as our Global Take Back Service), they could face negative feedback and lose business as a result of poor brand image. With these factors in mind, it’s clear that businesses must consider building a sustainable AI framework that supports operational efficiency, encouraging business growth.

Prioritising the implementation of technologies that limit energy consumption can be a huge help when it comes to ensuring regulatory compliance and the ability to meet greater sustainability goals. These also come with the ability to help organisations to future-proof against market instability with reduced reliance on energy along with strengthening brand reputation in an increasingly environmentally-conscious world.

This is within easy reach for many businesses as there is a large number of offerings in the market that can balance sustainability efforts, with high processing capabilities. At ASUS we have partnered with Intel to provide servers that prioritise energy efficiency. There is so much available to businesses today if they choose to take the initial step and consider a strategy to implement technologies which balance regulatory pressures, customer expectations, and overall business goals will help organisations to feel confident innovation won’t come at a cost to the environment.

IDC has raised this with its audience, recently releasing predictions on the technology industry which outlined; “To address the environmental challenges of harnessing AI’s benefits, enterprises are turning to Sustainable AI Frameworks that focus on minimising the environmental impact of artificial intelligence by addressing key elements such as energy efficiency, resource optimisation, and e-waste reduction.”

As AI innovation continues to grow, alongside market pressure, businesses will find it becomes clear which organisations within the market are able to cope, and which will be left behind. Ultimately, those who choose to embed sustainability into AI strategies will lead the way.

(Photo by Angela Benito)

See also: French initiative for responsible AI leaders

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.
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On Tuesday, he signed an executive order aimed at providing federal support to fast-track the development of infrastructure needed to power these AI DC facilities, the White House has announced.

The order sets out a plan to lease federal land managed by the Defence and Energy departments for gigawatt-scale AI data centres and clean power projects. The goal is to meet the immense energy requirements of these facilities in a shorter timeframe.

“The order will speed up how we build the next generation of AI infrastructure right here in America,” Biden said. He added that the initiative is designed to boost economic competitiveness, strengthen national security, promote clean energy, and ensure AI safety.

One notable aspect of the order is its emphasis on American-made technology. Companies that use federal sites for AI data centres will be ordered to purchase a fair amount of US-made semiconductors. The specifics will be worked out for each project and is in line with the Biden administration’s overall aim to invest over $30 billion in domestic chip production.

The administration is also working to streamline processes for building AI infrastructure. Federal agencies have been directed to expedite the granting of permits, improve connections to the electric grid, and advance transmission development around federal sites. The measures are intended to avoid delays that could hinder the rapid deployment of essential infrastructure.

Tarun Chhabra, White House technology adviser, emphasised the urgency of the endeavour. “It’s absolutely essential to make sure the AI industry can build the infrastructure it needs for training and deploying powerful AI models right here in the US,” he told reporters.

Chhabra noted that the demand for computing power and electricity is soaring, especially as AI developers work on advanced “frontier models,” the most powerful and resource-intensive AI systems available. He estimated that by 2028, some AI data centres could require as much as five gigawatts of capacity – enough energy to power millions of homes.

The executive order also seeks to align AI development with environmental goals. Companies developing projects are urged to use sustainable energy and have minimal impact on electricity prices. The requirement reflects growing concerns about the environmental impact of AI data centres, which consume enormous amounts of energy, plus water for cooling.

In a related move, the Commerce Department has tightened restrictions on AI chip and technology exports. The goal is to keep advanced computing capabilities in the US and allied nations while limiting access for competing countries. This complements the executive order’s focus on safeguarding national security by keeping cutting-edge AI models secure and based on US soil.

Biden also gave a bigger picture of AI with regards to national security. Chhabra pointed out that AI systems being developed today already have capabilities that might be used for malicious purposes, like weapon development or cyberattacks. By securing domestic data centres, the US reduces the likelihood of adversaries gaining access to these powerful systems.

The tech industry has reacted positively to the order. Major corporations like Microsoft, BlackRock, and SoftBank have announced significant investments in US-based AI infrastructure, aligning with the administration’s ambition for domestic technological leadership.

By addressing energy demands, environmental considerations, and national security risks, Biden’s executive order lays the groundwork for a robust, secure, and sustainable AI infrastructure. It reflects the administration’s commitment to ensuring that the US remains a global leader in AI development and deployment.

(Photo by Unsplash)

See also: US-China tech war escalates with new AI chips export controls

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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The facility stands out for its advanced infrastructure and focus on energy efficiency, reflecting broader efforts to meet the rising demands of AI computing sustainably.

The AI Factory is part of Firmus’s ongoing initiative to transform existing ST Telemedia Global Data Centres (STT GDC) into GPU-powered AI computing platforms. The redesigned centres are equipped with state-of-the-art hardware and efficient cooling systems, enabling them to meet both enterprise and research needs with improved energy performance metrics.

As artificial intelligence continues to need more power, energy efficiency has become a major issue. Firmus has addressed the issue for nearly a decade with its AI Factory platform, which combines advanced immersion cooling technology with dependable design, build, and operation services. The company states its platform has several significant advantages, including:

• Energy efficiency: 45% more FLOP per utility picoJoule than traditional data centres,
• Cost-effectiveness: Up to 30% cheaper total cost of ownership (TCO) than direct-to-chip cooling platforms,
• Scalability and sustainability: Supports high-density AI workloads while reducing environmental effects,
• Global expertise: A track record in building and operating immersion-cooled data centres in Singapore and Australia.

The deployment of the AI Factory in Singapore shows how innovative approaches to data centre infrastructure can address the energy demands of AI. The project highlights a potential pathway for sustainable AI development by achieving a pPUE of 1.02 and a reduction in energy consumption of 45%. The achievement aligns with Singapore’s National AI Strategy 2.0, which emphasises sustainable growth in AI and data centre innovation.

Tim Rosenfield, co-CEO of Firmus Technologies, explained the broader vision behind the project, noting that it’s about balancing AI growth with sustainability. “By rethinking data centre design, we have created a platform that supports the growth of AI while promoting environmental sustainability. If we can do it in Singapore, where space is constrained and the humid climate is against us, we can do it anywhere,” he said.

Firmus has recently changed its leadership team, adding Dr. Daniel Kearney as chief technology officer. Previously AWS’s Head of Technology for the ASEAN Enterprise business, Kearney leads the engineering team at Firmus. He pointed out how sustainable AI infrastructure is becoming essential as AI technologies expand. “This win against established data centre players recognises the importance of technology like ours in meeting the growth of AI and the energy challenges it brings,” he said.

The company has been advancing its work through the Sustainable Metal Cloud (SMC), an initiative aimed at improving the efficiency and sustainability of AI infrastructure. Recent updates from Firmus include:

• Power efficiency benchmarks: Firmus became the first to publish comprehensive power consumption data alongside performance results for the MLPerf Training benchmark,
• Policy contributions: Insights from Tim Rosenfield contributed to the Tony Blair Institute for Global Change’s policy agenda on managing the energy demands of the AI sector,
• Industry discussions: At ATxSG24, Firmus’s Chairman, Edward Pretty, joined a panel featuring organisations like NVIDIA, the World Bank, and Alibaba Cloud to explore the balance between sustainability and the computational needs of AI,
• Hypercube expansion: Firmus’s team of 700 is installing the first fleet of Sustainable AI Factories, known as HyperCubes in multiple regions.
• Engagement at NVIDIA GTC 2024: The company participated in two panels at NVIDIA’s GTC event, discussing sustainable AI infrastructure alongside partners like NVIDIA, Deloitte, and WEKA.

See also: The AI revolution: Reshaping data centres and the digital landscape 

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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Released in November 2024, the Commission’s annual report outlined 32 recommendations that could fundamentally alter how the two countries interact, with artificial intelligence taking centre stage in a new chapter of strategic rivalry.

US-China: the AGI moonshot and critical tech controls

At the heart of the report lies an ambitious proposal: establishing a government-backed programme to develop AGI – AI systems that could match and potentially exceed human cognitive abilities. 

However, the recommendation is just one piece of a larger technological puzzle, including export controls, investment screening, and new trade policies to preserve US technological advantages. 

The proposed AGI initiative would provide multi-year contracts to leading AI companies, cloud providers, and data centre operators. It would be backed by the Defense Department’s highest priority, “DX Rating” – a designation typically reserved for critical national security projects. 

This level of government involvement in AI development mirrors the urgency seen in previous technological races. It raises crucial questions about the role of state intervention in an industry primarily driven by private sector innovation.

The Commission’s tech-focused recommendations extend beyond AI. Notable proposals include restricting imports of Chinese-made autonomous humanoid robots with advanced dexterity, locomotion, and intelligence capabilities. 

The report also targets energy infrastructure products with remote monitoring capabilities, reflecting growing concerns about connected technologies in critical infrastructure. The report builds on existing export controls in the semiconductor space by recommending stronger oversight of technology transfers and investment flows. 

This comes as China continues to build domestic chip-making capabilities despite international restrictions. The Commission suggests creating an Outbound Investment Office that prevents US capital and expertise from advancing China’s technological capabilities in sensitive sectors.

Reshaping trade relations and investment flows

Perhaps most significantly, the report recommends eliminating China’s Permanent Normal Trade Relations (PNTR) status—a move that could reshape the technology supply chain and trade flows that have defined the global tech industry for decades. This recommendation acknowledges how deeply intertwined the US and Chinese tech ecosystems have become, while suggesting that this interdependence may now pose more risks than benefits.

Data transparency is another key theme, with recommendations for expanded reporting requirements on investments and technology transfers. The Commission calls for better tracking of investments flowing through offshore entities, addressing a significant blind-spot in current oversight mechanisms.

The report’s release comes at a critical juncture in technological development. China’s push for self-sufficiency in vital technologies and its “new quality productive forces” initiative demonstrates Beijing’s determination to lead in next-generation technologies. Meanwhile, AI capabilities and quantum computing breakthroughs have raised the stakes in technology competition.

However, the Commission’s recommendations face practical challenges. Achieving AGI remains a complex scientific challenge that may not yield quick results, regardless of funding levels. Additionally, restrictions on technology transfers and investment could have unintended consequences for global innovation networks that have historically benefited both nations.

If these recommendations are implemented, the tech industry may need to navigate an increasingly complex regulatory landscape. Companies would face new compliance requirements for international investments, technology transfers, and collaborative research projects.

Challenges and future implications

The effectiveness of the proposed measures will likely depend on coordination with allies and partners who share similar technological capabilities and concerns. The report acknowledges this by recommending multilateral approaches to export controls and investment screening.

US-China technological competition has entered a new phase where government policy may play a more direct role in shaping development. Whether this approach accelerates or hinders innovation remains to be seen, but the tech industry should prepare for increased scrutiny and regulation of international technological collaboration.

(Photo by Nathan Bingle)

See also: Chinese firms use cloud loophole to access US AI tech

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Manhattan Project 2.0? US eyes AGI breakthrough in escalating China rivalry appeared first on AI News.

With data centres burning vast amounts of energy, the growing demand for GenAI has sparked a debate about its sustainability.

The cost of intelligence: Generative AI’s carbon footprint

Behind every AI-generated email, idea, or recommendation are data centres running thousands of energy-hungry servers. Data centres are responsible for both training the large language models that power generative AI and processing individual user queries. Unlike a simple Google search, which uses relatively little energy, a single generative AI request can consume up to ten times as much electricity.

The numbers are staggering. If all nine billion daily Google searches worldwide were replaced with generative AI tasks, the additional electricity demand would match the annual energy consumption of 1.5 million EU residents. According to consultants Morgan Stanley, the energy demands of generative AI are expected to grow by 70% annually until 2027. By that point, the energy required to support generative AI systems could rival the electricity needs of an entire country—Spain, for example, based on its 2022 usage.

UK consumers want greener AI practices

The survey also highlights growing awareness among UK consumers about the environmental implications of generative AI. Nearly one in five respondents said they don’t trust generative AI providers to manage their environmental impact responsibly. Among regular users of these tools, 10% expressed a willingness to pay a premium for products or services that prioritise energy efficiency and sustainability.

Interestingly, over a third (35%) of respondents think generative AI tools should “actively remind” users of their environmental impact. While this appears like a small step, it has the potential to encourage more mindful usage and place pressure on companies to adopt greener technologies.

Efforts to tackle the environmental challenge

Fortunately, some companies and policymakers are beginning to address these concerns. In the United States, the Artificial Intelligence Environmental Impacts Act was introduced earlier this year. The legislation aims to standardise how AI companies measure and report carbon emissions. It also provides a voluntary framework for developers to evaluate and disclose their systems’ environmental impact, pushing the industry towards greater transparency.

Major players in the tech industry are also stepping up. Companies like Salesforce have voiced support for legislation requiring standardised methods to measure and report AI’s carbon footprint. Experts point to several practical ways to reduce generative AI’s environmental impact, including adopting energy-efficient hardware, using sustainable cooling methods in data centres, and transitioning to renewable energy sources.

Despite these efforts, the urgency to address generative AI’s environmental impact remains critical. As Uday Radia, owner of CloudNine PR, puts it: “Generative AI has huge potential to make our lives better, but there is a race against time to make it more sustainable before it gets out of control.”

(Photo by Unsplash)

See also: The AI revolution: Reshaping data centres and the digital landscape 

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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