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Time to share: Energy supply chain awaits UK government to unlock billions of investment

There are more energy projects awaiting final investment decisions (FIDs) in the UK now than there have been in decades, a trade body boss has warned. While this represents a great deal of potential investment across oil and gas as well as carbon capture and storage (CCS), offshore wind and other clean energy schemes, it […]

There are more energy projects awaiting final investment decisions (FIDs) in the UK now than there have been in decades, a trade body boss has warned.

While this represents a great deal of potential investment across oil and gas as well as carbon capture and storage (CCS), offshore wind and other clean energy schemes, it means development is also pent up with little to feed the UK supply chain until the commitment is made to unleash the cash.

Speaking at the annual Share Fair event, Dave Whitehouse, chief executive of the trade body Offshore Energies UK pointed to the firm’s latest research into supply chain sentiment, released ahead of the annual event in Aberdeen, which found almost all companies in the UK offshore energy supply chain are instead looking elsewhere around the world for work rather than in the UK.

OEUK CEO David Whitehouse © Supplied by OEUK
OEUK CEO David Whitehouse

“Almost 90% of our supply chain members are seeing that their growth opportunities lie overseas,” he said.

“I think it’s good to explore their expertise. But the truth is we need to change that. We need to unlock more projects here in the UK, and that means more oil and gas projects alongside our wind, floating wind, carbon storage and hydrogen projects.”

He added: “What our members are saying is, actually a significant number of them are seeing less activity.

“But the truth is, when you when you look across the UK, you are seeing more projects which are in that pre-final investment decision than probably I’ve seen in my career. The opportunity now is, how do you unlock those? How do you how do we get those projects unlocked? How do we create the certainty that those projects start to move forward?”

‘Don’t get too excited’

OEUK has hosted Share Fair for over 20 years. Designed to forge relationships with North Sea oil and gas operators with the local supply chain, the focus has shifted dramatically in recent years.

BP had a big stand at the show where its partner Hydrasun, delivered the latest update on a pivotal green energy project. The Aberdeen Hydrogen Hub, a joint venture between BP and Aberdeen City Council, has recently done a deal to bring in a 2.5MW electrolyser.

In more traditional vein, there was also the likes of Ineos presenting an update on progress in the Pegasus Area Licenses. The gas field lies around 66 miles north-east of Flamborough Head on the North Yorkshire coast.

A presentation by Celtic Sea Power also attracted attention from the audience of contractors keen to bid for work in floating offshore wind.

The company, owned by Cornwall Council, is supporting the development of 12GW of offshore wind off the coast of Wales and South West England and building supply chain involvement.

Celtic Sea Power business development manager Phil Johnston started his presentation by managing expectations.

He said: “I’ll explain the time frame as best I can. I wouldn’t get too excited. It’s going to be a long haul, but, you know, it’s a major, major market that’s opening up.”

The first to get a start in the region was a 32MW project being developed by Swedish firm Hexicon which won support from the UK government in the contracts for difference (CfD) funding round, AR4.

Others in the Celtic Sea hoping to land strike prices in this year’s AR7 round, which will enable developers to commit to investment, include Simply Blue and TotalEnergie’s 100MW Erebus project, Flotation Energy and Cobra’s 100 MW White Cross project and Floventis Energy’s 200MW Llyr project.

The latter recently changed hands after Dutch FPSO moorings giant SBM sold the Floventis portfolio to a small firm based in Fife, Cierco Energy.

“I don’t think it is any great secret the road to test demos is an easy one,” Johnston said.

Speed date meeting at OEUK Share Fair 2025 © Supplied by Michal Wachucik/ OEU
Speed date meeting at OEUK Share Fair 2025. Image: Michal Wachucik/ OEUK

Presentations at Share Fair are slick and well executed. Delegates can tune into presentations running across three stages using silent disco-style headphones. Meanwhile there are desks set up for meetings between developers and suppliers arranged not unlike speed dates.

OEUK supply chain and people director Katy Heidenreich confirmed the event attracted 550 delegates to discuss what is happening over the next 12 to 18 months.

Unlocking investment

The next year may be thin on the ground but over the next five years, the prize could be huge.

OEUK estimates that the private sector is set to invest up to £110 billion in UK energy projects. This is largely split between oil and gas and offshore wind, with the extra £10bn aimed at CCS and hydrogen.

However in order for this magnitude of investment to be achieved several things have to come into place and most of these are currently sitting on UK government desks in the Treasury and the Department for Energy Security and Net Zero (DESNZ).

These include the outcome of DESNZ’s building the North Sea’s energy future consultation to address the UK’s fiscal regime, which the industry accuses of being a jobs killer.

This is in addition to the government’s expected guidance for oil and gas firms on environmental impact assessments regarding scope 3 emissions on which the fate of the multi-billion pound Rosebank and Jackdaw oil and gas fields await.

As well, it is also expected Chancellor Rachel Reeves could yet pull a rabbit out of the hat for Acorn, a track-2 CCS project, around her Spring statement on 26 March.

OEUK supply chain and operations director Katy Heidenreich. © Supplied by OEUK
OEUK supply chain and operations director Katy Heidenreich.

Heidenreich said: “We are so incredibly fortunate that we still have a huge amount of resource under our North Sea.

“The Climate Change Committee have shown that between now and 2050 we are going to need around 13 billion barrels of oil.

“So 75% of our energy needs today are met by oil and gas, and we can meet around half of that from our own UK oil and gas resources, and we need to make the most of that.

“That is such a brilliant opportunity, not just for us to help with energy security and national security at home, but also, it’s the profits from that that help companies invest in new energies of the future.

“That’s the opportunity, and that’s what we need to make sure, working together with the government in partnership, with a competitive fiscal regime – the future of the North Sea consultation will set out the regulatory framework. The updated environmental impact assessment guidance will make sure projects are within the guidance that see those projects flow.

“Get the fiscal regime right. We get the regulatory framework right, and the opportunity is ours for the taking.”

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Video: Bluefield banks on solar expansion despite global headwinds

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Ashtead Technology sees “no shortage” of M&A opportunities

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Scotland generated record amount of renewable electricity in 2024

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Kolibri Sees Earnings Slip despite Production, Revenue Growth

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Cnooc Profit Rises on Increased Oil and Gas Drilling Output

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Former Arista COO launches NextHop AI for customized networking infrastructure

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Microsoft abandons data center projects as OpenAI considers its own, hinting at a market shift

A potential ‘oversupply position’ In a new research note, TD Cowan analysts reportedly said that Microsoft has walked away from new data center projects in the US and Europe, purportedly due to an oversupply of compute clusters that power AI. This follows reports from TD Cowen in February that Microsoft had “cancelled leases in the US totaling a couple of hundred megawatts” of data center capacity. The researchers noted that the company’s pullback was a sign of it “potentially being in an oversupply position,” with demand forecasts lowered. OpenAI, for its part, has reportedly discussed purchasing billions of dollars’ worth of data storage hardware and software to increase its computing power and decrease its reliance on hyperscalers. This fits with its planned Stargate Project, a $500 billion, US President Donald Trump-endorsed initiative to build out its AI infrastructure in the US over the next four years. Based on the easing of exclusivity between the two companies, analysts say these moves aren’t surprising. “When looking at storage in the cloud — especially as it relates to use in AI — it is incredibly expensive,” said Matt Kimball, VP and principal analyst for data center compute and storage at Moor Insights & Strategy. “Those expenses climb even higher as the volume of storage and movement of data grows,” he pointed out. “It is only smart for any business to perform a cost analysis of whether storage is better managed in the cloud or on-prem, and moving forward in a direction that delivers the best performance, best security, and best operational efficiency at the lowest cost.”

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PEAK:AIO adds power, density to AI storage server

There is also the fact that many people working with AI are not IT professionals, such as professors, biochemists, scientists, doctors, clinicians, and they don’t have a traditional enterprise department or a data center. “It’s run by people that wouldn’t really know, nor want to know, what storage is,” he said. While the new AI Data Server is a Dell design, PEAK:AIO has worked with Lenovo, Supermicro, and HPE as well as Dell over the past four years, offering to convert their off the shelf storage servers into hyper fast, very AI-specific, cheap, specific storage servers that work with all the protocols at Nvidia, like NVLink, along with NFS and NVMe over Fabric. It also greatly increased storage capacity by going with 61TB drives from Solidigm. SSDs from the major server vendors typically maxed out at 15TB, according to the vendor. PEAK:AIO competes with VAST, WekaIO, NetApp, Pure Storage and many others in the growing AI workload storage arena. PEAK:AIO’s AI Data Server is available now.

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SoftBank to buy Ampere for $6.5B, fueling Arm-based server market competition

SoftBank’s announcement suggests Ampere will collaborate with other SBG companies, potentially creating a powerful ecosystem of Arm-based computing solutions. This collaboration could extend to SoftBank’s numerous portfolio companies, including Korean/Japanese web giant LY Corp, ByteDance (TikTok’s parent company), and various AI startups. If SoftBank successfully steers its portfolio companies toward Ampere processors, it could accelerate the shift away from x86 architecture in data centers worldwide. Questions remain about Arm’s server strategy The acquisition, however, raises questions about how SoftBank will balance its investments in both Arm and Ampere, given their potentially competing server CPU strategies. Arm’s recent move to design and sell its own server processors to Meta signaled a major strategic shift that already put it in direct competition with its own customers, including Qualcomm and Nvidia. “In technology licensing where an entity is both provider and competitor, boundaries are typically well-defined without special preferences beyond potential first-mover advantages,” Kawoosa explained. “Arm will likely continue making independent licensing decisions that serve its broader interests rather than favoring Ampere, as the company can’t risk alienating its established high-volume customers.” Industry analysts speculate that SoftBank might position Arm to focus on custom designs for hyperscale customers while allowing Ampere to dominate the market for more standardized server processors. Alternatively, the two companies could be merged or realigned to present a unified strategy against incumbents Intel and AMD. “While Arm currently dominates processor architecture, particularly for energy-efficient designs, the landscape isn’t static,” Kawoosa added. “The semiconductor industry is approaching a potential inflection point, and we may witness fundamental disruptions in the next 3-5 years — similar to how OpenAI transformed the AI landscape. SoftBank appears to be maximizing its Arm investments while preparing for this coming paradigm shift in processor architecture.”

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Nvidia, xAI and two energy giants join genAI infrastructure initiative

The new AIP members will “further strengthen the partnership’s technology leadership as the platform seeks to invest in new and expanded AI infrastructure. Nvidia will also continue in its role as a technical advisor to AIP, leveraging its expertise in accelerated computing and AI factories to inform the deployment of next-generation AI data center infrastructure,” the group’s statement said. “Additionally, GE Vernova and NextEra Energy have agreed to collaborate with AIP to accelerate the scaling of critical and diverse energy solutions for AI data centers. GE Vernova will also work with AIP and its partners on supply chain planning and in delivering innovative and high efficiency energy solutions.” The group claimed, without offering any specifics, that it “has attracted significant capital and partner interest since its inception in September 2024, highlighting the growing demand for AI-ready data centers and power solutions.” The statement said the group will try to raise “$30 billion in capital from investors, asset owners, and corporations, which in turn will mobilize up to $100 billion in total investment potential when including debt financing.” Forrester’s Nguyen also noted that the influence of two of the new members — xAI, owned by Elon Musk, along with Nvidia — could easily help with fundraising. Musk “with his connections, he does not make small quiet moves,” Nguyen said. “As for Nvidia, they are the face of AI. Everything they do attracts attention.” Info-Tech’s Bickley said that the astronomical dollars involved in genAI investments is mind-boggling. And yet even more investment is needed — a lot more.

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IBM broadens access to Nvidia technology for enterprise AI

The IBM Storage Scale platform will support CAS and now will respond to queries using the extracted and augmented data, speeding up the communications between GPUs and storage using Nvidia BlueField-3 DPUs and Spectrum-X networking, IBM stated. The multimodal document data extraction workflow will also support Nvidia NeMo Retriever microservices. CAS will be embedded in the next update of IBM Fusion, which is planned for the second quarter of this year. Fusion simplifies the deployment and management of AI applications and works with Storage Scale, which will handle high-performance storage support for AI workloads, according to IBM. IBM Cloud instances with Nvidia GPUs In addition to the software news, IBM said its cloud customers can now use Nvidia H200 instances in the IBM Cloud environment. With increased memory bandwidth (1.4x higher than its predecessor) and capacity, the H200 Tensor Core can handle larger datasets, accelerating the training of large AI models and executing complex simulations, with high energy efficiency and low total cost of ownership, according to IBM. In addition, customers can use the power of the H200 to process large volumes of data in real time, enabling more accurate predictive analytics and data-driven decision-making, IBM stated. IBM Consulting capabilities with Nvidia Lastly, IBM Consulting is adding Nvidia Blueprint to its recently introduced AI Integration Service, which offers customers support for developing, building and running AI environments. Nvidia Blueprints offer a suite pre-validated, optimized, and documented reference architectures designed to simplify and accelerate the deployment of complex AI and data center infrastructure, according to Nvidia.  The IBM AI Integration service already supports a number of third-party systems, including Oracle, Salesforce, SAP and ServiceNow environments.

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Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs).  In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

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John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

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2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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