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Equinor Greenlights Johan Castberg Tieback

Equinor ASA and its partners have agreed to proceed with the first project to be connected to the Johan Castberg field. Johan Castberg started production in March as only the third development on Norway’s side of the Barents Sea, according to information on government website Norskpetroleum.no. The other two, Snøhvit and Goliat, came online 2007 […]

Equinor ASA and its partners have agreed to proceed with the first project to be connected to the Johan Castberg field.

Johan Castberg started production in March as only the third development on Norway’s side of the Barents Sea, according to information on government website Norskpetroleum.no. The other two, Snøhvit and Goliat, came online 2007 and 2016 respectively.

“Recoverable oil in the new subsea development [the Isflak discovery] is estimated at 46 million barrels, and start-up is planned as early as the fourth quarter of 2028”, the Norwegian primarily state-owned company said in an online statement.

Isflak, the first of several discoveries planned to be tied back to Johan Castberg, was discovered 2021. Its development is estimated to cost over NOK 4 billion, according to the statement.

“A rapid development is possible because we can copy standardized solutions from Johan Castberg. The reservoir is in the same license and is similar to the discoveries we have developed previously, which means that we can copy equipment and well solutions. Johan Castberg has been developed as a future hub in the area”, said Equinor senior vice president for project development Trond Bokn.

Equinor said, “The development solution for the Isflak discovery consists of two wells in a new subsea template tied back to existing subsea facilities via pipelines and umbilicals, and all new infrastructure is located within the current Johan Castberg license”.

“Equinor has therefore applied to the Ministry of Energy for confirmation that Equinor has fulfilled the impact assessment obligation and exemption from the requirement for a plan for development and operation”, it said. “Global combustion emissions have been assessed in line with new practice”.

Johan Castberg has raised Norway’s production capacity by up to 220,000 barrels per day, with estimated recoverable volumes of 450-650 million barrels, according to Equinor.

The approved development plan consists of the Skrugard, Havis and Drivis discoveries, proven between 2011 and 2013, according to Norskpetroleum.no.

On June 30, 2025, Equinor announced a new discovery in Johan Castberg. It put preliminary estimates for Drivis Tubåen, or well 7720/7-DD-1H, at 9-15 million barrels of oil. Equinor said then it would evaluate a potential tieback to existing infrastructure at Johan Castberg.

Drivis Tubåen is the 14th exploration well drilled in production license 532, awarded 2009, according to the Norwegian Offshore Directorate. Equinor operates the license with a 46.3 percent stake. Eni SpA-backed Var Energi ASA owns 30 percent. Norway’s state-owned Petoro AS has 23.7 percent.

“We see opportunities to add 250-550 million new recoverable barrels that can be developed and produced over Johan Castberg. The partnership is already planning six new wells for improved oil recovery, and we will explore more in the area”, Grete Birgitte Haaland, Equinor senior vice president for exploration and production North, said in the statement announcing the final investment decision for Isflak.

“Equinor’s ambition is to maintain the production level on the NCS [Norwegian continental shelf] from 2020 until 2035, although production from the current fields will decline”, Haaland noted. “A significant part will come from new wells and projects.

“We are planning about 75 subsea developments in the next few years, and this project is a good example of how this can be done efficiently working closely with license partners and authorities”.

Equinor said in the statement, “The Norwegian continental shelf is changing. Many of the developments in the future are smaller discoveries that can quickly be tied back to existing infrastructure and larger fields”.

“Costs and environmental footprints can thus be reduced, value creation and jobs can be extended and Norway’s role as a reliable and long-term energy supplier can be maintained”, Equinor added.

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Equinor Greenlights Johan Castberg Tieback

Equinor ASA and its partners have agreed to proceed with the first project to be connected to the Johan Castberg field. Johan Castberg started production in March as only the third development on Norway’s side of the Barents Sea, according to information on government website Norskpetroleum.no. The other two, Snøhvit and Goliat, came online 2007 and 2016 respectively. “Recoverable oil in the new subsea development [the Isflak discovery] is estimated at 46 million barrels, and start-up is planned as early as the fourth quarter of 2028”, the Norwegian primarily state-owned company said in an online statement. Isflak, the first of several discoveries planned to be tied back to Johan Castberg, was discovered 2021. Its development is estimated to cost over NOK 4 billion, according to the statement. “A rapid development is possible because we can copy standardized solutions from Johan Castberg. The reservoir is in the same license and is similar to the discoveries we have developed previously, which means that we can copy equipment and well solutions. Johan Castberg has been developed as a future hub in the area”, said Equinor senior vice president for project development Trond Bokn. Equinor said, “The development solution for the Isflak discovery consists of two wells in a new subsea template tied back to existing subsea facilities via pipelines and umbilicals, and all new infrastructure is located within the current Johan Castberg license”. “Equinor has therefore applied to the Ministry of Energy for confirmation that Equinor has fulfilled the impact assessment obligation and exemption from the requirement for a plan for development and operation”, it said. “Global combustion emissions have been assessed in line with new practice”. Johan Castberg has raised Norway’s production capacity by up to 220,000 barrels per day, with estimated recoverable volumes of 450-650 million barrels, according to Equinor. The

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TotalEnergies, Repsol, HitecVision Form UK North Sea Leader

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Eni Fires Up New Andalusia Solar Plant

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DCF Trends Summit 2025: AI for Good – How Operators, Vendors and Cooling Specialists See the Next Phase of AI Data Centers

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FinOps Foundation sharpens FOCUS to reduce cloud cost chaos

“The big change that’s really started to happen in late 2024 early 2025 is that the FinOps practice started to expand past the cloud,” Storment said. “A lot of organizations got really good at using FinOps to manage the value of cloud, and then their organizations went, ‘oh, hey, we’re living in this happily hybrid state now where we’ve got cloud, SaaS, data center. Can you also apply the FinOps practice to our SaaS? Or can you apply it to our Snowflake? Can you apply it to our data center?’” The FinOps Foundation’s community has grown to approximately 100,000 practitioners. The organization now includes major cloud vendors, hardware providers like Nvidia and AMD, data center operators and data cloud platforms like Snowflake and Databricks. Some 96 of the Fortune 100 now participate in FinOps Foundation programs. The practice itself has shifted in two directions. It has moved left into earlier architectural and design processes, becoming more proactive rather than reactive. It has also moved up organizationally, from director-level cloud management roles to SVP and COO positions managing converged technology portfolios spanning multiple infrastructure types. This expansion has driven the evolution of FOCUS beyond its original cloud billing focus. Enterprises are implementing FOCUS as an internal standard for chargeback reporting even when their providers don’t generate native FOCUS data. Some newer cloud providers, particularly those focused on AI infrastructure, are using the FOCUS specification to define their billing data structures from the ground up rather than retrofitting existing systems. The FOCUS 1.3 release reflects this maturation, addressing technical gaps that have emerged as organizations apply cost management practices across increasingly complex hybrid environments. FOCUS 1.3 exposes cost allocation logic for shared infrastructure The most significant technical enhancement in FOCUS 1.3 addresses a gap in how shared infrastructure costs are allocated and

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Aetherflux joins the race to launch orbital data centers by 2027

Enterprises will connect to and manage orbital workloads “the same way they manage cloud workloads today,” using optical links, the spokesperson added. The company’s approach is to “continuously launch new hardware and quickly integrate the latest architectures,” with older systems running lower-priority tasks to serve out the full useful lifetime of their high-end GPUs. The company declined to disclose pricing. Aetherflux plans to launch about 30 satellites at a time on SpaceX Falcon 9 rockets. Before the data center launch, the company will launch a power-beaming demonstration satellite in 2026 to test transmission of one kilowatt of energy from orbit to ground stations, using infrared lasers. Competition in the sector has intensified in recent months. In November, Starcloud launched its Starcloud-1 satellite carrying an Nvidia H100 GPU, which is 100 times more powerful than any previous GPU flown in space, according to the company, and demonstrated running Google’s Gemma AI model in orbit. In the same month, Google announced Project Suncatcher, with a 2027 demonstration mission planned. Analysts see limited near-term applications Despite the competitive activity, orbital data centers won’t replace terrestrial cloud regions for general hosting through 2030, said Ashish Banerjee, senior principal analyst at Gartner. Instead, they suit specific workloads, including meeting data sovereignty requirements for jurisdictionally complex scenarios, offering disaster recovery immune to terrestrial risks, and providing asynchronous high-performance computing, he said. “Orbital centers are ideal for high-compute, low-I/O batch jobs,” Banerjee said. “Think molecular folding simulations for pharma, massive Monte Carlo financial simulations, or training specific AI model weights. If the job takes 48 hours, the 500ms latency penalty of LEO is irrelevant.” One immediate application involves processing satellite-generated data in orbit, he said. Earth observation satellites using synthetic aperture radar generate roughly 10 gigabytes per second, but limited downlink bandwidth creates bottlenecks. Processing data in

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Here’s what Oracle’s soaring infrastructure spend could mean for enterprises

He said he had earlier told analysts in a separate call that margins for AI workloads in these data centers would be in the 30% to 40% range over the life of a customer contract. Kehring reassured that there would be demand for the data centers when they were completed, pointing to Oracle’s increasing remaining performance obligations, or services contracted but not yet delivered, up $68 billion on the previous quarter, saying that Oracle has been seeing unprecedented demand for AI workloads driven by the likes of Meta and Nvidia. Rising debt and margin risks raise flags for CIOs For analysts, though, the swelling debt load is hard to dismiss, even with Oracle’s attempts to de-risk its spend and squeeze more efficiency out of its buildouts. Gogia sees Oracle already under pressure, with the financial ecosystem around the company pricing the risk — one of the largest debts in corporate history, crossing $100 billion even before the capex spend this quarter — evident in the rising cost of insuring the debt and the shift in credit outlook. “The combination of heavy capex, negative free cash flow, increasing financing cost and long-dated revenue commitments forms a structural pressure that will invariably finds its way into the commercial posture of the vendor,” Gogia said, hinting at an “eventual” increase in pricing of the company’s offerings. He was equally unconvinced by Magouyrk’s assurances about the margin profile of AI workloads as he believes that AI infrastructure, particularly GPU-heavy clusters, delivers significantly lower margins in the early years because utilisation takes time to ramp.

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New Nvidia software gives data centers deeper visibility into GPU thermals and reliability

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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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