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OEUK launches the first set of guidelines for offshore wind turbine decommissioning

The process of decommissioning North Sea wind turbines has already started as the earliest installations reach the end of their operational life. By 2030, hundreds more will need to be removed. We have been decommissioning oil and gas installations in the North Sea for more than 20 years and the work is expected to go […]

The process of decommissioning North Sea wind turbines has already started as the earliest installations reach the end of their operational life.

By 2030, hundreds more will need to be removed.

We have been decommissioning oil and gas installations in the North Sea for more than 20 years and the work is expected to go on for another 50 years.

We have built up an unrivalled body of world-leading expertise in this technically demanding sector and made the processes as efficient as possible.

We have used this knowledge to produce two new sets of guidelines for wind turbine decommissioning.

The first covers technical and practical management of data, projects and teams, plus a deep dive into the regulatory framework around the processes involved.

The document highlights the vital lessons learnt from the oil and gas sector and provide recommendations on how to apply this knowledge to offshore wind.

The second set covers work breakdown structure (WBS), mirroring the process used in the decommissioning of oil and gas installations.

That means benchmarking costings and ensuring streamlined project management and decommissioning execution.

The Oil & Gas WBS is an integral tool used globally in decommissioning projects.

Providing an offshore wind decommissioning equivalent will be vital to the sector’s success within the decommissioning space.

Removal of offshore wind turbines is an expensive undertaking.

Ensuring workforce safety and protection of marine life; assessing the structure’s potential for flotation and appropriate evaluation of the weight of modules, are all major challenges at end-of-life operations, but the methods used by the oil and gas sector for cutting and transporting large steel components can be equally applied to the process.

Currently, offshore wind turbines don’t have the same longevity as oil and gas platforms and improving the process is something we will come back to time and again.

We do know that delaying decommissioning without a considered maintenance plan can greatly increase costs and introduce risks.

The composition of a wind turbine is predominantly steel, cast iron, and copper which along with their concrete bases, account for much of the total weight.

These materials can be recycled and sold, but the remaining 5% or more of the turbine’s weight resides in the electronics, lubricants, coolants and polymers in the blades.

Although there is a move to more recyclable methods of construction, these remain problematic.

Blades are mostly shredded and incinerated or sent to landfill.

Additionally, offshore wind farms have extensive subsea cable networks comprising conductors and various insulating and protective layers.

The conductor components are primarily made from copper and aluminium, both of which are easily recyclable.

However, the insulating and protective layers involve a more complicated recycling process, if they can even be recycled at all.

Some materials may have to be treated as hazardous waste, so using knowledge and experience from the petrochemicals industry is essential.

To ensure maximum value, the offshore wind sector is now integrating end of use considerations into project design.

Wind farms of the future will be created on the basis that their end-of-life phase will be as integral as operational requirements.

Developing these guidelines has been a two-year project with a working party made up of advisors from member companies but also engagement from other member firms across the energy sector including oil and gas operators and an extensive array of supply chain companies as well as wind turbine specialists from OEUK’s 400-plus member companies, four out of five of which are supply chain organisations.

We have tried to address the themes that are most relevant and most useful now.

Wind decommissioning is using the same supply chain, the same knowledge and the same geography to bring infrastructure into the same yards that are already engaged in decommissioning of oil and gas platforms.

These guidelines show what we’re trying to hand over.

They demonstrate we are doing what we said we’d do to in the North Sea Transition Deal, and that we’re running a just energy transition.

It is imperative we keep North Sea energy production as environmentally aware and as safe and sustainable as possible.

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Cisco unveils integrated edge platform for AI

Announced at Cisco’s Partner Summit, Unified Edge will likely be part of many third-party packages that can be configured in a variety of ways, Cisco stated. “The platform is customer definable. For example, if a customer has a workload and they’ve decided they want to use Nutanix, they can go

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Infoblox bolsters Universal DDI Platform with multi-cloud integrations

Universal DDI for Microsoft Management integration enables enterprises to gain control of their DNS and DHCP by centrally managing DNS and DHCP hosted on Microsoft server platforms. Integration with Google Cloud Internal Range applies consistent IPAM policies across Google Cloud, on-premises, and other cloud environments, which helps enterprise IT to

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Agentic AI: What now, what next?

Agentic AI burst onto the scene with its promises of streamliningoperations and accelerating productivity. But what’s real and what’s hype when it comes to deploying agentic AI? This Special Report examines the state of agentic AI, the challenges organizations are facing in deploying it, and the lessons learned from success

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SM Energy, Civitas Announce $13B ‘Transformational’ Combo

SM Energy Company and Civitas Resources Inc announced, in a joint statement released Monday, a “$12.8 billion transformational combination delivering superior stockholder value”. The companies noted in the statement that they have entered into a definitive merger agreement involving an all-stock transaction. Under the terms of the deal, each common share of Civitas will be exchanged for 1.45 shares of SM Energy common stock, the statement revealed, adding that the combined company’s enterprise value of approximately $12.8 billion is inclusive of each company’s net debt. After closing, the company will continue to trade as SM Energy, according to the statement, which noted that, upon completion of the transaction, SM Energy stockholders will own approximately 48 percent of the combined company and Civitas stockholders will own approximately 52 percent on a fully diluted basis. At this exchange ratio, and the respective companies’ closing share prices on October 31, 2025, inclusive of net debt, the combined company would have an enterprise value of approximately $12.8 billion, the statement noted. It highlighted that SM Energy will issue approximately 126.3 million shares of common stock as consideration to the holders of Civitas common shares in accordance with the terms of the merger agreement. “The combined company will have a premier portfolio of approximately 823,000 net acres, with the Permian position being the cornerstone,” the statement said. “Pro forma full-year 2025 consensus free cash flow generation of more than $1.4 billion enables sustained capital returns, and increased market capitalization enhances trading liquidity with broader investment appeal,” it added. The statement highlighted “identified and achievable annual synergies totaling $200 million, with upside potential to $300 million”. “Identified synergies include opportunities across the combined organization consisting of overhead and G&A, drilling and completion and operational costs, and cost of capital,” it added. “These synergies are expected to accelerate

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BP Sells Part of Permian, Eagle Ford Midstream Position

BP PLC announced Monday an agreement to farm down its stakes in midstream pipelines and facilities in the Permian basin and Eagle Ford play to Sixth Street for $1.5 billion. The assets – under bpx energy, BP’s onshore oil and gas business in the United States – include four Permian central processing facilities. Grand Slam, Bingo, Checkmate and Crossroads, which started operations in June, connect wells to third-party pipeline networks that carry oil and gas to customers. “Following completion of both transactions, bpx’s ownership interest in the Permian midstream assets will move to 51 percent (from 100 percent), while bpx’s ownership interest in the Eagle Ford midstream assets will move to 25 percent (from 75 percent)”, BP said in a press release. “Sixth Street will hold the remaining, non-operating interests”, while BP will remain operator, the British company said. Kyle Koontz, chief executive of bpx energy, said, “We recognized early on that investing in midstream would be an important ingredient to our success in these basins in terms of driving value, flow assurance and lowering emissions”. BP said it had paid $1 billion upon signing the transaction and will settle the remaining balance by yearend. “The effect on non-controlling interest reported in the income statement is projected to be in the range of $100-200 million per annum”, it said. In its quarterly report on Tuesday, BP said it expects to complete over $4 billion worth of asset sales in 2025, part of a $20-billion divestment target by 2027 under a “reset” plan it announced February. Last month BP penned an agreement to sell adjoining production and exploration assets on the United Kingdom’s side of the North Sea including the Culzean gas and condensate field to Serica Energy PLC for at least $232 million, as announced by Serica on October 13. The transaction consists

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North America Drops Rigs For 1st Time Since August

North America dropped 16 rigs week on week, according to Baker Hughes’ latest North America rotary rig count, which was published on October 31. The total U.S. rig count decreased by four week on week and the total Canada rig count dropped by 12 during the same period, taking the total North America rig count down to 733, comprising 546 rigs from the U.S. and 187 rigs from Canada, the count outlined. Of the total U.S. rig count of 546, 525 rigs are categorized as land rigs, 19 are categorized as offshore rigs, and two are categorized as inland water rigs. The total U.S. rig count is made up of 414 oil rigs, 125 gas rigs, and seven miscellaneous rigs, according to Baker Hughes’ count, which revealed that the U.S. total comprises 478 horizontal rigs, 57 directional rigs, and 11 vertical rigs. Week on week, the U.S. offshore and land rig counts each dropped by two, and its inland water rig count remained unchanged, Baker Hughes highlighted. The U.S. oil rig count dropped by six week on week, its miscellaneous rig count dropped by two, and its gas rig count rose by four, the count showed. The U.S. horizontal rig count dropped by seven week on week, while its vertical rig count dropped by one and its directional rig count increased by four, the count revealed. A major state variances subcategory included in the rig count showed that, week on week, Texas, Wyoming, and Colorado each dropped one rig and Louisiana, New Mexico, and North Dakota each added one rig. A major state variances subcategory included in the rig count showed that, week on week, the DJ-Niobrara and Haynesville basins each dropped one rig and the Barnett and Permian basins each added one rig. Canada’s total rig count of 187

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Crescent Posts $10MM Loss

Crescent Energy Co on Monday reported $9.51 million in company-attributed net loss (-$10.27 million including non-controlling stakes) for the third quarter, hit by a $73.53 million impairment of oil and gas properties. The Houston, Texas-based producer said in its quarterly report it has entered into agreements to divest over $800 million worth of non-core assets including the whole of its Barnett, conventional Rockies and Mid-Continent positions. Crescent expects to complete the transactions by yearend. “With these asset sales, Crescent has successfully executed its non-core divestiture program announced alongside the Vital Energy acquisition announcement, demonstrating the company’s commitment to continually evaluate opportunities to enhance the portfolio, simplify the business and deliver value for investors”, Crescent said. On August 25 it announced its $3.1-billion all-stock purchase of Vital Energy Inc. Expected to close this year, the combination will create a “top-10 independent”, the parties said. While Crescent’s net result was negative, adjusted net profit was $88.33 million, up from $81.97 million for the same three-month period last year as sales volumes increased. Realized prices fell for oil but rose for natural gas. Crescent’s adjusted earnings per share of $0.35 beat the Zacks Consensus Estimate of $0.3 per share. Q3 2025 net sales volumes averaged 253,000 barrels of oil equivalent per day (boepd), up from 219,000 boed in Q3 2024. That consisted of 103,000 bpd of oil, 631 million cubic feet a day of gas and 45,000 bpd of natural gas liquids – all up year-on-year. Revenue totaled $866.58 million, up from $744.87 million for Q3 2024. Income from operations came at $30.8 million, compared to -$7.42 million for Q3 2024. Operating cash flow was $204 million. Adjusted EBITDA landed at $486.54 million, up from $430.44 million for Q3 2024. So far in 2025 Crescent has completed around $33 million of its share repurchase

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Uniper Completes Sale of Ruhr District Heating Unit

Uniper SE said Monday it had completed the divestment of Uniper Waerme GmbH, a district heating network serving over 14,400 customers in Germany’s Ruhr area, to Steag Iqony Group’s Iqony Fernwaerme GmbH. Waerme is among the assets that the German power and gas utility agreed to sell to fulfill fair-competition guardrails imposed by the European Commission in approving Uniper’s bailout by the government in late 2022. Waerme has a network of over 750 kilometers (466.03 miles), according to Uniper. Waerme “is an expert in the efficient use of heat that is generated during electricity production in combined heat and power plants”, Uniper said in a press release. “In addition, they use a variety of other environmentally friendly alternatives for heat generation. This includes heat from mine gas, waste heat from industrial processes and heat generated in electric boilers and smaller decentralized CHP plants”. In the initial announcement of the transaction on August 4, Waerme managing director Nikola Feldmann said, “We are pleased to have found a buyer in the Steag Iqony Group that will continue on the path we have taken and be a reliable employer for our around 130 colleagues”. The companies did not disclose the transaction price. Earlier Uniper said it had signed an agreement to sell the Datteln IV coal-run power plant in North Rhine-Westphalia to ResInvest Group AS, toward the satisfaction of the bailout conditions. Commissioned 2020, the Datteln plant has a net output of 1,052 megawatts (MW). It supplies electricity and district heating to households, as well as traction power to rail operator Deutsche Bahn, according to Uniper. The over 100 employees at the site will transfer to Czechia’s ResInvest, Uniper said in an online statement September 19. The transaction is subject to regulatory approvals, it said. In July Uniper said it had sold its 18.26

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Aramco Q3 Profit Tops Estimates

Saudi Aramco posted a surprise increase in third-quarter profit as a production boost helped mitigate the impact of lower crude prices and helped the oil giant break a yearslong streak of falling earnings. Adjusted net income for the period rose about 1 percent to 104.9 billion riyals ($28 billion) from a year earlier, surpassing analyst estimates compiled by Bloomberg. Free cash flow exceeded the dividend payout for the first time in about two years, while net debt eased compared with three months ago.  The latest results follow a sequence of lower quarterly profit at Aramco over the past couple of years, and follow the firm’s move to raise output as part of an OPEC+ policy that’s helped it counter muted crude prices. The world’s biggest oil exporter is a lynchpin of the Saudi economy, with revenue from oil sales and hefty dividend payouts supporting the kingdom’s multitrilion-dollar economic rejig. Oil prices in London have declined 13 percent this year to about $65 a barrel, well below the more than $90 that the International Monetary Fund says Saudi Arabia needs to balance its budget. That’s translated into pullbacks in some major infrastructure and tourism projects in the kingdom, while Aramco has also slowed some domestic refining and chemical plans as it focuses on a mega natural gas development. Aramco sold its oil at about $70 a barrel in the third quarter, compared with nearly $79 a year earlier. But liquids production increased 3.8 percent to 10.8 million barrels a day, while natural gas output rose 5 percent. The company’s “ability to quickly ramp-up production and capture rising demand drove our strong third quarter performance,” Chief Financial Officer Ziad Al-Murshed said in the statement.  Aramco’s free cash flow – funds left over from operations after accounting for investments and expenses – rose to $23.6 billion in the quarter. That

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OpenAI spends even more money it doesn’t have

The aim, said Gogia, “is continuity, not cost efficiency. These deals are forward leaning, relying on revenue forecasts that remain speculative. In that context, OpenAI must continue to draw heavily on outside capital, whether through venture rounds, debt, or a future public offering.” He pointed out, “the company’s recent legal and corporate restructuring was designed to open the doors to that capital. Removing Microsoft’s exclusivity makes room for more vendors but also signals that no one provider can meet OpenAI’s demands. In several cases, suppliers are stepping in with financing arrangements that link product sales to future performance. While these strategies help close funding gaps, they introduce fragility. What looks like revenue is often pre-paid consumption, not realized margin.” Execution risks, he said, add to the concern. “Building and energizing enough data centers to meet OpenAI’s projected needs is not a function of ambition alone. It requires grid access, cooling capacity, and regional stability. Microsoft has acknowledged that it lacks the power infrastructure to fully deploy the GPUs it owns. Without physical readiness, all of these agreements sit on shaky ground.” Lots of equity swapping going on Scott Bickley, advisory fellow at Info-Tech Research Group, said he has not only been astounded by the funding announcements over the last few months, but is also appalled, primarily, he said, “because of the disconnect to what this does to the underlying technology stocks and their market prices versus where the technology is at from a development and ROI perspective … and from a boots on the ground perspective.” He added that while the financial pledges involve “huge, staggering numbers, most of them are tied up in ways that are not necessarily going to require all the cash to come from OpenAI. In a lot of cases, there is equity swapping. You have

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Verizon to build high-capacity fiber network to link AWS AI data centers

“AI will be essential to the future of business and society, driving innovation that demands a network to match,” Scott Lawrence, senior vice president and chief product officer at Verizon Business said in a statement. “This deal with Amazon demonstrates our continued commitment to meet the growing demands of AI workloads for the businesses and developers building our future.” This is not the first time that two companies have partnered. Verizon has previously adopted AWS as a preferred public cloud provider for its digital transformation efforts. The collaboration also extends to joint development of private mobile edge computing solutions, delivering secure, dedicated connectivity for enterprise customers. These efforts have been targeted at industries such as manufacturing, healthcare, retail, and entertainment.

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Supermicro Unveils Data Center Building Blocks to Accelerate AI Factory Deployment

Supermicro has introduced a new business line, Data Center Building Block Solutions (DCBBS), expanding its modular approach to data center development. The offering packages servers, storage, liquid-cooling infrastructure, networking, power shelves and battery backup units (BBUs), DCIM and automation software, and on-site services into pre-validated, factory-tested bundles designed to accelerate time-to-online (TTO) and improve long-term serviceability. This move represents a significant step beyond traditional rack integration; a shift toward a one-stop, data-center-scale platform aimed squarely at the hyperscale and AI factory market. By providing a single point of accountability across IT, power, and thermal domains, Supermicro’s model enables faster deployments and reduces integration risk—the modern equivalent of a “single throat to choke” for data center operators racing to bring GB200/NVL72-class racks online. What’s New in DCBBS DCBBS extends Supermicro’s modular design philosophy to an integrated catalog of facility-adjacent building blocks, not just IT nodes. By including critical supporting infrastructure—cooling, power, networking, and lifecycle software—the platform helps operators bring new capacity online more quickly and predictably. According to Supermicro, DCBBS encompasses: Multi-vendor AI system support: Compatibility with NVIDIA, AMD, and Intel architectures, featuring Supermicro-designed cold plates that dissipate up to 98% of component-level heat. In-rack liquid-cooling designs: Coolant distribution manifolds (CDMs) and CDUs rated up to 250 kW, supporting 45 °C liquids, alongside rear-door heat exchangers, 800 GbE switches (51.2 Tb/s), 33 kW power shelves, and 48 V battery backup units. Liquid-to-Air (L2A) sidecars: Each row can reject up to 200 kW of heat without modifying existing building hydronics—an especially practical design for air-to-liquid retrofits. Automation and management software: SuperCloud Composer for rack-scale and liquid-cooling lifecycle management SuperCloud Automation Center for firmware, OS, Kubernetes, and AI pipeline enablement Developer Experience Console for self-service workflows and orchestration End-to-end services: Design, validation, and on-site deployment options—including four-hour response service levels—for both greenfield builds

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Investments Anchor Vertiv’s Growth Strategy as AI-Driven Data Center Orders Surge 60% YoY

New Acquisitions and Partner Awards Vertiv’s third-quarter financial performance was underscored by a series of strategic acquisitions and ecosystem recognitions that expand the company’s technological capabilities and market reach amid AI-driven demand. Acquisition of Waylay NV: AI and Hyperautomation for Infrastructure Intelligence On August 26, Vertiv announced its acquisition of Waylay NV, a Belgium-based developer of generative AI and hyperautomation software. The move bolsters Vertiv’s portfolio with AI-driven monitoring, predictive services, and performance optimization for digital infrastructure. Waylay’s automation platform integrates real-time analytics, orchestration, and workflow automation across diverse connected assets and cloud services—enabling predictive maintenance, uptime optimization, and energy management across power and cooling systems. “With the addition of Waylay’s technology and software-focused team, Vertiv will accelerate its vision of intelligent infrastructure—data-driven, proactive, and optimized for the world’s most demanding environments,” said CEO Giordano Albertazzi. Completion of Great Lakes Acquisition: Expanding White Space Integration Just days earlier, as alluded to above, Vertiv finalized its $200 million acquisition of Great Lakes Data Racks & Cabinets, a U.S.-based manufacturer of enclosures and integrated rack systems. The addition expands Vertiv’s capabilities in high-density, factory-integrated white space solutions; bridging power, cooling, and IT enclosures for hyperscale and edge data centers alike. Great Lakes’ U.S. and European manufacturing footprint complements Vertiv’s global reach, supporting faster deployment cycles and expanded configuration flexibility.  Albertazzi noted that the acquisition “enhances our ability to deliver comprehensive infrastructure solutions, furthering Vertiv’s capabilities to customize at scale and configure at speed for AI and high-density computing environments.” 2024 Partner Awards: Recognizing the Ecosystem Behind Growth Vertiv also spotlighted its partner ecosystem in August with its 2024 North America Partner Awards. The company recognized 11 partners for 2024 performance, growth, and AI execution across segments: Partner of the Year – SHI for launching a customer-facing high-density AI & Cyber Labs featuring

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QuEra’s Quantum Leap: From Neutral-Atom Breakthroughs to Hybrid HPC Integration

The race to make quantum computing practical – and commercially consequential – took a major step forward this fall, as Boston-based QuEra Computing announced new research milestones, expanded strategic funding, and an accelerating roadmap for hybrid quantum-classical supercomputing. QuEra’s Chief Commercial Officer Yuval Boger joined the Data Center Frontier Show to discuss how neutral-atom quantum systems are moving from research labs into high-performance computing centers and cloud environments worldwide. NVIDIA Joins Google in Backing QuEra’s $230 Million Round In early September, QuEra disclosed that NVentures, NVIDIA’s venture arm, has joined Google and others in expanding its $230 million Series B round. The investment deepens what has already been one of the most active collaborations between quantum and accelerated-computing companies. “We already work with NVIDIA, pairing our scalable neutral-atom architecture with its accelerated-computing stack to speed the arrival of useful, fault-tolerant quantum machines,” said QuEra CEO Andy Ory. “The decision to invest in us underscores our shared belief that hybrid quantum-classical systems will unlock meaningful value for customers sooner than many expect.” The partnership spans hardware, software, and go-to-market initiatives. QuEra’s neutral-atom machines are being integrated into NVIDIA’s CUDA-Q software platform for hybrid workloads, while the two companies collaborate at the NVIDIA Accelerated Quantum Center (NVAQC) in Boston, linking QuEra hardware with NVIDIA’s GB200 NVL72 GPU clusters for simulation and quantum-error-decoder research. Meanwhile, at Japan’s AIST ABCI-Q supercomputing center, QuEra’s Gemini-class quantum computer now operates beside more than 2,000 H100 GPUs, serving as a national testbed for hybrid workflows. A jointly developed transformer-based decoder running on NVIDIA’s GPUs has already outperformed classical maximum-likelihood error-correction models, marking a concrete step toward practical fault-tolerant quantum computing. For NVIDIA, the move signals conviction that quantum processing units (QPUs) will one day complement GPUs inside large-scale data centers. For QuEra, it widens access to the

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How CoreWeave and Poolside Are Teaming Up in West Texas to Build the Next Generation of AI Data Centers

In the evolving landscape of artificial-intelligence infrastructure, a singular truth is emerging: access to cutting-edge silicon and massive GPU clusters is no longer enough by itself. For companies chasing the frontier of multi-trillion-parameter model training and agentic AI deployment, the bottleneck increasingly lies not just in compute, but in the seamless integration of compute + power + data center scale. The latest chapter in this story is the collaboration between CoreWeave and Poolside, culminating in the launch of Project Horizon, a 2-gigawatt AI-campus build in West Texas. Setting the Stage: Who’s Involved, and Why It Matters CoreWeave (NASDAQ: CRWV) has positioned itself as “The Essential Cloud for AI™” — a company founded in 2017, publicly listed in March 2025, and aggressively building out its footprint of ultra-high-performance infrastructure.  One of its strategic moves: in July 2025 CoreWeave struck a definitive agreement to acquire Core Scientific (NASDAQ: CORZ) in an all-stock transaction. Through that deal, CoreWeave gains grip over approximately 1.3 GW of gross power across Core Scientific’s nationwide data center footprint, plus more than 1 GW of expansion potential.  That acquisition underlines a broader trend: AI-specialist clouds are no longer renting space and power; they’re working to own or tightly control it. Poolside, founded in 2023, is a foundation-model company with an ambitious mission: building artificial general intelligence (AGI) and deploying enterprise-scale agents.  According to Poolside’s blog: “When people ask what it takes to build frontier AI … the focus is usually on the model … but that’s only half the story. The other half is infrastructure. If you don’t control your infrastructure, you don’t control your destiny—and you don’t have a shot at the frontier.”  Simply put: if you’re chasing multi-trillion-parameter models, you need both the compute horsepower and the power infrastructure; and ideally, tight vertical integration. Together, the

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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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