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Why fuel cells are redefining on site power for data centers

Access to power is now the defining factor for data center development, eclipsing traditional site selection considerations, such as proximity to fiber networks. As artificial intelligence drives explosive growth in compute demand, developers face a stark reality: without immediate, reliable power, schedules can stall, costs rise and relationships with both communities and customers are put […]

Access to power is now the defining factor for data center development, eclipsing traditional site selection considerations, such as proximity to fiber networks. As artificial intelligence drives explosive growth in compute demand, developers face a stark reality: without immediate, reliable power, schedules can stall, costs rise and relationships with both communities and customers are put at risk.

The scale of AI workloads magnifies the challenge. In major data center hubs, power demand is expected to more than double from 175 MW today to 375 MW by 2035. For technology companies, this shift has turned onsite generation from a backup measure into a primary source of power for operations and critical infrastructure. 

Yet, onsite legacy technologies that have long supplied power are showing their limits. Gas turbines and reciprocating engines bring noise, carbon emissions, significant water consumption and slow permitting timelines – liabilities in an industry where speed, scale and sustainability now define competitiveness. 

High-temperature solid oxide fuel cells (SOFCs), once overlooked as a niche solution, are changing the equation. With proven deployments across data centers and the ability to deliver power at the scale, speed and reliability AI demands, fuel cells have become the onsite power solution of choice for today’s digital infrastructure leaders.

Fuel Cells: A Solution Fit for the Digital Era

Fuel cells offer a strategic infrastructure choice for modern data centers, providing a fundamentally different approach to onsite power. Fuel cells convert natural gas directly into electricity without combustion, achieving 15% to 20% higher efficiency than most open-cycle gas turbines or reciprocating engines. 

In their recent white paper, “Fuel Cells: A Technology Whose Time Has Come,” KR Sridhar and Peter Gross of Bloom Energy explained that this efficiency reduces fuel consumption. “The capital cost advantages over gas turbines and engines grow even stronger if customers require higher availability,” they said.

The technology is also firmly established in the market. With more than 1.5 GW of Bloom Energy fuel cells deployed across over 1,200 sites globally, including hundreds of megawatts powering data centers, fuel cells have moved beyond niche applications into mainstream, mission-critical use. Their proven reliability demonstrates that they can meet the uptime expectations of high-performance computing environments while providing operational resilience.

Speed, Scalability and AI Compatibility

In the digital era, speed to power is critical. Every delay in bringing data center infrastructure online means idle GPUs and lost revenue. Today, Bloom Energy can deliver 50 MW of fuel cells in as little as 90 and 100 MW in 120 days if gas supply and permits are in place. This rapid deployment enables operators to align power availability with aggressive project timelines.

Scalability is built into fuel cell design. Modular, “copy-and-paste” architecture allows capacity to grow incrementally with compute demand. Operators can expand power without risking stranded assets and can scale precisely as workloads increase.

Fuel cells are also suited to support volatile AI workloads, which can drive load swings between 20% and 150% in milliseconds, often multiple times per minute. Fuel cells follow the demand changes instantly, unlike turbines or engines, which require large battery arrays to manage variable loads. 

“As solid state devices with no spinning components or mechanical lag, [fuel cells] respond at least twice as fast as rotating generators when stepping up, and instantly when stepping down. When combined with supercapacitors, they reach 100% in milliseconds,” Sridhar and Gross explained. This responsiveness ensures consistent performance without the complexity and cost of extensive energy storage.

Reliability and community alignment

Fuel cells provide a reliable source of power even during extreme conditions. By connecting directly to the resilient natural gas grid, they maintain uptime during outages on the electric grid and can support continuous operation through hurricanes, floods, wildfires and earthquakes. Millions of operating hours demonstrate their proven performance in diverse environments.

Reliability is further enhanced by a fuel cell system’s modular design and built-in redundancy, which eliminates the need for diesel backup. 

“With no moving parts, fuel cells face fewer mechanical failures. When maintenance is needed, modules as small as 65 kW can be hot-swapped without shutting down the entire system,” ensuring stable operation over long periods, according to Sridhar and Gross.

Fuel cells also align with community priorities. They operate nearly silently, reduce emissions and preserve land compared with traditional onsite generation. By avoiding the need for costly grid upgrades, they protect ratepayers from price increases. In some cases, fuel cells can even make data centers grid-supporting assets, contributing positively to the local energy ecosystem.

Securing the Future of AI-Driven Data Centers

Power availability is the defining constraint for modern data centers, particularly those supporting AI workloads. Fuel cells remove that constraint by providing clean, scalable, fast-to-deploy and resilient onsite power. Operators who adopt fuel cells today can ensure uptime, reduce operational costs and position themselves to meet the evolving demands of the digital economy.

Bloom Energy’s SOFC Energy Server® power systems can be deployed behind or in front of the meter in multiple configurations and contracting models. For operators seeking a solution that aligns technical, economic and community objectives, fuel cells represent a strategic choice. To learn more, download “Fuel Cells: A Technology Whose Time Has Come.”

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Anthropic signs billion-dollar deal with Google Cloud

US-based AI company Anthropic has signed a major deal with Google Cloud that is said to be worth tens of billions of dollars. As part of the deal, Anthropic will have access to up to one million of Google’s purpose-built Tensor Processing Unit (TPU) AI accelerators. “Anthropic and Google have

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Oil Glut Enabled Tougher Sanctions, JPM Says

In a report sent to Rigzone on Friday by Natasha Kaneva, head of global commodities strategy at J.P. Morgan, analysts at the company, including Kaneva, highlighted that the “oil glut enable[d]… tougher sanctions”. “WTI [West Texas Intermediate] prices falling into the $50s created an opportunity for the Trump administration to step up economic measures against Russia and pursue a more assertive approach to sanctions,” the J.P. Morgan analysts said in the report. “Mirroring last week’s action by the UK, the U.S. announced on Wednesday sanctions against Russia’s largest oil producers, blacklisting state-run Rosneft and privately held Lukoil, as well as their subsidiaries,” they added. “Until now, the U.S. has refrained from sanctioning Russia’s leading oil producers, viewing it as a ‘nuclear option’ due to concerns that their size could trigger a spike in oil prices and destabilize global energy markets,” they continued. In the report, the J.P. Morgan analysts noted that flows at risk are material. “Together, these two companies account for nearly half of Russia’s crude production and a similar share of its exports,” they said. “With Wednesday’s announcement, all four of Russia’s largest oil companies – Rosneft, Lukoil, Gazprom Neft, and Surgutneftegas – are now subject to U.S. curbs, following earlier measures imposed on Gazprom Neft and Surgutneftegas by the Biden administration in January,” they added. “In effect, 70 percent of Russia’s 2024 production and exports are now under sanctions. Transactions involving Rosneft and Lukoil must be wound down by November 21. In a coordinated move, the EU also unveiled its 19th package of sanctions, further targeting Russia’s energy revenues,” they continued. The analysts went on to state in the report that the effectiveness of these measures will depend on three key factors, “how well they are enforced; the response of major players in India and China; and

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Tenaris Bags Pipe Contract for Trion Field offshore Mexico

Woodside Energy Group Ltd has awarded Tenaris SA a contract for the supply of casing and tubing for the Trion oilfield in Mexican waters. “Tenaris will also provide line pipe and coatings for bends, flowlines and risers as part of the project’s subsea infrastructure”, the Luxembourg-headquartered industrial and energy pipe contractor said in a press release. “Under the Rig Direct® service model, Tenaris will supply 12,000 tons of casing and tubing, including 1,600 tons in the Super 13 Chrome steel grade”, Tenaris said. “For the line pipe portion, Tenaris will deliver approximately 16,000 tons of pipe for flowlines and risers, including the application of TenarisShawcor Marine 5-Layer Syntactic and Solid Polypropylene for flow assurance, and TenarisShawcor Fusion Bonded Epoxy, Three-Layer Polypropylene, and Liquid Epoxy coatings for corrosion protection. Line pipe and coatings will be supplied along with One Line® project solutions”. Pablo Gomez, Tenaris commercial vice president in Mexico, said, “This project underscores the strength of our customer partnerships and our ability to deliver advanced technological solutions for the most demanding offshore environments”. Woodside expects Trion to start producing 2028, targeting overseas markets. The Australian company, which operates the project with a 60 percent stake, announced the final investment decision (FID) on Trion in 2023. Also that year Woodside received approval from Mexico’s National Hydrocarbons Commission and secured an agreement with 40 percent partner Petroleos Mexicanos, which discovered Trion 2012, to inject $7.2 billion in capital. “Following the approval of the FDP [field development plan], Woodside has booked proved (1P) undeveloped reserves of 324.7 MMboe gross (194.8 MMboe Woodside share) and proved plus probable (2P) undeveloped reserves of 478.7 MMboe gross (287.2 MMboe Woodside share)”, Woodside said in a statement August 30, 2023. The reserves will be tapped through a floating production unit (FPU) with an output capacity of 100,000 barrels

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OEUK Announces Awards Host

In a release sent to Rigzone recently, industry body Offshore Energies UK (OEUK) announced that television presenter and radio host Stephen Mulhern has been confirmed as the host of this year’s OEUK awards ceremony. The ceremony is scheduled to take place at the P&J Live in Aberdeen, Scotland, on November 20. In the release, OEUK said the awards “celebrate the people and companies driving progress across the UK’s offshore energy sector – including oil and gas, wind, hydrogen, and carbon capture and storage” and added that the event “will once again spotlight the industry’s brightest stars, with more than 120 nominations received this year”.  OEUK highlighted in the release that Mulhern is known for presenting “a range of iconic shows”, including Dancing On Ice, Deal Or No Deal, Britain’s Got More Talent, In For a Penny, Catchphrase, and You Bet. “He also fronted the hugely popular Ant vs Dec segment on Ant and Dec’s Saturday Night Takeaway,” OEUK said in the release. “Alongside his television work, Stephen is a regular voice on Virgin Radio, covering for Chris Evans and Graham Norton,” it added. “An accomplished all-round performer, he has toured the UK with his variety and magic shows, is a BAFTA award-winning magician, and co-creator and producer of P&O Cruises’ exclusive magic and illusion show Astonishing,” OEUK continued. In the release, OEUK CEO David Whitehouse said, “we’re delighted to have Stephen Mulhern join us to host this year’s OEUK Awards”. “His energy, warmth and talent for engaging audiences will make the evening a truly memorable celebration of the people driving our industry forward,” he added. “The awards are about recognizing the innovation, commitment and collaboration that underpin the UK’s offshore energy success – and Stephen’s presence will add an extra spark to what promises to be an inspiring night,” Whitehouse noted. The full list of finalists for OEUK’s awards ceremony can be seen below: Apprentice of the YearCallum Duncan,

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Baker Hughes Invests $10MM in Tamboran

Tamboran Resources Corp said Monday it had raised $52.5 million net from issuing nearly three million common shares on the New York Stock Exchange (NYSE), including $10 million from Baker Hughes Co. “The public offering was supported by cornerstone investors, including a $10 million investment from new strategic partner, Baker Hughes, a leading energy technology company”, the Sydney-based early-stage natural gas exploration and production company said in a filing with the Australian Securities Exchange (ASX). The placement had a public offering price of $21 per share. The volume at closing included nearly 350,000 shares bought by underwriters under an option in their underwriting agreement with Tamboran. According to a prospectus filing with the United States Securities and Exchange Commission last Friday, the underwriters were RBC Capital Markets LLC, Wells Fargo Securities LLC, BofA Securities Inc, Johnson Rice & Co LLC, PEP Advisory LLC, Piper Sandler & Co and Northland Securities Inc. Besides its share subscription, Baker Hughes also signed a “preferred services agreement” with Tamboran under which the Houston, Texas-based company will deliver oilfield services and efficiency improvements “in Tamboran’s initial development of the Beetaloo Basin”, Tamboran said. “This activity is limited to a pre-set number of wells in the basin with an expiration period of the later to occur of three years or 20 wells”, Tamboran said. “The strategic relationship with Baker Hughes is established to provide industry-leading oilfield services and to Tamboran’s Beetaloo Basin operations, including drilling and completion fluids, drilling services, well design and construction, wireline services, cementing and completions intervention to improve well delivery and economics in the upcoming drilling and completions program”. Tamboran added, “Concurrently with the closing of the public offering, Tamboran entered into subscription agreements with certain investors with expected gross proceeds of up to $29.3 million in a PIPE [Private Investment in Public Equity],

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6 ways batteries provide a lifeline for customers in an outage

More than 2.5 million Americans depend on durable medical equipment, such as oxygen delivery systems, ventilators, and dialysis machines. For these vulnerable customers, even brief power interruptions can cause their equipment to malfunction, and longer outages can be life-threatening, if power isn’t restored quickly. Yet the U.S. power grid is aging and under increasing pressure, struggling to keep up with rising electricity demand and extreme weather events. As a result, power outages are becoming more frequent and severe. The Department of Energy warns that blackouts could increase 100-fold by 2030 and recent studies show the severity of outages has grown 20% annually since 2019. Battery storage systems give medically vulnerable customers reliable backup power when the grid fails, automatically activating within a few seconds to keep critical medical devices running. By providing this layer of energy resilience, batteries protect those most at risk while helping utilities enhance reliability and equity for medically dependent and underserved communities. What are the challenges facing the grid? Large portions of the U.S. grid were built decades ago and are now due for modernization, says Baalaji Dhanabalan, Vice President overseeing the Energy Resiliency Portfolio at Resource Innovations. Aging equipment from transformers to substations requires greater upkeep and investment to maintain reliability, he adds. This is compounded by the rise in extreme weather events and the growing demand for power driven by widespread electrification. As a result, utilities are increasingly concerned about how to keep the grid reliable, affordable and resilient, notes Dhanabalan. To meet these challenges, many are investing in grid modernization and resiliency programs that include distributed energy resources, such as home batteries and solar panels, as well as demand response programs that encourage customers to reduce or shift their electricity use during times of peak demand. These programs aim to lower electricity demand

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Why fuel cells are redefining on site power for data centers

Access to power is now the defining factor for data center development, eclipsing traditional site selection considerations, such as proximity to fiber networks. As artificial intelligence drives explosive growth in compute demand, developers face a stark reality: without immediate, reliable power, schedules can stall, costs rise and relationships with both communities and customers are put at risk. The scale of AI workloads magnifies the challenge. In major data center hubs, power demand is expected to more than double from 175 MW today to 375 MW by 2035. For technology companies, this shift has turned onsite generation from a backup measure into a primary source of power for operations and critical infrastructure.  Yet, onsite legacy technologies that have long supplied power are showing their limits. Gas turbines and reciprocating engines bring noise, carbon emissions, significant water consumption and slow permitting timelines – liabilities in an industry where speed, scale and sustainability now define competitiveness.  High-temperature solid oxide fuel cells (SOFCs), once overlooked as a niche solution, are changing the equation. With proven deployments across data centers and the ability to deliver power at the scale, speed and reliability AI demands, fuel cells have become the onsite power solution of choice for today’s digital infrastructure leaders. Fuel Cells: A Solution Fit for the Digital Era Fuel cells offer a strategic infrastructure choice for modern data centers, providing a fundamentally different approach to onsite power. Fuel cells convert natural gas directly into electricity without combustion, achieving 15% to 20% higher efficiency than most open-cycle gas turbines or reciprocating engines.  In their recent white paper, “Fuel Cells: A Technology Whose Time Has Come,” KR Sridhar and Peter Gross of Bloom Energy explained that this efficiency reduces fuel consumption. “The capital cost advantages over gas turbines and engines grow even stronger if customers require higher

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Intel sees supply shortage, will prioritize data center technology

“Capacity constraints, especially on Intel 10 and Intel 7 [Intel’s semiconductor manufacturing process], limited our ability to fully meet demand in Q3 for both data center and client products,” said Zinsner, adding that Intel isn’t about to add capacity to Intel 10 and 7 when it has moved beyond those nodes. “Given the current tight capacity environment, which we expect to persist into 2026, we are working closely with customers to maximize our available output, including adjusting pricing and mix to shift demand towards products where we have supply and they have demand,” said Zinsner. For that reason, Zinzner projects that the fourth quarter will be roughly flat versus the third quarter in terms of revenue. “We expect Intel products up modestly sequentially but below customer demand as we continue to navigate supply environment,” said Zinsner. “We expect CCG to be down modestly and PC AI to be up strongly sequentially as we prioritize wafer capacity for server shipments over entry-level client parts.”

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How to set up an AI data center in 90 days

“Personally, I think that a brownfield is very creative way to deal with what I think is the biggest problem that we’ve got right now, which is time and speed to market,” he said. “On a brownfield, I can go into a building that’s already got power coming into the building. Sometimes they’ve already got chiller plants, like what we’ve got with the building I’m in right now.” Patmos certainly made the most of the liquid facilities in the old printing press building. The facility is built to handle anywhere from 50 to over 140 kilowatts per cabinet, a leap far beyond the 1–2 kW densities typical of legacy data centers. The chips used in the servers are Nvidia’s Grace Blackwell processors, which run extraordinarily hot. To manage this heat load, Patmos employs a multi-loop liquid cooling system. The design separates water sources into distinct, closed loops, each serving a specific function and ensuring that municipal water never directly contacts sensitive IT equipment. “We have five different, completely separated water loops in this building,” said Morgan. “The cooling tower uses city water for evaporation, but that water never mixes with the closed loops serving the data hall. Everything is designed to maximize efficiency and protect the hardware.” The building taps into Kansas City’s district chilled water supply, which is sourced from a nearby utility plant. This provides the primary cooling resource for the facility. Inside the data center, a dedicated loop circulates a specialized glycol-based fluid, filtered to extremely low micron levels and formulated to be electronically safe. Heat exchangers transfer heat from the data hall fluid to the district chilled water, keeping the two fluids separate and preventing corrosion or contamination. Liquid-to-chip and rear-door heat exchangers are used for immediate heat removal.

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INNIO and VoltaGrid: Landmark 2.3 GW Modular Power Deal Signals New Phase for AI Data Centers

Why This Project Marks a Landmark Shift The deployment of 2.3 GW of modular generation represents utility-scale capacity, but what makes it distinct is the delivery model. Instead of a centralized plant, the project uses modular gas-reciprocating “power packs” that can be phased in step with data-hall readiness. This approach allows staged energization and limits the bottlenecks that often stall AI campuses as they outgrow grid timelines or wait in interconnection queues. AI training loads fluctuate sharply, placing exceptional stress on grid stability and voltage quality. The INNIO/VoltaGrid platform was engineered specifically for these GPU-driven dynamics, emphasizing high transient performance (rapid load acceptance) and grid-grade power quality, all without dependence on batteries. Each power pack is also designed for maximum permitting efficiency and sustainability. Compared with diesel generation, modern gas-reciprocating systems materially reduce both criteria pollutants and CO₂ emissions. VoltaGrid markets the configuration as near-zero criteria air emissions and hydrogen-ready, extending allowable runtimes under air permits and making “prime-as-a-service” viable even in constrained or non-attainment markets. 2025: Momentum for Modular Prime Power INNIO has spent 2025 positioning its Jenbacher platform as a next-generation power solution for data centers: combining fast start, high transient performance, and lower emissions compared with diesel. While the 3 MW J620 fast-start lineage dates back to 2019, this year the company sharpened its data center narrative and booked grid stability and peaking projects in markets where rapid data center growth is stressing local grids. This momentum was exemplified by an 80 MW deployment in Indonesia announced earlier in October. The same year saw surging AI-driven demand and INNIO’s growing push into North American data-center markets. Specifications for the 2.3 GW VoltaGrid package highlight the platform’s heat tolerance, efficiency, and transient response, all key attributes for powering modern AI campuses. VoltaGrid’s 2025 Milestones VoltaGrid’s announcements across 2025 reflect

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Inside Google’s multi-architecture revolution: Axion Arm joins x86 in production clusters

Matt Kimball, VP and principal analyst with Moor Insights and Strategy, pointed out that AWS and Microsoft have already moved many workloads from x86 to internally designed Arm-based servers. He noted that, when Arm first hit the hyperscale datacenter market, the architecture was used to support more lightweight, cloud-native workloads with an interpretive layer where architectural affinity was “non-existent.” But now there’s much more focus on architecture, and compatibility issues “largely go away” as Arm servers support more and more workloads. “In parallel, we’ve seen CSPs expand their designs to support both scale out (cloud-native) and traditional scale up workloads effectively,” said Kimball. Simply put, CSPs are looking to monetize chip investments, and this migration signals that Google has found its performance-per-dollar (and likely performance-per-watt) better on Axion than x86. Google will likely continue to expand its Arm footprint as it evolves its Axion chip; as a reference point, Kimball pointed to AWS Graviton, which didn’t really support “scale up” performance until its v3 or v4 chip. Arm is coming to enterprise data centers too When looking at architectures, enterprise CIOs should ask themselves questions such as what instance do they use for cloud workloads, and what servers do they deploy in their data center, Kimball noted. “I think there is a lot less concern about putting my workloads on an Arm-based instance on Google Cloud, a little more hesitance to deploy those Arm servers in my datacenter,” he said. But ultimately, he said, “Arm is coming to the enterprise datacenter as a compute platform, and Nvidia will help usher this in.” Info-Tech’s Jain agreed that Nvidia is the “biggest cheerleader” for Arm-based architecture, and Arm is increasingly moving from niche and mobile use to general-purpose and AI workload execution.

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AMD Scales the AI Factory: 6 GW OpenAI Deal, Korean HBM Push, and Helios Debut

What 6 GW of GPUs Really Means The 6 GW of accelerator load envisioned under the OpenAI–AMD partnership will be distributed across multiple hyperscale AI factory campuses. If OpenAI begins with 1 GW of deployment in 2026, subsequent phases will likely be spread regionally to balance supply chains, latency zones, and power procurement risk. Importantly, this represents entirely new investment in both power infrastructure and GPU capacity. OpenAI and its partners have already outlined multi-GW ambitions under the broader Stargate program; this new initiative adds another major tranche to that roadmap. Designing for the AI Factory Era These upcoming facilities are being purpose-built for next-generation AI factories, where MI450-class clusters could drive rack densities exceeding 100 kW. That level of compute concentration makes advanced power and cooling architectures mandatory, not optional. Expected solutions include: Warm-water liquid cooling (manifold, rear-door, and CDU variants) as standard practice. Facility-scale water loops and heat-reuse systems—including potential district-heating partnerships where feasible. Medium-voltage distribution within buildings, emphasizing busway-first designs and expanded fault-current engineering. While AMD has not yet disclosed thermal design power (TDP) specifications for the MI450, a 1 GW campus target implies tens of thousands of accelerators. That scale assumes liquid cooling, ultra-dense racks, and minimal network latency footprints, pushing architectures decisively toward an “AI-first” orientation. Design considerations for these AI factories will likely include: Liquid-to-liquid cooling plants engineered for step-function capacity adders (200–400 MW blocks). Optics-friendly white space layouts with short-reach topologies, fiber raceways, and aisles optimized for module swaps. Substation adjacency and on-site generation envelopes negotiated during early land-banking phases. Networking, Memory, and Power Integration As compute density scales, networking and memory bottlenecks will define infrastructure design. Expect fat-tree and dragonfly network topologies, 800 G–1.6 T interconnects, and aggressive optical-module roadmaps to minimize collective-operation latency, aligning with recent disclosures from major networking vendors.

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Study Finds $4B in Data Center Grid Costs Shifted to Consumers Across PJM Region

In a new report spanning 2022 through 2024, the Union of Concerned Scientists (UCS) identifies a significant regulatory gap in the PJM Interconnection’s planning and rate-making process—one that allows most high-voltage (“transmission-level”) interconnection costs for large, especially AI-scale, data centers to be socialized across all utility customers. The result, UCS argues, is a multi-billion-dollar pass-through that is poised to grow as more data center projects move forward, because these assets are routinely classified as ordinary transmission infrastructure rather than customer-specific hookups. According to the report, between 2022 and 2024, utilities initiated more than 150 local transmission projects across seven PJM states specifically to serve data center connections. In 2024 alone, 130 projects were approved with total costs of approximately $4.36 billion. Virginia accounted for nearly half that total—just under $2 billion—followed by Ohio ($1.3 billion) and Pennsylvania ($492 million) in data-center-related interconnection spending. Yet only six of those 130 projects, about 5 percent, were reported as directly paid for by the requesting customer. The remaining 95 percent, representing more than $4 billion in 2024 connection costs, were rolled into general transmission charges and ultimately recovered from all retail ratepayers. How Does This Happen? When data center project costs are discussed, the focus is usually on the price of the power consumed, or megawatts multiplied by rate. What the UCS report isolates, however, is something different: the cost of physically delivering that power: the substations, transmission lines, and related infrastructure needed to connect hyperscale facilities to the grid. So why aren’t these substantial consumer-borne costs more visible? The report identifies several structural reasons for what effectively functions as a regulatory loophole in how development expenses are reported and allocated: Jurisdictional split. High-voltage facilities fall under the Federal Energy Regulatory Commission (FERC), while retail electricity rates are governed by state public utility

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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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