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Land & Expand: Texas’ AI Boom Meets a New Political Reality

Hut 8 Advances a Gigawatt-Scale Campus Near Corpus Christi Another significant development came November 4, when Hut 8 reported continued progress on its Beacon Point AI data center campus in the Corpus Christi region. The company said that its previously announced second 352 MW IT-capacity lease had fully commercialized the campus, bringing the total contracted […]

Hut 8 Advances a Gigawatt-Scale Campus Near Corpus Christi

Another significant development came November 4, when Hut 8 reported continued progress on its Beacon Point AI data center campus in the Corpus Christi region.

The company said that its previously announced second 352 MW IT-capacity lease had fully commercialized the campus, bringing the total contracted IT capacity associated with the two phases to 704 MW. The campus is designed around approximately 1 GW of utility capacity, a separate measure from the critical IT load under lease. Hut 8 estimates approximately $19.6 billion in base-term contract value across the two phases.

In its third-quarter results, the company said construction of the campus substation had begun, alongside foundation and underground utility work for the first phase. Initial data hall delivery is targeted for the third quarter of 2027, with the second phase targeted for the second quarter of 2028.

The company also disclosed agreements to acquire two energized sites in West Texas, with up to 230 MW of utility capacity at full energization, subject to outstanding approvals and infrastructure development. Those acquisitions point to another important trend: the increasing value of existing electrical infrastructure and sites that can potentially be adapted to serve advanced computing.

As new greenfield projects face lengthy power studies and regulatory requirements, already energized locations may offer an alternative route to capacity. The distinction is especially important in markets such as Dallas-Fort Worth, where DCF’s analysis of CBRE’s first-half 2026 data found that approximately 95% of the region’s 765 MW under construction had already been preleased.

PowerHouse and Big Watt Win Approval for Taylor Technology Campus

Not every large new project is meeting resistance at the municipal level. On October 8, the City of Taylor approved a development agreement with PowerHouse Data Centers and Big Watt Digital for the proposed Taylor Technology Campus northeast of Austin.

The 664-acre project is designed to support as much as 1 GW of data center capacity, incorporating dedicated behind-the-meter generation, including a planned natural gas power facility. The agreement represents an alternative to development on unincorporated land with comparatively limited local zoning oversight.

According to the City of Taylor’s project documentation, the agreement establishes a path for annexation and binding requirements addressing environmental and quality-of-life concerns.

That distinction is significant. The Taylor project illustrates how local government oversight and continued development can coexist, provided developers and municipalities reach agreement on applicable standards. It does not remove the need for other permits, financing, generation infrastructure, or construction milestones.

For PowerHouse, a division of American Real Estate Partners, the development also extends a large national pipeline of potential AI infrastructure sites.

As DCF recently examined in its coverage of Brookfield’s investment in AREP, the transaction reflects the growing strategic value of land development combined with access to electricity and the ability to navigate increasingly complex approvals.

Soluna and Applied Digital Pursue Wind-Connected AI Infrastructure

Another approach to securing electricity is emerging in the Texas Panhandle. On October 21, Soluna Holdings and Applied Digital announced an agreement to form a joint venture for a proposed 50 MW critical IT facility at Soluna’s Project Dorothy 3 site near Silverton in Briscoe County.

The development would be co-located with the 150 MW Briscoe Wind Farm, with its initial phase drawing electricity from both wind generation and the grid. Under the proposed ownership structure, Applied Digital would hold 51% of the venture and Soluna 49%, following closing. ChronoScale, a publicly traded accelerated-computing company majority-owned by Applied Digital, has signed a nonbinding letter of intent to lease the planned facility.

Importantly, the transaction is not yet fully closed. The companies’ October 21 announcement identifies several remaining conditions, including Briscoe County approval of a project tax abatement, definitive lease agreements, power arrangements, and corporate approvals.

That tax-abatement condition takes on added significance as state leaders debate the future of incentives for data center development.

The project illustrates the attraction of pairing AI infrastructure with existing energy assets, while its outstanding conditions also demonstrate how even promising developments depend on a sequence of commercial and regulatory approvals. It is part of the broader shift toward hybrid power strategies that DCF examined in its recent Power First report from the 2026 Data Center Frontier Trends Summit.

Fermi’s Proposed 222 MW Lease Misses Its Closing Deadline

The challenge of converting development plans into binding commercial commitments is especially visible in West Texas.

On November 3, Fermi America disclosed that its proposed lease agreement with TensorWave had not become effective after the October 31 closing deadline passed without extension. The transaction covers a planned 222 MW data center facility at Fermi’s Project Matador development near Amarillo.

The proposed agreement was expected to generate approximately $6.5 billion over an initial 15-year term, assuming the transaction closed and the contractual conditions were fulfilled.

According to Fermi’s November 3 statement, remaining conditions include final documentation, operational agreements, board approvals, and project-level construction financing. Neither party has exercised its contractual termination rights, and Fermi says discussions are continuing. The company indicated that it expects to provide additional information during its November 12 earnings call, or sooner if appropriate.

Project Matador is one of the industry’s most ambitious proposed developments, built around a plan for extensive private power infrastructure to support AI computing capacity.

The TensorWave situation illustrates an increasingly important financing distinction. A proposed long-term lease can provide the foundation for a major infrastructure project, but the agreement must become effective and its associated construction financing must be secured before it can be treated as firm contracted capacity.

That distinction has become more consequential as AI computing itself emerges as a financeable infrastructure asset, a transition examined in DCF’s coverage of NVIDIA’s AI factory financing strategy.

Microsoft’s Nscale Decision Adds Another Qualification

Another development surfaced November 5, when Reuters reported that Microsoft had decided not to exercise an option to expand its existing computing agreement with Nscale at a Texas data center.

The proposed expansion would have substantially increased the contracted capacity at the company’s Ward County development. Importantly, the decision had reportedly been made months before the election, and the existing Microsoft-Nscale agreement remains in place. It therefore should not be characterized as a consequence of Texas’ political shift.

Nevertheless, the decision adds another example of the difference between an announced development pipeline, a customer option, and a firm contractual commitment. In a market measured in hundreds of megawatts and multibillion-dollar agreements, those distinctions are becoming essential to evaluating project readiness.

Dallas Inference Agreement Highlights the Value of Existing Capacity

Not every AI infrastructure deployment requires a new hyperscale campus.

On October 26, Forum Markets announced that its Forum Edge AI joint venture with Edge Node had entered into a $94.4 million, 36-month agreement with Fireworks, an AI inference platform. The agreement covers reservations of NVIDIA B300 GPU computing capacity at an existing Dallas data center, with deployment expected in late December 2026 or early January 2027.

The company’s SEC filing identifies a deployment involving 96 enterprise AI servers.

Unlike a greenfield gigawatt-scale campus, this arrangement relies on an existing powered facility. The distinction matters as the industry moves from an almost exclusive focus on the enormous infrastructure requirements of model training toward a broader mix of AI workloads, including inference services.

Existing facilities with available electrical and thermal capacity may provide a faster route to deployment, particularly while new projects undergo extended regulatory and interconnection reviews.

The opportunity to extract more usable compute capacity from infrastructure already in place is also drawing renewed attention. In a recent DCF Show interview with Hammerhead AI CEO Rahul Kar, the discussion centered on using AI workload orchestration to turn otherwise unused electrical capacity into productive inference infrastructure without compromising existing customer commitments.

ServerDomes Brings an Unconventional Model to Hudspeth County

The proposed ServerDomes Global project near Desert Haven in Hudspeth County illustrates a different response to the industry’s infrastructure challenges.

The company is pursuing a campus at Hueco Ranch, west of the state’s larger AI development concentrations. Plans reported for the site contemplate approximately 350 MW of data center capacity, potentially distributed across as many as ten geodesic dome structures. The proposed first phase would occupy roughly 700 acres within a larger property.

Rather than relying primarily on conventional utility service, ServerDomes proposes dedicated behind-the-meter natural gas generation and closed-loop cooling infrastructure. The company’s design is intended to accommodate high-density computing, including both air- and liquid-cooled configurations.

However, local residents have raised questions about the development’s effects on roads, water resources, wildlife, and the surrounding environment. According to local reporting by KVIA, representatives met with residents on October 26 after concerns that information about the project had not been communicated adequately. County officials have sought further information supporting the developer’s claims about water consumption and electrical generation.

Those claims require careful distinction from independently verified operating performance. A proposed closed-loop system, for example, does not by itself establish that a facility will have no continuing water requirements. The project’s development status and ultimate environmental footprint remain contingent on further documentation and implementation.

Hueco Ranch is representative of a larger challenge for AI infrastructure developers: private generation and unconventional building designs do not eliminate the need to establish credibility with local governments and communities. As DCF has previously examined in its reporting on community opposition, local acceptance is increasingly becoming a material consideration in determining which projects can advance.

San Antonio and Other Cities Tighten Local Controls

Regulatory pressure is also increasing within Texas’ established metropolitan markets.

On October 29, the San Antonio City Council voted 9-2 to adopt new data center development regulations. The rules establish additional land-use review and specific-use authorization requirements for affected zoning districts, along with standards addressing setbacks, landscaping, noise barriers, parking, and site access. The ordinance also prohibits new data center development in the Edwards Aquifer Recharge Zone District.

San Antonio’s action reflects a broader reassessment of the industry’s physical presence in urban and suburban communities. On October 27, League City approved a zoning amendment requiring special-use permits for data centers, giving local officials additional authority to evaluate proposed developments. Coppell has also advanced changes requiring specific review of data centers and cryptocurrency mining facilities in light-industrial districts.

Although the requirements vary, the underlying direction is similar. Communities that previously handled data centers through broad industrial-use classifications are creating more explicit standards for evaluating facilities with substantial electricity, water, generation, and land-use implications.

The result is an increasingly complicated local approval landscape, even before developers encounter the state’s evolving grid and environmental regulations.

A Statewide Permitting Pause Raises the Stakes

The municipal activity is occurring against the backdrop of Abbott’s statewide regulatory actions.

On September 21, the outgoing governor directed the Texas Commission on Environmental Quality to halt permits sought by data center projects until regulators completed audits examining electricity and water requirements. The directive followed earlier instructions to ERCOT, the Public Utility Commission of Texas, and the Texas Water Development Board to gather and verify information about proposed facilities.

Implementation became controversial in October after environmental advocates identified data center-related applications that appeared to have continued advancing. TCEQ subsequently acknowledged problems with its electronic filing process and temporarily shut down automated submissions while making changes intended to ensure applications received appropriate review.

The distinction between the state’s current pause and Hinojosa’s proposed future moratorium is important.

Abbott’s directives were tied to specified audits and regulatory review. Hinojosa has proposed maintaining a broader suspension of new approvals until lawmakers establish additional protections. Whether those measures can be implemented in the form proposed, and how they would apply to projects already permitted or under construction, will require further decisions by state officials.

The situation reflects a larger national shift toward more proof-driven data center development. As DCF explored in How States Are Rewriting the Rules for Data Center Growth, states are increasingly requiring developers to substantiate power availability, infrastructure plans, environmental performance, and community commitments before projects can advance.

The Coming Fight Over Tax Incentives

Among the most consequential policy questions is the future of Texas’ tax treatment of data centers.

The industry’s qualified data center sales-tax exemption has grown dramatically alongside AI infrastructure investment. According to state comptroller estimates reported by The Texas Tribune, the exemption is projected to reduce state revenue by approximately $3.2 billion over a two-year period.

Abbott called for eliminating the exemption and other data center incentives during the next legislative session. Hinojosa has also supported ending subsidies, while advocating additional community protections and greater transparency around proposed developments.

This is a significant area of policy overlap between the outgoing and incoming governors, even though their broader approaches differ.

The issue is particularly relevant for developers whose financial models or pending transactions depend on receiving public incentives. Repeal or modification of existing programs would require legislative action, with important questions about effective dates, existing beneficiaries, and possible transition provisions.

Industry advocates argue that data centers provide construction employment, property-tax revenue, and other economic benefits that should be considered when evaluating incentives. Critics question whether those benefits justify the scale of the exemptions and the public infrastructure required to support rapidly expanding AI loads.

The 2027 debate will help determine how Texas balances continued investment with the costs and obligations associated with data center development.

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North America rig numbers dip

Total drilling activity in North America decreased slightly the week ended Nov. 6 with a total of 827 rigs working, reported Baker Hughes. A 1-rig increase in the US helped offset a 3-rig loss in Canada. The total North American rig count is down 2 units from this time last

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Vaalco advances to second exploration phase in block offshore Côte D’Ivoire

Vaalco Energy Inc., Houston, has been granted government approval to begin the second exploration phase at Block CI-705, offshore Côte d’Ivoire. News comes following encouraging results following completion of the first exploration phase work commitments, which included the evaluation and interpretation of existing seismic and well data, the company said in a release Nov. 9. Work on the second exploration phase includes additional seismic reprocessing, relinquishing 25% of the exploration block to the government, and commitment to drill an exploration well by yearend-2028. In March 2025, Vaalco farmed into and became operator of the exploration license with a 70% working interest. The block lies in the Ivoirien basin about 70 km to the west of Vaalco’s CI-40 Block, which hold Baobab and Kossipo oil fields. “We see encouraging prospectivity on the block in the play types proven throughout the Ivoirien Basin including both structural and stratigraphic traps in the Upper Cretaceous and Albian sections,” said George Maxwell, Vaalco’s chief executive officer. “Recent nearby discoveries are on trend with CI-705 and provide additional validation of our play concepts and our view of the block’s prospectivity,” he continued.

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BSR, consortium enter talks for potential downstream collaborations

Vietnam Refining and Petrochemical Corp. (BSR) has entered talks with a consortium of FutureTec Co. and Zhejiang Hanghua Technology Co. Ltd. (Hanghua) to discuss and explore development opportunities along the refining and petrochemical value chain. At a Nov. 5 meeting between the parties, officials from the companies weighed potential collaborations on the deep processing of petroleum products, the development of value-added products, and research into related industrial infrastructure projects, BSR said in a release Nov. 6. While specific projects discussed at the meeting were not revealed, BSR said the event has laid the groundwork for further in-depth talks on potential areas of collaboration that would contributing to expanding the petrochemical refining value chain, improving resource utilization efficiency, and moving operations towards sustainable development. The proposed collaboration discussion comes amid shared interests of BSR and the FutureTec-Hanghua consortium in developing green, clean, and environmentally friendly products, as well as researching and developing new higher-value products, BSR said. With its experience in operating and managing refineries, BSR offers a favorable platform for expanding cooperation efforts with partners such as FutureTec and Hanghua that bring specialized capabilities in technology, research, and product development, added Nguyen Viet Thang, BSR’s general director. Potential collaborations with external partners come alongside BSR’s upgrading and expansion project now underway at the operator’s the 6.5-million tonne/year (tpy) refinery in the Dung Quat Economic Zone of Binh Tri Commune in Binh Son District, Quang Ngai Province, Vietnam. During the Nov. 5 meeting with the FutureTec-Hanghua consortium, BSR said its near-term plans for the refinery—which is currently operating at about 121% capacity—include further improving operational efficiency; optimizing technological processes; diversifying crude oil and product sourcing; as well as developing additional cleaner, sustainable fuels, petrochemicals, and high-value products. The operator said it will also continue focusing on efforts further efficient energy use,

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Every virtual megawatt needs a meter

Last month, Google announced a deal with Voltus for a virtual power plant (VPP) of up to 1,070 MW in PJM, roughly the output of a large nuclear reactor. Rather than build a plant, Voltus will offer homes and businesses financial incentives to trim usage when the grid is strained, through smart thermostats, batteries and flexible equipment. The deal represents an inflection point for the power and utilities sector, where “speed to power” innovations are defining the moment. It also underscores the importance of the equipment that will decide how far such programs go: the electric meter. Capacity you find instead of build NEMA’s 2026 Grid Reliability Study projects U.S. economy-wide electricity demand as much as 55% by 2050, with data center consumption alone growing 300% over the next decade. New generation and transmission can’t keep pace, as permitting, capital needs and equipment and skilled labor backlogs protracting project delivery timelines. As a result, operators are looking for capacity in the system they already have. On the transmission side, grid-enhancing technologies show what’s possible: PJM modeling finds they could unlock between six and seven GW of usable capacity. At the grid edge, the opportunity may be larger. Demand response contributed 33.3 GW of enrolled wholesale capacity in 2024, about 6.5% of peak demand in organized markets and could reach 20% of U.S. peak by 2030. Behind-the-meter resources, which include microgrids and aggregations of customer-sited resources (i.e., VPPs), are scaling too. What these grid-edge resources share is a need for measurement. A demand response event or VPP dispatch only has value if someone can prove the load dropped and pay the customer who dropped it. That job falls to the electric meter. Barriers to scale Despite the momentum, only 6.5% of U.S. electricity customers are enrolled in retail demand response programs.

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The next wave of energy storage capacity is already on the grid

Next week, much of the industry will gather in Las Vegas for RE+ to talk about what gets built next. It’s an important conversation, but I’d encourage asset owners to bring a second question with them: what more can we get from what’s already been built? This question matters more than ever as electricity demand climbs and customers feel it on their monthly bill. EIA expects consumption to grow another 3.1% in 2027, driven largely by data centers and other commercial loads, while residential customers will pay nearly 5% more for power this year. The industry is working hard to add capacity, but getting it built takes time. According to Lawrence Berkeley National Laboratory and GridTracker, the median project built in 2025 spent more than five years moving from interconnection request to commercial operation and only 13% of the capacity that requested interconnection between 2000 and 2020 had come online by the end of 2025. New generation is essential, but the fleet already operating is an opportunity we can’t afford to pass up. With nearly 52 gigawatts (GW) of utility-scale battery storage operating in the U.S. as of mid-2026, the installed base is too large to overlook and performance across it varies widely. When a battery energy storage system (BESS) falls short, the instinct is often to blame the battery and reach for augmentation or replacement, but in many cases the bottleneck is the controls, software and integration around it. Operating assets are under more pressure Higher prices should raise the value of delivering power when and where the grid needs it, yet revenues for many operating assets are moving in the other direction. In ERCOT, the average battery earned 84% less in 2025 than at its 2023 peak, as more storage competed for the same services. With incentive economics

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Beyond megawatts: Nuclear’s other capacity expansion challenge

Nuclear growth plans are accelerating as data centers, large-load customers, uprates, restarts, extended operations and new generation projects reshape the industry’s outlook. But the challenge of capacity expansion extends far beyond megawatts. Every utility must also expand the capacity of its workforce.  The workforce challenge is not simply about hiring more people. Recruiting is critical, but so are retention strategies, qualification timelines, knowledge transfer processes and the availability of experienced employees and contractors. Utilities must continue operating existing plants safely and reliably while extending asset life, modernizing infrastructure, preparing for growth and developing the next generation of workers. In many cases, the same people are asked to do all of it.  An experienced engineer supporting an uprate may also be needed for aging management reviews. The supervisor helping qualify new employees may also be responsible for outage preparation. The skilled craft resources needed for capital projects are often the same resources supporting ongoing plant reliability and maintenance activities. To execute an ambitious growth plan, your workforce needs support and clear expectations as it navigates the demands of the present and the future.  That reality makes employee engagement and retention critical operational necessities.  Keeping today’s fleet running while preparing for tomorrow’s expansion  Across the industry, organizations are managing a growing list of demands. Employees are operating plants, supporting outages, resolving equipment issues, onboarding new hires, transferring knowledge, implementing modernization efforts and preparing for future growth. Subsequent license renewal and long-term operations programs add further demands through inspections, evaluations, documentation and equipment replacement activities.  At the same time, many organizations continue to face shortages in experienced operators, engineers, technicians and other critical roles. Long qualification timelines and retirements only increase the pressure.  Growth introduces another challenge that is less visible but equally important: cognitive load. Experienced employees must continually sort through competing

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Behind-the-meter power: An effective tool for bringing large utility customers online faster

Data centers and AI infrastructure are intensifying the strain on existing power grids across the U.S. Large-load facilities are built quickly, only to face years-long waits for grid interconnection and new generation capacity, such as gas turbines. Behind-the-meter (BTM) power is becoming an effective solution to bridge the gap between what the grid can provide and what data centers need to operate smoothly. Utilities and large-scale customers alike are embracing BTM power: 80 percent of utilities view BTM power generation as permanent infrastructure and expect it to serve a significant share of large-load demand by 2030, according to Bloom Energy’s 2026 Utilities Insights Report. Nearly two-thirds of data center developers cite onsite power as their primary response when grid timelines slip. “BTM addresses a major issue, which is avoiding increases in grid retail prices,” says Nik Nunes, Chief Executive Officer at Industrial Development Funding (IDF), a top investment partner of Bloom Energy. “For that reason, several governors have come out in support of it.” Key considerations for successful BTM power generation BTM power isn’t always a simple fix. It involves complications related to regulatory requirements, power storage and permitting. Yet, when used in tandem with local utilities in front of meter power resources, it can provide an effective bridge for bringing large-scale customers online faster, helping them bypass lengthy wait times for a grid connection. BTM can also be affordable over the long term relative to other power sources. To launch a successful BTM power effort, data center developers must address growing public concerns about noise, water usage and emissions. In many jurisdictions, permitting has become a challenge, and BTM power projects are often delayed. To simplify air permitting, it’s helpful for BTM solutions to produce few or no combustion-related emissions. Bloom Energy fuel cells run on natural gas today

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Land & Expand: Texas’ AI Boom Meets a New Political Reality

Hut 8 Advances a Gigawatt-Scale Campus Near Corpus Christi Another significant development came November 4, when Hut 8 reported continued progress on its Beacon Point AI data center campus in the Corpus Christi region. The company said that its previously announced second 352 MW IT-capacity lease had fully commercialized the campus, bringing the total contracted IT capacity associated with the two phases to 704 MW. The campus is designed around approximately 1 GW of utility capacity, a separate measure from the critical IT load under lease. Hut 8 estimates approximately $19.6 billion in base-term contract value across the two phases. In its third-quarter results, the company said construction of the campus substation had begun, alongside foundation and underground utility work for the first phase. Initial data hall delivery is targeted for the third quarter of 2027, with the second phase targeted for the second quarter of 2028. The company also disclosed agreements to acquire two energized sites in West Texas, with up to 230 MW of utility capacity at full energization, subject to outstanding approvals and infrastructure development. Those acquisitions point to another important trend: the increasing value of existing electrical infrastructure and sites that can potentially be adapted to serve advanced computing. As new greenfield projects face lengthy power studies and regulatory requirements, already energized locations may offer an alternative route to capacity. The distinction is especially important in markets such as Dallas-Fort Worth, where DCF’s analysis of CBRE’s first-half 2026 data found that approximately 95% of the region’s 765 MW under construction had already been preleased. PowerHouse and Big Watt Win Approval for Taylor Technology Campus Not every large new project is meeting resistance at the municipal level. On October 8, the City of Taylor approved a development agreement with PowerHouse Data Centers and Big Watt Digital for

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Google targets AI’s next infrastructure bottlenecks with two new TPUs

“It’s like adding more lanes to the highway,” he observed. “We’re not necessarily making each car travel faster, we’re creating more capacity so more traffic can move through the system at the same time.” Handling bursts, idling However, an agentic workload doesn’t behave exactly like a traditional inference workload. “It is bursty, long running, but often idle,” Lohmeyer noted. While it might generate outputs and call tools, it still has to wait for a response, maybe from a human, “literally for days.” During that time, it doesn’t need to do anything; it just needs to preserve context. But if resources are tied up for that entire multi-day period, they’re being wasted “90% plus of the time,” he said. Google Cloud’s open source TPU Sync is designed to address these issues by unifying memory, storage, and networking in software. The model-state layer for TPUs turns chip high bandwidth memory (HBM), host DRAM, shared storage, and the data center network into a “single, co-designed memory hierarchy,” the company said. It automatically tiers KV caches off the chip in milliseconds, streams context across nodes, and synchronizes RL weights to cut transfer latency and Time to First Token (TTFT) by more than 90%.

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DCF Global: Britain’s New Bargain With the AI Data Center Industry

The Global Perspective: A New Bargain for the AI Economy? Britain’s new Data Centre Covenant may ultimately prove important well beyond the United Kingdom. Governments across the world are attempting to reconcile the economic promise of AI infrastructure with the extraordinary physical requirements of building it. Electricity networks must accommodate loads measured in hundreds of megawatts. Utilities must plan transmission and generation investments years in advance. Communities are being asked to host facilities whose construction costs can run into billions, but whose permanent employment footprints may be relatively modest. At the same time, national governments increasingly view domestic computing capacity as a strategic asset. Britain is attempting to connect those issues within a single policy framework. Its approach differs in important respects from the fragmented regulatory environment in the United States, where utility commissions, state governments, local authorities, and regional grid operators exercise separate—and sometimes competing—powers over development. Nevertheless, the underlying questions are increasingly similar. In DCF’s October examination of Virginia’s changing data center policies, the industry’s largest established market was confronting new expectations concerning infrastructure costs, utility commitments, community impacts, and the conditions under which large facilities should receive development approval. Britain’s Covenant addresses comparable pressures through a more coordinated national initiative. It effectively proposes that preferential treatment for strategically important data center development should be accompanied by demonstrable public value. That is a meaningful evolution in the relationship between government and the industry. For years, data center investment announcements have emphasized capital expenditure, construction employment, technological leadership, and economic development. Those considerations remain important. But Britain’s emerging framework asks a more demanding set of questions: Can the project obtain real electricity capacity? Will it pay its fair share of infrastructure costs? Does it contribute to domestic capability? What obligations does it have to its host community? And can

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Don’t mention the data center: OpenAI calls them ‘compute campuses’ instead

Data centers’ increasing power consumption is straining the grid, with AI servers accounting for an ever larger share of that consumption, with further increases forecast. These demands are leading to a growing number of protests against the development of data centers, which could lead to construction delays. OpenAI claims that its Grid Protectors Program will meet some of those issues head-on by taking into account future capacity needs and working to make power flexibility a key element in data center, sorry, compute campus, design. The company said that the approach would differ, region by region. It has yet to finalize all the details of the scheme, but it hopes to head off some of the protests. It remains to be seen whether it has this effect. Google recently took the opposite approach to the peak consumption problem, proposing to pay people to turn off their appliances at times of high demand so that it can continue to power its data centers.

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Agentic AI boom expected to reshape CPU market

These activities include planning tasks, scheduling subtasks, calling external tools, managing interactions between multiple agents and evaluating results. Agents also rely on conventional computing resources to execute Python code, search databases, crawl websites and process information, according to TrendForce. As a result, the CPU is enjoying a new lease on life and becoming a more significant component of AI infrastructure rather than simply serving as a supporting processor for GPUs, according to TrendForce. TrendForce notes that traditional AI data centers have typically deployed approximately one CPU for every four to eight GPUs, reflecting the industry’s emphasis on accelerating computationally intensive AI workloads.

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DCF Poll: Does the Data Center Industry Need a Political Reset?

Matt Vincent is Editor in Chief of Data Center Frontier, where he leads editorial strategy and coverage focused on the infrastructure powering cloud computing, artificial intelligence, and the digital economy. A veteran B2B technology journalist with more than two decades of experience, Vincent specializes in the intersection of data centers, power, cooling, and emerging AI-era infrastructure. Since assuming the EIC role in 2023, he has helped guide Data Center Frontier’s coverage of the industry’s transition into the gigawatt-scale AI era, with a focus on hyperscale development, behind-the-meter power strategies, liquid cooling architectures, and the evolving energy demands of high-density compute, while working closely with the Digital Infrastructure Group at Endeavor Business Media to expand the brand’s analytical and multimedia footprint. Vincent also hosts The Data Center Frontier Show podcast, where he interviews industry leaders across hyperscale, colocation, utilities, and the data center supply chain to examine the technologies and business models reshaping digital infrastructure. Since its inception he serves as Head of Content for the Data Center Frontier Trends Summit. Before becoming Editor in Chief, he served in multiple senior editorial roles across Endeavor Business Media’s digital infrastructure portfolio, with coverage spanning data centers and hyperscale infrastructure, structured cabling and networking, telecom and datacom, IP physical security, and wireless and Pro AV markets. He began his career in 2005 within PennWell’s Advanced Technology Division and later held senior editorial positions supporting brands such as Cabling Installation & Maintenance, Lightwave Online, Broadband Technology Report, and Smart Buildings Technology. Vincent is a frequent moderator, interviewer, and keynote speaker at industry events including the HPC Forum, where he delivers forward-looking analysis on how AI and high-performance computing are reshaping digital infrastructure. He graduated with honors from Indiana University Bloomington with a B.A. in English Literature and Creative Writing and lives in southern New Hampshire with

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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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