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From Brownfield to Breakthrough: Aligned Data Centers Extends Its AI-First Infrastructure Vision from Ohio to the Edge of Innovation

In an AI-driven world of exponential compute demand, Aligned Data Centers is meeting the moment not just with scale, but with intent. The company’s recent blitz of strategic announcements, led by plans for a transformative new campus on legacy industrial land in Ohio, offers a composite image of what it means to build data center […]

In an AI-driven world of exponential compute demand, Aligned Data Centers is meeting the moment not just with scale, but with intent.

The company’s recent blitz of strategic announcements, led by plans for a transformative new campus on legacy industrial land in Ohio, offers a composite image of what it means to build data center infrastructure for the AI era: rapid, resilient, regionally targeted, and relentlessly sustainable.

From converting a former coal power plant site into a hub for digital progress in Coshocton County, to achieving new heights of energy efficiency in Phoenix, to enabling liquid-cooled, NVIDIA-accelerated AI deployments with Lambda in Dallas, Aligned is assembling a modular, AI-optimized framework designed to meet both today’s and tomorrow’s computational extremes.

Ohio Expansion: A New Chapter for Conesville, and for Aligned

Announced July 24, Aligned’s newest mega-scale data center campus in Central Ohio will rise on a 197-acre parcel adjacent to the retired AEP Conesville coal-fired power plant, a brownfield site that once symbolized legacy energy and is now poised to power the future of digital infrastructure.

As noted by Andrew Schaap, CEO of Aligned Data Centers:

“Through this strategic expansion, Aligned not only reinforces its commitment to providing future-ready digital infrastructure in vital growth markets but also directly catalyzes billions of dollars in investment for the state of Ohio and the Coshocton County community.”

It’s a project with deep regional implications. The phased, multi-billion dollar development is expected to create thousands of construction jobs and hundreds of high-quality, long-term operational roles, while generating significant tax revenues that will support local services and infrastructure improvements.

The campus has already secured a foundational customer, with the first facility targeting initial capacity delivery in mid-2026.

This marks Aligned’s third campus in Ohio, a clear indication that the company sees the Buckeye State, with its abundant power, fiber routes, and shifting regulatory incentives, as fertile ground for AI and hyperscale growth.

But in Conesville, there’s also a deeper resonance: a shift from industrial legacy to digital future, grounded in economic revitalization.

Sustainability by Design: Phoenix Earns Triple Green Globes

As Aligned scales, the company is simultaneously sharpening its sustainability credentials. Nowhere is that more evident than in Phoenix, where its recently completed PHX-06 facility has earned a Three Green Globes® rating from the Green Building Initiative (GBI) — one of the highest levels of recognition for resource efficiency, environmental performance, and occupant wellness in new construction.

“As the global demand for AI and high-performance computing continues to accelerate, we’re continuously looking for new ways to increase the efficiency and sustainability of our data centers,” said Schaap. “This certification not only validates the exceptionally high standards we set for environmentally responsible design and construction; it underscores our unmatched speed of delivery, which enables massive, future-proof scalability across the Americas.”

PHX-06 earned its rating through a range of sustainability innovations, including reduced water usage, efficient energy systems, 100% renewable power sourcing, and a core architectural strategy centered on Aligned’s Adaptive Modular Infrastructure (AMI).

The AMI model utilizes standardized, prefabricated building components, minimizing waste, accelerating timelines, and dramatically reducing Scope 3 emissions typically generated during onsite construction.

“Achieving this level of sustainability is an outstanding accomplishment,” noted GBI CEO Vicki Worden. “Aligned continues to demonstrate its leadership in sustainability with its exceptional outcomes in energy efficiency, water conservation, carbon emissions reduction, and occupant health.”

As the highest certifying data center developer in the GBI program to date, Aligned is building a reputation not just for how quickly it can deliver infrastructure, but also for how responsibly it builds it.

Thermal Intelligence: Advanced Cooling Lab Pushes R&D for GPU Heat Loads

In the AI era, power is only half the equation. Heat is the other half.

In June, Aligned unveiled its new Advanced Cooling Lab, a Phoenix-based R&D facility dedicated to refining the company’s approach to air, liquid, and hybrid cooling strategies for next-generation GPUs and AI accelerators.

Aligned’s cooling ecosystem combines its patented Delta Cube™ air-cooled technology with its patent-pending DeltaFlow~™ liquid-cooled system. The new lab allows both to operate in tandem within hybrid environments, demonstrating how Aligned customers can fluidly scale from traditional air-cooled racks to high-density liquid cooling in the same data hall as workloads evolve.

“The Advanced Cooling Lab is a testament to our commitment to delivering cutting-edge data center solutions,” said Aligned CTO Michael Welch. “By investing in research and development, we can continue to provide our customers with the most flexible and advanced infrastructure available, capable of handling the dynamic demands of AI workloads.”

In sum, Aligned’s cooling technologies do more than just dissipate heat — they enable density, accelerate deployment, and extend infrastructure lifespan, all while supporting extreme performance tiers like NVIDIA’s Blackwell architecture.

Combined with its AMI platform, the new lab demonstrates Aligned’s readiness to meet compute demands that scale not just linearly, but exponentially.

Lambda Partnership: GPU Cloud Meets AI-First Data Center Fabric

If the cooling lab is Aligned’s engine of innovation, its recently announced partnership with Lambda is a high-performance test drive.

In May, Lambda — which is becoming known as the AI Developer Cloud trusted by leading engineers and startups alike — announced it would occupy Aligned’s new DFW-04 facility in Plano, Texas. The new data center is engineered from the ground up to support high-density, liquid-cooled GPUs, including infrastructure accelerated by NVIDIA’s Blackwell and Blackwell Ultra platforms.

“Deploying AI at scale is no easy feat,” said Ken Patchett, VP of Data Center Infrastructure at Lambda. “With its unrelenting focus on driving disruptive innovation in data center design, energy efficiency and cooling, Aligned is the ideal partner.”

The partnership is emblematic of a deeper alignment between cloud-native AI infrastructure providers and forward-leaning data center operators. It also underscores the growing need for AI-specialized facilities that can deliver not just kilowatts, but cooling, flexibility, and seamless scalability at the highest compute tiers.

Aligned CEO Schaap noted, “Particularly in Dallas, where demand for AI computation space has spiked, combining a GPU cloud built specifically for AI workloads with an AI-ready data center designed with liquid cooling technologies will be a game changer.”  

Conclusion: Infrastructure That Adapts as Fast as AI Evolves

So, spanning from a coal-fired past in Conesville to liquid-cooled futures in Plano, we see from these data points how Aligned is stitching together a data center platform not only built for speed and scale, but grounded in long-term sustainability, modularity, and technical vision.

The company’s strategy involves a fusion of real estate, advanced cooling, supply chain precision, and AI-aligned customer partnerships. This vision positions it as a vanguard builder in a world where digital infrastructure is increasingly inseparable from the future of industry, innovation, and economic development.

As generative AI, HPC, and GPU-based platforms push density to new extremes, Aligned Data Centers is ensuring the infrastructure beneath them evolves just as fast … and just as intelligently.

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Mapping Trump’s tariffs by trade balance and geography

U.S. importers may soon see costs rise for many imported goods, as tariffs on foreign goods are set to rise. On July 31, President Donald Trump announced country-specific reciprocal tariffs would finally be implemented on Aug. 7, after a monthslong pause. The news means more than 90 countries will see

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JF Expands in Southwest with Maverick Acquisition

The JF Group (JF) has acquired Arizona-based Maverick Petroleum Services. JF, a fueling infrastructure, petroleum equipment distribution, service, general contracting, and construction services provider, said in a media release that Maverick brings expertise in the installation, maintenance, and repair of petroleum handling equipment, Point-of-Sale (POS) systems, and environmental testing. As

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Lawmakers in House and Senate move to maintain Energy Star

When the Senate Appropriations Committee July 24 passed its fiscal 2026 funding bill for the U.S. Environmental Protection Agency, it included language to fund the Energy Star program at $36 million, the same as in fiscal 2024.  “The Committee recognizes the value of and continues to support the Energy Star program,” it states in the report that accompanies the bill.   House appropriators passed their version of the bill July 22, and it also included language funding the program, at a lower amount. “Within the [clean air] funds provided, at least $32,000,000 is for the Energy Star program,” says a committee-passed amendment to the House bill report.  The two bills still face floor votes and reconciliation into a single bill before the legislation goes to President Donald Trump for signature into law, but by shining a spotlight on Energy Star as a priority, lawmakers are sending a message they want to see the Trump administration maintain a program that’s been popular in both political parties since it was enacted in 1992, program backers say.  The “strong bipartisan support” for the Energy Star program is “one bright spot in the spending bills,” Sabine Rogers, federal policy manager at the U.S. Green Building Council, said on the organization’s website Aug. 6.  The Trump administration hasn’t said it wants to eliminate the program, but in its fiscal year 2026 budget request for the EPA, which it released in early May, it eliminated all funding for the Atmospheric Protection Program, which administers Energy Star.  “The Atmospheric Protection Program is an overreach of Government authority that imposes unnecessary and radical climate change regulations on businesses and stifles economic growth,” the administration said in the budget request. “This program is eliminated in the 2026 Budget.” The proposal sparked a backlash as a wide range of organizations joined

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Arizona utilities sign up for gas pipeline project, spurred by data center development

Arizona Public Service Co. and Salt River Project will buy capacity on Transwestern Pipeline’s just-announced Desert Southwest expansion project, which aims to deliver natural gas from the Permian Basin in Texas to Arizona, the utilities said Wednesday. APS, the project’s anchor customer, will use gas from the pipeline for gas-fired power plants that will support planned data centers in the utility’s service territory, said Ted Geisler, chairman, president and CEO of Pinnacle West Capital Corp., APS’ parent company, during a Wednesday earnings call. Two Fortis utilities — Tucson Electric Power and UniSource Energy Services — and the City of Mesa, Arizona, are finalizing negotiations with Transwestern, an Energy Transfer unit, according to the utilities. All existing interstate gas pipelines serving Arizona are fully subscribed, according to the utilities. Transwestern owns a 2,590-mile gas pipeline that can deliver 0.9 billion cubic feet a day from southwest Texas to Arizona. APS, SRP and TEP buy gas that is delivered on the pipeline. Transwestern plans to spend about $5.3 billion to expand its system by building 516 miles of 42-inch pipeline and adding compressor stations in Arizona, New Mexico and Texas, Energy Transfer said Wednesday. The project would add 1.5 Bcf/day of capacity to the Transwestern system, according to the company. Energy Transfer aims to complete its project by late 2029. Energy Transfer said it will launch an open season this quarter and expects the remaining capacity on the pipeline expansion to be fully subscribed. Depending on the results of the open season, the project could be expanded, the Dallas-based oil and gas infrastructure company said. Transwestern is considering more than doubling the pipeline’s capacity by using 46-inch pipe, Marshall McCrea, co-CEO of Energy Transfer, said Wednesday during an earnings conference call. APS expects to spend $7.3 billion over 25 years buying gas on

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Texas maintains non-spin reserve threshold in blow to some battery operators

Dive Brief: Texas regulators have opted to keep, for now, the minimum required duration and real-time state of charge for non-spin reserve resources at four hours, dashing the hopes of some battery energy storage system operators for a reduction that could increase competition and profitability. On July 31, the Public Utility Commission of Texas approved the rule, which the Electric Reliability Council of Texas adopted despite stakeholder opposition and the independent market monitor’s recommendation that it be reduced to one hour. The four-hour requirement will benefit gas peaker plants owned by independent power producers like Vistra and NRG Energy at the expense of Tesla, Engie, Enel and other stationary storage operators, Capstone analysts Monica Chen and Sanjana Patel wrote. It could also push some BESS operators out of the state’s market, they said. But analysts with Aurora Energy Research told Utility Dive it’s unlikely to result in dramatic operational changes. Dive Insight: The four-hour state of charge requirement was already unfavorable for BESS operators, but any negative impact from maintaining the status quo may be offset by less contentious revisions to the protocol, said Olivier Beaufils, Aurora head of U.S. Central. For example, the commission shortened the duration requirement for resources in the ERCOT Contingency Reserve Service from two hours to one hour, broadening access for shorter-duration energy storage systems, he said. As for the four-hour requirement for non-spin reserve resources, “I don’t think there’s much of a change there,” he said. “It’s more that the evolution people were expecting is not going to happen anytime soon,” Beaufils said, adding, “I think ERCOT is being a bit conservative as to what deployment for non-spin means.” Capstone expects the commission to revisit the four-hour requirement and other duration changes of the revised protocol about a year after they take effect on

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Why utilities should bring water into the data center energy conversation

Pete Elliott is senior technical staff consultant at ChemTreat and Richard Tribble is technical service consultant at ChemTreat. The growth of data centers is accelerating rapidly, driven by generative AI, cloud computing and increased digital infrastructure demand. As utilities plan for the resulting rise in electricity consumption, one critical factor is often left out of the conversation: water. Cooling systems are among the most resource-intensive components of data center operations. Whether using evaporative cooling towers, liquid-cooled systems, or air-based methods, the trade-offs between water consumption and energy demand carry significant implications for utilities and grid planning. In many cases, these trade-offs are not fully integrated into siting, design or forecasting discussions, despite their direct impact on infrastructure resilience and long-term environmental performance. Utilities and data center operators will need to coordinate more closely to address these challenges as energy and water demand rise in tandem. AI is reshaping infrastructure demand AI workloads require far greater computing power than conventional applications. This demand is driving up server rack power densities and increasing the heat load across data centers. Facilities that once averaged 8 kW per rack now often exceed 17 kW, with projections approaching 30 kW by 2027. As thermal loads increase, so do the cooling requirements. Data center power demand is expected to grow 50% by 2027 and potentially 165% by 2030. In parallel, total onsite and offsite water use associated with AI infrastructure is projected to reach 4.2 to 6.6 billion cubic meters annually, equivalent to nearly half the United Kingdom’s annual water withdrawals. These trends place added strain not only on utility-scale energy infrastructure, but also on regional water systems, particularly in areas already facing water scarcity or seasonal stress. Understanding the water-energy trade-off Evaporative cooling systems are commonly used in data centers due to their thermodynamic efficiency.

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Duke Energy Rakes in $6B with Duke Energy Florida Equity Sale

Duke Energy has reached an agreement for Brookfield, via its Super-Core Infrastructure strategy, to acquire a 19.7 percent indirect equity stake in Duke Energy Florida for a total of $6 billion. Brookfield, a prominent infrastructure investor, manages over $200 billion in assets across sectors such as utilities, transportation, midstream, and data, Duke Energy said. The investment supports Duke Energy’s ability to serve customers in its fast-growing electric and gas utilities, strengthens its balance sheet, and funds ongoing capital needs associated with its energy modernization strategy, the company said, adding that the investment represents a significant premium to Duke Energy’s current public equity valuation. Two billion dollars of the proceeds from the transaction will fund Duke Energy’s increased $87 billion, five-year capital plan, and $4 billion will be used to displace holding company debt, Duke Energy stated. “We’re pleased to have Brookfield, a highly regarded infrastructure investor, as a long-term partner in Duke Energy Florida”, Harry Sideris, Duke Energy President and Chief Executive Officer, said. “This significant transaction at a compelling valuation best positions Duke Energy to unlock additional capital investments in Duke Energy Florida during this unprecedented growth period. It also materially strengthens Duke Energy’s overall credit profile, which in turn enables us to invest in our energy modernization plans across our entire footprint – all while helping keep prices as low as possible for our customers,” he added. Duke Energy Florida serves two million customers in central and western Florida. The company’s five-year capital plan has increased by $4 billion, totaling over $16 billion in investments by 2029. This plan focuses on grid modernization, resiliency, and generation capacity enhancements to support growth in the region. Brookfield will invest $6 billion in Florida Progress, which owns Duke Energy Florida, in phases. It will receive $2.8 billion at the first closing

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USA Crude Oil Inventories Drop 3 Million Barrels Week on Week

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Incentivizing the Digital Future: Inside America’s Race to Attract Data Centers

Across the United States, states are rolling out a wave of new tax incentives aimed squarely at attracting data centers, one of the country’s fastest-growing industries. Once clustered in only a handful of industry-friendly regions, today’s data-center boom is rapidly spreading, pushed along by profound shifts in federal policy, surging demand for artificial intelligence, and the drive toward digital transformation across every sector of the economy. Nowhere is this transformation more visible than in the intensifying state-by-state competition to land massive infrastructure investments, advanced technology jobs, and the alluring prospect of long-term economic growth. The past year alone has seen a record number of states introducing or expanding incentives for data centers, from tax credits to expedited permitting, reflecting a new era of proactive, tech-focused economic development policy. Behind these moves, federal initiatives and funding packages underscore the essential role of digital infrastructure as a national priority, encouraging states to lower barriers for data center construction and operation. As states watch their neighbors reap direct investment and job creation benefits, a real “domino effect” emerges: one state’s success becomes another’s blueprint, heightening the pressure and urgency to compete. Yet, this wave of incentives also exposes deeper questions about the local impact, community costs, and the evolving relationship between public policy and the tech industry. From federal levels to town halls, there are notable shifts in both opportunities and challenges shaping the landscape of digital infrastructure advancement. Industry Drivers: the Federal Push and Growth of AI The past year has witnessed a profound federal policy shift aimed squarely at accelerating U.S. digital infrastructure, especially for data centers in direct response both to the explosive growth of artificial intelligence and to intensifying international competition. In July 2025, the administration unveiled “America’s AI Action Plan,” accompanied by multiple executive orders that collectively redefined

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AI Supercharges Hyperscale: Capacity, Geography, and Design Are Being Redrawn

From Cloud to GenAI, Hyperscalers Cement Role as Backbone of Global Infrastructure Data center capacity is undergoing a major shift toward hyperscale operators, which now control 44 percent of global capacity, according to Synergy Research Group. Non-hyperscale colocations account for another 22 percent of capacity and is expected to continue, but hyperscalers projected to hold 61 percent of the capacity by 2030. That swing also reflects the dominance of hyperscalers geographically. In a separate Synergy study revealing the world’s top 20 hyperscale data center locations, just 20 U.S. state or metro markets account for 62 percent of the world’s hyperscale capacity.  Northern Virginia and the Greater Beijing areas alone make up 20 percent of the total. They’re followed by the U.S. states of Oregon and Iowa, Dublin, the U.S. state of Ohio, Dallas, and then Shanghai. Of the top 20 markets, 14 are in the U.S., five in APAC region, and only one is in Europe. This rapid shift is fueled by the explosive growth of cloud computing, artificial intelligence (AI), and especially generative AI (GenAI)—power-intensive technologies that demand the scale, efficiency, and specialized infrastructure only hyperscalers can deliver. What’s Coming for Capacity The capacity research shows on-premises data centers with 34 percent of the total capacity, a significant drop from the 56 percent capacity they accounted for just six years ago.  Synergy projects that by 2030, hyperscale operators such as Google Cloud, Amazon Web Services, and Microsoft Azure will claim 61 percent of all capacity, while on-premises share will drop to just 22 percent. So, it appears on-premises data centers are both increasing and decreasing. That’s one way to put it, but it’s about perspective. Synergy’s capacity study indicates they’re growing as the volume of enterprise GPU servers increases. The shrinkage refers to share of the market: Hyperscalers are growing

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In crowded observability market, Gartner calls out AI capabilities, cost optimization, DevOps integration

Support for OpenTelemetry and open standards is another differentiator for Gartner. Vendors that embrace these frameworks are better positioned to offer extensibility, avoid vendor lock-in, and enable broader ecosystem integration. This openness is paired with a growing focus on cost optimization—an increasingly important concern as telemetry data volumes increase. Leaders offer granular data retention controls, tiered storage, and usage-based pricing models to help customers Gartner also highlights the importance of the developer experience and DevOps integration. Observability leaders provide “integration with other operations, service management, and software development technologies, such as IT service management (ITSM), configuration management databases (CMDB), event and incident response management, orchestration and automation, and DevOps tools.” On the automation front, observability platforms should support initiating changes to application and infrastructure code to optimize cost, capacity or performance—or to take corrective action to mitigate failures, Gartner says. Leaders must also include application security functionality to identify known vulnerabilities and block attempts to exploit them. Gartner identifies observability leaders This year’s report highlights eight vendors in the leaders category, all of which have demonstrated strong product capabilities, solid technology execution, and innovative strategic vision. Read on to learn what Gartner thinks makes these eight vendors (listed in alphabetical order) stand out as leaders in observability: Chronosphere: Strengths include cost optimization capabilities with its control plane that closely manages the ingestion, storage, and retention of incoming telemetry using granular policy controls. The platform requires no agents and relies largely on open protocols such as OpenTelemetry and Prometheus. Gartner cautions that Chronosphere has not emphasized AI capabilities in its observability platform and currently offers digital experience monitoring via partnerships. Datadog: Strengths include extensive capabilities for managing service-level objectives across data types and providing deep visibility into system and application behavior without the need for instrumentation. Gartner notes the vendor’s licensing

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LiquidStack CEO Joe Capes on GigaModular, Direct-to-Chip Cooling, and AI’s Thermal Future

In this episode of the Data Center Frontier Show, Editor-in-Chief Matt Vincent speaks with LiquidStack CEO Joe Capes about the company’s breakthrough GigaModular platform — the industry’s first scalable, modular Coolant Distribution Unit (CDU) purpose-built for direct-to-chip liquid cooling. With rack densities accelerating beyond 120 kW and headed toward 600 kW, LiquidStack is targeting the real-world requirements of AI data centers while streamlining complexity and future-proofing thermal design. “AI will keep pushing thermal output to new extremes,” Capes tells DCF. “Data centers need cooling systems that can be easily deployed, managed, and scaled to match heat rejection demands as they rise.” LiquidStack’s new GigaModular CDU, unveiled at the 2025 Datacloud Global Congress in Cannes, delivers up to 10 MW of scalable cooling capacity. It’s designed to support single-phase direct-to-chip liquid cooling — a shift from the company’s earlier two-phase immersion roots — via a skidded modular design with a pay-as-you-grow approach. The platform’s flexibility enables deployments at N, N+1, or N+2 resiliency. “We designed it to be the only CDU our customers will ever need,” Capes says. From Immersion to Direct-to-Chip LiquidStack first built its reputation on two-phase immersion cooling, which Joe Capes describes as “the highest performing, most sustainable cooling technology on Earth.” But with the launch of GigaModular, the company is now expanding into high-density, direct-to-chip cooling, helping hyperscale and colocation providers upgrade their thermal strategies without overhauling entire facilities. “What we’re trying to do with GigaModular is simplify the deployment of liquid cooling at scale — especially for direct-to-chip,” Capes explains. “It’s not just about immersion anymore. The flexibility to support future AI workloads and grow from 2.5 MW to 10 MW of capacity in a modular way is absolutely critical.” GigaModular’s components — including IE5 pump modules, dual BPHx heat exchangers, and intelligent control systems —

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Oracle’s Global AI Infrastructure Strategy Takes Shape with Bloom Energy and Digital Realty

Bloom Energy: A Leading Force in On-Site Power As of mid‑2025, Bloom Energy has deployed over 400 MW of capacity at data centers worldwide, working with partners including Equinix, American Electric Power (AEP), and Quanta Computing. In total, Bloom has delivered more than 1.5 GW of power across 1,200+ global installations, a tripling of its customer base in recent years. Several key partnerships have driven this rapid adoption. A decade-long collaboration with Equinix, for instance, began with a 1 MW pilot in 2015 and has since expanded to more than 100 MW deployed across 19 IBX data centers in six U.S. states, providing supplemental power at scale. Even public utilities are leaning in: in late 2024, AEP signed a deal to procure up to 1 GW of Bloom’s solid oxide fuel cell (SOFC) systems for fast-track deployments aimed at large data centers and commercial users facing grid connection delays. More recently, on July 24, 2025, Bloom and Oracle Cloud Infrastructure (OCI) announced a strategic partnership to deploy SOFC systems at select U.S. Oracle data centers. The deployments are designed to support OCI’s gigawatt-scale AI infrastructure, delivering clean, uninterrupted electricity for high-density compute workloads. Bloom has committed to providing sufficient on-site power to fully support an entire data center within 90 days of contract signing. With scalable, modular, and low-emissions energy solutions, Bloom Energy has emerged as a key enabler of next-generation data center growth. Through its strategic partnerships with Oracle, Equinix, and AEP, and backed by a rapidly expanding global footprint, Bloom is well-positioned to meet the escalating demand for multi-gigawatt on-site generation as the AI era accelerates. Oracle and Digital Realty: Accelerating the AI Stack Oracle, which continues to trail hyperscale cloud providers like Google, AWS, and Microsoft in overall market share, is clearly betting big on AI to drive its next phase of infrastructure growth.

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From Brownfield to Breakthrough: Aligned Data Centers Extends Its AI-First Infrastructure Vision from Ohio to the Edge of Innovation

In an AI-driven world of exponential compute demand, Aligned Data Centers is meeting the moment not just with scale, but with intent. The company’s recent blitz of strategic announcements, led by plans for a transformative new campus on legacy industrial land in Ohio, offers a composite image of what it means to build data center infrastructure for the AI era: rapid, resilient, regionally targeted, and relentlessly sustainable. From converting a former coal power plant site into a hub for digital progress in Coshocton County, to achieving new heights of energy efficiency in Phoenix, to enabling liquid-cooled, NVIDIA-accelerated AI deployments with Lambda in Dallas, Aligned is assembling a modular, AI-optimized framework designed to meet both today’s and tomorrow’s computational extremes. Ohio Expansion: A New Chapter for Conesville, and for Aligned Announced July 24, Aligned’s newest mega-scale data center campus in Central Ohio will rise on a 197-acre parcel adjacent to the retired AEP Conesville coal-fired power plant, a brownfield site that once symbolized legacy energy and is now poised to power the future of digital infrastructure. As noted by Andrew Schaap, CEO of Aligned Data Centers: “Through this strategic expansion, Aligned not only reinforces its commitment to providing future-ready digital infrastructure in vital growth markets but also directly catalyzes billions of dollars in investment for the state of Ohio and the Coshocton County community.” It’s a project with deep regional implications. The phased, multi-billion dollar development is expected to create thousands of construction jobs and hundreds of high-quality, long-term operational roles, while generating significant tax revenues that will support local services and infrastructure improvements. The campus has already secured a foundational customer, with the first facility targeting initial capacity delivery in mid-2026. This marks Aligned’s third campus in Ohio, a clear indication that the company sees the Buckeye State, with its

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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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