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Nuclear Momentum Meets the Megawatt Test

Valar then supplied the most visible connection between the criticality program and data center technology. After reaching criticality, Valar advanced Ward 250 to approximately 10 kilowatts of thermal output and conducted a separate demonstration in which power from the reactor was used to run Nvidia Blackwell-based computing hardware. On July 1, Valar and Nvidia also […]

Valar then supplied the most visible connection between the criticality program and data center technology. After reaching criticality, Valar advanced Ward 250 to approximately 10 kilowatts of thermal output and conducted a separate demonstration in which power from the reactor was used to run Nvidia Blackwell-based computing hardware. On July 1, Valar and Nvidia also announced that they were exploring a small Utah data center using closed-loop cooling and behind-the-meter advanced nuclear generation.

The demonstration load was microscopic beside a hyperscale campus that may require hundreds of megawatts. Nvidia described the work as an exploration of how behind-the-meter advanced nuclear systems could support future AI factories, not as an agreement to purchase a specified quantity of electricity.

Deployable Energy became the third developer to achieve zero-power criticality when its Unity reactor completed its experiment at Idaho National Laboratory on June 30. DOE announced the result July 1, noting that the three companies had satisfied the administration’s objective of achieving three advanced reactor criticality milestones by July 4.

The commercial follow-up came quickly. On July 7, Deployable Energy and energy-infrastructure facilitator GridMarket announced a partnership aimed at data centers, hyperscalers and industrial customers. The agreement includes a committed pilot project and priority access to future Unity capacity. The companies said they were targeting 500 megawatts of annual deployments from 2030 through 2035 and more than 3 gigawatts cumulatively.

The companies have not publicly named the pilot host or end customers. Even so, the committed pilot and access provisions put the arrangement ahead of a conventional memorandum of understanding. GridMarket is attempting to assemble sites, customers, technology and capital before commercial Unity units become available.

Aalo Atomics completed the fourth criticality experiment on July 4, with DOE announcing the achievement July 6. Aalo-X went from groundbreaking to a sustained chain reaction in approximately eight months, according to the company.

Aalo said the test would support a commercial-scale system designed to produce 10 megawatts of electricity for an on-site data center in 2027. That is a specific deployment objective, but no named data center operator or binding power buyer was disclosed.

Collectively, the four experiments demonstrated that developers can assemble fuel, components, safety documentation and qualified teams on compressed schedules when working through DOE-authorized test programs. They also supplied investors and potential customers with evidence that the underlying reactor physics works.

As yet, these startups have not demonstrated full-power conversion systems, multi-year reliability, commercial operating costs or repeatable manufacturing at scale. Those are the metrics that will determine whether microreactors can compete in the data center market.

Savannah River Introduces the Federal “Gas First, Nuclear Later” Model

On July 20, the National Nuclear Security Administration selected Amentum to negotiate a phased lease for an AI data center and dedicated power project at the Savannah River Site in South Carolina.

The proposed development would combine a 1-gigawatt data center with approximately 2 gigawatts of on-site generation. NNSA described the energy plan as natural gas “bridging to nuclear energy.” The additional generating capacity is intended both to support the data center and potentially increase power availability to the surrounding grid.

The announcement places nuclear power inside a federally sponsored data center development rather than adding it later as an unrelated clean-energy purchase. It also reflects growing political pressure to prevent large computing campuses from transferring the cost of new generation and grid upgrades to residential customers.

Amentum was selected to enter negotiations; it did not receive a final lease. The announcement did not identify a hyperscale tenant, reactor developer, nuclear technology, construction schedule or power purchase price. Permitting, security reviews, negotiations and other federal approvals remain outstanding.

Natural gas is expected to provide the bridge because the data center can be developed faster than new nuclear capacity. Nuclear could eventually replace or supplement that generation after reactors are licensed and constructed.

Private energy campuses being planned elsewhere have talked about a similar process: install gas turbines, grid connections or other immediately available generation first, establish the computing load and revenue stream, and then take advantage of SMR or other compact nuclear technologies when they become available.

This approach acknowledges an uncomfortable timing problem. AI infrastructure developers want power as soon as possible. Gas can satisfy near-term load, while dependable commercial capacity from many first-of-a-kind nuclear projects remains a 2030s proposition.

Washington Offers $17.5 Billion to Restart the Large-Reactor Supply Chain

The most consequential large-reactor announcement came June 23, when DOE issued a conditional commitment for up to $17.5 billion in American Nuclear Supply Chain Loans.

The structure could finance long-lead components for up to five projects, each containing two Westinghouse AP1000 reactors. Ten units at 1.1 gigawatts each would represent approximately 11 gigawatts of new nuclear capacity. DOE said bulk purchasing and early component orders could accelerate deployment by as much as three years. The AP1000 is established nuclear power technology, with 6 units in operation and 14 more currently under construction.

For each two-reactor project, Westinghouse and a participating utility or energy company would each contribute $500 million in equity before drawing federal loan funds. Westinghouse has signed letters of intent with seven potential partners that have identified sites, although DOE did not disclose their names or locations. The commitment remains conditional on technical, financial, legal and environmental requirements.

The financing addresses a fundamental obstacle to new large reactors. Components such as reactor vessels, steam generators and specialized forgings require long manufacturing schedules, but utilities are reluctant to order them before a project has final regulatory approval, customer commitments and financing. A coordinated order for 10 standardized reactors could give manufacturers enough visibility to expand factories, train workers and negotiate lower prices. It could also reduce the risk that every AP1000 project effectively begins by rebuilding its own supply chain.

Data center demand is driving some reactor-restart and new-build discussions, but no hyperscaler or other anchor customer has been disclosed for any of the five proposed AP1000 projects. That is where the large-reactor program still lags the Crane model. Federal financing can reduce equipment and schedule risk, but it cannot substitute for a customer willing to pay for the electricity over several decades. The unnamed projects will eventually need regulated utility cost recovery, long-term corporate contracts, government procurement or some combination of the three.

Existing Nuclear Plants Continue to Attract Buyers Beyond Data Centers

Not every significant nuclear contract is being driven by artificial intelligence. The Walmart agreement shows that demand for long-duration nuclear contracts also extends beyond hyperscalers and data center operators.

On June 23, Constellation and Walmart announced a long-term PPA for approximately 176 megawatts from the Dresden Clean Energy Center in Illinois. The total includes 30 megawatts of added capacity expected from uprates, or improvements that increase the output of existing reactors. Walmart will purchase electricity, capacity and environmental attributes during two 15-year terms beginning in 2029 and 2030. This is Walmart’s first nuclear-derived PPA.

Adding 30 megawatts at an operating plant will not satisfy a gigawatt-scale data center campus, but uprates can generally deliver incremental capacity faster and with less execution risk than new reactors.

At another nuclear plant restart that has already received federal funding, Palisades in Michigan, Holtec announced July 2 that it had completed the major physical-project phase of its restart effort. Work included inspections, turbine-generator preparation, fuel-handling equipment, steam-generator refurbishment and other plant upgrades. More than 5,000 individual work activities remained, followed by testing, verification, fuel loading and operational-readiness procedures before startup.

Palisades is not being restarted around a disclosed data center power contract. Importantly, as Crane and Palisades successfully return to service, utilities and technology companies may gain confidence that additional retired plants can be evaluated as near-term capacity resources.

The available pool is limited, but successful restarts would add another category to the nuclear development pipeline between operating-plant uprates and entirely new construction.

Fuel and Licensing Reforms Build the Foundation Beneath the Announcements

On June 22, DOE said it was negotiating with five companies—Exodys Energy, Flibe Energy, Oklo, SHINE Technologies and Standard Nuclear—over potential use of nearly 20 metric tons of surplus government plutonium. The material could be converted into advanced reactor fuel or used for nuclear research and development. The participants would be responsible for the cost and security of processing facilities and related operations. The initiative comes as the United States remains heavily dependent on foreign nuclear-fuel supplies and services. In 2025, approximately 77% of the enrichment services purchased by U.S. reactor operators were foreign-origin, while U.S.-origin material accounted for just 7% of uranium deliveries.

The NRC has simultaneously proposed major regulatory revisions. On June 18, the commission proposed changes intended to accelerate advanced nuclear fuel infrastructure. On July 1, it announced what it described as its most comprehensive reactor-licensing modernization in decades. The proposal would introduce more risk-informed and performance-based options, allow certain early site activities after an application is docketed, and revise requirements affecting construction, emergency planning, operations and decommissioning.

In July, the NRC proposed a broad modernization of environmental reviews. Among other changes, it would focus reviews more narrowly on impacts within the commission’s statutory authority and expand the potential use of categorical exclusions for some actions. The proposal remains subject to public review and follows recently completed NRC rules covering categorical exclusions and generic environmental findings for new reactors.

Faster and more predictable licensing could improve the economics of data center-backed projects by reducing the amount of time capital remains committed without producing revenue.

A Consequential Start to Summer, With the Hardest Work Still Ahead

A major restart moved closer to supplying Microsoft. Kairos advanced manufacturing and licensing work behind a binding agreement serving Google data centers. Four advanced reactors achieved criticality. A microreactor developer assembled a multigigawatt data center pipeline. Nvidia participated in a small nuclear-powered AI demonstration. DOE proposed financing 10 AP1000 units, and federal regulators opened broad efforts to streamline reactor, fuel and environmental reviews. Momentum, but no material new capacity yet.

Data center demand is helping to accelerate that rebuilding because data center developers have enormous capital resources, concentrated electricity requirements and a strong interest in round-the-clock generation. They can provide something nuclear projects have often lacked: a large buyer prepared to make a long-term commitment before construction is complete.

But data center demand does not repeal the disciplines of nuclear development. Reactors still have to be licensed, fueled, financed, constructed and operated safely. Power agreements must allocate schedule and cost risks. Transmission must be available unless generation is truly isolated behind the meter. Customers must remain committed through years of development.

Crane and Hermes 2 show what more fully defined, contract-backed nuclear projects look like, even though they remain on very different timelines—Crane as the restart of a previously operating commercial reactor, and Hermes 2 as a first-of-a-kind demonstration project targeted for 2030. The criticality demonstrations show how quickly technical progress can occur under an accelerated federal framework. Savannah River and the AP1000 loan program show how government is trying to assemble sites, capital and supply chains at unprecedented scale.

The coming year will reveal whether the other projects can close the remaining gap—turning demonstrations into products, pipelines into contracts, and nuclear ambition into dependable megawatts for both data centers and the American grid.

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Energy Department Announces $500 Million Award to Revitalize American Steelmaking

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Energy Secretary Keeps Critical Generation Available in Mid-Atlantic

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Energy Department Announces $500 Million to Secure America’s Critical Mineral and Battery Supply Chains

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bp lets Shah Deniz compression automation contract

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Federal court voids Texas GulfLink license over agency’s ‘serious procedural errors’

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IEA: Emergency reserve withdrawals slow

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PJM’s New Data Center Power Equation

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Zayo, NVIDIA Build the Long-Haul Backbone for Distributed AI

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Southern’s 17 GW Pipeline Puts AI Power Demand Into Utility Math

The headline number from Southern Company’s latest earnings report is hard to miss: electricity use by data centers across the utility’s system increased 55% in the second quarter compared with a year earlier. But the more consequential numbers may be the ones sitting behind it. Southern now has more than 1.2 GW of operating data center load, up by more than 500 MW from a year ago. At the same time, its electric utilities have signed contracts and large-load agreements totaling more than 17 GW by the mid-2030s, with another 8 GW in late-stage development and a prospective pipeline of large industrial and data center projects exceeding 75 GW. That leaves an enormous gap between the data center megawatts consuming electricity today and the load Southern has contractually positioned itself to serve during the next decade. For the data center industry, that gap may be the most important part of Southern’s second-quarter story. It offers a look at how utilities are beginning to convert the AI infrastructure boom from forecasts and campus announcements into contracts, generation procurement, transmission investment and eventually energized capacity. From Contracts to Megawatts Southern added roughly 6 GW of contracted large load during the quarter alone. Alabama Power signed three projects representing about 3 GW, while Georgia Power reached a 25-year agreement to serve OpenAI’s planned project in Effingham County near Savannah. That facility is expected to require approximately 3.2 GW and begin taking electric service in phases in 2028. The numbers nevertheless require an important distinction. Seventeen gigawatts contracted does not mean 17 GW will suddenly appear on Southern’s grid. Large data center campuses ramp gradually, often over several years, and Southern executives acknowledged that actual customer ramp schedules do not always match the assumptions made when projects are first approved. CEO Chris Womack said

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PORTS-Pike Takes Shape as an 8-GW AI Infrastructure Model

Back on March 31, 2026, we discussed we discussed SoftBank and SB Energy’s plans to redevelop the former Portsmouth Gaseous Diffusion Plant site near Piketon as a 10-GW artificial intelligence data center campus supported by almost an equal amount of new power generation. At the time, the plan called for as much as 10 GW of new generation, including 9.2 GW of natural gas capacity, along with approximately $4.2 billion of high-voltage transmission infrastructure developed with AEP Ohio. An initial 800-MW data center phase was targeted for service in 2028. The March story was notable because Pike County appeared to offer a preview of a new model for building hyperscale infrastructure: develop the generation, transmission and data center simultaneously rather than wait for an increasingly congested regional grid to deliver multiple gigawatts of capacity. Not to mention the reuse of a brownfield site with the encouragement of the federal government. Since then, almost every important part of the project has moved forward, and on August 17, the most consequential missing pieces fell into place. NVIDIA announced that it will become the exclusive AI compute infrastructure provider for the PORTS-Pike Technology Campus. OpenAI will be the data center customer, signing a 20-year lease with SB Energy for approximately 8 GW of IT capacity. NVIDIA will invest another $1.5 billion in SB Energy and provide credit support for the land, power and shell infrastructure behind an initial 4.25 GW of IT load, with an option covering approximately another 3.75 GW. The Securities and Exchange Commission filing accompanying the announcement makes the financial commitment even more significant. NVIDIA disclosed that its aggregate payment obligation associated with its initial commitment is capped at $105 billion. That is not a conventional capital commitment to spend $105 billion building the campus, nor is it simply a

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Nvidia scales back financing guarantee for OpenAI data center

Nvidia is scaling back a proposed financial guarantee tied to a massive OpenAI data center project in Ohio, reducing its initial commitment from as much as $250 billion to less than $120 billion, according to report in the Wall Street Journal. Earlier this month, Nvidia announced partnerships with major financial firms including Apollo Global Management, BlackRock, Blackstone, Brookfield Asset Management, Goldman Sachs and KKR, aimed at mobilizing more than $500 billion in capital for AI computing infrastructure. The change represents a significant restructuring of Nvidia’s role in financing the planned facility, which is being developed by SB Energy, a subsidiary of SoftBank. Under the revised arrangement, Nvidia would guarantee financing for the project’s first phase, representing roughly 5 gigawatts of capacity, or half of the total proposed capacity. Financing for the remaining capacity would be considered separately at a later stage.

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Texas Tightens Oversight of Data Center Development

Texas has spent the past decade building one of the most data center-friendly policy environments in the United States. But the state’s political posture is tightening. The emerging message from Austin is that continued data center growth will face greater scrutiny over grid costs, water use, tax incentives and community impacts. What is interesting about this policy conversation is that the Texas Legislature is not in regular session. The 89th regular session ended June 2, 2025, and the 90th Legislature does not convene until January 12, 2027. What has occurred instead is a concentrated period of interim committee work, gubernatorial recommendations, implementation of Senate Bill 6, calls for a special session, and regulatory action by the Public Utility Commission of Texas and the Electric Reliability Council of Texas. Together, those efforts are creating the framework for a broader legislative debate in 2027 while already affecting projects seeking ERCOT interconnection, infrastructure costs and site-selection decisions. Abbott Sets Out a New Policy Framework The policy shift accelerated June 10, when Gov. Greg Abbott directed the PUCT to require data centers to fully fund the electric infrastructure needed to serve their operations and directed PUCT and ERCOT to identify additional actions available under existing authority. Separately, Abbott pledged to work with lawmakers in 2027 on legislation requiring data centers to add electric capacity, use water-efficient cooling systems, report electricity and water use, phase out outdated tax incentives and adopt additional protections for neighboring communities. The most consequential shift began June 10, when Gov. Greg Abbott sent state electricity regulators a sweeping list of data center policy priorities. Abbott called for future legislation requiring new facilities to add generation to the Texas grid, pay the full cost of their interconnection and related infrastructure, use closed-loop or similarly water-efficient cooling systems, and file annual reports

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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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Mother tongue

“Daddy?” Theo curled against my side in bed. “Where do words go when they die?” I’d orchestrated the bedtime routine flawlessly: bath (taken), teeth (brushed),

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