Microsoft and Nvidia deploy AI to accelerate nuclear power plants for data center energy demands

Microsoft and Nvidia launch AI partnership to speed up nuclear power plant permitting and construction -- simulation tools and generative models could hasten historically lengthy processes

I'm sorry I caused a nuclear meltdown. That's on me, and it will never happen again. Microsoft and Nvidia have announced an AI-powered collaboration to accelerate the development and deployment of nuclear power plants that will power AI data centers in turn. The partnership, described in a Microsoft blog post, combines generative AI, digital twin simulation, and Nvidia's Omniverse platform to streamline the nuclear lifecycle from permitting through operations. The effort targets what Microsoft's blog calls an infrastructure bottleneck: expensive, years-long permitting processes, fragmented engineering data, and manual regulatory review that delay new nuclear plant construction. The companies say their collaboration will span four phases of nuclear development. In design and engineering, digital twins and high-fidelity simulations allow engineers to reuse proven design patterns and model the downstream effects of changes before construction begins. For licensing and permitting, generative AI handles document drafting and gap analysis across the tens of thousands of pages typically required for regulatory submissions. Construction gets 4D and 5D simulation, adding time scheduling and cost tracking to standard 3D spatial models. Much as Nvidia is doing to optimize its next-generation data center designs before a single shovel of dirt is moved, the idea is to virtually build a nuclear power plant before breaking ground, tracking physical progress against the digital plan, and catching potential schedule collisions early. In operations, AI-powered sensors and digital twins provide anomaly detection and predictive maintenance. The technology stack powering this effort includes Nvidia's Omniverse and AI Enterprise platforms and Earth 2, PhysicsNeMo, Isaac Sim, and Metropolis models alongside Microsoft's Generative AI for Permitting Solution Accelerator and Planetary Computer, all running on Azure. The idea of letting generative AI anywhere near safety-critical nuclear infrastructure might give the average reader pause, but it's already happening in the real world. Aalo Atomics, an Austin-based startup building modular nuclear reactors for data centers, has said that it reduced its permitting process workload by 92% using Microsoft's Generative AI for Permitting solution, saving an estimated $80 million annually. "Two things matter most: enterprise-scale complexity and mission-critical reliability," Yasir Arafat, chief technology officer at Aalo, said in the blog post. Aalo is currently building its Aalo-X experimental reactor at Idaho National Laboratory, with a target of achieving criticality by mid-2026. Two additional companies, Everstar and Atomic Canyon, are also building on the collaboration. Everstar, an Nvidia Inception startup, is bringing domain-specific AI for nuclear to Azure to manage project workflows and governed data pipelines, while Atomic Canyon's Neutron platform is now available in the Microsoft Marketplace, giving nuclear developers access to these capabilities through standard enterprise procurement. Given that the time span of new reactor construction stretches many years in the United States (fourteen years in the case of Southern Company's Vogtle Unit 3, for just one example), there's ample room for acceleration of the construction of those plants. Whether the growth of AI data center power demand will be sustained long enough to see Nvidia and Microsoft's efforts bear fruit will remain to be seen. Follow Tom's Hardware on Google News, or add us as a preferred source, to get our latest news, analysis, & reviews in your feeds.

Microsoft, Nvidia claim AI speeds approval of nuclear plants

Microsoft is working with Nvidia on nuclear power. Not to build it, but to offer AI-driven tools to deal with all the red tape, help with the design work, and optimize operations for nuclear projects. Announcing the move on social media site X, Microsoft President Brad Smith said this latest AI collaboration covers "the full lifecycle from permitting and design to construction and operations." Nuclear has long held promise as a stable source of carbon-free power, Smith added, and the aim of this particular initiative is to bring more of it online sooner. While building a nuclear plant is a highly complex operation, designing one and navigating the Byzantine regulations governing atomic energy can take years, cost hundreds of millions of dollars, and involve an immense amount of data processing and reporting, Microsoft claims. Of course, the Trump administration is seeking to solve this in a different way: by gutting the safety rules and skipping full environmental reviews for new reactors. AI, we're told, is expected to help by making highly complex work repeatable and predictable, and slashing development timelines without sacrificing safety. The system ensures there is a "paper trail," so regulators can verify everything, while each engineering decision is digitally linked to the evidence and regulations for auditing. Microsoft claims its tool, Generative AI for Permitting, reduced the time-intensive legwork to get approvals by 92 percent for Aalo Atomics, a firm working on mass-production of modular atomic reactors. Another, Southern Nuclear, has developed and deployed agents using Microsoft's Copilot to improve consistency in engineering and licensing. For design and engineering, digital twin technology and high-fidelity simulations enable faster iteration, while generative AI handles the drudge work of documentation drafting. Nvidia isn't just aiming at atomic plants with its digital twin technology; it also unveiled Omniverse DSX last year, a blueprint for designing and operating gigawatt-scale AI datacenters - one of the reasons why there is a pressing need for more nuclear power in the first place. More atomic power is seen as a solution for the burgeoning energy demands caused by the AI-driven datacenter building boom, but a nuclear plant typically takes at least five years to construct, while AI's energy demands mean more power is needed now. Microsoft has itself invested in nuke-generated electricity, and has a 20-year power purchase agreement (PPA) with Constellation Energy to restart the infamous Three Mile Island nuclear facility, but even this is not expected to be online before 2028. On the back of all the server farms it is building, Microsoft has seen its greenhouse gas emissions heading in the wrong direction. As The Register reported previously, its emissions have risen by nearly 30 percent since 2020, despite its much-publicized goal of becoming carbon-negative by 2030. The new AI for nuclear operations initiative brings together Nvidia's Omniverse, Earth 2, CUDA-X, AI Enterprise, PhysicsNeMo, Isaac Sim, and Metropolis, with Microsoft's Generative AI for Permitting and Planetary Computer. The combination represents an AI-powered digital ecosystem for nuclear energy on Azure, Microsoft said. ®

Microsoft and Nvidia announce AI partnership to fast-track nuclear power plants

Serving tech enthusiasts for over 25 years. TechSpot means tech analysis and advice you can trust. What just happened? If you've ever thought to yourself that what the world really needs is a slew of nuclear power plants to meet the enormous energy demands of AI data centers, here's some good news: Microsoft and Nvidia have announced an AI partnership designed to boost development and deployment of nuclear facilities. Before anyone starts picturing Copilot sitting in a control room, the companies say this is mostly about speeding up the slow work that comes before a reactor ever goes live. According to the company's post, Microsoft's new "AI for nuclear" initiative combines its Azure-based permitting tools with Nvidia's simulation stack to tackle licensing, plant design, construction planning, and ongoing operations. The biggest target is the permitting process. Microsoft says nuclear licensing can take years, cost hundreds of millions of dollars, and involve tens of thousands of pages of documentation. The pitch is that generative AI can draft paperwork, run gap analysis against historical permits, and flag inconsistencies before they become expensive delays. In theory, that leaves human experts and regulators to focus on safety rather than hunting formatting errors across a mountain of PDFs. Nvidia's part of the deal leans heavily on digital replicas. Using Omniverse, Earth 2, Isaac Sim, PhysicsNeMo, and other tools, developers can build a virtual version of a plant before the first shovel hits the dirt. Microsoft says 4D and 5D simulations add scheduling and cost tracking on top of 3D models, helping teams catch clashes, delays, and rework earlier. It's the same "build it twice, once digitally and once for real" idea Nvidia has been pitching for factories and AI infrastructure. This isn't a first-use case. Microsoft says Aalo Atomics cut its time-intensive permitting workload by 92% using the company's Generative AI for Permitting tools, saving an estimated $80 million annually. Southern Nuclear is also using Microsoft Copilot agents across engineering and licensing workstreams, while Idaho National Laboratory is applying AI to assemble safety analysis reports and standardize review methods. Because of the enormous power demand from the increasing number of AI data centers, tech companies are no longer just buying GPUs -- they're chasing the power plants to run them. Microsoft's is aiming to restart Three Mile Island to supply more than 800 megawatts of carbon-free power for its data centers. There's also been a proposal to repurpose retired Navy reactors for AI facilities.

US uses AI to speed up nuclear technology licensing applications

The United States has used AI to streamline the nuclear regulatory process. The Department of Energy used AI mapping to convert a safety analysis document required under DOE's authorization pathway for advanced reactor demonstrations into U.S. Nuclear Regulatory Commission (NRC) licensing documents for commercial deployment. The DOE revealed that this accomplishment shows the role AI can play in improving the efficiency and accuracy of nuclear technology licensing, and could one day help to accelerate timelines for the commercial deployment of advanced nuclear reactors. "Now is the time to move boldly on AI-accelerated nuclear energy deployment," said Rian Bahran, Deputy Assistant Secretary for Nuclear Reactors. "This partnership, combined with the President's orders, represents more than incremental 'uplift' improvements. It has the potential to transform how industry prepares its regulatory submissions and deploys nuclear energy while upholding the highest standards of safety and compliance." Everstar's Gordian AI solution, built on the Microsoft Azure platform, was recently used to convert the Preliminary Documented Safety Analysis for DOE's National Reactor Innovation Center's (NRIC) Generic High Temperature Gas Reactor (HTGR) into sections equivalent to an NRC license application, according to a press release. The DOE revealed that the final 208-page document took one day to generate. Typically, the process takes a team of people between four and six weeks to complete the same task. The AI tool also comprehensively identified missing or incomplete information needed to successfully complete an NRC application. Gordian was engineered for nuclear-grade technical work and is equipped with physics and engineering tools, as well as the ability to understand and integrate data through semantic ontology mapping, to ensure that the final output is computed and verified, not inferred, according to the DOE. "Nuclear is poised to solve today's critical energy challenges," said Kevin Kong, CEO and Founder of Everstar. "We're excited to partner with INL to meet the moment, working together to accelerate regulatory review and commercialization." "Our collaborations with DOE, INL and across the industry are demonstrating how we can effectively bring secure, scalable AI technologies to solve key energy challenges and achieve the broader national and economic security goals envisioned by the Department's Genesis Mission," said Carmen Krueger, Corporate Vice President, US Federal, Microsoft.

The race to build new nuclear reactors -- fast (with AI's help)

Why it matters: Nuclear energy is seen as critical to supplying enough power for AI data centers' massive electricity needs. * And AI itself is being seen as part of the solution. The big picture: A March report from the Nuclear Scaling Initiative research group concluded that "a concentrated set of structural bottlenecks" has created "an industrial capacity constraint" on future nuclear plant projects. * Unless that constraint is addressed, the result could be a series of one-off projects "rather than sustained, multi-unit delivery" of new plants, said the group, a collaboration among the Nuclear Threat Initiative, Clean Air Task Force and EFI Foundation. * The report said that while nuclear technology has advanced rapidly, other areas -- such as the development of supply chains as well as enough skilled workers to build the plants -- have not. Driving the news: At last week's CERAWeek energy conference in Houston, industry officials predicted that companies' willingness to try new approaches -- particularly with AI -- will speed things up. * "It's much more of a Silicon Valley-type ecosystem than we've ever seen in this sector," John Kotek, the Nuclear Energy Institute's senior vice president of policy development and public affairs, told Axios. * Two tech industry heavyweights -- Nvidia and Microsoft -- announced last week they're joining forces on a new initiative aimed at breaking nuclear construction bottlenecks. * It involves using AI tools that can help identify documentation inconsistencies, make sure the data for plant construction is consistent from beginning to end, and support "digital twins" -- virtual replicas that allow engineers to test changes. Zoom in: Aalo Atomics said it already has cut the time-intensive permitting process by 92% using Microsoft's Generative AI for Permitting solution while saving about $80 million a year. * Aalo broke ground last year on a precursor to the "Aalo Pod," a reactor designed for data centers that the company says will be in commercial use by 2029. * Aalo aspires to a "copy and paste" approach, said Jon Guidroz, the company's senior vice president of commercialization and strategy. * "We need to build this [nuclear] stuff the way server racks and data centers get built," he said. Another advanced-nuclear company, Kairos Power, said it's also aiming for a copy-and-paste approach by building in both New Mexico and Tennessee and comparing what works, said Mike Laufer, Kairos' CEO. * "So if you kind of combine those two, we're getting a lot of real information," Laufer said at a CERAWeek panel. * Google and Kairos plan to deploy a reactor for the Tennessee Valley Authority's grid to power Google's data centers in Tennessee and Alabama. Zoom out: Getting a qualified workforce fully up to speed to build many plants will take time, said Ross Ridenoure, Hadron Energy's chief nuclear officer. * "There will be, I think, a shortage initially, until the training programs catch up with the demand," he told Axios. * The Nuclear Energy Institute's Kotek, however, isn't fazed by any potential workforce shortages. * "What I've heard, particularly from labor, is, you show them the nuclear jobs, they'll find you the people," he said. "Because nuclear pays well, it's safe, it's long-term." The bottom line: Hyperscalers are bringing more than just a demand for electricity to the nuclear field -- they're bringing a much-needed sense of urgency, said TerraPower president and CEO Chris Levesque.

Microsoft and Nvidia unleash AI to slash nuclear project delays

Nuclear energy faces critical delays despite rising power demand * AI enables engineers to detect design inconsistencies before construction begins * Generative AI automates documentation workflows, creating audit-ready and traceable regulatory applications * High-fidelity Digital Twins validate designs virtually and reuse proven engineering patterns The global energy sector is facing unprecedented demand, yet nuclear power projects continue to encounter extensive delays before construction even begins. Highly customized engineering, fragmented datasets, and labor-intensive regulatory reviews slow progress across permitting, design, and construction phases. Engineers often spend thousands of hours drafting, cross-referencing, formatting, and reviewing tens of thousands of pages, leaving development timelines vulnerable to inefficiencies and cost overruns. AI solutions to reduce nuclear project bottlenecks These challenges reveal why nuclear energy remains critical but slow to deploy, despite urgent needs for reliable, carbon-free power - and to combat this, Microsoft and Nvidia are now collaborating to deploy AI tools which reduce bottlenecks across nuclear project lifecycles. "The world is racing to meet a historic surge in power demand with an infrastructure pipeline built for the analog age...Nuclear energy is the essential backbone for this future, but the industry remains trapped in a delivery bottleneck," Microsoft said in a blog post. High-fidelity digital twins and simulations allow engineers to validate designs virtually, reuse proven patterns, and detect inconsistencies early in planning stages. Generative AI can automate drafting, gap analysis, and documentation workflows, creating audit-ready, traceable applications for regulators. This approach compresses permitting timelines and reduces manual work, allowing experts to focus on evaluating safety rather than reconciling large volumes of text. "Two things matter most: enterprise-scale complexity and mission-critical reliability. There's no room for anything less than proven reliability," said Yasir Arafat, Chief Technology Officer at Aalo Atomics. Once plants are operational, AI-powered sensors and digital twins monitor performance and detect anomalies, enabling predictive maintenance while human operators remain in control. Southern Nuclear and Idaho National Laboratory have applied these tools to streamline engineering and safety analysis reports, improving consistency and supporting faster decision-making. AI also links design assumptions to operational performance, providing continuous visibility for operators, regulators, and stakeholders. This creates a more predictable and auditable environment that reduces risks without compromising safety. Nvidia Inception startups Everstar and Atomic Canyon are also contributing to this collaboration, each adding unique capabilities to the project. Everstar uses its domain-specific AI for nuclear power to help Azure manage project workflows and govern data pipelines, while Atomic Canyon provides developers with access to these tools through standard enterprise procurement via its Neutron platform. As AI continues to optimize engineering, permitting, and operations, nuclear energy may better meet the urgent surge in global energy demand. However, the industry must still navigate regulatory complexity and the need for disciplined execution. Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds. Make sure to click the Follow button! And of course you can also follow TechRadar on TikTok for news, reviews, unboxings in video form, and get regular updates from us on WhatsApp too.

Microsoft, NVIDIA join forces to accelerate nuclear reactor deployment with new tool

The partnership will take center stage this week at CERAWeek 2026, where the tech giants, alongside Aalo Atomics, will present their vision for a "Digital Age for Nuclear." Currently, projects often experience years of construction delays due to analog era bottlenecks like fragmented data, manual regulatory reviews, and highly customized engineering. The collaboration aims to solve these bottlenecks by providing a set of digital engineering tools to facilitate site permitting, construction, operations and maintenance phases of the reactor lifecycle. The surge in power demand, largely driven by the AI data centers, has created an urgent requirement for always-on, carbon-free nuclear power. This ecosystem provides end-to-end tools that combine AI and digital twins for creating faster iterative design and engineering solutions. Licensing and permitting is handled by Generative AI for document drafting and gap analysis. Construction is further optimized through 4D and 5D simulations that map schedules as well as avoid costly re-work, and AI-powered sensors enhance operation uptime and reduce maintenance downtime by detecting anomalies in advance by predictive maintenance.

Microsoft and Nvidia team up on AI nuclear push

Why it matters: The initiative is the latest example of the tech industry leaning on nuclear's emerging potential to deal with AI's voracious energy needs. Driving the news: Smith mentioned the "AI for nuclear" initiative during onstage remarks at the CERAWeek conference. * The two companies "have really created a solution that hopefully will play an important role in expanding the construction of nuclear power," Smith said. * The ultimate goal is to "provide end-to-end tools that streamline permitting, accelerate design, and optimize operations across the industry," said Darryl Willis, Microsoft's corporate vice president, worldwide energy and resources industry, in a subsequent blog post. * The collaboration will move nuclear companies away from "highly customized engineering" toward "repeatable, reference-based delivery" while maintaining regulatory standards and engineering accountability, Willis wrote. How it works: AI tools can help identify documentation inconsistencies, unify data across the lifecycle of plant construction, and support "digital twins," or virtual replicas that allow engineers to test changes, per Willis. * Generative AI can also help align new applications with past permits, and to simulate projects "before shovels hit the dirt," he wrote. * AI-powered sensors and operational digital twins could detect anomalies early that help keep the electricity grid stable. Zoom in: Microsoft noted that Aalo Atomics has reduced the permitting process by 92% using its generative AI permitting tool, saving an estimated $80 million a year. The bottom line: "AI is enabling the energy industry to deliver more power, faster, and safely. This Microsoft and NVIDIA collaboration provides the path to do exactly that for advanced developers, owners, and operators," Willis wrote.

Microsoft and NVIDIA plan to use AI to help build nuclear power plants to power AI

TL;DR: Microsoft and NVIDIA are partnering to use AI in accelerating nuclear power plant construction, aiming to create safe, carbon-free energy for AI infrastructure. Their AI tools streamline permitting, reduce documentation errors, and employ Digital Twins for efficient project management, cutting costs and delays significantly. It's no secret that investment in data centers and AI infrastructure has been straining energy resources, and that the biggest players in the industry are looking for a clean solution to meet the energy needs of the AI factories of the future. One of those solutions is nuclear power, with Microsoft's Darryl Willis, the Corporate Vice President of the company's Worldwide Energy and Resources Industry, calling it "the essential backbone for this future." And with the newly announced AI collaboration for nuclear power between Microsoft and NVIDIA, both companies are looking to accelerate the construction of new nuclear power plants for AI. With the help of AI. Yes, that means leveraging cutting-edge AI tools for streamlining the permitting process, which can cost "hundreds of millions of dollars." Plus, the creation of Digital Twins and simulations to enable faster iteration. Microsoft is clear that this collaboration isn't simply about accelerating the process, but also about enabling engineers and regulators to focus on "building a safe, secure, high-capacity, carbon-free power source that's on-time and on-budget." Here's a more detailed snippet from the announcement. Engineers can spend thousands of hours drafting, cross-referencing, formatting, searching, reviewing, and reworking materials. They have to identify and fix inconsistencies across tens of thousands of pages. It is little wonder that plants have been notorious for construction delays and cost overruns. To break this infrastructure bottleneck, we need to move away from highly customized engineering towards repeatable, reference-based delivery - while maintaining regulatory standards and engineering accountability. With AI, we can identify tiny documentation inconsistencies and resolve them quickly. By unifying data and simulation across the lifecycle, we ensure complex work remains: Traceable, Audit-Ready, Secure, and Predictable. The Digital Twin side of this collaboration signals what's in store for large-scale construction and infrastructure, as it leverages technologies such as NVIDIA Omniverse and NVIDIA Earth 2 to build a digital version of the nuclear plant before the first shovel hits the ground. And use that as a tool to track progress and spot any potential delays or roadblocks before they happen. For those worried that leaning on AI tools to help build nuclear power plants might sound like a bad idea, it's something that's already happening - albeit at a smaller scale than what's being outlined here. In its announcement, Microsoft includes a quote from Aalo Atomics about how the existing Microsoft Generative AI for Permitting solution (which is a part of this new collaboration) has reduced this time-intensive process by 92% and saved the company tens of millions of dollars.