# Energy Published articles for Energy. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers DevFeed: [Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers]() Original publisher: [Read original article]() Author: Josh Parker Published: 2026-09-16T13:00:33Z Content type: news Language: en Sources: [NVIDIA Blog]() Topics: [data centers](), [AI Infrastructure](), [Google](), [Nvidia](), [Artificial Intelligence](), [datacenter](), [benchmarking](), [Requirements]() Tags: [ai](), [ai-data-centers](), [ai-infrastructure](), [capacity](), [corporate](), [data-centers](), [energy](), [google](), [infrastructure](), [launch](), [metrics](), [nvidia](), [performance-metrics](), [requirements](), [resource](), [systems]() ### AI overview Emerald AI, Google and NVIDIA announced the AI Energy Management Alliance, a coalition focused on flexible AI data centers that can dynamically adjust electricity use in response to grid conditions. The article describes technology-neutral, performance-based requirements covering response speed, duration, predictability and emergency behavior. ### Source excerpt AI factories are the infrastructure of the intelligence era. Scaling them responsibly will depend as much on innovation across the grid as inside the data center. Today, Emerald AI, Google and NVIDIA announced the launch of the AI Energy Management Alliance (AEMA), a first-of-its-kind coalition advancing data centers that can dynamically manage their electricity use [...] ## How energy teams turn theft detection into governed action with Genie and AI business processes DevFeed: [How energy teams turn theft detection into governed action with Genie and AI business processes]() Original publisher: [Read original article]() Author: Daniel Zoccali; Jack Yallop Published: 2026-09-15T16:50:00Z Content type: article Language: en Sources: [Databricks]() Topics: [databricks](), [Machine learning](), [Artificial Intelligence]() Tags: [databricks](), [energy](), [fraud](), [industries](), [ml](), [model](), [reporting](), [safety](), [speed]() ### AI overview The article explains how energy teams can operationalize energy-theft detection by connecting model-generated risk signals with investigation, field operations, revenue recovery, and reporting in a governed workflow. It presents a Databricks implementation using a Databricks App, Lakebase, and Unity Catalog. ### Source excerpt Energy theft is the deliberate use of gas or electricity without paying for it, typically... ## America is building datacenters faster than the grid can power them DevFeed: [America is building datacenters faster than the grid can power them]() Original publisher: [Read original article]() Author: Dan Robinson Published: 2026-09-15T16:37:00Z Content type: news Language: en Sources: [www.theregister.com - Articles]() Topics: [datacenter](), [systems]() Tags: [ai-and-ml](), [datacenters](), [energy](), [generation](), [on-prem](), [report]() ### AI overview Meeting expected energy consumption through 2030 will require $110 billion in new generation resources as America builds datacenters faster than the power grid can support. ### Source excerpt Meeting expected energy consumption through 2030 will require $110 billion in new generation resources ## LF Energy Expands Global Energy Ecosystem with New Members, Open Source Projects and Technical Milestones DevFeed: [LF Energy Expands Global Energy Ecosystem with New Members, Open Source Projects and Technical Milestones]() Original publisher: [Read original article]() Author: andrewb@proximabiz.com (The Linux Foundation) Published: 2026-09-15T07:00:01Z Content type: news Language: en Sources: [Linux Foundation - Blog]() Topics: [Open Source](), [releases](), [Software](), [Benchmark](), [Artificial Intelligence]() Tags: [energy](), [global](), [infrastructure](), [open-source](), [operational](), [projects](), [security](), [technical]() ### AI overview LF Energy announced new general members, four open source technical projects, and milestones across its project portfolio. The article highlights growing adoption of open source tools for digital energy infrastructure, grid management, asset management, operational security, and interoperability, along with more than 30% year-over-year growth in LF Energy Summit registration. ### Source excerpt Expanded membership, new open source grid tools and portfolio advancements highlight industry commitment to shared digital energy infrastructure ## Teravolt looks to cannibalize older industries to meet AI power demand DevFeed: [Teravolt looks to cannibalize older industries to meet AI power demand]() Original publisher: [Read original article]() Author: Thomas Claburn Published: 2026-09-14T13:45:00Z Content type: article Language: en Sources: [www.theregister.com - Articles]() Topics: [Artificial Intelligence](), [datacenter](), [Bitcoin]() Tags: [ai](), [ai-and-ml](), [artificial-intelligence](), [bitcoin](), [datacenter](), [electricity-grid](), [energy](), [infra]() ### AI overview Teravolt is considering repurposing Bitcoin farms, aluminum smelters, and other older infrastructure as datacenters to help meet growing AI power demand. ### Source excerpt Bitcoin farms, aluminum smelters, and other old infra is more lucrative to repurpose as a datacenter ## Powering the AI era: How wave energy can complement a 24/7 energy mix DevFeed: [Powering the AI era: How wave energy can complement a 24/7 energy mix]() Original publisher: [Read original article]() Author: Elias Habbar-Baylac Published: 2026-09-10T15:20:22Z Content type: article Language: en Sources: [Cisco Blogs]() Topics: [AI Infrastructure](), [data centers](), [datacenter](), [Artificial Intelligence]() Tags: [ai](), [ai-infrastructure](), [chief-sustainability-office](), [cisco-purpose](), [data-center](), [data-centers](), [energy](), [environmental-sustainability](), [generation](), [infrastructure](), [megawatt](), [our-corporate-purpose](), [sustainability]() ### AI overview The article explains how wave energy could complement solar, wind, and batteries in meeting the continuous electricity needs of AI-era data centers. It discusses a modeled 100 MW flat-load data center and energy portfolios evaluated for cost, reliability, emissions, and round-the-clock availability. ### Source excerpt CorPower Ocean, a Cisco Investments portfolio company, has explored how wave energy technology could complement other sources for 24/7 energy needs. ## HPE Alletra Storage MP B10000 10.6.0 Arrives With Six-Node Scale-Out and Agentic Support Automation DevFeed: [HPE Alletra Storage MP B10000 10.6.0 Arrives With Six-Node Scale-Out and Agentic Support Automation]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-09T16:17:13Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [releases](), [Software](), [Automation](), [ransomware](), [real-time](), [data]() Tags: [agentic](), [architecture](), [automation](), [data](), [energy](), [enterprise](), [enterprise-storage](), [hpe](), [performance](), [products](), [ransomware](), [real-time](), [release](), [scale](), [software](), [storage](), [update]() ### AI overview HPE has generally released version 10.6.0, also called Release 6, for the Alletra Storage MP B10000. The update expands disaggregated block-and-file storage from four to six controller nodes, adds agent-based support automation and built-in real-time ransomware detection, and increases the StoreMore Guarantee to a 5:1 effective capacity ratio. ### Source excerpt HPE has made the 10.6.0 software release for the Alletra Storage MP B10000 generally available, landing inside the Q3 2026 window the company set when it previewed the release in May. HPE is also calling it Release 6 in its channel materials. The update takes the B10000's disaggregated block-and-file architecture from four controller nodes to The post HPE Alletra Storage MP B10000 10.6.0 Arrives With Six-Node Scale-Out and Agentic Support Automation appeared first on StorageReview.com. ## The majority of Doom: The Dark Ages' DLC got made 'in three or four months' DevFeed: [The majority of Doom: The Dark Ages' DLC got made 'in three or four months']() Original publisher: [Read original article]() Author: Diego Argüello Published: 2026-09-01T18:03:04Z Content type: news Language: en Sources: [gamedeveloper]() Topics: [Game Development](), [Xbox]() Tags: [doom](), [energy](), [game-development](), [job-cuts]() ### AI overview A former Id Software producer says most of Doom: The Dark Ages - Revelations was made in three or four months under severe crunch. He describes repeated 60- to 80-hour weeks and says the team faced intense pressure to meet expected quality levels. ### Source excerpt The team reportedly worked 60 to 80 hour weeks to get the project out the door. ## Paving the way for greener ammonia production DevFeed: [Paving the way for greener ammonia production]() Original publisher: [Read original article]() Author: David L. Chandler | Department of Materials Science and Engineering Published: 2026-08-20T18:45:00Z Content type: article Language: en Sources: [MIT AI News]() Topics: [Materials science and engineering](), [acid]() Tags: [agriculture](), [ai-for-materials-science](), [artificial-intelligence](), [bilge-yildiz](), [catalysts](), [chemistry](), [cleaner-fertilizer](), [cleaner-industry](), [computational-materials-science](), [computer-modeling](), [dmse](), [electrochemical-ammonia-production](), [emissions](), [energy](), [fertilizer-production](), [food](), [fossil-fuel](), [green-ammonia](), [greener-fertilizer](), [haber-bosch-process](), [industry](), [machine-learning](), [materials-science-and-engineering](), [mit-dmse](), [nitrogen-dissociation](), [nuclear-science-and-engineering](), [pollution](), [research](), [school-of-engineering](), [school-of-science](), [science](), [sustainability](), [transition-metal-nitrides]() ### AI overview MIT researchers developed an approach to predict promising catalyst materials for electrochemical ammonia production. The method could speed the search for alloys that may help make this lower-emissions process more competitive with the fossil-fuel-dependent Haber-Bosch process. ### Source excerpt New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that's essential to fertilizer and other products. ## Improving infrastructure efficiency for growing demand in the age of AI DevFeed: [Improving infrastructure efficiency for growing demand in the age of AI]() Original publisher: [Read original article]() Author: Yasmin McDowell,Lawrence Good,Ilya Yakovlev Published: 2026-08-18T17:00:00Z Content type: article Language: en Sources: [Dropbox Tech Blog]() Topics: [cloud-infrastructure](), [systems](), [data centers](), [Optimization](), [Hardware](), [Artificial Intelligence](), [networking](), [Magic Pocket]() Tags: [ai](), [availability](), [data-center](), [efficiency](), [energy](), [hardware](), [industry](), [infrastructure](), [networking](), [optimization](), [storage](), [systems]() ### AI overview Dropbox describes a system-level approach to improving infrastructure efficiency as AI-driven demand grows. Its engineering teams optimize capacity planning, hardware, power, cooling, storage, servers, networking, and facility design together so existing infrastructure can support growth before new data center capacity is added. ### Source excerpt As demand for AI continues to grow, so does the infrastructure needed to support it. ## Time: The cornerstone of digital sovereignty and independence DevFeed: [Time: The cornerstone of digital sovereignty and independence]() Original publisher: [Read original article]() Author: Luca Cicchelli Published: 2026-08-18T01:45:10Z Content type: article Language: en Sources: [APNIC Blog]() Topics: [digital sovereignty](), [systems](), [1.1.1.1](), [spoofing](), [Cybersecurity](), [5G](), [Cloud](), [Artificial Intelligence]() Tags: [5g](), [ai](), [cloud](), [cybersecurity](), [digital-sovereignty](), [energy](), [gnss](), [guest-post](), [ixps](), [operational](), [spoofing](), [systems](), [tech-matters](), [time]() ### AI overview Time is presented as a foundational requirement for digital sovereignty and independent operation. The article explains how synchronized time supports telecommunications, finance, energy, cloud and AI systems, and transport, while dependence on GNSS introduces risks from interference, jamming, and spoofing. ### Source excerpt Guest Post: Though often overlooked, time underpins telecommunications, finance, energy, cloud, AI, and transport systems. As dependence on GNSS increases, organizations need resilient, traceable time sources to strengthen cybersecurity, improve operational continuity, and support digital sovereignty. ## OpenAI joins PORTS-Pike project DevFeed: [OpenAI joins PORTS-Pike project]() Original publisher: [Read original article]() Published: 2026-08-17T05:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [datacenter](), [OpenAI](), [Nvidia](), [jobs]() Tags: [data-center](), [energy](), [global-affairs](), [infrastructure](), [jobs](), [local](), [nvidia](), [openai](), [partnership]() ### AI overview OpenAI has agreed to secure approximately 8 gigawatts-IT at the PORTS-Pike Technology Campus in Ohio in partnership with SB Energy, NVIDIA, and the U.S. Department of Energy. The project is expected to create construction and long-term operating jobs, fund community priorities, and support local infrastructure. Its data center will pay its energy and infrastructure costs and use closed-loop, air-cooled cooling systems to reduce ongoing water demand. ### Source excerpt OpenAI joins PORTS-Pike project, expanding community investment and supporting thousands of Southern Ohio jobs ## The Database at 550 Kilometers: What Orbital Computing Means for Distributed Databases DevFeed: [The Database at 550 Kilometers: What Orbital Computing Means for Distributed Databases]() Original publisher: [Read original article]() Author: Isaac Wong Published: 2026-08-06T00:00:00Z Content type: opinion Language: en Sources: [Cockroach Labs]() Topics: [data centers](), [Databases](), [Artificial Intelligence](), [Inference](), [GPU]() Tags: [2026](), [ai](), [compute](), [data-center](), [data-centers](), [database](), [distributed](), [energy](), [gpu](), [inference](), [infrastructure](), [nvidia](), [solar](), [space](), [spacex]() ### AI overview The article examines orbital data centers as a possible response to the energy, cooling, and land constraints of terrestrial facilities. It describes proposed satellite-based computing projects, including an orbital Nvidia H100 Gemini inference workload, and outlines the roles of solar power, radiative cooling, and open orbit. ### Source excerpt In Ashburn, Virginia, a row of servers draws 40 megawatts from the grid and exhales it as heat. ## Advancing the next era of national science DevFeed: [Advancing the next era of national science]() Original publisher: [Read original article]() Published: 2026-07-22T12:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [Frontier AI](), [OpenAI](), [API](), [codex](), [coding](), [Cybersecurity]() Tags: [accelerate](), [ai](), [api](), [codex](), [coding](), [cybersecurity](), [department-of-energy](), [energy](), [frontier-ai](), [global-affairs](), [government](), [gpt](), [infrastructure](), [innovation](), [models](), [openai](), [research](), [science](), [systems](), [tools](), [workflows]() ### AI overview OpenAI describes commitments to support the U.S. Department of Energy's Genesis Mission by providing frontier AI, Codex access, API support, specialized bioscience capabilities, model access, and cyber capabilities to researchers at national laboratories and universities. The initiative aims to accelerate scientific discovery and strengthen research infrastructure. ### Source excerpt OpenAI outlines its commitment to advancing American science working with the U.S. Department of Energy and national labs to use frontier AI to accelerate discovery. ## How Amazon tracks carbon intensity across its operations DevFeed: [How Amazon tracks carbon intensity across its operations]() Original publisher: [Read original article]() Author: Kerry Constabile Published: 2026-07-01T15:56:42Z Content type: news Language: en Sources: [Amazon Science homepage]() Topics: [amazon](), [data](), [Cloud](), [Routing (disambiguation)]() Tags: [amazon](), [amazon-sustainability-report](), [cloud-services](), [data](), [decarbonization](), [energy](), [operations](), [renewable-energy](), [routing](), [scale](), [sustainability](), [the-climate-pledge](), [transportation]() ### AI overview Amazon describes its use of sector-specific carbon-intensity metrics to track decarbonization across diverse operations. For retail, it measures emissions per unit shipped and reports a 39% reduction from 2019 to the end of 2025, attributing progress to carbon-free energy, routing improvements, lighter packaging, lower-carbon fuels, alternative transportation, and electric vehicles. ### Source excerpt Amazon is developing precise, sector-specific approaches to measuring decarbonization progress -- starting with emissions per unit shipped. ## Accelerating Gemini Nano models on Pixel with frozen Multi-Token Prediction DevFeed: [Accelerating Gemini Nano models on Pixel with frozen Multi-Token Prediction]() Original publisher: [Read original article]() Published: 2026-06-26T18:30:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [AI Inference](), [On-device AI](), [Google](), [LLMs](), [gemma]() Tags: [ai](), [efficiency](), [energy](), [gemini](), [inference](), [machine-intelligence](), [mobile-systems](), [natural-language-processing](), [on-device](), [on-device-ai](), [phones]() ### AI overview Google Research describes a method for retrofitting Multi-Token Prediction onto frozen Gemini Nano v3 production models to accelerate on-device inference on Pixel phones. The approach targets mobile energy and memory constraints, improving the speed and energy efficiency of features such as notification summaries and proofreading without requiring separate drafting models. ### Source excerpt Machine Intelligence ## Improving the speed and energy-efficiency of AI agents DevFeed: [Improving the speed and energy-efficiency of AI agents]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-06-25T04:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [agentic workflows](), [Loop Engineering](), [Green Software](), [Cloud](), [Microsoft](), [microsoft-azure]() Tags: [adam-belay](), [agentic-workflows](), [agents](), [ai](), [ai-agents](), [algorithms](), [artificial-intelligence](), [cloud](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [data](), [data-centers](), [defense-advanced-research-projects-agency-darpa](), [deployment](), [efficiency](), [electrical-engineering-and-computer-science-eecs](), [electronics](), [energy](), [energy-efficiency](), [gohar-chaudhry](), [machine-learning](), [microsoft](), [microsoft-azure](), [mit-schwarzman-college-of-computing](), [murakkab](), [research](), [school-of-engineering](), [software](), [sustainability](), [sustainable-computing](), [workflows]() ### AI overview MIT and Microsoft researchers developed Murakkab, a system that automatically designs and deploys agentic workflows by selecting models, tools, hardware configurations, and computational resources according to user priorities. Tests found that it reduced computational requirements, energy use, and costs without reducing performance. ### Source excerpt A new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications. ## The fuel of the future is already here: Why TRISO matters DevFeed: [The fuel of the future is already here: Why TRISO matters]() Original publisher: [Read original article]() Author: Katy Huff Published: 2026-06-24T19:57:09Z Content type: article Language: en Sources: [Amazon Science homepage]() Topics: [AI Infrastructure](), [amazon](), [cloud-computing]() Tags: [advanced-nuclear-reactors](), [advanced-reactor-fuel-fabrication](), [ai-infrastructure](), [amazon](), [amazon-nuclear-energy](), [clean-energy-data-centers](), [cloud-computing](), [decarbonization](), [durability](), [energy](), [haleu](), [integrity](), [modular-nuclear-reactors](), [nuclear-energy-for-ai](), [physical-science](), [renewable-energy](), [resilience](), [safety](), [science](), [sustainability](), [triso-fuel](), [triso-particles](), [x-energy-xe-100]() ### AI overview Amazon explains how TRISO nuclear fuel particles use layered carbon and ceramic coatings to contain radioactive byproducts and withstand extreme temperatures. The article connects the technology to rising energy demands from AI infrastructure and cloud computing, citing testing that found no detectable failures at 1600°C for 300 hours. ### Source excerpt Millimeter-scale particles of nuclear-reactor fuel are encased in four layers of different materials that act as a "miniature containment system". ## New chip could help tiny robots traverse complex environments DevFeed: [New chip could help tiny robots traverse complex environments]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-06-23T04:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Hardware](), [Algorithms](), [3D](), [navigation](), [real-time](), [Green Software](), [Computer science]() Tags: [3d](), [aeronautical-and-astronautical-engineering](), [algorithms](), [artificial-intelligence](), [assembly](), [augmented-and-virtual-reality](), [autonomous-vehicles](), [computer-chips](), [computer-science-and-technology](), [efficiency](), [electrical-engineering-and-computer-science-eecs](), [energy](), [energy-efficiency](), [gleanmer](), [hardware](), [inside](), [laboratory-for-information-and-decision-systems-lids](), [low-power](), [machine-learning](), [memory](), [mit-schwarzman-college-of-computing](), [national-science-foundation-nsf](), [navigation](), [peter-zhi-xuan-li](), [real-time](), [research](), [research-laboratory-of-electronics](), [robotics](), [school-of-engineering](), [sertac-karaman](), [system-on-a-chip](), [trajectory-planning](), [vivienne-sze](), [zih-sing-fu]() ### AI overview MIT researchers developed a low-power chip that combines an efficient mapping algorithm with dedicated hardware to generate detailed 3D maps for robot navigation in real time. The system-on-a-chip uses about 6 milliwatts and is intended for tiny autonomous robots and other battery-limited devices. ### Source excerpt Researchers combined an efficient algorithm with dedicated hardware to rapidly generate 3D maps for navigation using minimal memory and power. ## MIT in the media: For the future of tech, "Massachusetts can absolutely lead" DevFeed: [MIT in the media: For the future of tech, "Massachusetts can absolutely lead"]() Original publisher: [Read original article]() Published: 2026-06-18T04:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [AI Strategy](), [Robotics]() Tags: [ai](), [alumni-ae](), [applied-ai](), [articles](), [artificial-intelligence](), [biotechnology](), [cambridge-boston-and-region](), [computer-science-and-technology](), [courses](), [energy](), [faculty](), [funding](), [health](), [manufacturing](), [president-sally-kornbluth](), [quantum-computing](), [quantum-technologies](), [research](), [robotics](), [startup](), [startups](), [students](), [tech](), [technology-and-society]() ### AI overview MIT's research, AI initiatives, online courses, and entrepreneurship programs are highlighted in coverage of Massachusetts' technology ecosystem and its potential for continued leadership. ### Source excerpt Leaders, faculty across MIT discuss fostering innovation and talent in Greater Boston in special series of articles published alongside the outlet's annual list of 'Tech Power Players' ## A low-carbon computing platform from your retired phones DevFeed: [A low-carbon computing platform from your retired phones]() Original publisher: [Read original article]() Published: 2026-06-12T17:37:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Green Software](), [cloud-computing](), [datacenter](), [Hardware](), [cpu](), [Google]() Tags: [climate-sustainability](), [cloud](), [cloud-computing](), [compute](), [datacenter](), [distributed-systems-parallel-computing](), [efficiency](), [energy](), [energy-efficiency](), [google](), [hardware](), [memory](), [performance](), [servers](), [smartphones](), [storage](), [sustainability]() ### AI overview Researchers at the University of California San Diego, with Google's support, are developing a low-carbon cloud computing platform from retired smartphones. A planned datacenter using 2,000 Pixel smartphones aims to provide low-cost computing while reducing the need for newly manufactured hardware and its associated emissions. ### Source excerpt Climate & Sustainability ## Startup's nuclear-inspired cooling system could make data centers more sustainable DevFeed: [Startup's nuclear-inspired cooling system could make data centers more sustainable]() Original publisher: [Read original article]() Author: Zach Winn | MIT News Published: 2026-06-10T04:00:00Z Content type: article Language: en Sources: [MIT AI News]() Topics: [data centers](), [Artificial Intelligence](), [cloud-infrastructure](), [Computer science]() Tags: [ai](), [ai-data-centers](), [artificial-intelligence](), [computer-science-and-technology](), [cooling](), [data-center-cooling](), [data-center-sustainability](), [data-centers](), [efficiency](), [energy](), [energy-efficiency](), [energy-storage](), [ferveret](), [matteo-bucci](), [nuclear-science-and-engineering](), [power](), [reza-azizian](), [school-of-engineering](), [startups](), [sustainability](), [sustainable-computing](), [technology-and-society](), [water]() ### AI overview Ferveret, a startup founded by two MIT researchers, is adapting nuclear-reactor heat-transfer methods to cool AI data-center servers with a specialized liquid. Its Adaptive Phase Cooling system uses small, frequently detaching bubbles to improve heat transfer without water and with less electricity. ### Source excerpt Founded by two researchers from MIT, Ferveret reduces the amount of energy and water required to cool the chips that power AI. ## Building the infrastructure for the Intelligence Age in Michigan DevFeed: [Building the infrastructure for the Intelligence Age in Michigan]() Original publisher: [Read original article]() Published: 2026-06-01T12:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [datacenter](), [AI Infrastructure](), [stargate](), [Artificial Intelligence](), [OpenAI](), [jobs]() Tags: [ai](), [ai-infrastructure](), [codex](), [data-center](), [energy](), [global-affairs](), [infrastructure](), [jobs](), [openai](), [partners](), [partnership](), [stargate](), [work]() ### AI overview OpenAI has broken ground on The Barn, a 1GW data center campus in Saline, Michigan, as part of Stargate. The project includes commitments on infrastructure costs, water conservation, union and permanent jobs, community investment, tax revenue, and access to AI tools and training through Codex credits for eligible Michigan students. ### Source excerpt OpenAI breaks ground on a 1GW data center project in Michigan as part of Stargate, building AI infrastructure to expand access, create jobs, and support communities. ## Physics AI research that's shaping the industry. DevFeed: [Physics AI research that's shaping the industry.]() Original publisher: [Read original article]() Published: 2026-05-27T12:00:05Z Content type: news Language: en Sources: [Mistral AI Blog]() Topics: [AI Research](), [Physics-guided deep learning](), [Artificial Intelligence](), [data](), [datasets](), [AI Foundation Models](), [GPU](), [Machine learning](), [Transformer]() Tags: [ai](), [ai-research](), [data](), [datasets](), [deep-learning](), [design](), [energy](), [engineering](), [gpu](), [industry](), [machine-learning](), [models](), [performance](), [physics](), [real-time](), [research]() ### AI overview Mistral describes its acquisition of Emmi AI and its focus on Physics AI for industrial engineering. The article surveys published work on CFD, neural surrogates, foundation models, datasets, plasma turbulence, and real-time industrial simulation across aerospace, automotive, semiconductors, and energy. ### Source excerpt Published breakthroughs pushing the state of the art. [Next page]()