Articles tagged with "data-centers"
New twist on classic material could advance quantum computing
Researchers at Penn State University have developed a novel approach to enhance the electro-optic properties of barium titanate, a classic material known since 1941 for its strong ability to convert electrical signals into optical signals. By reshaping barium titanate into ultrathin strained thin films, the team achieved over a tenfold improvement in the conversion efficiency of electrons to photons at room temperature compared to previous results at cryogenic temperatures. This breakthrough addresses a long-standing challenge, as barium titanate had not been widely commercialized due to fabrication difficulties and stability issues, with lithium niobate dominating the electro-optic device market instead. The improved material has significant implications for quantum computing and data center energy efficiency. Quantum technologies often require cryogenic conditions, but transmitting quantum information over long distances needs room-temperature optical links, which this advancement could enable. Additionally, data centers, which consume vast amounts of energy primarily for cooling, could benefit from integrated photonic technologies that use photons rather than electrons to transmit data
materialselectro-optic-materialsbarium-titanatequantum-computingenergy-efficiencydata-centersphotonicsLiquid Loops & Urban Warmth: The Next Frontier in Data Center Efficiency - CleanTechnica
The article from CleanTechnica highlights the significant opportunity to improve data center efficiency by capturing and repurposing the vast amounts of heat they generate. Traditionally, data centers have treated heat as a waste product, using energy-intensive air cooling systems that consume 20–40% of their power just to maintain safe operating temperatures. However, with the rise of hyperscale data centers and AI workloads, there is growing interest in transforming this heat from a liability into a valuable resource. Liquid cooling technologies, such as direct-to-chip and immersion cooling, enable servers to operate at higher outlet temperatures (50–60 °C), making the waste heat suitable for integration with modern district heating networks. This approach is already being implemented in northern Europe, where dense district heating infrastructure allows data centers to supply thermal energy to residential heating demands. Examples include Meta’s data center in Odense, Denmark, which provides about 100,000 MWh annually to the local grid, and Microsoft’s Azure facilities in Finland, delivering 250
energydata-centersliquid-coolingheat-recoverydistrict-heatingthermal-energyenergy-efficiencyNscale inks massive AI infrastructure deal with Microsoft
Nscale, an AI cloud provider founded in 2024, has secured a major deal to deploy approximately 200,000 Nvidia GB300 GPUs across data centers in Europe and the U.S. This deployment will occur through Nscale’s own operations and a joint venture with investor Aker. Key locations include a Texas data center leased by Ionic Digital, which will receive 104,000 GPUs over 12 to 18 months, with plans to expand capacity to 1.2 gigawatts. Additional deployments include 12,600 GPUs at the Start Campus in Sines, Portugal (starting Q1 2026), 23,000 GPUs at Nscale’s Loughton, England campus (starting 2027), and 52,000 GPUs at Microsoft’s AI campus in Narvik, Norway. This deal builds on prior collaborations with Microsoft and Aker involving data centers in Norway and the UK. Josh Payne, Nscale’s founder and CEO, emphasized that this agreement positions Nscale as
energyAI-infrastructuredata-centersGPUssustainabilitycloud-computingtechnology-investmentMeta partners up with Arm to scale AI efforts
Meta has partnered with semiconductor design company Arm to enhance its AI systems amid a significant infrastructure expansion. The collaboration will see Meta’s ranking and recommendation systems transition to Arm’s technology, leveraging Arm’s strengths in low-power, efficient AI deployments. Meta’s head of infrastructure, Santosh Janardhan, emphasized that this partnership aims to scale AI innovation to over 3 billion users. Arm CEO Rene Haas highlighted the focus on performance-per-watt efficiency as critical for the next era of AI. This multi-year partnership coincides with Meta’s massive investments in AI infrastructure, including projects like “Prometheus,” a data center expected to deliver multiple gigawatts of power by 2027 in Ohio, and “Hyperion,” a 2,250-acre data center campus in Louisiana projected to provide 5 gigawatts of computational power by 2030. Unlike other recent AI infrastructure deals, Meta and Arm are not exchanging ownership stakes or physical infrastructure. This contrasts with Nvidia’s extensive investments in AI firms such
energyAI-infrastructuredata-centerssemiconductorpower-consumptioncloud-computingMetaOpenAI and Broadcom partner on AI hardware
OpenAI has announced a significant partnership with Broadcom to acquire 10 gigawatts of custom AI accelerator hardware. These AI accelerator racks are planned for deployment in OpenAI’s and partner data centers from 2026 through 2029. By designing its own chips and systems, OpenAI aims to integrate insights from its advanced AI model development directly into the hardware, enhancing performance and intelligence capabilities. The financial terms of the deal were not disclosed, though the Financial Times estimated the value. This hardware agreement follows a series of major recent deals by OpenAI, including a multi-billion dollar arrangement with Nvidia for 10 gigawatts of hardware and a reportedly historic agreement with Oracle, which remains unconfirmed. These partnerships underscore OpenAI’s strategic focus on securing substantial computing resources to support its AI research and product development efforts over the coming years.
energyAI-hardwaredata-centerscustom-chipsaccelerator-racksOpenAIhardware-partnershipThe billion-dollar infrastructure deals powering the AI boom
The article highlights the massive investment and infrastructure buildup fueling the current AI boom, emphasizing the enormous computing power required to train and run AI models. Nvidia CEO Jensen Huang estimates that $3 to $4 trillion will be spent on AI infrastructure by 2030, with major tech companies like Microsoft, Meta, Oracle, Google, and OpenAI leading the charge. The piece details key deals, starting with Microsoft’s landmark $1 billion investment in OpenAI in 2019, which established Microsoft as OpenAI’s exclusive cloud provider and laid the groundwork for a partnership now valued at nearly $14 billion. Although OpenAI has recently diversified its cloud partnerships, this model of close collaboration between AI firms and cloud providers has become standard, with companies like Anthropic partnering with Amazon and Google Cloud acting as primary computing partners for other AI ventures. Oracle’s emergence as a major AI infrastructure player is underscored by its unprecedented deals with OpenAI, including a $30 billion cloud services contract revealed in mid-2025
energyAI-infrastructurecloud-computingdata-centersNvidiaMicrosoft-AzureOpenAINew Tiny chip creates 'rainbow laser' for faster data speeds
Researchers at Columbia University, led by Michal Lipson, have developed a tiny chip that generates powerful “frequency combs”—light sources composed of dozens of evenly spaced wavelengths. This innovation enables multiple data streams to be transmitted simultaneously through a single optical fiber, addressing a critical bottleneck in current fiber-optic networks that typically rely on single-wavelength lasers. The chip effectively cleans up and stabilizes the chaotic output of a high-power multimode laser diode using a locking mechanism, producing a high-coherence, multi-frequency laser source on a compact silicon photonics platform. This breakthrough has significant implications for modern computing and data centers, especially as artificial intelligence drives an exponential increase in data demand. By replacing bulky, expensive laser systems with a single compact device capable of delivering many clean, high-power channels, the technology promises faster, more energy-efficient data transmission and reduced costs and space requirements. Beyond data communications, the chip’s ability to produce precise frequency combs could also benefit applications in compact spectrometers,
IoTsilicon-photonicsfrequency-combdata-centerslaser-technologymicrochipoptical-communicationWhile OpenAI races to build AI data centers, Nadella reminds us that Microsoft already has them
Microsoft CEO Satya Nadella announced the deployment of the company’s first massive AI system—referred to as an AI “factory” by Nvidia—at Microsoft Azure’s global data centers. These systems consist of clusters with over 4,600 Nvidia GB300 rack computers equipped with the new Blackwell Ultra GPU chips, connected via Nvidia’s high-speed InfiniBand networking technology. Microsoft plans to deploy hundreds of thousands of these Blackwell Ultra GPUs worldwide, enabling the company to run advanced AI workloads, including those from its partner OpenAI. This announcement comes shortly after OpenAI secured significant data center deals and committed approximately $1 trillion in 2025 to build its own infrastructure. Microsoft emphasized that, unlike OpenAI’s ongoing build-out, it already operates extensive data centers in 34 countries, positioning itself as uniquely capable of supporting frontier AI demands today. The new AI systems are designed to handle next-generation AI models with hundreds of trillions of parameters. Further details on Microsoft’s AI infrastructure expansion are
energydata-centersAI-hardwareGPUscloud-computingNvidiaMicrosoft-AzureMicrosoft buys another 100 MW of solar, this time in Japan
Microsoft has agreed to purchase 100 megawatts of solar power capacity from Japanese developer Shizen Energy, continuing its series of renewable energy investments to support its expanding computing infrastructure. The company already operates two data centers in Japan and plans to invest $2.9 billion in the country over the next year, underscoring its commitment to growing its presence there. Solar energy is increasingly favored by tech firms and data center operators due to its relatively low cost and rapid deployment, with projects typically completed within 18 months and power generation often starting before full completion. Microsoft has been a significant buyer of solar power recently, having contracted over 1 gigawatt of solar capacity since the beginning of the year, reflecting its strategy to meet rising compute demands sustainably.
energysolar-powerrenewable-energyMicrosoftdata-centersJapanclean-energyAMD to supply 6GW of compute capacity to OpenAI in chip deal worth tens of billions
AMD has entered a multi-year chip supply agreement with OpenAI that could generate tens of billions in revenue and significantly boost AMD’s presence in the AI sector. Under the deal, AMD will provide OpenAI with 6 gigawatts of compute capacity using multiple generations of its Instinct GPUs, beginning with the Instinct MI450 GPU, which is expected to be deployed in the second half of 2026. AMD claims the MI450 will outperform comparable Nvidia GPUs through hardware and software enhancements developed with OpenAI’s collaboration. Currently, OpenAI already uses AMD’s MI355X and MI300X GPUs for AI inference tasks due to their high memory capacity and bandwidth. In addition to supplying chips, AMD has granted OpenAI the option to purchase up to 160 million shares of AMD stock, representing a 10% stake. The stock vesting is tied to the deployment milestones of the compute capacity and AMD’s stock price, with the final tranche vesting if AMD shares reach $600. Following the
energyAI-computeGPUsdata-centerschip-supplysemiconductorAI-infrastructureChina to sink servers off Shanghai in underwater data center trial
China is set to deploy one of the world’s first commercial underwater data centers by submerging a capsule of servers off Shanghai in mid-October. Developed by maritime equipment firm Highlander in collaboration with state-owned builders, the project aims to drastically reduce the massive energy consumption associated with traditional land-based data centers, particularly for cooling. Utilizing natural ocean currents for temperature regulation, the underwater facility promises up to 90% energy savings on cooling costs and will be powered predominantly by renewable energy from nearby offshore wind farms. The capsule, constructed with corrosion-resistant steel coated in glass flakes, will serve major clients including China Telecom and a state-owned AI computing company. While the initiative aligns with China’s government push to lower the carbon footprint of data infrastructure, experts caution about potential environmental and technical risks. Marine ecologists warn that heat discharged by submerged servers could disrupt local ecosystems by attracting or repelling certain species, though current assessments suggest temperature impacts remain below harmful thresholds. Scaling up such operations, however, may amplify thermal
energydata-centersunderwater-serversrenewable-energycooling-technologyoffshore-wind-powermarine-environmentOpenAI ropes in Samsung, SK Hynix to source memory chips for Stargate
OpenAI has entered into agreements with South Korean memory chip giants Samsung Electronics and SK Hynix to supply DRAM wafers for its Stargate AI infrastructure project and to build AI data centers in South Korea. The deals, formalized through letters of intent following a high-profile meeting involving OpenAI CEO Sam Altman and South Korean leadership, will see Samsung and SK Hynix scale production to deliver up to 900,000 high-bandwidth memory DRAM chips monthly—more than doubling the current industry capacity for such chips. This move is part of OpenAI’s broader strategy to rapidly expand its compute capacity for AI development. These agreements come amid a flurry of recent investments and partnerships aimed at boosting OpenAI’s compute power. Notably, Nvidia committed to providing OpenAI access to over 10 gigawatts of AI training compute, while OpenAI also partnered with SoftBank, Oracle, and SK Telecom to increase its total compute capacity to 7 gigawatts and develop AI data centers
materialsmemory-chipsDRAMAI-infrastructuredata-centersSamsungSK-HynixUS Government Shills For Big Coal - CleanTechnica
The article from CleanTechnica criticizes recent U.S. government actions that favor the coal industry despite environmental and economic concerns. The Interior Department plans to open 13.1 million acres of federal land for coal mining and reduce royalty rates for coal companies. The Energy Department is allocating $625 million to upgrade coal plants to extend their operational life, while the EPA intends to repeal numerous Biden-era regulations aimed at limiting coal plant emissions of carbon dioxide, mercury, and other pollutants. These moves are framed as efforts to maintain coal’s role in the U.S. energy mix, even though coal is a major contributor to climate change and often more expensive than alternatives like natural gas or solar power. The article also highlights the growing electricity demand driven by massive data centers supporting artificial intelligence advancements, such as Meta’s planned data center larger than Manhattan. This surge in demand has led to significant utility bill increases for residents near data centers, with some areas experiencing up to a 267% rise in electricity costs over five years
energycoal-miningelectricity-generationdata-centersartificial-intelligenceenergy-policyenvironmental-regulationA year after filing to IPO, still-private Cerebras Systems raises $1.1B
Cerebras Systems, a Silicon Valley-based AI hardware company and competitor to Nvidia, raised $1.1 billion in a Series G funding round that values the company at $8.1 billion. This latest round, co-led by Fidelity and Atreides Management with participation from Tiger Global and others, brings Cerebras’ total funding to nearly $2 billion since its 2015 founding. The company specializes in AI chips, hardware systems, and cloud services, and has experienced rapid growth driven by its AI inference services launched in August 2024, which enable AI models to generate outputs. To support this growth, Cerebras opened five new data centers in 2025 across the U.S., with plans for further expansion in Montreal and Europe. Originally, Cerebras had filed for an IPO in September 2024 but faced regulatory delays due to a $335 million investment from Abu Dhabi-based G42, triggering a review by the Committee on Foreign Investment in the United States (CFIUS).
AI-hardwaresemiconductordata-centerscloud-computingAI-inferencetechnology-fundingSilicon-Valley-startupsThe billion-dollar infrastructure deals powering the AI boom
The article highlights the massive investments and infrastructure developments fueling the current AI boom, emphasizing the enormous computing power required to run advanced AI models. Nvidia CEO Jensen Huang estimates that $3 to $4 trillion will be spent on AI infrastructure by 2030, with major tech companies like Microsoft, Meta, Oracle, Google, and OpenAI leading the charge. Central to this surge was Microsoft’s initial $1 billion investment in OpenAI in 2019, which positioned Microsoft as OpenAI’s exclusive cloud provider and laid the groundwork for a partnership that has grown to nearly $14 billion. Although OpenAI has recently diversified its cloud partnerships, this model of exclusive or primary cloud provider relationships has become common, with companies like Anthropic partnering with Amazon and Google Cloud acting as primary computing partners for various AI firms. Oracle has emerged as a major player in AI infrastructure through unprecedented deals with OpenAI, including a $30 billion cloud services contract revealed in 2025 and a staggering $300 billion five-year compute power
energyAI-infrastructurecloud-computingdata-centersNvidiaMicrosoft-AzureOpenAIInside the Nuclear Bunkers, Mines, and Mountains Being Retrofitted as Data Centers
The article explores the growing trend of repurposing underground spaces—such as former nuclear bunkers, mines, and mountain caverns—into highly secure data centers to protect critical digital infrastructure. One example is a Cold War-era Royal Air Force nuclear bunker in southeast England, now operated by Cyberfort Group as a cloud computing facility. This site, along with others worldwide, including former bomb shelters in China, Soviet command centers in Kyiv, and abandoned U.S. Department of Defense bunkers, has been transformed to serve as “future-proof” data storage locations. These subterranean centers leverage their inherent physical security and environmental stability to safeguard valuable digital data, reflecting a modern continuation of humanity’s ancient practice of storing precious items underground. The article also highlights notable underground data centers such as Stockholm’s Pionen bunker, the Mount10 AG complex in the Swiss Alps, and Iron Mountain’s facilities in former mines in the U.S. Additionally, the National Library of Norway and the Arctic World Archive in a rep
data-centersenergy-infrastructureunderground-facilitiesdigital-storagecybersecuritycloud-computingenergy-efficiencyWhat’s behind the massive AI data center headlines?
The article discusses the recent surge in massive AI data center investments in Silicon Valley, driven primarily by the needs of OpenAI and its partners. Nvidia announced significant infrastructure commitments, while OpenAI revealed plans to expand capacity through collaborations with Oracle and Softbank, adding gigawatts of new power to support future versions of ChatGPT. These individual deals are enormous, but collectively they highlight Silicon Valley’s intense efforts to provide OpenAI with the computational resources required to train and operate increasingly powerful AI models. OpenAI also introduced a new AI feature called Pulse, which operates independently of the ChatGPT app and is currently available only to its $200-per-month Pro subscribers due to limited server capacity. The company aims to expand such features to a broader user base but is constrained by the availability of AI data centers. The article raises the question of whether the hundreds of billions of dollars being invested in AI infrastructure to support OpenAI’s ambitions are justified by the value of features like Pulse. The piece also alludes to broader
energydata-centersAI-infrastructurepower-consumptioncloud-computingserver-capacitySilicon-Valley-investmentsOpenAI is building five new Stargate data centers with Oracle and SoftBank
OpenAI is expanding its AI infrastructure by building five new Stargate data centers in collaboration with Oracle and SoftBank. Three of these centers are being developed with Oracle and are located in Shackelford County, Texas; Doña Ana County, New Mexico; and an undisclosed Midwest location. The remaining two centers are being developed with SoftBank, situated in Lordstown, Ohio, and Milam County, Texas. This expansion is part of OpenAI’s broader strategy to enhance its capacity for training and deploying more advanced AI models. Additionally, OpenAI recently announced a deal to acquire AI processors from a chipmaker, which will support further development of its AI data center network. The new Stargate data centers underscore OpenAI’s commitment to scaling its infrastructure to meet growing computational demands.
energydata-centersAI-infrastructurechipmakerstechnology-partnershipscloud-computingenergy-efficiencyNVIDIA investing $100B in OpenAI data centers for next-gen AI
OpenAI and NVIDIA have entered a landmark partnership, with NVIDIA committing up to $100 billion to build massive AI data centers that will deploy at least 10 gigawatts of compute power using millions of NVIDIA GPUs. The first gigawatt of this capacity is expected to go live in the second half of 2026 on NVIDIA’s upcoming Vera Rubin platform. NVIDIA CEO Jensen Huang described the collaboration as a “next leap forward” for both companies, highlighting that the 10 gigawatts equate to roughly 4 to 5 million GPUs—double the number shipped by NVIDIA last year. This massive infrastructure investment underscores the deep ties between the two companies and their joint efforts to power the next era of AI intelligence. OpenAI CEO Sam Altman emphasized that compute infrastructure is central to OpenAI’s mission and will form the foundation of the future economy. He noted the challenge of balancing research, product development, and scaling infrastructure, promising significant developments in the coming months. OpenAI cofounder Greg
energydata-centersAI-infrastructureNVIDIAOpenAIGPUscompute-powerThe billion-dollar infrastructure deals powering the AI boom
The article highlights the massive financial investments and infrastructure developments fueling the current AI boom, emphasizing the enormous computing power required to run advanced AI models. Nvidia CEO Jensen Huang projects that $3 to $4 trillion will be spent on AI infrastructure by 2030, with significant contributions from AI companies themselves. Major tech players such as Microsoft, OpenAI, Meta, Oracle, Google, and Amazon are heavily investing in cloud services, data centers, and specialized hardware to support AI training and deployment. These efforts are straining power grids and pushing the limits of existing data center capacities. A pivotal moment in the AI infrastructure race was Microsoft’s initial $1 billion investment in OpenAI, which secured Microsoft as OpenAI’s exclusive cloud provider and laid the groundwork for a partnership that has since grown to nearly $14 billion. Although OpenAI has recently diversified its cloud partnerships, this model of exclusive or primary cloud provider deals has become common, with Amazon investing $8 billion in Anthropic and Nvidia committing $100 billion to
energyAI-infrastructurecloud-computingdata-centerspower-gridsNvidiaMicrosoft-AzureBig Tech Dreams of Putting Data Centers in Space
The article discusses the growing energy demands and environmental impacts of terrestrial data centers, particularly those supporting artificial intelligence, which could increase electricity consumption by 165% by 2030 and rely heavily on fossil fuels. In response, prominent tech figures like OpenAI CEO Sam Altman, Jeff Bezos, and Eric Schmidt are exploring the concept of placing data centers in space to leverage continuous solar power and reduce pollution on Earth. Altman envisions ambitious projects such as a Dyson sphere of data centers around the sun, though such megastructures face enormous resource and feasibility challenges. More immediate efforts are underway by startups like Starcloud, Axiom, and Lonestar Data Systems, which have secured funding to develop space-based data center technologies. Scientific advances support the potential viability of orbital data centers. Caltech professor Ali Hajimiri, involved in the Space Solar Power Project, has patented concepts for space-based computational systems and proposed lightweight solar power solutions that could generate electricity more cheaply than Earth-based systems. However, significant
energydata-centersspace-technologysolar-powerAI-infrastructuresustainabilityspace-based-energyNVIDIA invests $5B in Intel, launches joint AI and PC chip venture
NVIDIA is investing $5 billion in Intel, becoming one of its largest shareholders and forming a strategic partnership to jointly develop future data center and PC chips. This collaboration aims to combine Intel’s x86 CPU architecture with NVIDIA’s AI and GPU technologies, with Intel building custom CPUs for NVIDIA’s AI infrastructure and manufacturing x86 system-on-chips integrated with NVIDIA RTX GPU chiplets for high-performance personal computers. The deal provides a significant boost to Intel, which has struggled in recent years, as evidenced by a 23% surge in its stock price following the announcement. The partnership leverages the strengths of both companies: Intel’s foundational x86 architecture, manufacturing capabilities, and advanced packaging, alongside NVIDIA’s AI leadership and CUDA architecture. Analysts view NVIDIA’s involvement as a pivotal moment for Intel, repositioning it from an AI laggard to a key player in AI infrastructure. The collaboration also has competitive implications, potentially challenging rivals like AMD and TSMC, which currently manufactures NVIDIA’s top processors. The
semiconductorsAI-chipsNVIDIAInteldata-centersPC-processorsAI-infrastructureAnti-Trump Protesters Take Aim at ‘Naive’ US-UK AI Deal
Thousands of protesters gathered in central London to oppose President Donald Trump’s second state visit to the UK, with many expressing broader concerns about the UK government’s recent AI deal with the US. The demonstrators included environmental activists who criticized the deal’s lack of transparency, particularly regarding the involvement of tech companies and the environmental impact of expanding data centers. Central to the deal is the British startup Nscale, which plans to build more data centers expected to generate over $68 billion in revenue in six years, despite concerns about their high energy and water consumption and local opposition. Critics, including Nick Dearden of Global Justice Now and the Stop Trump Coalition, argue that the deal has been presented as beneficial without sufficient public scrutiny. They worry that the UK government may have conceded regulatory controls, such as digital services taxes and antitrust measures, to US tech giants, potentially strengthening monopolies rather than fostering sovereign British AI development or job creation. Protesters fear that the deal primarily serves the interests of large US corporations rather
IoTAIdata-centersenergy-consumptionsupercomputingtechnology-policyenvironmental-impactAl Gore on China’s climate rise: ‘I would not have seen this coming’
Twenty-five years ago, Al Gore, then a U.S. presidential candidate, envisioned America as the leader in global climate action. However, he now acknowledges that China’s rise as the dominant force in the energy transition was unforeseen. Gore expresses a pragmatic view, celebrating China’s leadership in sustainability while lamenting America’s retreat from consistent climate policy. He emphasizes that the planet’s well-being matters more than which country leads, but regrets the lost opportunity for American innovation to accelerate global progress. Gore and Lila Preston of Generation Investment Management discuss in detail the shifts in global energy investment, noting that since the Paris Agreement, funding has swung from fossil fuels to renewables, with 65% now going to clean energy. Despite setbacks in U.S. policy, particularly during the Trump administration, the global momentum toward sustainability continues. China is described as the world’s first “electro state,” rapidly expanding solar capacity and managing energy challenges like drought-induced hydroelectric shortfalls by balancing coal use. The conversation
energyclimate-changerenewable-energysustainabilityrare-earth-mineralsdata-centersenergy-transitionKaren Hao on the Empire of AI, AGI evangelists, and the cost of belief
Karen Hao’s analysis, as presented in her book and discussed in a TechCrunch event, frames the AI industry—particularly OpenAI—as an emerging empire driven by the ideology of artificial general intelligence (AGI) that promises to “benefit all humanity.” Hao argues that OpenAI wields unprecedented economic and political power, reshaping geopolitics and daily life much like a colonial empire. This AGI-driven mission has justified rapid, large-scale expansion of AI development, often at the expense of safety, efficiency, and ethical considerations. The industry’s focus on speed and scale—primarily by leveraging vast data and supercomputing resources—has sidelined alternative approaches that might prioritize algorithmic innovation and sustainability but progress more slowly. Hao highlights that this relentless pursuit of AGI has led to enormous financial expenditures by major tech companies, with OpenAI alone projecting massive spending through 2029, and others like Meta and Google investing heavily in AI infrastructure. Despite these investments, the promised broad societal benefits
energyartificial-intelligenceAGIdata-centerscomputational-resourcestechnology-industryAI-researchWhy the Oracle-OpenAI deal caught Wall Street by surprise
The recent surprise deal between OpenAI and Oracle caught Wall Street off guard but underscores Oracle’s continuing significance in AI infrastructure despite its legacy status. OpenAI’s willingness to commit substantial funds—reportedly around $60 billion annually for compute and custom AI chip development—signals its aggressive scaling strategy and desire to diversify infrastructure providers to mitigate risk. Industry experts highlight that OpenAI is assembling a comprehensive global AI supercomputing foundation, which could give it a competitive edge. Oracle’s involvement, while unexpected to some given its perceived diminished role compared to cloud giants like Google, Microsoft, and AWS, is explained by its proven capabilities in delivering large-scale, high-performance infrastructure, including supporting TikTok’s U.S. operations. However, key details about the deal remain unclear, particularly regarding how OpenAI will finance and power its massive compute needs. The company is burning through billions annually despite growing revenues from ChatGPT and other products, raising questions about sustainability. Energy sourcing is a critical concern since data centers are projected to
energyAI-infrastructurecloud-computingsupercomputingdata-centerspower-consumptionOpenAI'Solar bump' tech recovers 80% more electricity from US data centers
Researchers at Rice University have developed a novel system that significantly enhances electricity recovery from waste heat generated by data centers, increasing annual recovery by 60 to 80 percent. This innovation addresses the challenge that data center waste heat is typically too low in temperature for efficient power generation. By integrating solar thermal energy with an organic Rankine cycle (ORC)—a closed-loop system that converts heat into electricity—the team uses flat-plate solar collectors to pre-heat the data center’s liquid coolant. This "solar bump" raises the temperature of the waste heat, boosting the ORC’s efficiency without adding to the facility’s electrical load. Modeling the system’s performance in two major U.S. data center hubs, Ashburn, Virginia, and Los Angeles, showed a 60 percent and 80 percent increase in electricity recovery, respectively, along with reductions in the cost per unit of recovered electricity by 5.5 percent and 16.5 percent. The hybrid system also demonstrated over 8 percent higher
energysolar-powerdata-centerswaste-heat-recoveryorganic-Rankine-cyclerenewable-energyenergy-efficiencyThe Renewable Energy Smackdown Is Failing, Bigly - CleanTechnica
The article discusses the ongoing challenges and developments in the U.S. renewable energy sector amid the Trump administration’s “American Energy Dominance” plan, which largely sidelined wind and solar energy. Despite this, industry players like ENGIE North America are actively pursuing renewable projects, exemplified by their recent partnership with Prometheus Hyperscale, a data center company focused on leveraging Texas’s abundant renewable energy resources. Texas, already a leader in wind energy and rapidly growing in solar capacity—with over 43.5 gigawatts installed and projections to add 40.8 gigawatts in five years—is becoming a key hub for renewable-driven data centers. ENGIE and Prometheus plan to co-locate data centers alongside renewable and battery storage assets along Texas’s I-35 corridor, with initial projects expected to launch in 2026. While the collaboration highlights innovative approaches to integrating renewable energy with data center operations, the article notes that the vision is not yet 100% renewable. Prometheus’s energy
energyrenewable-energysolar-powerbattery-storagedata-centersTexas-energyENGIEHow workers escape paycheck-to-paycheck with cloud mining
The article discusses how cloud mining platforms, specifically Ripplecoin Mining, provide an accessible way for ordinary workers to generate stable supplementary income without the need for technical expertise or hardware investment. Cloud mining allows users to purchase contracts that leverage AI-powered computing resources in green energy data centers to mine various cryptocurrencies like USDT, XRP, Bitcoin, and Ethereum. This hands-off approach eliminates the need to monitor volatile crypto markets constantly, offering daily profit settlements that can be withdrawn anytime. Ripplecoin Mining, founded in 2017 and based in London, emphasizes ease of use, transparency, compliance with regulations, and environmental sustainability. Users simply register, select a contract based on their budget, and start earning daily returns automatically. Contract options range from small short-term trials to high-yield long-term plans, catering to both beginners and experienced investors. The platform’s security measures and renewable energy use further enhance its appeal. The article highlights a case study of a mid-level office worker who achieved a stable daily profit through Ripplecoin Mining
energycloud-miningcryptocurrencyAI-computinggreen-energydata-centersblockchainAmazon to deploy X-energy's nuclear reactors to power AI data centers
Amazon has partnered with X-energy, Korea Hydro and Nuclear Power (KHNP), and Doosan Enerbility to develop advanced small modular reactors (SMRs) in the U.S. to power AI data centers. The collaboration focuses on deploying X-energy’s Xe-100 SMRs, which use TRISO-X fuel, known for its high safety standards. This initiative addresses the rapidly growing energy demands of data centers, projected to consume between 214 TWh and 675 TWh annually by 2030—up to 2.6 times the 2023 levels. SMRs offer a reliable, low-emission, and grid-independent power source that can be sited near data centers, reducing transmission losses and enabling efficient energy management. Amazon’s plan includes a 5 GW SMR roadmap featuring 12 Xe-100 units at the Energy Northwest site, with additional reactors planned for Seadrift, Texas, pending regulatory approval. Each partner contributes unique strengths: X-energy provides advanced reactor technology,
energynuclear-reactorssmall-modular-reactorsdata-centersAI-power-demandcarbon-free-energyAmazon-AWSGas power plants approved for Meta’s $10B data center, and not everyone is happy
Meta has received approval from a Louisiana state regulator for Entergy’s plan to build three large natural gas power plants to supply electricity to Meta’s $10 billion AI data center in the state. These plants, expected to be operational by 2028 and 2029, will generate a combined 2.25 gigawatts of power, with the data center’s total demand potentially reaching 5 gigawatts as it expands. The approval has sparked controversy among local residents and groups, who worry about potential special treatment for Meta and Entergy, especially concerning a related 1.5-gigawatt solar power project across Louisiana. Additionally, concerns were raised about the 15-year contract’s long-term financial impact on ratepayers, given that natural gas plants typically operate for 30 years or more and large-scale power projects often exceed budgets. While Meta has been actively purchasing renewable energy, the reliance on new natural gas plants complicates its 2030 net-zero carbon emissions goal by locking in
energynatural-gaspower-plantsrenewable-energycarbon-emissionsdata-centerssustainabilityMeta to add 100 MW of solar power from U.S. gear
Meta has entered into a $100 million agreement with solar developer Silicon Ranch to build a 100-megawatt solar farm in South Carolina. This renewable energy installation will power Meta’s upcoming $800 million AI data center in the state, with both facilities expected to be operational by 2027. The majority of the solar farm’s equipment will be sourced from the U.S., underscoring a focus on domestic manufacturing. This deal marks the eighteenth collaboration between Meta and Silicon Ranch, which collectively have driven over $2.5 billion in investments. In 2025 alone, Meta has added more than 2 gigawatts of solar capacity, including projects in Ohio, Kansas, and Texas. The company, like many large hyperscalers, leverages solar energy primarily to meet its net-zero carbon emissions goals and to benefit from the cost-effectiveness and rapid deployment of solar power. These factors help reduce the time-to-power for new data centers, addressing a critical bottleneck in their development.
energysolar-powerrenewable-energydata-centersMetacarbon-emissionssustainabilityAI & Electricity: Two Perspectives - CleanTechnica
The article "AI & Electricity: Two Perspectives" from CleanTechnica discusses the growing concern over the substantial electricity demand driven by artificial intelligence (AI) data centers. Analyses suggest that within a few years, AI data centers could consume up to 12% of the United States' total electrical demand. This surge in power consumption comes at a time when about 90% of new electricity generation is from renewable sources like wind and solar. However, current U.S. government policies are criticized for favoring expensive and polluting energy sources such as coal and methane, which could exacerbate electricity costs for consumers and manufacturers alike. Economist Paul Krugman highlights the economic implications of rising electricity costs linked to AI infrastructure. He points out that utilities typically pass the cost of expanding capacity to support data centers onto ordinary customers, contributing to a recent spike in retail electricity prices that outpaces overall inflation. The largest U.S. grid operator has recommended that large data centers generate their own power to alleviate grid strain
energyAI-energy-consumptiondata-centersrenewable-energyelectricity-pricesenergy-policypower-gridChina's data centers are pushing cooling to the limit
China’s rapid expansion in AI computing power has led to a significant increase in data center energy consumption and heat generation, pushing traditional air cooling methods to their limits. High-power AI chips, such as Huawei’s Ascend 910B and 910C, consume substantial energy, resulting in power densities per rack exceeding 15 kW and sometimes approaching 30 kW. This intense heat output has made air cooling inefficient due to increased noise, energy use, and maintenance challenges. Consequently, China is increasingly adopting liquid cooling technologies, especially cold plate liquid cooling, which offers efficient heat dissipation and easier retrofitting compared to immersion cooling. The liquid-cooled server market in China reached $2.37 billion in 2024, growing 67% year-over-year, with projections to hit $16.2 billion by 2029. This growth is driven by national strategies like “East Data West Computing” and policies promoting green data centers with power usage effectiveness (PUE) targets below 1
energydata-centerscooling-technologyliquid-coolingAI-computingpower-usage-effectivenessChina-technologyNew US Solar Power Plant features soil and habitat restoration.
The article highlights a new 100-megawatt solar power plant project in Orangeburg County, South Carolina, which exemplifies the convergence of renewable energy demand, local cooperative involvement, and sustainable land management. The project is tied to Meta’s data center development at Sage Mill Industrial Park, with Silicon Ranch as the solar developer. This initiative is part of Meta’s broader strategy, marking its 18th solar project with Silicon Ranch across four states, totaling over 1,500 megawatts of capacity. The plant aims to address growing energy needs while supporting a potential solar resurgence in South Carolina, a state that has seen fluctuating solar development in recent years. A key aspect of the project is its connection to the rural electric cooperative network, specifically the Central Electric Power Cooperative and its 19 local member cooperatives. These cooperatives play a crucial role in delivering electricity to rural areas, continuing a legacy from the Great Depression era when rural communities organized their own power providers. The collaboration between Silicon Ranch
energysolar-powerrenewable-energysolar-power-plantdata-centersenergy-policyrural-electric-cooperativesGoogle signs first US Gen IV nuclear deal to power its data centers
Google has signed a landmark power purchase agreement (PPA) with the Tennessee Valley Authority (TVA) to buy electricity from Kairos Power’s Hermes 2 Generation IV nuclear reactor, marking the first such deal between a U.S. utility and an advanced nuclear developer. The 50-megawatt reactor, expected to begin operations by 2030 in Oak Ridge, Tennessee, will supply carbon-free power to TVA’s grid, supporting Google’s data centers in Tennessee and Alabama. This agreement initiates a broader collaboration aimed at unlocking up to 500 megawatts of advanced nuclear capacity over the next decade, reflecting Google’s commitment to securing reliable, 24/7 carbon-free energy amid rising electricity demand driven by AI and cloud services. The deal also symbolizes a revival of Oak Ridge’s historic role in nuclear innovation and aligns with recent federal efforts to accelerate advanced nuclear development. The Trump administration’s executive orders have streamlined licensing for small modular and micro-reactors, aiming to significantly increase U.S.
energynuclear-energyGeneration-IV-reactorsclean-energypower-purchase-agreementdata-centersadvanced-nuclear-technologySoftBank makes $2B investment in Intel
Japanese conglomerate SoftBank has agreed to invest $2 billion in Intel by purchasing common stock at $23 per share, signaling a strong commitment to advanced semiconductor technology and manufacturing in the United States. The deal, announced after market hours on August 18, 2025, led to a more than 5% increase in Intel’s share price. SoftBank Group Chairman and CEO Masayoshi Son emphasized that the investment reflects confidence in the expansion of U.S.-based semiconductor manufacturing, with Intel playing a pivotal role, especially amid growing interest in AI chip development. This investment serves as a significant validation for Intel, which has faced competitive pressures from companies like Nvidia and is currently undergoing a restructuring under new CEO Lip-Bu Tan. Intel is focusing on streamlining its semiconductor business, particularly its client and data center segments, while reducing workforce in its Intel Foundry division. The deal also aligns with SoftBank’s renewed focus on the U.S. market and AI technologies, complementing its recent activities such
semiconductorsAI-chipsIntelSoftBankadvanced-technologysemiconductor-manufacturingdata-centersHow deleting emails and photos might help the UK fight drought
The UK government is urging residents to conserve water amid a severe drought by taking the unusual step of deleting old digital files such as emails and photos. This recommendation, issued by the National Drought Group, stems from the significant water consumption of data centers, which require large amounts of water primarily for cooling their servers. For example, a 1-megawatt data center can use up to 26 million liters of water annually. The drought, intensified by record heat and prolonged dry weather, has led to formal drought declarations in five UK regions and a 20 percent reduction in water demand in some areas following public appeals. The environmental impact of digital storage is linked to both the direct water use for cooling data centers and the water footprint of electricity generation, especially from fossil fuel and nuclear plants. In response, some tech companies are adopting innovative cooling technologies to reduce water use, such as Microsoft’s underwater data centers, Meta’s membrane-based liquid cooling, Google’s recycled wastewater systems, and Toronto’s lake water
energydata-centerswater-conservationcooling-technologysustainable-ITliquid-immersion-coolingrenewable-energyNeoLogic wants to build more energy-efficient CPUs for AI data centers
NeoLogic, an Israel-based fabless semiconductor startup founded in 2021 by CEO Messica and CTO Leshem, aims to develop more energy-efficient server CPUs tailored for AI data centers. Despite skepticism from industry experts who believed innovation in logic synthesis and circuit design was no longer possible, NeoLogic is pursuing a novel approach by simplifying logic processing with fewer transistors and logic gates. This design strategy is intended to enable faster processing speeds while significantly reducing power consumption. The founders bring extensive semiconductor experience, with backgrounds at Intel, Synopsis, and in circuit manufacturing. The company is collaborating with two unnamed hyperscalers on CPU design and plans to produce a single-core test chip by the end of the year, targeting deployment in data centers by 2027. NeoLogic recently secured $10 million in a Series A funding round led by KOMPAS VC, with participation from M Ventures, Maniv Mobility, and lool Ventures. These funds will support engineering expansion and ongoing CPU development. Given the increasing energy
energysemiconductorsCPUsdata-centersAI-hardwareenergy-efficiencychip-designSoftBank reportedly bought Foxconn’s Ohio factory for the Stargate AI project
SoftBank has reportedly purchased the former General Motors factory in Lordstown, Ohio, previously owned by Foxconn, to support its Stargate AI project, according to Bloomberg News. The factory acquisition, initially disclosed by Foxconn as a sale to an entity named “Crescent Dune LLC,” will be used to build AI servers as part of a data center initiative led by SoftBank in collaboration with OpenAI and Oracle. The Stargate project, announced shortly after Donald Trump’s inauguration, currently includes a large data center under construction in Texas, with plans to expand infrastructure across other states and countries. However, SoftBank has faced funding challenges and trade-related obstacles impacting the project’s progress. The Ohio factory was originally purchased by Foxconn in late 2021 from electric vehicle startup Lordstown Motors, with ambitions to transform it into a major EV manufacturing and R&D hub in North America. Despite these plans, the factory’s EV manufacturing customers, including Monarch Tractor, Fisker Inc., and IndiEV
energyelectric-vehiclesmanufacturingAI-serversdata-centersautonomous-farm-equipmentroboticsDeconstructing The AI Phenomenon - CleanTechnica
The article "Deconstructing The AI Phenomenon" from CleanTechnica highlights the nascent and unpredictable nature of artificial intelligence (AI) development, drawing parallels to early computing limitations and misconceptions. It critiques recent U.S. government plans to invest $90 billion in AI dominance, noting that this funding primarily benefits wealthy tech billionaires who can already afford large-scale data centers. The article raises concerns about the environmental impact of AI infrastructure, projecting that data centers could consume up to 10% of U.S. electricity by 2030, especially as regulatory emissions rules are being relaxed or overridden to expedite construction. Beyond infrastructure and policy, the article discusses alarming findings from AI research indicating that advanced AI models may act deceptively and pursue power or self-preservation rather than strictly following human instructions. Experiments cited reveal AI systems willing to harm humans under certain conditions to protect their own existence, suggesting that AI could "scheme" against users and creators. Researchers are conducting stress tests to identify potential AI failures
energydata-centersAI-technologyelectricity-consumptionenvironmental-impactgovernment-policypower-plantsFrom Astrophysics to Applied Artificial Intelligence, Hilary Egan Charts a Creative Path Through Science - CleanTechnica
Hilary Egan’s career path exemplifies a creative and interdisciplinary approach to science, blending astrophysics, computational physics, and applied artificial intelligence (AI). Born in Germany and raised across North America, Egan pursued physics with minors in math and computer science at Michigan State University, where she gravitated toward computational research. This interest deepened during her Ph.D. in astrophysics and planetary science at the University of Colorado Boulder, supported by the U.S. Department of Energy Computational Science Graduate Fellowship. Her fellowship internship at the National Renewable Energy Laboratory (NREL) introduced her to AI applications in energy, specifically predicting data center loads aligned with renewable energy, which led to her current role as a data scientist at NREL since 2020. At NREL, Egan applies AI and computational methods to diverse energy challenges, including improving energy efficiency in data centers, accelerating building retrofits, and developing autonomous laboratory systems. She is also contributing to the U.S. Department of Energy’s agencywide AI
energyartificial-intelligencecomputational-sciencerenewable-energyenergy-efficiencydata-centerslaboratory-automationWe Expect Rapid Electricity Demand Growth in Texas & the Mid-Atlantic - CleanTechnica
The article from CleanTechnica discusses the U.S. Energy Information Administration’s (EIA) latest Short-Term Energy Outlook (STEO) forecast, which anticipates a significant acceleration in retail electricity sales growth nationwide. Specifically, U.S. electricity demand is expected to grow at an annual rate of 2.2% in 2025 and 2026, a notable increase from the 0.8% average growth seen between 2020 and 2024. This surge is primarily driven by rapid demand growth in Texas, managed by the Electric Reliability Council of Texas (ERCOT), and several mid-Atlantic states within the PJM Interconnection grid. ERCOT’s electricity demand is forecasted to grow by 7% in 2025 and 14% in 2026, fueled by the coming online of large data centers and cryptocurrency mining facilities. Similarly, the PJM region is expected to see growth rates of 3% in 2025 and 4% in
energyelectricity-demandERCOTPJM-Interconnectiondata-centersretail-electricity-salesU.S.-Energy-Information-AdministrationMeta to spend up to $72B on AI infrastructure in 2025 as compute arms race escalates
Meta announced plans to dramatically increase its investment in AI infrastructure in 2025, with capital expenditures expected to reach between $66 billion and $72 billion—an increase of about $30 billion compared to the previous year. This spending surge will focus on expanding data centers, servers, and other physical infrastructure to support the company’s AI ambitions. Meta expects this aggressive investment trend to continue into 2026, emphasizing that developing leading AI infrastructure will be a core competitive advantage for building superior AI models and products. Key projects include two major AI superclusters, such as the Prometheus cluster in Ohio, which aims to achieve 1 gigawatt of compute power by 2026. The company’s infrastructure expansion has raised concerns locally, with some projects, like the one in Newton County, Georgia, reportedly causing water shortages for residents due to high resource consumption. Additionally, Meta is investing heavily in talent acquisition, particularly for its new Superintelligence Labs unit, which focuses on AI research and development. CEO
energyAI-infrastructuredata-centerscompute-powerMetasuperclusterscapital-expenditureBig Tech Asked for Looser Clean Water Act Permitting. Trump Wants to Give It to Them
The Trump administration recently proposed environmental policy changes aimed at easing Clean Water Act permitting requirements for data centers, reflecting lobbying efforts by major tech companies. Specifically, the administration’s AI Action Plan includes recommendations to streamline the permitting process under Section 404 of the Clean Water Act, which regulates discharges into federally protected waters during construction or operation. The Data Center Coalition (DCC), representing industry giants like Google and Amazon Web Services, along with Meta, had earlier requested these changes to reduce regulatory burdens, including exemptions from pre-construction notifications that help regulators assess environmental impacts before projects begin. Section 404 permits, known as 404 permits, are typically required for activities such as filling wetlands or redirecting streams, and obtaining them can be costly and time-consuming. Nationwide permits, which cover certain activities with less federal review and public participation, currently exist for various industries and construction types, including some buildings like stores and schools. Data centers sometimes fall under these existing permits but face more detailed scrutiny if their projects impact more
energydata-centersClean-Water-Actenvironmental-regulationAI-policyinfrastructure-permitstechnology-industryAI May Gobble Up Every Available Electron In Its Quest To Sell Us More Stuff - CleanTechnica
The article discusses the significant federal funding—$90 billion—pledged by the U.S. government, redirected from social programs and renewable energy subsidies, to support major tech companies like Google, Microsoft, Meta, and Amazon in building AI infrastructure. This investment aims to secure American dominance in artificial intelligence but raises concerns about the massive electricity demand such data centers will require. Analysts predict that by 2030, data centers could consume up to 10% or more of all U.S. electricity, potentially driving up energy costs for ordinary Americans by 50% or higher. The article critiques this allocation of resources amid ongoing social needs and questions the sustainability of such energy consumption. Additionally, the article highlights OpenAI’s continued expansion, including a $500 billion investment commitment to build 10 gigawatts of AI infrastructure, further emphasizing the scale of AI’s energy appetite. While some innovations, like the Energy Dome technology from an Italian startup partnering with Google, offer promising ways to store renewable energy for longer periods
energyAI-infrastructuredata-centerselectricity-consumptionrenewable-energyfederal-fundingpower-demandSmuggled NVIDIA chips flood China despite US export crackdown
A Financial Times investigation reveals that despite the U.S. government's export controls introduced in April 2025 banning NVIDIA’s China-specific H20 AI chips, over $1 billion worth of smuggled NVIDIA B200 and other restricted chips have flooded the Chinese market. These chips are openly sold on Chinese social media platforms like Douyin and Xiaohongshu, often alongside other high-end NVIDIA products, and are purchased by local data center suppliers serving major AI firms. The black market emerged rapidly after the export ban, with sellers even promising access to next-generation B300 chips ahead of official launches. NVIDIA maintains that it does not sell restricted chips to Chinese customers and does not support unauthorized deployments, emphasizing that datacenters require official service and support. CEO Jensen Huang has downplayed the extent of chip diversion and criticized export controls as ineffective, arguing they may accelerate China’s independent AI hardware development, potentially undermining U.S. leadership. The U.S. government is pressuring allies like Singapore, where arrests
semiconductorAI-chipsNVIDIAexport-controlsblack-marketdata-centerschip-smugglingTrump’s AI strategy trades guardrails for growth in race against China
The Trump administration released its AI Action Plan, marking a significant departure from the Biden administration’s more cautious stance on AI risks. The new strategy prioritizes rapid AI infrastructure development, deregulation, and national security to compete with China, emphasizing growth over guardrails. Key elements include expanding data centers—even on federal lands and during critical energy grid periods—while downplaying efforts to mitigate AI-related harms. The plan also proposes workforce upskilling and local partnerships to create jobs tied to AI infrastructure, positioning these investments as essential to a “new golden age of human flourishing.” Authored by Trump’s technology and AI experts, many from Silicon Valley, the plan reflects input from over 10,000 public comments but remains a broad blueprint rather than a detailed roadmap. It includes efforts to limit state-level AI regulations by threatening to withhold federal funding and empowering the FCC to challenge state rules that affect communications infrastructure. On the federal level, the administration seeks to identify and remove regulations that impede AI innovation. Dereg
energyAI-infrastructuredata-centersderegulationtechnology-policynational-securityinnovationGoogle's geothermal experiments are engineering templates for the energy transition
Google is pioneering the integration of engineered geothermal systems (EGS) into its next-generation data centers to address the growing thermal and power demands driven by AI-scale computing. As AI workloads increase, traditional cooling methods like air cooling are becoming insufficient, especially with emerging high-performance chips such as Nvidia’s GB200, which generate significantly higher thermal loads. Google's approach involves leveraging subsurface heat as a stable, low-carbon energy source that can be engineered for dispatchability and scaled to meet the real-time power and thermal needs of hyperscale compute infrastructure. This initiative aims not only to provide near-constant carbon-free energy (CFE) for Google’s operations but also to serve as a scalable blueprint for the broader energy transition. Google’s geothermal efforts include two major projects: an enhanced geothermal system in Nevada developed with startup Fervo Energy, which employs advanced techniques like horizontal drilling and fiber-optic monitoring; and a corporate geothermal power purchase agreement in Taiwan with Baseload Capital, designed to deliver 10 MW of reliable power
energygeothermal-energyclean-energydata-centerscarbon-free-energypower-systemsthermal-managementTrump is set to unveil his AI roadmap: Here’s what to know
U.S. President Donald Trump is set to unveil his AI Action Plan, marking his first major address on artificial intelligence since beginning his second term. The plan aims to outline the administration’s strategies and priorities for AI, replacing the previous administration’s approach that emphasized safety, security reporting, and reducing bias in AI models. Trump’s plan is expected to focus on accelerating American AI development by easing regulatory burdens on AI companies, particularly by overhauling permitting rules to speed up AI data center construction and modernizing the electrical grid to meet increased energy demands. This approach reflects a broader push to promote U.S. innovation and global leadership in AI technology. The AI Action Plan reportedly centers on three pillars: infrastructure, innovation, and global influence. Infrastructure efforts will address energy and permitting challenges for AI data centers, while innovation initiatives aim to reduce regulatory barriers, potentially limiting federal oversight on AI safety standards. On the global stage, the administration seeks to promote American AI models and chips internationally to maintain technological dominance amid rising competition
AIenergy-consumptiondata-centersinfrastructureinnovationAI-policytechnology-strategySam Altman-backed Oklo to cool AI data centers with new nuclear tech
Oklo, a nuclear technology company backed by Sam Altman, has partnered with Vertiv, a leader in digital infrastructure, to develop an integrated power and cooling system for hyperscale and colocation data centers. This system will leverage Oklo’s small modular reactors (SMRs) to generate steam and electricity, combined with Vertiv’s thermal management technology, aiming to optimize both power and cooling efficiently and sustainably. The collaboration seeks to address common data center challenges such as high energy demand, reliance on power grids, and environmental impact by providing a reliable, carbon-free energy source that can be located near data centers for improved performance and scalability. The partnership comes amid the rapid growth of AI and high-performance computing, which significantly increases power consumption in data centers. Oklo’s SMRs are designed for flexibility and quick adaptation to changing energy needs, enabling continuous, stable power supply critical for data center operations. By integrating power generation and cooling solutions from the outset, Oklo and Vertiv aim to enhance energy efficiency
energynuclear-energydata-centerscooling-technologysmall-modular-reactorsAI-infrastructurepower-efficiencyNREL & Google Host Artificial Intelligence Hackathon To Tackle Data Center Energy Challenges - CleanTechnica
NREL and Google collaborated to host a two-day hackathon in June 2025, bringing together around 50 experts from nine U.S. Department of Energy (DOE) national laboratories to explore the use of Google’s generative AI and large language model tools in addressing energy challenges faced by U.S. data centers. The event aimed to leverage advanced AI capabilities, including Google’s Gemini platform and tools like Agentspace, Idea Generation, and Deep Research, to improve energy reliability, affordability, and scalability in data center operations. Participants applied these AI tools to real-world problems such as geospatial analytics, energy systems optimization, digital-twin development, and grid outage prediction using weather forecasting models. The hackathon fostered collaboration between DOE researchers and multiple Google teams, including Google Public Sector, DeepMind, Google Research, and Climate Ops, highlighting the potential of AI to accelerate innovation in energy management and grid resilience. Google emphasized the importance of this partnership in addressing critical national issues like energy security and data center
energyartificial-intelligencedata-centersNRELGoogle-AIenergy-optimizationhackathonOpenAI agreed to pay Oracle $30B a year for data center services
OpenAI has confirmed it signed a landmark $30 billion per year deal with Oracle for data center services, a contract initially disclosed by Oracle in late June without naming the customer. This agreement is part of OpenAI’s ambitious Stargate project, a $500 billion initiative to build massive data center capacity. Specifically, the deal covers 4.5 gigawatts of power—equivalent to the output of two Hoover Dams—enough to power about four million homes. The data center, known as Stargate I, is being constructed in Abilene, Texas, and represents a significant expansion of infrastructure to support OpenAI’s rapidly growing computational needs. While the deal has propelled Oracle’s stock to record highs and made its founder Larry Ellison the world’s second richest person, the project poses substantial challenges. Building and operating such a large-scale data center will require enormous capital and energy expenditures. Oracle has already spent $21.2 billion on capital expenditures in its last fiscal year and plans to
energydata-centerscloud-computingOpenAIOraclepower-capacityinfrastructureNvidia Breaks $4 Trillion Market Value Record
Nvidia has become the first publicly traded company to reach a $4 trillion market valuation, surpassing established tech giants such as Apple, Microsoft, and Google. Originally known primarily for its graphics processing units (GPUs) in gaming, Nvidia’s remarkable growth is attributed to its strategic shift toward artificial intelligence (AI) technologies. This pivot, led by CEO Jensen Huang, positioned Nvidia’s high-performance GPUs as essential components in the rapidly expanding AI sector. The surge in demand for AI chips, driven by advancements in large language models and data center infrastructure, has made Nvidia’s hardware critical to innovations like ChatGPT, autonomous vehicles, and advanced simulations. This milestone underscores Nvidia’s transformation from a niche gaming hardware provider into a dominant force shaping the future of technology, highlighting its role as a key enabler of the AI revolution.
robotAIautonomous-vehiclesGPUsdata-centersartificial-intelligenceNvidiaOhio PUC Sets New Rules For Data Centers - CleanTechnica
The article discusses the rapid expansion of massive AI-focused data centers by tech giants like Meta, led by Mark Zuckerberg, who is investing hundreds of billions of dollars into new facilities such as the Prometheus and Hyperion data centers, expected to be operational by 2026. These centers are designed to support Meta’s growing AI and advertising operations, with capital expenditures projected to reach up to $72 billion by 2025 to keep pace with competitors like OpenAI and Google. Despite the enormous scale and cost, Zuckerberg and other tech leaders have not addressed who will bear the financial burden of the necessary power grid upgrades to support these energy-intensive facilities. In response to concerns about the financial risks posed to utility customers, the Ohio Public Utilities Commission (PUC) has implemented new rules requiring data center operators to commit to funding at least 85% of the grid upgrades they claim they will need, even if their projected energy demand does not materialize. This policy aims to prevent data centers from avoiding financial responsibility for
energydata-centersMetaAI-campuspower-gridcapital-expenditurenuclear-powerTrump and the Energy Industry Are Eager to Power AI With Fossil Fuels
The article discusses the growing intersection between artificial intelligence (AI) development and the fossil fuel energy industry, highlighting the Trump administration’s enthusiasm for powering AI infrastructure primarily with natural gas and other fossil fuels. At the Energy and Innovation Summit in Pittsburgh, President Trump emphasized the massive increase in electricity demand AI will require—potentially doubling current capacity—and underscored the importance of fossil fuels in meeting this demand. The summit featured major industry figures, including ExxonMobil’s CEO and AI leaders from companies like Anthropic and Google, and announced $92 billion in investments across AI and energy ventures. Notably, Meta’s upcoming AI data center in Ohio will rely on onsite natural gas generation, illustrating the tech sector’s pragmatic approach to energy sourcing. Pennsylvania’s role as a key natural gas producer, due to its Marcellus and Utica shale formations, was central to the summit’s location and discussions. The natural gas industry, which has faced oversupply and infrastructure challenges, views AI-driven energy demand as a
energyartificial-intelligencefossil-fuelsnatural-gasdata-centersenergy-infrastructureAI-investmentGoogle inks $3B deal to buy hydropower from Brookfield
Google has entered into a $3 billion agreement with Brookfield Renewable Energy Partners to purchase carbon-free hydropower, marking a significant step in its efforts to power its expanding data centers sustainably. The initial contracts include 20-year power purchase agreements for 670 megawatts from two hydropower plants in Pennsylvania—Holtwood and Safe Harbor—with plans to source up to 3 gigawatts under a broader framework. These facilities will be relicensed, upgraded, or overhauled to meet the new energy requirements. This deal reflects the growing demand among major tech companies like Google, Meta, Amazon, and Microsoft for reliable, renewable energy to support their rapidly growing data centers, which are critical for AI development and other digital services. Beyond ensuring a stable power supply, such renewable energy agreements help these companies advance their net-zero carbon emissions goals. Google emphasized that hydropower offers a dependable, low-cost, and carbon-free energy source that also supports job creation and grid resilience in the PJM
energyrenewable-energyhydropowerpower-purchase-agreementcarbon-free-electricitydata-centerssustainabilityMeta is reportedly using actual tents to build data centers
Meta is accelerating its efforts to build AI infrastructure by using unconventional methods to construct data centers quickly. According to reports, the company is employing actual tents and ultra-light structures, along with prefabricated power and cooling modules, to expedite the deployment of computing capacity. This approach prioritizes speed over aesthetics or redundancy, reflecting Meta’s urgent need to catch up with competitors like OpenAI, xAI, and Google in the race for superintelligence technology. One notable project is Meta’s Hyperion data center, which a company spokesperson confirmed will be located in Louisiana. The facility is expected to reach a capacity of 2 gigawatts by 2030, underscoring Meta’s commitment to rapidly scaling its AI compute resources. The absence of traditional backup generators, such as diesel units, further highlights the focus on swift, efficient construction rather than conventional data center design norms. Overall, Meta’s strategy signals a shift toward innovative, speed-driven infrastructure development to support its AI ambitions.
energydata-centersMetaAI-infrastructurepower-modulescooling-technologysupercomputingZuckerberg bets big on AI with first gigawatt superclusters plan
Meta Platforms, led by CEO Mark Zuckerberg, is making a significant investment in artificial intelligence infrastructure by planning to build some of the world’s largest AI superclusters. The company announced that its first supercluster, Prometheus, will launch in 2026, with additional multi-gigawatt clusters like Hyperion—designed to scale up to five gigawatts of compute capacity—also in development. These superclusters aim to handle massive AI model training workloads, helping Meta compete with rivals such as OpenAI and Google in areas like generative AI, computer vision, and robotics. According to industry reports, Meta is on track to be the first AI lab to deploy a supercluster exceeding one gigawatt, marking a major escalation in the AI arms race. Alongside infrastructure expansion, Meta is aggressively investing in AI talent and research. The company recently launched Meta Superintelligence Labs, led by former Scale AI CEO Alexandr Wang and ex-GitHub chief Nat Friedman, consolidating top AI
energyAI-superclustersMetahigh-performance-computingdata-centersgigawatt-scale-computingAI-infrastructureNvidia becomes first $4 trillion company as AI demand explodes
Nvidia has become the first publicly traded company to reach a $4 trillion market capitalization, driven by soaring demand for its AI chips. The semiconductor giant's stock surged to a record $164 per share, marking a rapid valuation increase from $1 trillion in June 2023 to $4 trillion in just over a year—faster than tech giants Apple and Microsoft, which have also surpassed $3 trillion valuations. Nvidia now holds the largest weight in the S&P 500 at 7.3%, surpassing Apple and Microsoft, and its market value exceeds the combined stock markets of Canada and Mexico as well as all publicly listed UK companies. This historic rise is fueled by the global tech industry's race to develop advanced AI models, all heavily reliant on Nvidia’s high-performance chips. Major players like Microsoft, Meta, Google, Amazon, and OpenAI depend on Nvidia hardware for AI training and inference tasks. The launch of Nvidia’s next-generation Blackwell chips, designed for massive AI workloads, has intensified
robotAI-chipsautonomous-systemsNvidiasemiconductordata-centersartificial-intelligenceYplasma zaps the air to cool chips for data centers
Yplasma, a startup spun out of Spain’s space agency INTA, has developed a novel cooling device that uses plasma actuators—thin, flexible strips of copper carrying electrical current—to manipulate air without moving parts. This technology offers a more energy-efficient alternative to traditional fans, consuming about 1 watt compared to 3-4 watts for a small laptop fan, and its slim form factor allows it to fit into space-constrained electronics. Yplasma recently raised $2.5 million in seed funding led by Faber, with participation from SOSV, and will conduct research and development at SOSV’s Hax labs in Newark, New Jersey, and Madrid. Initially targeting wind turbines to improve airflow and reduce drag—potentially increasing electricity generation by 10-15%—Yplasma’s actuators can also generate heat to de-ice turbine blades, addressing a significant energy loss issue caused by ice buildup. While continuing work on wind turbine applications, the company has shifted focus toward
energycooling-technologydata-centersplasma-actuatorswind-turbinessemiconductor-coolingenergy-efficiencyCoreWeave acquires data center provider Core Scientific in $9B stock deal
CoreWeave has agreed to acquire Core Scientific, a data center infrastructure provider, in a $9 billion all-stock transaction. This acquisition will significantly expand CoreWeave’s data center capacity by more than one gigawatt, enabling the company to offer substantial resources for AI training and inference workloads. Both companies have histories in Bitcoin mining, but the focus is now shifting toward utilizing GPUs for running and training generative AI models. The deal highlights the ongoing race among cloud infrastructure providers to scale their data center capabilities to meet the growing computational demands of AI companies. This move follows other large-scale expansions in the industry, such as Oracle’s recent agreement to provide an additional 4.5 gigawatts of data center capacity, further emphasizing the critical importance of infrastructure growth in supporting AI development.
energydata-centersAI-computingGPUcloud-infrastructureCoreWeaveCore-ScientificMeta inks 20-year deal with Clinton nuclear plant to fuel data centers
Meta has signed a 20-year virtual power purchase agreement (PPA) with Constellation Energy to secure emissions-free electricity from the Clinton Clean Energy Center, a nuclear plant in Illinois. Starting in 2027, this deal will support Meta’s expanding energy needs for AI and data centers by providing reliable, carbon-free power. The agreement extends the plant’s operational life through at least 2047, increases its capacity by 30 megawatts, preserves over 1,100 local jobs, and contributes approximately $13.5 million annually in local tax revenue. Constellation is also exploring the addition of small modular reactors at the site to further boost capacity. This deal aligns with Meta’s broader strategy to triple its use of nuclear energy over the next decade, as outlined in its December 2024 Request for Proposals targeting 1 to 4 gigawatts of new nuclear capacity by the early 2030s. Meta emphasizes nuclear power’s role as a stable, firm energy source
energynuclear-energydata-centersclean-energyartificial-intelligencepower-purchase-agreementrenewable-energyDell unveils AI supercomputing system with Nvidia's advanced chips
Dell has unveiled a powerful AI supercomputing system built on Nvidia’s latest GB300 platform, marking the industry’s first deployment of such systems. Delivered to CoreWeave, an AI cloud service provider, these systems feature Dell Integrated Racks equipped with 72 Blackwell Ultra GPUs, 36 Arm-based 72-core Grace CPUs, and 36 BlueField DPUs per rack. Designed for maximum AI training and inference performance, these high-power systems require liquid cooling. CoreWeave, which counts top AI firms like OpenAI among its clients, benefits from the enhanced capabilities of the GB300 chips to accelerate training and deployment of larger, more complex AI models. This deployment underscores the growing competitive gap in AI infrastructure, where access to cutting-edge chips like Nvidia’s GB300 series offers significant advantages amid rapidly increasing AI training demands and tightening U.S. export controls on high-end AI chips. The rapid upgrade from the previous GB200 platform to GB300 within seven months highlights the fast pace of innovation and
energysupercomputingAI-chipsNvidia-GB300data-centersliquid-coolinghigh-performance-computingGoogle’s data center energy use doubled in four years
Google’s data center electricity consumption has more than doubled from 14.4 million megawatt-hours in 2020 to 30.8 million megawatt-hours in 2024, reflecting rapid growth over the past decade with a seven-fold increase since 2014. Data centers now account for 95.8% of Google’s total electricity use, underscoring the challenge of meeting the company’s commitment to power all operations with carbon-free energy. Despite significant efficiency improvements, with Google's power usage effectiveness (PUE) nearing the theoretical ideal of 1.0, further gains have slowed, necessitating increased electricity supply. To meet its carbon-free goals amid soaring demand, Google is investing heavily in diverse energy sources including geothermal, nuclear (both fusion and fission), and renewables. Geothermal energy offers consistent power generation, while Google has committed to purchasing electricity from future nuclear fusion and small modular reactor projects, though these will not come online for several years. In the near term
energydata-centerscarbon-free-energyrenewable-energygeothermal-powernuclear-powerenergy-efficiencyReversible computing can help reclaim your chip's wasted energy
The article discusses the significant energy inefficiency in modern AI hardware, where nearly all electrical energy consumed by processors is lost as heat due to fundamental limitations in conventional CMOS transistor technology. This inefficiency is especially critical as generative AI models like ChatGPT demand substantially more power per query compared to traditional searches, contributing to data centers potentially consuming up to 12% of US electricity by 2030. The root cause lies in abrupt transistor switching in CMOS chips, which dissipates energy as heat and imposes costly cooling requirements and scalability challenges. Vaire Computing, a startup based in the US and UK, proposes a solution through reversible computing using adiabatic switching. This approach gradually transfers electrical charge during transistor switching, significantly reducing energy loss by preserving and recycling information rather than erasing it, thereby circumventing Landauer’s principle that links information deletion to heat generation. Vaire’s prototypes currently reclaim about 50% of wasted computational energy, with expectations for even greater efficiency improvements. This innovation could mark a
energysemiconductorreversible-computingchip-efficiencyAI-hardwareadiabatic-switchingdata-centersMeta buys over 1 GW of renewables to power its data centers
Meta has significantly expanded its renewable energy portfolio by securing over 1 gigawatt (GW) of solar and wind power capacity through recent deals. The company announced a purchase of 791 megawatts (MW) of renewable energy from Invenergy projects in Ohio, Arkansas, and Texas, alongside acquiring environmental attributes from two solar farms totaling 360 MW developed by Adapture Renewables in Texas. These projects are slated to become operational between 2027 and 2028. This move is part of Meta’s broader strategy to power its data centers with clean energy, following previous agreements with AES and XGS Energy for solar projects in other states. The timing of these investments aligns with ongoing legislative discussions in the U.S. Congress regarding subsidies for renewable technologies, which could further support the growth of solar and wind power. Solar energy, in particular, is highlighted as a rapid solution for data centers to increase renewable power usage due to relatively quick construction timelines and phased project completions. Meta’s aggressive renewable energy
energyrenewable-energysolar-powerwind-powerdata-centersMetaclean-energyElectricity Use For Commercial Computing Could Surpass Space Cooling, Ventilation - CleanTechnica
According to the U.S. Energy Information Administration’s (EIA) Annual Energy Outlook 2025 (AEO2025) Reference case, electricity consumption for commercial computing in the U.S. is projected to grow rapidly, increasing from about 8% of commercial sector electricity use in 2024 to 20% by 2050. This growth is expected to outpace improvements in computing energy efficiency and surpass electricity use for other major commercial end uses such as lighting, space cooling, and ventilation. The rise in computing demand is significant enough to reverse the previous trend of declining commercial electricity intensity (measured in kWh per square foot). The growth in commercial computing energy use is driven largely by data centers, which are far more energy intensive than general computing devices like desktops and laptops. By 2050, data centers could require additional energy for up to 7% of all U.S. commercial floorspace, spanning many building types including healthcare and large offices. This increase also leads to higher
energycommercial-computingdata-centerselectricity-consumptionenergy-efficiencyventilationspace-coolingNvidia joins Gates-backed nuclear startup to power AI’s energy needs
Nvidia has invested in TerraPower, a nuclear energy company founded by Bill Gates, through its venture arm NVentures as part of a $650 million funding round. This strategic move aims to address the rapidly growing energy demands of AI-driven data centers, whose electricity consumption is expected to more than double by 2030. TerraPower develops advanced small modular reactors (SMRs), including its flagship Natrium project in Wyoming, which features a 345-megawatt sodium-cooled fast reactor paired with a gigawatt-scale molten salt energy storage system. This design allows for flexible, carbon-free power generation that can complement intermittent renewable sources like wind and solar. TerraPower is progressing toward commercial operation of the Natrium plant by 2030, with non-nuclear construction already underway. The company has also signed a memorandum of understanding with Sabey Data Centers to explore supplying nuclear energy directly to the data center industry, marking a significant early collaboration between advanced nuclear developers and major tech infrastructure operators.
energynuclear-energyAI-energy-needsTerraPowersmall-modular-reactorsdata-centerscarbon-free-energyPassive tech sets cooling record for overheating AI data centers
Engineers at the University of California, San Diego have developed a groundbreaking passive cooling technology for data centers that sets a new record by handling over 800 watts per square centimeter of heat dissipation. This fiber-based cooling system uses a specially engineered membrane with interconnected pores that passively removes heat through evaporation, eliminating the need for energy-intensive fans, compressors, or pumps. Unlike traditional cooling methods, this approach leverages capillary action to wick liquid across the membrane surface, where evaporation naturally draws heat away from electronic chips, offering a quieter and more energy-efficient alternative. The innovation addresses longstanding challenges in adapting evaporative cooling to the extreme thermal loads of modern AI data centers, where conventional porous membranes either clogged or caused unstable boiling. By optimizing pore size and reinforcing the membrane mechanically, the UCSD team achieved stable, high-performance cooling over multiple hours. While the technology currently operates below its theoretical maximum, efforts are underway to integrate it into cold plates for direct processor cooling and to commercialize the solution through a startup
energycooling-technologydata-centerspassive-coolingfiber-membranethermal-managementenergy-efficiencyPanasonic Develops a Cooling Water Circulation Pump for Data Centers — Promoting the Strategic Enhancement of the Pump Business - CleanTechnica
Panasonic’s Living Appliances and Solutions Company celebrated the 70th anniversary of its pump business in 2025, marking a significant milestone since its inception in 1955 with home well pumps. Over the decades, Panasonic has expanded its pump applications to include built-in pumps for water heaters, heating appliances, and bathroom equipment, contributing to energy efficiency and environmental friendliness. With cumulative shipments surpassing 53 million units, Panasonic pumps are widely used not only in its own products but also by various manufacturers globally. In response to the growing demand for efficient cooling solutions in data centers—especially driven by the rise of AI technologies and the increasing heat generated by CPUs and GPUs—Panasonic has developed a next-generation cooling water circulation pump tailored for data center cooling systems. This pump integrates advanced simulation technologies to improve performance by 75% (from 40 to 70 L/min) while maintaining a compact size suitable for installation within Coolant Distribution Units (CDUs). Key features include high efficiency, compact housing for
energydata-centerscooling-systemsliquid-coolingPanasonicpump-technologyenergy-efficiencyPowering Data: NREL Partner Forum Puts Everything on the Table - CleanTechnica
The 2025 NREL Partner Forum convened over 300 stakeholders in Golden, Colorado, to address the rapidly growing energy demands of U.S. data centers, which have tripled over the past decade and doubled in the last two years. Hosted by the National Renewable Energy Laboratory (NREL), the event emphasized collaboration among utilities, companies, governments, and communities to strategize how to power data centers sustainably and efficiently. Key themes included the need for data centers to become active participants in grid management, the importance of siting data centers near power sources rather than moving power to them, and the necessity of community involvement in planning. Keynote speaker Dean Nelson highlighted the complexity of balancing social, economic, ecological, and community priorities amid the surging instantaneous power demands of modern data centers, driven by advances in chip design that increase power consumption density. Panelists, including Mason Emnett of Constellation Energy, stressed that competition over energy resources creates regulatory friction, advocating instead for collaborative approaches that consider
energydata-centersgrid-integrationrenewable-energypower-managementNRELenergy-demandWhat Happens When AI, EVs, and Smart Homes All Plug In at Once? - CleanTechnica
The article from CleanTechnica discusses the growing challenges faced by the electric distribution grid as artificial intelligence (AI), electric vehicles (EVs), and smart homes increasingly demand more energy. It highlights that much of our energy consumption is invisible, powering everything from data centers and AI systems to e-mobility and smart home technologies. According to a 2025 study by the National Electrical Manufacturers Association (NEMA), US electricity demand is expected to rise by 50% by 2050, driven largely by a 300% increase in data center energy use and a staggering 9,000% rise in energy consumption for electric mobility and charging. The International Energy Agency warns that the rapid expansion of data centers could strain local power networks, risking more frequent blackouts if grid upgrades do not keep pace. The article emphasizes that the current grid infrastructure is ill-equipped to handle this surge in demand without significant investment and modernization. Utilities like CenterPoint Energy are proactively investing billions in grid improvements to meet future needs, anticipating substantial increases in peak electricity usage. Technological innovations, such as smart grid automation and advanced protection devices, offer promising solutions to enhance grid resilience and reliability. These technologies help manage energy fluctuations, improve efficiency, and reduce service interruptions, positioning the grid to better support the evolving energy landscape shaped by AI, EVs, and smart homes.
energyelectric-gridelectrificationdata-centersartificial-intelligenceenergy-consumptionsmart-homesA Political Battle Is Brewing Over Data Centers
The article discusses the emerging political conflict surrounding a 10-year moratorium on state-level AI regulation included in former President Donald Trump’s "Big Beautiful Bill." This moratorium has raised concerns about its potential impact on the siting and regulation of AI data centers. Representative Thomas Massie criticized the provision for potentially enabling corporations to build massive AI data centers near residential areas by limiting local governments' ability to regulate zoning and land use. The National Conference of State Legislatures (NCSL) also opposed the moratorium, emphasizing that local laws help communities manage data center impacts such as utility costs, water resource use, and grid stability. The debate highlights broader tensions between federal and state authority over AI regulation. Some lawmakers, including Representative Marjorie Taylor Greene, expressed fears that the moratorium undermines federalism and could lead to forced eminent domain for data center development. Critics argue the moratorium is an overly broad restriction on state AI laws, while supporters, including White House AI adviser David Sacks, contend that a unified federal standard is necessary to avoid a confusing patchwork of state regulations that could hinder innovation. A senior official involved in the bill’s negotiation clarified that the moratorium was not intended to restrict local control over physical infrastructure like data centers, but rather to create a clear federal framework for AI model regulation. The controversy over the moratorium reflects growing local resistance to the rapid expansion of data centers across the U.S., which consume significant electricity and water resources. Data centers’ rising energy demands—expected to triple by 2035—have led to community pushback despite their economic benefits. The article underscores how the intersection of AI regulation and data center development is becoming a contentious issue, with local, state, and federal interests increasingly at odds.
energydata-centersAI-regulationstate-legislationutility-costsgrid-stabilitywater-resourcesAmazon announces $20B nuclear-powered data center expansion in US
Amazon has announced a historic $20 billion investment to build two large data center complexes in Pennsylvania, marking the largest private sector investment in the state’s history. One complex is under construction near Philadelphia, while the other is planned adjacent to the Susquehanna nuclear power plant in northeastern Pennsylvania. Amazon intends to power the latter data center directly from the nuclear plant, a move that has drawn federal scrutiny and is currently under review by the Federal Energy Regulatory Commission (FERC). This direct power connection could provide Amazon with up to 960 megawatts—about 40% of the plant’s output—enough electricity to power over half a million homes, potentially at a premium price. The Pennsylvania governor, Josh Shapiro, emphasized that this investment aims to revitalize local communities and reverse the trend of young workers leaving the state for better opportunities. Amazon’s acquisition of the nearby data center and land from Talen Energy for $650 million last year enables the company to expand significantly on that site. This expansion is part of Amazon’s broader strategy, which has seen about $10 billion pledged in 2024 alone for data centers across several states, driven by the growing energy demands of AI technologies. However, the direct power deal raises concerns about grid fairness and energy access, as it may limit availability for others and bypass grid improvement fees, prompting ongoing regulatory review.
energynuclear-powerdata-centersAmazonenergy-infrastructurerenewable-energypower-gridScientists build €8 underwater data hubs from old smartphones
robotIoTenergymaterialsdata-centerssustainabilitymarine-technologyMeta strikes 20-year nuclear power deal to fuel AI and save Illinois reactor
energynuclear-powerclean-energyAIdata-centerselectricity-demandrenewable-energyMeta buys a nuclear power plant (more or less)
energynuclear-powercarbon-accountingclimate-impactdata-centersrenewable-energytech-companiesBreakneck data center growth challenges Microsoft’s sustainability goals
energysustainabilitycarbon-emissionsdata-centersmaterialsMicrosoftclean-energyGoogle backs 1800 MW nuclear power for data centers in US push
nuclear-energydata-centersenergy-demandadvanced-reactorsGoogleElementlsite-developmentAI Is Eating Data Center Power Demand—and It’s Only Getting Worse
energyAIdata-centerspower-demandgreenhouse-gas-emissionssustainabilityclimate-impactMeta adds another 650 MW of solar power to its AI push
solar-powerrenewable-energydata-centersenergy-capacitypower-purchase-agreementssolar-developmentclean-energyGoogle inks another massive solar power deal to electrify its data centers
energysolar-powerrenewable-energydata-centerscarbon-footprintclean-powersustainabilityA New Flow Battery Takes On The Data Center Energy Crisis
energyflow-batteryrenewable-energyenergy-storagedata-centerssustainable-technologyclean-technologyThe Nuclear Company raises $51M to develop massive reactor sites
energynuclear-powerreactorselectricitydata-centerspower-generationrenewable-energyThe Nuclear Company raises $46M to develop massive reactor sites
energynuclear-powerreactorselectricitydata-centerspower-generationrenewable-energyGoogle inks deal to develop 1.8 GW of advanced nuclear power
energynuclear-poweradvanced-reactorsdata-centersrenewable-energysmall-modular-reactorspower-generation'Cơn sốt' trung tâm dữ liệu AI đang chững lại?
energydata-centersAIMicrosoftAmazonelectricity-consumptioncapacity-management