Nvidia liquid cooling system slashes data center water use, but AI's broader water problem persists

Nvidia wants to cut data center water use, but that's not the same as fixing AI's water problem

Nvidia just announced a warm-water cooling system that it says can dramatically reduce the amount of water a data center uses -- eliminating "pretty much all water usage" inside the data center itself, according to an Nvidia executive in a press release. "The water consumption challenge for data centers is largely solved," Josh Parker, chief sustainability officer at Nvidia, recently told Axios. But that's only part of the water story. As long as AI data centers run on fossil fuels -- a choice tech companies are increasingly making -- the savings stop at the data center's walls. The core issue is how Nvidia measures data center water use. According to its blog post, the company essentially draws a line around the data center. Anything inside gets counted, anything outside gets ignored. To be fair, Nvidia's system does appear to deliver on its facility-level promise -- the coolant runs in a closed loop, filled once and recirculated for the life of the facility, meaning no new water is consumed to cool the chips. In favorable climates, the company says, that can amount to a 100% reduction in on-site water use. TechCrunch has asked Nvidia to clarify the matter, and we'll update this article if we receive a reply. The problem is, water use outside of the data center -- primarily in electricity generation and chip manufacturing -- can double or triple the total water footprint of a facility. That means Nvidia's solution addresses about a quarter to a third of AI data centers' total water consumption. The new system is clever, pumping coolant into racks at 45˚ C (113˚ F). That's hot for humans but not for computer chips. After passing through a server, the coolant emerges at 55˚ C (131˚ F), Nvidia said, bringing a significant amount of heat away from the hardware. At that temperature, the outside air in most climates can draw heat off passive radiators without evaporative cooling or, in some cases, fans. A data center without fans or chillers would not only use less water, it would be more efficient and quieter. But no data center can operate without an electricity supply, and many types of power plants are themselves major water consumers. Fossil fuel power plants are one of the largest water users in the U.S., consuming 2.7 billion gallons per day, according to the U.S. Geological Survey -- most of it for evaporative cooling. Natural gas power plants use 1.17 liters of water for every kilowatt-hour of electricity they generate, according to a recent study. Coal plants are even more water-intensive, using 2.2 liters per kilowatt-hour. Fossil fuel power plants collectively generate about half of all data center power today, according to the IEA. Hydropower dams, which supply around 10% of data center power, don't consume water in the same direct way, but evaporation from their reservoirs into 6.8 liters lost per kilowatt-hour generated. Geothermal, a source tech companies are starting to explore, varies widely -- it can be higher or lower depending on the specific technology. Some enhanced geothermal startups, like Fervo, have pledged to use mostly "degraded" water that would otherwise go unused. Wind and solar power, on the other hand, use vanishingly small amounts of water, about 0.01 liters and 0.03 liters per kilowatt-hour, respectively -- figures that include the water needed for manufacturing and cleaning solar panels. While renewables are providing a growing share of new electricity capacity, natural gas and coal are expected to provide more than 40% of new electricity needed to meet data center demand through 2030, the IEA projects. Without major changes to that trajectory, data centers will still consume large amounts of water, regardless of what Nvidia does inside its walls.

Nvidia announces liquid cooling system that runs 'hotter than a hot tub' -- promises to reduce electricity consumption and cut water use by up to 100%, but sustainability challenges remain

AI GPU maker Nvidia just announced a "hotter than a hot tub" liquid cooling system that it says will cut water and electricity use. According to the company, this new solution will run coolant -- composed of 75% water and 25% propylene glycol -- at 113 degrees F (45 deg C). By comparison, the water in hot tubs hovers at 100 to 104 degrees F (38 to 40 deg C). This feels counterintuitive, but the company says that the "cool" water is enough to handle the heat generated by Nvidia's Rubin chips and exit the system at 131 degrees F (55 deg C). Traditional water-cooling methods, especially those that use chillers, often account for nearly 40% of a data center's power consumption. Aside from that, these systems must often deal with water loss through evaporation. On the other hand, air-cooled facilities also use a considerable amount of electricity, plus they also generate noise pollution. On the other hand, Nvidia says that this new solution uses a lot fewer resources because of its higher base temperature. Since 113 degrees F is often higher than ambient temperature, data centers can simply rely on outdoor dry coolers to expel the heat to the environment. This is also a closed-loop system; Nvidia claims an up to 100% reduction in water consumption -- it's "filled once and runs closed for the life of the facility." This solution is most effective in regions with cooler climates, but it should still be effective in warmer areas as long as the ambient temperature is below 113 degrees F. Data centers that face occasional temperature swings that exceed this limit may still be required to turn on their chillers. Nevertheless, this should still reduce resource consumption, as it only needs to run them a few times per year. Aside from that, this should also allow these systems to run more efficiently, as the chillers don't have to work as hard to hit the target temperature. It's estimated that increasing a chiller plant's target temperature by 1.8 degrees F (1 degree C) would reduce electricity costs by 4%. This means that data centers would save significantly on power consumption if they set their chiller units to the 70 to 75 degrees F (21 to 24 degrees C) that traditional chillers run, according to Vertiv, to the 113 degrees F (45 degrees C) that Nvidia recommends for its Rubin chips. This solution addresses several of the issues that many local governments raised that led to the delay of more than 75 data centers earlier this year. However, it will likely take time for this cooling system to roll out to new and existing projects, so we expect the delays and resistance to continue until Nvidia's liquid cooling system gains wider adoption. Furthermore, this only addresses the water use of the data center itself -- the GPU servers themselves still require massive amounts of electricity. Unfortunately, most of the power used by data centers, at least in the United States, comes from fossil fuel power plants, which themselves consume a lot of water. Developments that aren't tied to the grid and get their electricity from natural gas turbines may not need as much water, but residents are concerned about the pollution they generate. Still, this new cooling solution is a step in the right direction to help make AI more sustainable. Follow Tom's Hardware on Google News, or add us as a preferred source, to get our latest news, analysis, & reviews in your feeds.

Hotter Than a Hot Tub: The 45°C Breakthrough to Cool AI's Biggest Machines

Your browser doesn't support HTML5 video. Here is a link to the video instead. Hot tubs sit at about 38 to 40 degrees Celsius, warm enough that most people can only soak for about 15 minutes. NVIDIA's newest AI servers can run their cooling liquid even hotter -- up to 45 degrees Celsius, or 113 degrees Fahrenheit. That higher temperature limit is precisely what makes them more energy efficient. The Rubin generation of NVIDIA AI infrastructure is the world's first to achieve 100% liquid cooling -- every chip, every networking component, cooled entirely by liquid in a closed loop with no fans anywhere in the system. This liquid cooling methodology is outlined in the NVIDIA DSX AI factory reference design, a guide that outlines best practices to design, build and operate the entire AI factory infrastructure stack. Although each generation offers significantly more computing power for each watt, full liquid-cooled AI compute infrastructure enables data centers to dramatically reduce cooling energy consumption -- making a meaningful difference to overall data center energy use at hyperscale. "The NVIDIA DSX reference design for AI factories has zero water consumption -- we have eliminated massive amounts of power usage and pretty much all water usage," said Ali Heydari, director of data center cooling and infrastructure at NVIDIA. "With dry-cooler-based designs, it's a closed-loop system with no evaporative water cooling -- outside of maybe 1% of the year when we might need chillers in some climates." Historically, cooling alone has accounted for up to 40% of a data center's electricity consumption, making it one of the most significant areas where efficiency improvements can drive down both operational expenses and energy demands. Industry estimates suggest that raising chiller plant temperatures by just one degree can cut cooling energy costs by about 4%. At scale, those savings add up quickly. A 50-megawatt hyperscale facility can save over $4 million annually in cooling-related energy and water costs by moving to liquid-cooled infrastructure. In favorable climates, NVIDIA's 45-degree liquid-cooling architecture can enable chiller-less operation with dry coolers, reducing facility cooling water consumption from roughly 2.6 million gallons per megawatt per year for conventional cooling-tower-based systems to near zero -- up to a 100% reduction in water use. The reason: traditional air-cooled data centers depend on large volumes of cooled air to remove heat from IT equipment, often requiring energy-intensive cooling infrastructure during hot weather. With NVIDIA's 45-degree liquid cooling, heat is captured directly at the chip and transported through liquid loops operating at much higher temperatures, allowing outdoor dry coolers to reject heat efficiently for much of the year while significantly reducing mechanical cooling requirements and facility water consumption. The data center ambient temperature is flexible -- warm summer air is fine -- because nothing in the server depends on cool air. The liquid does all the work -- and the same liquid can be recirculated in a closed loop so no new water is consumed to cool the chips. A New Standard for the Industry Because the NVIDIA Rubin platform integrates 100% liquid-cooled infrastructure, every cloud provider and data center operator building for it is making the transition. The ecosystem is keeping pace. Motivair, the advanced cooling division of Schneider Electric, has worked alongside NVIDIA's product roadmap for nearly a decade -- and Richard Whitmore, its president and CEO, says the relationship only intensified as power densities crossed the threshold where air cooling was no longer a viable option. "Once the watts per chip crossed a certain level, liquid cooling became mandatory," said Whitmore. Too Hot to Cool AI Infrastructure Is Hotter Than You'd Think There's a long-standing misconception in the industry that a cold data center is an efficient one. Decades ago, if a data center didn't feel like a walk-in freezer, people would assume something was wrong. In reality, chips can sustain far warmer environments than that instinct suggests. Silicon processors generate enormous internal heat -- the coolant entering a fully liquid-cooled chip at 45 degrees Celsius exits at roughly 55 degrees, having absorbed that heat load across the chip surface. Yet performance doesn't degrade. The processors continue to operate at full performance because liquid-cooled cold plates keep device temperatures within validated operating limits, even with coolant entering the rack at 45 degrees Celsius. No Fans, No Cold Aisles -- A Fundamentally Different Machine Walk into a traditional data center and notice two things: the noise -- cooling fans contribute to total noise levels at or above 85 decibels, loud enough to require ear protection -- and the physical choreography of hot aisles and cold aisles, carefully managed to push cooled air across components. The Rubin architecture changes the picture. Coolant -- 75% water and 25% propylene glycol -- flows through cold plates that sit directly on processors, pulling heat out at the source. Running that coolant at up to 45 degrees Celsius means that in many climates, the facility loop can reject heat without turning on mechanical chillers and noisy fans. That unlocks something beyond energy savings: the possibility of eliminating water consumption entirely. In the right geography -- somewhere with reliably cool outdoor air -- a liquid-cooled data center can reject its heat through coolant distribution units that capture heat directly at the source and transport it to outdoor dry coolers, essentially large radiator coils positioned outside the building. The loop is filled once and runs closed for the life of the facility. And it takes dramatically less space in the AI factory compared to traditional air-cooling infrastructure. "In the right geographic location, with the right system design, you don't need any refrigeration equipment," Whitmore said. "You can just put big radiator coils outside and use the air temperature for all your cooling. It's incredibly efficient." The geography caveat matters. A data center in the Scottish Highlands and one in Phoenix, Arizona, face very different realities. But even in warmer climates, the shift toward 45-degrees-Celsius coolant moves operators significantly closer to that chiller-less ideal -- where chillers may turn on just a few days a year when the outside air temperature demands it. Another key benefit of this new model for AI factories is the potential for waste heat recovery, where residual heat from AI factory operations can be repurposed to heat commercial or residential buildings nearby. The Engineering Problem Nobody Had Solved Previous liquid-cooled servers were hybrid: GPUs and CPUs got cold plates, but the rest of the system stayed air-cooled, with finned heat sinks designed to shed heat into moving air. In a fully liquid-cooled server, the cooling for these components needed to be completely redesigned to use liquid. NVIDIA's thermal engineering team reworked how those components handle heat, designing cooling loops that simplify how liquid is routed to multiple high-power chips on the board using a single inlet and outlet, resulting in a cleaner tray-level cooling architecture. One visible outcome: Rubin servers have clean, sealed front panels where air-cooled servers have perforated bezels. Another: fully liquid cooled servers enable higher rack density than air-cooled servers, so a system that previously occupied six rack units now fits in two -- more compute, less space, less noise. AI workloads are not getting lighter. The compute demand driving data center construction is growing faster than almost any other category of infrastructure investment. Without efficiency improvements in how that compute is cooled, the energy cost of running AI at scale would grow in lockstep with the hardware. Liquid cooling at up to 45 degrees Celsius -- hotter than a hot tub, cooler for the planet -- is one of the most important tools the industry has to close that gap. Learn more about liquid cooling, the NVIDIA DSX platform for AI factories and NVIDIA's approach to energy-efficient AI infrastructure.

NVIDIA's 113°F cooling system brings data center water use near zero

One of the world's leading technology companies, Nvidia, has just unveiled a new data center cooling system that uses a liquid coolant hotter than a hot tub to cut energy consumption. The Californian company's latest Rubin platform can operate using liquid coolant at temperatures up to 113 degrees Fahrenheit (45 degrees Celsius). The approach greatly reduces the need for energy-intensive chillers and cooling infrastructure. According to the company, the feat is part of the DSX AI factory reference design, which introduces fully liquid-cooled infrastructure throughout the entire system. Every processor, networking part, and high-performance computing element is cooled by liquid in a closed-loop system. Ali Heydari, Nvidia data center cooling and infrastructure director, noted that the DSX AI factory design reduces nearly all water use and cuts a substantial amount of the power necessary for cooling. "With dry-cooler-based designs, it's a closed-loop system with no evaporative water cooling - outside of maybe one percent of the year when we might need chillers in some climates," he added. Cooling has accounted for up to 40 percent of total power demand. Traditional data centers utilize large volumes of cooled air to remove the heat generated by servers. This requires extensive cooling infrastructure, like fans, chillers, cooling towers, and carefully managed hot and cold aisles. Meanwhile, Nvidia's Rubin platform captures heat directly at the chip level. It can reportedly reduce cooling water consumption from about 2.6 million gallons per megawatt per year to almost zero in suitable climates. The system relies on a liquid coolant made up of 75 percent water and 25 percent propylene glycol, which circulates through cold plates attached to processors. The liquid enters at temperatures of up to 113 degrees Fahrenheit and exits at about 131 degrees Fahrenheit (55 degrees Celsius), once it absorbs the heat generated by the chips. Since the heat is removed directly from the source, the processors can continue operating at full performance even with much warmer coolant temperatures than traditional cooling systems would allow. As per Nvidia, the higher operating temperatures unlock considerable efficiency gains. Industry estimates suggest that increasing chiller temperatures by just 1.8 degrees Fahrenheit (one degree Celsius) can reduce cooling energy costs by four percent. In practice, this means that a 50-megawatt hyperscale facility can save more than USD four million per year in cooling-related energy and water costs by adopting liquid-cooled infrastructure. "In the right geographic location, with the right system design, you don't need any refrigeration equipment," Richard Whitmore, president and CEO of Motivair, Schneider Electric's advanced cooling division, pointed out. "You can just put big radiator coils outside and use the air temperature for all your cooling." The move to complete liquid cooling also required a major server redesign. Earlier liquid-cooled servers used a hybrid approach, cooling CPUs and GPUs with cold plates while relying on air cooling for other components. Nvidia engineers reworked cooling pathways across the entire server and created a system that uses a single liquid loop to cool multiple high-power components. The redesign has also improved space efficiency. The company revealed that fully liquid-cooled servers can reach higher rack densities. This allows more computing power to fit into a smaller footprint. "Once the watts per chip crossed a certain level, liquid cooling became mandatory," Whitmore concluded in a press release.

NVIDIA claims its new AI data centers use almost no water -- here's what that actually means

As AI races forward, so does one of the industry's biggest environmental challenges: water Training and running AI models requires enormous amounts of computing power, and keeping those powerful chips cool often means consuming large amounts of water. It's become a growing source of concern as tech companies build massive AI data centers across the United States. NVIDIA says it has a solution. The company recently unveiled a new liquid-cooling system designed for its next-generation AI infrastructure that it claims could reduce cooling water consumption to nearly zero in certain environments. The announcement arrives as public scrutiny of AI's environmental footprint continues to grow, with communities questioning whether new data centers are placing too much strain on local resources. So what exactly is NVIDIA proposing, and does it really solve AI's water problem? Why AI data centers use so much water AI systems run on specialized chips called GPUs, many of which are designed by NVIDIA. These chips generate enormous amounts of heat when processing AI workloads. Historically, many data centers have relied on cooling towers that use water evaporation to remove heat. While effective, the process can consume millions of gallons of water annually. As AI models become larger and more powerful, cooling demands have increased alongside them, turning water consumption into one of the most controversial aspects of the AI boom. The issue has become especially sensitive in regions already facing water shortages or drought conditions. NVIDIA's new approach According to NVIDIA, its latest cooling system circulates warm liquid directly around AI hardware at temperatures reaching approximately 45°C (113°F). Rather than relying on traditional cooling towers, the warmer liquid can be paired with dry coolers, which function more like large radiators and do not require significant water consumption. NVIDIA says this could reduce facility cooling water use from roughly 2.6 million gallons per megawatt annually to nearly zero in favorable climates. The company also argues that operating at higher liquid temperatures improves overall energy efficiency while creating opportunities to reuse waste heat elsewhere. In other words, NVIDIA's goal is o redesign the entire thermal management process around water conservation. The important caveat The company's claims primarily address one specific category of water use: cooling. And while that matters, cooling isn't the only way AI consumes water. Water is also used throughout the broader AI supply chain, including electricity generation, semiconductor manufacturing and data center construction. Even if cooling water usage falls dramatically, AI systems still carry an environmental footprint beyond the walls of the data center itself. Of course, there's also the question of scale. AI demand continues to grow at an extraordinary pace. Critics argue that efficiency gains can sometimes be offset by rapid expansion, meaning total resource consumption may continue rising even as individual facilities become more efficient. Why this matters The industry's largest companies are now under pressure to demonstrate that future AI growth can occur without placing unsustainable demands on water and energy resources. NVIDIA is not alone here -- Microsoft has made similar zero-water cooling claims for its newest data centers. NVIDIA isn't claiming that AI no longer has an environmental footprint. Instead, it's targeting one of the most visible concerns surrounding modern data centers: water-intensive cooling system Whether NVIDIA's approach becomes the new standard remains to be seen, but it offers a glimpse of how the industry may attempt to address one of its most persistent criticisms. Follow Tom's Guide on Google News and add us as a preferred source to get our up-to-date news, analysis, and reviews in your feeds. Subscribe to Tom's Guide on YouTube and follow us on TikTok. Finally, you can visit our dedicated Tom's Guide Savings Squad hub for expert help on getting the best products for less.

Water joins energy as top AI flashpoint

Why it matters: After spending much of the past year defending data centers' electricity demands, major tech companies driving the AI boom are increasingly making the case that their water use is manageable too. Driving the news: Over the past several weeks, Google, Amazon and Microsoft have each launched new efforts to explain and justify the water use of their AI infrastructure, highlighting measures such as water replenishment projects, recycled-water use and new cooling technologies. * Nvidia -- the world's dominant AI chip maker -- claimed this week that water concerns could be largely addressed by its latest generation of technology. What they're saying: "The growing conversation about water and energy use by data centers has forced these companies to scramble, to rethink what they're doing and to become more transparent about what they're doing," said Peter Gleick, co-founder of the Pacific Institute, a California-based water research nonprofit, and one of the nation's leading water experts. * "They're starting to understand the reputational risk of the massive rollout of data centers that have big energy and water footprints." Friction point: Roughly 70% of people in the U.S. said they would oppose data centers in their communities, with equal weight placed on water and energy use as top concerns, according to Gallup polling from May. State of play: Such worries are infiltrating debates at all levels around the world. * The United Nations Secretary General António Guterres called for more transparency on data centers' energy, water and land use in a speech earlier this week in London. * Also this week, lawmakers in Virginia -- which has the world's highest number of data centers -- moved toward clamping down on the most water-intensive methods of cooling. Reality check: Compared to other major industries, data centers actually use far less water -- a point tech executives are quick to point out and some independent experts agree with. "The projections for water demand are not eyebrow-raising," said Sarah Porter, director of the Kyl Center for Water Policy at Arizona State University. * Concerns about water are largely a "substitute for concerns people have for this fast-developing industry." Yes, but: Experts, including both Gleick and Porter, caution that aggregate water-use figures can obscure local impacts, particularly in drought-prone regions where even modest demand can become contentious. * "The important point is: How much water does a data center use in the region where it's taking the water from?" Gleick said. * Comparisons to other industries also may do little to ease concerns in communities facing the prospect of a big new industrial neighbor. How it works: Energy and water are intricately -- and sometimes inversely -- connected. * Water-based cooling systems generally use less electricity than air-based systems, creating a tradeoff between water consumption and energy demand. * Generating the electricity that powers data centers requires water as well if it's powered by fossil fuels or nuclear power. Wind and solar require no water. Zoom in: Water-intensive cooling has historically been favored because it uses less energy and is less expensive, but it is facing growing public opposition. * "However, the court of public opinion has spoken loudly that consuming water for cooling on data centers is no longer an acceptable method," said Aaron Bilyeu, chief development officer of Cloverleaf Infrastructure, a data center developer. Zoom out: For all the focus on cooling technology, much of a data center's broader water footprint comes from the electricity it consumes rather than water used directly at the facility. * A recent Bank of America report estimated electricity generation accounts for roughly 75% of a data center's total water footprint. What's next: Transparency is emerging as a key next phase of AI water worries. * Tech giants, including Microsoft and Google, are set to release annual environmental reports in the coming weeks that could shed more light on their water use. What we're watching: Guterres added urgency to those moves when he proposed an AI environmental transparency initiative this week.

Cooling just became the most strategic choice in AI infrastructure

AI cooling becomes critical to data center performance and scalability For most of the last forty years, data center performance gains came from one place: smaller transistors. Moore's Law and Dennard scaling did the work. Each new generation of silicon delivered more performance at the same or lower power, and thermal was a maintenance problem, not a performance limiter. Cooling sat in the background. Operators measured it through PUE, optimized for it where convenient, and otherwise treated it as overhead. That world is over. Dennard scaling broke years ago, transistor efficiency gains are leveling off, and AI accelerator TDPs have climbed from 700 watts in the H100 generation to over 1,400 watts in current Blackwell deployments, with NVIDIA's upcoming Rubin platform expected to push further. Thermal is no longer something that happens after the architectural decisions. It is now the binding constraint on how much performance a chip can sustain, and it is becoming one of the most strategic choices an AI data center operator can make. Why this matters now The macro numbers explain why this matters now. Data centers already consume up to 4.5 percent of total U.S. electricity production, a figure projected to reach 12 percent by 2028. McKinsey estimates global data center spending could approach $7 trillion by 2030, and that data center power demand will reach 220 gigawatts in the same window. None of that capacity arrives quickly. New transmission lines and substations now take five to ten years to permit and build, which means operators cannot simply order more power when they need to scale. The result is a hard pressure to extract maximum performance from the power they already have under contract. That pressure is what is reshaping how the industry thinks about cooling. Cooling is no longer just an afterthought For years, cooling was measured as an efficiency loss, captured through metrics like Power Usage Effectiveness (PUE) that quantified how much energy was burned on overhead before reaching the IT load. Today, the more meaningful metric is how much useful compute you extract per unit of power. NVIDIA's Jensen Huang now describes this as "performance per watt" or "tokens per watt" for AI workloads, and cooling plays a direct role in both halves of that equation. Direct-to-chip liquid cooling has become the new baseline because it removes heat far more effectively than air. But even direct-to-chip is being pushed to its limit by 1,000+ watt accelerators, and most current deployments still require facility water around 30 degrees Celsius to stay within ASHRAE W2 and W3 envelopes, which means chillers running for much of the year in warm climates. Better thermal management has effects on both sides of the tokens-per-watt equation. It reduces facility overhead, so more of the contracted power reaches the rack. And it allows chips to operate closer to their full thermal headroom, sustaining higher performance for longer. Those gains compound. Recent UCLA study has shown that combining a 17 percent improvement in facility efficiency with a 15 percent gain in server-level performance per watt from better thermal management translates to roughly 35 percent more tokens per watt within the same power envelope. In a 10 megawatt facility, that is more than a megawatt of additional usable compute, with no additional grid commitment. At GTC 2026, NVIDIA CEO Jensen Huang made this argument explicitly. He told the audience that beyond the silicon roadmap, infrastructure-level optimization across power and cooling represents another factor of two in performance still on the table. "There's no question in my mind there's a factor of two in here, and a factor of two at the scale we're talking about is gigantic," he said. That gain does not come from a smaller transistor. It comes from rethinking how power and thermal energy move through the rack. Recent UCLA study suggests that at least one third of that infrastructure-level gain is attributable specifically to cooling. Cooling is no longer a support function. It is a primary lever for performance. Water is becoming a hard constraint Power is not the only pressure point. Water is emerging as an equally critical and often more immediate constraint on data center expansion. Traditional cooling architectures often rely on evaporative processes that consume vast amounts of water. According to the Environmental and Energy Study Institute, large data centers may use up to 5 million gallons per day, comparable to the daily water use of a town of 10,000 to 50,000 people. This is drawing notice from regulators and communities in already water-stressed areas. The result is longer permitting cycles, higher project risk, and in some cases new developments paused entirely. States and municipalities are also implementing stricter reporting requirements and adjusting electricity rate structures specifically for data centers. Operators now have to factor water alongside power into site selection. Facilities that minimize energy waste and reduce or eliminate water consumption are better positioned to navigate this environment. The shift toward next-generation cooling In response, the industry is entering a new phase of cooling innovation. Air cooling is no longer sufficient for high-density AI workloads. Liquid cooling has become the baseline, but within liquid cooling, not all approaches deliver the same efficiency or scalability. The next wave of innovation focuses on improving heat transfer at the source: removing thermal energy more effectively at the chip level while reducing system-wide overhead. Some of these approaches draw on heat transfer techniques refined in other high-density power industries such as nuclear power generation, where the challenge of moving large amounts of thermal energy from a constrained physical space has been studied for decades. The goal is straightforward. Better cooling enables higher rack densities, allows operation at higher facility water temperatures, and reduces or eliminates reliance on water-intensive heat rejection. Just as importantly, the next generation of cooling architectures is being designed to integrate with existing data center footprints, so operators can evolve their infrastructure rather than rebuild it from scratch. NVIDIA's Vera Rubin platform, announced at CES 2026, was a clear signal of where this is heading. Vera Rubin is designed for 45 degree Celsius supply water, which means dry coolers can do most of the heat rejection year-round and mechanical chillers become optional in most climates. That is a fundamental shift in how cooling infrastructure will be designed for the next decade. A defining moment for data center design The data center industry is at an inflection point. AI compute demand is accelerating, and every resource needed to support it, power, water, physical space, is becoming harder to secure. Cooling sits at the intersection of all three. It determines how efficiently power is used, how much water is consumed, and ultimately, where infrastructure can be deployed. The operators that recognize this now will have a sustained advantage. How to keep data centers cool under AI workload pressure has become one of the most strategic decisions in modern infrastructure. We feature the best web hosting services: tested and reviewed. This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

Nvidia says its new data center design will fix AI's water problem | Fortune

Nvidia thinks it has the solution for that: its new server infrastructure. The company announced on Monday that its newest AI servers will entirely use liquid cooling, a method that eliminates the need for air-cooling fans that rely on water. Instead, heat will be dissipated by a liquid coolant made of water and propylene glycol that's recirculated in a closed loop. The company says the system doesn't need to draw in new water. "We have eliminated massive amounts of power usage and pretty much all water usage," Ali Heydari, Nvidia's director of data center cooling and infrastructure, said in a statement. In addition, the coolant can remain operational at temperatures of up to 45 °C or 113 °F, a much higher temperature than previous systems. The move towards a more energy-efficient system comes as the United Nations predicted earlier this month that AI-related water consumption could equal the annual needs of 1.3 billion people by the end of the decade. Meanwhile, Nvidia is not the only company working towards significantly reducing its water consumption. In August 2024, Microsoft announced that its new data centers will stop using water for cooling, saving more than 125 million liters of water per year per data center. "The thing that's exciting about what Nvidia announced is it shows really what's possible in terms of pushing up this liquid input temperature to 45°C," said Andrew A. Chien, a professor of computer science at the University of Chicago. "It's super important to push it up, because in many cases it allows you to do that cooling, that exhausting of heat to the outside environment without running HVAC units, without running air conditioners. Because if it's cool enough outside, you don't need to." Chien directs the CERES Center for Unstoppable Computing. For the past 10 years, the center has studied how to make data centers more efficient and reduce their negative environmental impacts. A higher cooling temperature goes against conventional wisdom, he explained. The industry standard is 30°C, which requires much more air conditioning to maintain. "The reason that they want to do this is that if you can cool the chips at a higher temperature, it becomes easier to vent that heat into the outside environment, because it's a higher temperature supply, and heat flows downhill," Chien said. While he said zero water use is unrealistic, liquid cooling will significantly reduce the need for water. The catch is that these systems are expensive. Nvidia did not immediately respond to Fortune's request for comment on the costs of the systems or if the company will be retrofitting existing data centers with the technology. The company estimates that a 50-megawatt hyperscale facility could save over $4 million a year in cooling-related energy and water costs by moving to liquid-cooled infrastructure. "It is a direction that more people should be trying to get to, because it'll reduce the total power consumption of these large data centers," Chien said.

Microsoft points to lower water use in AI era

Driving the news: Microsoft said its newest AI-focused data center designs -- first unveiled in 2024 -- do not consume water for cooling during normal operations. * The move is part of a broader effort that the company says has helped improve its water efficiency by nearly 90% since the early 2000s. * The company also said it replenished more water globally in fiscal year 2025 than it used across its operations, a milestone toward its goal of becoming water positive by 2030. State of play: Microsoft's newest AI data centers continuously recirculate coolant directly to the chips and use air-cooled chillers outside the building, eliminating the need for water-consuming cooling towers during normal operations. * The result, Microsoft says, is that the systems require an initial water fill but do not consume water during normal cooling operations. Between the lines: Much like the other tech companies' recent announcements, the information is not entirely new. * Instead, Microsoft is compiling years of cooling technology improvements and water stewardship work as opposition to data centers intensifies. * "There's nothing really new here, other than we continue to innovate," Steve Solomon, Microsoft's vice president of data center engineering, said in an interview. * "This is updating where we're at and it's really an extension to what we issued in 2024, which was an extension to the years before that." Friction point: What is new is opposition. * Roughly 70% of Americans oppose building data centers in their communities, according to Gallup polling released in May, with water and energy concerns the top two reasons. What they're saying: "I have community [members] ask me questions about it, and if I come across and say we don't use water, they look at me like this guy's full of it," Solomon said. * "But the reality is, the data centers that are getting all the press on the AI -- we do not consume water." Yes, but: Most of Microsoft's existing data center fleet still uses some water for cooling. The company says many facilities rely on systems that use outside air and only periodically require water. * In Phoenix, for example, some of Microsoft's data centers use an evaporative cooling system that relies on water when temperatures exceed roughly 85 degrees Fahrenheit, Solomon said. * Microsoft said approximately 90% of its current owned data center fleet already operates with low- or zero-water cooling systems. How it works: Operators generally balance water consumption against electricity consumption when choosing cooling methods for the entire building. Zoom out: Water use inside a data center is only one piece of a broader debate. Producing the electricity needed to run AI infrastructure can also require significant amounts of water, depending on the power source. Reality check: To support the rapid AI buildout, Microsoft, along with other tech giants, is increasingly turning to natural gas-fired electricity, which does require more water compared to wind and solar, which require essentially none. * Chevron announced a 20-year deal with Microsoft earlier this week to provide gas-fired power for a major West Texas data center project. * Solomon said that right now their main focus is on water use at the data center itself, not water associated with electricity. What we're watching: Nvidia said earlier this week its latest AI systems could remove the need for any mechanical chilling equipment at all. * Solomon, commenting on its potential before that Monday announcement, said "that would be the ultimate case." Sign up here for Axios' Future of Energy newsletter.

Nvidia says AI's water challenge is largely solved

Why it matters: It's a bold claim with high stakes by the world's dominant chip maker. Data centers are facing growing scrutiny for their use of energy and water, and Nvidia's chips are helping drive the AI boom behind much of that demand. Driving the news: Nvidia announced Monday at London Climate Week that its latest AI system can be fully cooled with liquid warm enough to reduce the need for additional chilling equipment. * "The water consumption challenge for data centers is largely solved," said Josh Parker, Nvidia's chief sustainability officer, in an interview last week ahead of his trip to London. The big picture: Nvidia's announcement comes on the heels of Google and Amazon defending their data center water practices amid growing local opposition to AI infrastructure. * Tech companies are increasingly arguing that efficiency gains will blunt the environmental impacts of the AI buildout. Between the lines: Nvidia's latest claim goes further, suggesting that next-generation AI systems could change the underlying cooling equation altogether. How it works: Nvidia's coolant -- a recirculated liquid mixture that includes water and propylene glycol, similar to automotive antifreeze -- can run at 113 degrees Fahrenheit. * Because the liquid can operate at higher temperatures than previous systems, data centers may be able to rely less on chilling equipment that uses large amounts of energy or water -- or even eliminate it altogether. What they're saying: "It would be a big deal for everybody if we got all of the chips to do that," said Steve Solomon, Microsoft's vice president of data center engineering, who was asked about the potential before learning of Nvidia's announcement. * Solomon said it could eliminate the need for any type of mechanical chiller in most climates most of the time -- even in hot places such as Arizona. Reality check: Even if Nvidia's technology dramatically reduces cooling-related water use, that doesn't mean water concerns disappear entirely. * The new systems would take years to spread across the industry, and many existing data centers will continue operating older cooling technologies. * Nvidia declined to discuss the costs of its systems, and the pace of adoption may also depend on the economics of facilities designed for fully liquid-cooled AI infrastructure (though Nvidia says it'll save data center operators money on cooling costs). Zoom out: Water use inside a data center is only one piece of a broader debate. Producing the electricity needed to run AI infrastructure can also require significant amounts of water, depending on the power source. What's next: Nvidia's technology could make each unit of AI computing far more efficient, but the company is also explicit that those gains are meant to support more growth. * "AI workloads are not getting lighter," Parker wrote in a blog post. Without efficiency improvements, he argues, the energy needed to run AI would continue rising alongside demand. What we're watching: Efficiency gains may reduce the water and energy needed for each AI system. Those same gains could also accelerate the buildout of AI infrastructure and increase the industry's overall footprint.

Nvidia Says It's Figured Out How to Solve This Big Problem With Data Centers

Nvidia's latest announcement goes a step further, proposing to greatly reduce the immense amounts of water (300,000 gallons per day for a mid-size facility) guzzled by data centers to keep their systems cool. In a press release, the chip giant described a coolant for its AI system that is "warmer than a hot tub," with the potential to eliminate water use altogether. The coolant, a mixture of water and propylene glycol, can run as hot as 113 degrees Fahrenheit, pulling heat from processors as it flows through cold plates mounted on them. This reduces the need for chilling equipment while improving efficiency. With cooling accounting for 40 percent of electricity-use in data centers, optimizing the process through warmer temperatures is a win-win for both natural resources -- water and energy -- at the heart of data center operations. Nvidia's head of sustainability Josh Parker told Axios that the technology "largely solved" the issue of water consumption at data centers. The company made the advancement on Monday at London Climate Week. But gaps remain in answering for the costs of this new system, and the timeline and viability of its adoption across data centers.

India's AI boom cannot ignore its water crunch

India's AI growth risks exacerbating severe water stress as data centers, crucial for AI infrastructure, consume vast amounts of water. Cities like Hyderabad and Bengaluru, already facing shortages, are becoming AI hubs. While AI promises inclusive growth, its physical demands strain local resources, necessitating urgent policy reforms and location-specific planning to balance digital ambitions with sustainable resource management. Boston/Bengaluru: India's growth story has often relied on alignment between society, state and market. Public infrastructure, private innovation and social needs have advanced together in this mixed-economy model. In AI, that has meant shared compute, open datasets and a deliberate effort to keep access affordable. At its core is a democratic instinct: the belief that AI should work for everyone. But AI infrastructure is not abstract. It's physical, resource-intensive and tied to local ecosystems. This raises the question: what happens when this rapid expansion collides with a country facing severe water stress? Global tech companies are committing investments to expand cloud capacity in India. Domestic players are doing the same. The goal is to make AI cheaper, faster and more accessible. Data centres, which power everything from search engines to genAI models, require cooling to operate. A single large facility can consume as much water in a day as a small village. Even in the US, the strain is becoming evident, from groundwater pressures in Texas to rising withdrawals in Virginia's 'Data Centre Alley'. In India, this trend intersects with a fragile reality. The country is home to nearly 18% of the world's population, but has access to only about 4% of its freshwater resources. Most cities are already dealing with falling groundwater levels, infra pressures, and growing competition between domestic, agricultural and industrial use. These same cities are now becoming hubs of data centre expansion. Hyderabad, Bengaluru and parts of Maharashtra are attracting significant investment in AI infra even as they face recurring water shortages. In Pune, concerns over water access have already sparked public pushback. Unlike electricity, which can be transmitted, water is local. When data centres draw from urban supplies, they compete with households, farmers and small businesses, often relying on potable, drinking-grade water. At the same time, AI's water footprint extends well beyond data centres. Power generation itself, including some RE sources, can be water-intensive, and production of advanced semiconductor chips requires vast quantities of ultra-pure water. The true resource demand of AI infra is far greater than what is immediately visible. India's AI ambitions are designed to address pressing domestic challenges. From improving agricultural productivity, expanding access to healthcare and widening educational opportunities, AI is being positioned as a tool for inclusive growth. But the infra that enables these solutions may also be placing additional strain on the systems that sustain everyday life. More computing requires more energy. More energy often requires more water. In a country where water is already scarce, this creates a feedback loop that cannot be ignored. And, yet, policy frameworks have not fully caught up with this reality. While several states have introduced incentives to attract data centre investments, only a handful meaningfully incorporate sustainability criteria. As a result, facilities can be built in water-stressed regions without standardised reporting or clear accountability to local communities. A clear unified national framework governing water use or disclosure is needed. Things can get worse as demand scales. More than 60% of India's existing data centre capacity is expected to operate in high water-stress regions this decade. Corporate sustainability commitments offer some reassurance. But their impact remains uneven. Major tech companies have pledged to become 'water positive', investing in watershed restoration and replenishment efforts. Yet, these interventions often operate at a broader regional level and don't necessarily offset localised strain, particularly in cities already facing shortages. Globally, Google alone reported using over 5.6 bn gallons of water for its data centres in 2023, a figure that continues to rise alongside AI demand. Infrastructure is also proving vulnerable to environmental stress. During a 2022 heatwave in Britain, cooling failures forced temporary shutdowns of major data centres during demand peaks. Despite this, incentives driving expansion remain largely economic. Tax benefits, subsidised land and fast-track approvals continue to prioritise rapid growth, often without integrating long-term water and energy constraints into planning decisions. None of this suggests that India should slow down its AI ambitions. The real challenge is not whether India should invest in AI infra, but how. Location-specific planning must become central to decision-making. In water-scarce regions, less water-intensive cooling systems may need to be prioritised, even at the cost of higher energy use. Standardised reporting on water and energy use would enable better oversight and more informed public debate. India has demonstrated global leadership in building DPI. The next phase will require applying that same rigour to physical systems that support it. Success of a digital future will depend not only on data and compute, but on whether natural resources that sustain it are managed with equal ambition and care. The writers are co-founders, Leherum

Elon Musk Gives A Nod As Nvidia Argues AI Data Centers Aren't The Water Drain Many Believe: 'Numbers May

Nvidia Pushes Back On AI Water Consumption Concerns On Monday, in a post on X, Nvidia highlighted findings from the Manhattan Institute showing that data centers account for just 0.2% of daily water usage in the U.S., while arguing that advances in cooling technology are dramatically reducing the industry's water footprint. The chipmaker said newer AI facilities are increasingly adopting liquid-cooling systems that can significantly reduce or even eliminate the need for water-intensive cooling towers. Musk shared Nvidia's post on X and responded with a one-word endorsement: "True." According to Nvidia, AI facilities using 45-degree Celsius liquid cooling can rely on dry coolers rather than traditional cooling-tower systems. This reduces cooling-related water consumption from roughly 2.6 million gallons per megawatt annually to near zero in favorable climates. Rubin AI Systems Aim To Eliminate Cooling Water Use In a blog post published Sunday, Nvidia said its upcoming Rubin-generation AI infrastructure will be the company's first platform to use fully liquid-cooled architecture. "The NVIDIA DSX reference design for AI factories has zero water consumption," said Ali Heydari, Nvidia's director of data center cooling and infrastructure. Heydari added that dry-cooler-based systems operate as closed loops with "pretty much all water usage" eliminated except in limited circumstances. Nvidia said the design also reduces energy demand by capturing heat directly at the chip level, avoiding the need to cool large volumes of air. Historically, cooling has represented as much as 40% of a data center's electricity consumption. Water Emerges As AI's Next Infrastructure Challenge The discussion comes as investors and policymakers increasingly scrutinize the resources required to support AI expansion. Meanwhile, local opposition to new data centers has intensified across the U.S., with critics citing concerns ranging from water availability and energy demand to noise and infrastructure strain. Price Action: Shares of NVDA closed Monday at $208.65, down 0.97% and slipped another 0.41% to $207.79 in after-hours trading, according to Benzinga Pro. According to Benzinga Edge Stock Rankings, Nvidia ranks in the 98th percentile for Growth, supported by strong price performance in medium and long-term time frames but a negative price trend in the short term. Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

Nvidia claims it can ease water consumption problem for AI data centers

Every technology boom eventually gets a villain the public can picture. For the railroads, it was land grabs. For artificial intelligence (AI), it became a data center quietly drinking a town's water while a chatbot wrote someone's emails. That picture is not imaginary. Massive computing warehouses run hot, and the cheapest way to keep thousands of chips from cooking themselves has long been water, pumped through cooling loops and often evaporated straight into the air. As the AI race accelerated, local fights over wells, aquifers, and permits spread from Arizona to Ireland, and "thirsty AI" became shorthand for everything people distrust about the buildout. Google (GOOGL) and Amazon (AMZN) have spent recent weeks defending their cooling to skeptical communities, and the industry's answer has mostly been the same promise that efficiency will eventually shrink the footprint. I have watched that narrative harden for two years, which is why a claim out of London this week caught my attention. Nvidia (NVDA), whose chips sit at the center of nearly every AI data center, now says the water problem is close to fixed. GummyBone / Getty Images Why data centers got so thirsty Cooling is the hidden cost of computing. Data centers use water two ways, directly to carry heat off the chips, and indirectly through the power plants that feed them electricity. The direct number is already large, and the indirect number is larger. * U.S. data centers consumed about 17 billion gallons of water for cooling in 2023, a total on pace to double or even quadruple by 2028, according to Lawrence Berkeley National Laboratory. * The power plants feeding those data centers used roughly 12 times more water than the cooling itself, the same Lawrence Berkeley National Laboratory report found. * Training the GPT-3 model consumed about 700,000 liters of fresh water on-site, according to researchers at the University of California, Riverside. Numbers that big are hard to feel, so here is the translation. That 17 billion gallons is roughly the yearly water use of 160,000 American homes, and it is the floor, not the ceiling, of where this is heading. When I lined those figures up, the takeaway was simple. The water story was never really about your chatbot. It was about thousands of buildings, each one hot, each one local, each one fighting a city council somewhere over a permit. It also comes down to a brutal trade-off baked into how these buildings stay cool. Evaporative systems spray water to shed heat and lose much of it into the air for good. Closed-loop systems recycle the water but burn far more electricity running chillers to cool it back down. Operators have spent years choosing which resource to waste. That is the choice Nvidia says it can erase. What Nvidia actually changed Nvidia's pitch is mechanical, not magical. Its newest AI systems are designed for liquid cooling that still works when the liquid is warm, using a recirculated mix of water and propylene glycol, similar to automotive antifreeze, that can run at about 113 degrees Fahrenheit, according to Axios. That temperature is the whole point. Because the coolant can stay hot, a data center can lean less on the energy-hungry chillers that themselves burn power and evaporate water, or skip them entirely. "The water consumption challenge for data centers is largely solved," said Josh Parker, Nvidia's chief sustainability officer, according to Axios. : Nvidia is not the only one who sees the upside. The claim could remove the need for a mechanical chiller in most climates most of the time, even somewhere as hot as Arizona, said Steve Solomon, Microsoft's (MSFT) vice president of data center engineering. "It would be a big deal for everybody if we got all of the chips to do that," Solomon said, according to Axios. When I read the spec, the part that mattered to me was that temperature, not the press release. Warm-water cooling has existed for years in high-performance computing. What is new is a dominant chip vendor designing its flagship product around it and telling operators they will save money doing it. The number that scared everyone is shrinking Here is the part most coverage skips. The scariest water statistic in AI was already falling before Nvidia said a word. The viral "bottle of water per query" figure traces to that University of California, Riverside team, which estimated GPT-3 drank roughly a 500-milliliter bottle for every 10 to 50 responses. The lead researcher has since said newer, far more efficient models use a small fraction of that, closer to 15 milliliters per prompt and about five milliliters inside the data center itself. So the per-question footprint is collapsing as the per-building footprint keeps climbing. My read is that those two facts are the entire debate. Each AI answer gets cheaper to cool, while the sheer number of buildings drags the total higher. Nvidia's claim lands right in that gap. The company is offering hardware that cuts the cost per building at the exact moment the public has fixated on a per-question number that no longer holds. What it means for your portfolio Strip out the environmental guilt and the investor stakes get clearer. Water fights are permitting risk, and permitting risk is the quiet threat to the AI infrastructure trade. If warm-water cooling removes the most visceral local objection, it makes data centers easier to approve and faster to build, which feeds the chip demand priced into NVDA today. Local opposition to AI infrastructure is already growing, which is exactly why Google and Amazon have been on defense, according to Axios. Every delay an angry community wins pushes back the revenue that justifies a chip order today. The reasons for caution are real, and Nvidia named most of them. New systems take years to spread, older data centers keep running older cooling, the company declined to discuss costs, and the water used to generate electricity does not go away, according to Axios. There is also a trap inside the good news. Efficiency that makes each AI system cheaper to cool can also accelerate the buildout, pushing the industry's total water and energy use up even as every unit gets leaner. That is the tension worth watching as an investor. The chips can run warm. Whether the backlash cools with them is the one part Nvidia cannot engineer. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published June 24, 2026 at 2:03 AM.

Microsoft, Nvidia Seeks Alternatives to Solve Datacentre Energy Challenges

While one indicates that datacentres and climate cannot go hand-in-hand, the other seeks to solve a third of the problem While AI giants are busy dreaming of the moolah from forthcoming public offers, some of the old hands in the game seem to focusing real world challenges beyond the hype. Microsoft and Nvidia seeking means to resolve the real-world challenge of energy and water demand from datacentres, the single stop option for AI delivery of any kind. On Monday, Microsoft collaborated with Chevron to develop a 2.67-gigawatt natural gas power plant in West Texas to power the former's cloud datacentres. And close on its heals came an announcement from Nvidia of a warm-water cooling system that could eliminate "pretty much all water usage" within datacentres. Microsoft has drawn up a 20-year power purchase agreement whereby the Chevron plan will provide dedicated power to its datacentre through two large GE Vernova turbines along with a Caterpillar subsidiary Solar Turbines. Just in case you find that name familiar, it is the one used by xAI in Memphis, which has raised the hackles of conservationists. Chevron is gung-ho about the project as is evident from its press release that highlights the fact that it would be "among the largest co-located natural gas power and datacentre developments in the United States." Of course, it does raise the question over Microsoft's avowed aim of eliminating carbon emissions by 2030. According to a report published by the Environmental Integrity Project, the new project could potentially release over 13 million tons of carbon dioxide, 3200 tons of criteria air pollutants and 278,000 pounds of hazardous air pollutants once it become operational. Coming to Nvidia's plans, their press release claims that their latest AI servers can run on coolant warmer than a hot tub -- and that counterintuitive choice is one of the biggest efficiency leaps in datacentre history. They claim that this would largely solve the water consumption challenge of all datacentres. Of course, that still doesn't remove the problem that Microsoft has attempted to solve through potentially polluting gas power. The challenge is how Nvidia is measuring datacentre water use as the company says it draws a line around the datacentre and anything inside is counted and everything outside is ignored. Which might still be a better way to measure than others do as Nvidia's system does deliver on its facility-level premise whereby the coolant runs in a closed loop that is filled once and recirculated for the life of the facility. So, no new water is required to cool the chips, which is why the company says it can reduce on site water use to zero. However, what the experts are not able to fathom is how water use outside datacentres, specifically in power generation and chip manufacturing can be impacted. Especially since this water is sometimes as large as triple the water footprint within a facility. So, would it be safe to state that Nvidia's solution tackles a third of the water consumption challenge? Coming to the actual system itself, it pumps coolant into racks at 45 degrees which is quite comfortable for chips but not humans. This goes via a server and emerges at 55 degrees, taking a significant part of the heat away from the hardware. At this point, the outside air in most geographies can remove heat off passive radiators without evaporative cooling or the use of fans or other artificial means. This also reduces the datacentre humming. Because the Nvidia Rubin platform (which is what they are calling it) integrates 100% liquid-cooled infrastructure, every cloud provider and data center operator building for it is making the transition, the press release states. The company also revealed that the ecosystem around it is also keeping pace. Motivair, the advanced cooling division of Schneider Electric, has collaborated for nearly a decade -- and Richard Whitmore, its president and CEO, says the relationship only intensified as power densities crossed the threshold where air cooling was no longer a viable option. From Nvidia's point of view, this move is a start that could define future industry standards. "AI workloads are not getting lighter. The compute demand driving datacentre construction is growing faster than almost any other category of infrastructure investment," it says. Without efficiency improvements in how that compute is cooled, the energy cost of running AI at scale would grow in lockstep with the hardware. Liquid cooling at up to 45 degrees Celsius -- hotter than a hot tub, cooler for the planet -- is one of the most important tools the industry has to close that gap, the press release concludes.