Tag: AI data centers

  • Prysmian’s 24-Fiber Hollow-Core Cable Makes AI’s 90 km Reach a Supply Question

    Prysmian’s 24-Fiber Hollow-Core Cable Makes AI’s 90 km Reach a Supply Question

    TL;DR · 30-second read

    The Short Version

    Light moves faster through air than through glass. That is why cable maker Prysmian and fiber developer Relativity Networks are building cable with hollow strands, which carry data nearly 50% faster.

    They have now shown it can be reliably blown through plastic tubes at up to a brisk walking pace.

    Why care? Buildings that run artificial intelligence together must sit close enough to work in step. This cable could stretch that limit from about 37 miles to 56, making land and electricity easier to find. The companies have not said how much they can make or what it costs.

    Prysmian said in a July 22, 2026 press release that it and Relativity Networks had completed high-density cable deployment tests with conduit manufacturer Dura-Line. At Dura-Line’s test facility in Clinton, Tennessee, a cable using Relativity’s ChronoCore hollow-core fibers was installed at jetting speeds of up to 350 feet per minute. Jetting uses compressed air to carry a cable through a narrow duct.

    Prysmian also said its Claremont, North Carolina plant has made a 10mm-diameter cable containing 24 hollow-core fibers that meets customer attenuation requirements, meaning limits on signal loss. The company said it is scaling fiber production, including through investments in its Eindhoven facility, and that hollow-core cables are available now for AI data center deployment.

    Executive Summary

    Hollow-core fiber guides light through an air-filled channel instead of solid glass, and the companies say this moves data nearly 50% faster than conventional fiber. They argue the speed gain could extend the maximum distance between data centers in a synchronized cluster from 60 km to 90 km (56 miles).

    The July announcement addresses a more practical concern: whether this specialized fiber can be packed into a dense cable, manufactured in a commercial plant and installed with the microduct methods used in network construction. Microducts are small protective tubes that carry fiber cable. The reported results point toward yes on each count, although the published evidence includes few performance details.

    That shifts attention to commercial questions. A single 24-fiber cable on a 90 km route would require 2,160 km of hollow-core fiber, and Prysmian and Relativity have not disclosed production volumes, pricing or named customers. For AI infrastructure planners, those figures will help determine whether the extended reach can be built into real site plans.

    Why 24 Fibers Turns 90 km Into a Supply Question

    The reach argument comes down to timing. Data centers working as a synchronized cluster can only be so far apart before signals take too long to arrive. The companies put that limit at 60 km with conventional glass fiber. Because hollow-core fiber carries data nearly 50% faster, they say the limit could extend to 90 km, a 50% increase in reach.

    Relativity CTO Rodrigo Amezcua Correa set out the test for the technology: “A breakthrough fiber technology only matters if it can be manufactured, cabled, and deployed at scale.” The announcement offers evidence on each step, at differing levels of maturity. Production is being scaled, a commercial plant has put 24 fibers into a 10mm cable, and installation reached up to 350 feet per minute, or about 107 meters per minute. At that top speed, a continuous 90 km pull would take roughly 14 hours. Real builds proceed in segments and at varying speeds, but the figure suggests that placement speed is unlikely to be the main limit on a project of this length.

    Fiber volume is a harder constraint to assess. By our arithmetic, one 24-fiber cable over 90 km uses 2,160 km of hollow-core fiber, while two separate routes for resilience would use 4,320 km, before spares or additional cables. An operator planning a multi-site AI cluster needs to know whether that quantity can be delivered on schedule and at what price. Those are now the most consequential unknowns for buyers, even though the companies describe the cable as available now. Prysmian’s Eindhoven investment signals an intent to add capacity, but no output figure accompanies it.

    What the Clinton Test Does and Does Not Establish

    The jetting result has practical value. Compressed-air installation is a demanding step for a cable, and carrying it out with a commercial conduit manufacturer moves the work closer to field conditions than a fiber measurement alone. Combining Relativity’s fiber with Prysmian’s existing Sirocco cable architecture also builds on an established cable design instead of an entirely new one.

    The broader claims go further than the disclosed data. The headline says the companies “deploy” the cable, while the body describes tests at a dedicated facility. Those results are presented as showing readiness for real-world deployment, yet no duct length, route profile or post-installation signal-loss figure has been published. “Highest density” is also a comparison with the companies’ own hollow-core cables, not an industry benchmark. The cable “delivers the expected optical performance” and meets “customer attenuation requirements,” but neither phrase comes with a number.

    None of this undercuts the milestone, which is a reasonable step 15 months into the partnership. It does separate what has been shown, a successful installation test and plant production, from what still needs proof: sustained performance on long operating routes carrying live traffic.

    A Wider Map, Not More Power

    The siting implication is the strongest commercial argument. On a simple geometric view, raising the radius around an existing campus from 60 km to 90 km expands the potential search area by about 2.25 times. Actual fiber routes follow roads and rights-of-way rather than straight lines, so the usable gain would be smaller and would vary by location. Even so, more candidate sites matter to operators that the companies describe as competing for scarce land, power and water.

    A larger search area does not create any of those resources, however. A site 90 km away still needs its own electricity supply, permits and water plan, as well as a fiber route that can be built. Hollow-core fiber makes more locations eligible for a synchronized cluster without making any given site viable. The economic test is whether a site in the 60-to-90 km band offers enough advantage to justify any added cost for specialty fiber on that route.

    If the economics work, likely beneficiaries include operators with campuses near the current distance limit, landowners and power-rich areas in that wider band, and suppliers of the cable and conduit. Prysmian’s Claremont production also matters for a market it describes as the major US data center market, since cable made in the US may simplify logistics for domestic projects. How much advantage that offers depends in part on where the fiber itself will be produced, which the companies have not fully laid out.

    Background

    Prysmian, a Milan-based cable maker, formed its partnership with Relativity Networks to industrialize hollow-core fiber 15 months before this announcement, according to the company. In the arrangement described, Relativity contributes its ChronoCore fiber technology, while Prysmian provides high-density cable design and manufacturing and is scaling fiber production.

    Hollow-core fiber has drawn interest because AI data center networks are sensitive to latency, the time data takes to travel between points. If operators can place synchronized facilities farther apart, they can look beyond the immediate area of an existing campus for land, power and water, provided the specialized fiber can be produced and installed economically.

    Sources

    Source: Hollow Core Fiber: Prysmian and Relativity Networks deploy their highest density HCF cable to date, Prysmian’s July 22, 2026 press release on high-density hollow-core cable testing with Dura-Line.

  • Molex-Prysmian 10-Year Pact Shows AI Fiber Supply Starts at the Glass Preform

    Molex-Prysmian 10-Year Pact Shows AI Fiber Supply Starts at the Glass Preform

    TL;DR · 30-second read

    The Short Version

    Two companies behind the cables inside the giant computer buildings that run artificial intelligence have signed a ten-year deal. Molex, a maker of connectors, will supply its customers with glass-fiber cable made by Prysmian, one of the world’s biggest cable makers.

    Prysmian says it will spend $1.43 billion to more than double how much fiber it makes in the United States, adding about 600 American jobs. The money reaches all the way back to the first step: making the glass rods that fiber strands are pulled from.

    Artificial intelligence runs on light moving through these hair-thin threads, and big buyers now want supply promised a decade ahead.

    Molex and Prysmian have entered a 10-year supply agreement to expand fiber connectivity for AI data centers, Lightwave reported on July 21, 2026. Under the arrangement, hyperscalers (the largest cloud and internet operators) and data center builders can secure Prysmian fiber cable supply through Molex.

    Alongside the agreement, Prysmian will invest $1.43 billion to extend fiber cable production at U.S. plants, including the glass preform stage, which it says will more than double its domestic fiber capacity. The company expects to create 1,000 jobs worldwide, 600 of them at U.S. manufacturing sites.

    Executive Summary

    The deal pairs a connectivity specialist with one of the world’s largest cable manufacturers for a decade. Molex CEO Joe Nelligan called it “a strategic expansion in the U.S., bringing increased capacity to support the growing demand for data center solutions.” Prysmian CEO Massimo Battaini said the agreement and capacity investments “strengthen our leadership in data centers.”

    What makes the announcement more than a distribution tie-up is where the money goes. Prysmian’s investment reaches upstream to preform, the glass that every strand of fiber is drawn from. That is the step that determines whether new cable capacity is real or merely a reshuffling of existing output, and it is why a ten-year term makes sense for both sides.

    For data center buyers, the agreement adds another source of fiber connectivity in a market where Corning has already signed a string of large partnerships. For Prysmian, it marks a push from grid, long-haul and submarine cable into the fiber that runs inside data centers, a segment it forecasts will add $11 billion of value through 2035.

    Why AI Fiber Capacity Starts at the Glass Preform

    Optical fiber begins as a preform: a thick rod of ultra-pure glass that is heated and drawn into strands thinner than a human hair, which are then bundled and jacketed into cable. The sequence matters. A manufacturer can add cabling lines, but unless it buys glass from someone else, the amount of fiber it can ship is capped by how much preform it can make. So the most telling detail in this announcement is not the $1.43 billion figure itself but where it is spent: extending U.S. production “including the glass preform stage,” with the stated result of more than doubling Prysmian’s domestic fiber capacity.

    Doubling fiber output without more preform would simply move the constraint one step upstream. Glass-making capacity is a long-lived asset, and a commitment of this size is easier to underwrite against a long contract than against spot orders. The ten-year term lines up with that logic, and with Prysmian’s own planning horizon, which runs to 2035.

    The people affected are those who buy connectivity for AI clusters, where large numbers of processors and switches are linked by fiber. Customers who source through Molex gain access to supply backed by new glass capacity rather than a reallocation of existing cable. The broader lesson for buyers is practical: a fiber or connectivity supply promise is only as firm as the preform behind it, and where a supplier’s glass comes from is now a fair question in any procurement discussion.

    Molex Turns Itself Into a Route to Fiber Supply

    Molex is best known for connectors, not glass. The agreement repositions it as a channel through which hyperscalers can lock in fiber cable, with both companies stressing “supply chain optionality and resilience through diversified sourcing” and improved lead-time reliability. The company describes the deal as one pillar of a broader global strategy to scale fiber cable supply, which suggests Molex intends to add further sources rather than rely on one.

    The more interesting fit is with Molex’s work on co-packaged optics (CPO), which places optical connections directly beside a processor or switch chip instead of in pluggable modules at the edge of the equipment. That shortens the electrical path, which matters as AI systems push more data between chips. Molex recently completed its acquisition of Teramount, a fiber-to-chip connectivity provider, and has expanded its CPO interconnect toolkit. A vendor that controls both the connection at the chip and a long-term supply of the cable leading to it can offer customers a more complete package than either piece alone.

    Corning Has Already Drawn the Map

    Molex and Prysmian are following a pattern rather than inventing one. Corning has secured multi-billion-dollar partnerships across nearly every layer of the AI connectivity chain: a service provider (Lumen), cloud and data center operators (Amazon and Meta), GPU maker NVIDIA, chip designer Broadcom and connector maker US Conec. The common thread is fiber producers tying their manufacturing to the companies that design, buy and install AI infrastructure, years in advance.

    For buyers, a second vertically linked supply chain is useful in its own right: it provides an alternative, and with it some negotiating leverage, when demand is outrunning manufacturing. For Prysmian, the agreement extends a business built on power grid cable, long-haul digital links and submarine telecom into the “inside” data center market, which it expects to grow with modernization cycles for performance and energy efficiency, AI-driven architecture changes and higher fiber density.

    What the Numbers Do and Do Not Establish

    Several figures in the announcement are firm commitments: a ten-year agreement, a $1.43 billion investment, a doubling-plus of U.S. fiber capacity, and 1,000 expected jobs, 600 of them in the U.S. Others are forecasts. Prysmian values the data center segment at $11 billion on an incremental basis through 2035 compared with 2025, including $1 billion of yearly revenue from 2031. That is a projection of market opportunity, not contracted business.

    The capacity claim is also relative. “More than double” is measured against a current baseline that has not been quantified publicly, so the absolute amount of new fiber, and how much of it is earmarked for Molex customers, cannot yet be calculated. That does not weaken the direction of the deal; it limits how precisely anyone can size it.

    Background

    Prysmian is one of the world’s largest cable makers, operating 112 manufacturing facilities in 50 countries, including more than 20 plants in North America. Its U.S. footprint includes optical fiber plants in Claremont and Lexington and a submarine cable facility under development in Somerset, Massachusetts. Historically its data center business has centered on energy and long-distance digital connections, such as grid cables and long-haul fiber, rather than cabling inside the building.

    Molex is a connectivity manufacturer led by CEO Joe Nelligan. It has been building out co-packaged optics interconnect products and recently completed its acquisition of fiber-to-chip specialist Teramount. Demand for fiber inside data centers is being driven by modernization cycles aimed at performance and energy efficiency, AI-driven changes in system architecture and rising fiber density, the same forces behind Corning’s recent partnerships with cloud providers, chipmakers and connector firms.

    Sources

    Source: Molex and Prysmian enter fiber AI data center supply pact, Lightwave’s report on the companies’ 10-year fiber supply agreement and Prysmian’s $1.43 billion U.S. capacity expansion.

  • Savannah River Pick Shows DOE’s 16 AI Sites Are a Power Bet, Not Just a Land Deal

    Savannah River Pick Shows DOE’s 16 AI Sites Are a Power Bet, Not Just a Land Deal

    TL;DR · 30-second read

    The Short Version

    The United States government is opening some of its own land to companies that want to build the huge computer warehouses that run artificial intelligence. One of the first chosen sites is in South Carolina, at a lab that supports the nation’s nuclear weapons work.

    The twist: these projects are meant to come with their own power plants. The biggest artificial intelligence facilities can need as much electricity as a large power plant produces, and building power on-site is meant to keep that cost off ordinary households’ bills.

    Engineering firm Amentum was picked to build it. No price, size or start date has been announced.

    Microgrid Knowledge reported on July 20, 2026 that the National Nuclear Security Administration (NNSA), part of the U.S. Department of Energy (DOE), has selected Virginia-based engineering firm Amentum to develop a co-located artificial intelligence data center and on-site power generation project at the Savannah River National Laboratory site in South Carolina. The selection followed a competitive request for proposals that DOE began last year, after identifying 16 federal sites it judged could host AI data centers paired with their own energy infrastructure.

    The effort, formally the Savannah River Site Artificial Intelligence Infrastructure and Energy Generation Project, has no announced timeline, generating technology, capacity or cost. DOE says the project could meet its own electricity needs without shifting large costs to utility customers and could also increase the power available to the grid.

    Executive Summary

    NNSA has named Amentum to lead construction of both an AI data center and the power plant that would feed it, on federal land at one of the country’s principal nuclear security sites. It is a concrete step in DOE’s program to put AI computing on government property, and the first selection at Savannah River under that program.

    The significance lies less in the land than in the pairing. DOE did not simply offer acreage; it screened its sites for their ability to host data centers together with co-located generation, and it justified the Savannah River project on the grounds that it would not push large grid-upgrade costs onto utility customers. That makes federal sites a potential route around the slowest and most politically sensitive part of AI buildout: getting enough electricity to the building.

    What has been announced is a selection and a scope, not a financed, sized project. The generating technology, megawatt capacity, tenant, financing and schedule are all still undisclosed, so the model’s claims about cost and grid benefits remain untested.

    Sixteen Sites, One Condition: Bring the Power

    DOE’s list of 16 federal sites was not a catalogue of empty lots. According to the department, it identified sites that could support AI data centers paired with co-located energy infrastructure. The Savannah River award makes that pairing explicit: generation is in the project’s official name, and Amentum is contracted to build the power supply alongside the data center rather than to plug into whatever the local utility can provide.

    The reason is the grid connection itself. A large new electricity user normally joins the grid through an interconnection process, in which the utility studies whether its lines and power plants can serve the new load and what must be built if they cannot. At AI scale, those upgrades are substantial: industry projections cited in the coverage put future AI server racks at up to 1 megawatt each and the largest AI campuses at around 1 gigawatt, roughly the output of a large power plant. When a utility builds for a customer that size, the question of who pays tends to fall on its other customers. DOE’s stated case for Savannah River answers that directly, saying the project could generate its own needs “without shifting huge costs to utility customers.”

    That is where federal land earns its place. A large, secured, government-controlled site offers space, a single landowner and an existing security perimeter for putting generation right next to the load, which many sites closer to population centers struggle to offer. The trade-off is engineering: AI training creates wide, fast swings in power demand, and a self-supplied site has less grid backing to absorb them. Whatever generation Amentum ultimately builds will need to be designed around that volatility, which makes the power system as central to the project as the data center it serves.

    Why a Nuclear Security Site, and Why Amentum

    NNSA Administrator Brandon Williams framed the award as a way to “move faster, apply innovative technologies, and make productive use of federal land while maintaining our commitment to mission delivery.” That last clause matters. Savannah River hosts sensitive defense work, and any private-sector partner operating there has to coexist with it. Amentum already does; it was selected earlier this year to provide design and engineering services for the site’s Tritium Finishing Facility, which supports the nuclear weapons program.

    That existing footprint is a competitive advantage that is hard to replicate. Contractors that already understand federal security, procurement and site operations are positioned to win the first wave of these awards, while conventional data center developers may find their route onto federal land runs through partnerships with such firms. Amentum and NNSA say they will collaborate on expanding private-sector partnerships in the project, which leaves room for tenants, financiers or generation owners still to be named.

    What Is Settled, and What Still Rests on “Could”

    The announcement establishes a selection made through a competitive process, a defined scope covering both compute and generation, and a named site. Those are real commitments of intent from a federal agency. The headline benefits are conditional, however: the project could meet its own electricity needs, and it could increase power available to the grid. Williams himself called it a “proposed partnership.”

    Until the parties disclose the generation type, capacity and commercial structure, the ratepayer-protection claim cannot be measured. Its value depends on details not yet public: whether the site stays connected to the grid for backup, who pays for that connection, and on what terms any surplus power is sold. The first projects under DOE’s program will set the template for the remaining sites, so those terms will matter well beyond South Carolina.

    Background

    The Savannah River Site in South Carolina is a Department of Energy complex overseen by the National Nuclear Security Administration, the DOE agency responsible for nuclear weapons and nuclear security. Its national laboratory supports defense programs including tritium production. Amentum, a Virginia-based firm spun out of AECOM about six years ago, ranks as the second-largest U.S. government services contractor behind Leidos and was already working at the site on the Tritium Finishing Facility.

    The award sits within a wider federal push to use government land for AI infrastructure. DOE identified 16 of its sites as candidates for data centers paired with their own power, and Energy Secretary Chris Wright has described the AI race as “the next Manhattan project.” The pressure behind that push is electricity: an analysis by the Penn State Institute of Energy and the Environment projects AI’s share of global electricity use could rise from 4% to 20% by 2035.

    Sources

    Source: Amentum to Develop Co-Located AI Data Center and Power Infrastructure at Savannah River National Laboratory (Microgrid Knowledge, July 20, 2026): NNSA selects Amentum to build an AI data center with on-site power generation at the Savannah River Site.

  • PowerPlay’s 400 MW Abilene Plan Shows How AI Builders Route Around the Grid Queue

    PowerPlay’s 400 MW Abilene Plan Shows How AI Builders Route Around the Grid Queue

    TL;DR · 30-second read

    The Short Version

    A company called PowerPlay AI wants to build a very large artificial intelligence computing center outside Abilene, Texas. It plans to make its own electricity on site from natural gas instead of waiting to plug into the public power grid.

    The target is 400 megawatts by 2028. That is roughly the electricity a mid-sized American city uses.

    Why it matters: new projects can wait many years for a grid connection. Building your own power skips that line. The partner, the money and the customers have not been named yet.

    PowerPlay AI announced on July 20, 2026, in a release distributed via PR Newswire, an initial 400-megawatt “behind-the-meter” AI data center development in the greater Abilene area of West Texas. Behind-the-meter means the campus would be powered by generation on or next to the site rather than drawing its main supply from the public grid. The project is a joint venture with a Nasdaq-listed “neocloud,” a specialist cloud provider that rents out AI computing capacity. The partner is not named.

    According to the release, the joint venture has completed site feasibility work, infrastructure assessment and land acquisition. It is now progressing natural gas service agreements and moving toward selecting a preferred independent power producer after a request-for-proposal process. The target is to deliver the first 400 megawatts of behind-the-meter power in 2028.

    Executive Summary

    The announcement is a power-first data center plan. PowerPlay AI describes itself as a company that turns raw land into “power-secured, shovel-ready sites” for hyperscalers (the largest cloud companies) and data center operators. Here it is pairing that model with a publicly traded neocloud. The site is unincorporated, which the company says frees it from zoning restrictions. It is served by installed natural gas and adjacent fiber, and it sits near several gigawatt-scale AI campuses that are operating, under construction or proposed.

    It matters because of the rationale PowerPlay gives. Luke Velterop of PowerPlay AI said interconnection queues, the waiting lists to connect new large loads and generators to the grid, “now stretch into the 2030s.” A 2028 target from on-site gas generation is a direct bid to beat that timeline. The plan also echoes federal policy that, in the company’s words, calls on industry to “build, bring or buy” its own energy.

    The release discloses a scale, a location, a fuel and a date. It does not disclose the partner, the financing, a customer or a signed power contract. It describes an early but real development rather than a campus under construction.

    Why Behind-the-Meter Is the Whole Strategy

    The conventional route for a large data center is to request a grid connection and wait. The utility and the grid operator must study whether the transmission system can carry the new load, and upgrades can take years. PowerPlay’s own framing puts that wait into the 2030s. Its answer is to change the order of operations. First it secures a site with a gas pipeline already in the ground; the release includes a photo captioned as a March 2026 pipeline installation. Then it contracts an independent power producer, a company that builds and runs power plants and sells the output, to generate electricity at the campus. On that sequence, the project targets 400 megawatts in 2028, years ahead of the queue timeline the company cites.

    That is the mechanism behind the headline. The binding constraint on this project is no longer a place in line with the utility. It is a gas supply agreement, a generation contract and the equipment to build a plant. Those are commercial negotiations a developer can push forward, rather than an administrative queue it cannot. The groups affected are neoclouds that need capacity quickly to serve customers renting AI chips, and landowners with pipeline access, who now hold a scarce asset. Utilities and grid operators also lose some of their role as the gatekeeper for where large AI loads can appear.

    This is one project, and it does not prove that the grid is being abandoned. It does show clearly what a developer now treats as the scarce input. PowerPlay has spent its effort so far on land, gas and a power producer, not on tenants.

    The Queue Doesn’t Disappear, It Moves

    Bypassing the grid swaps one set of risks for another. The release says the joint venture is “progressing” gas service agreements and “moving toward” choosing a power producer. Neither the fuel contract nor the generation partner is final. Gas-fired generation equipment has its own procurement lead times. A plant of this size also needs air permits before it can run. The 2028 date depends on all of these steps landing on schedule.

    Reliability is the other trade-off. A grid-connected campus can fall back on the wider system when a generator trips. An islanded campus has to build in spare generating capacity and redundancy to reach the uptime that AI customers expect. That usually means the plant must be larger than the computing load, or the usable computing capacity will be smaller than the headline power figure. The release gives 400 megawatts of power. It does not say how much of that becomes rentable computing capacity. Fuel cost is a third exposure: an on-site gas plant ties the campus’s operating costs to natural gas prices in a way that a blended grid tariff partly smooths out.

    A Land-and-Power Developer Meets a Neocloud

    The joint venture divides the work in a sensible way. PowerPlay’s stated business is assembling land and securing power. The neocloud partner, which the release credits with “world-class AI infrastructure expertise,” presumably supplies the computing side and the customer relationships. Neoclouds compete with the largest cloud providers mainly on how quickly they can bring GPU capacity online. A partner that brings its own power addresses the problem that most often delays them.

    The release also says the project is positioned for “engagement with leading AI infrastructure operators and hyperscalers.” That suggests the campus is still looking for end users rather than delivering for a signed tenant. That is normal at this stage, but it is the difference between a power-secured site and a financed data center. Readers weighing the announcement should treat the 400 megawatts as a development target backed by land and gas access, not as contracted capacity.

    Why Abilene, and Why Now

    Location is a central part of the pitch. The company says the site is near several gigawatt-scale AI campuses, which gives it an existing ecosystem of contractors, fiber routes and workers experienced in large builds. An unincorporated site avoids municipal zoning review, one fewer approval on the critical path. Being part of a cluster cuts both ways, though. Nearby projects compete for the same construction labor, generation equipment and pipeline capacity. The first advantage PowerPlay cites, speed, depends on securing those inputs ahead of its neighbors.

    Background

    PowerPlay AI, legally PowerPlay AI Pty Ltd according to the release’s disclaimer, describes itself as a developer that transforms raw land into power-secured, shovel-ready sites for enterprises, hyperscalers and data center operators, “taking AI infrastructure from ground to gigawatt.” Its announcement was issued from New York.

    The Abilene area of West Texas has become one of the country’s most closely watched AI data center corridors. It is home to the Crusoe-developed campus associated with OpenAI and Oracle’s Stargate project, along with other large campuses built or proposed nearby. Texas combines abundant natural gas, available land and its own grid operator, ERCOT. Developers are pairing these more and more with on-site generation as demand for AI computing runs ahead of what the grid can connect quickly.

    Sources

    Source: PowerPlay AI Announces 400 MW Behind-the-Meter AI Data Center Development in Greater Abilene with Nasdaq-Listed Neocloud Joint Venture Partner (PR Newswire, July 20, 2026) — PowerPlay AI’s announcement of a gas-powered, behind-the-meter AI campus joint venture near Abilene, Texas, targeting 400 MW in 2028.

  • BofA’s 100 GW Gap Shifts the AI Power Debate From Forecasts to Who Builds and Pays

    BofA’s 100 GW Gap Shifts the AI Power Debate From Forecasts to Who Builds and Pays

    TL;DR · 30-second read

    The Short Version

    America’s artificial intelligence boom may need far more electricity than power companies plan to supply. Bank of America analysts expect a shortfall by 2030 about equal to the output of 100 large nuclear reactors.

    Some builders of giant computing centers may make their own power on site, often with natural gas engines. Some coal plants due to close are staying open.

    The big unresolved question is who pays. The answer could shape what households and businesses see on their electric bills.

    Utility Dive reported on July 17, 2026 that Bank of America analysts expect the United States to need more than 230 gigawatts (GW) of new generating capacity over the next five years, while regulated utilities add only about 93 GW of accredited supply, leaving a gap of more than 100 GW. Data centers alone could add roughly 125 GW of electric load, helping push electricity demand growth to a 4.1% compound annual rate from 2026 through 2030.

    With large gas turbines largely sold out through 2030, the analysts expect data center developers to turn increasingly to on-site gas engines. They expect utilities to extend coal plant operations, deploy batteries and pursue transmission upgrades.

    Executive Summary

    BofA’s forecast puts a number on a problem the power and data center industries have been circling: planned utility additions cover only a minority of the capacity the analysts think the country will need by 2030. About 93 GW of accredited utility supply set against more than 230 GW of need is roughly 40% coverage.

    The more useful part of the report concerns what happens next. More than 7.5 GW of data center projects with on-site generation are under construction and another 60 GW-plus are in pre-construction. Coal plants in seven states have had retirements delayed or canceled, and engine manufacturers have expanded production. Each of those responses carries its own costs, and utilities and regulators are still working out how to allocate the cost of new infrastructure.

    That is why the planning question is changing. Utilities have raised their demand forecasts in each of the past three years, so attention is moving toward which assets can be delivered by 2030 and who will finance them. The forecast itself still depends on a fast AI hardware rollout, which is the main assumption to test.

    Why the Debate Is Moving Past the Forecast

    For years, the central argument in utility planning was whether projected data center demand would show up. BofA’s analysts take a firmer position. “The market is no longer constrained by demand — it is constrained by where power can actually be delivered,” they wrote. Their evidence is that utilities have revised demand forecasts upward in each of the past three years as AI-related load has arrived faster than expected.

    The arithmetic explains the shift. Against a need of more than 230 GW, regulated utilities are expected to add about 93 GW of accredited supply, a shortfall the analysts put at more than 100 GW. Even if demand came in somewhat below the forecast, a gap of that size would still leave planners deciding which resources to build, extend or contract, and who should carry the cost. Data centers’ roughly 125 GW of added load is a bit over half of the 230 GW figure, although load and generating capacity are not identical measures. The requirement is therefore larger than data centers alone.

    The demand question is not fully closed, however. The outlook rests largely on projections from BofA’s semiconductor analysts about how quickly AI chips and servers will be deployed. A slower hardware rollout would change the size of the gap, so the claim that demand is no longer the constraint is strongest as a description of the current market and depends on that rollout continuing.

    On-Site Power Is Growing, but 7.5 GW Is Not 100 GW

    The most visible response is behind-the-meter generation, meaning power plants built at the customer’s site rather than supplied solely through the utility grid. More than 7.5 GW of such data center projects are under construction, which is a small fraction of a gap exceeding 100 GW. Adding the 60 GW-plus in pre-construction brings the pipeline to more than 67.5 GW. That still falls short of the gap, and projects in pre-construction are not yet being built.

    Equipment availability is shaping the technology choice. Large gas turbines remain the preferred source of flexible power, but manufacturing capacity is largely committed through 2030 and new units can take years to enter service after shipment. Reciprocating engines, which work on a similar principle to a very large car engine, can be deployed faster and respond quickly to changing loads. Caterpillar, INNIO, Rolls-Royce and Wärtsilä have expanded production, according to the analysts.

    On-site generation does not take these projects off the grid. BofA expects facilities to pair self-generation with traditional grid connections to improve reliability and shorten timelines. Developers would therefore take on more of the power-plant work while still relying on utilities, which keeps questions about grid costs and connection terms open.

    The Capacity on Paper May Overstate What Shows Up at Peak

    The analysts also argue that planned additions may overstate available supply. A resource’s nameplate rating is its maximum output, while accredited capacity reflects what grid planners can count on during peak demand. Wind and solar typically earn less accreditation than their nameplate ratings suggest, so BofA concludes that firm resources, meaning those that can run on demand, will remain essential even as renewable generation expands.

    That helps explain why existing plants have become part of the plan. The report identifies coal plants in Maryland, Wisconsin, Indiana, Utah, Kansas, Nebraska and Mississippi whose retirements were delayed or canceled to preserve dispatchable capacity. Batteries, transmission expansion and regulatory changes that make fuller use of existing generators could also help.

    Transmission is the slowest of these options. BofA cites the Champlain Hudson Power Express, which took 16 years from planning to energization. That is one example rather than a typical schedule, but it shows why new lines may do little for a shortfall measured through 2030. It also gives weight to the analysts’ emphasis on where power can actually be delivered, since generation in one region does not help a site the grid cannot reach.

    Who Pays Is the Harder Question

    Prices are unlikely to close this gap on their own. Academic research cited in the report suggests a 10% increase in real electricity prices typically reduces consumption by 1% to 2% in the short to medium term. Set against forecast demand growth of 4.1% a year, that reduction is less than half of one year’s projected increase.

    Limited price response puts more weight on cost allocation. Utilities and regulators are already addressing how to connect large new loads and divide the cost of new infrastructure. BofA notes that higher power prices could cause some demand destruction among customers and energy-intensive industries, so these decisions could reach well beyond the data center sector.

    The likely mix of solutions also spreads costs differently. On-site engines place more of the build-out with developers, life extensions for existing plants run through utilities and their regulators, and transmission can involve many parties over many years. The choice of what gets built is therefore closely tied to who ends up paying for it.

    Background

    US electricity consumption grew little for about a decade as efficiency improvements, LED adoption and distributed solar generation offset new demand. AI infrastructure has changed that outlook, and utilities have raised their demand forecasts in each of the past three years. Because turbines, transmission lines and other grid assets can take years to deliver, faster load growth can quickly become a supply problem.

    Regulators are responding as well. The Federal Energy Regulatory Commission has issued a decision on data center interconnection, the process of connecting a facility to the grid. In June, Texas, facing a 438 GW queue, approved an initial large-load interconnection process. These moves reflect the same issue at the center of BofA’s report: how large new customers connect to the system and on what terms.

    Sources

    Source: AI data center growth could force US utilities to rethink generation plans, BofA says, Utility Dive’s July 17, 2026 brief on Bank of America’s forecast of a US electricity supply gap through 2030.

  • Project Tango’s 5-1 Denial Shows AI Campuses Can Outgrow Local Zoning Codes

    Project Tango’s 5-1 Denial Shows AI Campuses Can Outgrow Local Zoning Codes

    TL;DR · 30-second read

    The Short Version

    County leaders in Palm Beach County, Florida, voted 5 to 1 to turn down Project Tango. It was a giant complex of computers for artificial intelligence, planned near about 2,400 homes and an elementary school.

    A big worry was a constant low hum, day and night. The builders said cooling would need a one-time fill of about 650,000 gallons of water, roughly one Olympic swimming pool.

    The bigger lesson is that local building rules are struggling to decide what these new facilities even are. The developer can try again.

    Palm Beach County commissioners on Wednesday, July 15, 2026, voted 5-1 to deny without prejudice Project Tango, a proposed AI data center campus in Loxahatchee, WPEC (CBS12) reported. The vote followed hours of debate over low-frequency noise, water use, traffic and compatibility with a rural area that opponents said now includes about 2,400 homes and Saddle View Elementary School. Commissioner Maria G. Marino cast the lone vote in favor. Mayor Sara Baxter recused herself on the County Attorney’s advice because of her prior public statements opposing the project.

    The request before the board covered Phase 2 of the site: 280,000 square feet of data and information processing, 148,000 square feet of cooling-related utility space and about 1.15 million square feet of warehouse. The applicant projected a $34.5 billion asset at build-out over six to seven years and about $561 million in tax revenue at build-out.

    Executive Summary

    Project Tango did not fail on a single number. It failed because commissioners could not agree with the applicant on what the project was. The developer’s attorney argued that data processing was already a permitted use on a site approved years ago for economic development. County staff answered that the application would add roughly 1.5 million square feet to that approval. One commissioner called the proposal “an AI hyperscale whatever” and questioned whether the county’s definitions had kept pace.

    That dispute is the part that matters beyond Palm Beach County. Many AI data center plans rely on land entitlements granted for warehouses, light industry or generic economic development. Project Tango shows a local board declining to treat those older approvals as covering a 24-hour computing campus. The questions it pressed hardest, on low-frequency noise and on water, are ones existing codes were not written to answer.

    Because the denial was without prejudice, the applicant can return with a revised plan. The hearing showed fairly clearly what the next attempt would need to bring: independent expert evidence, a named end user, and firmer answers on noise and water.

    An AI Campus the Zoning Code Wasn’t Written For

    The sharpest exchange of the hearing was about categories rather than engineering. Applicant attorney Brian Seymour described the request as an “allocation of permitted uses, not a new use,” noting that data and information processing is already allowed under the county’s code for the site. County staff rejected that framing directly: “That is incorrect. That is why we are here today. This application is to add square footage.” Staff said the site is approved for 2,020,000 square feet of Economic Development Center uses and that the request would add about 1.5 million square feet to the master plan. Opponents described the result as a 3.6-million-square-foot campus.

    Commissioner Joel Flores put the underlying problem plainly: “This is not exactly a data center. This is something new.” He said he was struggling with whether the county was relying on older definitions “just because they haven’t been updated.” The applicant argued the campus should be treated as light industrial and noted it would replace existing heavy industrial operations, including asphalt and concrete plants. By conventional land-use logic, that is a reasonable argument, since a data hall generates little truck traffic or dust. But a hyperscale AI campus (a very large facility built to run AI workloads at scale) runs around the clock, needs substantial cooling equipment and draws significant electricity. Those traits do not map neatly onto a code category written for offices, warehouses or light manufacturing.

    This matters for developers and investors who treat an existing entitlement as a de-risked asset. Project Tango is a single case and should not be read as a statewide trend. It does show that a board can decline to extend a years-old approval to cover an AI campus, even when the use is technically listed, if it concludes the scale and operating profile are materially different from what was approved. Sites whose value depends on legacy economic-development or industrial zoning carry that risk until local codes define AI facilities explicitly.

    Closed-Loop Cooling Shifted the Water Question Instead of Settling It

    The applicant’s water figures for the computing itself were modest. Its engineer said the campus would use a closed-loop cooling system, which circulates the same water rather than evaporating it daily. The data processing portion would use about 1,696 gallons per day, mostly for restrooms, sinks and kitchens. For comparison, county Water Utilities Director Ali Bayat said the neighboring Arden community uses about 400,000 to 500,000 gallons of drinking water a day. On that basis, daily data center use would be well under 1% of the neighborhood’s use.

    Scrutiny moved to other parts of the plan. The system would need a one-time fill of about 650,000 gallons, roughly a day and a half of Arden’s consumption. The warehouse portion was projected at about 50,000 gallons a day, around a tenth of Arden’s daily use. When Commissioner Maria Sachs asked who would be using it, Seymour said he did not know the headcount because that information came from the contract purchaser. Flores also asked what happens if the loop water must be drained or becomes contaminated. The applicant’s environmental health expert said it would be collected and disposed of off-site under Florida rules.

    The lesson for operators is that closed-loop designs can defuse the familiar evaporative-cooling objection, but that alone does not end the conversation. Boards will ask about every gallon on the site plan. A number without a named user or an explanation reads as a gap, whatever the cooling design.

    Why Meeting the Noise Standard Didn’t End the Noise Debate

    Low-frequency noise drew one of the longest lines of questioning. The applicant’s experts said the project would meet county noise standards and keep levels near Arden and the school within existing ambient levels. Acoustics expert Dr. Norm Bronner acknowledged that low-frequency noise “will exist,” but said it likely would not be particularly noticeable at the predicted levels. Commissioners focused on whether a constant hum would be audible to residents and students. “We’re not talking about music,” Sachs said. “We’re talking about a hum that resonates.”

    The one measurement taken in the chamber illustrates why compliance with the standard did not settle the matter. During a quiet moment, the applicant’s expert recorded 43.9 dBA and 59.8 dBC. A-weighted decibels (dBA), common in noise rules, discount low frequencies roughly as the human ear does at moderate volume. C-weighted readings (dBC) count low frequencies more fully. A gap of about 16 decibels in an ordinary quiet room shows how much low-frequency energy an A-weighted limit can leave out. That is the kind of sound a round-the-clock campus of fans and chillers produces.

    Seymour offered pre- and post-operation noise studies, with shutdown or mitigation if the project failed its conditions. That is a meaningful commitment on paper. However, it asks a board to approve first and verify later. Sachs said she could not accept the project without a scientist able to vouch for a comparable operating facility. That standard points developers toward bringing measured data from existing sites rather than modeled projections alone.

    What the Denial Leaves on the Table

    The economic case was substantial: a projected $34.5 billion asset at build-out over six to seven years, much of it in equipment and computers, and about $561 million in tax revenue at build-out. Commissioner Marino, the lone dissent, said, “I would say we need this.” Other commissioners did not dispute the size of the investment. They said the evidence on compatibility was incomplete, and Vice Mayor Woodward said approval would require “a lot more experts, conditions.”

    Denial without prejudice keeps the project alive in principle. A resubmission would likely need to resolve the square-footage dispute with staff, identify the end user, explain the warehouse water figure and bring independent low-frequency noise evidence. The hearing also carried signs of how heated the local debate had become. Flores disclosed that his office had received threatening calls, and a court had denied an emergency request to block the hearing. Any developer returning to this site, or pursuing a similar one elsewhere in Florida, should expect a long and closely examined process.

    Background

    The Project Tango site in Loxahatchee was approved in 2016 for Economic Development Center uses and currently hosts heavy industrial operations, including asphalt and concrete plants. Residential growth has since surrounded it. The Arden community and Saddle View Elementary School now sit nearby, and opponents put the number of surrounding homes at about 2,400. Residents said they learned of Project Tango about eight months before the vote.

    In Florida, land-use decisions like this one are quasi-judicial. Commissioners act somewhat like judges, weighing evidence presented at a hearing, and they must avoid appearing to have prejudged the case. The Project Tango fight reflects a wider pattern in which AI data centers, designed to run power-hungry computing around the clock, are testing local zoning codes written before such facilities existed at this scale.

    Sources

    Source: Palm Beach County commissioners reject controversial Project Tango AI data center (WPEC): CBS12 coverage of the July 15, 2026 commission vote on the Loxahatchee AI data center proposal.

  • Submer’s €1bn Flix Bet: An AI Cooling Firm Sees the Value in Land and Power

    Submer’s €1bn Flix Bet: An AI Cooling Firm Sees the Value in Land and Power

    TL;DR · 30-second read

    The Short Version

    A Barcelona company best known for keeping computers cool is spending about €1 billion to build and run its own huge computer warehouse for artificial intelligence.

    Submer plans to put it on the grounds of an old chemical factory in the Spanish town of Flix, which stopped operating in 2023. Catalonia’s regional president turned out for the announcement.

    What makes it interesting: a company that used to sell equipment to building owners now wants to be the owner. It has not yet said how big the site will be, when it opens, or who will use it.

    Submer, the Barcelona-based company that built its name in immersion cooling, plans a €1 billion ($1.14 billion) AI data center on the site of the former Ercros chemical plant in Flix, Catalonia, Data Center Dynamics reported. The facility will be built in two phases and operated by Rubix Data Centers, the AI data center division Submer launched in June, which aims to lease it to a single tenant running AI workloads.

    The project was unveiled on Saturday, July 11, at an event attended by Salvador Illa, president of the government of Catalonia, and Miquel Sàmper, the regional minister of business and labor. Submer has not disclosed the facility’s planned capacity or construction timeline; renders appear to show four data halls arranged around a central building.

    Executive Summary

    The headline number is €1 billion, but the more consequential fact is who is spending it. Submer’s business has been supplying cooling systems to other people’s data centers. With Flix, it becomes a developer and operator in its own right, following last year’s launch of the InferX AI cloud platform and June’s launch of Rubix Data Centers.

    Submer CEO Patrick Smets framed the move as a deliberate climb up the value chain: “we will expand across the full stack, from land and power to cloud and Edge.” Rubix, led by former Stack executive John Eland, leads its pitch not with cooling technology but with a claim of 8GW of power available across vacant sites in the Americas, EMEA and APAC. That ordering signals where the company believes durable value in AI infrastructure now sits.

    What the announcement does not yet establish is the project’s scale, power supply, financing or customer. Until those are disclosed, Flix is best read as a statement of strategy and site selection rather than a funded, contracted build.

    From Selling Cooling to Owning the Building

    Submer’s trajectory over roughly a year tells the story: an immersion cooling specialist (immersion cooling submerges servers in a non-conductive liquid to carry heat away more efficiently than air) launched an AI cloud platform, InferX, then a data center division, Rubix, and now a €1 billion campus. Each step moves the company closer to the end customer and further from being a component supplier.

    The economic logic is straightforward. An equipment vendor is typically paid once per deployment, and its fortunes depend on how many facilities its customers build. An operator that leases a facility earns recurring rent for the life of the lease and controls the asset that everything else depends on: the site, the building and its power supply. Smets’ own phrasing, “from land and power to cloud and Edge,” puts land and power first. Eland made the same point from the operator’s side: “We intend to operate the facility we are building here, so we are not simply passing through Flix.”

    That is the substance behind reading Flix as a bet on land and power rather than on cooling hardware. The company has not said whether Submer’s own immersion systems will be deployed at Flix, which underlines the point: the announcement is about owning capacity, not showcasing a product.

    Why Power Is the Asset Rubix Leads With

    For AI data centers, the scarce input is increasingly not buildings or servers but a site with a large, deliverable grid connection. That is why Rubix’s headline claim is 8GW of available power across vacant sites, a figure measured in gigawatts, or thousands of megawatts. Framing a data center business around power first reflects how the market now prices development opportunities.

    Former heavy-industrial sites such as the Ercros plant are attractive candidates in principle, because industrial users often required substantial electrical infrastructure and the land is already zoned for industrial use. Ercros also operates a solar farm on the site today. But Submer has not said what grid capacity is available at Flix, whether it is already connected, or how the solar installation fits into the project’s power plans. Those details will determine how quickly and how large Flix can realistically become.

    The 8GW figure deserves the same even-handed reading. It is a claim about power available across vacant sites, and Rubix has not broken it down by location, by grid status or by how much of it is contractually secured versus identified. As a signal of ambition it is clear; as a measure of deliverable capacity it is not yet substantiated.

    The Single-Tenant Model Cuts Both Ways

    Rubix aims to lease Flix to a single tenant for AI workloads. This build-to-suit approach is common for large AI campuses: one creditworthy customer on a long lease can anchor the financing for a very large build, and two-phase construction lets capital be deployed in step with demand.

    The flip side is concentration. Until a tenant signs, the €1 billion figure describes an intended investment rather than a committed one, and the facility’s design, timing and financing will likely hinge on that single counterparty. Without a disclosed capacity, it is also impossible to judge whether €1 billion is a large or modest sum per megawatt relative to comparable AI builds.

    A Supplier Becoming a Peer, With Political Backing

    Moving into operations can create tension with existing customers: data center operators that buy Submer cooling may now find the same company bidding for AI tenants. How Submer manages that overlap between its cooling business and Rubix will be worth watching.

    On the other side of the ledger, the project arrives with visible public support. The presence of Catalonia’s president and its business minister at the launch, and Submer’s framing of the project as part of the “reindustrialization of Flix,” suggest the regional government sees AI infrastructure as a use for idled industrial land. That backing can matter for permitting and grid access, though no specific commitments from the administration were announced.

    Background

    Submer, based in Barcelona, established itself as a specialist in immersion cooling, a technique that submerges servers in a non-conductive fluid to remove heat more efficiently than traditional air cooling, an approach that has gained attention as AI chips grow denser and hotter. Over the past year the company has expanded beyond cooling, launching the InferX AI cloud platform and, in June 2026, Rubix Data Centers, a division that develops and operates AI data centers and is headed by John Eland, formerly of data center operator Stack.

    The Flix site was home to a chemical plant run by Ercros until industrial operations ceased in January 2023. Ercros now operates a solar farm on the site. Redeveloping former industrial land for data centers has become a recurring theme as developers look for sites with industrial zoning and access to power.

    Sources

    Source: Submer plans €1bn data center at former chemical plant in Catalonia (Data Center Dynamics) — Submer’s Rubix division will build and operate a two-phase AI data center on the former Ercros site in Flix.

  • $19.2B North Carolina Withdrawal Shows County Zoning Is a Gate on AI Capacity

    $19.2B North Carolina Withdrawal Shows County Zoning Is a Gate on AI Capacity

    TL;DR · 30-second read

    The Short Version

    A company called Energy Storage Solutions has dropped its plan for a $19.2 billion building full of computers for artificial intelligence in a rural North Carolina county.

    At first it would have used about 300 megawatts of electricity, roughly what a couple of hundred thousand homes use, and possibly three times that later.

    Local officials had already refused it a permit. Now they are considering a two-year ban on any new projects like it. The takeaway: a county vote can stop part of the artificial intelligence boom before a single computer is installed.

    A proposed $19.2 billion AI data center in Edgecombe County, North Carolina, has been withdrawn by its developer, Energy Storage Solutions, Data Center Dynamics reported on July 15, 2026. County Manager Eric Evans told the board of commissioners at its July 6 meeting that the company had pulled the project earlier in the month. The multi-phase campus was planned for the Kingsboro development area near Tarboro, about 70 miles east of Raleigh.

    The county denied the project a special-use permit late last year, when it was described as an eight-phase, 300MW campus on 52 acres. Other accounts put the eventual build-out at 300 acres and 900MW. At the same July 6 meeting, commissioners discussed a 24-month moratorium on new data center developments. A public hearing is scheduled for August.

    Executive Summary

    The Edgecombe withdrawal takes one of North Carolina’s largest announced AI data center proposals off the table, at least for now. The obstacle on the public record was not chips, turbines or transformers. It was a county special-use permit, the discretionary approval a local board can grant or refuse. Commissioners refused it, the developer appealed, and the project has now been withdrawn while that appeal was reported to be ongoing.

    The episode matters beyond one county because two policy layers are tightening at once. Locally, Edgecombe is weighing a two-year pause on all new data center projects. At the state level, the House has passed the Ratepayer Protection Act, which would make data center developers pay upfront for the grid expansion, transmission upgrades and new generation their facilities require. Together they change both whether a campus can be built and who pays to power it.

    For developers, utilities and the cloud and AI companies that lease capacity, the practical point is that a site’s local approval status now belongs in capacity forecasts alongside land and megawatts.

    The Gate on This 300MW Campus Was a County Vote

    Most public discussion of AI infrastructure constraints centres on chips, power supply and electrical equipment. In Edgecombe County, the documented obstacle came earlier than any of those. Late last year, the board of commissioners denied a special-use permit for an eight-phase, 300MW data center campus on 52 acres. A special-use permit is discretionary. Even where land is zoned for industrial use, a county board can attach conditions or say no. Energy Storage Solutions appealed and said it would proceed. By early July, the county manager was telling commissioners the project had been withdrawn.

    The moratorium under discussion would turn one project’s rejection into a countywide freeze. For 24 months, no developer could bring a new data center through the county’s approval process. Campuses like this one are planned in phases across several years, so a two-year stop at the approval stage delays the first phase, and every phase behind it, by at least that long. That delay holds whether or not power, financing and tenants are ready.

    Several groups absorb that risk. Developers and landowners assemble parcels on the expectation of approval. Utilities plan transmission and generation around announced loads. Tenants, usually cloud and AI companies, need capacity delivered on a specific date. For all of them, entitlement status, meaning whether a site actually holds the local approvals needed to build, is as material as the megawatt figure in the announcement. A single county vote removed a planned 300MW from the pipeline here, and possibly 900MW.

    A $19.2 Billion Figure Without a Fixed Size

    The $19.2 billion headline is the project’s most quoted number and its least anchored one. The permit application the county reviewed described 300MW on 52 acres. Other reports described a 300-acre campus reaching 900MW. Divided across 900MW, the figure works out to about $21 million per megawatt. Divided across 300MW, it is about $64 million per megawatt. A threefold gap makes it impossible to benchmark the proposal against other campuses or to tell whether the figure includes the servers and AI chips inside the buildings, which often cost more than the buildings themselves.

    Headline figures for multi-phase campuses tend to describe a full build-out rather than a first phase. That makes them useful as a measure of ambition and weak as a measure of what is financed or contracted. For readers tracking AI capacity announcements, the useful distinction is between the capacity a regulator has actually reviewed, here 300MW, and the capacity that appears in the eventual vision, here up to 900MW.

    North Carolina Moves the Grid Bill Toward Developers

    The state-level change could matter more than any single county’s decision. The Ratepayer Protection Act, passed by the North Carolina House and awaiting Senate approval, would require data center developers to cover the upfront costs of grid expansion, transmission upgrades and new power generation for their facilities. The practical effect is to shift those costs away from a utility’s general customer base and onto the project. That raises the capital a developer needs before a site produces revenue, and it makes locations near existing grid capacity relatively more valuable.

    The bill also includes a coal plant moratorium. Public utilities could not retire coal-fired plants until regulators approve new large-scale nuclear facilities. That provision would keep existing generation on the system while new supply is planned. Its cost and environmental trade-offs will be argued on their merits in the Senate.

    Taken together, the local and state layers raise the bar for projects that lack committed customers and deep financing. Developers with signed tenants and capital to fund grid upgrades are better placed under these rules than those seeking approvals first and backers later. Counties and ratepayers gain more leverage over terms. The open question for the industry is how many other North Carolina counties adopt similar tools. The state has seen resident opposition to data center proposals in several places.

    Background

    North Carolina has become a hotspot for data center development, with some local residents opposing new projects in several parts of the state. Edgecombe County, whose seat is Tarboro, about 70 miles east of Raleigh, became one focal point when Energy Storage Solutions proposed a multi-phase AI data center campus in the Kingsboro development area.

    The county board of commissioners denied the project a special-use permit late last year. The developer appealed and said it would proceed, before withdrawing the project in early July 2026. State lawmakers are meanwhile debating the Ratepayer Protection Act, which would make data center developers pay upfront for the grid infrastructure and generation their facilities require.

    Sources

    Source: North Carolina AI data center proposal withdrawn as county officials mull moratorium, Data Center Dynamics’ report on the withdrawal of Energy Storage Solutions’ $19.2 billion Edgecombe County project and the county’s proposed 24-month moratorium.

  • Nvidia and Mitsubishi Heavy Reportedly Weigh AI Data Center Cooling and Power Tie-Up

    Nvidia and Mitsubishi Heavy Reportedly Weigh AI Data Center Cooling and Power Tie-Up

    Nvidia and Japan’s Mitsubishi Heavy Industries are reportedly in early discussions about collaborating on cooling and power infrastructure for AI data centers, according to a July 13, 2026 Seeking Alpha report surfaced via Google News.

    The item is a brief report of external reporting; no formal announcement, deal value, timeline, or product scope has been confirmed by either company.

    Executive Summary

    The reported talks would pair the dominant supplier of AI accelerators with one of the world’s largest heavy-engineering conglomerates, whose portfolio spans gas turbines, HVAC systems, and industrial cooling. On paper, the fit is obvious: AI clusters built around Nvidia’s highest-end GPUs are pushing rack densities and heat loads well past what conventional air-cooled data centers were designed to handle, and grid interconnection queues in key markets are measured in years rather than months.

    What matters for readers is less the headline than the pattern. Chipmakers are increasingly reaching upstream into the physical plant — power generation, thermal management, on-site energy — because compute deployment is now gated by megawatts and cooling capacity, not silicon supply. Whether this specific pairing produces a concrete product, a joint venture, or nothing at all remains unclear from the available reporting.

    Why a Chip Company Cares About Chillers

    Modern AI training racks can dissipate 100 kilowatts or more — an order of magnitude above traditional enterprise servers — and next-generation GPU platforms are pushing hotter still. At those densities, air cooling stops being economical and liquid cooling, whether direct-to-chip cold plates or full immersion, becomes mandatory. Mitsubishi Heavy’s industrial thermal and HVAC businesses are the kind of scaled manufacturing base that a chip vendor would want aligned with its reference designs, so that when a customer buys a rack, the cooling loop is engineered, warrantied, and shippable at the same cadence as the servers.

    The power side of the reported discussion is equally telling. Mitsubishi Heavy builds gas turbines and is active in nuclear and hydrogen-adjacent equipment. Data center developers in the United States, Japan, and Europe are increasingly signing behind-the-meter or on-site generation deals because utility interconnection timelines cannot keep pace with hyperscaler expansion plans. A relationship with a turbine manufacturer is one way to shorten that critical path.

    Strategic Logic, With Caveats

    For Nvidia, the strategic prize is deployment velocity: every month a customer waits for power or cooling is a month of deferred GPU revenue and a window for a rival platform. For Mitsubishi Heavy, aligning with the dominant AI compute vendor could pull its industrial equipment into a growth market with unusually inelastic demand. Both narratives are plausible, and both have been used to explain similar chatter around other equipment makers over the past 18 months.

    The measured read, however, is that a report of exploratory talks is not a partnership. Neither company has published terms, and Seeking Alpha itself is aggregating reporting rather than breaking primary news. Readers should treat the item as a signal of direction — chip vendors seeking closer ties to power and thermal OEMs — rather than as a confirmed commercial arrangement.

    Winners, Losers, and the Middle of the Stack

    If a formal collaboration materializes and yields co-engineered reference designs, the pressure would land squarely on independent liquid-cooling specialists and on power-equipment competitors that lack a chip-vendor relationship. Colocation operators would likely welcome a validated, warrantied stack because it reduces integration risk on the largest deals. Hyperscalers, who tend to prefer multi-sourcing and their own custom designs, may care less at the design level but still benefit from a deeper supplier bench.

    The counter-scenario is that talks fizzle, or produce only a narrow marketing arrangement. That outcome would be consistent with how many announced infrastructure partnerships have played out — press coverage first, meaningful shipments much later, if at all. Either way, the underlying constraint is real: AI infrastructure is now a power-and-cooling problem as much as a semiconductor one.

    Background

    Nvidia is the dominant supplier of graphics processing units used for AI training and inference, and its data center segment has become the fastest-growing business in enterprise compute. Its accelerators are the reference platform for most large-model training clusters, which has made the physical constraints of deploying them — power, cooling, real estate — the industry’s binding bottleneck.

    Mitsubishi Heavy Industries is a diversified Japanese engineering conglomerate with more than a century of history in power generation, thermal equipment, aerospace, and industrial machinery. Its portfolio includes gas turbines, HVAC systems, and nuclear-related equipment, giving it multiple potential entry points into the data center power-and-cooling stack.

    Source: Nvidia, Mitsubishi Heavy mull team up for AI data center cooling, power: report – Seeking Alpha — brief report of exploratory discussions between the two companies on AI data center infrastructure, aggregated via Google News.

  • Meta’s 5 GW Louisiana AI Campus Comes With Seven Gas Plants. Power Is the Project.

    Meta’s 5 GW Louisiana AI Campus Comes With Seven Gas Plants. Power Is the Project.

    TL;DR · 30-second read

    The Short Version

    Meta, the company behind Facebook and Instagram, is turning its artificial intelligence data center in Richland Parish, Louisiana, into its biggest anywhere. It says it will spend more than $50 billion there.

    The surprising part is the electricity. At full size, the site is planned to use about as much power as five large nuclear reactors produce. To supply it, Meta’s deal with the local utility, Entergy, pays for seven new natural gas power plants and three giant batteries.

    Meta says local households will save money as a result. It has not published how it calculated that.

    Meta announced on July 13, 2026 that it is expanding its Richland Parish, Louisiana data center to 5 gigawatts (GW) of compute capacity. That makes it the largest site in Meta’s fleet. The campus will house Hyperion, which Meta calls its largest multi-gigawatt AI training cluster. Meta puts the total investment in the region at more than $50 billion, supporting over 7,500 jobs at peak construction and 1,000 permanent roles once the site is operating.

    The announcement also describes a new agreement with Entergy Louisiana. It will fund seven new natural gas-fueled generating plants, three grid-scale batteries, nuclear uprates and other purchased power. Meta says the agreement will deliver about $2 billion in customer savings, on top of $650 million it announced earlier, for a total of $2.65 billion over 20 years.

    Executive Summary

    Meta is scaling a single campus in rural northeast Louisiana to 5 GW and committing more than $50 billion to it. The site is being built to host Hyperion, a training cluster of the kind used to build large AI models, which runs tens of thousands of processors near full load around the clock. Alongside the headline figures, Meta lists $1.6 billion in contracts with Louisiana businesses to date, more than $1 billion in roads, water and wastewater improvements, a $5 million gift to Louisiana Delta Community College, and $215 million for Entergy’s affordability and efficiency programs.

    The most consequential part of the announcement is the power arrangement, more than the jobs or the grants. At this scale, a data center is no longer a customer that plugs into existing grid capacity. It is a reason for a utility to build new generation. The Entergy agreement funds a portfolio of gas plants, batteries, nuclear upgrades and purchased power. Meta has also committed to help fund up to 2.5 GW of clean and renewable energy. How fast, and on what terms, that generation arrives will largely decide when Hyperion reaches full scale and who carries the cost.

    At Five Gigawatts, the Utility Sets the Schedule

    A gigawatt is a billion watts, and the data center industry uses it to size how much electricity a campus can draw. A large nuclear reactor produces roughly one gigawatt. Meta’s expanded Richland Parish site is rated at 5 GW of compute capacity. It will host Hyperion, described as a multi-gigawatt AI training cluster. Training clusters are an unusually demanding kind of load: thousands of accelerator chips running together for weeks at a time, drawing close to peak power continuously. A regional grid does not keep that much idle capacity in reserve, so a load of this size has to arrive with its own new generation.

    That is what the Entergy agreement is for. According to Meta, it funds seven new natural gas-fueled generating plants, three grid-scale batteries, nuclear uprates and other purchased power. Nuclear uprates are upgrades that raise the output of existing reactors. Read that list next to the construction figures and the order of work becomes clear. Server halls, contractors and workforce programs are the visible part of the project. The pace, though, is governed by when the plants, batteries and grid connections come online. Construction crews can be scaled up relatively quickly. New generation depends on equipment deliveries, utility engineering and regulatory processes that a data center builder does not control.

    This affects several groups. Entergy Louisiana’s other customers have bills tied to how costs are allocated. The state regulators who oversee the utility’s resource plans must weigh a single customer’s demand against system-wide reliability. And anyone forecasting Meta’s AI capacity needs to know when Hyperion actually reaches multi-gigawatt scale. Meta has not said how the seven plants’ combined output compares with the 5 GW figure. That is the number that would show how much of the campus the new generation actually covers.

    The $2.65 Billion Savings Claim Needs Its Arithmetic

    Meta says the new agreement is expected to deliver about $2 billion in savings to Entergy Louisiana customers, on top of $650 million announced previously. Spread over 20 years, the combined $2.65 billion averages roughly $130 million a year. The usual argument for such savings is that a very large, steady customer helps pay a utility’s fixed costs, which lowers the share left for everyone else. That argument can hold. It depends, however, on contract terms: who pays for the new plants, over what period, and what happens if the anchor customer’s demand falls short of plan.

    Meta did not lay out that mechanism or the assumptions behind the figure. Its broader commitment is that it will pay for the energy, water and related infrastructure it uses so that other customers’ bills do not rise. That is a meaningful policy statement, but its strength sits in contract language that has not been published. The $215 million contribution to Entergy’s Power to Care and residential energy efficiency programs is more concrete: it is a direct transfer with a stated amount. Until the underlying terms are visible, the headline savings figure is best read as a projection, not a guarantee.

    Clean-Energy Matching Next to New Gas Generation

    Meta says it will match 100% of the Richland Parish site’s energy use with clean and renewable energy, as it does at its other data centers. It also commits to help fund up to 2.5 GW of clean generation. Matching is an accounting method: a company funds or buys clean electricity equal to what it consumes over a period. It does not require the clean power to be produced at the same hour or on the same grid as the consumption. The gas plants and batteries in the Entergy agreement exist because a round-the-clock training load needs power that can be supplied on demand, including at night and during low-wind periods.

    Both statements can be true at once, but readers should hold them together. Up to 2.5 GW is a ceiling, not a commitment to 2.5 GW. Renewable plants also typically produce well below their rated capacity averaged over a year. Clean generation tied to this agreement alone would therefore not obviously cover the annual consumption of a 5 GW campus running near full load. Meta has not said where the balance will come from, or whether it is matched annually or hour by hour.

    $50 Billion In, 1,000 Permanent Jobs Out

    The job figures follow the usual pattern for hyperscale data centers, which are capital-heavy and need relatively few staff to run. Meta cites 7,500 jobs at peak construction and 1,000 operational roles, or about $50 million of investment per permanent job. The larger local effects are construction spending, tax revenue and infrastructure. Meta reports $1.6 billion contracted with Louisiana businesses to date and more than $1 billion spent on roads, water and wastewater systems. It also says Richland Parish teachers received yearly bonus checks 400% higher than the previous year because of increased tax revenue from the project.

    The workforce measures are aimed at the gap between the two job numbers. They include full scholarships for data center trade certificates for Richland Parish high school graduates starting with the class of 2026, contractor-run programs at Louisiana Delta Community College, and a reported 37% rise in enrollment at the University of Louisiana at Monroe’s construction management school. Making the state’s Source Louisiana portal the default subcontracting platform widens access for local firms. The general contractors (DPR Construction, Turner Construction Company and Mortenson Construction) and in-state subcontractors benefit most directly during the build. The open question for the parish is what that construction workforce does when the peak ends.

    Background

    Meta Platforms, the parent of Facebook, Instagram and WhatsApp, operates a global fleet of data centers. It is one of the handful of hyperscalers, the companies that build computing capacity at the largest scale. Meta broke ground on its Richland Parish campus in northeast Louisiana in December 2024, and the July 2026 announcement expands the site to 5 GW, making it the largest in Meta’s fleet. The area is served by Entergy Louisiana, a regulated electric utility, and Meta has worked with Entergy on power supply since before the site came online.

    AI training clusters have changed data center planning. Earlier facilities drew tens or hundreds of megawatts. Clusters built to train frontier AI models are now planned in gigawatts, which brings power generation, transmission and utility regulation into the center of each project. Meta has partnered since 2022 with the Center on Rural Innovation on programs near its data centers and says it is extending that partnership to Northeast Louisiana.

    Sources

    Source: Deepening our investment in Richland Parish, Louisiana – Meta Data Centers. Meta’s July 13, 2026 announcement expanding its Richland Parish AI data center to 5 GW, with details of its Entergy Louisiana energy agreement and local investments.