Oracle has reportedly made a deal with Tencent for a five-year lease at several Oracle data centers in Southeast Asia, covering about 100,000 advanced AI chips unavailable in China. The deal is estimated to be worth about $7 billion, which would come out to about $1.60 per chip per hour over five years, with about 30% upfront, according to a report by the Financial Times (FT). The deal lands as compute rental prices continue to climb, per Chief Strategy Officer James Mitchell on Tencent’s August 12 earnings call. Neither company has commented on the report, but such leases are legal under current U.S. rules, per the FT.

The estimated chip-hour price is around 43% less than the roughly $2.80 per GPU-hour for Nvidia’s H100 with a one-year contract, per research firm SemiAnalysis in August. It’s also about 48% lower than the $3.09 per GPU-hour for a three-year contract with Nvidia’s B200, per a 2025 filing by Japanese data center operator Datasection for an unnamed customer. Market trends have pricing running the other way, with the FT reporting longer terms and larger upfront payments for such leases. Tencent president Martin Lau said on the same call the company could sell its existing orders at “more than 30% profit” compared to what it “paid just a few months ago.”

No chips are named. The FT says that such leases could reach even Nvidia’s top processors, but that does not mean this deal involves Nvidia hardware. One-year H100 contracts on SemiAnalysis’s index were above the estimated rate at about $1.70 per GPU-hour even as of October 2025, with the B200 rate being even more expensive despite its longer, three-year term. Going by raw B200 server costs, which exclude buildings, power, networking, and financing, 100,000 B200s would cost $5.44 billion, or about 78% of the reported value, based on Datasection’s 2025 purchase of servers with 5,000 B200s for $272 million.

Without specifics on the hardware being rented, it is not possible to determine whether this is a bulk deal or if the leasing costs are closer to the actual hardware cost. The pricing on paper, however, better fits Hopper-class at volume. Hopper would include the H100 and H200 and, with H200 imports still limited, could meet the criterion of the chips in the deal not being available in China.

The Oracle data centers are located outside China, with Tencent merely renting time on them. Details including the countries involved, sites, and start date remain undisclosed. Oracle has two Singapore cloud regions, with a Malaysia one announced. The FT says the biggest clients of Southeast Asian data centers are ByteDance and Alibaba, with Chinese firms using the capacity especially for AI training, which domestic chips cannot yet do. Tencent previously inked a $1.2 billion-plus deal for Datasection Blackwell rentals in Japan and Australia, the FT reported in December 2025.

Some Oracle clients have prepaid for GPUs or brought their own hardware since its March call, and fiscal Q4, from March to May, added $67 billion of AI contracts, mostly of those two kinds, per its June call. June through August, per its quarterly filing, the company “received $11.4 billion of prepayments from customers that included a significant financing component.” Deferred revenue rose from $15.4 billion to $30.8 billion over the quarter. No customers were named, so this can’t be tied to Tencent. The company reported 97.9% GPU utilization during its September 10 earnings call, with renewals at a 20% average premium, which was mostly on GPUs four years or older.

Tencent prepaying about 30% makes sense given Oracle’s statements earlier this year. It’s a good deal for both parties. Oracle would improve its cash flow following a quarter of negative free cash flow, and Tencent Cloud’s May price raises, per Mitchell, could help recoup the cost of the rented chips.

The legal picture, given the friction between the United States and China over AI export controls, is thorny. The Remote Access Security Act, a bipartisan bill that passed the House 369–22 in January, would give the U.S. government the right to regulate remote cloud access to sensitive technology, which could cover the chips under the reported deal. The bill specifically targets cloud loopholes and applies to any foreign person rather than naming countries, to prevent adversaries from leveraging cloud networks to bypass U.S. export bans. The bill currently sits in the Senate Banking Committee.

Separately, Export Administration Regulations license requirements under the Department of Commerce’s Bureau of Industry and Security (BIS) have covered shipments of advanced AI chips, including to China-headquartered companies abroad, since November 2023. Cloud rentals were left out, with the BIS only asking for comment on them. Renting remains one loophole around BIS guidance on restricted chips. Bloomberg reported that the BIS was reviewing offshore access with legal rentals included. The deal is also not barred by Tencent being on the Pentagon’s 1260H list of “Chinese military companies,” as this is not a sanction. No statement about the deal by any regulatory government official accompanied the report.

According to The Information, the Department of Commerce is drafting a rule to block Chinese firms from renting compute in third countries, such as Thailand and Singapore, which would align with the reported details of this deal. U.S. President Donald Trump and Chinese President Xi Jinping met late last month in Washington, covering AI and extending a trade truce for a further two months.

However, the deal is of a type that might face trouble from both the House-passed bill and Commerce’s reported rule. But the latter cannot be enforced under current law, an attorney at Baker McKenzie told The Information. At the summit, the two leaders agreed to set up a channel to handle AI-related incidents, but nothing was announced on chip controls. While the U.S. has cleared some firms, including Tencent, to buy Nvidia’s H200, China has let in only about 10,000 for Tencent so far, the FT reported in August. The next meeting between the two, at APEC in Shenzhen in November, may clarify the situation.

The reported deal comes weeks before Oracle’s Investor Day on Oct. 28 in Las Vegas, during its Oct. 25–28 Oracle AI World event at the Venetian. That would be a chance for the company to disclose details about the deal, such as announcing what hardware is to be leased. Given the hardware math, our assumption is that it involves older or non-Nvidia hardware rather than an action born of financial stress at Oracle. The month following Oracle’s event, Tencent is expected to report its Q3 results. These events could also reveal more concrete details about the arrangement.

Amazon will no longer require nondisclosure agreements (NDA) with government agencies involved in its data center projects and will adhere to its new Data Center Commitment program designed to address mounting opposition to AI infrastructure, it disclosed on Friday in a blog post. The company also unveiled plans to invest more than $1 billion over five years in communities hosting its facilities. The announcements come as more than 100 data center moratoriums are being considered across the U.S., so AWS wants to make data centers more attractive to locals.

No NDAs

Amazon's decision to no longer require NDAs from government officials working with it is part of the company's newly announced Data Center Commitment program aimed at making data center building more transparent and somewhat less unpleasant to people living nearby. Among other things, the company vows to hold community open houses, disclose information about projects as early as possible, and listen to local concerns as development proceeds. Amazon also vows annual disclosure of its energy consumption and efficiency, water consumption and efficiency, and the proportion of electricity supplied by carbon-free sources.

Speaking of power usage efficiency (PUE), Amazon reports a global PUE of 1.14 for 2025, compared with an industry average of 1.25 and 1.63 for on-premises enterprise data centers. It also says its facilities were 7x more water-efficient than the industry average and that it had reached 75% of its goal to become water-positive by 2030.

Many concerns

Also, new sites will use backup generators compliant with EPA Tier 4 emissions standards. While Amazon emphasizes that new sites will use backup generators meeting EPA Tier 4 emissions standards, the commitment is somewhat ambiguous in general, as the specification limits vary by engine power and generator classes, whereas Amazon does not specify the generator classes it intends to deploy.

The company says an average U.S. data center consumes around 170,000 gallons of water per day, whereas an average Amazon facility uses less than 13,000 gallons, equivalent to 42 U.S. households. However, Amazon does not distinguish between the water consumption of a typical AWS data center designed for general-purpose cloud workloads and newly built AI data centers packed with power-hungry AI accelerators, which certainly have substantially different cooling requirements.

In general, Amazon is trying to counter concerns about the resource requirements of data centers, although some of its comparisons remain rather ambiguous.

When it comes to energy efficiency, the new Built Together initiative will add more than $1 billion to Amazon’s existing community spending. The company expects to provide more than 300,000 students with access to free community-college education over five years. It currently operates three Modular Training Centers, has six more under development, and plans another 16. Each facility can train roughly 2,000–4,000 people annually, with Amazon targeting as many as 100,000 trained workers per year by the end of 2028.

Amazon also plans energy-efficiency upgrades for more than 300 schools and community buildings and 30,000 homes, targeting energy-bill reductions of 20%–40% and savings of approximately $700 per household annually. Separately, more than 65 contracted water projects are expected to return over 8 billion gallons annually, more than twice the water Amazon says its data centers consumed in 2025.

Google’s latest data center construction project in Finland is being investigated after the company representing the search giant allegedly cleared over 300 hectares of forest. The reported issue is that Google’s local operator, Tuike Finland, cleared the 420 football fields' worth of trees without obtaining a mandatory environmental impact assessment beforehand, says AFP.

Google sees Finland as an attractive European data center host country due to a number of favorable factors. The source notes that it is a country with a cool climate, plus stable and cheap energy supplies (mostly nuclear, wind and hydro). Moreover, Finland sees data centers as a solution to address some current woes such as slow economic growth and record-high unemployment levels.

This new development near Muhos, a small town with fewer than 9,000 residents, isn’t the first for Google in Finland. It already has a facility up and running in Hamina, in the south, but hopes to expand in Muhos, Kajaani, and Vaala, in the north. Overall, it is a massive expansion project, and part of a 13-billion-euro ($15-billion) investment in Finland over the next two years. Finland’s potential data center appeal has also made it a location of choice for Microsoft and TikTok.

While the local mayor looks forward to the massive investment, growth of business, and general economic boom for the region, residents are waking up to the experience of others where data centers have sprung up. Concerns about impacts on the environment, energy supply stability, and energy prices are simmering under the surface.

Google seems to have trampled on some of these concerns already, with these reports of trees already felled and excavators clearing the ground before government agency approval. Not a good start.

"In our view, operations at this construction site should be suspended until it is clarified whether the project is in compliance with the law," Hanna Halmeenpaa, chair of the board of the Finnish Association for Nature Conservation, told AFP at the edge of the freshly deforested area near Muhos. Even some nature preservation areas have been logged, reckons the chair. Halmeenpaa was responsible for filing the suspension request with the conservation agency.

Google denies prematurely devastating the forest. It told AFP that tree felling had been "in compliance with Forestry Act requirements." Moreover, its Finland comms manager said, in a contrasting statement to that of Halmeenpaa, that Google has been ensuring "high-value nature zones within the sites have been protected during forestry works."

We haven’t seen any other reports indicating that preparation and construction work has ceased at the new data center development site near Muhos. So it seems like Google will plow ahead, hoping or knowing that the political and/or business will is sufficiently strong to ensure it won’t have to undo any of the actions it has already completed.

Amazon has issued grave warnings to communities opposing data centers, stating that their actions could cause irreversible damage to the U.S. economy and national security. In a lengthy 3000-word post earlier today, October 2, CEO of Amazon Web Services (AWS), Matt Garman detailed the many benefits of Artificial Intelligence, comparing the technology’s impact on the economy to those of modern transportation systems and the Internet, before attempting to debunk “myths” around data centers and calling on local communities to be more receptive to build-outs as a matter of national urgency. The post also details Amazon's plans to do more for data center host communities through its “Built Together” community investment frameworks.

After outlining AI’s impact and the need for data center buildouts, Garman explained why it was imperative for the U.S. to lead the AI race. “The countries that lead in AI will shape it and get the most from it in the short and long run. The choices we make today will determine that outcome, and a lapse in our nation’s focus or resolve could put us behind, and potentially irreparably so,” he wrote, presenting urgent buildouts as a key factor in leading that race.

Next, Garman addressed growing anti-data center movements that have reportedly blocked data center projects worth $68 billion in the second quarter of 2026 alone, warning that if the 100 data center moratoriums being considered across the country should go through, “the US could be writing its own losing ticket to this race, and the consequences would last generations.” He also pointed out that unlike transportation infrastructure, the comparably critical data center buildout is not funded by taxpayer money, but by private firms.

The post dismissed many of the concerns about the buildouts as myths, then proceeded to attempt to debunk them. Garman said that, contrary to popular belief, “Data centers actually use very little water relative to other industries,” a position many hyperscalers have repeated. Amazon earlier claimed that its data centers consume only 0.075% of the water Americans use to water their lawns and gardens.

Garman also claims the narrative that data centers are driving up energy bills is “misleading and convenient scapegoating.” He argues that AI is simply precipitating an expansion of power infrastructure that was always bound to happen. “Once we collectively build out this new capacity, again funded by the private sector, it should lead to flat or lower rates in the future for residents living in communities with these expanded grids,” he said. On the other hand, contradictory reports claim that AI data centers trigger a "massive irreversible" 76% electricity price spike. The U.S. House also recently passed a bill that directed regulators to consider making AI data centers pay for grid upgrades to minimize the impact on residents. The bill was eventually rejected in the Senate, with opponents saying it was "toothless" and didn't do enough to protect residents.

Speaking on pollution, Garman says that data centers emitting huge amounts of pollution with their large backup diesel generators is a myth. He claims that while data centers have rarely used backup power in case of a power outage, this is only necessary because many industries depend on the facilities. This claim doesn’t exactly address growing concerns of pollution from gas turbines powering off-grid data centers. Elon Musk recently came under fire for using unlicensed gas turbines at the Colossus data center.

Lastly, Garman said claims that communities do not benefit from data centers are false, citing “considerable tax revenue, positive economic impact, large numbers of good jobs, and education programs” as some of the benefits to the communities where data centers are built. Microsoft pledged to invest $1 billion in local infrastructure improvements in its Hyperion data center community and had reportedly awarded $1.6 billion in contracts to local businesses since construction began, in addition to paying teacher bonuses. As benefits specifically on Amazon’s part, Garman listed an estimated $3 billion in taxes to St. Joseph County, Indiana, over time; more than $1 billion already contributed to communities across the U.S.; thousands of jobs created in building and running the data centers; and education programs with over 10,000 educators and learners enrolled.

The company says it plans to do more. Through its “Built Together” initiative, Amazon says it will “add more than $1 billion over the next five years to what we’re already doing — with communities in the driver’s seat to determine what’s most useful for them across education, job training, energy affordability, water and energy preservation, and local priorities.”

Garman insists that data centers can’t be separated from the revolutionary impact of AI. U.S. President Donald Trump appears to agree, at least on the “revolutionary impact” aspect, and has repeatedly expressed a desire to maintain a lead over China. On the other hand, data center critics claim that responsible implementation of the build-outs, and not AI itself, is the bone of contention.

Like several industry leaders and hyperscalers, Garman insists that many of the issues were being blown out of proportion, and implied that much of the anti-data center sentiment could be traced to nefarious foreign influence. “With any change, there will be important questions raised, but there will also be misinformation and outright lies, and in the age of social media and 24/7 news, myths take hold faster than ever before. In fact, this buildout is so important geopolitically that there are widespread reports of various countries intentionally seeding misinformation in the U.S. about data centers to trick us into slowing down,” he said.

The United States Senate has decided against advancing the Ratepayer Protection Act, a bipartisan bill designed to shield everyday Americans from rapidly rising electricity costs driven by data center buildouts nationwide. On September 30, the bill fell short of the 60 votes required to pass the bill by just three votes, ending 57-43, according to a Reuters report. The Ratepayer Protection Act bill had cleared the U.S. House of Representatives just two weeks earlier, with the Senate as the last procedural step before President Donald Trump could sign it into law. Following the vote, the bill is now officially dead.

Introduced in the Senate by Senator Jon Husted, the bill was the legal culmination of President Trump’s “Ratepayer Protection Pledge.” It sought to institute a federal standard for states and Public Utility Commissions, directing regulators to consider whether entities that consume large amounts of electricity, such as data centers, should cover the incremental costs of energy infrastructure needed to serve them.

Proponents say the act would prevent data center operators from passing infrastructure costs to residents and small businesses, a growing concern in communities seeing a rise in data center construction. “If America wants to lead the world in AI and strengthen our national security, we have to build the energy infrastructure to support it. But we must do that without passing the costs on to working families and small businesses. The Ratepayer Protection Act would keep America globally competitive while protecting Ohioans and Americans from higher electricity bills,” said Husted.

On the other hand, opponents, mostly Democrats, labeled the bill “toothless,” arguing that its non-binding nature provided no real protection because it did not mandate that states adopt the standard; it simply directs regulators to consider it as part of their rate-setting processes. Only four Democrats voted for the bill; the general consensus was that it does not go far enough to protect consumers from soaring electricity bills.

With the bill’s collapse, Congress has yet to impose any new federal protection on data center-related grid costs. Some lawmakers have suggested they may reevaluate the issue after the mid-term elections in November, possibly with revisions that would require utility regulators to ensure data center operators cover additional costs caused by their operations. The debate over data center energy costs and who should cover them will likely remain a key issue during campaigns, especially in states where new facilities are planned or where buildouts are ongoing.

Meanwhile, local communities continue to push back against data centers over several issues, including electricity bill hikes. Some states are already taking steps to address the hikes. An Oregon power company hiked data center bills by 30% and cut residential electricity costs by 1.3%. Certain hyperscalers are also moving their data centers off-grid, with others pledging to supply electricity to the grid or offset increases in residents’ bills.

Microsoft’s “biomimicry” program is reshaping the land around its data centers with restored wetlands and native gardens to help the buildings blend into local ecosystems at 20-plus sites, reports The Verge. Critics question the company’s motives after recent energy deals, such as a 20-year deal inked in June to buy power from a planned Chevron gas plant in West Texas. Public Citizen’s Texas director, Adrian Shelley, called the plan “basically lipstick on a pig.”

Microsoft says the approach is now part of all new projects in the U.S. The goal is to blend “data centers into the natural landscape” at sites across the United States and Germany, gauging community input and using ecological research to map the local environment. Microsoft’s team uses a tool called Ecosystem Intelligence, which runs on Azure and scores various features of the site, including water quality, biodiversity, and noise abatement.

Solutions, according to Microsoft’s director of global land strategy, Kaitlin Chuzi, are customized to the local habitat and should restore what was lost, while plant buffers quiet data center humming and help “minimize the visual impact on communities near our data centers.” Named sites include Mecklenburg County, Virginia; Mount Pleasant, Wisconsin; East Point, Georgia; Bedburg, Germany; and other projects in Ohio, North Carolina, and Wyoming.

The Mount Pleasant site, home to Fairwater, which Microsoft calls the “world’s most powerful AI data center,” has 100 acres of prairie and forest in a Lamparek Creek restoration with the Root-Pike Watershed Initiative Network. Its executive director, Dave Giordano, told the outlet that Microsoft developed its stormwater ponds with forebays to retain sediment, one of a number of accommodations for the environment. “Not all data center companies are the same,” he said. It is a living example of the company’s answer to AI data center backlash.

San Antonio District 6 Councilmember Ric Galvan told the outlet that there are more than a dozen data centers in his district, with more proposed. He cited concerns about the impact on traffic and the environment, including tree removal, following a 2022 approval of a Microsoft plan to remove 2,642 trees from a 33-acre tract for a data center.

Microsoft spokesperson Jennifer Lyons, however, said in an email to the outlet that the company is investing in more than 400 acres of woodland and pollinator prairie restoration in San Antonio and intends to leave the “land more productive than we received it.” Galvan said Microsoft may be “covering their bases,” which he said is fine if residents’ concerns are addressed. He proposed a moratorium on new data centers in August, backed by Public Citizen, but the council opted against a blanket pause and is weighing zoning rules instead, with a vote scheduled for Oct. 15.

Shelley also pointed to adjacent effects, specifically pollution from new gas plants built to supply energy for data centers. “I cannot really see any level of biomimicry investment that makes a gas plant a desirable neighbor,” he told the outlet. Chevron says its plant would provide “approximately 2.67 gigawatts” of power if the plan goes through, with first power anticipated in 2028.

Meanwhile, Texas Gov. Greg Abbott has paused approvals for data centers seeking to connect to the state’s main power grid until regulators audit them. In September, he barred the state’s environmental agency from issuing new data center permits until the audit is done. Water use, a common criticism, was only about 0.4% of the state’s total from data centers in 2025, according to the Houston Advanced Research Center (HARC). It projects water usage of 0.5% to 2.7% by 2030.

Emissions have risen by Microsoft’s own accounting, too. Its 2026 Environmental Sustainability Report, released in July, puts the total up 25% in fiscal 2025, “driven primarily by the expansion of our datacenter infrastructure” and by Microsoft pausing its use of unbundled renewable energy certificates, a type of accounting credit. Microsoft has 2030 goals of becoming carbon negative and water positive, meeting the latter in fiscal 2025 by its own measure.

Holly Alpine, who led ecosystem restoration and climate resilience work near Microsoft’s data centers until leaving in 2024, still sees a gap between data center buildouts and sustainability goals. Microsoft said in an email to the outlet that AI at a global scale must have “a range of energy solutions in the near term.”

Microsoft had no clear answer when questioned if it would ever change its mind on a site. Chuzi called it “an ongoing learning process to understand what that means to be a good neighbor.” HARC’s Erin Kinney told the outlet the real test is how Microsoft calculates, tracks, and shares the benefits with communities. Accurate measurement would make it easier to have genuine cooperation moving forward so that both data center companies and local communities can come together to mitigate environmental impacts.

Amazon announced a new community program called “Built Together,” where the company promised to invest $1 billion over the next five years on data center communities. According to the company blog post, it will provide the funding to the residents while they determine the best use of the funds to be allocated, including projects that reduce electricity bills.

“With Built Together, Amazon will add more than $1 billion over the next five years to what we’re already doing — with communities in the driver’s seat to determine what’s most useful for them across education, job training, energy affordability, water and energy preservation, and local priorities,” AWS CEO Matt Garman wrote. He said that Amazon is focusing on three key issues that matter most to residents living near its data centers: education and workforce pathways, community energy affordability and water solutions, and flexible funding for local priorities with communities in the lead.

The company says that education and workforce pathways will allow the people living near data centers to pursue associate’s degrees related to in-demand fields at zero out-of-pocket costs, with Amazon covering the shortfall after financial aid. It even claimed that it has already established agreements with local community colleges and expects to launch them in the next few months, with a goal of connecting more than 300,000 students from data center communities to its free degree access. Aside from this, Garman also said that the company is expanding its Modular Training Centers, which provide free certification programs for skilled trade workers so they can eventually get employed at Amazon or its partner construction firms, with a target of funding training for up to 100,000 workers per year.

Amazon is also looking to provide grants to schools, community buildings, and even homes in data center communities to help deploy energy-efficient solutions. These include heat pumps and HVAC systems, insulation, water heaters, batteries, solar installations, and more, with an aim to reduce electricity costs by around 20% to 40% annually and reduce household electricity expenses by up to $700 per year. Last, but not least, Garman said that it’s partnering with local nonprofit organizations and community foundations to ensure that its earmarked funds are best spent according to the needs of the residents. “Every community is different,” said the AWS chief. “What matters most in rural Oregon is not the same as what matters in suburban Virginia or a mid-size city in Ohio.”

The first part of Garman’s post actually addressed many of the concerns raised by community members near these developments, calling them “false” and “misleading,” despite various reports that have raised concerns about utility hikes and noise pollution. Still, it seems that these initiatives are designed to alleviate some of these issues and make data centers more acceptable to communities where they’re being proposed. This is especially true as many projects are being delayed due to bipartisan AI data center bans, especially as polls show that the majority of Americans resist having one put up near their residences.

Other AI hyperscalers and data center developers have offered incentives to communities even before Amazon made this announcement. SpaceXAI offered a 50% discount on Starlink plans to placate its residential neighbors in Memphis and Southaven, while another developer said that it will give $10,000 checks to 4,500 households if its 1,300-acre facility gets approved. One data center site in Maryland even proposed an astounding $110-million package to the community, which is said to be the biggest-ever package offered in U.S. history. Many critics decry moves like these as “bribes,” though, just so developers can get their projects going, but New York State recommended a similar pathway, suggesting a $1 million investment per data center megawatt built in the community.

These values might seem like a lot of money, especially as Amazon’s promised $1 billion investment amounts to $200 million per year. But even though this might seem like a good amount, it’s a tiny fraction of the trillions of dollars projected to be spent on data centers through 2050. Amazon itself is expected to have a capital expenditure of $220 billion on AI data centers this year, making its community efforts cost just 0.1% of its overall AI infrastructure budget.

NorthPoint Development wants to build a data center on 1,300 acres in the Pocono foothills, near Hazle Township, Pennsylvania. As well as seeking to charm the local government with various funding packages, it has proposed paying checks of $10,000 per household. Despite the Pennsylvania town’s median income of $60,000, the offer isn’t being warmly welcomed by locals, reports the Wall Street Journal. Those interviewed were widely against the data center development plans and cited several reasons for being averse to accepting the payout. The major concerns regarded potential impacts on property values, the specter of noise pollution, and a distrust of both the AI moguls and local government representatives.

Offer letters began to be received by Hazle Township back in June. The WSJ recently talked to several residents about NorthPoint’s $10,000 offer. While some say the $10,000 would be handy, it couldn’t find many residents who were “eager to welcome the data center for the payout,” in the journal’s words. We’d point out that opinion polling can often be inaccurate, as what people say and what they do, voting-wise, doesn’t always line up.

Interviewees cited a number of key reasons for their data center development aversion. We distilled the following points from the source:

• Noise pollution concerns
• Water and energy cost worries
• Dislike of AI
• Distrust of AI moguls and local authorities
• Potential negative impact on property prices

Traditionally, developers have offered towns and cities packages worth tens of millions, including funding for local services. But direct cash payments to residents represent a new phase of their charm offensive, the WSJ indicates. Perhaps the idea for the direct payments to residents came after “a raucous public meeting last year, where angry locals asked what they had to gain by supporting the data center,” ponders the source.

The locals won’t just get the direct payout, though. Other funds up to $120 million over the next 15 years have been dangled like a carrot for community and local services investments — improved schools, emergency services, and so on.

Meanwhile, Hazle Township’s government already rejected the data center project on zoning grounds last year, and it has enacted a temporary moratorium on data center construction. Finally, the $10,000 offer to households is simply not enough in many interviewed folks’ opinions. Residents could feel insulted by it, regarding the offer as a bribe, concludes the WSJ report.

The Russian military has started striking data centers within Ukraine in its latest escalation against the country. According to the BBC, a Russian drone hit the data center, which was situated in a central business district in Kyiv, damaging it and killing four people in the area. Multiple reports also suggest that other data centers and network infrastructure have been hit across the country as well, with President Volodymyr Zelensky saying that Moscow wants to maximize disruption for the common people.

“All this affects people’s ability to stay connected, study, work,” Zelensky said. He also wrote in a social media post, “The Russians are constantly expanding their escalation operation: American and other businesses, data centers, internet providers — for Russia, all ordinary life is simply a target. It is important that the world responds to all of this and that Russia feels the response to its terror.” Russia, on the other hand, confirmed that it attacked the Datagroup site, claiming that Ukrainian military intelligence used it, and that it’s also targeting other data and telecommunications centers owned by New-Telco, United DC, Kyivstar, and Parkovyi.

These attacks have left about 100,000 households in Ukraine without internet connectivity, and some companies have begun migrating their data across the border to avoid disruption. Nevertheless, one government official said that Ukraine’s internet network is highly decentralized, but people should still expect some local disruptions. However, Ukraine Foreign Minister Andrii Sybiha said that Russia’s targeting of data centers would affect the flow of “life-saving information.” “Rapid alerts about missile and drone threats are essential — they save lives. This is crucial civilian infrastructure… It is not a military target,” Sybiha said. “It is essential to keeping everyday life functioning.”

Data centers are considered critical infrastructure as modern society increasingly relies on online services. Because of this, they’re now considered strategic targets in a conflict. While government-owned data processing sites have historically been one of the first targets in military operations, Iran’s response to the U.S.’s bombing campaign in March marked one of the first instances where commercial civilian data center infrastructure was deliberately targeted. This included drone and missile attacks on AWS Middle East regional data centers in Dubai and Bahrain. It also directly threatened the offices of Nvidia, Microsoft, Apple, Google, and 14 other American tech companies in the region, as well as OpenAI’s Stargate AI data center in Abu Dhabi.+

The DataOne data center in Vineland, New Jersey, has just been hit with a record $1.07 million fine for operating unpermitted portable generators on the construction site. According to the New York Times, state inspectors spotted 62 of these units powering the facility back in late July.

Residents had already complained about it at a February town hall meeting. Inspectors said that there were no generators on site when they first visited in December last year. However, some residents said that “some type of unit” was spotted by satellite imagery back in February, leading to their complaint at the community assembly.

Residents of Vineland have already made multiple complaints about the development. Some of the issues t include the unpermitted construction of a 1.5-million-gallon LNG tank and unacceptable noise levels, especially at night, that affected homes within a half-mile radius of the construction site. They also said that there was little to no public consultation on the project before it went into full swing, with the people only finding out that a data center was being constructed in their neighborhood after Microsoft announced a $33 billion deal with Nebius, which in turn contracted DataOne to supply the compute they need.

Despite a record fine, some residents feel that the punishment isn’t enough. “It’s a ‘don’t ask for permission, just ask for forgiveness later’ kind of deal,” longtime Vineland resident Steve Brown told the Times. He also added, “It’s still kind of a drop in the bucket for a company that has several billion dollars of capital.” Long-time community member Tiffany Leone-Vespa also added, “What’s $1.07 million? They should have done it for each generator they were running illegally. They’re billionaires. It’s like pocket change.”

On the other hand, DataOne disagreed with the fine. A company spokesperson said that “We will apply for the air permits for the temporary generators,” and also added that it’s transitioning from the polluting and noisy portable turbines to more modern fuel cells. New Jersey ordered it to comply with the permitting requirements and to stop using the generators if they’re not granted within 45 days.

This is a similar situation that the citizens of Memphis and Southaven faced when SpaceXAI deployed 69 unpermitted generators to provide power to its Colossus 2 data center. It has become the subject of a lawsuit, especially as the community raised concerns that they were spewing thousands of tons of pollutants in the primarily black neighborhood. However, the Department of Justice stepped in and asked the court to dismiss the case because the site “supports mission-critical operations.” Elon Musk’s company eventually agreed to remove all unpermitted turbines, but said that the process will take over a year as replacement 1.2-gigawatt plants gradually come online.

China has launched nine satellites — including its first integrated “rocket and satellite” AI computing project — as part of its push to put AI computing in orbit. According to a Digitimes report, the Kinetica 1 Y18 rocket, operated by Chinese commercial launch provider CAS Space, lifted off on September 20, carrying the nine satellites to their planned orbits.

The payload of greatest interest is the “Supercomputing-1” satellite, developed by Chinese AI computing infrastructure company S-AIDC. Also known as the S-AIDC-1, the satellite is designed to capture and process Earth-observation data in orbit instead of sending data back to terrestrial data centers. Keeping the processing local is meant to cut cross-regional data processing times from hours to minutes. The satellite features both a high-res optical payload and the image-processing AI computer.

According to Digitimes, the launch highlights China's efforts to develop orbital computing as part of a “broader integrated computing network.” In early June, the Chinese government approved the Space Computing Industry Innovation Center, which aims to bring together rocket and satellite manufacturers, semiconductor fabs, and AI tech companies to build a space computing network. A couple of factors are driving this spike in the development of off-planet computing, foremost among them being the AI boom.

The demand for artificial intelligence has spurred the construction of numerous data centers to house AI accelerators. These data centers, some of which can house hundreds of thousands of accelerators, consume unprecedented amounts of electricity, placing significant strain on the grid. This, along with land use, water consumption for cooling, and noise, has fueled growing anti-data sentiment, with local residents blocking $68 billion worth of new data center projects in Q2 2026.

Despite numerous economic and practical challenges, space might offer an alternative with unlimited area, access to solar power, constant cold conditions, and a dead-quiet vacuum. These advantages have made orbital computing a serious topic of discussion. SpaceX is leading the charge with the AI1 satellite, a proposed orbital data center that will deliver 150 kW of peak compute power. The company aims to achieve 1 GW per year of space AI compute by 2027 and has begun constructing the 11-million-square-foot Gigasat facility that would manufacture the 6,000 satellites required to meet this goal.

Beyond the large-scale serving of AI models, putting edge compute capacity in space is already useful for a range of applications. Earth-observation satellites can process images onboard to identify wildfires, storms, floods, ships, or other objects of interest, sending only the useful results back to Earth instead of dumping enormous amounts of raw data to ground stations. The same approach can speed up weather monitoring, disaster response, communications, and even the management of satellite constellations, where spacecraft could make more decisions independently rather than waiting for instructions from Earth.

The launch of a single satellite with edge AI capabilities on board is a far cry from an entire orbital data center, but China's approach could prove to be a more practical and immediate application for advanced computing capabilities in orbit.

An Nvidia-backed startup plans to establish a Bitcoin mining operation in space before the year is out. Starcloud will fire up its cryptocurrency mining ASICs after its second spacecraft reaches orbit later this year. “We’ll be the first to mine Bitcoin in space,” claimed Starcloud CEO Philip Johnston in a recent interview with Documenting Bitcoin.

Starcloud was founded in 2024 with the headlining goal of moving data centers to space. “As launch costs fall, data centers in space will leverage continuous solar energy and radiative cooling, rapidly scaling to gigawatts while avoiding permitting constraints on Earth,” reads its mission statement. The firm spells out its proposition in far greater detail in a white paper on its website, highlighting the appeal of training AI in space. However, the ample supply of solar energy is also great for cryptomining.

So, when Starcloud-2 reaches orbit, it will be tasked with raising some crypto-cash. In the embedded interview segment, Johnston said: “We’ll have some Bitcoin mining ASICs on the second spacecraft launching later this year.” At the time of writing 1BTC is worth roughly $86,000, quite a way down from highs several months ago.

Starcloud-2 is just the second of four currently planned satellite launches from the startup. It is framed as the company's first commercial mission, and like the prior satellite, will feature a GPU cluster. Interestingly, the official Starcloud-2 project page doesn’t mention Bitcoin mining or ASICs, so Johnston’s reveal is quite eyebrow-raising. Moreover, for something that seems a bit like an afterthought, “Potentially it [Bitcoin mining] is one of the most compelling use cases of space compute,” the Starcloud CEO told Documenting Bitcoin.

Johnson provided some financial insight into why there is now a Bitcoin side gig or pivot being considered. He cited the lower costs of ASICs vs. GPUs: they are about 30x cheaper than GPUs per kilowatt, he told the host. A specific example given was a 1KW Nvidia B200 chip at $30,000 vs. a 1KW ASIC at $1,000. Solving the energy supply situation in space for GPUs, or for ASICs, isn’t relevant to the business, said Johnson. We wonder what Nvidia will think about that.

While the availability of near-uninterrupted solar power is a big attraction of space-based compute, there are downsides. For example, satellites aren’t easy to service, and convection cooling doesn’t work in a vacuum. Commercial space-based data centers are so new that some of the problems and solutions will only become entirely clear after pioneering deployments like the Starcloud-2.

Enterprise SSD brand DapuStor revealed a new dual-mode configuration for its J5060 enterprise drive that combines SLC (single-level cell) and QLC (quad-level cell) flash on a single drive. The drive’s new firmware runs “selected QLC cells” in a faster pseudo-SLC (pSLC) mode, trading capacity for speed.

As an example, the 30.72TB model trades around 4TB of QLC for 800GB of pSLC, a ratio closer to 5:1 than 4:1. The other two configurations put aside 400GB or 1.2TB with a cost between 6% and 20% of the QLC capacity. “No dedicated SLC NAND is required,” as this uses a “software-defined media configuration,” DapuStor said. Announced last month during FMS 2026, the drive still lacks pricing, a named customer, and a general availability date.

Typical consumer QLC drives have a pSLC cache that fills with super-fast performance, with the data later transferring over to QLC. However, this pSLC mode is dynamic and variable in size. DapuStor’s implementation uses a fixed region sized by the operator, and the regions are exposed as individual block devices to the host. The J5060 is also higher capacity, from 15.36 to 122.88TB, and in the U.2 form factor for PCIe 4.0 x4. Endurance is rated at 0.5 DWPD (Drive Writes Per Day) over five years. The stock 30.72TB model is rated at 30,000 random-write IOPS at 16KB. Its write latency is 35 microseconds.

The capacity trade-off improves what QLC is worse at, random writes, by more than seven times, DapuStor said. It also says average 4K random-write latency is below 8 microseconds. The pSLC has over 25 times the program/erase cycles of the QLC region, although without region-specific DWPD or TBW numbers. DapuStor achieves this with three firmware changes: die-level isolation, optimized SLC reserve allocation, and region-aware I/O scheduling. The high-performance region targets workloads that benefit, namely “database journals, write-ahead logs (WALs), and metadata caches.” The idea is that this drive configuration precludes the need for specialized SLC drives where failure could be an issue; however, you still end up with a dead dual-mode drive on a failure.

The NVMe specification has defined this arrangement since 2019, with an NVM Express presentation at FMS 2019 claiming the goal was to “enable one SKU to be configured by customer for their use case.” An FMS 2019 example showed that some media units run as a small fast region, while the rest run at full density. A prior drive with the same idea, via a Phison firmware split and a host driver, was the consumer Enmotus/Phison FuzeDrive P200 with our 2021 verdict stating that “excessive pricing isn’t for everyone.” Enmotus wound down the same year. It’s also possible to mod a QLC drive to SLC, as we covered in 2024. The difference here is that DapuStor hands the host a second and separate block device with storage software control.

Competitors have other solutions. Sandisk’s bet is on Direct Write QLC on its UltraQLC platform, “which eliminates SLC buffering by enabling power-loss safe writes on the first pass,” Sandisk said, but there are still performance differences, according to our own reporting. Alternatively, Micron’s solution offers a separate cache drive in its XTR. The drive uses 176-layer TLC entirely in SLC mode and is rated at up to 35 DWPD. The drive acts as an optional write buffer for arrays of Micron’s 6000-series SSDs. For reference, Micron rates the XTR at 15 microseconds for QD1 writes.

Product promises are valuable, but any full comparison requires seeing the drives in actual use. Questions remain specifically regarding DapuStor’s drive, as pSLC region specifications are lacking. It is uncertain what commands the drive employs and whether the region split is modifiable live; usability depends much on the undemonstrated storage software. More details for the QLC-based, PCIe 5.0 sibling R6060 would be nice, too. Utilizing multi-bit flash in a single-bit, SLC mode for performance or endurance reasons is not a new idea, but balancing those with the increasing need for capacity remains a challenge.

Anthropic and OpenAI are reportedly scrambling to secure smaller AI data center deployments as they race to bring more compute capacity online while gigawatt-scale projects undergo construction. According to a September 18 CNBC report, the two AI giants are exploring agreements for existing facilities with roughly 20-30 MW of capacity, despite already committing tens of billions of dollars to much larger AI infrastructure projects.

Anthropic has reportedly sounded out potential deals of that size across the UK and Nordic countries, according to CNBC, citing four people familiar with the discussions. OpenAI has also explored smaller deployments in the Nordics, while sources said both companies have discussed similar opportunities in the United States.

“We’re building a diversified compute portfolio to meet growing demand for AI around the world,” an OpenAI spokesperson told CNBC. The company added that different workloads require different infrastructure and that it evaluates potential deployments based on performance, reliability, timing, and cost. Anthropic declined to comment.

The smaller facilities would complement the enormous AI campuses both companies are already pursuing. Anthropic, for example, reportedly signed a roughly $45 billion agreement with Nscale for around 460 MW of compute capacity at a West Virginia development. OpenAI, meanwhile, said earlier this year that its Stargate infrastructure commitments had already surpassed the project's original 10 GW target, before announcing another 3 GW in Georgia and 8 GW in Ohio.

These projects provide the large clusters of accelerators needed to train increasingly large AI models, in which thousands of GPUs must work together via high-bandwidth interconnects. However, they also take years to develop, requiring land, grid connections, substations, cooling infrastructure, and huge amounts of power before the accelerators can begin operations.

Meanwhile, both OpenAI and Anthropic need immediate capacity to meet the inference demand for their models. As it turns out, inference can be distributed across multiple smaller clusters, making smaller data centers appropriate for these tasks and increasing the demand for such facilities.

Smaller deployments also circumvent some of the issues plaguing large data center buildouts. In the U.S. alone, local opposition blocked 45 data center projects worth $68 billion in the second quarter of 2026 over land usage, noise pollution, and electricity and water consumption. Existing, small facilities do not face the same pressure.

“Securing a few megawatts at an existing powered site can be more practical than waiting for a much larger block in one location,” Jabez Tan, head of research at Structure Research, told CNBC. “For workloads that can operate across separate sites, a collection of smaller deployments can add up to substantial capacity.”

Renting capacity is already standard practice for AI companies, as AI labs lease capacity from hyperscalers, dedicated data center operators, and rapidly expanding GPU-focused neoclouds. This allows them to spread workloads across multiple providers.

Edit: 8/24/2026 6:25am PT: Energy provider Entergy reached out to clarify the savings to customers outlined below, stating, "The correct number is $2.65 billion over 20 years in customer savings. This information is found in our Meta fact sheet that is publicly available at www.entergy.com/datacenters and in our press release first announcing the savings on March 27, 2026." We have corrected the story below accordingly.

Amended article follows:

Local opposition blocked or delayed $68 billion in data center projects between April and June this year, according to a September 21 Bloomberg report citing data from research group Data Center Watch. The report says 30 state houses have implemented rules on data center location and resource consumption, with communities pursuing moratoriums on planned construction even before developers apply for permits. Conversely, hyperscalers have spent over $1 trillion on data infrastructure since 2023, with an additional $745 billion in Capex expected in 2026 alone.

The blocked-project figures reflect widespread opposition to data centers across the United States over concerns about land usage, noise pollution, and electricity and water consumption. In July this year, 142 AI data center protests were simultaneously staged across 42 states in one weekend. Data Center Watch’s research estimates that there are 843 opposition groups across all U.S. states except Hawaii.

One leading concern is the environmental impact of AI data centers. Each consume huge amounts of water to cool hundreds of thousands of accelerators powering artificial intelligence, with AI reportedly set to consume up to 600 billion gallons of water by 2030. The hyperscalers, on the other hand, insist the issue is being blown out of proportion.

OpenAI CEO Sam Altman says 38,000 ChatGPT queries use as much water as producing one almond, while Microsoft says its new data center architecture consumes as little water as a restaurant. Meanwhile, in May this year, an AI data center project secretly consumed 29 million gallons of water within a year and three months before low water pressure alerted nearby residents to its existence.

Protesters also commonly cite electricity consumption as a major concern. Analysts project that data centers will consume 20% of U.S. power by 2035. Local residents are already feeling the effects. An AI data center in Virginia led to an irreversible 76% hike in residents’ electricity bills, prompting the state to eventually mandate hyperscalers to cover the cost of the transmission infrastructure required exclusively for the project.

Many regions are now implementing similar mandates, with hyperscalers offering to offset the bills in many cases. These concerns, along with the extreme power demands of AI data centers, have also led hyperscalers to build on-site power, with some offering to supply power back to the grid. Meta, for example, recently signed an agreement with utility company Entergy Louisiana for 7 GW of power for its Hyperion facility. Entergy claims Meta's payment provide other customers with $2.65 billion in savings over 20 years.

Meanwhile, the shift to off-grid, on-site power generation is creating yet another issue driving the protests. Due to their scalability and speed of availability, many hyperscalers are relying on gas plants, which mostly burn fossil fuels to generate electricity. Elon Musk's Colossus 2 data center recently came under fire after 59 unpermitted natural gas turbines powering the data center released thousands of tons of pollutants into predominantly black communities in Mississippi. Elsewhere, Amazon’s custom 35-turbine gas plant has been authorized to emit 33 million tons of greenhouse gases annually, a move that will make it the largest single source of CO₂ pollution in the U.S.

The growing sentiments present a sort of dilemma. AI is proving to be quite the revolutionary technology and has seen massive adoption and skyrocketing usage. To meet demand, hyperscalers are erecting data centers at breakneck speed, which residents now oppose. Proponents say data centers are an absolute necessity and any opposition stifles growth.

Opponents, on the other hand, say they are only demanding responsible execution and have nothing against AI. President Trump has condemned communities that have opposed data centers, saying that they “want to end up being backwards and poor.” He has also implied that China could be behind the sentiment, orchestrating movements behind the scenes. Meanwhile, officials across the country are reportedly facing death threats and gunfire over AI data center projects, even as AI data center investments are projected to hit $32 trillion by 2050.

The U.S. House of Representatives just passed a bill that creates a federal standard requiring data centers to pay for grid upgrades made in their favor. H.R. 9340, also known as the Ratepayer Protection Act, amends the Public Utility Regulatory Policies Act of 1978, which would require each State regulatory authority and each non-regulated electric utility to consider the adoption of the bill within two years of its passing, if it is signed into law.

This bill would ensure that data centers with a capacity of 100 megawatts or more would have to pay “the full, incremental cost of any generation, transmission, or distribution upgrade necessary to serve the load of such large-load customer, including in the event of such large-load customer terminating a contract or other agreement with the electric utility pertaining to the sale of electric energy, or otherwise ceasing the purchase of electric energy from the electric utility.” This bill closely follows President Donald Trump’s “Ratepayer Protection Pledge,” where he made AI hyperscalers, utility providers, and state governors promise that they will pay their own way when it comes to their electricity demands. All this stemmed from the surprise price hikes that many residential users and small businesses suffered from because of the massive demand by AI data centers and has become one of the primary reasons why the majority of Americans now oppose data center developments in their communities.

Oregon is actually one of the first states to have taken concrete steps in controlling the utility price increases when it passed the POWER Act in 2025. This law is even more stringent, with any development using more than 20 megawatts required to pay its fair share, and has already resulted in a 30% hike for data center electricity bills and a 1.3% reduction for residential power costs. Virginia has also followed suit soon after its governor signed the Ratepayer Protection Pledge in July 2026, with Virginia’s State Corporation Commission requiring data centers to pay for all required transmission infrastructure.

Even though the House of Representatives has already passed H.R. 9340, it still needs to go through the Senate before finally heading towards the White House for signing by the President. But even if it passes through the remaining hurdles, and the U.S. adopts a federal standard where large data centers pay for grid upgrades done in their name, it’s still up to each state regulator if they will adopt the standard. Furthermore, states have up to two years to make a final decision, meaning there’s a chance that the various temporary data center bans and moratoriums would have expired even before state regulators would have enacted this bill.

New York State Governor Kathy Hochul has just announced the Community Investment Framework (CIF), which serves as a negotiation guide for towns and municipalities in the state when they’re dealing with data center developers, recommending that communities demand $1 million per megawatt for the privilege of housing data centers. According to Empire State Development [PDF], the state’s economic development agency, the CIF offers “a structured approach to identifying, negotiating, and documenting investments from data center developers/operators/owners that address local priorities and create lasting community benefits.”

The document recommends six principles during data center negotiations: an investment benchmark of $1 million per megawatt of utility demand; long-term planning, including plans for when the data center leaves the facility; a roadmap to manage ongoing costs for projects funded through the CIF; a list of local priority investment areas to address the needs of the community; local ownership confirmation of projects receiving funding from data centers; and clear timelines for any program, especially those that require phased, multi-year investments. Aside from these, it also gave several recommendations, such as focusing on community engagement, engaging decision-makers and counsel, incentivizing good faith and timely negotiations, and maintaining flexibility, among others.

While data centers have been around for decades now, AI data centers are relatively new and are putting more pressure on electricity and water supplies. They also offer limited job creation and community value compared to other industries, which is why Loudoun County, Virginia, which hosts 250 data centers, has started reining in these facilities as well. More than 500 states, counties, and localities across the nation have already passed a moratorium or temporary ban against data centers, including states like New York and Texas. However, these have an expiration date, meaning government units only have a limited time before they would have to start processing data center applications once more.

This framework is a useful guide for when municipalities have to start negotiating with data center developers again, helping ensure that these projects would bring more benefit to the community while limiting their negative effects. One Pennsylvania town actually created a similar comprehensive document, outlining 43 specific demands before approving a proposed data center in Plymouth Township. Unfortunately, the said developer decided to cancel the application and file a new one instead, with the town accusing it of demanding approval “by tantrum.”

Reports suggest that various data center developers have requested up to 9,000 MW from the state grid. However, this does not include operators that are opting to bring their own power sources or build their own power plants on site. So, if New York towns and municipalities adopt the CIF in their negotiations with data center developers, this could potentially add $9 billion or more towards their coffers. This may seem like a lot of money, but it’s a drop in the bucket compared to the expected $32 trillion that some experts suggest will be invested in data centers by 2050.

ABF substrates, the specialized insulating and wiring bases that connect tiny silicon chips above them to the much larger printed circuit boards below, sit beneath most high-end CPUs, GPUs, and AI accelerators. Featuring the Ajinomoto build-up film (ABF), these substrates have been critical to the semiconductor industry since the late 1990s, with personal computers, workstations, servers, and networking silicon driving steady demand for decades.

The artificial intelligence boom has multiplied that demand exponentially. Training and inference for frontier models now run across data centers, each housing hundreds of thousands of accelerators and providing hundreds of megawatts of compute. Nvidia alone shipped an estimated 3.2 million Blackwell GPU packages through the end of 2025, with every one of those accelerators packaged on an ABF substrate. Meanwhile, the industry is already entering the gigawatt era with humongous data center buildouts, each expected to house millions of AI accelerators.

This edifice rests on a remarkably narrow supply chain. Practically every advanced logic and AI chip made today by Intel, AMD, and Nvidia depends fundamentally on ABF substrates. These substrates are the conventional default for high-performance packaging. They are made by a small group of specialists, including Unimicron, Ibiden, Kinsus, Shinko Electric Industries, Samsung Electromechanics, and Nan Ya PCB. The upstream supply chain gets much tighter.

The one common denominator across ABF substrates, regardless of manufacturer, is the Ajinomoto build-up film itself. Each substrate maker laminates its build-up layers using dielectric film supplied by Japan's Ajinomoto, which controls a reported 95% or more of the global market. A single company, better known for food seasoning than microelectronics, sits at the base of one of the most concentrated supply chains in computing, almost singlehandedly supplying a material for hundreds of millions of semiconductor devices. Not surprisingly, demand is now growing beyond what the supply chain can comfortably supply.

Compounding this crunch, modern AI accelerators now pack multiple compute, memory, and supporting components onto a single board. As a result, the substrate is getting larger across the X-Y footprint to accommodate the expanding package. Manufacturers are also adding more build-up layers to the substrate to route the growing number of signals and power connections. Each additional layer requires another ABF layer, further multiplying demand across millions of accelerators and extending manufacturing times.

Unfortunately, the complications don't stop there. Beyond further straining the supply chain, expanding the substrates is creating technical problems, such as warpage, yield issues, and electrical losses within the component itself. This leaves the ABF substrate ecosystem facing two related challenges: producing enough advanced substrates for a rapidly expanding fleet of AI accelerators, while simultaneously re-engineering these substrates so they can continue to scale without becoming unmanufacturable or impractical.

The ABF substrate roadmap is consequently as much about supply-chain capacity as it is about the hardware itself, with suppliers such as Ajinomoto and Ibiden outlining plans to expand material and manufacturing capacity, respectively. At the same time, the wider industry — Intel, Samsung, and SK's Absolics among them — is exploring glass-core substrates and other material technologies to push past the limits of organic ABF.

ABF substrates

Silicon dies, including CPUs and GPUs, cannot communicate directly with the printed circuit board beneath them. The connection pads on a die are spaced micrometers apart, while the traces on a motherboard are spaced hundreds of micrometers to millimeters apart. Every high-performance chip, therefore, sits on an intermediary package substrate — a dense, multilayer board that fans the ultra-fine connections on the die outward into connections large enough for the motherboard to handle, while also providing signal routing, power and ground distribution, and mechanical support for the package.

ABF substrates used in AI accelerators typically consist of a rigid, glass-reinforced resin core sandwiched between successive build-up layers of copper wiring and insulating film. The core provides much of the mechanical rigidity, while the layers provide the increasingly dense wiring required close to the silicon.

To create the substrate, the manufacturer laminates the ABF dielectric onto the structure, forms microscopic vias — commonly with a CO2 laser — and then uses lithography and copper deposition to create a new wiring layer. High-end substrates typically use a semi-additive process (SAP), in which fine copper traces are plated up from a thin conductive seed layer. Another ABF layer is then laminated over it, and the process repeats. The film electrically separates successive copper layers, while plated microvias connect them vertically.

Ajinomoto developed the film in the 1990s, after which it gradually became the industry default for its low dielectric loss, fine-line capability, and smooth lamination. The company reportedly accounts for roughly 95% of the substrate film market, with its nearest competitor, Sekisui Chemical, holding only a low-single-digit share.

The manufacturing tier above the film is more populated but still concentrated. Unimicron, Ibiden, and Shinko together account for roughly three-quarters of the substrate market by most estimates, with AT&S and Nan Ya PCB rounding out the leading group. These companies take ABF and other materials and manufacture the finished multilayer substrate. Semiconductor packaging companies, such as TSMC and Amkor, then integrate those substrates into packages containing the processor, memory, and other components.

AI accelerators are pushing substrates outward and upward

To deliver the compute and memory bandwidth that frontier models demand, the industry is packing ever more silicon onto each AI accelerator. Designers now place multiple large logic dies alongside a growing number of high-bandwidth memory stacks on a single package. Nvidia's Blackwell generation mounts two reticle-sized GPU dies and eight HBM3E stacks on a single package, with its upcoming Rubin and Rubin Ultra parts pushing it further still. TSMC's CoWoS packaging is scaling from around 3.3 reticles — each roughly 830 square millimeters of silicon — a generation ago to 5.5 reticles in volume production in 2026, with a roadmap reaching 9.5 reticles in 2027 and beyond 14 reticles by 2029, when a single package is expected to carry roughly ten compute dies and twenty or more memory stacks.

This expansion of the accelerator package is driving the substrate’s expansion on two physical levels. The first expansion is the substrate's footprint in the X-Y axes. The base has to get wider and longer to accommodate the larger package footprint. Ibiden's current roadmap puts its cutting-edge substrate size at 90 × 90mm (3.54 x 3.54 inches) in 2026, 110 × 110mm (4.33 x 4.33 inches) in 2028, and 130 × 130mm (5.12 x 5.12 inches) and larger from 2030 onward. Ajinomoto independently expects the representative advanced AI packages its film goes into to grow from roughly 100 mm² in 2026 to about 120 mm² for 3D AI packages from 2031.

The second expansion is along the Z axis through additional layers. An expanded collection of compute dies and memory creates more signals to route, while the corresponding increase in power draw requires extensive power and ground distribution, all of which must be carried in a growing number of layers. Ibiden's roadmap targets a 10-X-10 buildup structure in 2026, 12-X-12 in 2028, and 14-X-14 from 2030. Here, the numbers represent the build-up layers on either side of the central substrate core: “10-X-10” means 10 build-up layers per side of the core — which is represented by the “X” — each comprising one dielectric layer (ABF) plus one patterned copper layer, working as a pair.

Nan Ya PCB's roadmap points in the same direction. From an 11+N+11 baseline, it targets 24-layer substrates in 2026 and more than 24 layers in the first half of 2027, while tightening line and space from a 9/12 µm baseline to 8/8 µm and then to 6/7 µm by early 2027. Layer-counting conventions differ between vendors, so a per-side figure and a total layer count don't necessarily line up directly.

The substrate’s expansion in both directions creates several challenges. Increasing the X-Y area makes the package harder to keep flat. Silicon, copper, the substrate core, and the polymer build-up materials that make up the substrate expand by different amounts when heated. As the package is bonded during assembly at around 250⁰C and then cooled, these mismatches cause the layers to pull against one another, leading to warping — a problem that becomes harder to control as package dimensions increase.

Excessive warpage can undermine solder-joint formation, layer-to-layer alignment, and reliability, while a larger substrate also occupies more manufacturing-panel area and exposes more area to potential defects. Organic substrates are reported to lose usable flatness once packages exceed roughly 120mm per side, a threshold that the largest AI accelerators are now reaching and that Ibiden's own roadmap — climbing toward 130mm and beyond — is set to cross.

The growing layer count along the z-axis also creates manufacturing challenges around yield, capacity, and time. Every new substrate layer requires a full manufacturing sequence of several steps, all held to sub-ten-micron tolerances. Each added layer increases the chance of a defect or alignment error that can scrap the whole substrate.

Additionally, layer count consumes manufacturing capacity and time in proportion. This is why Ibiden frames future demand in terms of semi-additive processing load rather than a simple substrate count, as a single advanced substrate now consumes far more of a line's capacity than a finished-unit tally would suggest.

Overall, the simultaneous expansion in substrate area and layer count means ABF consumption is rising much faster than processor shipments alone suggest. Ajinomoto illustrated this in its 2025 integrated report with a larger AI substrate that had about 3.5 times the board area and three times as many ABF layers as a conventional design — 18 layers against six — consuming roughly ten times as much ABF overall. This surging material consumption, set against an extremely concentrated supply base, extends the ABF substrate story beyond a technical problem into a supply-chain constraint.

The supply chain constraint

Like many components in the semiconductor industry chain before the AI boom, demand for ABF substrates periodically swung both ways. A severe bottleneck through 2020-2022 — driven by pandemic-era PC and server demand — was followed by an oversupply in 2023, as substrate manufacturers expanded capacity. However, that capacity was built for low-layer-count, smaller consumer substrates, not the large-body, multi-layer packages AI demands.

These advanced products require sufficiently large manufacturing formats, fine SAP wiring, tight layer registration, acceptable warpage, and high yields across much larger structures. Ibiden captures this by measuring demand not in finished substrates but in semi-additive-process load — the actual processing work each part imposes on a line. Indexing 2024 at 1.0, it expects the SAP load of a single AI-server substrate to reach 1.8 times that in 2026 and 2.5 times in 2028, with the company stating that substrate expansion will push total SAP demand beyond industry supply capacity, indicating a constraint in the manufacturing process itself.

The bottleneck is even tighter at the ABF material level. Ajinomoto's film capacity was already running at full load in the second quarter of 2026, at a reported two million square meters per month, although the company has outlined plans to increase capacity. A near-monopoly supplier at full capacity while consumption surges paints a clear picture of the bottleneck’s severity.

Unsurprisingly, prices have moved accordingly. Ajinomoto notified substrate manufacturers in May 2026 that it would raise ABF film prices by approximately 30%, effective in the third quarter. The hike is coming alongside comparable increases in copper-clad laminates from Resonac and Mitsubishi Gas Chemical, compounding pressure across the whole stack. Further tightening the squeeze, Ajinomoto recently cut shipments of the critical ABF film to China by 30%.

The growing ABF substrate problem cannot simply be attributed to Ajinomoto running out of film. In fact, while it's running at full capacity, the company says it has no concerns about its overall supply chain. The constraint stretches across the entire chain containing ABF, glass cloth, and other materials, SAP equipment, large-format substrate factories, yield, and customer-qualified production capacity.

The immense industry demand is progressively tightening the crunch. Several supply-chain analyses converge on an ABF supply-demand shortfall of roughly 10% in the second half of 2026, widening to around 21% in 2027 and potentially exceeding 40% by 2028, with demand for substrate area projected to grow at a compound annual rate near 39% from 2025 to 2028 as accelerators integrate more components.

The roadmap to recovery: more capacity, better materials

The industry is responding to ABF substrates' multifaceted constraints on multiple fronts: expanding manufacturing capacity to relieve near-term supply pressure while qualifying new materials and substrate architectures to break through the technical limits. Capacity expansion is already underway across the supply chain.

Ibiden is executing ¥500 billion ($3.1 billion) in capital investment across fiscal years 2026 to 2028 — the largest single substrate expansion on record — targeting 2.8 times its 2024 capacity for ASIC and AI-server substrates by 2028. Unimicron raised its 2026 capital spending to a record NT$34 billion ($1.07 billion), with a focus on ABF substrates. Meanwhile, Samsung Electro-Mechanics, Samsung's substrate arm, has committed $1.2 billion to expand ABF substrate production, with volume production expected by the third quarter of 2027.

Pegatron's substrate unit, Kinsus, has approved NT$23.5 billion ($722 million) for ABF equipment over three years and now focuses its most advanced lines almost entirely on AI clients, aiming to lift monthly output at its Taoyuan plant by roughly 25% by 2027. While these projects address the shortage directly, their lead times mean the crunch may continue for a while, as supply cannot respond instantly to the AI demand spike.

Ajinomoto is expanding upstream as well. A new plant in Gunma entered full operation in 2025. The company has invested roughly ¥25 billion ($157 million) in ABF production since 2023 and has said it will invest at least as much again by 2030, targeting a capacity increase of more than 50%. It is also adding a third Japanese base for varnish production — envisioned to provide capacity comparable to Gunma — with construction planned for 2028 and operations to begin in 2032.

However, capacity only solves the problem if the current substrate architecture can continue to scale. The material roadmap — aimed at addressing the physical constraints of ABF substrates — is therefore advancing parallel to the factory roadmap. Ajinomoto says present and future ABF generations are being engineered for larger, more multilayered substrates, high-bandwidth I/O, lower transmission loss, and improved resistance to warpage and humidity. The company expects newer, higher-value ABF grades to take an increasing share of its portfolio through 2030.

Substrate makers are addressing the problem from the process side. Nan Ya plans to move beyond 150 mm body sizes and 24 layers while shrinking copper line/space geometry toward 6/7 microns in the first half of 2027. Its materials roadmap includes an ultra-low-CTE core material with a CTE below 3 ppm/°C, alongside low-Dk, low-Df, and low-CTE dielectrics. Finer wiring allows a substrate to support more connections without relying solely on additional area or layers, while low-expansion materials help keep the growing structure flat.

Eventually, the substrate's central core itself may change to glass. Organic substrate cores are increasingly difficult to keep dimensionally stable as packages approach and surpass 100 mm. Glass can be matched more closely to silicon's thermal expansion — providing dimensional stability — and offers substantially lower dielectric loss for high-speed links. It has therefore emerged as one of the industry's main solutions to warpage.

As we detailed in our glass substrate roadmap, the move to a glass core is drawing a broad field, as it sits at the intersection of substrate-making, glass manufacturing, and advanced packaging, pulling in chip-and-packaging houses, display and glass specialists, and the incumbent substrate makers alike. Intel demonstrated a package that combines EMIB with a glass substrate at NEPCON Japan in January 2026, although the company still places commercial glass-substrate deployment in the latter half of the decade.

SK Group subsidiary Absolics is operating a low-volume glass-substrate manufacturing facility in Covington, Georgia — backed by $100 million in US CHIPS Act funding — producing prototype and qualification samples for customers, such as AMD for its MI400-series accelerators, while Samsung Electro-Mechanics is producing prototypes on a pilot line in Sejong and now plans mass production through its glass-core joint venture after 2027.

TSMC, meanwhile, is pursuing panel-level packaging through its chip-on-panel-on-substrate (CoPoS) platform, moving to a 310 x 310mm panel format, with a pilot line at its VisEra subsidiary, trial production targeted for 2027 and mass production for the second half of 2028. Glass-core substrates are a separate, later step on TSMC's roadmap, with commercial scale projected after 2030. Ibiden also puts “glass core” on its substrate technology roadmap around 2030 as a solution for warpage control.

The glass core — most likely a late-2020s-to-2030s technology — is positioned as a solution to the warpage wall. It replaces the organic core, not the ABF itself, which would remain the buildup material. A glass core may soften ABF demand per package, as glass's flatness allows finer routing and potentially fewer buildup layers, but it does not remove the material or the dependency. There's the possibility that a future dielectric material will eventually replace ABF, although that doesn't seem to be the industry's main focus currently.

Regardless, the near-term roadmap centers on more advanced SAP capacity, rapidly expanding factories, improved materials, and increased supply. Through the late 2020s, finer wiring, lower-loss ABF, lower-CTE materials, and better warpage control will enable organic substrates to stretch toward 110 mm and beyond. Around 2030, glass cores offer a path toward the 130 mm-plus packages that Ibiden and others already have on their roadmaps.

Modular laptop manufacturer Framework has just announced that it's dropping some of its memory pricing for its new Framework Laptop 13 Pro after previously doubling it back in July, including retroactively for orders that have already shipped. Posting on social media and in an update on its blog, the company says that it's been able to source new inventory at a reduced cost.

"We have a positive update today on LPCAMM2 pricing! We were able to source a limited quantity at lower cost, and are retroactively reducing prices for orders that shipped at higher price, as well as offering the lower price to orders through Batch 10" according to the company's recent X post. A further update, posted on the company's blog, goes on to explain that Framework's Supply Chain team "has been working continuously to source additional inventory at better prices."

The lower prices are due to a "limited quantity" of Micron 32GB and 64GB LPCAMM2 memory modules that the company has secured at "lower cost," and that as the company is "committed to passing on savings whenever we can," it is passing the price reductions back to customers. LPCAMM2 memory is available for the Intel Core Ultra Series 3 version of the Framework laptop. Other models, like those shipping with AMD Ryzen AI 300 CPUs, are using SO-DIMMs instead.

The price reductions are being applied to "both already shipped and a subset of pending pre-orders," according to chief executive Nirav Patel. This improves the situation for consumers compared to the last price update on July 22, which saw Framework almost double its prices for 32GB and 64GB LPCAMM2 memory in the Laptop 13 Pro. While these new prices are "still above our original pre-order launch baseline, they are lower than the last cost update that drove our current pricing for new pre-orders," according to the company.

This pricing isn't expected to last for long, however. As Framework notes, only a limited quantity of new modules has been acquired at lower cost. Framework explains on X that these are being made available "first-come, first-serve to customers through Batch 10". If the company is able to source more, then it'll "open it to later batches and then to new pre-orders."

Framework is automatically refunding the difference if your order has already shipped and you paid the higher price. Pending pre-orders through to Batch 10 have also been adjusted to reflect the better pricing. If you're waiting on a pre-order and want to update the RAM capacity you've ordered to take advantage of the lower prices, that option is now available via the order summary page, with instructions in Framework's Help Center if you run into trouble.

Those with a DIY Edition Framework 13 Pro that has already shipped and who want to switch to the 32GB or 64GB LPCAMM2 modules at the lower price can also fill out this contact form to organize a swap.

Patagonia, a region of Argentina with 17,300 glaciers, has the potential to turn into a data center hotspot. The cool climate and abundant energy resources there are drawing interest from the likes of Amazon, Google, and OpenAI, according to Reuters. However, there needs to be more work on tapping into the resources and equipping high-speed networking, like fiber, to make the place irresistible. There’s also the question of political stability with a presidential election next year.

Argentina, and Patagonia in particular, has some juicy lures for potential hyperscale data center operators, and the cold climate is a bonus. That environment helps keep data centers cool and use less power while maintaining agreeable thermals. Patagonia has tens of thousands of glaciers across the Northern Patagonian Ice Field and the Southern Patagonian Ice Field combined.

Another bonus to would-be Patagonian data center operators are the range of energy sources there. Reuters mentions hydroelectric power, wind, and shale gas, but some operators who are already established are also adding solar.

Then, the social and political climate looks good for data centers in Argentina. According to the source, the populace doesn't hate data centers yet. At least there seems to be no campaign groups or public backlash. It is also reported that President Javier Milei has been making changes to court Big Tech. That’s a positive, and may be a negative. Positive in that the Argentines are now being accommodating to the needs of huge AI data centers. Negative, as there’s a presidential election next year, where things could take a dramatic turn, or not. There are also some regions in Patagonia where data center expansions may be complicated by the wishes and needs of indigenous communities. Businesses offering sizable, long-term investments aren’t keen on uncertainty.

With the pretty good environment for hyperscale buildouts established, it isn’t that surprising to see Reuters say OpenAI has confirmed a $25B and 500MW clean energy data center in the country. Lesser-known (to us) companies like Poland's Green Capital also plan a $3B and 300MW data center in Patagonia. It is also reported that FlexDomes, a U.S.-based green data center company, is planning the first stage of a 120MW facility.

Meanwhile, in neighboring South American countries, there are large developments from the likes of Amazon, Google, and others. Argentina must have these data center whales in its sights, as they are known to be scouting for expansion into new locations.

As well as political / business risk, Argentina has some structural weaknesses that need to be addressed by those developing in the country. It is said to have connectivity and power grid infrastructure deficiencies, for example. In other locations, we have seen these addressed on almost a per-project basis, with some state intervention, but it adds some high costs to setting up.

A Bitcoin mining data center in El Reno, Oklahoma, has been condemned after it leaked 3 million gallons of water, reports Koco TV News. Schools, businesses, and city and county offices were all closed last week due to the leak.

According to the source report, the Athlon Blockchain LLC-owned data center shouldn’t even have been operating, as the city issued it a Stop Work Order in 2023 due to “multiple fire and life safety code violations as well as the expiration of the building and electrical permits that had previously been issued.” The city asserts that none of the costs related to the water leak at the property will be passed on to citizens, according to the source.

We don’t know whether the Bitcoin mining data center development went ahead despite the Stop Work Order in 2023 due to ignorance or a devil-may-care attitude toward regulation. Koco reports that the owner of the property was given until the end of 2023 to comply with safety codes and obtain new permits, while construction should have been put on hold. Now it is believed that the firm building the facility set up the data center and began operations without any further consultation with the city. Perhaps the owners thought they could sidestep the Stop Work Order by housing the data center in an array of shipping containers.

Clearly, regulators should check that codes, directives, and ordinances are obeyed. This incident shows a disastrous leak from an insufficiently policed operator with serious repercussions for local citizens. Thus, the city has now committed to routinely reviewing compliance. As for the waste and costs involved in this case, a statement on behalf of the city says it is “preparing to take the necessary legal actions to recoup all costs and expenses related to the water leak from the property owner, including city resources expended in locating and addressing the leak.”

There has been a lot of controversy recently regarding data center usage of water. Concerns have been heightened due to widespread drought conditions in the Northern Hemisphere this summer.

Denver Water, which supplies the city and its surrounding areas, has imposed Stage 1 drought restrictions in its service area starting August 2026 as water supplies continue to drop. According to Gadget Review, commercial properties like data centers can only water grass twice a week — on Tuesdays and Fridays — until September 30. Starting October 1, lawn sprinklers will be banned for use until the Board of Water Commissioners declares otherwise. However, one resident who was out walking their dog saw that the new AI data center built close to their home was watering its lawn and using so much water that some areas have started to puddle.

“We can’t water our lawns until next summer, at the earliest, but you better believe that they are watering their entire green with so many sprinklers that it’s already making a giant pond, but I can’t water my f****ng tomatoes. I hate it here,” one resident claimed in the video.

This has understandably raised a lot of outrage, especially with all the widespread, bipartisan resistance that these data centers have been facing. However, there are still a lot of unknowns when it comes to the video. Firstly, we do not know when the video was shot; there’s a possibility that it was recorded on either a Tuesday or a Friday, meaning the site was well within its rights to water its lawns, at least until September 30.

The publication also noted several other possibilities: it could be using recycled, non-potable water, which Denver Water explicitly states, “are approved to irrigate any day of the week”; it could hold a variance from the utility provider, granting them permission to water their grass under “special circumstances,” or it was just plainly violating the law. Without further information, there’s just no way we can determine what is going on based on a single video. Nevertheless, this compounds the negative perception that data centers are already facing. Although closed-loop cooling technologies like those from Microsoft and Nvidia have essentially cut data center water consumption for cooling to zero, we still cannot get around the fact that several sites have already caused water issues for their neighbors.

Many people are raising issues about data centers’ massive resource consumption and the other negative effects like noise and air pollution that they could potentially bring to their surroundings. It’s for these reasons that Denver, and hundreds of other jurisdictions, have passed temporary bans and moratoriums on data center development.

Amid growing community backlash, SpaceXAI offered a 50% discount to anyone living near its two data centers in Memphis, Tennessee, and claimed that thousands have already taken advantage of the promotion. Aside from the discounts offered to residents of the city and neighboring Southaven, Mississippi, SpaceXAI Memphis said in its X post that it’s also waiving the upfront hardware cost for the recently launched Starlink V5 rental kit across all plans, saving users up to $349 in one-time costs.

Critics say that Elon Musk is simply making this move to buy goodwill with his neighbors, especially as his data centers have been in hot water over the deployment of unpermitted turbines to deliver much-needed power. "Communities in Memphis and North Mississippi aren’t asking for discounted internet service,” SELC Senior Attorney Amanda Garcia told PCMag. “They're asking xAI to shut down its illegal, unpermitted power plant that continues to pump out staggering amounts of harmful (sic) pollution, including smog-forming nitrogen oxides, fine particulate matter, and hazardous chemicals like formaldehyde.” While SpaceXAI has since promised to remove all 69 of its unpermitted generators, it says it will do so only over a span of one year as its 1.2 GW power plant comes online to replace them.

Starlink residential plans are available in three tiers: 100 Mbps for $55 a month, 200 Mbps for $85 a month, and Max for $130 a month. Residents who subscribe to any of these plans could get them for just $27.50, $42.50, or $65, respectively, resulting in massive savings. This makes the cheapest Starlink plan more affordable than other internet service providers like AT&T and Xfinity, whose plans often start at $35 to $40 per month.

However, those competitors offer fiber-based connections with speeds up to 300 Mbps, meaning users would be getting a downgrade if they switch over. However, some users in the r/memphis subreddit commented that this is a great option for areas of Memphis and Southaven that still lack fiber access, and it could also be a useful backup for those who need reliable internet service. There were also several complaints about outrageous fees from other options, which drive their internet costs well above $40, making the $27.50 monthly fee for the 100 Mbps Starlink plan a tempting option. Interestingly, the company is also offering the same discount in Vermilion Parish, Louisiana, where SpaceX plans to build its new spaceport.

While the company’s social media post makes it seem like 2,000 is an achievement, it’s still a small number relative to the city's total population. The latest U.S. Census Bureau estimates that Memphis alone has a population of over 600,000 people and more than 250,000 households. That means the new subscribers account for less than 1% of the total homes in the city. Aside from that, SpaceXAI’s latest earnings report says that it has more than 12 million subscribers, so the 2,000 new subscribers from the city are just a drop in the company’s massive bucket of Starlink users.

Independence City Council member John Perkins lost his position after 68.05% of voters opted to oust him in a special election because he supported data centers. According to NBC News, Perkins was one of the five councilors who said yes to the tax breaks amounting to more than $6 billion for the Nebius data center being built in the area.

Many members of the community have been campaigning against this development ahead of the March City Council meeting when these tax breaks were approved, but the council ended up voting 5-2 anyway in favor of the data center. Perkins is the third to have lost their seat after this vote, with Jared Fears, who was running for re-election in the city council, and Bridget McCandless, who was running for mayor, losing their respective bids.

“Politicians aren’t entitled to elected positions. They’re elected by the people to serve those people. When they stop serving the people they were elected to represent, they’re voted out of office,” a member of the Stop the AI Data Center in Independence Facebook group said. “This is democracy in action.” While Perkins hasn’t released a statement yet after the release of the unofficial results of the Special Recall Election, he previously said in an Op-Ed on The Kansas City Star that he stands by his decision to support the Nebius tax breaks and that recalling him would be a setback for the city.

“You can disagree with that call, and I respect that. However, disagreement isn’t a crime, and I don’t believe it is grounds to attempt to overturn an election that happened two years ago,” Perkins wrote. “One vote is not a reason to erase the previous hard work I’ve done for my district.”

Despite the massive support for ousting Perkins, we should also note that the voter turnout for this issue has been abysmally small. Out of the 14,250 registered voters in Jackson County, only 1,643, or 11.5%, went to the polls to vote for or against the councilor.

Another Missouri town has voted out half of its city council, which approved a data center project within its jurisdiction. The people of Festus, Missouri, ousted four of the eight members of its council in a regular election in April 2026 after they approved a 360-acre data center project in the area. Another petition was raised to have the remaining four members recalled, but the measure was shot down by the council.

The popularity of data centers has fallen across the country, with the number of bans and moratoriums over these developments exceeding 500, spread across towns, cities, counties, and even states. Interestingly, the pushback against these developments straddles beliefs and political affiliation, making it harder for hyperscalers to get new projects off the ground.

OpenAI CEO Sam Altman has downplayed the water consumption issue that AI data centers are facing, saying that it has been blown out of proportion over time and does not keep up with the latest developments in data center cooling technology. Altman said this in an episode of the Sources Podcast with Alex Heath, where the two talk about the backlash against AI development. He claimed that producing a single almond in California is equivalent to 38,000 ChatGPT queries.

“You know, I saw this thing going around about the water usage of ChatGPT. And it was like every time you run a single ChatGPT query, it’s like, you know, you run your shower for like six hours. And the water never comes back, and it’s just done. I don’t have the exact calculation in front of me, but I think the real number is something like — doing this from memory, it might be wrong, but it’s close — for every 38,000 ChatGPT queries, that is the same amount of water that is used in the production of a single almond in California… This is like the full-on, you know, total true water accounting, not just what’s running in one data center,” Altman told the host.

“There’s a question of like where this came from because the people that are scarfing down 12 almonds at a time don’t feel like they’re doing something horrible from a water perspective, for the most part. It is true that data centers at one point used evaporative cooling, but they have not done that in a long time. Like if you look at a modern very large data center, it uses the equivalent amount of water as an office building in terms of, you know, people like running the sinks and the toilets and whatever. So, that has been a robust meme and difficult to disprove, but I don’t think it holds up to any scrutiny.”

It’s true that almonds are some of the most water-intensive crops being grown in the U.S. Researchers say that it takes about 1.1 gallons of water to grow a single almond. By comparison, Altman's own statements in the past indicate that one ChatGPT response uses somewhere between 1 to 50mL of water, ostensibly using older evaporative cooling techniques, or about 0.0002 to 0.013 gallons per query. While this is nowhere near Altman’s 38,000 estimate, it’s still about 85 to 5,500 ChatGPT queries per almond using an unspecified cooling method. Nevertheless, training AI models in older facilities can use far more water, with estimates suggesting that GPT-3 used up almost 185,000 gallons of water with older systems, while the increasing popularity of AI, especially AI agents which use up a lot more tokens than just chatbots, means that data centers could still use more water compared to almond farming.

In fact, multiple data centers across the United States have faced issues with their water consumption, with one site in Fayette County, Georgia, using up 29 million gallons over a span of 15 months and another development in Morgan County, Georgia, allegedly causing the water of its neighbors to turn muddy. Altman admitted that data centers that used older technologies like evaporative cooling used a lot of water, but he also mentioned that new techniques and technologies have been developed that cut down data center water use. Some examples of this include Nvidia’s liquid cooling system that runs “hotter than a hot tub,” which cuts water use by 100%, and Microsoft’s closed-loop cooling systems, which use the same amount of water as a restaurant. Amazon even claimed that its data centers consume only 0.075% of the water that Americans use for their lawns and gardens.

You can watch the complete podcast episode below.

PricewaterhouseCoopers LLP (PwC) estimates that spending on AI data centers could reach as much as $31.6 trillion in the next decade and a half, with optimistic outlooks suggesting that capital expenditure could potentially hit $50 trillion. Bloomberg reports that this amount exceeds the spending that railways, electrification, or the internet required when they were being set up for the first time. It also pointed out that investments in AI data center infrastructure aren’t a one-time expense that would last decades, unlike railroad networks, the power grid, or fiber optic cables — instead, data center operators are expected to purchase new GPUs and related infrastructure every four to six years.

GPU development is happening at breakneck pace, with Nvidia, AMD, and other manufacturers releasing new generations every two to three years. In fact, one Google architect said that a data center GPU service life is only about one to three years, which has got some experts concerned that GPU depreciation could be the next big crisis for hyperscalers. “Railways. Electrification. The internet. Each required enormous amounts of capital and defined an era,” the publication reiterated from the report. “The AI infrastructure cycle underway dwarfs all three. This one resets every four to six years — and shows no signs of ending.”

Nvidia and other chip manufacturers would be some of the biggest winners in this spending spree, but other hardware industries would also benefit, like networking equipment and even the copper material needed for running power inside data centers. PwC is confident in its forecast, especially as it claimed that both capital and demand for the AI build-out exist. It also broke down the investment in each region — spending in the U.S. is projected to hit $15.1 trillion, followed by the Asia-Pacific region, including China and India, at $8.2 trillion. Europe will likely spend $5.6 trillion, and it’s trailed by the Middle East at $1.1 trillion and Africa, with $255 billion.

The AI build-out is not without risks, though. The report cited power availability, data sovereignty requirements, and chip availability as factors affecting the build-out. For example, data centers in the U.S. are forecasted to consume 20% of its total power supply by 2035, which is why operators are turning to natural gas turbines for on-site power. However, this has also led to jet engine shortages, which is why SpaceX has started in-house turbine blade manufacturing to cut delivery delays by up to 18 months. It also said the geopolitical tensions, like trade bans on rare earth elements and high-end chips, could cut the global investment forecast by 20%.

There are still some concerns that the current AI boom is a bubble that will pop sooner or later. This is especially true as some AI tech companies currently have “hidden debt” worth around $1.65 trillion, while costs have started spiking as AI companies like OpenAI look for a path towards profitability. Despite that, Nvidia is still going full steam ahead, partnering with several firms to build a $500 billion AI infrastructure fund for further AI investments.

The Oklahoma Office of the Attorney General commanded the City of Claremore to release body cam footage requested by farmer Darren Blanchard and his legal team without charging them $17,125.44. According to 404 Media, the city is asking for that amount so that it will release information on Blanchard’s arrest in April 2026 for speaking 30 seconds longer than the allowed time during a public consultation for a proposed data center in the area, as well as city records of previous disturbances in other public meetings. This led Kate Griffin, one of the farmer’s lawyers, to complain to the Oklahoma Attorney General, which looked at the situation.

Claremore justified the fees by saying that it would need to spend $16,540.44 for a legal review of requested records “to ensure that all information which must be withheld relating to members of the public and the City’s personnel is redacted in order to protect their privacy.” It’s also asking for $585 — equal to the 15-hour pay of a city clerk — to conduct the search of the documents.

“The City knows and is aware that any documents released to Mr. Blanchard and to those associated with him, regardless of the privacy implications of individuals named in such documents, are subject to wide distribution, including on social media,” Claremore said in its response to the Oklahoma AG. It also added, “Her persistence in maintaining an overly onerous request demonstrates that this dispute has nothing to do with transparency and likely has everything to do with causing excessive time/money expense to the City in order to generate public sympathy for her client and negative publicity for the City.”

However, Assistant Attorney General for Oklahoma Anthony Sykes said that this isn’t a valid reason to charge Blanchard thousands of dollars for this request. He said that the state’s law says that public bodies can only charge for the direct costs of searching and copying data when it comes to information requests. More than that, all the fees being charged must be disclosed publicly beforehand.

“The City has not posted a schedule of fees as required by the Open Records Act. Having failed to give the requisite notice of the fees charged for public access to City records, the City is foreclosed from charging search fees,” Sykes said. “If I were to conclude otherwise, there would be no incentive for public bodies to comply with the statute. They could simply ignore what the ORA requires and charge what they deem reasonable on a case-by-case basis.”

Another justification the city used for the egregious fees is the need to redact the body cam footage “to protect the privacy of the public and City personnel.” However, the assistant attorney general said that the incident happened at a public meeting with no reasonable expectation of privacy. Because of this, the city should hand over the requested data as soon as possible.

Blanchard is being charged with trespassing, a municipal crime with a penalty of just $200, making these charges very steep by comparison. Even though it might’ve been easier to plead guilty and pay the fine, the farmer is fighting the city on the grounds that it’s violating his right to free speech.

This isn’t the only arrest across the country that’s related to resistance from data center projects. A Kansas teacher was arrested in July 2026 for lightly clapping at a meeting in support of a speaker after they finished speaking, although the town eventually dropped the charges against them. In fact, as of August 2026, at least 37 people have been arrested for protesting against data centers.

BT, the UK’s largest telecommunications provider, is slowly upgrading its entire network to fiber, with the company looking to move residential endpoints away from copper, and it seems that it will make a killing when it recycles its old cables. According to The Guardian, the company has signed a deal with EMR, one of the largest cable recycling companies in the country, for the recovery of around 200,000 tons of copper over a span of four years. Although the total value of the deal is unclear, the latter has also already paid more than USD 134 million (GBP 99 million) to the telecoms company for a few thousand tons of copper. Aside from the deal with EMR, BT and its subsidiary, Openreach, could also sell the recovered copper directly on the spot market.

More than 22,000 metric tons have already been recovered from the system since BT started its network upgrade, with the metal costing around USD 8,500 per metric ton on the market. If the company sold all that material in the open market, it would have made revenue of USD 187 million. However, the massive AI-driven demand for copper has pushed prices to a record high of more than USD 14,000 per metric ton. The upgrade work is expected to continue well into the 2030s, with Openreach estimating that it could still recover up to 200,000 metric tons of material. That means the company could make an estimated USD 2.7 to 2.8 billion just from the sale of these old network cables.

The AI boom is pushing up demand for several industries — from high-tech products like memory and storage chips and jet engines to “exotic” materials such as rare earth elements and glass cloth fibers. Most people will not equate copper to AI data centers, especially as the PCBs used in their servers often contain so little of the metal, relatively speaking. AI data centers are also switching to optical interconnects and silicon photonics, meaning the internal networks of these data centers will increasingly rely on fiber optics.

However, data centers are forecast to use 194 gigawatts of power by 2035, and all this power can only be transferred via metal cables. While you can also use aluminum wires to transmit power, copper is often the preferred choice for its stability, better electrical conductivity, increased durability, and superior thermal performance. So, as AI hyperscalers expand their operations and build more data centers, the demand for copper wires will also increase accordingly. Utility providers will also need to purchase more cables as they upgrade the grid to deliver the electricity needed by the AI infrastructure.

The AI-powered boom for copper material is a win-win situation for BT, Openreach, and their subscribers. The people will now get end-to-end fiber connections in their homes, hopefully giving them better speed and reliability, while the providers are basically getting a discount on the upgrades that they’re making on their networks.

Donald Trump doesn't appear to be a fan of the data center backlash that has swept the nation. Posting on his Truth Social platform, the President said that communities that reject data centers only do so because "they want to end up being backwards and poor," and posited that China "could not be happier with this anti Data Center movement." The comment comes amid a wide, albeit unorganized, pushback to data center buildouts in the United States that's left local communities and municipalities reckoning with an unanticipated and rapid infrastructure buildout.

Local pushback has been widespread and consistent across the country. Earlier this month, an Amazon data center came under fire for circumventing public feedback based on old laws. Since April, leaders across the nation have received an elevated number of credible death threats related to data centers since April. And last month, the number of local bans on data center developments crossed over 500 within the United States.

The President says to "let Data Reign" if communities "want to be successful and rich, with far lower taxes and jobs all over the place." Presumably, the President missed a comma after "taxes" and does not mean that data centers will lower the number of jobs available. The economic argument surrounding data centers is a tough issue to quantify, though it's not completely detached from reality.

A July study from Georgia Tech found that data center developments increase local employment by 3.5%, total wages by 5%, business establishments by 4.7%, and median household income by 1.9%. Further, the developments reduce unemployment rates. Critically, however, the study found that these benefits mainly show up in metropolitan areas, calling the benefits in rural areas "negligible." The study also highlights that data centers often employ fewer than 100 permanent workers, with specialized services "imported from outside the country."

The research also looked into trade-offs with electricity prices, finding that prices rise an average of 5% after a data center is built in a community.

In another analysis, Brookings found that, although new data center construction creates jobs, the number is somewhere between 100 and 200 permanent positions. Additionally, it found that areas with data centers see average home prices rising between 2% and 5% without any impact on wages.

Early attempts at studying the effects of data centers on local communities have, on one hand, substantiated the claims that data centers bring economic activity. On the other, they suggest that economic activity is smaller than expected, localized to the area in question, and comes with unintended side effects like higher electricity prices. There's also an environmental concern, one that is difficult to study in the midst of buildouts.

Instead of outright banning data centers, local governments and increasingly state governments have paused development to study the impact. In July, New York Governor Cathy Hochul signed a one-year moratorium on data center construction to study the economic and environmental impacts. In early August, Texas Governor Greg Abbott directed state agencies to cut data centers off from connecting to the Texas power grid until an audit of the facility's power and water usage is completed. Republican Governor Mike DeWine of Ohio has made similar directives.

At a national level, the Artificial Intelligence Data Center Moratorium Act, sponsored by Representative Alexandria Ocasio-Cortez, proposes a pause on data center construction and new AI products until the government can review both the environmental impacts of new data center construction, as well as the impacts on jobs for new AI products. The bill has been introduced, though it has yet to be debated in committee or voted on in the House.

A team of scientists in Germany and Japan has demonstrated a solid-state cooling system that uses heat to generate the mechanical work required for refrigeration, potentially opening a route to processors and data centers that recycle some of their own waste heat for cooling. Developed by researchers at the Karlsruhe Institute of Technology (KIT) and the University of Tsukuba, the system — detailed in Nature Energy on August 28 — replaces the electrically powered actuator normally required for elastocaloric cooling with a heat-responsive shape-memory alloy, allowing the cooling cycle to run from an external heat source rather than a motor.

The prototype combines two ultra-thin metal films that serve as an actuator and a refrigerant. A 22-micrometer titanium-nickel (TiNi) shape-memory film contracts when heated, converting thermal energy into mechanical motion. This motion stretches and releases a 26.5-micrometer titanium-nickel-iron (TiNiFe) refrigerant film, triggering a reversible phase transition that produces cooling. In laboratory tests, Joule heating the actuator to 86°C produced a 12.9 K temperature span across the refrigerant film — the difference between its hottest and coldest states during the cooling cycle — and a 4.0 K span across the assembled cooling device, measured between its hot and cold sides. When the researchers replaced the resistance heating with an external 130°C heat source, the prototype still maintained a 2.2 K device-level temperature span, demonstrating that an external thermal source could drive the cooling mechanism.

Conventional refrigeration and air conditioning systems mostly use vapor-compression cooling. A compressor raises the pressure and temperature of a refrigerant, which then dumps heat in a condenser before expanding and evaporating at low pressure to absorb heat from the space being cooled. The technology is mature and efficient, but requires an electrically driven compressor and relies on refrigerants with significant global warming potential.

Solid-state cooling moves heat without the conventional compressor-and-refrigerant loop. Thermoelectric coolers, for example, use electrical current to create a temperature difference across semiconductor materials and are already common in compact electronics. However, the researchers note that thermoelectric devices typically reach only 10% to 15% of the theoretical reversed-Carnot efficiency limit, roughly one-quarter that of modern vapor-compression systems.

Elastocaloric cooling takes a different route. Certain shape-memory alloys change crystal structure when mechanically loaded and unloaded. Applying stress induces a phase transition that releases latent heat and warms the material. Once that heat is rejected, releasing the load reverses the transition, causing the material to absorb heat and cool. The solid alloy effectively becomes the refrigerant.

The problem is that the material still has to be repeatedly stretched and released. Existing elastocaloric systems generally use motors, hydraulic systems, or electromechanical actuators to provide the required force, adding electrical consumption, bulk, and mechanical complexity — particularly troublesome for miniature coolers. Instead, the KIT-Tsukuba team made one shape-memory alloy drive another. Heating the TiNi actuator film causes it to recover its original shape and contract. Mechanically coupled to the TiNiFe refrigerant film, that contraction supplies the force required for the cooling cycle. As the actuator heats and cools, it loads and unloads the refrigerant without an electric motor.

Broken down further, the system works as follows: the researchers take a shape-memory alloy (TiNiFe refrigerant film) that cools when released after being stretched. Instead of using a mechanical system to repeatedly stretch and release that alloy, they use another shape-memory alloy (TiNi) that contracts when heated and mechanically couple it to its cooling counterpart. When the TiNi is heated, it contracts, stretching and “loading” the refrigerant film. Once the heat is removed, the TiNi relaxes, releasing the film and triggering the phase transition that causes it to cool. Under cyclic heating, the TiNi alloy therefore provides the repeated stretching and releasing motion the TiNiFe requires for elastocaloric cooling.

The thermal actuator delivered a force-to-displacement ratio of 14.5 N/mm, compared with 1.1 N/mm for a commercial electromechanical actuator the researchers used as a reference. The thin films also provide a high surface-to-volume ratio for rapid heat transfer. Under Joule-heated actuation, the integrated device reached a steady 4.0 K temperature span after 20 cycles and a specific cooling power of 4.43 W/g. When driven from the external heat source, those figures fell to 2.2 K and 3.32 W/g, respectively.

This external-heat result is the real proof of concept. While the technology is still an early-stage laboratory experiment, a scaled, perfected version could have interesting implications. Typically, the heat the system needs to operate is generated from electricity or another form of energy. However, an ideal scenario would be to repurpose existing waste heat — a setup already attainable in data centers. Therefore, the technology has the potential to cool processors using the heat they generate!

However, applying it as a data center cooling technology is far from the technology's current state. The prototype produced just 2.09 milliwatts of cooling power at zero temperature lift. That is nowhere near the heat loads of modern processors, much less AI accelerators or data-center racks. The researchers also cite relatively slow actuation, limited strain rate, and the current heat-exchanger geometry among the factors constraining performance. There also needs to be a way to make the heating cyclical.

The team is now working to connect multiple films in parallel to increase cooling capacity. Further progress will require scaling the active material, improving heat transfer and operating frequency, and proving long-term durability. For now, the researchers have demonstrated the underlying energy chain in which heat can be converted into mechanical motion, and that motion can be turned into useful cooling without an electric motor driving the refrigeration cycle.

The DataOne data center in Vineland, New Jersey, has faced a slew of complaints from the community since construction began in 2025. According to Stand.earth, the project has reportedly been operating several unpermitted gas turbines on site, spewing air pollution in the area near two local schools. Aside from that, the site has also faced allegations of constructing an unpermitted 1.5-million-gallon liquefied natural gas storage tank and of unacceptable noise levels at night, which affected residents within a half-mile radius of the data center.

Matt Williams, chairperson of the Sustain South Jersey group, told Tom’s Hardware that construction had already begun even before Nebius signed a multi-year agreement to “deliver dedicated capacity to Microsoft from its new data center in Vineland, New Jersey,” in October 2025. However, the residents only became aware that the project was a data center after the $19.4 billion deal to secure around 100,000 Nvidia GB300 GPUs for the tech giant was made public.

Vineland residents began seeing references to the data center in various government documents, prompting several questions to the city government. Because of this, the city called a town hall meeting last January 2026 — several months after construction on the data center had already begun, with DataOne CEO Charles-Antoine Beyney admitting that the meeting should have been initiated several months before.

A few weeks before the town hall, some people living within a half-mile radius of the site started complaining about noise from the development. While they couldn’t confirm the source of the noise, it was often described as a low hum, similar to that of a generator. A later investigation revealed that the site had 62 gas turbines deployed in the area, with at least 45 running at any given time. This is similar to what SpaceXAI has done in Memphis, Tennessee, where it deployed 69 unpermitted natural gas turbines to power its data centers. While the company has since promised to remove these polluting generators, it will do so only over a span of one year, as they’re being slowly replaced by a 1.2-GW on-site power plant.

There have also been concerns that the site’s stormwater management system does not comply with the state’s regulations. A third-party engineering review stated that if these issues are not fixed, they could result in on-site and off-site flooding, especially given the site’s massive 55-acre size. The experts also noted that the data center has “underestimated the annual groundwater recharge by at least 20 million gallons per year,” which could result in lower aquifer levels and reduce the amount of water available or the water quality for the people living in the area.

“The incident should shatter the illusion that Microsoft is a ‘good neighbor’ or in any way more responsible than the other Big Tech companies,” Stand.earth Senior Campaigner Nathan Taft said in the statement. “This investigation has revealed that far from ‘doing this work differently than other’ as it promised, Microsoft is drawing directly from Elon Musk’s xAI playbook of doing the damage first and asking for permission later.”

In an interview with Tom’s Hardware, Nathan said that even though Microsoft does not directly own or operate the Vineland data center, it stands to reason that the tech giant should do something about all these complaints, as it’s the one that has contracted Nebius for the computing power, which resulted in DataOne’s construction project. He compared this to a contractor making a mess on their client’s neighbor’s property. Even though a third-party provider — DataOne — was at fault for the issue, the fact that the people have already been complaining should give Nebius pause and compel Microsoft to do something.

DataOne’s actions in New Jersey directly contradict the promise Microsoft made back in January 2026, and residents are asking the tech giant to stand by its word. Although the concerns about air and noise pollution are technically not mentioned in the company’s “community-friendly” commitments, these issues still impact the quality of life of the people living around the DataOne data center. Aside from that, the unpermitted construction shows it does not adhere to the rules of Vineland. “The developers have been ‘act first, pay the fine, and ask for forgiveness later,’” says Mr. Williams.

X’s Global Government Affairs team posted on its account that it identified a 200,000-strong bot farm operating on the platform, with 200 of them posting information designed to influence public perception. According to the team, the accounts are suspected to have been created by Chinese operators, and that they’re using the accounts to amplify the negative impacts of AI data centers, especially on electricity prices.

“We identified a bot farm of approximately 200,000 accounts. Within this farm, we found 200 accounts posting in a manner that could manipulate a legitimate debate about American AI and energy policy,” the team said in its post on the platform. “These posts contained claims that AI data centers are driving up household electricity prices and straining the grid. Others included AI-generated cartoons that depicted data-center operators enriching themselves at the public's expense.”

Some of the accounts shared by the team show names like Thomas Jackson, Patricia Robinson, Sandra Thompson, and Kenneth Flores, making it seem like they’re owned by Americans, and they’re sharing news stories from legitimate sources like The Southern Maryland Chronicle.

For example, some of their posts share the story of how PJM Interconnection hiked its prices by 76% due to AI data center demand. However, they add commentary, and sometimes even include AI-generated images designed to inflame the emotions of someone just scrolling through their feed. One narrative they’re pushing is that the costs of putting up data centers are being borne by ordinary people as big tech companies enrich themselves.

It’s unclear who sponsored or sanctioned the China-linked accounts on X, but there have been reports of China-linked operations designed to divide U.S. opinion on AI. However, the resistance against data centers isn’t all driven by Chinese propaganda, as billionaire investor Kevin O’Leary once claimed. In fact, a recent poll suggested that the biggest driver of data center protests is based on “object-level” local environmental and economic harms, especially as many other projects have shown the negative impacts they had on the community.

The concerns that many residents have about data center developments in their area are indeed valid and true, but so is the threat of foreign intervention in domestic American politics. This is no surprise, though, as nation-states have always used propaganda and information to advance their own interests. The internet, social media, and artificial intelligence have made this easier in recent years, though, so both platforms and people need to be more vigilant than ever.

Indiana Michigan Power, or I&M, which serves over half a million residential customers across the two states, said that it’s planning to cut rates for residential customers in Indiana. According to the company, it’s planning “one of the nation’s largest base rate reduction plans,” with the total bill reduction saving Hoosiers approximately $59 million in electric bills by 2027. This translates to about $100 per year for each home that uses around 1,000 kWh monthly. Aside from that, I&M wants to freeze rates for the next three years, offering its customers a measure of stability as data centers are forecasted to use 20% of U.S. power by 2035.

The plan is still under consideration by the Indiana Utility Regulatory Commission (IURC), with a decision expected by June 2027, with residents seeing savings by the summer of that year. This also isn’t the first time the state has seen electricity rate cuts in recent months. I&M has already reduced its rates twice in the first half of 2026, offering some users much-needed relief from rising electricity costs brought about by the massive demand from AI data centers.

PJM Interconnection, which operates the grid that I&M uses, has implemented “irreversible” price hikes of up to 76%, but it seems that I&M was able to isolate ratepayers from increased prices. It achieved this through load growth, allowing it to recoup its capital investments on grid upgrades more quickly, and the increased revenue brought by the massive consumption of large customers like data centers.

“As Indiana continues to experience unprecedented growth, we are taking action to help our customers benefit from that growth through lower costs, enhanced value and continued investments to strengthen our system,” said I&M president and chief operating officer Maryam S. Brown. “We are proud to join forces with state leaders to advance economic development and make energy more affordable – while continuing to provide system reliability upgrades.”

Indiana isn’t the first state to see reduced rates driven by increased rates or usage by larger customers. Oregon approved a 1.3% reduction in residential electricity prices in early July, as customers that used up 20 MW or more saw a 30% increase in their utility bills. Virginia, which plays host to a ton of data centers, is now following suit, with its regulators requiring firms to pay for dedicated upstream electrical infrastructure being built to serve their needs.

Moves like this should allow some Americans to see their bills go down a little bit and address one of the major concerns that they raise whenever a data center project is proposed in their neighborhood. However, several other issues like water supply impact and noise pollution must also be resolved to reduce the community’s resistance to these developments.

Researchers from the University of Mary Washington in Virginia found that of the 31 localities with an existing, approved, or proposed data center, 25 of them have non-disclosure agreements (NDAs) that make it difficult, if not impossible, for their citizens to find information about these projects. According to NPR, these NDAs have left the questions of many residents unanswered, making them feel left out of the decision process and increasing their distrust of their leaders.

Many officials defended signing these secrecy agreements, saying that this is standard practice among tech companies, and that they could lose the potential business and revenue that data center projects could bring to their jurisdiction if they fail to sign the NDA. Louisiana Economic Development Secretary Susan Bourgeois even told the publications that NDAs are “fundamental for economic development” as they allow the state to compete with other states and territories for the data centers’ business. “The last thing that they want to have happened in the beginning of the discussion, or in any part of the discussion, is for their information that they’re sharing to be disclosed publicly. So, without NDAs, our work, frankly, just doesn’t happen,” the agency secretary said to NPR. She also added, “The irony is that we, we use NDAs not to be more cloaked, we use NDAs to be more forthcoming.”

NDAs aren’t only limited to Louisiana, as other towns across the U.S. have signed these secrecy agreements even before they started talks with potential data center projects in their regions. Some Wisconsin citizens raised a similar issue in early 2026, when at least four municipalities reportedly signed NDAs with Microsoft and Meta as they negotiated with the two companies. These confidentiality agreements are some of the things that drive the heated debate between elected officials and ordinary citizens, with the latter often feeling betrayed and sold out by the former when they belatedly find out that a data center will be put up in their community.

However, West Feliciana Parish proved that it could get a data center deal without keeping its details top secret. Parish President Kenny Havard said that economic development does not require NDAs. “I don’t think NDAs are necessary unless they’re going to bring you in a room and share some proprietary information. When you’re talking about land sales, tax incentives, those sorts of things that affect the citizens, it should be out in the open. It should be transparent,” Havard told the outlet. He also said, “We’re proud that we did it without having to sign NDAs. And I think it just shows that you can do these projects without keeping the people in the dark.”

Data centers are unpopular among U.S. citizens right now, with projects facing resistance and moratoriums across the nation. While we’ve seen over a hundred protests against the developments happen simultaneously, researcher Andy Masley wanted to answer one question: what is driving the pushback against these projects? Is it big tech? AI skepticism? Or maybe even China? But after reviewing data from multiple polls, his answer seems quite simple: the “object-level local environmental and economic harms” that have been widely reported in the media.

Multiple data center sites owned and operated by different hyperscalers have found themselves in hot water with the people surrounding them. The biggest issue that caught the attention of the public is the massive amounts of electricity that these developments use, requiring grid operators like PJM Interconnection to expand their infrastructure to service AI data center needs, which costs billions of dollars. Unfortunately, the capital expenditure for these upgrades has typically been passed on equally to all users, with ratepayers seeing price hikes of up to 76% on their utility bills.

It has gotten to the point that President Donald Trump had to make tech giants, AI hyperscalers, utility operators, and state governors sign a “ratepayer protection pledge” so that AI companies “pay their own way” when it comes to their electricity needs. But this move was too little, too late to halt increased electricity costs to the huge swathe of the American population that PJM Interconnection serves. Oregon is the only state, so far, to have passed a law that requires sites using 20MW or more to pay for their own share, with PGE, the state’s largest power provider, hiking data center bills by 30% while also cutting residential costs by 1.3%.

There have also been reports of two data centers in Georgia and another in Wyoming causing water issues in the surrounding neighborhoods. This includes low water pressure due to excessive consumption, a drop in quality with muddy water pouring out of taps, and water discharges that contaminated a city’s reclamation water supply. Aside from those, there are also problems with noise pollution, like the site that generates noise 24/7, as if “someone set up a vacuum, like in your living room,” and air pollution from mobile turbine generators and dedicated natural gas power plants.

All of these are “object-level” concerns, meaning these are specific issues that exist, have happened on other sites, and are directly observable by other people. However, Masley also points out that some of the coverage of these issues was either overblown or only showed the concerns of the residents, without putting them into the context of the actual project and comparing them with other existing data centers in other areas. Because of this, many people have become fearful that the issues found in other developments will automatically apply to the data center being proposed in their community.

Some data center developers also aren't helping to assuage fears. Some are pushing back against moratoriums and bans, and have begun suing local jurisdictions. One town in Pennsylvania listed 43 specific demands that the developer called “too difficult” and pulled out of negotiations before applying again, with the council calling the move an attempt at “approval by tantrum.”

Lux Claridge, the teacher who was arrested in Emporia, Kansas, during an AI data center meeting for clapping, said that the city has dropped the charges against them. According to 404 Media, the Emporia assistant city attorney told Claridge’s lawyer that the case has been dismissed without prejudice in municipal court because of conflicts on the matter. Unfortunately, that doesn’t mean that they’re in the clear yet, as the case has been bumped to the County Attorney’s office for further review.

“Today, I was informed by my attorney that the city has dropped my charges and has passed my information along to the county,” Claridge told the publication. “As far as I know, I’m in the clear unless the county is feeling froggy.” This series of unfortunate events started when the teacher politely clapped five times after a speaker gave their comments against the proposed data center in the city. It seems that the city’s commissioners had warned against clapping and other reactions beforehand, saying that it was disruptive. So, when they clapped, someone from the crowd, presumably someone with authority, asked a police officer to take the next person who claps outside of the venue.

This was when several cops approached Claridge, who asked them to leave, but they stood firm, saying, “I have a right to speak.” When the authorities insisted that they go, they just said, “Drag me out,” after which the four officers cuffed the individual, physically lifted them, and hauled them off to the Lyon County Jail. They were finally let out after eight hours, after which they were charged with disorderly conduct and interfering with a law enforcement officer.

After this incident, the city canceled the public meetings set for August 5 and August 19, 2026, and moved them online. The city said that commissioners were receiving death threats from external sources and that it’s taking the measure to protect the safety of its officials and the public. However, it also didn’t allow public comments, which some are questioning, although it did tell citizens that they can phone in their concerns instead. Nevertheless, the city will return to in-person meetings soon, and it will also open public comments once more, with Claridge quoting Emporia mayor Becky Smith saying that she’s “willing to give us another shot to act like grown-ups.” Emporia is expected to put the data center ban to a vote in November via public ballot. However, it also said that even if the people approve the proposed ordinance, it can only take effect after it has been ruled that the petition is deemed legal in the first place.

Nvidia has spent the last several months providing key disclosures about its next-gen Vera CPU for agentic data centers, which it continued at Hot Chips 2026. Although we've already learned a lot about Vera, how it compares to AMD's next-gen Venice CPUs, and the inner workings of the Olympus core, Nvidia provided a bit more color at Hot Chips on spatial multithreading, the memory subsystem, and what types of workloads it's targeting with Vera.

As a quick refresher, Vera is the first CPU with a custom Nvidia core, following up on Grace, which used a stock Arm design. It's shipping as a single, 88-core SKU, and it has some key design differences compared to Nvidia's x86 competition, most notably a multi-threading implementation that Nvidia calls spatial multi-threading, an LPDDR5X memory subsystem, and a monolithic compute die rather than using compute chiplets.

Nvidia says it's designed Vera specifically for agentic AI workloads, a category that's still being defined in terms of performance benchmarking. Many CPU-intensive tasks serve as proxies for agentic workloads (i.e., code compilation), though measuring performance across a full agentic chain is complex and inconsistent. Nvidia, in its own slides (see the end of this article), calls agentic AI the "most complex computing workload in history," after all.

Nvidia provided an example of a headless browser to show the benefits of Vera, using optimized code to mimic how an agent would use a browser. Compared to the 96-core EPYC 9655P, Nvidia says Vera runs 24% faster as browser instances scale.

This slide is a good demonstration of the complexities in measuring traditional workloads and applying that performance to agentic workflows. Agents will often fetch websites for information, but there are several layers where agents can trim back compared to humans; in this case, agents can run through a browsing workflow 4.5x faster by cutting things like GUI rendering, fonts, media decoding, and more.

Another touchstone for agentic performance is code compilation, as agents seek out software to compile on the system. This might be the most direct benchmark of agentic AI performance with current workflows right now. Though, as previously mentioned, agentic chains are long, complex, and involve several different workloads.

Once again, compared to the 96-core EPYC 9655P, Nvidia claims Vera can compile the Linux kernel 22% faster with a native AArch64 target, and 14% faster when cross-compiling for x86.

Nvidia's big cores for agentic AI — another look at Olympus and how it fits into Vera

Nvidia reiterated the importance of the large cores inside Vera, including the large BPU, neural branch predictor, and 10-wide decode. Nvidia has previously disclosed the Olympus core architecture, which you can read about in our Vera deep dive. Broadly speaking, however, it's a wide core optimized for high single-core throughput.

One of the more interesting design points of Vera is spatial multi-threading, which Nvidia described in more detail during its Hot Chips 2026. In short, Nvidia separates core resources on two pipelines, though data and cache can move between threads as needed. To demonstrate the benefit, Nvidia shared the results from SPEC CPU 2017 intrate that you can see below.

This shows the "noisy neighbor" effect. Nvidia measured single-core performance and then measured the same workload with another thread active. Nvidia's data shows that Vera is less concerned with the neighboring thread, whereas a "traditional CPU" sees a larger slowdown. Nvidia didn't clarify which CPU it's comparing Vera to here, however.

Nvidia's slide does a good job illustrating, but it's worth noting the difference compared to traditional SMT nonetheless. With traditional SMT, resources are time-sliced between threads, leading to gaps between BP and decode, as illustrated in the slide. With spatial multithreading in Vera, threads are still fighting for resources within the core. However, spatial multithreading allows Nvidia to deal with the demand of neighboring threads in a deterministic way, leading to a more consistent downturn in per-core performance when the second thread is working.

Nvidia's second-gen Scalable Coherency Fabric (SCF) moves data across the die. Nvidia didn't provide any new disclosures around SCF at Hot Chips, but you can see how the fabric is laid out in the slide below. Centralized Coherency Switch Nodes (CSNs) connect the cores to pools of L3 cache totaling 164 MB and the broader memory subsystem.

At a system level, one of the more interesting choices Nvidia made was to use LPDDR5X as opposed to traditional RDIMMs, a choice that it was only able to make due to the serviceable SOCAMM2 design. Nvidia includes eight SOCAMM2 slots per Vera CPU on a board, offering up to 1.5 TB of capacity with 1.2 TB/s of bandwidth.

LPDDR5X can deliver transfer rates higher than DDR5 RDIMMs, at least compared to single-rank DIMMs. However, it seems the driving force behind LPDDR5X wasn't performance but rather power consumption. One of the pillars of Vera, according to Nvidia's Hot Chips presentation, was to deliver a CPU for power-limited data centers. Micron says its LPDDR5X consumes about a third of the power compared to a traditional RDIMM.

Nvidia demonstrated that point a little differently, using bandwidth per watt as a point of comparison between the LPDDR5X system in Vera and traditional RDIMMs. This illustration does the job, though it could be a bit misleading, measuring power draw against peak bandwidth.

Nvidia tells us that a fully loaded memory system with Vera consumes between 30W and 40W, with 1.5 TB at 9600 MT/s. Power demands for RDIMMs vary wildly depending on capacity, channels, and transfer rate, though power consumption can easily climb over 100W depending on the configuration.

Although Nvidia has deployed Grace in the data center — to the tune of "hundreds of thousands" of standalone servers, apparently — Vera represents Nvidia's first big push to gobble up market share in the expanding agentic CPU market. It's highly targeted, as evidenced by the fact that Nvidia is only delivering a single 88-core SKU, and it's already being put to use in large-scale deployments, with Nvidia announcing yesterday a deployment of Vera at SpaceXAI.

Nvidia has shared the slide above before, which it once again showed at Hot Chips 2026. It's normalizing per-core performance in SPEC CPU 2026 against the AMD EPYC 9755. The core differences explain the big disparity in numbers; in reality, Vera led in overall score by 3%. Regardless, this is the slide Nvidia is using to pitch Vera, claiming it offers a big improvement in the workloads that are most relevant for agentic AI.

The most formidable opponent for Vera isn't Turin, however. It's Venice, which AMD launched in June, and Diamond Rapids, which Intel detailed just moments after Nvidia left the stage. Vera has a lot of interesting talking points already, but it'll be interesting to watch how Nvidia scales (or doesn't scale) its data center CPU business over the next few generations. Perhaps we'll see the firm double down on these agentic workflows, or maybe concessions and product segmentation to appeal to hyperscalers. Time will tell.

Full Nvidia Vera Hot Chips 2026 presentation

Officials in Marshall, Michigan, did what data center opponents across the country have been demanding: on August 3, its city council passed a one-year moratorium on new builds. Ten days later, police told council members they were the subject of a credible death threat tied to the project. The same week, the 300-person town of Salix, Iowa, postponed its own moratorium vote after Facebook posts put its government "in the crosshairs," and in Box Elder County, Utah, a commissioner who approved a project told KSL he has police stationed outside his house. Then, on August 21, NBC News reported that city leaders nationwide are now receiving death threats over data centers, regardless of which way officials vote.

Marshall Mayor Scott Wolfersberger told local news station WWMT that the city's police department contacted him on August 12 about the threat and that the investigation is ongoing. Councilor James Hackworth wrote in a social media post that members had received "a legitimate death threat" and that disagreement, protest, and voting the council out are all part of democracy. It's unclear whether the sender supports or opposes data centers, and no suspect has been identified to date.

Meanwhile, Salix Mayor Kevin Nelson has said that the Woodbury County Sheriff's Office is investigating posts that called for "various death and terroristic type things" against the entire city government. Nelson said threats first came in May, after the town annexed 900 acres of farmland in April for a site Google is evaluating.

Woodbury County is separately challenging the annexation in court. The council met a week late on August 20 and voted 3-2 against the moratorium, with Nelson calling officers into the room as members of the public and councilman Gene Monk objected. "We ask for a cool-down period for a year to research, then we can make an educated decision. We can let the people vote for it after that — do something different," Monk said. "It's too big of a decision for us five people [council members]."

Over in Box Elder County, Utah, Commissioner Lee Perry has said that he and fellow Commissioners Boyd Bingham and Tyler Vincent had received threats after voting through two resolutions for the Stratos project area, with an audience of roughly 500 chanting "shame" at the meeting.

Previous incidents show these are more than idle threats. In April, Indianapolis councilman Ron Gibson had 13 rounds fired into his home after backing a rezoning, and Saline Township, Michigan, treasurer Jennifer Zink resigned in May citing threats over the 1.4GW Oracle and OpenAI campus that triggered moratoriums in at least 19 Michigan municipalities. Emporia, Kansas, moved its August 5 and August 19 commission meetings online and dropped public comment after its leaders were threatened.

Recent data published in the Soufan Center's July IntelBrief, which is based on a year of scraping X and Reddit, found hundreds of posts with threat language between July 2025 and July 2026, and a volume surge beginning in April that hasn't receded. Most violent threats in its dataset are targeted towards infrastructure rather than people, with posts naming council members and planning commissions a small minority. Many use memes, emojis, and misspellings to dodge moderation.

The center also found that each new incident now draws far more secondary amplification than it did earlier in the year. Emporia's mayor said the threats to his commission didn't appear to come from locals, and Salix, Emporia, and Marshall have all now canceled, moved, or restricted public meetings because of them, at a point when more than 500 local restrictions on data centers are in place nationwide.

Five months after the arrest of Supermicro co-founder Yih-Shyan “Wally” Liaw and two other co-conspirators for the alleged smuggling of Nvidia hardware into China, the company announced that it has completed its independent investigation and released its findings to the public, resulting in the termination of several employees. Supermicro said that the investigation, which was handled by an external law firm and conducted by an “independent forensic accounting consultant,” finds that neither the company nor its current senior executives were part of the alleged AI chip smuggling. It also said that it’s adopting all the recommendations to enhance its export compliance programs, although it did not directly admit that it was lacking in that department.

“The investigation team reviewed the customer transactions that were the subject of the federal indictment, as well as transactions with a selection of other customers who bought restricted products, and did not find any evidence that any current member of senior management had knowledge of the alleged diversion scheme or of any actual diversion of restricted products by the Company,” Supermicro said in the statement. It also added, “The Company’s compliance personnel have acted in good faith, with the support of management, to mitigate the risk of the Company’s products subject to export controls being diverted to restricted parties or locations.”

This odyssey began in March when the U.S. charged Liaw alongside Supermicro sales manager Ruei-Tsang “Steven” Chang and third-party broker Ting-Wei “Willy” Sun with conspiracy to unlawfully divert cutting-edge U.S. artificial intelligence technology to China. The accused aren’t operating a small-time smuggling operation, either — reports estimate that the three have smuggled hardware worth $2.5 billion since 2024. That massive amount has got shareholders worried that a huge chunk of the company’s sales come from illicit sales, resulting in some investors suing the company for securities fraud. Because of this, the company’s independent advisors also looked into this issue and said that it “did not find any evidence that the Company’s previously issued financial statements could not be relied upon based on the potential diversion of restricted products.”

Even though the third-party investigation exonerated Supermicro’s senior executives, it also resulted in the termination of several employees. The affected people were from the sales, technical support, and business development departments, although they were fired for breaking the company’s policies and code of conduct — the company said these moves were made "in connection with the investigation." Notably, none of the personnel were from its compliance department, and it’s also unclear how many people were dismissed.

Supermicro also said that it’s enhancing its export compliance program, which Nvidia CEO Jensen Huang said it must fix. Even though the company was never accused of wrongdoing and wasn’t part of the defendants in the case against the alleged smugglers, the fact that some of its employees were able to run a massive diversion scheme right within the organization raises major questions about the effectiveness of its compliance department. It said that it has already made changes that were recommended by its General Counsel and Chief Compliance Officer even before the third-party investigation concluded, and that its independent directors “will oversee implementation of the remaining recommendations.”

The high demand for AI chips in China has meant the smuggling operations are quite lucrative, even as the U.S. is tightening its grip on export controls and Chinese authorities are commanding that its tech companies prioritize locally made Chinese chips instead of American AI GPUs. Nevertheless, the race to build ever more powerful AI models means that there is such a massive demand for the most advanced AI GPUs from Nvidia that some people are looking for ways to circumvent these bans and make “easy” money.

Loudon County, Virginia, located just 22 miles west of Washington, D.C., has the greatest concentration of data centers in the United States. According to The New York Times, after years of booming data center construction that has brought lots of benefits to the local region, the county is beginning to rein in data center construction in response to local residents' complaints.

It all started when a federal government demand led to the installation of fiber internet lines in the area, owing to its proximity to Washington, D.C. This grew even more during the dot-com craze of the late ‘90s, when many companies built a ton of fiber connections in the region. This made it ideal for building early data centers in the area, with AOL moving its headquarters in the region in 1996. By the year 2000, the county voted to categorize data centers as office parks, meaning companies can build these structures with little oversight and approvals.

This incentivized tech giants to build data centers in the area; by 2007, there were already 29 such facilities in Loudoun, with the number growing almost ten-fold nearly 20 years later. Interestingly, it seemed that the negative impacts of these projects in the area were little to none. In fact, the people of Loudoun appreciated them, as they brought in a lot of money for the county. Data centers brought in a $150 million income in 2015, but this number has grown to $1.1 billion in 2025. This cash windfall allowed Loudoun to cut property taxes to just $0.805 per $100 of assessed value — that’s less than 0.8%, making it among the lowest in the United States, especially for a suburban area.

Aside from that, the tax windfall from data centers allowed the county to fund more schools, with two new ones opened in the area, plus another one under construction, build a $102 million recreation center that has multiple pools and hydro massage chairs, plus spend $22 million converting a former presidential estate into a public park. This also allowed the county to expand its fire and emergency services, and ensure that its roads, bridges, and tolls are in excellent shape. Because of this, many residents support data centers in the region; in a July town hall meeting discussing it, some people attended wearing shirts that said: “I Support Data Centers Because I Like: Lower Taxes, Excellent Schools, Better Job Opportunities, and More.”

This is a stark contrast to what the rest of the country is seeing when it comes to data centers. New developments have raised various issues nationwide, from electricity price hikes up to 76% in the biggest power region of the U.S. and excessive water consumption that caused low water pressures for neighboring communities to 24/7 noise pollution that basically made the area unlivable and allegations of air pollution brought about by unpermitted gas turbines needed to power the data center. It’s for these reasons that many people are protesting the development of these projects in their communities, and several counties and states have passed data center moratoriums.

Despite widespread support for data centers in Loudoun, people are starting to push back against more recent developments. Loudoun Board of Supervisors member Juli Briskman, who is among the people in charge of its land, zoning, and economic policies, said, “It’s gone way too far. We’ve become addicted to the data centers for their tax revenues, but at what cost?” Some residents have also started complaining about data center developments in their vicinity. A Vantage data center, which has started operations recently, was the center of a noise complaint because of its diesel and gas turbine generators, while another resident in nearby Ashburn is raising an issue about Dominion Energy planning to put up a 185-foot-tall high-voltage electricity transmission tower in her backyard. There have also been reports that another tech company is buying over 100 homes in a luxury community for $4 million apiece, which is double their current market value.

Because of these issues, Loudoun ended its policy of zoning data centers as office parks, meaning anyone who wants to build a project in the area must now go through an approvals process from the public. This will make it significantly slower to get projects like these off the ground, and there’s also no guarantee of approval. Just last month, Amazon applied to build four more data centers in the region, and some board members have already signaled that they will reject the project.

When done right, data centers can bring economic prosperity for the community that they are in, which is exactly what Loudoun County was able to achieve. After all, data centers aren’t just about AI — they’re also used to serve the digital economy and keep the internet running, so that online services like Facebook, Instagram, Netflix, Spotify, Google Maps, Uber, and more can operate smoothly at scale. However, the massive processing power demanded by artificial intelligence workloads means that data centers serving its needs use up tons more power and water, which can make living near one untenable for most residents unless the local government takes steps to protect their interests.

Beijing has been encouraging its tech giants to build data centers across the country as the central government believes that computing power, especially in the age of AI, correlates to national power. Because of this, many Chinese companies like Huawei and Tencent have been actively building AI infrastructure in rural provinces, like Guizhou province, which is located more than 500 miles to the northwest of Shenzhen. According to Tech Xplore, dozens of these facilities have been constructed in the area in recent years, with more on the way.

Unlike the U.S., where data centers face increasingly tough opposition, these build-outs are seemingly approved with relative ease, and the people living around them apparently appreciate the changes that the data centers and related infrastructure brought to the area. “It used to be a barren mountain, but since the area has developed, transportation has become more convenient, trade has picked up, business opportunities have emerged,” one shopkeeper told the publication. Another local, Li Xixiu, praised the development of the main road as tech companies entered the area, saying that it “boosted the economy of the area,” and that there have been more local opportunities since then. “All the villagers in our neighborhood now find jobs nearby, unlike before, when they had to go to other places,” said Li. Still, it must be noted that Beijing places tight control on objections and protests, and that ordinary people cannot just object to policies set by the central government.

One of the reasons behind American opposition to data centers is the egregious electricity price increases they’ve brought on the average user. The PJM Interconnection region, the biggest power region in the United States, has seen a massive 76% increase in electrical costs because of the burden that data centers have put on the grid. Aside from that, it’s estimated that 20% of power generated in the U.S., amounting to 194GW, will be allocated to data centers by 2035. By comparison, analysts say China has a massive advantage in power generation, with several western Chinese provinces offering steep discounts on their electricity bills for AI companies that use Chinese chips. Furthermore, because the state subsidizes the power costs of residential and agricultural users, the average citizen does not worry that a nearby data center would cause their utility costs to increase.

These rural provinces also have large swaths of land allocated for renewable energy production, with energy overproduction becoming a problem for some operators. So, the construction of these power-hungry buildings actually helps solve the problem by using up surplus power instead of letting it go to waste. The availability of land and power in these western provinces makes it more attractive and affordable to put up data centers, compared to areas east of the country which are largely built up and have higher population concentrations.

Still, this development is not without issue. The Research Institute for Democracy, Society, and Emerging Technology (DSET) in Taiwan said in an email to AFP that while Guizhou has seen an average GDP growth of 7.4% over the past 10 years, wages didn’t increase as much and lagged behind much of the rest of the nation. “This contrast suggests that while data centers drive heavy investment in land and equipment, their impact on boosting local per capita income remains limited,” DSET researchers Cartus Bo-Xiang You and Angela Glowacki wrote.

Data centers have become a hot topic uniting Americans recently, with over 70% opposing the building of this infrastructure near their homes. So, Liquid Death and Garage Beer have banded together to create a viral ad asking viewers to drink their products, create pee, and then send it to the AI data center of their choice. According to Marketing Dive, the concept started with Liquid Death’s creative team, with comedian Sabrina Jalees coming up with the data center idea. It was repurposed into this ad, featuring NFL star Jason Kelce, who co-owns Garage Beer, showing the two brands teaming up together to promote their products and asking people to pee on computers "to save humanity."

“We have a lot of affinity for what those guys are doing: they’re doing comedy, and they’re also an indie trying to break into the mainstream. We’re positioning our energy drink as a light beer of energy — it’s fewer calories, it’s lighter, it’s more drinkable — so that was the strategy,” Liquid Death vice president of creative Andy Pearson told the publication. As for the peeing on data center concept, Pearson added that it’s the one issue that's common across America. “When you look at the data, it is literally the one thing that unites all Americans right now, across the spectrum.” In the video below, Kelce opens by stating "AI data centers waste millions of gallons of water."

Aside from electricity use and consumption pushing prices for all consumers, the next big issue that many data centers face is the amount of water that they consume in their operations. There have been several instances of data centers affecting the water supply of the neighborhood that they’re in. One example of this is this 615-acre campus in Fayetteville, which has been causing low water pressure for over 15 months as it secretly sucked 29 million gallons of water, while another report showed a Meta data center allegedly muddying the water supply in a Georgia town.

These concerns had tech giants like Microsoft and Amazon release claims that their data centers only consume a small amount of water, while Nvidia has also been developing technologies that will cut data center water use by up to 100%. Still, many feel that these efforts aren’t enough to address the issues being felt right now, leading to passionate and widespread resistance against these projects across the nation.

The two indie brands are trying to get on board the issue in a more lighthearted, less preachy way, making use of humor and a bit of crudeness to touch on sensitive issues like data centers. While the video has a disclaimer saying, “to please don’t actually send your pee,” some developments plan to use treated wastewater instead of fresh water for their water demands, so some data centers already use “pee” to cool their GPUs. We just wish that more of these facilities did this from the beginning, instead of making thousands of people suffer from water problems.

There’s light at the end of the tunnel for Nine PBS. We reported last week that the station lost access to 50TB of data representing 70 years of TV history. The issue was that its cloud storage provider went out of business and access to this important set of backups was abruptly cut off. In the meantime, a judge has cleared the way for Nine PBS to retrieve its archival data and programming from Iron Mountain Data Centers.

Let us refresh your memories of this case by sketching out a timeline of how we got here, before discussing the latest ruling.

• 2019: Nine PBS began using Open Source Storage (OSS) as its cloud storage provider.
• 2019-2025: Annual cloud storage contract renewals occur without incident.
• February 2026: Nine PBS wanted to meet with OSS about contract renewal but couldn’t get in touch.
• March 6, 2026: Without any new agreement inked, the existing contract expired on March 6, with the terms allowing 30 days for the customer to retrieve their data. However, OSS seemed to cut off access to Nine PBS cloud data without any warning or any grace period.
• March 13, 2026: Nine PBS learned that OSS saved its cloud data at physical servers housed in Iron Mountain, Colorado. So it wrote to request that Iron Mountain preserve and return the data. However, Iron Mountain doesn’t confirm or deny that it holds this data.
• April 16, 2026: Nine PBS filed suit against OSS, and new OSS owner James Tramel confirms the data is secured at Iron Mountain.
• May 2026: Tramel stops responding, later claiming he was defrauded into buying OSS.
• June 2026: Nine PBS obtains a default judgment stating it owns the data in question and has the right to possess it. Later the same month, Iron Mountain admits it possesses the data. However, Iron Mountain decides to block any access as it says OSS owns the physical servers.
• July 28, 2026: Nine PBS files a lawsuit against Iron Mountain, the data center provider for OSS, seeking protection against data deletion or modification.

Nine PBS - "70 years of our organization’s history" in danger

The latest development in this twisting and turning case of Nine PBS’s lost data seems like good news for the station. On August 12, 2026, a Denver judge established a process that would allow Nine PBS to retrieve its 50TB of archival data from Iron Mountain’s Denver data center.

The outlined framework includes appointing a third-party vendor, such as a former OSS employee, to assist in the retrieval of the data from the hardware in Iron Mountain. This must be done within 30 days. Moreover, Nine PBS must pay the current and overdue storage fees that OSS missed, and any physical devices the third party takes off the premises must be returned to Iron Mountain after data retrieval. Lastly, Nine PBS must verify no other ex-OSS client data is accessed, and indemnify Iron Mountain against any corruption of data owned by others.

Both Nine PBS and Iron Mountain are requested to provide progress updates on the data retrieval process by September 14. Hopefully this will be a lesson learned by Nine PBS, and it will swiftly implement a proper 3-2-1 backup of its irreplaceable data, so any cloud provider error doesn’t cause such a calamity in the future.

PJM Interconnection, the grid operator serving 67 million people across 13 states and Washington, D.C., asked federal regulators on Thursday to approve rules that would cut power to new data centers ahead of households during supply shortages, Reuters reports. The filing with the Federal Energy Regulatory Commission follows two consecutive capacity auctions that failed to secure enough generation, and PJM's board projects roughly 70 GW of new large load by 2038 against roughly 15 GW of generation retired since 2022.

Existing facilities aren't affected, with the proposed Interim Resource Adequacy Service applying only to new loads of 50 MW or more at a single site that connect without bringing their own generation, or otherwise securing supply, by June 1, 2027. Those facilities would be curtailed before PJM deploys Pre-Emergency Load Management, which are the demand-response programs that pay other customers to cut consumption during grid stress.

Attached to the scheme is a new Large Load Registry, which tracks the location and megawatt draw of every 50 MW-plus site in PJM's territory and whether it brings its own supply. Affected customers would be compensated at a FERC-approved hourly rate set at 50% of the penalty rate PJM pays existing demand-response resources during full grid emergencies. It’s understood that operators can waive that payment in line with the White House's Ratepayer Protection Pledge.

PJM can't actually flip the switch itself, however. The operator told Reuters that it lacks the authority to curtail individual sites and would need to rely on utilities and state governments to carry out the reductions, which is why the registry data will be shared with states to set load-shedding priorities. Virginia, home to the world's largest data center cluster, has already ordered operators to pay for their own dedicated grid infrastructure.

Data centers in PJM’s territory have been curtailed before under a Department of Energy emergency order issued in May, which enabled the operator to call on large loads with backup generation as a last resort ahead of rolling blackouts. PJM expected less than 5,800 MW of reserves during that heat event, with Maryland and Virginia under the most strain. Thursday's filing would turn that one-off emergency authority into an established mechanism.

In July, PJM’s capacity auction for the 2028/29 delivery year hit its $325 per megawatt-day price cap and still came up some 6,800 MW short of the operator’s reliability requirement. Its independent market monitor has attributed a 75.5% jump in regional power costs directly to data center demand.

A separate one-time backstop procurement, running September 30 through October 21 with offers capped at $555 per megawatt-day, aims to backfill the shortfall, and from the 2029/2030 auction onward PJM plans to exclude new large loads that don't bring their own supply from the demand it procures for at all.

Cherokee Nation, the largest tribe in the U.S. with more than 475,000 citizens, has banned hyperscale data center development on its tribally owned and trust lands, after a task force convened by Principal Chief Chuck Hoskin Jr. found that 64% of 1,593 surveyed citizens opposed construction of the facilities inside the tribe's 14-county reservation in northeastern Oklahoma. The 37-page report cited energy and water consumption, air quality, noise, and cultural resource protection among citizens' concerns, and the tribe said it won't support projects on non-tribal land within the reservation without early consultation.

"Our primary responsibility is to protect our citizens and tribal communities from these threats, so we will not support any hyperscale data centers on our reservation without proper consultation," Hoskin said in the tribe's statement.

The task force couldn't establish how many data centers Oklahoma actually has, however. For the same June 2026 date, the report cites Cleanview counting 12 operating and 17 planned projects statewide, DataCenterMap listing 46 operational facilities, and ConstructConnect showing 33 in the pre-construction pipeline. No state or federal rule requires data centers to register anywhere, so the task force's most reliable method for detecting sites was monitoring the Oklahoma Department of Environmental Quality for backup-generator air permits, which themselves don't cover every project.

Every active hyperscale project inside the reservation is sited on non-tribal land and is unaffected by the ban. Google's Pryor campus, for example, has operated since 2011 through at least five expansion phases and forms part of the company's $9 billion Oklahoma commitment, while Project Clydesdale near Owasso and Project Mustang in Claremore, which received a 25-year property tax abatement per phase, both proceed under municipal and county approvals. The report concedes the tribe has no direct regulatory control over such land, only leverage via consultations.

Most projects purposely avoid federal permits that would trigger such tribal consultations under NEPA, and Cherokee Nation joins the Seminole Nation and Kickapoo Tribe, which passed their own moratoriums in March and July according to Tribal Business News. Tulsa itself paused new approvals for nine months in March, part of a wave that has seen at least 69 US jurisdictions block new builds and 19 Michigan municipalities freeze approvals after the Saline Township Stargate fight.

The same survey that recorded 64% opposition found 73% of respondents use generative AI tools, with 34% using them daily and 19% weekly. The report calls this "a clear disconnect" between citizens' perceptions and their actions, and recommends fact sheets and explainers on how everyday AI use feeds hyperscale demand. It also recommends a permanent advisory committee to evaluate future proposals and advise the principal chief as new projects emerge.

The global data center optical interconnect market is expected to reach $144.4 billion by 2030, up from $13.7 billion in 2024 — a 48.1% compound annual growth rate (CAGR) — according to a China Insights Consultancy (CIC) report commissioned by a Chinese laser-chip maker, Yuanjie Semiconductors, as part of its Hong Kong IPO filing. The report draws on data from LightCounting and interviews with industry experts. Of that future market, silicon photonics, the practice of manufacturing photonic chips from the same silicon material and mature CMOS foundry processes used for conventional semiconductors, is projected to account for 63.7% of revenue, its share climbing from 16.6% in 2020 as the industry shifts toward denser, more power-efficient designs like co-packaged optics.

The moves that would turn those projections into reality are already well underway. Over the past year, the AI industry has invested more than $15 billion in co-packaged optics, photonic chips, higher-speed transceiver modules, and fiber, developing new integration techniques, acquiring photonics startups, and forming alliances among the biggest players. More recently, OpenLight and Tower Semiconductor placed OpenLight's photonic design kit inside Cadence's mainstream chip-design software. This step makes the laser-integrated 400G and 1.6T chips at the heart of co-packaged optics easier to design and bring to market.

The tech behind the numbers

For decades, data centers have relied largely on copper traces and cables to move data across circuit boards, within racks, and across clusters. Copper is cheap, reliable, and easy to integrate. However, its power consumption and signal losses increase sharply with bandwidth and distance. As AI data centers are packed with ever more powerful GPUs, shuttling enormous volumes of data and pushing networks toward higher speeds, copper hit a wall. Past a few hundred gigabits per lane, its usable reach collapses to a meter, or two, before signal loss and power draw become unmanageable.

The solution has been a transition to photonics, moving data as light instead of electrical signals. An optical transceiver converts electrical signals from switches and processors into laser light, sends it down a fiber, and converts it back at the far end, carrying far more bandwidth over greater distances at much higher speeds. Today, pluggable transceivers pack a laser chip, digital signal processor (DSP) chips, and several optical components into one compact module. As GPUs grow more capable and AI workloads swell, both the volume of data and the speed it must travel keep climbing, pushing the industry from 400G links to 800G to 1.6T and beyond

At the same time, the industry is trying to move the optics closer to the compute. In conventional systems, GPU signals travel inches along copper traces across the board to reach the transceiver on the faceplate. At extreme data rates, even that relatively short electrical journey consumes considerable power. Co-packaged optics (CPO) fixes this by pulling the optical engine out of the pluggable module and placing it as a chip — the photonic integrated circuit (PIC) — directly on the switch or accelerator package, shrinking the electrical path to millimeters. The push for faster optical chips, aiming for terabits-per-second speeds, serves both CPO and the pluggable modules that remain the industry mainstay.

The PIC does everything but generate light. Because laser chips are highly sensitive to heat, they can't be folded into the PIC, which, in co-packaged optics, becomes part of the switch or accelerator package that runs extremely hot. Therefore, the laser stays a separate chip. Whether feeding a co-packaged PIC or a pluggable module, those laser chips are always needed, which is exactly what Yuanjie, the company that commissioned the CIC forecast, makes.

The PIC itself is where silicon photonics comes in. Photonic chips were once built entirely from costly III-V materials in specialized fabs; Silicon Photonics (SiPh) instead patterns the optical circuitry onto silicon using the same mature, high-volume CMOS processes as ordinary chips — saving money and time and making PICs mass-producible. On the other hand, silicon cannot lase. As a result, laser chips still rely on the more expensive III-V method, using materials such as indium phosphide. Circumventing exactly that is the aim of the recent OpenLight–Tower platform. Their approach integrates III-V laser material directly with silicon photonics at the wafer level, aiming to bring the laser into the same scalable manufacturing flow as the rest of the PIC.

The numbers behind the growth

Together, the different photonics technologies solving the AI data transfer bottleneck are driving a huge market in the industry. CIC projects the data center optical interconnect market growing from $13.7 billion in 2024 to $144.4 billion in 2030, a compound annual growth rate of 48.1%, more than a tenfold increase in six years. Growth accelerates over this period, with the steepest gains occurring after 2027. The report breaks down the three main ways: technology, use case, and data rates, each showing where the spending and resulting revenue are concentrated.

By technology, it splits the market between silicon photonics and everything else. SiPho's share climbs from 16.6% in 2020 to 63.7% of total revenue ($91.9 billion) by 2030, with its revenue compounding at 68.5% annually, compared with 32.6% for the rest, and the crossover past half the market landing around 2027. According to CIC, silicon-based optics— primarily PICs — will grow to become the default.

The use-case breakdown shows which parts of data center networking are driving optical demand: scale-up inside the rack, scale-out across a data center, and scale-across between data centers. Scale-up — the short-reach links from servers and chips to the top-of-rack switch — takes the lead with a 561.5% CAGR in revenue. Note that this figure compounds off a near-zero 2024 base, where a tiny absolute gain reads as an absurd percentage. Scale-across follows at 108.5% and scale-out at 42.7%, while the entire non-AI segment, traditional workloads from telecom to enterprise servers, trails at 37.5%. However, in actual revenue and not growth, scale-out is the largest tier at $64.5 billion in 2030, followed by non-AI at $40.2 billion and scale-up, for all its headline growth — at just $32.1 billion, with scale-across last at $7.6 billion.

The data-rate breakdown captures a generational migration of speed. In 2024, the market still ran on the previous two generations, 400G at $5.9 billion and 800G at $4.5 billion, with legacy 200G-and-below links adding another $3.3 billion and the faster tiers barely registering. By 2030, that order is inverted. 1.6T, only entering commercial deployment in 2026, becomes the single biggest segment at $65.6 billion, expanding at an 867.3% CAGR from a 2024 base of essentially zero; 3.2T, a category that didn't exist in 2024 at all, appears only from 2027 and still vaults to $44.5 billion. Together, those two next-generation speeds make up roughly $110 billion of the $144.4 billion total. The rest slides down the ladder: 800G stays healthy at a 34.8% CAGR to $26.7 billion, but 400G flatlines — 1.0% annual growth to $6.3 billion, after leading the prior cycle at 75.3% — and 200 G and below actively contracts, shrinking 15.4% a year.

The moves behind the numbers

While the CIC figures are just projections, the actual moves happening in the industry point in the same direction. Over roughly the past year, more than $15 billion has moved through silicon photonics. Nvidia invested $2 billion each into Coherent and Lumentum — makers of the lasers and optical components that go inside transceivers — in March, followed by $2 billion into Marvell and a $500 million warrant deal with fiber maker Corning, each bundled with multi-year purchase commitments. Meanwhile, Microsoft, Meta, and OpenAI have teamed up with hardware giants Broadcom, AMD, and Nvidia to establish an Optical Compute Interconnect (OCI) Multi-Source Agreement (MSA) group to develop protocol-agnostic scale-up interconnection technology for AI clusters.

On the mergers-and-acquisitions side, Marvell, before the Nvidia investment, closed its $3.25 billion cash-and-stock acquisition of Celestial AI, a photonic interconnect startup, to gain its Photonic Fabric platform for linking chips optically inside the rack. Meanwhile, Ayar Labs, which builds optical I/O chiplets that move data directly off the compute package, raised a $500 million round at a valuation of roughly $3.75 billion. Elon Musk also received regulatory approval to acquire Mesh, an optical transceiver manufacturer.

Those bets converge on co-packaged optics as the architectural prize. Nvidia's Spectrum-X and Quantum-X photonics switches, built on TSMC's COUPE process, are the flagship deployments. Broadcom is pushing its own CPO Tomahawk line and has foundries TSMC and GlobalFoundries, with Tower supplying the silicon underneath. The one constraint the money cannot instantly buy away is the laser: high-speed III-V sources remain the scarce link, with Lumentum currently the only vendor shipping the 200G-per-lane EMLs that 1.6T modules require at volume. That scarcity — and the whole industry's dependence on laser chips regardless of which design wins — is exactly why a supplier like Yuanjie sits aligned with wherever the market goes.

The race to solve AI's copper bottleneck for scale-up and scale-out intensified last week, as the Federal Communications Commission (FCC) is drafting a measure that would block imports of new Chinese transceiver models, with officials hoping to publish the rule before the end of 2026. Yesterday, we covered exactly how much of the Secure Networks Act might rely on Chinese-made optical module manufacturers.

The technology is currently driving billions in acquisitions among companies like Marvell and Nvidia, and sending stock prices for dedicated Western Photonics companies like Coherent and Lumentum skyrocketing, amid calls that key materials like indium phosphide are in short supply.

Following the FCC's Secure Networks Act proposal, the market reacted immediately, with shares of China’s Zhongji Innolight, Eoptolink, and TFC Optical tumbling in early Shenzhen trading. Meanwhile, U.S. rivals Coherent and Lumentum closed 12.4% and 8.9% higher. Before Wednesday ended, however, the Chinese companies had clawed back much of the ground, even as analysts downplayed the impact of such a ban. Innolight still finished 7.3% lower in Shenzhen, while TFC actually closed 2.3% higher.

The whipsawing market movement was an apt representation of the potential implications of such a ban. Photonics, the industry's answer to its latest bottleneck of moving data between chips, is arguably the hottest technology in AI infrastructure right now. It is also a market defined by deep mutual entanglement. However, the FCC's proposal conveniently overlooks the fact that the biggest customer of China's photonics hardware is the United States.

With a crucial U.S.-China summit looming in September, the AI supply chain is being weaponized, once again, for global trade and supply negotiations, turning Silicon Photonics into a bargaining chip.

AI's latest bottleneck is now a US-China tech wars battleground

As AI clusters scale into the hundreds of thousands of processors, the biggest problem is moving data between them. Computing tasks on frontier AI models are distributed across thousands of GPUs using parallel computing techniques. This setup requires the processors to exchange huge volumes of data multiple times a second. Copper interconnects still dominate, but as per-lane signaling climbs toward 200 Gbps, attenuation and crosstalk make passive copper impractical beyond a meter or two. Optical transceivers solve that problem by converting a chip's electrical signals into photons for transmission over fiber and back again, carrying far more data over longer distances at lower power.

As we examined in our recent detailed AI photonics roadmap, Vendors are racing from 800G modules to 1.6T parts while shortening electrical paths with co-packaged optics, which moves optical engines even closer to switch ASICs and, eventually, accelerators. The race to solve AI's photonics bottleneck is therefore becoming as strategically important as securing GPUs and HBM.

The money is already moving accordingly. Nvidia has reportedly committed $4 billion across Coherent and Lumentum to lock up supply. Elsewhere, Marvell agreed to pay $3.25 billion upfront for silicon photonics startup Celestial AI, with earnouts potentially taking the deal to $5.5 billion. At the same time, Elon Musk has received FTC clearance to acquire Mesh Optical. Meanwhile, Microsoft, Meta, and OpenAI have teamed with Broadcom, AMD, and Nvidia in an optical interconnect alliance to develop an open optical scale-up interconnect.

China has been building its own stack. Wuxi's CHIPX pilot line — the country's first dedicated photonic chip fab — began mass-producing six-inch photonic wafers in 2025. Shanghai opened a state photonic computing laboratory in June alongside newly listed startup Lightelligence. Crucially, Chinese officials note photonic chips don't require the EUV lithography tools Washington has cut off.

Commercially, China appears to be currently leading the market. Chinese vendors account for nearly two-thirds of global transceiver unit shipments and roughly 60% of datacom transceiver revenue, according to Counterpoint Research. Innolight — fresh off a $6.8 billion Hong Kong IPO, the city's biggest this year — leads with a 27% revenue share, ahead of Coherent's 17%, with Eoptolink third and Lumentum at roughly 6%.

However, those figures do not reveal the deep-seated supply-chain entanglements that severely complicate any ban. Innolight and Eoptolink reportedly supply the majority of 800G modules in Nvidia's AI clusters, while pairing DSP chips from Broadcom and Marvell with laser components from Lumentum, Coherent, and Mitsubishi Electric. Western rivals, in turn, need Chinese indium phosphide — export-controlled by Beijing since 2025 — for their lasers.

The U.S. ban

It is amid the intense photonic race, marked by co-dependency between the two countries, that the FCC is seeking to ban related Chinese hardware. Reuters says the agency is drafting a rule that would deny new models of Chinese optical transceivers the equipment authorization they need to be imported, marketed, or sold in the US.

Washington fears the transceivers could become vectors for data theft, malware, or service disruption, with officials reportedly seeking to avoid another Huawei situation, in which Chinese telecom hardware became so embedded in U.S. infrastructure that removing it proved slow and expensive.

If enacted, the rule would be the latest round in a years-long technology conflict spanning security fears and market dominance, one that has extended squarely into AI. On the inbound side, the FCC has banned Huawei gear since 2019. It added foreign-made drones to its Covered List in December 2025, new consumer routers in March, and power inverters and advanced robots in July — each time citing national security. On the outbound side, Washington restricts AI GPUs, ASML's EUV machines, chipmaking tools, and manufacturing tech from reaching China, aiming to slow its AI ascent.

The Trump administration has argued that these bans have barely had any impact on the U.S. economy while enhancing national security. A photonics ban may be more consequential. The U.S. is effectively contemplating short-term disruption to prevent a scenario where the next generation of a critical AI technology, the optical layer of every future data center, would be Chinese hardware. On the other hand, the FCC appears to accept the current supply chain reliance, as the millions of Chinese modules already installed would stay put.

China’s response

For every ban the US issues, Beijing insists it emerges stronger. Officials credit the chip restrictions with forcing focus. Chinese firms delivered 1.65 million AI GPUs in 2025, with homegrown suppliers like Huawei and Cambricon ramping up production as Nvidia's local market share fell below 60%. Domestic firms are also developing alternative manufacturing approaches. Prinano recently claimed wafer-scale photonic-chip production using nanoimprint lithography instead of DUV, although important yield and volume data remain undisclosed. China now says it doesn't even want American chips, blocking Nvidia H200 imports while certifying domestic accelerators for state procurement.

The photonics response has been similar, this time with open displeasure. China's Foreign Ministry said it "firmly opposes" the potential restriction and accused Washington of overstretching national-security concerns. Chinese legal and market analysts told SCMP that existing approved modules should remain unaffected. They argued that Western suppliers lack the packaging capacity, cleanrooms, and manufacturing scale to replace Chinese production within the next few years.

Dai Menghao of law firm King & Wood, quoted in the SCMP report, called the measure "relatively mild," expecting a framework like the FCC's router and inverter rules, where approved hardware keeps selling, and only new models face denial. That comparison doesn't exactly match. Routers, unlike photonics, are a mature category. In a market right in the middle of a transition, almost everything shipping into next-generation builds would fall under the "new model" category.

Still, Chinese experts insist Washington is underestimating its own exposure. "The market and policymakers tend to underestimate how dependent the AI infrastructure ecosystem remains on Chinese optical-module vendors," said Neil Shah, vice-president of research at Counterpoint. "Replacing that capacity within the next couple of years would be very difficult."

For now, the rule that would affect a ban remains a draft, subject to comment periods, carve-outs, and court challenges. With a potential US-China summit looming in September, the world's most important AI component has now potentially turned into a geopolitical flashpoint.

The number of local bans on new data center developments jumped to over 500 in July, according to recent data. Local politicians in the United States are refusing to approve new data center construction in greater numbers, posing a threat to the expansion required by AI firms to provide the capacity needed to power the new technology. The analysis, conducted by The Information from legal documents and local news reports, shows that this isn’t a partisan issue.

Republican- and Democrat-run states, towns and counties have all begun to block new data center projects, with Texas and New York both prominent entries from both sides of the political divide, and with the majority of the bans appearing in the Midwest and South, according to the report.

Politicians aren’t doing this out of spite, but in response to the growing concern from residents over the impact on communities. Among them are the impact of noise on local residents, as well as the disproportionate impact on public services, including on water and electricity supplies. It follows Texas Governor Greg Abbott’s moratorium on data center approvals in recent weeks until an extensive audit has been conducted of companies looking to hook their new centers up to the Texan power grid.

The Information’s analysis shows that the bans are growing fast, jumping from 300 in late June to over 500 in July. The ban in Texas is particularly noteworthy due to the state becoming a prominent home for AI data centers. Despite Governor Abbott’s pause, Amazon is still hoping to build a new gas power plant in Pecos County, Texas, to power a data center at the same location. That location is already believed to likely become the single biggest source of environmental pollution in the U.S. once it’s operational.

The rapid growth of new data centers in Texas and nearby states has likely fueled those concerns from residents. The Information reports that most of the bans are in the Midwest and South, with more than 400 restrictions now in place, with nearly three-quarters of the moratoriums approved in July occurring in southern states like Georgia and Florida. Florida, in particular, is quickly stopping new developments, with 14 out of 23 current active restrictions in that state being approved in July, and 15 more under consideration.

Small and big, rural and urban states alike are all seeing political capital used on preventing AI data center expansion. Kathy Hochul, Democrat Governor of New York, recently signed an executive order that paused approval for all data centers consuming 50 megawatts of energy or more. Massachusetts and Nebraska halted tax breaks for developers, while in Colorado, 19 bans are now in place around Denver, and more elsewhere in the state, due to concerns specifically around the impact on the environment and on water usage. In Nashville, Tennessee, a 23-acre data center development next to a zoo, expected to cost up to $700 million, is also facing local and political resistance.

It’s no surprise to see politicians begin to wake up to the public malaise against AI development. Over 70% of Americans are reportedly against more AI data centers, and direct resistance against them is growing, with at least 37 people arrested so far this year for protesting against new developments.

The public pushback against data center construction projects is only growing stronger, even as some protesting local residents have been arrested in the process. That hasn't perturbed those still standing against the AI infrastructure projects, though, and they continue showing up at town meetings, holding protest rallies, and making themselves heard — even with the 24/7 drone of a data center hum in the background.

The latest effort saw Nashville residents and local politicians move to block the construction of a $700 million data center set to be built right next to the Nashville Zoo at Grassmere. The city council approved a blocking measure last week, and now Mayor Freddie O'Connell will wield it to make sure the project doesn't go ahead.

This follows on from another recent story where a Kentucky farming family was offered 10 times their land value to sell up to data center developers, and they refused. Virginia's State Corporation Commission, which regulates public utilities, just ruled that data centers must pay for all the required transmission infrastructure that they have exclusive use of, in an effort to reduce energy bills for residents.

Nobody wants to live near a data center

Data center projects have been firmly disliked by large bodies of Americans since the beginning of this major AI buildout. Early in 2025, it became clear that even as the major AI companies were promising hundreds of billions for "AI factories," governments around the world rushed to build capacity. There was only one problem: residents near the proposed build sites would not be taking it lying down.

In April 2025, Elon Musk's Colossus data center was an early target for protest after it was found to be using permitless mobile gas turbines for power. It's been hit with enough pushback since then that SpaceX has now agreed to remove the 69 turbines it ultimately installed, although it is going to take over a year to complete the move of these allegedly mobile turbines.

By the Fall of last year, evidence had begun to mount about the negative impact of these installations. Water shortages and potential contamination, electricity price increases for residents, and the constant, unending noise that may be causing health problems with sub-audible frequencies.

There's also the slowly growing number of "against" voices in polling for new data centers. What started as a light advantage to the "supports" respondents in September became a near-majority a few months later. Now more than 70% of Americans don't want data centers near their homes, and there's little chance of that changing as the stories of issues during and after construction of these facilities continue to mount.

How the people are fighting back

Protest has been at the forefront of the anti-data center campaigners' playbook since the start, and that's not stopping any time soon. On one weekend in July, anti-data center protestors organized in 42 states to stage 142 protests across the country, all calling for blocks, halts, and moratoriums on the data center rollout.

This is after months of campaigning, which led to close to 70 jurisdictions around the country blocking new data center builds. Some of them, permanently.

Where politicians are more on the side of the developers, the people are going to meet them in person. They're going to town halls and seeking meetings and making their voices heard.

Sometimes politicians don't like that, and people are removed - even when protesting peacefully - and in several cases they've actually been arrested. Close to 40 people have been arrested in 2026 for pushing back against data center rollouts. In one case, because they went beyond their allotted speaking time, and in another, because they clapped following an impassioned statement by a fellow citizen.

In other cases, though, politicians are listening. In Nashville, the local council and the mayor are all on board to protect the local Zoo and residents' bills and ears. This is particularly important because it shows that local legislators can use their political power to block data centers — potentially preventing the White House from using its own to drive projects through.

The forever war

The data center builders aren't taking all of this helplessly. They have the ears of government and massive platforms to evangelize AI and data centers; They've been doing it everywhere from the White House to social media. They've tried building in more rural areas where there are fewer people to protest, paying for their own behind-the-grid power, and offering to spend millions in local investment to counter negative effects.

But it's not working. People don't like data centers. They don't want to live near them. And on top of that, many don't even like the technology the hyperscalers want to build this all for, anyway.

It's unlikely that those bankrolling (and hoping to make money on) the data center AI build-out will just give up and go home, but the residents fighting back against their gargantuan construction projects aren't going to do so either.

This is a long war, and one that neither side is likely to back down from. But in a rare ray of hope in 2026's landscape of high PC and electronics prices due to AI data centers soaking up computing hardware, it's one that the people seem to be winning, for now.

A new Amazon data center is set to become the single largest source of environmental pollution in the U.S., according to a New York Times report on August 8. The tech giant — which already operates the most data centers worldwide — is reportedly building a natural gas power plant in Pecos County, Texas, to power its new data center at the same site. According to project permits, the plant would generate up to 7.65 gigawatts of power using 35 natural gas turbines. The new plant — which burns natural gas to generate electricity — has been authorized to release 33 million tons of CO₂ annually, more planet-warming gases than any other power plant in the country, says the NY Times report.

Conversely, Amazon had pledged to achieve net-zero carbon emissions across all its global business operations by 2040. The company made the promise in 2019 when it initiated and co-founded The Climate Pledge — a voluntary coalition of over 700 companies and partners — aimed at addressing its own corporate footprint and rallying global supply chains. However, the company has seen its emissions rise each year for the past several years, something analysts attribute to a spike in data centers to support the AI boom. The company is currently building several additional AI data centers globally, including the one that the new gas plant would power in Texas.

Amazon has acknowledged the impact of its intense AI ambitions on its earlier climate pledges but insisted the company remained committed to them, despite obvious struggles. “The world looks different now than when we co-founded the climate pledge,” said Margaret Callahan, an Amazon spokeswoman. Still, “our commitment hasn’t changed,” she said, echoing similar statements by Microsoft, which is struggling to fulfill its 2030 sustainability promise amid carbon-heavy AI expansion, but insists it remains committed to it.

As detailed in our data center power roadmap, an increasing number of hyperscalers and data center operators are switching from grid connections to dedicated on-site power generation. The “behind-the-meter” moves are being triggered mainly by the long timelines required to set up new power infrastructure to connect new power-hungry data centers to the grid, but also by growing anti-data center sentiments over irreversible hikes in the electricity bills of nearby communities.

While many companies are also pursuing nuclear and renewable energy options — examples being Microsoft’s Three Mile Island nuclear deal and Meta’s agreement to secure up to 1GW of orbital solar energy capacity — gas appears to be the leading preference due to its scalability and speed of availability. The Trump administration has thrown its weight behind such projects for data centers, promoting oil, natural gas, and coal over renewable energy sources.