Leading chipmakers Samsung Electronics and Taiwan Semiconductor Manufacturing Co. announced plans to adopt ASML’s latest chipmaking machines in the next several years—and they also joined Intel in agreeing to a crucial technology change that could boost chip production on the new machines by 40 percent.

This signifies the semiconductor industry’s broader embrace of high NA EUV photolithography technology that can cost up to $400 million per machine and is only provided by the Dutch technology company ASML, Bloomberg reports. The technology would allow chip designers to implement even smaller features in potentially more powerful and efficient next-generation chips produced for AI data centers and consumer electronics such as smartphones, tablets, and laptops.

ASML’s EUV (extreme ultraviolet) lithography machines enable chipmakers to use powerful laser light to imprint patterns in silicon wafers, layer by layer, and gradually form the computer circuitry that makes silicon chips work. Compared to older deep ultraviolet lithography, EUV technology harnesses a more powerful source of light with a shorter wavelength to create even smaller features on silicon wafers.

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© Michel de Heer | ASML

Leading chipmakers Samsung Electronics and Taiwan Semiconductor Manufacturing Co. announced plans to adopt ASML’s latest chipmaking machines in the next several years—and they also joined Intel in agreeing to a crucial technology change that could boost chip production on the new machines by 40 percent.

This signifies the semiconductor industry’s broader embrace of high NA EUV photolithography technology that can cost up to $400 million per machine and is only provided by the Dutch technology company ASML, Bloomberg reports. The technology would allow chip designers to implement even smaller features in potentially more powerful and efficient next-generation chips produced for AI data centers and consumer electronics such as smartphones, tablets, and laptops.

ASML’s EUV (extreme ultraviolet) lithography machines enable chipmakers to use powerful laser light to imprint patterns in silicon wafers, layer by layer, and gradually form the computer circuitry that makes silicon chips work. Compared to older deep ultraviolet lithography, EUV technology harnesses a more powerful source of light with a shorter wavelength to create even smaller features on silicon wafers.

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© Michel de Heer | ASML

In early June, a fire broke out in a still-unfinished building at the Lake Mariner data center in Somerset, New York, exposing just how little the local fire department knew about what it was walking into. Firefighters reportedly found no working alarm, no suppression system, and three dead hydrants; the safety documents they’re legally entitled to see reportedly burned up in the blaze.

Steve Matisz, chief of the Barker Fire Department, said his crew went into the building “kind of blind,” facing heavy black smoke from chemicals they couldn’t identify because the safety sheets meant to inform them had apparently burned up. “It’s been a difficult situation,” Matisz said. He wasn't sure what to think about the claim that the safety sheets had burned in the fire.

The site is a former coal mine on Lake Ontario. The $3.2 billion campus is one of the largest AI data center buildouts in New York, and it has many stakeholders. A company called TeraWulf owns and operates the data center on land it leases from a company owned by its own CEO; Fluidstack, a UK-based AI company, will run the center; Google holds warrants for a future 14 percent equity stake and has agreed to guarantee Fluidstack’s lease payments; and Anthropic is among the AI companies whose compute demand the facility exists to serve.

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Meta is testing robots that can plug in cables, reset servers, and handle other tasks inside its data centers, according to several current and former workers familiar with the projects. The ongoing effort, which has not been previously reported, may eventually allow Meta to operate its rapidly expanding data center footprint with fewer humans, keeping labor costs in check as its spending on AI infrastructure soars.

Meta is using robots and related hardware from several different vendors, including Watney Robotics, Kinova, and ABB, according to the same workers, who asked to remain anonymous because they weren’t authorized to speak to the media. Kinova and ABB declined to comment. Watney didn’t respond to requests for comment.

In one experiment, Meta is evaluating whether a Kinova Gen3 robotic arm could be used for power cycling or cutting off electricity to servers. The company is also testing a different robot to swap networking cables. One Meta data center worker estimates that if it’s successful, the bot could replace up to 80 percent of some people’s workloads. “We thought those of us performing the physical tasks were safe for a while, but not anymore,” says the worker. “It’s coming for us all, unfortunately.”

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Data centers have become the largest driver of a surging electricity demand that is straining US power grids. But the AI data center boom has also accelerated investment in a technology that could provide a silver lining for everyone—solid-state power transformers that replace industrial-age technology with modern power electronics.

Power grids currently rely on conventional transformer technology that is painstakingly assembled by hand and has a fundamental design dating back to the 1880s. Two copper wire coils manually wound around a steel core create electromagnetic fields that help step up voltage levels of alternating current electricity for long-distance transmission or step down voltage levels for the electricity use of homes and businesses. The largest power transformers cannot be mass-manufactured but are instead custom-built for each utility company’s electrical substations.

Manufacturing constraints, coupled with the scramble to upgrade US power infrastructure, have meant utility companies and other customers must wait up to several years for delivery of new power transformers. That not only hinders power grid infrastructure expansion needed to support growing electricity demand, but also delays the process of replacing aging power transformers.

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The Trump administration is quietly considering a rule change that could make it easier for polluters to build facilities—including certain gas plants and diesel generators that power data centers—with little to no notice to the public.

On Wednesday, the Environmental Protection Agency held a public hearing on a proposed rule change that would hand the power to states to decide how the public participates in the permitting process for certain new sources of air pollution. The proposed rollback comes as data centers face greater pushbackacross the US, with many communities using the permitting process to try to slow down development. Any changes could have major consequences for how ordinary people are given notice about new or expanded polluting facilities coming into their neighborhoods.

“As someone actively working in communities with data centers, I know this to be fundamentally true: People want to have a say,” Vanessa Lynch, a Pennsylvania organizer with Moms Clean Air Force, said at the EPA hearing.

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Energy companies are raising money at IPO at their fastest pace this century, taking advantage of investors’ hunt for new ways to bet on the boom in power-intensive AI data centers.

Initial public offerings for energy firms raised $12.6 billion in the first half of this year, according to data firm Dealogic. That marks the highest half-year level since the peak of the dotcom bubble in late 1999 and the highest first-half figure on record. It is well above 2025’s full-year total of $4.3 billion.

The surge in fundraising comes as access to the vast amounts of energy needed to run data centers emerges as a bottleneck in a multi-trillion-dollar AI investment boom.

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© Michael Nagle/Bloomberg

The prototype could bring steady power to remote sites and AI data centers.