As I discovered while I continued that line of reporting, building new nuclear plants isn't so simple or so fast. And as my colleague David Rotman lays out in his story for the package, the AI boom could wind up relying on another energy source: fossil fuels. So what's going to power AI? Let's get into it. When we started talking about this big project on AI and energy demand, we had a lot of conversations about what to include. And from the beginning, the climate team was really focused on examining what, exactly, was going to be providing the electricity needed to run data centers powering AI models.

In the field of phase change phenomena, the lack of accessible and diverse datasets suitable for machine learning (ML) training poses a significant challenge. Existing experimental datasets are often restricted, with limited availability and sparse ground truth, impeding our understanding of this complex multiphysics phenomena.

In the AI arms race, all the major players say they want to go nuclear. Over the past year, the likes of Meta, Amazon, Microsoft, and Google have sent out a flurry of announcements related to nuclear energy. Some are about agreements to purchase power from existing plants, while others are about investments looking to boost unproven advanced technologies. These somewhat unlikely partnerships could be a win for both the nuclear power industry and large tech companies. Tech giants need guaranteed sources of energy, and many are looking for low-emissions ones to hit their climate goals.

Donald Trump signed a series of executive orders on Friday intended to spur a "nuclear energy renaissance" through the construction of new reactors he said would satisfy the electricity demands of data centers for artificial intelligence and other emerging industries. The orders represented the president's latest foray into the policy underlying America's electricity supply. Trump declared a national energy emergency on his first day in office over and moved to undo a ban implemented by Joe Biden on new natural gas export terminals and expand oil and gas drilling in Alaska. Nuclear does not carry oil and gas's carbon emissions, but produces radioactive waste that the United States lacks a facility to permanently store. Some environmental groups have safety concerns over the reactors and their supply chain. Trump signed four orders intended to speed up the approval of nuclear reactors for defense and AI purposes, reform the Nuclear Regulatory Commission with the goal of quadrupling production of electricity over the next 25 years, revamp the regulatory process to have three experimental reactors operating by 4 July 2026 and boost investment in the technology's industrial base.

This story is a part of MIT Technology Review's series "Power Hungry: AI and our energy future," on the energy demands and carbon costs of the artificial-intelligence revolution. These somewhat unlikely partnerships could be a win for both the nuclear power industry and large tech companies. Tech giants need guaranteed sources of energy, and many are looking for low-emissions ones to hit their climate goals. For nuclear plant operators and nuclear technology developers, the financial support of massive established customers could help keep old nuclear power plants open and push new technologies forward. "There [are] a lot of advantages to nuclear," says Michael Terrell, senior director of clean energy and carbon reduction at Google.

The U.S. still has its sights on winning the global AI race. First stop: Commandeering AI manufacturing. Announced just last week, a 500 billion infrastructure investment from artificial intelligence giant Nvidia will bring domestic AI manufacturing to the U.S. -- that's half a trillion dollars going toward mass production of the the country's own AI supercomputers as well as NVIDIA's Blackwell chips. The AI supercomputers will take over a million square feet of manufacturing space in Texas, while factories and manufacturing partners across Arizona -- operated by the Taiwan Semiconductor Manufacturing Co., which landed a similar deal in March -- will be tasked with building and testing chips. Proponents say it's a welcome investment in the country's growing AI economy, potentially boosting jobs and aiding in the development of an AI workforce.

U.K. government officials have raised private concerns that Chinese-manufactured drones are being used to take high resolution images of critical national infrastructure sites in the U.K., going against guidance from the country's security services. National Grid PLC, which operates the nation's electricity and gas networks, uses drones made by Shenzhen-based SZ DJI Technology to take videos, photographs and thermal images of its electricity substations, according to information posted on its website as recently as September. DJI drones have also been used to survey the construction of Electricite de France SA's Hinkley Point C nuclear power plant, to inspect solar farms, and by Thames Water to monitor reservoirs and the water supply. Deployment of the drones comes despite a warning in 2023 by the U.K.'s National Protective Security Authority (NPSA), part of the domestic security service MI5, that British organizations managing sensitive sites should be wary of using drones "manufactured in countries with coercive data sharing practices," a reference to China. Moreover, in 2022, the U.S. Department of Defense included DJI on a blacklist of Chinese firms with military ties.

There are reasonable arguments to suggest that AI tools may eventually help reduce emissions, as the IEA report underscores. But what we know for sure is that they're driving up energy demand and emissions today--especially in the regional pockets where data centers are clustering. So far, these facilities, which generally run around the clock, are substantially powered through natural-gas turbines, which produce significant levels of planet-warming emissions. Electricity demands are rising so fast that developers are proposing to build new gas plants and convert retired coal plants to supply the buzzy industry. The other thing we know is that there are better, cleaner ways of powering these facilities already, including geothermal plants, nuclear reactors, hydroelectric power, and wind or solar projects coupled with significant amounts of battery storage. The trade-off is that these facilities may cost more to build or operate, or take longer to get up and running.

Black Mirror is more than science fiction – its stories about modernity have become akin to science folklore, shaping our collective view of technology and the future. Each new innovation gets an allegory: smartphones as tools for a new age caste system, robot dogs as overzealous human hunters, drones as a murderous swarm, artificial intelligence as new age necromancy, virtual reality and brain chips as seizure-inducing nightmares, to name a few. It is a must-watch, but must we take it so seriously? Black Mirror fails to consistently explore the duality of technology and our reactions to it. It is a critical deficit.