Out-of-this-world fix for data center backlash could be on NASA's horizon

NASA Administrator Jared Isaacman is backing a once-futuristic answer to America’s fight over AI data centers: Move them into Earth orbit.Isaacman said Wednesday that solar-powered facilities in space could tap the sun’s energy without competing for the land, water and grid capacity required by sprawling data centers proposed across the country."Let’s take our data centers, put them in Earth orbit, take advantage of that free fusion reactor that’s out there for us and use that to ensure we do win the space race for sure, but the AI race, too," Isaacman said in an interview with Nexstar DC.Isaacman’s idea comes as voters push back on the data center boom.A Fox News poll this summer found 70% of voters oppose building AI data centers in their own area, while 79% said construction should slow to address environmental and community concerns rather than move as quickly as possible to maintain a competitive edge over China.TRUMP TO HONOR ARTEMIS II ASTRONAUTS WHO TRAVELED FARTHER FROM EARTH THAN ANY HUMANS IN HISTORYNASA Administrator Jared Isaacman testifies before a U.S.

Senate Appropriations Commerce, Justice, Science, and Related Agencies Subcommittee hearing.(Reuters)Half of those opposed said environmental issues, including energy and water use, pollution and noise, were their chief concern.The idea comes with its own engineering problems.

AI chips produce immense heat, and satellites would have to release it through large radiators.Operators would also need cheap, reliable launches, radiation-resistant hardware and laser links fast enough to connect thousands of computers spread across orbit.That has not stopped companies from trying to turn the concept into a business.

Google has called Project Suncatcher a "moonshot" to place its TPU chips on solar-powered satellites linked by lasers.It plans to launch two prototype satellites by early 2027 to test its hardware in orbit and determine whether the satellites can share data fast enough for AI workloads...