Google’s Project Suncatcher to put ML infrastructure in space
Google's Project Suncatcher is a long-term research moonshot, announced last year, exploring whether space could one day host scalable machine-learning infrastructure. The project is now scheduled for its first test in orbit, launching a prototype satellite to evaluate how Google Tensor Processing Units perform in space.
The rationale is that in low Earth orbit, satellites can access near-constant sunlight, generating up to eight times more solar power than on Earth. Eventually, it could be possible to link together multiple constellations of satellites, allowing them to manage larger AI workloads while in orbit. Google frames this as working backward from an end goal of ensuring AI's benefits in key areas, from healthcare to scientific discovery, can reach everyone far into the future, and compares the measured, deliberate steps to early research into autonomous driving and quantum computing.
The initial mission is onboard the upcoming Transporter-18 rideshare mission with SpaceX and was developed in partnership with Planet. It is designed to gather in-orbit data on how Google's TPUs handle the physical stress of spaceflight and the radiation and thermal extremes of space. As Google prepares for the early test launch and works toward a next milestone in 2027, the Project Suncatcher team discussed what it hopes to learn and the engineering hurdles ahead in a new video series.
On hardware survival, a rocket trip into low Earth orbit lasts about 10 minutes, during which the spacecraft experiences intense vibration and sustained acceleration loads up to 10 times the force of gravity, or g-force. Individual components such as the TPU chips can experience even greater forces up to 50 to 100 g. The team conducted vibration testing by intensely shaking the satellite on all three axes to mimic the frequencies of a rocket launch, and said they were pleasantly surprised that the hardware held up to the force. Once in space, radiation outside Earth's atmosphere presents another challenge: solar events and cosmic rays can wreak havoc on electronics, so the team tested TPUs in a proton beam facility at UC Davis's Crocker Nuclear Laboratory while running AI workloads.