Google’s Project Suncatcher Satellite Generates First AI Response in Orbit

Google said on October 30 that its Project Suncatcher prototype satellite had generated its first artificial intelligence response using a data centre-class tensor processing unit (TPU) in orbit. The milestone marks an early test of the company’s research into running AI workloads in space, according to a blog post by Travis Beals, Senior Director of Paradigms of Intelligence.

Launched on October 1, the satellite is part of Google’s research project exploring whether space could host scalable machine learning infrastructure. Built in partnership with Planet, the prototype was launched aboard SpaceX’s Transporter-18 rideshare mission. Google said it had completed the satellite’s commissioning checklist, including powering up the host and TPU trays and running initial machine learning tests.

During a ground-station pass, Google uplinked a prompt to its onboard Gemma 4 open model, asking it to generate a haiku about being in space. As the satellite passed Svalbard, Norway, the response was transmitted back to Earth.

The haiku generated by the model read:

“Blue marble below

Data streams in silent grace

Starlight feeds my core. ✨”

Google said it subsequently tested the model with space-themed limericks and prompts requesting telemetry information about the payload systems. The company described the milestone as the first AI response from a data centre-class TPU in orbit.

The next phase of Project Suncatcher will evaluate how the TPUs perform under thermal stress and radiation exposure in orbit. Google said these tests would help determine whether its hardware can reliably execute AI workloads in space.

The company plans to use the findings to advance its next milestone, involving two interconnected satellites in 2027. The proposed system is intended to explore how multiple satellites could work together to support AI computing in orbit.

Project Suncatcher explores the feasibility of solar-powered satellite networks equipped with Google’s TPUs. The company said the initiative aims to investigate the long-term potential of scaling machine learning infrastructure beyond Earth.