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Orbital aims for space AI data centers

Orbital plans its first test mission for space-based AI data centers in 2027, aiming to overcome Earth's power constraints.

Daniel Singer

By Daniel Singer, Editor, StartupHub.ai

2 min read

Conceptual image of satellites in orbit with glowing data center elements.
Orbital plans to deploy AI data centers on satellites in low Earth orbit.

In brief

  1. 1Orbital targets a 2027 test mission for its space-based AI data centers.
  2. 2The company cites power and cooling constraints on Earth as a driver for its orbital approach.
  3. 3Orbital plans to leverage solar power and radiative cooling in low Earth orbit.
Contents(3)

Orbital, a startup building AI data centers in space, has set a 2027 target for its first test mission. The company aims to bypass terrestrial power and cooling limitations by operating in low Earth orbit, a move backed by funding from a16z Speedrun.

The demand for AI compute is outstripping available power, a bottleneck Orbital believes can only be solved by generating energy in orbit. Its strategy focuses on using solar power and radiative cooling to overcome the energy constraints that limit current AI infrastructure.

Factory-1 Opens in Los Angeles

Orbital is opening Factory-1, its research and development facility in Los Angeles, signaling a commitment to in-house innovation.

Orbital-1 Mission Details

The company's first satellite, Orbital-1, is slated for a SpaceX Falcon 9 launch in April 2027. This mission will validate sustained GPU operation in space, test radiation hardening, and demonstrate commercial AI inference workloads. Orbital is also seeking FCC approval for a constellation of satellites.

Addressing AI's Energy Ceiling

Orbital CEO Euwyn Poon highlights that AI progress is constrained by the power grid. He states that in orbit, continuous solar power and distinct cooling methods offer a scalable solution.

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The company's architecture is tailored for AI inference, which is more distributed and suitable for a constellation of satellites than the tightly coupled GPUs required for large model training.

Orbital's approach could redefine the scalability of AI infrastructure, moving beyond Earth's energy limitations. This venture into Orbital AI data centers is part of a growing trend exploring space for compute resources, as detailed in AI's Next Frontier: Datacenters in Space and the Race for Supremacy. The broader implications for energy and the new space race are explored in Powering the Cosmos: AI, Nuclear, and the New Space Race.

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TopicsOrbitalAI data centersSpace TechnologyNvidiaa16z SpeedrunSpaceXLow Earth OrbitEuwyn Poon

Daniel Singer

Written by

Daniel Singer

Editor, StartupHub.ai

Daniel Singer is the editor of StartupHub.ai, a technology expert and thought leader on AI and its applications across sectors, from fintech and healthcare to developer tooling and consumer software. He writes and tests the tools covered here thoroughly and regularly, and built StartupHub.ai to give founders, operators and buyers a clearer read on what they are actually being sold.

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