Orbital AI data centers face four engineering gaps with no demonstrated solutions: radiation hardening at compute density scale, thermal management in vacuum, in-orbit repair infeasibility, and continuous power availability in LEO

SpaceX's S-1 filing identifies four specific engineering challenges that lack demonstrated solutions at orbital data center scale. First, radiation hardening: no radiation-hardened chips exist for the compute density needed at data center scale. Terafab's D3 chips would be the first attempt, making them unproven. Second, thermal management: Earth data centers rely on liquid cooling and outside air, but LEO vacuum requires radiators and heat pipes for heat rejection — the S-1 calls this 'one of the hardest challenges' in orbit. Third, in-orbit repair: the S-1 states repair is 'infeasible' with current approaches, meaning every component must be radiation-hardened, redundant, or disposable, with failed hardware becoming debris or requiring expensive deorbit. Fourth, continuous power: Musk's orbital AI thesis rests on 5x solar irradiance advantage, but satellites in LEO are only in sunlight approximately 60% of orbit, requiring storage for continuous compute. These are not generic risks — they are specific, measurable engineering constraints. The S-1's legal language ('remain untested and may not perform reliably in orbit') indicates these are not solved problems being refined, but fundamental gaps without demonstrated solutions. Each constraint is falsifiable: radiation hardening can be tested, thermal management can be measured, repair capability can be demonstrated, and power continuity can be validated. The absence of solutions across all four simultaneously creates compounding risk.