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Robots will train faster in simulation than on real hardware
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Antioch's Series A is a bet that robots learn faster in software. Software teams ship a change, run the tests, and know within minutes whether it worked. Physical AI teams have spent years waiting on hardware, because every new perception model meant another fleet run, another sensor rig, another week of collecting data on a real road or a real farm. That gap is the whole company. Antioch's pitch is that the fleet moves into simulation. Spin up many virtual copies of the machine with…
antiochrobotics@antiochroboticsSep 8
Today, we’re announcing Antioch’s $32 million Series A, led by @GreylockVC with participation from @A_StarVC, @Category_VC, @BoxGroup, @IcehouseVenture, and angels. While AI has drastically accelerated software development, physical autonomy has been constrained by slow, expensive hardware-based development. Antioch enables physical AI teams to build, test, and validate systems at the speed of software. We’re proud to be working with leading teams including @amazon @ring, @NVIDIARobotics, and @nebiusai as we make scaled, high-fidelity simulation the standard for physical AI development. Our sincere thanks to the legion of investors, customers, partners, and advisors who are making this step change possible. We’re scaling rapidly and hiring across simulation, infrastructure, machine learning, 3D graphics, go-to-market, and operations.