The promise of physical AI is that engineers will be able to program physical agents the same way they do digital ones.
We’re not there yet. Robotics is still held back by a paucity of data from physical spaces. To train their machines, companies need to build mock-up warehouses to test their machines, while an entire industry is springing up around surveilling factory lines and gig workers to train deep learning models to operate robots.
Another option is simulation; detailed virtual replicas of real-world environments could provide the data and workspaces that roboticists need to do this work in a scalable way.
Antioch, a startup building simulation tools for robot developers, wants to close what the industry calls the sim-to-real gap — the challenge of making virtual environments realistic enough that robots trained inside them can operate reliably in the physical world.
“How can we do the best possible job reducing that gap, to make simulation feel just like the real world from the perspective of your autonomous system?” Antioch cofounder Harry Mellsop said.
To do that, the company told TechCrunch today that it has raised an $8.5 million seed round that values it at $60 million, led by venture firm A* and Category Ventures, with additional participation from MaC Venture Capital, Abstract, Box Group, and Icehouse Ventures.
Mellsop started the New York-based company with four cofounders in May of last year. Two of the other founders, Alex Langshur and Michael Calvey, joined him to cofound Transpose, a security and intelligence startup, and sell it to Chainalysis for an undisclosed amount. The other two — Collin Schlager and Colton Swingle — previously worked at Meta Reality Labs and Google DeepMind, respectively.
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