Skild AI is developing a foundation model for robotics - a universal controller designed to operate across different robot morphologies including arms, humanoids, and quadrupeds.
Founded in 2023 by Carnegie Mellon professors Deepak Pathak and Abhinav Gupta, the company is building systems that learn from observation and adapt to new robot bodies and environments without requiring task-specific training. The technical approach centers on massive simulation combined with deep learning to create what the company describes as physically-grounded intelligence. The architecture aims to enable robots to generalize across tasks and form factors, analogous to how large language models generalize across text domains.
The company raised $300 million in Series A funding and has established partnerships with NVIDIA and Amazon. Target applications include manufacturing and logistics, where the ability to deploy a single model across different robot types could reduce the engineering overhead of task-specific programming. Technical domains span computer vision, deep learning, and robotics, with emphasis on simulation-based training methods that can scale across diverse robotic platforms.
Skild AI applies foundation model techniques to the control problem in robotics, tackling the complexity of physical interaction, real-time control constraints, and the reality gap between simulation and deployment. The company is research-driven, focused on moving algorithms from academic settings into physical systems that operate in industrial environments.