Dream Labs Raises $90M Seed to Bring Robot AI Across Different Machines

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Dream Labs, a startup founded by former NVIDIA robotics researchers, has raised $90 million in seed funding and launched a public API for Dream-1, a model designed to carry skills across different robots. The financing was led by B Capital alongside Kindred Ventures, with participation from A.Capital, Unusual Ventures and other investors.

The company is tackling a costly bottleneck in robotics: a machine that learns a task does not automatically pass that knowledge to a different machine. Dream Labs wants developers to start with a shared model, then adapt it when a particular robot or application requires more specialized training.

The launch includes an API, a fine-tuning service and a browser-based Robot Playground. The latter lets users send instructions to physical robots in the company’s San Francisco office. Dream Labs says the funding will primarily support compute as it expands model capabilities and capacity.

Dream Labs calls Dream-1 a World Action Model. Its technical account of the launch describes a system that predicts video and actions together: anticipating how a scene will change is linked to deciding what a robot should do next.

The distinction matters because robot bodies differ. Joint commands that work on one arm will not necessarily work on another. Dream-1 can instead predict end-effector poses—the desired position and orientation of each gripper, along with whether it should be open or closed. Each robot’s inverse-kinematics solver translates those targets into movements its own joints can execute.

That provides a common interface across machines without requiring them to share identical hardware. The model uses three camera views: one looking at the scene and one on each wrist. Its video representation gives it a way to reason about different-looking arms and grippers through the same visual medium.

For developers, the product packages that research into a relatively direct loop.