1/ Better robot models come from better data.
That takes two things: hardware that captures it fully, and tooling that turns it into training signal.
We built the first. Today, @GroundedSI launches the second: Grounded API. Access both hardware + API ↓
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Earth Rover Mini+ spotted in-the-wild with @Meta Muse on board, building its own perception-to-action stack 🤯
Muse was told to find a black ball. So it installed PyTorch + Depth Anything itself, estimated the distance, then drove the rover.
Agentic robotics is getting real.
We’re building human-centric robotics from the data layer up, the missing piece for generalist robots.
RoboCap + Grounded API turn raw human action into metric 3D labels ready for training.
The hardware and the tooling have always been fragmented. We built them as one stack ↓
Great way to scale real world data for humanoid robotics
The only way that LLM scaling laws apply is if there is enough data, and this is how you solve the data bottleneck
Congratulations @micoolcho and team!!