Lane B · Robotics

Sinewgrid Motion trains policies that move real hardware.

Sinewgrid Motion trains vision-language-action policies for manipulation and whole-body control. Pretraining draws on video and simulation at scale. Post-training uses demonstrations and reinforcement learning on tasks that can be measured on real robots.

TeleoperationScarce, exact actions

Human videoBroad, no action labels

SimulationAbundant, imperfect physics

Illustrative ordering of data volume. Not measured values.

PretrainVideo and simulation
ImitateTeleoperated episodes
Post-trainReinforcement learning
EvaluateHeld-out real tasks

FIG. 3 · Simulated arm solving inverse kinematics for a pick-and-place task. Schematic.

Planning a training run?

Tell us the model, the data and the schedule. We reply with a capacity plan and the evidence behind it.

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