Tesla’s key innovation allows Optimus to scale task learning rapidly using third-person video footage
Tesla just released footage of Optimus performing tasks autonomously such as taking out the garbage, cleaning using a dustpan, cooking and vacuuming etc. This was achieved by teaching Optimus the tasks by watching first-person video of a human operator performing the task.
But a recent breakthrough in scaling Optimus’s learning capabilities is set to fast track Optimus’s ability to learn new tasks quickly.
Tesla’s breakthrough was discovering humanoid robots can be taught a large volume of new tasks quickly by learning from watching third-person video footage of humans performing the required tasks. Tesla discovered this approach is much more successful at enabling Optimus to learn quickly than attempting to use teleoperation or first-person video alone.
How does third-person video learning work with Optimus? Optimus’s neural network processes third-person videos to map human actions to its movements. This involves computer vision to interpret perspectives, deep learning to extract task sequences, and reinforcement learning to refine actions in real or simulated environments. The system builds on Tesla’s FSD tech, using multi-camera neural networks for perception.
Third-person videos are less controlled than first-person demos, with issues like occlusions, varying angles, and inconsistent quality. Tesla’s breakthrough involves overcoming these to extract reliable task data, though full autonomy from such videos is still developing.
Musk shares some insights on how Tesla plans to go about building Optimus’s AI using this new approach:
Insight from the leader of the Tesla Bot team regarding this new training method:
Summary of these new developments by The Humanoid Hub:
Tesla just released footage of Optimus performing tasks autonomously such as taking out the garbage, cleaning using a dustpan, cooking and vacuuming etc. This was achieved by teaching Optimus the tasks by watching first-person video of a human operator performing the task.
But a recent breakthrough in scaling Optimus’s learning capabilities is set to fast track Optimus’s ability to learn new tasks quickly.
Tesla’s breakthrough was discovering humanoid robots can be taught a large volume of new tasks quickly by learning from watching third-person video footage of humans performing the required tasks. Tesla discovered this approach is much more successful at enabling Optimus to learn quickly than attempting to use teleoperation or first-person video alone.
How does third-person video learning work with Optimus? Optimus’s neural network processes third-person videos to map human actions to its movements. This involves computer vision to interpret perspectives, deep learning to extract task sequences, and reinforcement learning to refine actions in real or simulated environments. The system builds on Tesla’s FSD tech, using multi-camera neural networks for perception.
Third-person videos are less controlled than first-person demos, with issues like occlusions, varying angles, and inconsistent quality. Tesla’s breakthrough involves overcoming these to extract reliable task data, though full autonomy from such videos is still developing.
Musk shares some insights on how Tesla plans to go about building Optimus’s AI using this new approach:
Insight from the leader of the Tesla Bot team regarding this new training method:
Summary of these new developments by The Humanoid Hub:
