technologyScore 60/100Watch
Imitation learning via demonstration (teaching robot by hand) replacing months of engineering; data collected and trained in cloud, deployed locally
Jensen Huang· NVIDIA· AI· 2026-05-27· about Seed Studio, NVIDIA (NVDA)
“Previously you need to spend months of trainings to understand the spatial planning on the robots, how it moves... But now what you do with the robots is after they're setting up you train it. Like you train a dog. You teach it how to do it with like holding its hand to do the operations for several times. Then you send all the data back to train on the cloud and deploy on a JSON.”
Why it matters
Imitation learning model reduces engineering time from months to days/weeks, enabling rapid robot customization for domain-specific tasks. Creates recurring data-collection and training workloads.
Investment implication
High-volume demand for cloud GPU capacity for robotics model training. Data pipeline and annotation tools become critical. Companies like Scale AI, Labelbox, or cloud GPU providers (Lambda Labs, CoreWeave) benefit.