Models were overfit to $250k hardware. Billions of simulations trained a universal brain for $4k robots that adapts in seconds.
A robotics technology company building a general-purpose AI foundation model designed to control diverse hardware forms, from quadrupeds to humanoids, across unpredictable physical environments.
Robotics development suffers from critical data scarcity, where collecting real-world training data takes minutes per demonstration while AI systems...
General-purpose AI brain for robotics and physical world automation.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
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Reprogramming robots required weeks of expert coding. Now, staff retask machines in five minutes using a simple tablet interface.
Physical trials risked hardware damage. Simulating years of learning in hours cut dev cycles from weeks to days.
Latency made robots too slow for the real world. A multi-agent system now coordinates vision and movement at human speed.
Reprogramming robots required weeks of expert coding. Now, staff retask machines in five minutes using a simple tablet interface.
Physical trials risked hardware damage. Simulating years of learning in hours cut dev cycles from weeks to days.
Serial testing bottlenecked development. Now, parallelized checks validate hundreds of complex conversation paths in seconds.
SSetup and data analysis held back shops for weeks. AI now runs those workflows, helping merchants land their first sale in days.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.