CMU Robotics Institute AIs Learn New Tasks with Unprecedented Flexibility

TrajAir

Artificial intelligence is great at doing specific tasks. But AI algorithms tend to be inflexible, not able to pick up new jobs without extensive re-refinement. The AirLab team at Carnegie Mellon University’s Robotics Institute has used PSC’s Bridges-2 system to develop a series of approaches that can allow a robot to pick up new capabilities without such time- and computation-expensive retraining.

The post CMU Robotics Institute AIs Learn New Tasks with Unprecedented Flexibility appeared first on HPCwire.

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