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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.

Article From: "Andrew Jolly"   Read full article »


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