Right now machine-learning algorithms can simulate robots performing complex maneuvers to find the most efficient process. Over time, BMW wants to use the simulation to have robots learn how to perform increasingly complex jobs. (From 2021)
, which involves an algorithm experimenting and learning, from positive feedback, how to achieve a specific goal., a professor at Carnegie Mellon University who focuses on AI and digital simulations. Zhao says simulations are crucial to using AI for industrial applications, partly because it is impossible to run machines through millions of cycles to gather training data.
“In the future, we can just put a new robot in this facility, and say, ‘OK, talk with the other robots and find the best way to produce this body.’”, a professor at Harvard Business School who specializes in manufacturing technology, says the sophistication of simulation has been increasing steadily, and he says simulation primarily saves time and money by preempting future manufacturing problems.
Shih says there is plenty of hype around AI for manufacturing but adds, “There are lots and lots of applications” for the technology too. Nvidia CEO Jensen Huang discussed BMW’s use of Omniverse during his keynote at the company's annual GTC conference, held virtually on Monday. Nvidia initially made graphics chips for gaming but broadened its focus when these chips proved adept at training AI programs. The company has since leapt into several other industries where AI is important, including automotive and medical imaging.
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