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Webinar | Applied Materials

Science at Work: Changing the game for Artificial Intelligence with neuromorphic computing

Abstract: Artificial Intelligence is transforming science and society. It powers voice-activated digital assistants, guides self-driving cars, and recognizes our faces. But AI is fragile. Types of AI such as machine learning or neural networks need reams of data to learn and perform well. And if you swap one set of data with another, those techniques might falter.

We need AI to withstand the elements. But this will require us to turn AI on its artificial head. Can we help AI adapt to new and extreme environments – in space, inside nuclear power plants, or anywhere temperatures exceed 500 degrees Fahrenheit?

In this webinar, Angel Yanguas-Gil, principal materials scientist at Argonne, will discuss how his discoveries can allow AI to perform and adapt better than conventional methods and use much less power – less than one watt. Yanguas-Gil will show how a newly designed neuromorphic computer chip can reduce power by one order of magnitude without sacrificing accuracy. To do this, his team drew on new materials, designs, and hardware.