An RIT scientist has been tapped by the National Science Foundation to solve a fundamental problem that plagues artificial neural networks. Christopher Kanan, an assistant professor in the Chester F.
The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.
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