New AI approach bridges the 'slim-data gap' that can stymie deep learning approaches

Scientists have developed a deep neural network that sidesteps a problem that has bedeviled efforts to apply artificial intelligence to tackle complex chemistry—a shortage of precisely labeled chemical data. The new method gives scientists an additional tool to apply deep learning to explore drug discovery, new materials for manufacturing, and a swath of other applications.

from News on Artificial Intelligence and Machine Learning https://ift.tt/2GM2PT8

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