Abstract:Despite numerous superhuman achievements in complex challenges, standalone AI does not free life science from the long-term bottleneck of linearly extracting new knowledge from exponentially growing new data, severely limiting the success rate of drug discovery. Inspired by the state-of-the-art AI training methods, we trained a human-centric hybrid augmented intelligence (HAI) to learn a foundation model6 that extracts all-encompassing knowledge of human physiology and diseases. To evaluate the quality of HAI'… Show more
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