Unlike humans, most AIs cannot simultaneously train and execute. Rather, they divide their effort into two steps: training and inference. During the training phase, the AI’s quality measurement and improvement algorithms evaluate and amend its model to obtain quality results. In the case of halicin, this was the phase when the AI identified relationships between molecular structures and antibiotic effects based on the training-set data. Then, in the inference phase, researchers tasked the AI with identifying antibiotics that its newly trained model predicted would have a strong antibiotic
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