Algorithm decides on chemical compromises when optimising self-driving experiments
Greek mythology inspires machine-learning approach
Scientists in Canada have devised a machine-learning algorithm for optimising chemistry experiments. The algorithm, which they tested on a self-driving laboratory, judges the chemical merit of competing variables to identify the best conditions according to the user’s preferences.