An artificial intelligence system enables robots to conduct autonomous scientific experiments — as many as 10,000 per day — potentially driving a drastic leap forward in the pace of discovery in areas from medicine to agriculture to environmental science.
That artificial intelligence platform, dubbed BacterAI, mapped the metabolism of two microbes associated with oral health — with no baseline information to start with. Bacteria consume some combination of the 20 amino acids needed to support life, but each species requires specific nutrients to grow. The U-M team wanted to know what amino acids are needed by the beneficial microbes in our mouths so they can promote their growth.
o find the right formula for each species, BacterAI tested hundreds of combinations of amino acids per day, honing its focus and changing combinations each morning based on the previous day’s results. Within nine days, it was producing accurate predictions 90% of the time.
Unlike conventional approaches that feed labeled data sets into a machine-learning model, BacterAI creates its own data set through a series of experiments. By analyzing the results of previous trials, it comes up with predictions of what new experiments might give it the most information. As a result, it figured out most of the rules for feeding bacteria with fewer than 4,000 experiments.
The applications go beyond microbiology. Researchers in any field can set up questions as puzzles for AI to solve through this kind of trial and error.
Source: science daily
