AI Could Make Better Beer. Here’s How.
upstart writes:
To compare the models, they split the data into a training set and a test set. Once a model was trained on the data within the training set, they evaluated its ability to predict the test set.
The researchers found that all the models were better than the trained panel of human experts at predicting the rating a beer had received from RateBeer.
Through these models, the researchers were able to pinpoint specific compounds that contribute to consumer appreciation of a beer: people were more likely to rate a beer highly if it contained these specific compounds. For example, the models predicted that adding lactic acid, which is present in tart-tasting sour beers, could improve other kinds of beers by making them taste fresher.
"We had the models analyze these beers and then asked them 'How can we make these beers better?'" says Kevin Verstrepen, a professor at KU Leuven and director of the VIB-KU Leuven Center for Microbiology, who worked on the project. "Then we went in and actually made those changes to the beers by adding flavor compounds. And lo and behold-once we did blind tastings, the beers became better, and more generally appreciated."
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