What could go wrong?

Over the next few months, an artificial intelligence algorithm will gradually take over the planning of experiments based on the battery test runs. Once fully functioning, this robot graduate student will decide how to modify the concentrations of the ingredients it’s testing. “It’s automating not only the manual part of doing the experiment but also the planning part,” says Brian Storey, the Toyota Research Institute scientist leading the project.

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Science has long been considered one of the human activities least likely to be farmed out to robots. That’s changing as sensors, sequencers, and satellites churn out digital information by the terabyte. “We just cannot handle the amount of data anymore,” says Manuela Veloso, who heads Carnegie Mellon’s machine learning department. It’s a daily concern for biotech companies and a wide range of other businesses struggling to make sense of the unprecedented swell of raw information.

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