For all their power, neural networks have a huge problem that needs to be overcome: how they work is a mystery.

Google has designed a new open-source library intended to crack open the black box of machine learning and give engineers more insight into how their machine learning systems operate. As reported by VentureBeat, the Google research team says that the library could grant “unprecedented” insight into how machine learning models operate.

According to Google research engineer Roman Novak and senior research scientist at Google, Samuel S. Schoenholz, the width of models is tightly correlated with regular, repeatable behavior. In a blog post, the two researchers explained that making neural networks wider makes their behavior more regular and easier to interpret.

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