Recent progress in machine learning has raised a series of urgent questions: How can we train and debug deep learning models? How can we understand what is going on inside a neural network? And, perhaps most important, how can we design systems that serve people best? We'll show a series of examples from the People+AI Research (PAIR) initiative at Google–ranging from data visualizations for researchers, to tools for medical practitioners, to guidelines for designers–that illustrate how thinking carefully about data can lead to better tools, more effective design, and help humans and AI work together.

Tags: google

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