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Neural Networks Need Data to Learn. Even If It’s Fake.
Real data can be hard to get, so researchers are turning to synthetic data to train their artificial intelligence systems.
Sparse Networks Come to the Aid of Big Physics
A novel type of neural network is helping physicists with the daunting challenge of data analysis.
The Computer Scientist Peering Inside AI’s Black Boxes
Cynthia Rudin wants machine learning models, responsible for increasingly important decisions, to show their work.
The Researcher Who Would Teach Machines to Be Fair
Arvind Narayanan uses quantitative methods to expose and correct the misuse of quantitative methods.
How Big Data Carried Graph Theory Into New Dimensions
Researchers are turning to the mathematics of higher-order interactions to better model the complex connections within their data.
A Computer Scientist Who Tackles Inequality Through Algorithms
Rediet Abebe uses the tools of theoretical computer science to understand pressing social problems — and try to fix them.
The Computer Scientist Who Shrinks Big Data
Jelani Nelson designs clever algorithms that only have to remember slivers of massive data sets. He also teaches kids in Ethiopia how to code.
Prepping for a Flood of Heavenly Bodies
Mario Jurić is leading the push to get astronomy ready for the torrents of data that are about to flow.
To Build Truly Intelligent Machines, Teach Them Cause and Effect
Judea Pearl, a pioneering figure in artificial intelligence, argues that AI has been stuck in a decades-long rut. His prescription for progress? Teach machines to understand the question why.