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Machine learning
Latest Articles
Where We See Shapes, AI Sees Textures
To researchers’ surprise, deep learning vision algorithms often fail at classifying images because they mostly take cues from textures, not shapes.
How Artificial Intelligence Is Changing Science
The latest AI algorithms are probing the evolution of galaxies, calculating quantum wave functions, discovering new chemical compounds and more. Is there anything that scientists do that can’t be automated?
Foundations Built for a General Theory of Neural Networks
Neural networks can be as unpredictable as they are powerful. Now mathematicians are beginning to reveal how a neural network’s form will influence its function.
A New Approach to Understanding How Machines Think
Neural networks are famously incomprehensible, so Been Kim is developing a “translator for humans.”
Machine Learning Confronts the Elephant in the Room
A visual prank exposes an Achilles’ heel of computer vision systems: Unlike humans, they can’t do a double take.
New AI Strategy Mimics How Brains Learn to Smell
Machine learning techniques are commonly based on how the visual system processes information. To beat their limitations, scientists are drawing inspiration from the sense of smell.
A Poet of Computation Who Uncovers Distant Truths
The theoretical computer scientist Constantinos Daskalakis has won the Rolf Nevanlinna Prize for explicating core questions in game theory and machine learning.
How Artificial Intelligence Can Supercharge the Search for New Particles
In the hunt for new fundamental particles, physicists have always had to make assumptions about how the particles will behave. New machine learning algorithms don’t.
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.