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A New Link to an Old Model Could Crack the Mystery of Deep Learning
To help them explain the shocking success of deep neural networks, researchers are turning to older but better-understood models of machine learning.
Major Quantum Computing Strategy Suffers Serious Setbacks
So-called topological quantum computing would avoid many of the problems that stand in the way of full-scale quantum computers. But high-profile missteps have led some experts to question whether the field is fooling itself.
How Computationally Complex Is a Single Neuron?
Computational neuroscientists taught an artificial neural network to imitate a biological neuron. The result offers a new way to think about the complexity of single brain cells.
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.
Computer Scientists Discover Limits of Major Research Algorithm
The most widely used technique for finding the largest or smallest values of a math function turns out to be a fundamentally difficult computational problem.
Proof Assistant Makes Jump to Big-League Math
Mathematicians using the computer program Lean have verified the accuracy of a difficult theorem at the cutting edge of research mathematics.
The Computer Scientist Training AI to Think With Analogies
Melanie Mitchell has worked on digital minds for decades. She says they’ll never truly be like ours until they can make analogies.
Same or Different? The Question Flummoxes Neural Networks.
For all their triumphs, AI systems can’t seem to generalize the concepts of “same” and “different.” Without that, researchers worry, the quest to create truly intelligent machines may be hopeless.
What Makes Quantum Computing So Hard to Explain?
To understand what quantum computers can do — and what they can’t — avoid falling for overly simple explanations.