What's up in
Neuron Bursts Can Mimic Famous AI Learning Strategy
A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI.
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.
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.
Latest Neural Nets Solve World’s Hardest Equations Faster Than Ever Before
Two new approaches allow deep neural networks to solve entire families of partial differential equations, making it easier to model complicated systems and to do so orders of magnitude faster.
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.
Artificial Neural Nets Finally Yield Clues to How Brains Learn
The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could.
Deep Neural Networks Help to Explain Living Brains
Deep neural networks, often criticized as “black boxes,” are helping neuroscientists understand the organization of living brains.
Complexity Scientist Beats Traffic Jams Through Adaptation
To tame urban traffic, the computer scientist Carlos Gershenson finds that letting transportation systems adapt and self-organize often works better than trying to predict and control them.