What's up in
deep learning
Latest Articles
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.
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.
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.
The Year in Biology
While the study of the SARS-CoV-2 virus was the most urgent priority, biologists also learned more about how brains process information, how to define individuality and why sleep deprivation kills.
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.
Why Is Glass Rigid? Signs of Its Secret Structure Emerge.
At the molecular level, glass looks like a liquid. But an artificial neural network has picked up on hidden structure in its molecules that may explain why glass is rigid like a solid.
Common Sense Comes Closer to Computers
The problem of common-sense reasoning has plagued the field of artificial intelligence for over 50 years. Now a new approach, borrowing from two disparate lines of thinking, has made important progress.