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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.
The Computer Scientist Peering Inside AI’s Black Boxes
Cynthia Rudin wants machine learning models, responsible for increasingly important decisions, to show their work.
Self-Taught AI Shows Similarities to How the Brain Works
Self-supervised learning allows a neural network to figure out for itself what matters. The process might be what makes our own brains so successful.
Will Transformers Take Over Artificial Intelligence?
A simple algorithm that revolutionizes how neural networks approach language is now taking on image classification as well. It may not stop there.
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.
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.
An Idea From Physics Helps AI See in Higher Dimensions
The laws of physics stay the same no matter one’s perspective. Now this idea is allowing computers to detect features in curved and higher-dimensional space.