Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

AI"s inability to continually learn remains one of the biggest problems standing in the way to truly general purpose models.

Previously met with skepticism, AI won scientists a Nobel Prize for Chemistry in 2024 after they used it to solve the protein folding and design problem, and it has now been adopted by biologists ...

Continual learning in neural networks addresses the challenge of adapting to new information accumulated over time while retaining previously acquired knowledge. A central obstacle to this process is ...

For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...

The ability to precisely predict movements is essential not only for humans and animals, but also for many AI applications - from autonomous driving to robotics. Researchers at the Technical ...

What if AI could keep learning like a human brain, in new conditions even after it was used, deployed & put to use in real life? A Liquid Neural Network (LNN) is a new type of artificial intelligence ...

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...