The information bottleneck (IB) principle is a powerful information‐theoretic framework that seeks to compress data representations while preserving the information most pertinent to a given task.

In recent years, as the field of deep learning has matured, a small but growing group of researchers and technologists has begun to question the prevailing assumptions behind neural networks. Among ...

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.

Engineers have uncovered an unexpected pattern in how neural networks -- the systems leading today's AI revolution -- learn, suggesting an answer to one of the most important unanswered questions in ...

(A) Schematic illustration of the DishBrain feedback loop, the simulated game environment, and electrode configurations. (B) A schematic illustration of the overall network construction framework. The ...

For all their brilliance, artificial neural networks remain as inscrutable as ever. As these networks get bigger, their abilities explode, but deciphering their inner workings has always been near ...