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.

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.

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. The 2024 Nobel Prize in physics has been awarded to two scientists who laid the foundations for ...