In the previous chapter, we learned various strategies to guide AI models 'down the mountain' (optimization algorithms), such ...

A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI.

The most common technique used to train neural networks is the back-propagation algorithm. Back propagation requires a value for a parameter called the learning rate. The effectiveness of back ...

Backpropagation is not limited to function derivatives. Any algorithm that effectively takes the loss function and applies gradual, positive changes back through the network is valid.

A new technical paper titled “The backpropagation algorithm implemented on spiking neuromorphic hardware” was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal ...

AI transforms RF engineering through neural networks that predict signal behavior and interference patterns, enabling ...

Blame is the main game when it comes to learning. I know that sounds bizarre, but hear me out. Neural circuits of thousands, if not more, neurons control every single one of your thoughts, reasonings, ...