[Janelle] decided to use the char-rnn library built by [Andrej Karpathy] to do the heavy lifting. After training it on a list of over 11,000 existing tomato varieties, the neural network was then ...

In the present work, we identified an algorithmic neural substrate for modular computation through the study of multitasking artificial recurrent neural networks." The key objective of the recent ...

Starting with basic shapes like squares and triangles, the team created a recurrent neural network (RNN ... can be useful far beyond this first example.” As AI continues to shape the world ...

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...

The 1980s also saw the widespread use of the backpropagation algorithm for training the synaptic weights in both feedforward and recurrent neural ... For example, a recurrent network that is ...