What is memory in neural networks?

What is memory in neural networks?

Memory in neural networks refers to the ability of the network to retain information from previous inputs, allowing it to make informed predictions based on past experiences.

How do recurrent neural networks utilize memory?

Recurrent neural networks (RNNs) use memory by maintaining a hidden state that captures information from previous time steps, enabling them to process sequences of data.

Can you explain the difference between short-term and long-term memory in this context?

Short-term memory in neural networks typically refers to immediate past inputs, while long-term memory retains information over longer periods, often managed by architectures like LSTMs.

What are some applications of memory in neural networks?

Applications include natural language processing, time series prediction, and any task requiring sequential data analysis.