What are memory models in deep learning?

What are memory models in deep learning?

Memory models in deep learning refer to architectures that can store and retrieve information over time, enhancing learning.

How do these models improve performance in tasks like language processing?

They allow the model to remember previous inputs, which is crucial for understanding context in language tasks.

Can you give examples of memory models used in AI?

Sure! Examples include Long Short-Term Memory (LSTM) networks and Gated Recurrent Units (GRUs), both designed to handle sequential data.

What are the limitations of these memory models?

Limitations include difficulty in capturing long-range dependencies and increased computational complexity.