AI systems can sometimes forget important context, leading to errors and misunderstandings.
Understanding the order of events is crucial in various tasks such as language processing and behavior analysis.
Traditional neural networks struggle with sequences and lack the ability to retain information over time.
To address this issue, researchers developed Recurrent Neural Networks (RNNs) that can maintain internal memory of past inputs for better sequence processing.