Long Short-Term Memory (LSTM) is a type of artificial neural network designed to process and predict sequences of data. Unlike traditional neural networks, LSTMs can remember information for long periods, making them ideal for tasks like language translation and speech recognition. They achieve this by using special units called memory cells, which can store information and decide when to keep or forget it. LSTMs are particularly useful in applications where context is important, such as analyzing time series data or understanding the meaning of sentences. By effectively managing memory, LSTMs help computers learn from past experiences, improving their ability to make accurate predictions in various fields.