Long Short-Term Memory (LSTM) is a term from Artificial Intelligence and Big Data. LSTMs are special types of artificial neural networks that are particularly good at recognising patterns in data series that extend over longer periods.
Imagine you want to predict revenue for the coming months based on past sales figures. Traditional methods struggle with this because they often only consider current figures. LSTMs work differently: they remember important information from the past, and can therefore better predict what will happen next.
Typical application areas include demand forecasting, speech recognition, or the automatic detection of fraud patterns in financial data. Long Short-Term Memory networks particularly show their strengths in tasks where processes or changes over time are important.
An everyday example: Voice assistants such as Siri or Alexa use LSTM models to correctly understand spoken sentences – because they track the context of individual words within a sentence. This makes LSTMs a key technology for many modern digital applications.
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