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Long Short-Term Memory (LSTM)

LSTM (memoria a lungo e breve termine)

An LSTM, long short-term memory, is an advanced variant of recurrent networks, designed to remember information over much longer spans. Its secret is a memory cell regulated by 'gates', small mechanisms that decide what to keep, what to forget, and what to release at each step. It's like a diligent assistant with a notebook: they jot down important information, erase what's become useless, and consult their notes when needed, avoiding forgetting crucial facts from much earlier. This mechanism largely solves the vanishing-gradient problem typical of classic RNNs.

Definition

For years LSTMs were the standard for translation, speech recognition, time-series forecasting, and text generation. Though surpassed by transformers on many language tasks, they remain competitive and efficient when data is sequential, resources are limited, or sequences aren't too long, and are still widely used in industry.

Related terms

• Recurrent Neural Network (RNN)
• Transformer
• Attention Mechanism
• Deep Learning
• Neural Network

More in Fondamenti AI

• LLM (Large Language Model)
• Token
• Context Window
• Temperature
• AI Hallucination
• Fine-tuning
• RAG (Retrieval Augmented Generation)
• Embedding

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