# What is Recurrent Neural Network? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Neural Architectures  
> **Canonical Citation:** [https://spidits.com/ai-glossary/recurrent-neural-network](https://spidits.com/ai-glossary/recurrent-neural-network)

## Definition
A Recurrent Neural Network (RNN) is a class of artificial neural network where connections between nodes form a directed graph along a temporal sequence, allowing it to exhibit temporal dynamic behavior and process variable-length inputs.

## Architectural Mechanics & Deep Dive
A Recurrent Neural Network (RNN) is a class of artificial neural networks designed to process sequential data. Unlike feedforward networks, RNNs possess internal memory loops that pass hidden state signals from one sequence step to the next, capturing temporal dependencies, though they can suffer from vanishing gradients on long text.

## Industry Applications & Real-World Use Cases
Legacy translation engines, time-series forecasting, and speech processing.

## Frequently Asked Questions

### What is the main limitation of standard RNNs?
The vanishing gradient problem, where gradients decay exponentially when backpropagating through long sequences, causing the network to forget early tokens.

### What architectures resolved RNN training limitations?
LSTMs (using cell gating states) and subsequently Transformers (using parallel self-attention mechanisms).

## Related Terminology
- [lstm](https://spidits.com/ai-glossary/lstm)
- [neural-network](https://spidits.com/ai-glossary/neural-network)
- [transformer](https://spidits.com/ai-glossary/transformer)

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*From the SPIDITS AI Knowledge Base (336+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*