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AI Glossary

What is Attention Mechanism?

How AI models focus on relevant parts of input when generating output.

By Council Research TeamUpdated: Jan 27, 2026

Definition

Attention allows transformers to weigh the importance of different input tokens when producing each output token. Self-attention enables the model to understand relationships between all parts of the input simultaneously.

Examples

1Understanding that "it" refers to "the cat" in a sentence
2Focusing on relevant code when debugging
3Connecting questions to their context

Why It Matters

Attention is why AI can understand context and relationships in text—it's the core innovation behind modern language models.

Related Terms

Transformer (Architecture)

The neural network architecture behind modern AI like GPT and Claude.

Token (AI)

A chunk of text (roughly 4 characters or 3/4 of a word) that AI models process.

Context Window

The maximum amount of text an AI can process in a single conversation.

Common Questions

What does Attention Mechanism mean in simple terms?

How AI models focus on relevant parts of input when generating output.

Why is Attention Mechanism important for AI users?

Attention is why AI can understand context and relationships in text—it's the core innovation behind modern language models.

How does Attention Mechanism relate to AI chatbots like ChatGPT?

Attention Mechanism is a fundamental concept in how AI assistants like ChatGPT, Claude, and Gemini work. For example: Understanding that "it" refers to "the cat" in a sentence Understanding this helps you use AI tools more effectively.

Related Use Cases

Best AI for Coding

Best AI for Writing

AI Models Using This Concept

ClaudeClaudeChatGPTChatGPTGeminiGemini

See Attention Mechanism in Action

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