AI Glossary

What is Transformer (Architecture)?

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

By Council Research TeamUpdated: Jan 27, 2026

Definition

Transformers, introduced in the "Attention Is All You Need" paper (2017), use self-attention mechanisms to process sequences efficiently. This architecture enables models to understand context across long texts and powers virtually all modern LLMs.

Examples

1GPT (Generative Pre-trained Transformer)

2BERT

3Claude's underlying architecture

Why It Matters

Transformers are why modern AI understands context so well. The architecture breakthrough enabled the current AI revolution.

Related Terms

Large Language Model (LLM)

An AI system trained on vast text data to understand and generate human-like text.

Attention Mechanism

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

Token (AI)

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

Common Questions

What does Transformer (Architecture) mean in simple terms?

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

Why is Transformer (Architecture) important for AI users?

Transformers are why modern AI understands context so well. The architecture breakthrough enabled the current AI revolution.

How does Transformer (Architecture) relate to AI chatbots like ChatGPT?

Transformer (Architecture) is a fundamental concept in how AI assistants like ChatGPT, Claude, and Gemini work. For example: GPT (Generative Pre-trained Transformer) Understanding this helps you use AI tools more effectively.