What is a Transformer (AI Architecture)?

The Engine Behind Large Language Models and Generative AI

Understanding Self-Attention and Parallel Processing

Revolutionizing Natural Language Processing and Beyond

The **Transformer** is a groundbreaking neural network architecture introduced in 2017 that has become the **backbone of nearly all modern Large Language Models (LLMs)** and much of **generative AI**. Its key innovation lies in its **self-attention mechanism**, which allows the model to weigh the importance of different words (or parts of data) when processing a sequence, regardless of their position. This enables highly parallel processing and better handling of long-range dependencies in data, overcoming limitations of previous architectures like RNNs. Transformers have revolutionized natural language processing (NLP) and are now applied across various modalities, continuing to drive AI advancements in 2025. 🔄🧠