Transformer

A neural network architecture that revolutionized AI by allowing models to process sequences of data simultaneously rather than sequentially, making modern LLMs possible. The key innovation is the 'attention mechanism' that lets the model focus on different parts of the input at once, understanding how words relate to each other across an entire sentence or document. It's like reading a book where you can instantly reference any previous chapter while understanding the current page, rather than only remembering the previous sentence. This parallel processing makes transformers incredibly efficient and powerful, enabling them to understand context, nuance, and long-range dependencies in text that previous architectures couldn't handle effectively.