Transformer Architecture

The Transformer architecture is a neural network model designed for understanding and generating language. It uses mechanisms called 'attention' to weigh the importance of different words in a sentence, allowing it to capture context more effectively than previous models. Transformers process input data all at once, rather than step-by-step, which makes them highly efficient. They consist of layers that analyze relationships between words, helping the system grasp meaning, context, and nuance. This architecture underpins many advanced AI language tasks, enabling more accurate translation, summarization, and conversation capabilities.