Transformer
A Transformer is a deep learning model architecture for processing sequential data such as text. Using a technique called attention, the model can focus on all parts of the input at once, so it understands and generates content more effectively.
How it works
At its core is self-attention, which lets the model weigh the importance of every other word in a sentence as it processes each word. This is more efficient than earlier word-by-word models (such as RNNs) and captures long-range dependencies. The Transformer architecture underpins many of today's advanced AI models (such as GPT and BERT) and has driven major progress in natural language processing and related fields.
Examples
- 1.Powering chatbots like ChatGPT for conversation and text generation
- 2.Enabling more accurate machine translation in tools like Google Translate
- 3.Helping programmers autocomplete code in coding assistants like GitHub Copilot