Transformer Architecture
The Transformer architecture is a deep learning model primarily used for processing sequential data, most notably in natural language processing (NLP). It introduced the 'attention mechanism,' which allows the model to weigh the importance of different parts of the input sequence when processing each element. This ability to focus on relevant context across long sequences makes it highly effective.
It's like a student who can quickly identify and focus on the most important sentences in a long text to understand its core meaning, rather than reading every word with equal attention.
Transformers revolutionized NLP and power many state-of-the-art AI models, including Large Language Models, due to their efficiency and ability to handle long-range dependencies in data.
Learn one new AI thing every day.
Daily Deck sends you seven plain-English cards like this every morning. Free.
Start free