What is a transformer in gen AI?

Transformers, a type of neural network architecture, are pivotal in enabling machines to understand and generate human language, playing a crucial role in natural language processing tasks such as machine translation, text summarization, and question answering. Their ability to grasp relationships between words and phrases, even when distant in a sentence, is facilitated by an attention mechanism, allowing them to focus on relevant parts of text based on context. Comprising two main components—the encoder, which converts input text into numeric representations, and the decoder, which generates text from these representations—transformers utilize self-attention to determine word importance and an autoregressive layer in the decoder for word prediction. This technology has been instrumental in various applications, including language translation, chatbots, text summarization, content creation, sentiment analysis, and code completion, significantly impacting industries by making processes more efficient and interactions more natural. As research advances, transformers are expected to become even more sophisticated and ubiquitous, continuing to drive the integration of artificial intelligence into everyday technology and transforming how we work and communicate.