How GenAI Works

GenAI is made possible by enormous datasets that teach AI models how to respond to user-provided prompts. These models find commonalities between similar types of data and use this information to generate new content. Data scientists and subject-matter experts can refine the algorithm’s learning by reviewing its outputs and associated prompts.

GenAI solutions take advantage of LLMs that use deep neural networks to process and generate novel text. These models are trained on large amounts of text data and are designed to deliver meaningful outputs. LLMs rely on transformer models to process input sequences in a parallel fashion, which improves performance and speed compared to traditional neural networks.