Large language models (LLMs) and diffusion models, such as ChatGPT and Stable Diffusion, have unparalleled potential. They have been trained on all the public texts and images on the internet, offering valuable contributions to a wide range of tasks. By lowering the entry barrier, any developer can now leverage LLMs and diffusion models to tackle problems that were previously unsuitable for automation.

This book provides a solid foundation in generative artificial intelligence, including practical applications of these models. When developers begin to integrate LLMs and diffusion models into their workflows, they often face challenges in ensuring reliable results. Authors James Phoenix and Mike Taylor demonstrate how a set of principles, known as prompt engineering, can help you collaborate effectively with artificial intelligence.

Learn how to empower artificial intelligence to work for you. This book explains:

• The structure of the interaction between your application's AI model and the detailed steps between them
• How the AI model's requests arise from converting your application's problem into a document completion problem in the model's training domain
• The influence of LLM architecture and the diffusion model - and how to interact better with it
• How these principles apply in practice to the fields of natural language, text and image generation, and code

Pages: 396, Dimensions: 17.8x17.8cm