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Name: Herman E Optimizing Prompt Engineering for Generative AI 2025
Format: pdf
Size: 6.74 MB

Title: Optimizing Prompt Engineering for Generative AI
Author: Erik Herman
Language: English
Year: 2025
Subjects: N/A
Publisher: Mercury Learning and Information
ISBN: 1501523694
Total pages: 217

Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation.

With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI.