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Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs

Contributor(s): Phoenix, James (Author), Taylor, Mike (Author)

ISBN: 9781098153434

Publisher: O'Reilly Media

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$79.99
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Pub Date: June 25, 2024

Dewey: 006.35

LCCN: 2024391019

Lexile Code: 0000

Features: Illustrated, Index, Price on Product

Target Age Group: NA to NA

Physical Info: 0.86" H x 9.19" L x 7.00" W ( 1.47 lbs) 422 pages

Descriptions, Reviews, etc.

Description: 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. --

Brief description: Mike Taylor built and ran a 50-person marketing agency, including working on innovation projects with Unilever, Nestle, and Facebook. Over 300,000 people have taken his marketing courses on LinkedIn Learning.

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