01578nam a22002297a 4500 20260709110011.0 260709s2024 |||||||| |||| 00| 0 eng d 9781098153434 PK-LaUMT 006.35 PHO-P Phoenix, James 13455 Prompt engineering for generative AI : future-proof inputs for reliable AI outputs at scale / James Phoenix and Mike Taylor Beijing : O'Reilly, 2024 xvii, 401 p. Index present "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." -- Amazon.com Eng Artificial intelligence Computer programs 8923 AI-computer program 13456 Taylor, Mike 13457 BK 141348 141348 0 0 0 0 01 01 2026-07-09 0 006.35 PHO-P 153272 2026-07-09 11:00:27 2026-07-09 BK