Language:
English
Pages:
1 online resource (396 pages)
,
illustrations
Edition:
First edition.
DDC:
006.3/5
Keywords:
Natural language generation (Computer science)
;
Artificial intelligence Computer programs
;
Natural language processing (Computer science)
;
Génération automatique de texte
;
Intelligence artificielle ; Logiciels
;
Traitement automatique des langues naturelles
Abstract:
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.
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