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Can I read Generative AI Application Integration Patterns: Integrate large language models into your applications on EtoBox?

Generative AI Application Integration Patterns: Integrate large language models into your applications by Juan Pablo Bustos, Luis Lopez Soria is a nonfiction available to read on EtoBox.

What is Generative AI Application Integration Patterns: Integrate large language models into your applications about?

Unleash the transformative potential of GenAI with this comprehensive guide that serves as an indispensable roadmap for integrating large language models into real-world applications. Gain invaluable insights into identifying compelling use cases, leveraging state-of-the-art models effectively, deploying these models into your applications at scale, and navigating ethical considerations. Key Features • Get familiar with the most important tools and concepts used in real scenarios to design GenAI apps • Interact with GenAI models to tailor model behavior to minimize hallucinations • Get acquainted with a variety of strategies and an easy to follow 4 step frameworks for integrating GenAI into applications Book Description Explore the transformative potential of GenAI in the application development lifecycle. Through concrete examples, you will go through the process of ideation and integration, understanding the tradeoffs and the decision points when integrating GenAI. With recent advances in models like Google Gemini, Anthropic Claude, DALL-E and GPT-4o, this timely resource will help you harness these technologies through proven design patterns. We then delve into the practical app

Who reads Generative AI Application Integration Patterns: Integrate large language models into your applications?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Juan Pablo Bustos, Luis Lopez Soria
Publisher
Packt Publishing
Published
2024
Language
EN
ISBN
9781835887608
Category
nonfiction
Subjects
Computer Science, Stem

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