Generative AI Design Patterns by Valliappa Lakshmanan (.ePUB)

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File Size: 14.4 MB

Generative AI Design Patterns: Solutions to Common Challenges When Building GenAI Agents and Applications by Valliappa Lakshmanan, Hannes Hapke
Requirements: .ePUB reader, 14.4 MB
Overview: Generative AI enables powerful new capabilities, but they come with some serious limitations that you’ll have to tackle to ship a reliable application or agent. Luckily, experts in the field have compiled a library of 32 tried-and-true design patterns to address the challenges you’re likely to encounter when building applications using LLMs, such as hallucinations, nondeterministic responses, and knowledge cutoffs. This book codifies research and real-world experience into advice you can incorporate into your projects. Each pattern describes a problem, shows a proven way to solve it with a fully coded example, and discusses trade-offs. Supervised Machine Learning (ML) involves training a problem-specific model on a large training dataset of example inputs and outputs—but GenAI applications rarely include a training phase. Instead, they commonly use general-purpose foundational models. This book is focused on design patterns for AI applications that are built on top of foundational models, such as Open AI’s GPT, Anthropic’s Claude, Google’s Gemini, or Meta’s Llama. Examples in Python.
Genre: Non-Fiction > Tech & Devices

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