Generative AI Design Patterns: Solutions to Common Challenges When Building GenAI Agents and Applications - Tapa blanda
Sinopsis
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 are already hard at work compiling a library of tried-and-true design patterns to address the challenges you're likely to encounter when building applications using LLMs and other GenAI models--hallucinations, nondeterministic answers, and knowledge cutoffs among them. You'll find 31 of the most essential here.
Authors Valliappa Lakshmanan and Hannes Hapke codify advances in research and real-world experience into advice that you can readily incorporate into your projects. Each detailed explanation includes a description of the problem, a proven pattern to solve it, an example, and a discussion of potential trade-offs. Whether you read it cover to cover for inspiration or use it as a daily reference, this practical guide will help you troubleshoot whatever problems may arise.
- Design around the limitations of LLMs, such as hallucination and nondeterminism
- Force LLMs to generate text that follows a specific style or grammar
- Maximize creativity while balancing different types of risk
- Extend the capability of an LLM beyond just content creation
- Use patterns together to solve a variety of different use cases
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Valliappa (Lak) Lakshmanan works closely with management teams across a range of enterprises to help them employ data and AI-driven innovation to grow their businesses. Previously, he was the Director for Data Analytics and AI Solutions on Google Cloud and a Research Scientist at NOAA. He co-founded Google's Advanced Solutions Lab and is the author of several O'Reilly books and Coursera courses. He was elected a Fellow of the American Meteorological Society (the highest honor offered by the AMS) for pioneering machine learning algorithms in severe weather prediction.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Paperback. Condición: new. Paperback. 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.Design around the limitations of LLMsEnsure that generated content follows a specific style, tone, or formatMaximize creativity while balancing different types of riskBuild agents that plan, self-correct, take action, and collaborate with other agentsCompose patterns into agentic applications for a variety of use cases 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798341622661
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Paperback. Condición: New. 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.Design around the limitations of LLMsEnsure that generated content follows a specific style, tone, or formatMaximize creativity while balancing different types of riskBuild agents that plan, self-correct, take action, and collaborate with other agentsCompose patterns into agentic applications for a variety of use cases. Nº de ref. del artículo: LU-9798341622661
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Paperback. Condición: New. 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.Design around the limitations of LLMsEnsure that generated content follows a specific style, tone, or formatMaximize creativity while balancing different types of riskBuild agents that plan, self-correct, take action, and collaborate with other agentsCompose patterns into agentic applications for a variety of use cases. Nº de ref. del artículo: LU-9798341622661
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