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AuthorRichard D. Avila, Imran Ahmad

Discover how to design intelligent software systems by balancing AI and traditional architecture. This guide offers a roadmap for robust, scalable AI-enabled systems, blending principles with practical insights. Key Features Learn to integrate AI with traditional software architectures, enabling architects to design scalable, high-performance systems Explore key tools and processes to mitigate risks in AI-driven system development, ensuring timely project delivery and budget control Gain hands-on experience through case studies and exercises, applying architectural concepts to real-world AI systems Architecting AI Software Systems provides a definitive guide to building AI-enabled systems, emphasizing the balance between AI’s capabilities and traditional software architecture principles. As AI technologies gain widespread acceptance and are increasingly expected in future applications, this book provides architects and developers with the essential knowledge to stay competitive. It introduces a structured approach to mastering the complexities of AI integration, covering key architectural concepts and processes critical to building scalable and robust AI systems while minimizing development and maintenance risks. The book guides readers on a progressive journey, using real-world examples and hands-on exercises to deepen comprehension. It also includes the architecture of a fictional AI-enabled system as a learning tool. You will engage with exercises designed to reinforce your understanding and apply practical insights, leading to the development of key architectural products that support AI systems. This is an essential resource for architects seeking to mitigate risks and master the complexities of AI-enabled system development. By the end of the book, readers will be equipped with patterns, strategies and concepts necessary to architect AI-enabled systems across various domains.

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cloud nativeartificial intelligencebackend
ISBN: 1804615978
Publisher: Packt Publishing
Publish Year: 2025
Language: English
Pages: 212
File Format: PDF
File Size: 2.9 MB
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