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Architecting AI Software Systems

Architecting AI Software Systems

By : Richard D Avila, Imran Ahmad
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Architecting AI Software Systems

Architecting AI Software Systems

5 (2)
By: Richard D Avila, Imran Ahmad

Overview of this book

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.
Table of Contents (14 chapters)
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1
Architecting Fundamentals
5
Architecting AI Systems
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12
Other Books You May Enjoy
13
Index

Architecting AI Systems

The second part of the book walks you through more detailed explanations, guides, and lessons learned to build AI-enabled systems. This part of the book starts with conceptual design, one of the most critical phases led by an architect. The final chapters of this section go into more detail on the architect’s role in going from conceptual design to system testing. Finally, a case study is highlighted as a real and common challenge where an AI-enabled system can readily transform a business problem.

The following chapters are included in this section:

  • Chapter 4, Conceptual Design for AI Systems
  • Chapter 5, Requirements and Architecture for AI Pipelines
  • Chapter 6, Design, Integration, and Testing
  • Chapter 7, Architecting a Generative AI System – A Case Study
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