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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
12
Other Books You May Enjoy
13
Index

Summary

This chapter has explored the critical journey from architectural concepts to functioning AI systems through design, integration, and testing. Much like a musical composition that remains theoretical until performed, AI architectures must be realized through thoughtful design decisions, systematic integration approaches, and comprehensive testing strategies to deliver their intended value.

The Design fundamentals section established how requirements, use cases, and system modes form the foundation for translating architectural vision into concrete components. The use case diagram (Figure 6.1) illustrated the complex interactions between diverse stakeholders and system functionality, while the system modes state diagram (Figure 6.2) mapped the operational states an AI system must navigate throughout its life cycle.

Block definition diagrams detailed the core components of AI pipelines – data cleansing, data transformation, machine learning models, pipeline operations...

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Tech Concepts
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Programming languages
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