فهرست مطالب

• Cover Page
• About This eBook
• Title Page
• Copyright Page
• Contents
• Preface
• Acknowledgments
• About the Authors
• 1. Introduction
• 1.1 What We Talk about When We Talk about Things: Terminology
• 1.2 Achieving System Qualities
• 1.3 Life-Cycle Processes
• 1.4 Software Architecture
• 1.5 AI Model Quality
• 1.6 Dealing with Uncertainty
• 1.7 Summary
• 1.8 Discussion Questions
• 1.9 For Further Reading
• 2. Software Engineering Background
• 2.1 Distributed Computing
• 2.2 DevOps Background
• 2.3 MLOps Background
• 2.4 Summary
• 2.5 Discussion Questions
• 2.6 For Further Reading
• 3. AI Background
• 3.1 Terminology
• 3.2 Selecting a Model
• 3.3 Preparing the Model for Training
• 3.4 Summary
• 3.5 Discussion Questions
• 3.6 For Further Reading
• 4. Foundation Models
• 4.1 Foundation Models
• 4.2 Transformer Architecture
• 4.3 Alternatives in FM Architectures
• 4.4 Customizing FMs
• 4.5 Designing a System Using FMs
• 4.6 Maturity of FMs and Organizations
• 4.7 Challenges of FMs
• 4.8 Summary
• 4.9 Discussion Questions
• 4.10 For Further Reading
• 5. AI Model Life Cycle
• 5.1 Developing the Model
• 5.2 Building the Model
• 5.3 Testing the Model
• 5.4 Release
• 5.5 Summary
• 5.6 Discussion Questions
• 5.7 For Further Reading
• 6. System Life Cycle
• 6.1 Design
• 6.2 Developing Non-AI Modules
• 6.3 Build
• 6.4 Test
• 6.5 Release and Deploy
• 6.6 Operate, Monitor, and Analyze
• 6.7 Summary
• 6.8 Discussion Questions
• 6.9 For Further Reading
• 7. Reliability
• 7.1 Fundamental Concepts
• 7.2 Preventing Faults
• 7.3 Detecting Faults
• 7.4 Recovering from Faults
• 7.5 Summary
• 7.6 Discussion Questions
• 7.7 For Further Reading
• 8. Performance
• 8.1 Efficiency
• 8.2 Accuracy
• 8.3 Summary
• 8.4 Discussion Questions
• 8.5 For Further Reading
• 9. Security
• 9.1 Fundamental Concepts
• 9.2 Approaches to Mitigating Security Concerns
• 9.3 Summary
• 9.4 Discussion Questions
• 9.5 For Further Reading
• 10. Privacy and Fairness
• 10.1 Privacy in AI Systems
• 10.2 Fairness in AI Systems
• 10.3 Achieving Privacy
• 10.4 Achieving Fairness
• 10.5 Summary
• 10.6 Discussion Questions
• 10.7 For Further Reading
• 11. Observability
• 11.1 Fundamental Concepts
• 11.2 Evolving from Monitorability to Observability
• 11.3 Approaches for Enhancing Observability
• 11.4 Summary
• 11.5 Discussion Questions
• 11.6 For Further Reading
• 12. The Fraunhofer Case Study
• 12.1 The Problem Context
• 12.2 Case Study Description and Setup
• 12.3 Summary
• 12.4 Takeaways
• 12.5 Discussion Questions
• 12.6 For Further Reading
• 13. The ARM Hub Case Study
• 13.1 Introduction
• 13.2 Our Approach
• 13.3 LLMs in SME Manufacturing
• 13.4 A RAG-Based Chatbot for SME Manufacturing
• 13.5 Architecture of the ARM Hub Chatbot
• 13.6 MLOps in ARM Hub
• 13.7 Ongoing Work
• 13.8 Summary
• 13.9 Takeaways
• 13.10 Discussion Questions
• 13.11 For Further Reading
• 14. The Banking Case Study
• 14.1 Customer Churn Prediction
• 14.2 Key Challenges in the Banking Sector
• 14.3 Summary
• 14.4 Takeaways
• 14.5 Discussion Questions
• 14.6 For Further Reading
• 15. The Future of AI Engineering
• 15.1 The Shift to DevOps 2.0
• 15.2 AI’s Implications for the Future
• 15.3 AIWare or AI-as-Software
• 15.4 Trust in AI and the Role of Human Engineers
• 15.5 Summary
• 15.6 Discussion Questions
• 15.7 For Further Reading
• References
• Index