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Building AI Intensive Python Applications

You're reading from   Building AI Intensive Python Applications Create intelligent apps with LLMs and vector databases

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781836207252
Length 298 pages
Edition 1st Edition
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Table of Contents (18) Chapters Close

Preface 1. Chapter 1: Getting Started with Generative AI 2. Chapter 2: Building Blocks of Intelligent Applications FREE CHAPTER 3. Part 1: Foundations of AI: LLMs, Embedding Models, Vector Databases, and Application Design
4. Chapter 3: Large Language Models 5. Chapter 4: Embedding Models 6. Chapter 5: Vector Databases 7. Chapter 6: AI/ML Application Design 8. Part 2: Building Your Python Application: Frameworks, Libraries, APIs, and Vector Search
9. Chapter 7: Useful Frameworks, Libraries, and APIs 10. Chapter 8: Implementing Vector Search in AI Applications 11. Part 3: Optimizing AI Applications: Scaling, Fine-Tuning, Troubleshooting, Monitoring, and Analytics
12. Chapter 9: LLM Output Evaluation 13. Chapter 10: Refining the Semantic Data Model to Improve Accuracy 14. Chapter 11: Common Failures of Generative AI 15. Chapter 12: Correcting and Optimizing Your Generative AI Application 16. Other Books You May Enjoy Appendix: Further Reading: Index

Other remedies

Some other technical remedies can be employed even more easily than the ones detailed in this chapter. Some of these may improve the accuracy and performance of your GenAI application, though the level of effort involved varies. As an example, during MongoDB’s testing of GPT, it was discovered that the accuracy rate for the same set of questions was improved by 7% between GPT-3.5 and GPT-4. Getting such a level of improvement in accuracy via prompting, retrieval augmentation, or late interaction strategies is certainly possible but would have been difficult.

So, it is worth investigating every avenue of potential improvement, including areas such as hardware upgrades, code optimization, concurrency management, database query optimization, and even just upgrading your software. All of these can improve the results of your GenAI application and should be independently investigated:

  • Hardware and software upgrades: Upgrade computational resources, such...
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