Large Language Model-Based Solutions : HOW TO DELIVER VALUE WITH COST-EFFECTIVE GENERATIVE AI APPLICATIONS 9781394240739, 9781394240722, 1677858242
Learn to build cost-effective apps using Large Language Models In Large Language Model-Based Solutions: How to Deliver V
118 93 16MB
English Pages 224 Year 2024
Table of contents :
Cover
Table of Contents
Title Page
Introduction
GenAI APPLICATIONS AND LARGE LANGUAGE MODELS
IMPORTANCE OF COST OPTIMIZATION
MICRO CASE STUDIES
WHO IS THIS BOOK FOR?
SUMMARY
1 Introduction
OVERVIEW OF GenAI APPLICATIONS AND LARGE LANGUAGE MODELS
PATHS TO PRODUCTIONIZING GenAI APPLICATIONS
THE IMPORTANCE OF COST OPTIMIZATION
SUMMARY
2 Tuning Techniques for Cost Optimization
FINE‐TUNING AND CUSTOMIZABILITY
PARAMETER‐EFFICIENT FINE‐TUNING METHODS
COST AND PERFORMANCE IMPLICATIONS OF PEFT METHODS
SUMMARY
3 Inference Techniques for Cost Optimization
INTRODUCTION TO INFERENCE TECHNIQUES
PROMPT ENGINEERING
CACHING WITH VECTOR STORES
CHAINS FOR LONG DOCUMENTS
SUMMARIZATION
BATCH PROMPTING FOR EFFICIENT INFERENCE
MODEL OPTIMIZATION METHODS
PARAMETER‐EFFICIENT FINE‐TUNING METHODS
COST AND PERFORMANCE IMPLICATIONS
SUMMARY
REFERENCES
4 Model Selection and Alternatives
INTRODUCTION TO MODEL SELECTION
MOTIVATING EXAMPLE: THE TALE OF TWO MODELS
THE ROLE OF COMPACT AND NIMBLE MODELS
EXAMPLES OF SUCCESSFUL SMALLER MODELS
DOMAIN‐SPECIFIC MODELS
THE POWER OF PROMPTING WITH GENERAL‐PURPOSE MODELS
SUMMARY
5 Infrastructure and Deployment Tuning Strategies
INTRODUCTION TO TUNING STRATEGIES
HARDWARE UTILIZATION AND BATCH TUNING
INFERENCE ACCELERATION TOOLS
MONITORING AND OBSERVABILITY
SUMMARY
CONCLUSION
BALANCING PERFORMANCE AND COST
FUTURE TRENDS IN GenAI APPLICATIONS
SUMMARY
INDEX
Copyright
Dedication
ABOUT THE AUTHOR
ABOUT THE TECHNICAL EDITOR
End User License Agreement
Cover
Table of Contents
Title Page
Introduction
GenAI APPLICATIONS AND LARGE LANGUAGE MODELS
IMPORTANCE OF COST OPTIMIZATION
MICRO CASE STUDIES
WHO IS THIS BOOK FOR?
SUMMARY
1 Introduction
OVERVIEW OF GenAI APPLICATIONS AND LARGE LANGUAGE MODELS
PATHS TO PRODUCTIONIZING GenAI APPLICATIONS
THE IMPORTANCE OF COST OPTIMIZATION
SUMMARY
2 Tuning Techniques for Cost Optimization
FINE‐TUNING AND CUSTOMIZABILITY
PARAMETER‐EFFICIENT FINE‐TUNING METHODS
COST AND PERFORMANCE IMPLICATIONS OF PEFT METHODS
SUMMARY
3 Inference Techniques for Cost Optimization
INTRODUCTION TO INFERENCE TECHNIQUES
PROMPT ENGINEERING
CACHING WITH VECTOR STORES
CHAINS FOR LONG DOCUMENTS
SUMMARIZATION
BATCH PROMPTING FOR EFFICIENT INFERENCE
MODEL OPTIMIZATION METHODS
PARAMETER‐EFFICIENT FINE‐TUNING METHODS
COST AND PERFORMANCE IMPLICATIONS
SUMMARY
REFERENCES
4 Model Selection and Alternatives
INTRODUCTION TO MODEL SELECTION
MOTIVATING EXAMPLE: THE TALE OF TWO MODELS
THE ROLE OF COMPACT AND NIMBLE MODELS
EXAMPLES OF SUCCESSFUL SMALLER MODELS
DOMAIN‐SPECIFIC MODELS
THE POWER OF PROMPTING WITH GENERAL‐PURPOSE MODELS
SUMMARY
5 Infrastructure and Deployment Tuning Strategies
INTRODUCTION TO TUNING STRATEGIES
HARDWARE UTILIZATION AND BATCH TUNING
INFERENCE ACCELERATION TOOLS
MONITORING AND OBSERVABILITY
SUMMARY
CONCLUSION
BALANCING PERFORMANCE AND COST
FUTURE TRENDS IN GenAI APPLICATIONS
SUMMARY
INDEX
Copyright
Dedication
ABOUT THE AUTHOR
ABOUT THE TECHNICAL EDITOR
End User License Agreement
