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Generative AI with Amazon Bedrock

You're reading from   Generative AI with Amazon Bedrock Build, scale, and secure generative AI applications using Amazon Bedrock

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781803247281
Length 384 pages
Edition 1st Edition
Tools
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Authors (2):
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Shikhar Kwatra Shikhar Kwatra
Author Profile Icon Shikhar Kwatra
Shikhar Kwatra
Bunny Kaushik Bunny Kaushik
Author Profile Icon Bunny Kaushik
Bunny Kaushik
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Table of Contents (18) Chapters Close

Preface 1. Part 1: Amazon Bedrock Foundations FREE CHAPTER
2. Chapter 1: Exploring Amazon Bedrock 3. Chapter 2: Accessing and Utilizing Models in Amazon Bedrock 4. Chapter 3: Engineering Prompts for Effective Model Usage 5. Chapter 4: Customizing Models for Enhanced Performance 6. Chapter 5: Harnessing the Power of RAG 7. Part 2: Amazon Bedrock Architecture Patterns
8. Chapter 6: Generating and Summarizing Text with Amazon Bedrock 9. Chapter 7: Building Question Answering Systems and Conversational Interfaces 10. Chapter 8: Extracting Entities and Generating Code with Amazon Bedrock 11. Chapter 9: Generating and Transforming Images Using Amazon Bedrock 12. Chapter 10: Developing Intelligent Agents with Amazon Bedrock 13. Part 3: Model Management and Security Considerations
14. Chapter 11: Evaluating and Monitoring Models with Amazon Bedrock 15. Chapter 12: Ensuring Security and Privacy in Amazon Bedrock 16. Index 17. Other Books You May Enjoy

Evaluating and selecting the right FM

Now that we’ve understood the different types of FMs available in Amazon Bedrock, how do we determine which one is best suited for our specific project needs? This section will help you learn how to evaluate the model fit for your use case.

The first step is to clearly define the problem you’re trying to solve or the use case you want to build. Get as specific as possible about the inputs, outputs, tasks involved, and any other requirements. With a well-defined use case in hand, you can research which models have demonstrated capabilities relevant to your needs. Narrowing the options upfront based on capabilities will streamline the evaluation process.

Once you’ve identified some potential candidate models, the next step is to examine their performance across standardized benchmarks and use cases. Amazon Bedrock provides a capability to evaluate FMs, also called model evaluation jobs. With model evaluation jobs, users...

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