Generative AI with Amazon Bedrock : Build, scale, and secure generative AI applications using Amazon Bedrock

Become proficient in Amazon Bedrock by taking a hands-on approach to building and scaling generative AI solutions that are robust, secure, and compliant with ethical standards

Key Features

• Learn the foundations of Amazon Bedrock from experienced AWS Machine Learning Specialist Architects
• Master the core techniques to develop and deploy several AI applications at scale
• Go beyond writing good prompting techniques and secure scalable frameworks by using advanced tips and tricks
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

The concept of generative artificial intelligence has garnered widespread interest, with industries looking to leverage it to innovate and solve business problems. Amazon Bedrock, along with LangChain, simplifies the building and scaling of generative AI applications without needing to manage the infrastructure.

Generative AI with Amazon Bedrock takes a practical approach to enabling you to accelerate the development and integration of several generative AI use cases in a seamless manner. You’ll explore techniques such as prompt engineering, retrieval augmentation, fine-tuning generative models, and orchestrating tasks using agents. The chapters take you through real-world scenarios and use cases such as text generation and summarization, image and code generation, and the creation of virtual assistants. The latter part of the book shows you how to effectively monitor and ensure security and privacy in Amazon Bedrock.

By the end of this book, you’ll have gained a solid understanding of building and scaling generative AI apps using Amazon Bedrock, along with various architecture patterns and security best practices that will help you solve business problems and drive innovation in your organization.

What you will learn

• Explore the generative AI landscape and foundation models in Amazon Bedrock
• Fine-tune generative models to improve their performance
• Explore several architecture patterns for different business use cases
• Gain insights into ethical AI practices, model governance, and risk mitigation strategies
• Enhance your skills in employing agents to develop intelligence and orchestrate tasks
• Monitor and understand metrics and Amazon Bedrock model response
• Explore various industrial use cases and architectures to solve real-world business problems using RAG
• Stay on top of architectural best practices and industry standards

Who this book is for

This book is for generalist application engineers, solution engineers and architects, technical managers, ML advocates, data engineers, and data scientists looking to either innovate within their organization or solve business use cases using generative AI. A basic understanding of AWS APIs and core AWS services for machine learning is expected.

Table of Contents

1. Exploring Amazon Bedrock
2. Accessing and Utilizing Models in Amazon Bedrock
3. Engineering Prompts for Effective Model Usage
4. Customizing Models for Enhanced Performance
5. Harnessing the Power of RAG
6. Generating and Summarizing Text with Amazon Bedrock
7. Building Question Answering Systems and Conversational Interfaces
8. Extracting Entities and Generating Code with Amazon Bedrock
9. Generating and Transforming Images Using Amazon Bedrock
10. Developing Intelligent Agents with Amazon Bedrock
11. Evaluating and Monitoring Models with Amazon Bedrock
12. Ensuring Security and Privacy in Amazon Bedrock

Shikhar Kwatra, a senior AI/ML solutions architect at Amazon Web Services, holds the distinction of being the world's Youngest Master Inventor with over 500 patents in AI/ML and IoT domains. He serves as a technical journal reviewer, book author, and educator. Shikhar earned his Master's in Electrical Engineering from Columbia University. With over a decade of experience spanning startups to large-scale enterprises, he specializes in architecting scalable, cost-efficient cloud environments and supports GSI partners in developing strategic industry solutions. Beyond his professional pursuits, Shikhar finds joy in playing the guitar, composing music, and practicing mindfulness.

Bunny Kaushik is an AWS solution architect and ML specialist who loves to build solutions and help customers innovate on the AWS platform. He is an Amazon SageMaker SME, generative AI hero, and ML thought leader within AWS. He has over 10 years of experience working as an ML specialist and managing projects across different teams and organizations. Outside of work, he enjoys swimming, playing volleyball, rock climbing, and exploring new places.