Building Generative AI Solutions for Industries with AWS (Paperback)

Building Generative AI Solutions for Industry with AWS is a comprehensive guide for developers, and data scientists aiming to harness the power of Generative AI across a range of industrial domains using Amazon Web Services. This hands-on book provides readers with the knowledge and practical skills to design, secure, govern, and deploy GenAI solutions effectively in real-world environments.

The book begins with an introduction to the fundamentals of Generative AI and the AI/ML services offered by AWS. Readers will explore industry use cases and learn how to kick-start their journey building GenAI applications on the AWS cloud. It focuses on security and governance, covering essential practices for data privacy, access control, encryption, compliance, and ethical AI deployment. Each chapter then dives deep into specific industry applications―automotive, manufacturing, healthcare, financial services, and media & entertainment. From autonomous driving and predictive maintenance to fraud detection and content creation, readers will learn how GenAI is transforming operations and unlocking new opportunities in these fields. The book also addresses cost management strategies for GenAI on AWS, offering guidance on optimizing resources and budgeting efficiently.

Concluding with future possibilities and implementation best practices, this book equips professionals with the tools and insights to build scalable, secure, and compliant GenAI systems tailored to their domain.

What you will learn:

• Understand the fundamentals of Generative AI and AWS AI/ML services.
• How to build and deploy secure, compliant GenAI applications on AWS.
• Explore real-life GenAI use cases across industries like automotive, healthcare, and finance.
• Gain insights into managing GenAI costs and optimizing AWS resources.

Who this book is for:

Software developers, machine learning engineers, data scientists, and cloud architects who want to build real-life Generative AI solutions using AWS. 

Neel Sendas is a Principal Technical Account Manager at Amazon Web Services (AWS). In this role, he serves as the AWS Cloud Operations lead for some of the largest enterprises that utilize AWS services. Drawing from his expertise in cloud operations, in this book, Neel presents solutions to common challenges related to ML Cloud Governance, Cloud Finance, and Cloud Operational Resilience & Management at scale. Neel also plays a crucial role as part of the core team of Machine Learning Technical Field Community leaders at AWS, where he contributes to shaping the roadmap of AWS Artificial Intelligence and Machine Learning (AI/ML) Services. Neel is based in the state of Georgia, United States.

Saurabh Saxena is Senior Principal Technical Account Manager at AWS. During the last 12 years, he has provided strategic technical guidance to enterprise customers, helping them navigate complex cloud transformations and maximise their AWS investments. With deep technical expertise across AWS services and a focus on business outcomes, he partners with key stakeholders to architect solutions that drive innovation and operational excellence. Saurabh often leads high-impact customer engagements, developing technical roadmaps, and coordinating cross-functional teams to guarantee successful cloud adoption. He specialises in translating complex technical concepts into business value, helping organizations leverage AWS technologies to achieve their strategic goals.

Joseph Sacco is a Principal Technical Account Manager at Amazon Web Services (AWS), as well as a member of the AWS Healthcare and Life Sciences Technical Field Community (TFC). In his role, he serves as a strategic technical advisor for some of the largest Healthcare and Life Science (HCLS) customers that utilize AWS services. Prior to joining Amazon, Joseph was the Director of IT at a Healthcare startup focused on optimizing electronic healthcare data. Joseph brings over 15 years of experience with technology solutions and digital transformations in the HCLS space, from private providers and biopharmaceutical, to some of the largest health systems around the globe. Pulling from his expertise in HCLS and Generative AI, in this book, Joseph provides real-life examples on how AI can help to speed up lengthy regulatory and compliance processes, enhance diagnostic accuracy and increase speed in radiology workflows, reduce clinician burnout, enhance clinical decision making, and more. Joseph is based in the state of Connecticut, United States.