Generative AI on Aws: Building Context-Aware Multimodal Reasoning Applications

Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology.

You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images.

• Apply generative AI to your business use cases
• Determine which generative AI models are best suited to your task
• Perform prompt engineering and in-context learning
• Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA)
• Align generative AI models to human values with reinforcement learning from human feedback (RLHF)
• Augment your model with retrieval-augmented generation (RAG)
• Explore libraries such as LangChain and ReAct to develop agents and actions
• Build generative AI applications with Amazon Bedrock

Chris Fregly is a Principal Solutions Architect for Generative AI at Amazon Web Services (AWS) based in San Francisco, California. Chris holds every AWS certification. He is also co-founder of the global Generative AI on AWS Meetup. Chris regularly speaks at AI and Machine Learning meetups and conferences across the world. Previously, Chris was an engineer at Databricks and Netflix where he worked on scalable big data and machine learning products and solutions. He is also co-author of the O'Reilly book, Data Science on AWS.

Antje Barth is a Principal Developer Advocate for AI and Machine Learning at Amazon Web Services (AWS) based in San Francisco, California. She is also co-founder of the global Generative AI on AWS Meetup. Antje frequently speaks at AI and machine learning conferences and meetups around the world, including the O'Reilly AI and Strata conferences. Besides Generative AI, Antje is passionate about helping developers leverage big data, containers, and Kubernetes platforms in the context of AI and Machine Learning. Prior to joining AWS, Antje worked in technical evangelist and solutions engineering roles at MapR and Cisco. She is also co-author of the O'Reilly book, Data Science on AWS.

Shelbee Eigenbrode is a Principal Solutions Architect for Generative AI at Amazon Web Services (AWS) based in Denver, Colorado. She is co-founder of the Denver chapter of Women in Big Data. Shelbee holds 6 AWS certifications and has been in technology for 23 years spanning multiple industries, technologies, and roles. She focuses on combining her DevOps and ML backgrounds to deliver ML workloads at scale. With over 35 patents granted across various technology domains, Shelbee has a passion for continuous innovation and using data to drive business outcomes.