DESCRIPTION
Generative AI can streamline technical and business processes, increase efficiency, and free up your resources' time to focus on more strategic initiatives. This book takes the readers through a series of steps to deepen their understanding of the forces that shape an organization's implementation of Generative AI at scale and successfully dealing with them.
This book starts with GenAI potential uses, challenges and enterprise deployment strategies. You will learn to scale GenAI models along with LLMOps, choose the right LLM, and use prompt engineering and fine-tuning to customize the outputs. This book introduces a GenAI operating system as well as an orchestration platform for workflow automation. It discusses ethical considerations, designing a target operating model, cost optimization, Retrieval-augmented Generation (RAG), Model as a Service (MaaS), and Confidential AI. Finally, it explores the future of multi-modal AI assistants in enterprises.
This book makes it easier for readers to debunk myths, and address fallacies and common misconceptions that could harm organizational investment and reputation. There are also practical and enterprise class scenarios and information that could help in improving implementations, within your organization, enabling you to achieve success beyond scaling challenges.
WHAT YOU WILL LEARN
● Strategies for scaling GenAI models and discovering LLMOps for managing them.
● How to leverage GenAI to streamline enterprise class processes, boost efficiency, and explore new possibilities.
● Implementations in the enterprise class deployments, addressing potential issues and connecting with enablers and accurate growth strategy and execution principles.
WHO THIS BOOK IS FOR
This book is for decision makers like CIOs, CTOs, CAIOs, Enterprise Architects, Chief Engineers, and anyone who wishes to learn how to have a rewarding implementation of Generative AI for their organizations and clients.
