BOOKS - Enterprise GENERATIVE AI Well Architected Framework and Patterns: An Architec...
Enterprise GENERATIVE AI Well Architected Framework and Patterns: An Architect
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Enterprise GENERATIVE AI Well Architected Framework and Patterns: An Architect's Real-life Guide to Adopting Generative AI in Enterprises at Scale
Author: Suvoraj Biswas
Year: September 11, 2023
Format: PDF
File size: PDF 6.0 MB
Language: English

Welcome to the and quot;Enterprise Generative AI Well Architected Framework and Patterns and quot; a comprehensive step by step guide designed for Enterprise IT Professionals to explore the cutting-edge world of generative artificial intelligence (AI) systems within the context of enterprise applications.

As most of the businesses continue to embrace AI-driven solutions to streamline processes, drive automation and generate valuable insights, the importance of robust and scalable generative AI architectures becomes increasingly evident. When I decided to explore the Generative AI solutions, as a Solutions Architect I faced a lot of challenges, roadblocks and at the same time learned a lot while exploring many tools and technologies during the initial steps. My everyday learning and challenges pushed me to come up with generic well architected frameworks for my fellow IT professionals to build world class software to delight the Enterprise stakeholders following the existing common LLM integration and adoption pattern.
This book is intended to provide readers with a clear understanding of the fundamental principles, methodologies, and best practices for implementing generative AI in large-scale enterprise environments. Whether you are a seasoned AI practitioner(Architects, Engineers Engineering Managers or Product Managers) seeking to deepen your knowledge or an enterprise leader (VPs, CXOs, Founders) exploring the potential of Generative AI for your organization, this book offers valuable insights into leveraging the power of generative models effectively and responsibly. We will also discuss the challenges and ethical considerations associated with deploying AI systems in enterprise settings and provide strategies to address these concerns.

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