BOOKS - Enterprise Generative AI Well Architected Framework & Patterns An Architect's...
Enterprise Generative AI Well Architected Framework & Patterns An Architect
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Enterprise Generative AI Well Architected Framework & Patterns An Architect's Real-life Guide to Adopting Generative AI in Enterprises at Scale
Author: Suvoraj Biswas, Moumita Biswas
Year: 2024
Format: /RETAIL PDF EPUB
File size: 17.1 MB
Language: ENG

Welcome to the "Enterprise Generative AI Well Architected Framework & Patterns" 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. We have all witnessed how OpenAI has recently reshaped the digital landscape through the introduction of tools like ChatGPT, which gained a substantial user base surpassing all popular social media applications. ChatGPT has been powered by what we call Generative AI which not only has remarkable influence in the consumer sphere but also many Enterprises are adopting to solve many business challenges which previously appeared impossible. Generative AI is a form of Deep Learning system which is able to generate new original contents (texts or digital media - audio or Video or images). It uses the Machine Mearning algorithm and artificial neural networks to recognize the underlying pattern in the training data to predict new original contents without any human intervention or influences. 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.

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