Generative AI for Cloud Solutions: Architect modern AI LLMs in secure, scalable, and ethical cloud environments

English | 2024 | ISBN: 978-1835084786 | 300 Pages | PDF, EPUB | 33 MB

Explore Generative AI, the engine behind ChatGPT, and delve into topics like LLM-infused frameworks, autonomous agents, and responsible innovation, to gain valuable insights into the future of AI

Key Features

• Gain foundational GenAI knowledge and understand how to scale GenAI/ChatGPT in the cloud
• Understand advanced techniques for customizing LLMs for organizations via fine-tuning, prompt engineering, and responsible AI
• Peek into the future to explore emerging trends like multimodal AI and autonomous agents

Generative artificial intelligence technologies and services, including ChatGPT, are transforming our work, life, and communication landscapes. To thrive in this new era, harnessing the full potential of these technologies is crucial. Generative AI for Cloud Solutions is a comprehensive guide to understanding and using Generative AI within cloud platforms. This book covers the basics of cloud computing and Generative AI/ChatGPT, addressing scaling strategies and security concerns. With its help, you’ll be able to apply responsible AI practices and other methods such as fine-tuning, RAG, autonomous agents, LLMOps, and Assistants APIs. As you progress, you’ll learn how to design and implement secure and scalable ChatGPT solutions on the cloud, while also gaining insights into the foundations of building conversational AI, such as chatbots. This process will help you customize your AI applications to suit your specific requirements. By the end of this book, you’ll have gained a solid understanding of the capabilities of Generative AI and cloud computing, empowering you to develop efficient and ethical AI solutions for a variety of applications and services.

What you will learn

• Get started with the essentials of generative AI, LLMs, and ChatGPT, and understand how they function together
• Understand how we started applying NLP to concepts like transformers
• Grasp the process of fine-tuning and developing apps based on RAG
• Explore effective prompt engineering strategies
• Acquire insights into the app development frameworks and lifecycles of LLMs, including important aspects of LLMOps, autonomous agents, and Assistants APIs
• Discover how to scale and secure GenAI systems, while understanding the principles of responsible AI