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Harnessing Snowflake with Generative AI and LLMs

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Book Details
Language
English
Publishers
Independently published (17 July 2024)
Weight
0.06 KG
Publication Date
17/07/2024
Pages
33 pages
ISBN-13
9798333391674
Dimensions
15.24 x 0.2 x 22.86 cm
SKU
9798333391674
Author Name
Anand Vemula (Author)
Anand Vemula is a technology, business, ESG and Risk governance Evangelist. He has more than 27 plus years of experience. Has worked in MNC at a CXO level. Has been a part of various projects and forums across customers in BFSI, Healthcare, Retail, Manufacuring, Lifesciences, Energy Industry Verticals. Certified in all the technologies and Enterprise Digital ArchitectRead more about this authorRead less about this author
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In the rapidly evolving landscape of artificial intelligence and data management, "Harnessing Snowflake with Generative AI and LLMs" serves as a comprehensive guide for leveraging the powerful combination of Snowflake's Data Cloud and advanced generative AI technologies, particularly Large Language Models (LLMs). This book is designed for data scientists, AI practitioners, and business leaders eager to unlock the full potential of their data and AI initiatives.

The book begins with an introduction to the foundational concepts of generative AI and LLMs, explaining their significance and impact on various industries. It provides a clear overview of Snowflake's unique architecture and capabilities, highlighting its ability to efficiently store, manage, and analyze large volumes of data.

By integrating Snowflake with generative AI, readers will learn how to build scalable and efficient AI-driven solutions that can handle complex data processing tasks in real-time. A detailed exploration of integrating generative AI with Snowflake follows, showcasing practical applications and real-world use cases.

These include enhancing customer support through advanced chatbots, automating content creation for marketing, and implementing predictive analytics for more informed business decisions. The book emphasizes best practices for using Snowflake with LLMs, covering data quality, scalability, and security considerations.

Further chapters delve into the technical aspects of Snowflake, such as data warehousing, real-time data processing, and performance optimization for AI workloads. The book also addresses crucial ethical considerations, including bias, fairness, and data privacy, ensuring that readers are equipped to develop responsible and compliant AI solutions.

Looking ahead, the book explores emerging technologies and future trends in generative AI and Snowflake, providing insights into the next wave of innovations. Readers will gain a thorough understanding of how to stay ahead in the AI landscape by continuously adapting to new advancements.

"Harnessing Snowflake with Generative AI and LLMs" is an essential resource for anyone looking to effectively combine cutting-edge AI techniques with robust data management practices, driving transformative results in their organization. .

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