The Generative AI Practitioner's Guide: How to Apply LLM Patterns for Enterprise Applications

by Arup Das, David Sweenor

Overview

Generative AI is revolutionizing the way organizations leverage technology to gain a competitive edge. However, as more companies experiment with and adopt AI systems, it becomes challenging for data and analytics professionals, AI practitioners, executives, technologists, and business leaders to look beyond the buzz and focus on the essential questions: Where should we begin? How do we initiate the process? What potential pitfalls should we be aware of?


This TinyTechGuide offers valuable insights and practical recommendations on constructing a business case, calculating ROI, exploring real-life applications, and considering ethical implications. Crucially, it introduces five LLM patterns—author, retriever, extractor, agent, and experimental—to effectively implement GenAI systems within an organization. The Generative AI Practitioner's Guide: How to Apply LLM Patterns for Enterprise Applications bridges critical knowledge gaps for business leaders and practitioners, equipping them with a comprehensive toolkit to define a business case and successfully deploy GenAI.


In today's rapidly evolving world, staying ahead of the competition requires a deep understanding of these five implementation patterns and the potential benefits and risks associated with GenAI. Designed for business leaders, tech experts, and IT teams, this book provides real-life examples and actionable insights into GenAI's transformative impact on various industries.


Empower your organization with a competitive edge in today's marketplace using The Generative AI Practitioner's Guide: How to Apply LLM Patterns for Enterprise Applications. Remember, it's not the tech that's tiny, just the book!™

Product Details

BN ID:	2940185785508
Publisher:	TinyTechGuides LLC
Publication date:	10/06/2024
Sold by:	Barnes & Noble
Format:	eBook
File size:	6 MB

About the Author

Arup Das is a distinguished AI and ML expert who has had a significant impact on the GenAI industry. As the Head of AI & Gen AI Industry Specialists at UiPath, he leads initiatives to enhance automation in various sectors, boosting revenue growth and operational efficiency. His passion for AI and strategic vision make him a leading voice in the industry, dedicated to solving complex business problems and driving innovation.


With over two decades of technology leadership experience, Arup has successfully led venture capital raises and exits. His career includes key roles at Avenue One, Compass, and Machine Analytics, developing low-code AI platforms and NLP solutions.


Arup also educates future leaders as a Professor at the Villanova School of Business and Monmouth University, teaching AI ethics, business applications, and advanced NLP techniques.


He holds an MBA from Cornell University, a Master’s in Analytics from Villanova University, and a Master’s in Computer Engineering from Stony Brook University. He has received several honors, including Villanova University Student Spotlight recognition and a Thought Leader of the Year award. Connect with him on LinkedIn.


David Sweenor is a top-25 AI and analytics thought leader, international speaker, entrepreneur, and acclaimed author who holds several patents. He is a marketing leader, analytics practitioner, and specialist in the business application of AI, ML, data science, the IoT, and business intelligence.

With over 25 years of hands-on business analytics experience, Sweenor has supported such organizations as Alation, Alteryx, TIBCO Software, the SAS Institute, IBM, Dell, and Quest in advanced analytical roles. Follow David on Twitter (@DavidSweenor) and connect with him on LinkedIn.