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Generative AI Design Patterns - Five Key Patterns for Enhanced AI Systems

Toronto Machine Learning Series (TMLS) via YouTube

Overview

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Explore a 35-minute conference talk from the Toronto Machine Learning Series where Principal ML Engineer Krishnachaitanya Gogineni from Observe.AI examines five crucial generative AI design patterns and their practical applications. Dive deep into Retrieval Augmented Generation (RAG), Cluster Pulse, State Based Agents, Guard Rails, and Auto-Prompting, understanding how each pattern contributes to enhancing AI systems' capabilities and safety. Learn how these patterns work together through a real-world case study of a Personalized K-8 Tutor, demonstrating how combining multiple design patterns can create adaptive, personalized learning experiences. Gain practical insights into implementing these patterns while discovering their potential for developing innovative AI solutions that are both powerful and responsibly constrained.

Syllabus

Generative AI Design Patterns

Taught by

Toronto Machine Learning Series (TMLS)

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