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Challenges of ML/AI Applications and Vector Embeddings with Weaviate - Part 3

Data Science Dojo via YouTube

Overview

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Explore the challenges and solutions of scaling ML/AI applications in industry through this 56-minute webinar focused on practical implementations using Weaviate. Dive into how ML/AI powers critical systems like secure internal search, recommendation engines, and e-commerce platforms, with special attention to Retrieval-Augmented Generation (RAG). Learn the architectural foundations and development process through live demonstrations, including an exploration of the open-source RAG tool Verba. Discover emerging trends in AI systems, including AI agents and Generative Flow Learning (GFL), while gaining valuable insights into common implementation pitfalls. Starting with foundational concepts of vector embeddings and vector search, progress through advanced topics like hybrid search, query augmentation, and decision trees. Get hands-on exposure to agentic architectures through the Elysia framework demonstration and understand the future trajectory of AI applications at scale.

Syllabus

00:00 Overview of AI in the Real World
01:16 Recap of Webinar 1: What is a Vector Embedding?
05:31 Recap of Webinar 2: What is Vector Search?
09:47 Search at Scale
15:03 Hybrid Search
22:39 Retrieval Augmented Generation RAG
23:55 Demo: Verba – Open Source RAG
36:49 E-Commerce with AI
39:22 Next Horizon: Agentic Architectures
42:03 Example: Elysia – Agentic RAG Framework
47:02 Query Augmentation and Decision Trees
49:22 Common Pitfalls in AI Implementation

Taught by

Data Science Dojo

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