Wikipedia Vector Search Demo with Weaviate

Explore a comprehensive demonstration of Wikipedia Vector Search using Weaviate in this 24-minute video presentation. Learn how to implement semantic search through Wikipedia using GraphQL, Sentence-BERT, and BERT Q&A. Discover the power of neural search and its intuitive comparison to familiar search systems like Google. Gain insights into how information retrieval enhances supervised learning tasks, particularly with the Weaviate Question Answering Module. Examine the generalization of these concepts to advanced AI models like AlphaFold2, Frozen, and GPT-3. Follow along with practical demo queries and explore topics such as CO-Search, Retrieve-then-Read for NLP, and applications in various data domains. Access additional resources and links to deepen your understanding of open-domain question answering, knowledge-intensive NLP tasks, and cutting-edge AI research.

Introduction
What is Wikipedia?
Wikipedia NLP Tasks
Wikipedia Dataset Statistics
How this was setup
Demo Query #1
Demo Query #2
Demo Query #3
Demo Query #4
CO-Search
Retrieve-then-Read for NLP
Retrieve-then-Read for AlphaFold2 and more
General Ideas