Multi-Vector embeddings revolution? or evolution?
UB4.136 | Day 2 | 15:55 - 16:25 | Speakers: Marcin Antas, Roberto Esposito
Abstract
What are multi-vector embeddings? How do they differ from regular embeddings? And how can you build an AI-powered OCR system in under 5 minutes without paying a fortune for infrastructure? If you're curious for answers, join me! I'll break down ColBERT embeddings, explore how MUVERA compression is revolutionizing the way we work with multi-vectors, and show you how to leverage it all to build an AI-powered OCR system on resource constrained devices such as Raspberry Pi.
Weaviate DB: https://github.com/weaviate/weaviate Multi-Vector vision embeddings demo: https://github.com/antas-marcin/weaviate-multi-vector-example
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Speakers
Hi, I'm Marcin, Core Engineer at Weaviate. I'm a pragmatic programmer with a passion for AI and ML algorithms. I'm always eager to dive into the latest innovations and share insights with others. In my free time, I'm all about staying active, with a true passion for IRONMAN triathlons.
Roberto is a Research Engineer on the Applied Research team at Weaviate, where he's currently focused on multi-vector support for the Weaviate vector database. He holds a master's degree from the University of Pisa, where his research centered on Approximate Nearest Neighbor Search (ANN) and compression algorithms.
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