Using Vector Databases for Multimodal Embeddings and Search - Zain Hasan - NDC London 2024

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Many real-world problems are inherently multimodal, from the communicative modalities humans use such as spoken language and gestures to the force, proprioception, and visual sensors ubiquitous in robotics. In order for machine learning models to address these problems and interact more naturally and wholistically with the world around them and ultimately be more general and powerful reasoning engines we need them to understand data across all of its corresponding image, video, text, audio, and tactile representations.

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thank you for posting it. This is a good way for understanding Vector DB.Thank you for
explaining it so eloquently and with comparison.
I wanted fo know abt vector db and this is the very thorough. Almost many overviews in VectorDB starts with statistical understanding which becomes diffifculf for us who wants to know how coherently it works.

prlgix

This is it. This is the future and I've been searching & experimenting for MONTHS and this is literally the FIRST instance I have found of this type of implementation of Multi-Modality!

s.m.mustafaakailvi

Using Vector Databases for Multimodal Embeddings and Search - Zain Hasan - NDC London 2024

Using Vector Databases for Multimodal Embeddings and Search - Zain Hasan - NDC London 2024

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