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

This talk was recorded at NDC London in London, England. #ndclondon #ndcconferences #developer #softwaredeveloper
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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.
In this talk, Zain Hasan will discuss how we can use open-source multimodal models (such as github.com/fac..., that can see, hear, read, and feel data(!), to perform cross-modal search(searching audio with images, videos with text etc.) at the billion-object scale with the help of open source vector databases. I will also demonstrate, with live code demos and large-scale datasets, how being able to perform this cross-modal retrieval in real-time can help users add natural search interfaces to their apps. This talk will revolve around how we scaled the usage of multimodal embedding models in production and how you can add cross-modal search into your apps.

[@s.m.mustafaakailvi2915]

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!

[@pr0l0gix]

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.

[@meteatamel5433]

Good presentation on the topic of multi-modality. Thanks!