Vladimir Orshulevich Presents:
Semantic Multimodal Multilingual Similarity Engine
Since multimodality became popular, lots of engineers are trying to make a domain-universal search. The search engines that will find in images by textual query, HTML file by piece of audio, and so on. So here is our (Unum) approach with a bias toward GPU accelerating inference (for underlying models) and a passion to distribute everything.
During the presentation, we will discuss the following questions:
-How to build fast and precise Semantic Textual Similarity engine.
-Multilingual sentence encoders.
-What is CLIP and how can we find an image with a textual query.
-Building indices: Approximate Nearest Neighbor Algorithms and toolkits.
-What is the future of the semantic cross-domain search.
Presentation Slides: [ Ссылка ]
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