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X-WR-CALDESC:Events for Huntsville AI
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DTSTART;TZID=America/Chicago:20240417T180000
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SUMMARY:Choosing an Embedding Model
DESCRIPTION:We have Josh Phillips presenting this week\, so you don’t want to miss this! \nJoin us as we explore the crucial task of selecting optimal embedding models to enhance AI performance across a variety of applications. This meetup will delve into the Multilingual Transferable Embedding Benchmark (MTEB)\, a pivotal resource providing a comprehensive framework to evaluate embedding models over diverse task categories and numerous languages. The selection of the right embedding model is vital\, yet challenging due to the myriad of options and their inherent trade-offs. \nThis presentation will not only introduce you to MTEB’s holistic approach across eight core NLP tasks but will also guide you through the practical steps of identifying\, shortlisting\, and benchmarking models to find the best fit for your specific needs. \nAgenda: \n\nIntroduction to Embedding Models – Gain insights into why choosing the right model is critical for AI tasks.\nOverview of MTEB – Understand the framework of the Multilingual Transferable Embedding Benchmark and its application across 100+ languages.\nDeep Dive into MTEB Tasks – Explore the eight fundamental tasks within MTEB\, including bitext mining\, classification\, clustering\, and more.\nCase Studies – Walk through real-world use cases\, demonstrating how to apply MTEB in selecting models for tasks such as walking path recommendations\, form filling automation\, and building a documentation assistant.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSeries: \nOver the next several sessions\, we will be diving deeper into separate components needed for RAG – hopefully resulting in a chat-based Q&A service for the NASA Technical Report Server.  We were introduced to this data during our submission for the 2022 NASA SpaceApps Challenge – where we placed 2nd. Our submission was a semantic search based on the abstracts for the NSTR dataset of 10\,000 papers. \nI hope to have the video from our last session posted today. You can check for updates at https://hsv.ai/videos \nLinks: \n\nMultilingual Transferable Embedding Benchmark (MTEB)\nMTEB Github\nMTEB Paper\nHuntsville AI 2022 SpaceApps Submission – https://github.com/HSV-AI/spaceapps2022\n\n\nDetails: \n\nDate – 04/17/2024\nTime – 6-7pm\nLocation – HudsonAlpha\nAddress –  601 Genome Way Northwest\, Huntsville\, AL 35806\nZoom –https://us02web.zoom.us/j/81626946368?pwd=c2M3QTlXSy9ZS20xdkZrUHBIMHdOdz09
URL:https://hsv.ai/event/choosing-an-embedding-model/
LOCATION:HudsonAlpha\, 601 Genome Way Northwest\, Huntsville\, AL\, 35806
ATTACH;FMTTYPE=image/png:https://hsv.ai/wp-content/uploads/2024/04/Choosing-an-Embedding-Model.png
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