Language Models Bootcamp Day 1 Highlights

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  • ฤas pล™idรกn 1. 08. 2024
  • ๐’๐ž๐œ๐ซ๐ž๐ญ๐ฌ ๐จ๐Ÿ ๐‹๐š๐ซ๐ ๐ž ๐‹๐š๐ง๐ ๐ฎ๐š๐ ๐ž ๐Œ๐จ๐๐ž๐ฅ๐ฌ ๐๐จ๐จ๐ญ๐œ๐š๐ฆ๐ฉ! ๐Ÿš€
    Day 1 of our LLM Bootcamp was an exhilarating journey into the heart of Large Language Models. Here's a glimpse into the cutting-edge topics our participants dived into:
    ๐Ÿ. ๐”๐ง๐๐ž๐ซ๐ฌ๐ญ๐š๐ง๐๐ข๐ง๐  ๐ญ๐ก๐ž ๐‹๐‹๐Œ ๐„๐œ๐จ๐ฌ๐ฒ๐ฌ๐ญ๐ž๐ฆ: Raja Iqbal kickstarted the day with an expansive overview of the LLM ecosystem, unveiling the technologies and frameworks driving the generative AI revolution.
    ๐Ÿ. ๐‚๐ก๐š๐ฅ๐ฅ๐ž๐ง๐ ๐ž๐ฌ ๐š๐ง๐ ๐‘๐ข๐ฌ๐ค๐ฌ ๐ข๐ง ๐„๐ง๐ญ๐ž๐ซ๐ฉ๐ซ๐ข๐ฌ๐ž ๐€๐๐จ๐ฉ๐ญ๐ข๐จ๐ง ๐จ๐Ÿ ๐‹๐‹๐Œ๐ฌ: This session focused on the practical hurdles enterprises face when adopting LLMs, discussing engineering, ethical, and legal challenges. Raja equipped attendees with the knowledge to navigate and mitigate these risks effectively.
    ๐Ÿ‘. ๐€๐ญ๐ญ๐ž๐ง๐ญ๐ข๐จ๐ง ๐Œ๐ž๐œ๐ก๐š๐ง๐ข๐ฌ๐ฆ ๐š๐ง๐ ๐“๐ซ๐š๐ง๐ฌ๐Ÿ๐จ๐ซ๐ฆ๐ž๐ซ๐ฌ: Luis Serrano captivated our audience with an in-depth session on attention mechanisms and transformers. From self-attention to multi-headed attention and encoder/decoder architecture, participants unraveled the complexities of these vital components of LLMs.
    ๐Ÿ’. ๐„๐ฏ๐จ๐ฅ๐ฎ๐ญ๐ข๐จ๐ง ๐จ๐Ÿ ๐„๐ฆ๐›๐ž๐๐๐ข๐ง๐ ๐ฌ: Raja further provided a comprehensive review of classical text representation techniques and the power of semantic embeddings like Word2Vec. This session laid a solid theoretical foundation for understanding how embeddings have evolved in text analytics and NLP tasks.
    ๐Ÿ“. ๐‡๐š๐ง๐๐ฌ-๐จ๐ง ๐„๐ฑ๐ž๐ซ๐œ๐ข๐ฌ๐ž ๐ฐ๐ข๐ญ๐ก ๐“๐…-๐ˆ๐ƒ๐… & ๐“๐ซ๐š๐ง๐ฌ๐Ÿ๐จ๐ซ๐ฆ๐ž๐ซ: The day concluded with a practical session where participants got their hands dirty with TF-IDF and Transformer exercises, including:
    o Preparing datasets with vectors
    o Writing data schemas for a vector database (using Redis)
    o Storing the data and creating a vector search index
    o Performing complex queries on a vector database including tag filters, numeric filters, text filters, geographic filters, combining filters, unions, range queries, and more.
    By the end of the day, attendees walked away with a robust understanding of LLM architecture, embeddings, attention mechanisms, and practical skills in handling vector databases.
    ๐ŸŒ ๐‰๐จ๐ข๐ง ๐ฎ๐ฌ ๐Ÿ๐จ๐ซ ๐ญ๐ก๐ž ๐ง๐ž๐ฑ๐ญ ๐œ๐จ๐ก๐จ๐ซ๐ญ ๐š๐ง๐ ๐›๐ž ๐ฉ๐š๐ซ๐ญ ๐จ๐Ÿ ๐ญ๐ก๐ข๐ฌ ๐ญ๐ซ๐š๐ง๐ฌ๐Ÿ๐จ๐ซ๐ฆ๐š๐ญ๐ข๐ฏ๐ž ๐€๐ˆ ๐ฃ๐จ๐ฎ๐ซ๐ง๐ž๐ฒ: hubs.la/Q02DjWtK0

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