How modern search engines work - Vector databases explained! | Weaviate open-source

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  • Опубликовано: 17 ноя 2024

Комментарии • 26

  • @bryanbischof4351
    @bryanbischof4351 3 года назад +16

    This is really well presented. One further topic for ppl to investigate if they’re curious is the latent spaces that the vectors are encoded with, the distance functions in those LS, and how traditional lookups might suffer.

  • @bamigbadeopeyemi2953
    @bamigbadeopeyemi2953 3 года назад +7

    This presentation took away the complexity at comprehending what vector search engine is. I was totally lost on the concept but got a clear understanding of what Ai search engine is general. Thanks for sharing 😘. With Weaviate, vector search engine at scale certainty is 💯✍🏼

  • @ChatGPT-ef6sr
    @ChatGPT-ef6sr Год назад +2

    Super sleek explanation

  • @internetbro6519
    @internetbro6519 Год назад +2

    I just found your channel and you are awesome! Love the whisper at the end (yup, it's the main reason I'm leaving this comment 😃 such great personality), well done!

  • @dawidtaborski
    @dawidtaborski Год назад +3

    Thank you for this content.

  • @DerPylz
    @DerPylz 3 года назад +10

    Very informative! Thanks!
    Also: Congrats on the 7k subs! 🎉

  • @dawid_dahl
    @dawid_dahl Год назад +2

    Excellent presentation! 🙌🏻

  • @WhatsAI
    @WhatsAI 3 года назад +6

    Such a great subject to cover! Congrats on the sponsor as well! Super well explained as always!

  • @ThamizhanDaa1
    @ThamizhanDaa1 2 года назад +4

    Your channel is so underrated! I'm a PhD student and this is so helpful!!

    • @AICoffeeBreak
      @AICoffeeBreak  2 года назад +3

      Thanks! This makes me so happy being a PhD student too!

  • @wii3willRule
    @wii3willRule 3 года назад +8

    Your channel is so useful, as someone who's beginning to work in the world of AI

    • @AICoffeeBreak
      @AICoffeeBreak  3 года назад +4

      Thanks! Making useful things is our goal. 😊

  • @adithyavenkateswaran7908
    @adithyavenkateswaran7908 3 года назад +7

    That is a brilliant explanation! Love it!!

  • @Skinishh
    @Skinishh 2 года назад +2

    Very well explained! However, usually the first step in a search engine is a candidate selection step, that reduces the number of candidates with a faster algorithm. Performing similarity matching between your query and EVERY item in the database is too heavy to compute in 1-2 seconds.

  • @paleyshow
    @paleyshow Год назад +1

    This is super helpful and very intuitively explained, finally understand vector databases! :)

  • @高长宽
    @高长宽 3 года назад +9

    wonderful!

  • @elinetshaaf75
    @elinetshaaf75 3 года назад +8

    Cool

  • @ssss-u7w
    @ssss-u7w 9 месяцев назад

    do u have any example with Vector Geo data ? please make video on that that

  • @Diego0wnz
    @Diego0wnz 3 года назад

    How do transformers understand abbreviations or bigram/trigrams on a character level of words? I never understand how this preprocessing step is done, I only learned about the old elmo method

  • @amparoconsuelo9451
    @amparoconsuelo9451 Год назад

    Please give a Python code to search vector database.