Training AI Models with Federated Learning

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  • Опубліковано 6 лис 2024

КОМЕНТАРІ • 23

  • @mahiaravaarava
    @mahiaravaarava 2 місяці тому +1

    It's incredible how it allows data to be used without compromising privacy or security. This could be a game-changer for industries that handle sensitive information, like healthcare and finance.

  • @clivejefferies
    @clivejefferies Рік тому +5

    I really enjoy this series. The explanations are really clear and simple to understand.

  • @sarahgh8756
    @sarahgh8756 Місяць тому

    I love your explanation method. all clear, with the best order possible and I love the color of markers :))) Thank you. Really helpful.

  • @timyasin2909
    @timyasin2909 Рік тому +1

    In what degree you are considering SMPC instead of other encryption for secure model aggregation? Anyway, Thanks for the comprehensive recent concepts! FTL is new!

  • @pedrojesusrangelgil5064
    @pedrojesusrangelgil5064 Рік тому +1

    Nice content , where to learn more about federated leraning? Thanks!

  • @MddM-q4u
    @MddM-q4u Рік тому +7

    I prefer it when you draw things from scratch. I am even learning how to do that in preparation for my job interview.

    • @IBMTechnology
      @IBMTechnology  Рік тому +3

      We've done it both ways and lately we're experimenting with more pre-drawn diagrams so the speaker can cover their main points more quickly. For example, the Cybersecurity Architecture videos with Jeff Crume are longer than usual (12 to 25 minutes) with multiple board changes: ua-cam.com/video/jq_LZ1RFPfU/v-deo.html

  • @tim-d-s
    @tim-d-s Рік тому +1

    This was concise and well put together. Thank you!

  • @joshuathomasbrooks9450
    @joshuathomasbrooks9450 3 місяці тому

    Can you explain more examples? Like healthcare data. I understand from a high level but not in practice.

  • @1989arrvind
    @1989arrvind Рік тому

    Federated learning explanation was great 👍👍👍👍👍

  • @neail5466
    @neail5466 Рік тому

    An example of dataset and the regarding insight would have been helpful to understand why the insight is not back traceable.

  • @amoghkamattarcar9676
    @amoghkamattarcar9676 Рік тому

    Any new research on Federated Learning applied to Foundation Models?

  • @glitchAI
    @glitchAI 6 місяців тому

    nice. this gave me the intuition.

  • @MariaAkterRimi-h9y
    @MariaAkterRimi-h9y 7 місяців тому

    very nicely interpreted!

  • @aneesharma3240
    @aneesharma3240 Рік тому

    It would be very great if, spoken about dataset distribution- iid and non iid and how FL is effected . Specifically non iid setting.

  • @gauravpoudel7288
    @gauravpoudel7288 Рік тому

    awesome content

  • @felix_1891
    @felix_1891 Рік тому

    Thanks man

  • @timonesh7949
    @timonesh7949 Рік тому

    greatt!!

  • @ousefk5476
    @ousefk5476 8 місяців тому

    Are you mirrored or did you master the art of writing mirrored?

  • @prianigel
    @prianigel Рік тому +1

    We need regulation in the industry where publicaly traded companies issue fractional stocks to those teaching AI models from web scraping for example.
    Lets say I post code for a tcp socket server IBM would like to use. AI scrapes it, learns it, uses it, and voila, I now am issued one thousandth of a share of IBM.
    But not the 30 script kiddies who copied my code and put on the Holy You Tube ... because AI would know I posted it first.
    Or I could say, ah, that would be cool to share, but why post it, I will just get ripped off anyway?
    Fractional stock issuance solves the clerical head aches of other systems I believe

    • @adamconrad5249
      @adamconrad5249 5 місяців тому

      A good idea, but current language models are fundamentally bad at knowing where the got their data from. hopefully we can solve this!

  • @jstevh
    @jstevh Рік тому

    Identify cats? 😅

  • @thomasgale8695
    @thomasgale8695 Рік тому

    You realize that sharing the updated learning gives up the individual companies competitive advantage without giving up their sensitive data? They're giving the milk for free, but keeping their cow.