What is JAX?

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  • Опубликовано: 5 окт 2024

Комментарии • 36

  • @GoogleResearch
    @GoogleResearch  Год назад +1

    Subscribe to the Google Research Channel → goo.gle/GoogleResearch

  • @khidhrhalab3543
    @khidhrhalab3543 Год назад +7

    If you were new to the field what would you learn first?jax or tensorflow ?

  • @gufrankanat3383
    @gufrankanat3383 Год назад +4

    Such a great introduction. Thanks for sharing

  • @stokedfool
    @stokedfool 4 месяца назад

    Definitely interested in what JAX has to offer. Appreciate the explanation. Cheers

  • @isaacatia-abugbilla2476
    @isaacatia-abugbilla2476 Год назад +15

    Will there be a specialization course for jax on learning platforms like you did with tensorflow?

    • @LaurenceMoroney
      @LaurenceMoroney Год назад +8

      No plans at the moment, sorry! I'm going to refresh the TensorFlow specializations, so may have some room for JAX in that.

    • @isaacatia-abugbilla2476
      @isaacatia-abugbilla2476 Год назад

      @@LaurenceMoroney Perfect! Thank you

  • @marverickbin
    @marverickbin Год назад +2

    Im into pytorch.
    Why should I consider going jax?

    • @LaurenceMoroney
      @LaurenceMoroney Год назад +5

      I'll give the answer in two ways, and the same as I give my staff.
      First: Soft skills --- it's never good to be a one-trick pony. Learn as many of the technologies that are as adjacent to yours as possible. Even if you never adopt them, it will make you understand your own better. I encourage Googlers to kick the tires of Pytorch for those very reasons. Otherwise all one would ever learn is from marketing and hype.
      Two: Hard skills -- the goal of JAX is to be a high performance numeric computing framework. It makes it a foundational technology in deep learning, but not *only* in deep learning. It's not a straight up apples to apples comparison. It lets you do things at a lower level that higher level frameworks like torch, tensorflow and keras abstract away. There's nothing wrong with abstraction, of course, but, if you want to be better at X, it's always good to have a way of getting deeper.

  • @pedropgusmao
    @pedropgusmao Год назад +4

    Why is this separate from Tensorflow?

    • @thedislikebutton163
      @thedislikebutton163 Год назад

      This is for researchers primarily. Different usecase

    • @LaurenceMoroney
      @LaurenceMoroney Год назад +4

      It's not. We work on both. But, to be clear, TensorFlow has high-level APIs for defining and training neural nets (amongst other scenarios) -- JAX is primarily optimized for numeric computing -- so it's not limited to deep learning etc.

    • @readbyname
      @readbyname 6 месяцев назад

      ​​@@LaurenceMoroney what about flax? Is flax going to replace tensorflow or tensorflow.keras for ML and DL?

  • @user-wr4yl7tx3w
    @user-wr4yl7tx3w Год назад +2

    More videos on Jax. 😊

    • @LaurenceMoroney
      @LaurenceMoroney Год назад

      This is the first in a series. Let me know what kind of stuff you'd like to see.

  • @gokulakrishnanm
    @gokulakrishnanm Год назад +1

    I heard that you are going to refresh TF specialisation when it will be done.

    • @LaurenceMoroney
      @LaurenceMoroney Год назад +2

      We're just getting started, so no end-date is confirmed, but in general, I'm aiming for early summer.

    • @gokulakrishnanm
      @gokulakrishnanm Год назад +1

      @@LaurenceMoroney ok I can wait for it 😇

  • @kartikpodugu
    @kartikpodugu Год назад

    how to convert a model trained using JAX to ONNX format ?

  • @SofianMW
    @SofianMW 5 месяцев назад

    great!

  • @MarcoServetto
    @MarcoServetto Год назад +2

    I wonder, is there any support for ML in Java instead? now that we are moving toward SW as a way to combine more and more ML systems seen as black boxes, It would be convenient to have support for other kinds of languages.
    In particular, python tends to favor a "system" programming style where the machine you are running on and how stuff is installed on it is relevant, and we often end up with a family of connected processes.
    While Java tend to push toward a large long living process where dynamic class loading with multiple class loaders can take care with more efficiency and portability of those same situations.

    • @falcon20243
      @falcon20243 Год назад

      The main code for most ML libraries is in C++. There are bindings available for most of the popular languages including Java. Both pytorch and tensorflow support JVM languages. This video is about JAX which is mainly for research purposes. People mostly use JAVA when they want to deploy models in Android.

    • @LaurenceMoroney
      @LaurenceMoroney Год назад

      There are bindings for Java in TensorFlow, but they're not nearly as popular as JavaScript or Python.

  • @ranimsaidi9564
    @ranimsaidi9564 Год назад

    How can JAX help in HPC applications?

    • @LaurenceMoroney
      @LaurenceMoroney Год назад +1

      If you need math done really really fast with JIT compilation that’s optimized for accelerators - that’s how JAX can help HPC 😀

  • @FoodReviewerByNusrat
    @FoodReviewerByNusrat Год назад

    good content

    • @LaurenceMoroney
      @LaurenceMoroney Год назад

      Thanks!

    • @FoodReviewerByNusrat
      @FoodReviewerByNusrat Год назад

      @@LaurenceMoroney I think you have been working on youtube for a long time but not getting the expected success.. If you want I can help you and do something good..

    • @LaurenceMoroney
      @LaurenceMoroney Год назад

      @@FoodReviewerByNusrat I’m happy with the level of success I’ve had 😀

  • @Fortyq
    @Fortyq Год назад +1

    how is this better than PyTorch?

    • @LaurenceMoroney
      @LaurenceMoroney Год назад +2

      Apples and Oranges

    • @Fortyq
      @Fortyq Год назад

      @@LaurenceMoroney IMO, JAX is just another frontend for XLA. I would be happy to listen to your opinion.

    • @LaurenceMoroney
      @LaurenceMoroney Год назад +1

      That’s what the X in JAX stands for! 😊