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learndeeply

HN member
Joined
Tue, Mar 22, 2022, 5:43 PM UTC
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389
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89 items

About learndeeply

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Recent public activity

  1. comment
    Comment #33701238

    Hilarious name for an open source project released by a government lab.

  2. comment
  3. comment
    Comment #33580092

    > For me, it was simply a gut feeling. I’ve been talking to founders and doing deep dives into technology companies for decades. It’s been my entire professional life as a writer. …

  4. comment
    Comment #33580028

    Is it common to have the same number of employees as there are companies funded at a VC? Is each one assigned a company?

  5. comment
    Comment #33579522

    Brilliant way to get thousands of tech people to look at your business card. Edit: This was updated, it used to point to his real Github username. Not that there's anything wrong w…

  6. comment
    Comment #33558217

    Aside from the project itself, the production value of this video is crazy good.

  7. comment
    Comment #33463809

    JAX is a DSL on top of XLA, instead of writing Python. Example: a JAX for loop looks like this: def summ(i, v): return i + v x = jax.lax.fori_loop(0, 100, summ, 5) A for loop in Ti…

  8. comment
    Comment #33463138

    Previous discussion: https://news.ycombinator.com/item?id=22374825 Wonder if anyone's turned Instagram's version of Blurhash into a library?

  9. comment
    Comment #33462639

    I can't think of anything that neural nets can't beat, except small tabular data with boosted decision trees. Can you give some examples?

  10. comment
    Comment #33462627

    The code is very easy to read. Doesn't seem like there's data/model parallelism support for training, which will be important for real-world use.

  11. comment
    Comment #33380513

    https://github.com/intel/intel-extension-for-pytorch PyTorch version. Looks like it's been supported a lot longer than TensorFlow, the repo dates back over a year.

  12. comment
    Comment #33380471

    > And honestly, their hardware is pretty bad for ML given you can pick up a used 3090 for $600. How do you know it's bad? Do you have benchmarks? Just checked, used 3090s are going…

  13. comment
    Comment #33340002

    No, it's meant for taking something like a CSV file and deciding if each row matches a specific category. A common example, have a CSV, columns corresponding to different features …

  14. comment
    Comment #33295284

    My mistake, I was thinking of gpt-neox. Thanks for the correction.

  15. comment
    Comment #33291290

    > Tensorflow serving is barely controllable, and requires insane tuning to make it perform the same as pytorch What are you using for serving PyTorch models?

  16. comment
    Comment #33291228

    PyTorch has been a darling of almost every noteworthy open source model for the past 3-4 years (BLOOM, GPT-J, StyleGAN3, detectron, etc). Personally, I've only seen people use Tens…

  17. comment
    Comment #33291198

    Looks like its just a name collision. It's a tensor used in distributed models, thus Distributed Tensor, or DTensor for short.

  18. comment
    Comment #33281155

    The parent comment said it would be "a good start". It's like adding sleep(1000) to a benchmark to purposely make it look worse than your own product.

  19. comment
    Comment #33270967

    How would I be able to respond to the post in detail if I didn't read it? What a bizarre, defensive response. To address your points: - Multiple formats were compared Yes, but not …

  20. comment
    Comment #33270931

    "ML" was never monopolized by Python. Boosted decision trees, as the post demonstrates, are commonly done in Matlab, R, or Julia. Deep learning however is 99% Python interface.

  21. comment
    Comment #33270903

    Python can be fast if you don't intentionally cripple it. Doing the following will be most likely a lot faster than postgresml: - replace json (storing data as strings? really?) wi…

  22. comment
    Comment #33265071

    > Vivid Natural — A slide of jam, jazzman, hook, band, pipe, and coil. Small contrasting details in natural colors. vivid natural. This one generates the string instruments with th…

  23. comment
    Comment #33265037

    Can you summarize the approach you took on creating the model? Really curious!

  24. comment
    Comment #33255555

    (not a hardware engineer) This looks like Google's version of Infiniband, which is basically mandatory for large scale ML-training servers due to issues with Ethernet, as described…

  25. comment
    Comment #33244958

    Microsoft invested $1B in OpenAI in 2019, the valuation is probably somewhere in the neighborhood of $5-20B.