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kipukun
Joined 42 karma

  1. XGBoost is just faster on the GPU, regardless of the file format. A sibling post also pointed out compression helping out on bandwidth.
  2. The cuDF interop in the roadmap [1] will be huge for my workloads. XGBoost has the fastest inference time on GPUs, so a fast path straight from these Vortex files to GPU memory seems promising.

    [1] https://github.com/vortex-data/vortex/issues/2116

  3. This game is awesome. I have no other feedback other than I had a lot of fun.
  4. You'd be surprised. As long as your query is using Polars natives and not a UDF (which drops it down to Python), you may get good results.
  5. To the second footnote: you could utilize Polar's lazyframe API to do that cosine similarity in a streaming fashion for large files.
  6. For your wimsey library, using “pipe” to validate the contracts would seem to me to drastically slow down the Polars query because the UDF pushes the query out of Rust into Python. I think a cool direction would be to have a “compiler” which takes in a contract and spits out native queries for a variety of dataframe libraries (pandas/polars/pyspark). It becomes harder to define how to error with a test contract but that can be the secret sauce.
  7. Most people want unlimited for the convenience. You can very easily go to Fi or a budget carrier for more fine-grained plans like the ones you described.

    EDIT: typo

  8. Looking at your YC history, Rubbrband was initially meant to be "a way to train open-source Machine Learning models in just one line of code." I'm curious what this initial offering was and why you pivoted.
  9. Gainax's financial troubles are well documented in an interview with Hideaki Anno, where he detailed how the company was pretty dysfunctional from the start. The company's president was arrested for tax fraud in 1999, for example. This has been a long time coming.
  10. On the Parquet topic, the Polars lazyframe workflow of operating on a Parquet file is so convenient for me when wrangling hundreds of millions of rows. You avoid loading the data into a SQL server if you don't need to.
  11. Might've been overlooked, but "fastly" should probably be "quickly" on the main page.
  12. Do you think you'll add local file support in the future? Also, do you have any plans on making the reading of a source parallel? For example, connectorx uses an optional partition column to read chunks of a table concurrently. Cool how it's abstracted.
  13. I'll bite -- he discovered a vulnerability in a large company and responsibly disclosed it to them. How is that a felony? Why would you post a felony online?
  14. 1. I use it on all of my servers.

    2. FreeBSD offers a coherent base system with sane tools. pf is a godsend, and the ports collection is a good trade-off of configuration and simplicity. ZFS used to be a killer feature but is being integrated into Linux systems.

    3. FreeBSD is designed around "general purpose" use and has a lot of backing from corporations like Netflix.

    4. FreeBSD is missing a true container solution that is compatible with Docker (jails don't count). There has been some work on this as of the most recent BSDcon, so I'm hopeful.

    5. I never want to look at iptables again.

    EDIT: fix spacing

  15. Why not explain that POV?
  16. so you're saying Valve should release software that, if a bug appears in this now unsupported Chrome version, is now susceptible to this bug that will literally never get fixed?
  17. Neat project. Any roadmap for cross-validation support (GridSearchCV and friends)?
  18. You know, I really like this idea. It's simple, straight-forward, the website loads, and its demographic is mostly everyone. Good stuff. One qualm is that two scrollbars show up, probably from some overflow: scroll stuff. Would consider looking at that.
  19. Reading the article, they analyze data they show on charts. You could make the same conclusions they're drawing by also looking at the charts. Sure it's a shameless plug, but it definitely doesn't discredit their analysis.

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