Data Science

  • 214 Posts
  • 505 Comments
Joined 1 year ago
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Cake day: June 17th, 2023

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  • Building from source is the opposite of hacky. It’s the recommended way to deal with things like this where you are concerned about trust and security. I understand that it’s not something you’ve done before, but it not as complicated as it sounds. There are many tutorials on how to build programs from source.

    I understand that providing official packages for fedora/rhel, Ubuntu/debian, and arch-based distro packages along with a flatpack and Appimage would make a lot of sense, but for whatever reason, signal has decided not to. Perhaps you can message the signal team to ask why they choose not to do this.




  • The down votes from non-subscribed accounts are amusing to me. These people clearly are looking for their “all” feed to be curated in some way. Ironically, machine learning could potentially help with that, but there are many people burnt out by the hype cycle (I don’t blame them).

    Regarding the article. It looks like the advancement here is finding methods to efficiently use sets of graphs which are an order of magnitude larger than prior methods could use for training? They also seem to have used more sets of graphs than prior models across a wider set of domains. Am I reading this correctly?







  • I’ve been comparing crates on crates.io against their upstream repositories in an effect to detect (and, ultimately, help prevent) supply chain attacks like the xz backdoor1, where the code published in a package doesn’t match the code in its repository.

    The results of these comparisons for the most popular 9992 crates by download count are now available. These come with a bunch of caveats that I’ll get into below, but I hope it’s a useful starting point for discussing code provenance in the Rust ecosystem.

    No evidence of malicious activity was detected as part of this work, and approximately 83% of the current versions of these popular crates match their upstream repositories exactly.