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Joined 2 years ago
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Cake day: July 14th, 2023

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  • They put their repo first on the list.

    Right. And are we talking about the list for OBS or of repos in general? I doubt Fedora sets the priority on a package level. And if they don’t, and if there are some other packages in Flathub that are problematic, then it makes sense to prioritize their own repo over them.

    That said, if those problematic packages come from other repositories, or if not but there’s another alternative to putting their repo first that would have prevented unofficial builds from showing up first, but wouldn’t have deprioritized official, verified ones like OBS, then it’s a different story. I haven’t maintained a package on Flathub like the original commenter you replied to but I don’t get the impression that that’s the case.



  • A paid skillful engineer, who doesn’t think it’s important to make that sort of a change and who knows how the system works, will know that, if success is judged solely by “does it work?” then the effort is doomed for failure. Such an engineer will push to have the requirements written clearly and explicitly - “how does it function?” rather than “what are the results?” - which means that unless the person writing the requirements actually understands the solution, said solution will end up having its requirements written such that even if it’s defeated instantly, it will count as a success. It met the specifications, after all.









  • Giphy has a documented API that you could use. There have been bulk downloaders, but I didn’t see any that had recent activity. However you still might be able to use one to model your own script after, like https://github.com/jcpsimmons/giphy-stacks

    There were downloaders for Gfycat - gallery-dl supported it at one point - but it’s down now. However you might be able to find collections that other people downloaded and are now hosting. You could also use the Internet Archive - they have tools and APIs documented

    There’s a Tenor mass downloader that uses the Tenor API and an API key that you provide.

    Imgur has GIFs is supported by gallery-dl, so that’s an option.

    Also, read over https://github.com/simon987/awesome-datahoarding - there may be something useful for you there.

    In terms of hosting, it would depend on my user base and if I want users to be able to upload GIFs, too. If it was just my close friends, then Immich would probably be fine, but if we had people I didn’t know directly using it, I’d want a more refined solution.

    There’s Gifable, which is pretty focused, but looks like it has a pretty small following. I haven’t used it myself to see how suitable it is. If you self-host it (or something else that uses S3), note that you can use MinIO or LocalStack for the S3 container rather than using AWS directly. I’m using MinIO as part of my stack now, though for a completely different app.

    MediaCMS is another option. Less focused on GIFs but more actively developed, and intended to be used for this sort of purpose.


  • Wouldn’t be a huge change at this point. Israel has been using AI to determine targets for drone-delivered airstrikes for over a year now.

    https://en.m.wikipedia.org/wiki/AI-assisted_targeting_in_the_Gaza_Strip gives a high level overview of Gospel and Lavender, and there are news articles in the references if you want to learn more.

    This is at least being positioned better than the ways Lavender and Gospel were used, but I have no doubt that it will be used to commit atrocities as well.

    For now, OpenAI’s models may help operators make sense of large amounts of incoming data to support faster human decision-making in high-pressure situations.

    Yep, that was how they justified Gospel and Lavender, too - “a human presses the button” (even though they’re not doing anywhere near enough due diligence).

    But it’s worth pointing out that the type of AI OpenAI is best known for comes from large language models (LLMs)—sometimes called large multimodal models—that are trained on massive datasets of text, images, and audio pulled from many different sources.

    Yes, OpenAI is well known for this, but they’ve also created other types of AI models (e.g., Whisper). I suspect an LLM might be part of a solution they would build but that it would not be the full solution.


  • Both devices have integrated memory, so that 16 GB will look more like a 11/5, 12/4, or maybe even 14/2 split. The Steam Deck is also $400 for an LCD model or $550 for the OLED, not $800. It’s reasonable to expect more performance when you pay more.

    Because the Steam Deck has a lower native resolution, that means that less of the RAM will be used for the integrated GPU. Downscaling from 1080p to 720p doesn’t look good, either - and you could downscale to 540p if supported, but if you need to do that (vs choosing to for an emulated game) it probably won’t be pretty, either.

    This device is also running Windows, rather than a streamlined Linux-based launcher, meaning that more of that RAM will be taken up by OS processes by default.

    The article talks about how the 8840U benefits from more, fast RAM. You won’t get near the 8840U’s full potential gaming with 16 GB. 24 GB, on the other hand, would have been enough that games expecting 16 GB of system RAM would have been able to get it, even while devoting 6-7 GB to the GPU and 1-2 GB to the OS.





  • Thanks for clarifying! I’ve heard nothing but praise for Kagi from its users so that’s what I was assuming, but Searxng has also been great so I wouldn’t have been too surprised if you’d compared them and found its results to be on par or better.

    By the way, if you’re self hosting Searxng, you can use add your own index. Searxng supports YaCy, which is an actively developed, open source search index and crawler that can be operated standalone or as part of a decentralized (P2P) network. Here are the Searxng docs for that engine. I can’t speak to its quality as I still haven’t set it up, though.