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

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  • 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.






  • 500 grams of what, though? Folgers?

    The current average price per pound (454 grams) of ground coffee beans in the US was double that just a couple months ago, so spending $3.00 per pound would necessitate getting cheaper than average - and therefore, likely lower quality than average, or at least lower perceived quality than average - beans.

    The sorts of beans that companies tend to stock (IME) that are perceived as higher quality aren’t the same brands that I tend to buy (generally from local roasters), but they’re comparably priced. For a 5 pound (2267 grams) bag of one of their blends (which are roughly half the price of their higher end beans), it’s similar to what you’d pay for 5 pounds of Starbucks beans - about $50-$60.

    Often when a company says “free coffee,” they don’t mean “free batch-brewed drip coffee,” but rather, free espresso beverages, potentially in a machine (located in the break room) that automates the whole process. I assume that’s what Intel is doing.

    At $10 per pound (16 ounces) and roughly 1 ounce (28 grams) of beans per two ounce pour of espresso, that means that if each person on average drinks two per day, then that’s $1.25 for coffee per person per day.

    However, logistics costs (delivering coffee to all the company’s break rooms) and operational costs (the cost of the automatic machine and repairs, at minimum; or the cost of baristas, or adding the responsibility to someone’s existing job (and thus needing more people or more hours) if just batch brewing) have to be added on top of that. Then add in the cost of milk, milk alternatives, sweeteners, cups, lids, stir sticks, etc…

    Obviously if they just had free coffee grounds and let people handle the actual brewing of coffee in the break room, it would be much cheaper. But if the goal is to improve morale, having higher quality coffee that people don’t have to make themselves is going to do that better.






  • 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.