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

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  • It’s okay, the author of the article didn’t actually read (or understand) the Copyright Office’s recommendations. They are:

    Based on an analysis of copyright law and policy, informed by the many thoughtful comments in response to our NOI, the Office makes the following conclusions and recommendations:

    • Questions of copyrightability and AI can be resolved pursuant to existing law, without the need for legislative change.
    • The use of AI tools to assist rather than stand in for human creativity does not affect the availability of copyright protection for the output.
    • Copyright protects the original expression in a work created by a human author, even if the work also includes AI-generated material.
    • Copyright does not extend to purely AI-generated material, or material where there is insufficient human control over the expressive elements.
    • Whether human contributions to AI-generated outputs are sufficient to constitute authorship must be analyzed on a case-by-case basis.
    • Based on the functioning of current generally available technology, prompts do not alone provide sufficient control.
    • Human authors are entitled to copyright in their works of authorship that are perceptible in AI-generated outputs, as well as the creative selection, coordination, or arrangement of material in the outputs, or creative modifications of the outputs.
    • The case has not been made for additional copyright or sui generis protection for AI- generated content.

    Pretty much everything the article’s author stated is contradicted by the above.




  • 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.


  • 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.


  • As it is, you only see new comments if you scroll past the post again (and your client has refreshed it) or if you open it directly. If your client hasn’t updated the comment count or if you refresh your feed and the post falls off, you’ll never see it anyway.

    A “Watch” feature would solve this better. If you watch a post, you get aggregated notifications for edits and comments on the post. If you watch a comment, you get aggregated notifications for replies to it or any of its children.

    By aggregated notifications, I mean that you’d get one notification that said “The post you watched has been edited; 5 new comments” rather than a notification for each new comment.

    Then, in addition to exposing a “Watch” action on posts and comments, clients could also enable users to automatically hide posts that are watched, either by marking them as hidden or by hiding watched posts without updates.

    If the latter approach were taken, notifications might not even be necessary - the post could just get added back into the user’s feed when changes were made. It would result in a similar experience to forums, where new activity in a topic would bump it to the front, but it would only impact the people who were watching it.

    You can kinda get that behavior by sorting your feed by Active, but this could be used with other sorting methods.



  • 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.






  • “But tante, then we will never have Open Source AI”. Exactly. That’s how reality works. If you can’t fulfil the criteria of a category you are not in that category. The fix is not to change the criteria. That’s playing pigeon chess.

    This is a bad take. If your criteria aren’t grounded in reality, they aren’t useful, so of course you should change the criteria.

    It’s also a missed opportunity to point to an AI model that did things right and that would qualify as “open source AI” even if that definition were not watered down. For example, OLMo (which I just learned about) says that they provide full insight into the training data as well as “full model weights, training code, training logs, training metrics in the form of Weights & Biases logs, and inference code.” Their most complex models are 7B models, which is enough to be relevant.

    Saying “Meta and Alphabet will never release Open Source AI that meets the proposed definition” is fine. Saying “we’ll never have Open Source AI, period, that meets the proposed definition” means your proposed definition needs rewritten.