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Joined 2 years ago
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Cake day: July 9th, 2023

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  • Raster images do not need to be rendered - see Rendering:

    Rendering is the process of generating a photorealistic or non-photorealistic image from input data such as 3D models…Today, to “render” commonly means to generate an image or video from a precise description (often created by an artist) using a computer program.

    Note that “render” is a fairly generic term, and it is sometimes used like “render to the screen,” to just mean to display something. Rasterisation may be a better term to use here, since it only applies to vector graphics, and is the part of the process I am referring to.

    In any case, except for possibly reading fewer bytes from disk, the vector case includes all the same compute and memory cost as the raster image - it just has added overhead to compute the bitmap. On modern hardware, this doesn’t take terribly long, but it does mean we’re using more compute just to launch/load things.


  • It’s also worth noting apps have to ship higher resolution assets now, due to higher resolution displays. This can include video, audio, images, etc. Videos and images may be included at multiple resolutions, to account for different sized displays.

    For images, many might assume vectors are the answer, but vectors have to be rendered at runtime, which increases startup time in the best case scenario, and isn’t even always supported on all platforms, meaning they have to be shipped alongside raster assets of a few different sizes, further increasing package bloat. And of course the code grows to add the logic to properly handle all the different asset types and sizes.

    All this (packaging dependencies, plus assets/asset handling) to say it isn’t always malware, ads, electron, etc. Sometimes it’s just trying to make something that looks nice and runs well (enough) on any machine.



  • I’ve had the same problem with HeliBoard learning garbage. I just changed my settings though, and I think it should help:

    1. Open HeliBoard settings
    2. Open Text correction settings
    3. Scroll all the way to the bottom, and turn off “Add words to personal dictionary”

    If you scroll all the way to the top again, you can manually manage the personal dictionary, including adding words you do want, and deleting any junk that was added by mistake, before switching that setting off.




  • I’ve personally lived in places where the closest convenience store was 2.25 km, and the grocery store was nearly 18km, as well as places where a convenience store was literally a part of my building, and grocery stores were walkable distances.

    The U.S. is enormous and varied. Take a look at truesizeof and compare the U.S. and Europe (don’t forget to add Alaska and Hawaii - they won’t be included in the contiguous states). Consider how different London is from rural Romania.


  • This ignores the first part of my response - if I, as a legitimate user, might get caught up in one of these trees, either by mistakenly approving a bot, or approving a user who approves a bot, and I risk losing my account if this happens, what is my incentive to approve anyone?

    Additionally, let’s assume I’m a really dumb bot creator, and I keep all of my bots in the same tree. I don’t bother to maintain a few legitimate accounts, and I don’t bother to have random users approve some of the bots. If my entire tree gets nuked, it’s still only a few weeks until I’m back at full force.

    With a very slightly smarter bot creator, you also won’t have a nice tree:

    As a new user looking for an approver, how do I know I’m not requesting (or otherwise getting) approved by a bot? To appear legitimate, they would be incentivized to approve legitimate users, in addition to bots.

    A reasonably intelligent bot creator would have several accounts they directly control and use legitimately (this keeps their foot in the door), would mix reaching out to random users for approval with having bots approve bots, and would approve legitimate users in addition to bots. The tree ends up as much more of a tangled graph.


  • This ignores the first part of my response - if I, as a legitimate user, might get caught up in one of these trees, either by mistakenly approving a bot, or approving a user who approves a bot, and I risk losing my account if this happens, what is my incentive to approve anyone?

    Additionally, let’s assume I’m a really dumb bot creator, and I keep all of my bots in the same tree. I don’t bother to maintain a few legitimate accounts, and I don’t bother to have random users approve some of the bots. If my entire tree gets nuked, it’s still only a few weeks until I’m back at full force.

    With a very slightly smarter bot creator, you also won’t have a nice tree:

    As a new user looking for an approver, how do I know I’m not requesting (or otherwise getting) approved by a bot? To appear legitimate, they would be incentivized to approve legitimate users, in addition to bots.

    A reasonably intelligent bot creator would have several accounts they directly control and use legitimately (this keeps their foot in the door), would mix reaching out to random users for approval with having bots approve bots, and would approve legitimate users in addition to bots. The tree ends up as much more of a tangled graph.


  • I think this would be too limiting for humans, and not effective for bots.

    As a human, unless you know the person in real life, what’s the incentive to approve them, if there’s a chance you could be banned for their bad behavior?

    As a bot creator, you can still achieve exponential growth - every time you create a new bot, you have a new approver, so you go from 1 -> 2 -> 4 -> 8. Even if, on average, you had to wait a week between approvals, in 25 weeks (less that half a year), you could have over 33 million accounts. Even if you play it safe, and don’t generate/approve the maximal accounts every week, you’d still have hundreds of thousands to millions in a matter of weeks.