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Joined 10 months ago
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Cake day: November 22nd, 2023

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  • I really don’t understand how people use Instagram. I’ve tried, but it’s about 45% ads, 10-15% posts by people I don’t follow, it’s not in chronological order (or any sense of order for that matter), and regardless of whether I was on there yesterday or 2 months ago, it’ll show me about 40 posts before saying “You’re all caught up from the past 3 days!” and then refuse to show me any more.

    I guess this is why I’m here on Lemmy and went crawling back to Tumblr, one of the last vestiges of the old internet. At this point, I’d rather watch a platform die than become marketable to advertisers and shareholders.


  • This is why I said “you might as well do something worth the punishment.” In the US, protesting can get you more harsh sentences than crimes like assault or robbery. And not to “That’s, like, just your opinion, man” but…it’s just my opinion that their time would’ve been better spent blocking the street and holding up rush hour traffic or something for the punishment that they got. Like you said, it clearly worked because people are talking about it - and talking about it enough that the arguing in another post on this article got the post locked.

    I’m not here to rag on them. Again, there’s no “right way to protest,” and this is a noble cause to protest for.








  • The only way these “play to earn” games can work is as a pyramid scheme. Everybody wants more money out of the pot than they’re putting in, and the company sure as hell isn’t going to run at a loss. Many of them seem to only deal with currency through their own exchange (for fiat currency directly) or through markets backed by coins that are also backed by fiat currency, like bitcoin, for exactly the reasons that you laid out. Can’t make money if everybody is buying your funny money with other funny money that lost 99% of its value 3 months after it appeared.

    The only other way somebody could make this work is if the players are the product, but at that point, why wouldn’t you just sell ad space on a website.



  • Steam has a very generous 2 hours played policy where the system will basically refund you no questions asked so long as you have played less than 2 hours of the game (refunds beyond that are totally possible but usually require manual review before approval).

    This means that you can buy the game, open it once, leave a negative review, and get it refunded. Which is more impactful on Sony’s bottom line than leaving a review on Metacritic or something because it directly affects the game’s rating on the largest platform for PC gaming, and is therefore more likely to see action taken to fix the issue. Sony doesn’t care if people make angry social media posts, but they will care if they can directly see it impacting their profit margins.


  • I think the first stat in the graph is the most important one and really speaks to the reason for the last one. I said this is another post about this article, but video games have become their own kind of third space. Going out with friends has become so expensive, whether you’re going to a movie or something else, and in a lot of places you can’t go to hang out without having to spend money anyways, so video games have become a replacement way to hang out with friends. And that’s before you start talking about stuff like friends who moved across the country for work or something.



  • Another Millennial here, so take that how you will, but I agree. I think that Gen Z is very tech literate, but only in specific areas that may not translate to other areas of competency that are what we think of when we say “tech savvy” - especially when you start talking about job skills.

    I think Boomers especially see anybody who can work a smartphone as some sort of computer wizard, while the truth is that Gen Z grew up with it and were immersed in the tech, so of course they’re good with it. What they didn’t grow up with was having to type on a physical keyboard and monkey around with the finer points of how a computer works just to get it to do the thing, so of course they’re not as skilled at it.


  • Because we’re talking pattern recognition levels of learning. At best, they’re the equivalent of parrots mimicking human speech. They take inputs and output data based on the statistical averages from their training sets - collaging pieces of their training into what they think is the right answer. And I use the word think here loosely, as this is the exact same process that the Gaussian blur tool in Photoshop uses.

    This matters in the context of the fact that these companies are trying to profit off of the output of these programs. If somebody with an eidetic memory is trying to sell pieces of works that they’ve consumed as their own - or even somebody copy-pasting bits from Clif Notes - then they should get in trouble; the same as these companies.

    Given A and B, we can understand C. But an LLM will only be able to give you AB, A(b), and B(a). And they’ve even been just spitting out A and B wholesale, proving that they retain their training data and will regurgitate the entirety of copyrighted material.



  • The argument that these models learn in a way that’s similar to how humans do is absolutely false, and the idea that they discard their training data and produce new content is demonstrably incorrect. These models can and do regurgitate their training data, including copyrighted characters.

    And these things don’t learn styles, techniques, or concepts. They effectively learn statistical averages and patterns and collage them together. I’ve gotten to the point where I can guess what model of image generator was used based on the same repeated mistakes that they make every time. Take a look at any generated image, and you won’t be able to identify where a light source is because the shadows come from all different directions. These things don’t understand the concept of a shadow or lighting, they just know that statistically lighter pixels are followed by darker pixels of the same hue and that some places have collections of lighter pixels. I recently heard about an ai that scientists had trained to identify pictures of wolves that was working with incredible accuracy. When they went in to figure out how it was identifying wolves from dogs like huskies so well, they found that it wasn’t even looking at the wolves at all. 100% of the images of wolves in its training data had snowy backgrounds, so it was simply searching for concentrations of white pixels (and therefore snow) in the image to determine whether or not a picture was of wolves or not.


  • Yep, they literally cannot work any other way than as a ponzi scheme. Because the people “earning” want to take more money out of the system than they put in, and the company is taking money out as well just to keep the game running and the employees paid, as well as to make a profit. So you need substantially more suckers buying into the system than the money that is being paid out.

    Eventually, somebody is gonna be left holding an empty bag.


  • I’m reminded of a comment I saw once where somebody was saying how when they were young, they were told that AI would do the miserable jobs so that people would have more time to make art and poetry, while today the AI makes art and poetry so that we can work longer hours at the miserable jobs.

    And the AI bros say that this is just a necessary step towards automating away the crappy jobs, but it’s not like they’ll stop automating everything else if/when AI reaches that point. The AI will still continue to automate away the hyman experience of art and culture for the rich. They’re not going to suddenly decide to implement Luxury Gay Space Communism at that point. They’ll just cram everybody into Kow Loon style ghettos.