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Joined 1 year ago
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Cake day: November 22nd, 2023

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  • The worst I have to do is use a different proton version or add in a launch option.

    And therein lies the problem that keeps most people from switching to Linux. It’s a super simple thing to do, but Linux users fall into the same fallacy that experts in any field do: just how little the average person knows about the subject. The fact that something doesn’t just work when you try to open it would leave many people stumped. Especially with tech literacy rates declining thanks to kids growing up using mostly cell phones as their daily driver rather than an actual computer and the plug and play nature of Windows and Macs. Asking your average gamer to add command line arguments to a launcher would probably be like telling them they just have to hot wire their car if it doesn’t start when you turn the key.




  • By “abrupt,” I mean that Windows 7 ended service updates just last year, and Windows 10 will end next year. And by “current,” I mean that Windows 11 overtook 7 as the second most used version of Windows in 2022.

    We’ve known that they’re ending support for 10 next year for a few years, but that end of life timeline is very short compared to previous versions of Windows. If 10 had the same end of life timeline as 7, we’d be seeing service updates for 10 ending in 2030. And 11 may be the newest version of Windows, but it is by all means not the most used version and is most likely not the version currently being used by most people that this article is relevant to.





  • The underlying point misses why people have problems with the current AI bubble. I’ll cheer when they replace CEOs with AI - it seems like the best job to be replaced with LLMs and would save companies billions of dollars that could be used to improve the lives of workers. There’s tons of AI being used for all kinds of cool things already like spotting cancer in MRIs.

    The issue people have with AI isn’t the tech. It’s who’s making it and why. It’s not being used to make life easier and better, it’s being used to cut decent paying jobs and commodify part of the human experience, all while making big profits without paying the people whose work was stolen to make those profits.

    It’s just a different flavor of the fast fashion industry stealing high fashion designs and churning out their cheap knockoffs from factories in China where they don’t have to worry about things like safety standards or paying their workers a living wage.


  • Fun fact: After the adoption of electric lighting in homes became common, there was a massive increase in the demand for maids and cleaning services because people simply couldn’t see just how dirty their houses were when everybody was using candles.

    Another fun fact: With the introduction of the computer and similar technology into many jobs, productivity skyrocketed, but wages didn’t rise to match the increase in company profits. However, it was still viable for the average American household to live off of the wages of one 40 hour per week job. Today, the average American household requires at least 2 full-time salaries in order to survive, despite technology continuing to push productivity even higher and companies continuously reporting their most profitable year ever, year over year. Despite technology, the amount of work per household has effectively doubled or more over the past 60 years.



  • “When I was young, they told me that one day, AI would do the menial labor so that we would have more time to do what we love - like art, music, and poetry. Today, the AI does art, music, and poetry so that I can work longer hours at my menial labor job for lower wages.”

    Also, on point one, I still see a lot of job hirings for personal secretaries and people for data entry and to take minutes at meetings, and plenty of people complaining about not being able to actually talk to somebody on the phone to get their problem solved.


  • A lot of this started in the US because the big telecom companies were paid a lot of money by the government to roll out broadband in the middle of the country, where customers are spread out enough that they didn’t want to bother building the infrastructure, but they took the money and did none of the work. So, these communities did it themselves. Some of them literally burying fiber optics cables by hand through their farm fields.

    I remember reading somewhere a few years ago about how this is feasible on the neighborhood level now at potentially better speeds and cheaper than the telecom companies with a satellite connection that people can use via a wi-fi network across the neighborhood.



  • 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.





  • 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.