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Joined 1 year ago
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Cake day: June 8th, 2023

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  • …are you serious?

    There would be so much data in understanding people’s light usage. For example, you could figure out how late or early people get up, number of people living in a house, how crowded the house is, how many lights are used per room, etc etc. it would be a gold mine of information.

    Let’s say you’re a home automaton designer. You want to design devices to be used in the home, but in order to design such devices, you need enough of a stockpile of user data. This lightbulb data would be incredible valuable.

    You can probably even analyse the data and determine things like whether someone is watching tv late at night.

    From a nefarious view, how valuable would this data be to robbers and thieves?


  • These things are interesting for two reasons (to me).

    The first is that it seems utterly unsurprising that these inconsistencies exist. These are language models. People seem to fall easily into the trap in believing them to have any kind of “programming” on logic.

    The second is just how unscientific NN or ML is. This is why it’s hard to study ML as a science. The original paper referenced doesn’t really explain the issue or explain how to fix it because there’s not much you can do to explain ML(see their second paragraph in the discussion). It’s not like the derivation of a formula where you point to one component of the formula as say “this is where you go wrong”.


  • phario@lemmy.catoLinux@lemmy.mlHyprland is a toxic community
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    1 year ago

    Hmmm. If abuse happens, is the right idea to say that “I don’t need this community”?

    I’m not sure how that HackerNews comment helps in the slightest. If my university has an obscure basket weaving community and people are getting abused in that community, should I just say “Eh we don’t actually need a basket weaving community”.

    It’s also amusing to me that a commenter on a relatively obscure and niche website is complaining that that don’t need (or care about abuse that transpired on) a niche community from another website. And then this comment is echoed in yet another niche community.






  • Sorry, I think you misunderstand that I’m talking about a large scale problem rather than a personal problem. Of course people can individually download videos to preserve.

    Imagine losing YouTube’s videos next week. You would have effectively lost nearly two decades worth of media chronicling human and technological development (more if you take into account that YouTube has repositories of older media).

    Someone described it like the Library Alexandria. In terms of density of information, I think the comparison is apt.

    A good comparison that might be too old for some readers. Back in the 80s and 90s, the early internet was populated via usenet discussions. Google eventually bought this data and merged it into Google Groups. However Google Groups was disbanded. This meant that some archives can no longer be accessed because to do so requires some active component no longer in service. We have effectively lost gigantic chunks of early 90s internet history. A lot of this history was quite important in many facets of life.


  • There is already something like this via the Wayback Machine (who indeed do copies of video media but more typically VHS and other things) and things like the Russian Library genesis, which is kept in torrent format.

    The problem really is that storage for video media is insane compared to storage of document or even photo data.

    If people here haven’t read into it, it’s incredibly interesting to look into the way the Internet Archive works. In particular you have to begin to concern yourselves with how long it takes for HDs, SSDs, and other media to degrade in time.


  • Hmm to be fair with YouTube you don’t think this is now a repository of incredibly valuable resources? If YouTube went down and we lost all videos, we would be losing many important resources, from historical documentaries no longer easily found in media, to guides on woodworking.

    It’s a bit scary. Once you remove the crap, it’s an incredibly valuable library resource and time capsule.


  • I just noticed this.

    As others have mentioned the stars have been largely useless in the last little while so to be honest I’m not sure this has any impact. Even sites that try and give a rating based on fake reviews are not helpful because so many reviews are faked. The only helpful part is to try and read negative reviews.

    I imagine this star fiasco is something that’s easy for browser plugins to reverse.

    I would love to see AI and Machine Learning used to filter out fake reviews. This would actually be useful.


  • Nah this is changing.

    This of course is what they said about tablets. Now people are replacing desktop or laptop workflow with tablets, or alternatively tablets are being designed with removable keyboards so the lines are blurred.

    I know scientific researchers who now only travel to conferences with tablets instead of their laptops.

    Finally, I predict that we’re moving to cloud computing. It’s the natural way. You VPN into a network and your computing is done on a cluster or on a central computer.

    The same is already happening for gaming. People are connecting controllers and glasses like the Xreal Air to phones, then networking into a computer to play a desktop game on their phone.


  • I can tell by your writing that you’re a rational person and you’ve obviously thought about things. But…I’m not sure we’re arguing about the same thing.

    The point is that you would previously be able to buy a new car for say $20k or a used one for $5k. The used one might drive nearly as well as the new one, if properly maintained. So you were “saving” $15k.

    The idea that brand new items can lose value to their “steady-state” value (imagine a graph that sharply descends in the first year) isn’t an absurd one.

    That said, I understand that some people might value that “new feeling” and want to pay that $15k difference. Or might value their time and troubles in potentially dealing with the issues of a used car.

    Of course, people are raising the issue that the market might have changed recently. I don’t really follow the pricing of new cars. I remember a few years ago hearing that the car industry was in trouble because essentially cars were lasting longer and longer and so they were unable to keep on selling the new models to suckers.


  • Yes.

    I think with something like this you have to do a literature search. Even then it’s kind of tough because I’m sure it’s very hard to do objective tests of these traits.

    You might say that any activity has similar aspects. Learning a difficult passage in music, learning to speak languages, learning to throw a basketball through a hoop, etc.

    I’m not sure there is a huge amount of evidence that video games teach resilience any more than any other similar activity. Moreover, it’s easily the kind of thing that our biases set us up to believe things that aren’t there. For every person who learned resilience from video games, there might be three other people who learned poor lessons, like “I should be lazy and play video games and not study for my exams.”

    With academic or professional resilience, I can’t say I’ve seen any positive correlation with video games.

    I could easily argue that excessive video game play makes you less resilient to doing non-video-game challenges.




  • Part of the problem with AI is that it requires significant skill to understand where AI goes wrong.

    As a basic example, get a language model like ChatGPT to edit writing. It can go very wrong, removing the wrong words, changing the tone, and making mistakes that an unlearned person does not understand. I’ve had foreign students use AI to write letters or responses and often the tone is all off. That’s one thing but the student doesn’t understand that they’ve written a weird letter. Same goes with grammar checking.

    This sets up a dangerous scenario where, to diagnose the results, you need to already have a deep understanding. This is in contrast to non-AI language checkers that are simpler to understand.

    Moreover as you can imagine the danger is that the people who are making decisions about hiring and restructuring may not understand this issue.


  • Amazing work.

    One of the biggest issues I had with BI4L was how annoying US-Centric it was. I’m not sure how you can address this issue in the Wiki but you should be aware it does reek of American arrogance :)

    I guess at a minimum maybe make some kind of tag or filter for the country?

    Is there some intention to eventually open editing up to others? I assume you don’t want to maintain this kind of list to perpetuity.