I'm not too keen on Tomorrowland. it's got a lot of great man theory messages in it, which isn't surprising since it was written and directed by Brad Bird, a notorious Objectivist
ranked-choice is the wrong choice here. it's expensive to print new ballots and the process is needlessly convoluted and wasteful. approval voting is not only cheap and effective, it more accurately represents the will of the people
it’s just a lot of Israelis seem to see all gazans as hamas now, which is ~~problematic~~ genocidal
fixed it for you
opt-in analytics! servers running Synapse can choose to send a bit of analytics information like number of users, but it's opt-in so the number is potentially even higher
i'm not informed much either, but here's what i gather; it's centralized around the proprietary Snap Store and you can't run your own Snap repositories, Snap apps take ages to start up, and each Snap app is mounted as a separate partition (???). there's a whole bunch of technical issues that go over my head too, and Snaps have seen so little adoption that Canonical basically had to twist the arms of flavor maintainers to drop Flatpak support and support Snap out of the box. it's evidently so bad even Ubuntu's official flavors wouldn't support it until Canonical forced them to
yes. it only surfaces citations that may back up the content better, an editor still has to read the source and approve the change
Wikipedian here - AI on Wikipedia is actually nothing new. we've had a machine learning model identify malicious edits since 2017, and Cluebot (an ML-powered anti-vandalism bot) has been around for even longer than that.
even so, this is pretty exciting. from what i gather, this is a transformer model turned on its side; instead of taking textual data and transforming it, it checks to see if two pieces of textual data could reasonably be transformations of each other. used responsibly, this could really help knock out those [dubious] and [failed verification] tags en masse
lmao nice catch, i'll edit the date
to be honest i'm not entirely sure what the draw is either. many reaction videos are based around a theme, like "school tiktoks i watch instead of doing homework", so maybe it's an easy way to find more-or-less quality content about a particular subject without having to actually look for it. or maybe people just watch for the funny faces, given that SSSniperWolf's audience tends to be very young.
i do like "[expert] reacts to..." videos where an expert does a thorough analysis of some media featuring their field of expertise, like "Traçeur reacts to Mirror's Edge" or "Martial artist reacts to Avatar: The Last Airbender" or "Chemist reacts to Breaking Bad", but that is an entirely different thing than freebooting because it's thoughtful commentary that's transformative and adds to the video
it's in the name: generative pre-trained transformer. the one thing ChatGPT and GPT-3/3.5/4 are truly good at is transforming data. it can restructure paragraphs to have a different flow, take class notes and make flashcards out of them (that's how i use ChatGPT), or even take non-textual data and potentially present it in textual format if trained right
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