[+] -13 points 10 hours ago (2 children)

Sure they can. The fundamental similarity here is anti-intellectualism, a distrust in the notion that science and technology are positive things that can enhance our lives. America is rife with it these days and the result is all sorts of beliefs sweeping through society that stand in opposition to what the "experts" say. Vaccines cause autism. Pasteurization is bad. "Chemicals" or "GMOs" are bad. Transgenderism isn't real. Data centers are responsible for vast quantities of water consumption. LLMs are incapable of creating anything original. And so on. Once these beliefs get rooted then any effort to dislodge them only becomes part of the narrative of untrustworthy oligarchs and technocrats trying to manipulate people, which is especially tricky because many of them are trying to manipulate people. Makes it hard to know which authorities to trust without learning enough to become one yourself, and learning is hard when you don't know which information sources to start with.

Unfortunately I have no idea how to counter such a large-scale movement in society. As the old saying goes, you can't reason someone out of a position they didn't reason themselves into. A lot of the anti-science sentiment comes from irrational sources - fear of the uncertain future, fear of losing prestige and power, fear of loss of personal autonomy. Some of those fears are rooted in real concerns but the reactions they can provoke are not necessarily productive.

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  • [–] 11 points 17 hours ago (5 children)

    Alas, "the least-worst candidate who had a plausible chance of winning" is generally the best outcome for most democracies.

    Don't let the perfect be the enemy of the good. Or the "well he's okay I guess", in this case.

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  • [–] 7 points 18 hours ago (8 children)

    On the plus side, from what I've read they're mostly old fashioned sane conservatives rather than Trumpian lunatics. Some of them are on the far right edge but hopefully the rest will keep them in check, the party's actual policies aren't too bad.

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  • [–] 1 point 1 day ago

    Ah, the code itself won't really help with that.

    My setup is: LM Studio running the local model Qwen3.8-27V, quantized down to Q4 with Q8 for the KV cache, on my system that gives me 128000 tokens context. The harness is VS Code with the Qwen Code Companion installed.

    I opened the folder that has all the music I wanted to organize as a workspace, adding a git repository with all the actual music folders gitignored. This was the first prompt I gave the agent once all that was in place:

    The folder you're in, and the subfolders inside it, are where I've been putting the music that I've generated using various AI music generation services (and my own local Ace-Step 1.5 model) over the past year or so. I've stored a lot of metadata (usually in a .json file) along with the music files themselves, along with lyrics in .srt and .lrc form, cover art, and so forth - different formats, different sources, not entirely consistent. I've decided that it's about time that I try to organize this all a bit better, and I'll be enlisting your aid. :)

    [ A few specific paragraphs about the details of the filesystem layout omitted]

    Before I explain the format the text files are in and how I'd like them to be converted, would you like to take a look around the folders to familiarize yourself with them and write whatever preliminary memories and notes you might want? And of course ask me questions about the stuff in here if anything isn't clear in its purpose or organization.

    Then after it had looked around and had read the various different metadata formats, it asked me some questions about what data I'd like to have in "unified" metadata files for each of the tracks, file naming conventions, and whether I wanted it to do anything with the cover art and subtitle files. I answered the various questions (telling it to leave the cover art and subtitles alone for the time being) and it wrote some python scripts that ran through all the existing metadata to tidy up the stuff that fit existing patterns and create a list of all the oddball exceptions it ran across for me to fix manually. It found stuff like situations where the punctuation was different between music file and metadata file, where there were cover images with no apparent music associated with them, and so forth.

    It became a back-and-forth exchange of me telling it what to fix and it finding new things that I didn't know needed fixing. Eventually I had enough random Python scripts to wrangle that I asked it to write a GUI, which made it much more convenient for me to edit the metadata by hand wherever needed as well.

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