[–] 3 points 1 month ago

Best native Linux DAWS if you want to try:

  • Bitwig - Like Ableton but better (paid, proprietary)
  • Renoise - Tracker focused (paid, proprietary)
  • Reaper - Clunky but very capable (cheap, proprietary)
  • LLMS - Very simple daw (free, libre)
  • Ardour - Full featured but rough around the edges (free, libre)
  • Bespoke - Modular workflow, supports VSTs (free, libre)
  • VCV Rack - Modular workflow, VCV modules only (free, libre)

All the paid daws have free demos.

FWIW I also release all my plugins with native Linux builds: https://replicataudio.com/

Got some cool new stuff coming out soon. HMU on discord and I will give you free copies (applies to anyone reading this comment).

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  • [–] 1 point 1 month ago

    I'll admit that I overlooked that but a single user is going to be weighted VERY low. Especially if their data looks like an outlier.

    Seems pretty unlikely to me that you could really influence the model in a meaningful way like that.

    Better off focusing on public/authoritative data that will get weighted a lot heavier.

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  • [–] 2 points 1 month ago (1 child)

    Yeah.. Normies for sure don't use the term "LLM". I don't think it would scare them though. They're used to being confused 💀

    When I see "AI" I think "tech bro hype" whereas "LLM" makes me think the developer is more likely to have a realistic view of the technology.

    I guess this depends a lot on your target demo. But but even just cutting down on usage of the exact term "AI" would help I think. Basically anything is better.

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  • [–] 1 point 1 month ago (3 children)

    I looked at your site. Realistically I think we're talking about two different things here. There are tools which were programmed with the assistance of AI and then there are AI powered tools. Your stuff is clearly the latter.

    I think ai powered tools are a lot harder to sell people on right now. The ai powered area is where I see by far the most shovelware/slop.

    To be blunt, when I see a new ai powered tool I assume several things:

    • This is low effort slop
    • A tech bro vibe coded this 100%
    • No one cares about this
    • It will either make a ton of money or be abandoned next week
    • If it's popular, anthropic will buy/clone it and everyone will use their version instead

    I know this isn't true of every ai powered app but it's true of 99% of them right now. I really have no idea how you could convince people yours isnt slop.

    One idea might be to stop using the term "AI". It's a buzzword with strong connotations. Some people hear it and think "gold rush", some people think "slop" or "data center".

    Personally I would be a lot more likely to take a project seriously if they used the term "LLM" or "machine learning" to describe what powers the product.

    Also, I don't see anything that looks like obvious AI art to me but DONT USE AI ART. AI art is already terrible on its own but when I see AI art mixed with AI text telling me about an AI powered app I'm 1000% done giving my attention.

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  • [–] 13 points 1 month ago* (last edited 1 month ago) (10 children)

    So they advised us to feed as much data as we can into these AIs, so that when policymakers ask AI about their options, they will not only get the lobbyist answer.

    That's not how AI works though. You can't feed data into an AI in a way that affects the answers other people get. It's not learning anything in real-time like that.

    If you want to "feed data" into an AI system all you can really do is publish that data publicly and wait for it to be scraped up into their training data.

    Edit: I'll admit that I overlooked the fact they do add conversations to training data but a single user is going to be weighted VERY low. Especially if their data looks like an outlier.

    Seems pretty unlikely to me that you could really influence the model in a meaningful way like that.

    Better off focusing on public/authoritative data that will get weighted a lot heavier.

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  • [–] 10 points 1 month ago (5 children)

    I think this is a major over generalisation that misses the main point of why people don't want AI projects. The real questions are:

    • Is this slop?
    • Does a human understand all of this code?
    • Did a human design this deliberately or is it completely derivative and uninspired?
    • Will a human take responsibility for bugs that come up?
    • Did a human write the docs?
    • Will this be maintained or just a weekend project with no substance?
    • Does this actually serve a purpose?

    Idk how to address these things really. I could see the AI tag going both ways, but I do think it's painting with too broad a brush.

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  • submitted 8 months ago* (last edited 8 months ago) by to c/programming@lemmy.ml
     

    I'm new to Fish and really liking it so far but the list type is really confusing me.

    Something that I find really non-intuitive about fish is the list data type.

    You can set a list like this

    set my_list a b c
    echo my_list[1] #a
    

    But if you try this it doesnt work:

    function mklist
      echo a b c
    end
    set lst (mklist)
    echo $lst[1] # a b c
    

    Putting the echo in quotes doesnt work either.

    You can do:

    function mklist
        echo a b c
    end
    set lst (string split " " -- (mklist))
    echo $lst[1] # a
    

    But needing to always split your return values is kinda terrible.

    So it seems like what fish expects you to do is echo multiple lines.

    function mklist
        echo a
        echo b 
        echo c
    end
    set lst (mklist)
    echo $lst[1] # a
    

    Its just very weird to me that it doesnt understand a comma delimited string to be a list.

    I feel like I must be missing something.


    Edit: FWIW I think I get why they designed it like this after thinking some more. It just feels weird.

    This requires you to be explicit about returning lists. Otherwise any echo with spaces would be treated as a list and not a single value

     

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