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Comment by mumboentourage | Hacker News Reader

isn't there so many things that the "consumer friendly" ai apps (e.g. muse, dots, duets, bots) offered by frontier ai labs cannot do, though?

for instance whenever i have them download a youtube video to transcribe subtitles from or fetch some text from a website verbatim, i get a "paraphrased" version citing copyright issues and they are pretty adamant / explicit about having me upload the materials (subtitles, archived website, etc.) myself to process, which defeats the purpose of using a consumer ai app. it seems like this cannot be avoided unless we use open source ai.

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If there is something that the AI can't do, I don't use it for that.

Why not just use a script with yt-dlp and whisper?

downloading the entire audio just to run it through whisper would be an inefficient (and token costly) workaround, i think.

there are other cases beyond when the models thought my requests violate their mandates (e.g. copyright concerns), e.g. the lack of root access to fix configuration / certificate issues (for instance, when a browser within the app's environment has certificate issues that require root user access, but the "consumer friendly" ai app doesn't have a dev mode).

How do tokens and copyright things play into this? I don't really understand. You can just pipe the audio straight from yt-dlp into whisper and it just transcribes it directly.

sorry i didn't understand your question either. i didn't say tokens and copyright things in the same context?

re: copyright mandates of consumer ai apps, i was saying that they refuse to work with things they got from third-party sites (say, .vtt from youtube) verbatim and relay the output without somehow paraphrasing it, unless you directly feed them .vtt or somehow trick them into believing that you're the copyright owner.

re: token usage, i was saying that your suggested approach (yt-dlp and whisper) is more token costly (or at least compute heavy). say for a 2-hour youtube video, i'd need to run whisper on the audio, plus speaker diarization to identify who's saying what, instead of simply downloading the .vtt file directly.

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