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Read: An Analysis of "Resistance Money, The Philosophical Case for Bitcoin" - Libereco's latest blogo
  • Even assuming an observer somehow knows the serial number of a spent bill, there is no central database tracking cash transactions. There is no history attached to cash, and no further trail for the observer to follow. While it is unlikely that an observer knows which specific bill you owned, it is downright impossible for the observer to know how you came into possession of said bill, or how it will be spent in the future.

    I'd push back on this. Many people get cash from a bank ATM. Businesses often deposit the cash they receive back into a bank. Truthfully I think there are very few hops between the cash withdrawal and deposit, and banks can easily check serial numbers and associate them with you. So an observer like the government/financial authority can probably piece together in most cases how you came into possession of a bill based on ATM withdrawal and where you spent it, based on deposit.

    I think this same method is why Bitcoin's privacy is lacking. Satoshi said in the Bitcoin paper that privacy can be maintained by ensuring our addresses remain pseudonymous. In reality, that's just too difficult to do and too much information is leaked because addresses can be tracked and traced and labelled especially when going to and from exchanges when people want to pay for things that do not accept cryptocurrency. So, although I don't think Bitcoin's privacy is better than cash, mostly to the point that serial numbers are not recorded on non-bank cash transfers, I think it's wrong to say cash is "downright impossible" to track.

  • Are there any good open source text-to-music models, preferably with lyrical abilities?
  • Interestingly, Jukebox from OpenAI was trained on what appears to be copyrighted music and involved styles and renditions that explicitly referenced specific artists. It's now four years old though. The demo songs don't seem to be available anymore on Soundcloud.

    There is MusicLM from Google (2023) - no lyrics. Also, AudioCraft from Meta (2023) - also no lyrics as far as I can tell.

  • Are there any good open source text-to-music models, preferably with lyrical abilities?

    Only recently did I discover the text-to-music AI companies (udio.com, suno.com) and I was surprised about how good the results are. Both are under lawsuit from RIAA.

    I am curious if there are any local ones I can experiment with or train myself. I know there is facebook/musicgen-large on HuggingFace. That model is over 1 year old and there might be others by now. Also, based on the card I get the feeling that model is not going to be good at doing specific song lyrics (maybe the lyrics just were absent from the training data?). I am most interested in trying my hand at writing songs and fine-tuning a model on specific types of music to get the sounds I am looking for.

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    InitialsDiceBearhttps://github.com/dicebear/dicebearhttps://creativecommons.org/publicdomain/zero/1.0/„Initials” (https://github.com/dicebear/dicebear) by „DiceBear”, licensed under „CC0 1.0” (https://creativecommons.org/publicdomain/zero/1.0/)FR
    fran @lemmy.dbzer0.com
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