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Joined 1 year ago
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Cake day: June 11th, 2023

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  • Being close (and “sometimes” precise) to the intended meaning is an equally useless metric to measure performance.

    Depending on what you allow for “well close enough I think” asking ChatGPT to tell a story without any reading of fMRI would get you to these results. Especially if you know beforehand it’s gonna be a story told.


  • It’s the other way round. Code is being written to fit how a specific machine works. This is what makes Assembly so hard.

    Also there is by design no understanding required, a machine doesn’t “get” what you are trying to do it just does what is there.

    If you want a machine to understand what specific code does and modify that for another machine that is extremely hard because the machine would need to understand the semantics of the operation. It would need to “get” what you were doing which isn’t happening.




  • Sure but until I see such a thing I chose not to believe in fairy tales.

    Decompiling arbitrary architecture machine code is quite a few levels above everything I’ve seen so far which is generally pretty basic pattern recognition paired with statistics and training reinforcement.

    I’d argue decompiling arbitrary machine code into either another machine code or legible higher level code is in a whol other league than what AO has proven to be capable of.

    Especially because with this being 90% accurate is useless.


  • About half the time, the text closely – and sometimes precisely – matched the intended meanings of the original words.

    Don’t be surprised but about half of the time I can predict the result of a coin flip.

    I’m not saying it’s not interesting but needing custom training and an fMRI is not “an AI can read minds”

    It can see if patterns it saw previously reappear in a heavily time delayed fMRI. Looking for patterns you already know isn’t such an impressive feat Computers have done this for ages now.

    It litterally can’t read minds.