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Joined 2 years ago
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Cake day: July 1st, 2023

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  • If we had control over the weak force:

    • We can likely turn elements into other elements at will
    • We can manufacture safe decay sources for a new class of nuclear energy
    • We can probably create safe “decay batteries” tuned to their specific use cases. Batteries that last for tens of thousands the lifespan of current chemical ones.
    • Potentially engineer with neutrinos. Imagine communication via neutrinos, you could transmit straight through the earth.

    I mean, with control over matter like that, at the scale of electricity, Star Trek matter replicators would be a thing.


  • The sad part is is that you’re right.

    And the reason that it’s sad is that most of the individual veneers on proprietary projects deeply about a project itself and have the same goals as they do with open source software, which is just to make something that’s useful and do cool shit.

    Yep, the business itself can force them not take care of problems or force them to go in directions that are counter to their core motivations.



  • You make it sound as if they don’t already have a place in the world. Ml models have been employed to solve problems for the greater part of a decade or more now. Deeply integrated into damn near everything that you interact with.

    When you get an MRI or a CAT scan AI helps identify and call out peculiarities.

    The traffic lights and traffic management in your city is probably partially operated using “AI”.

    Wear and tear on parts of your car are predicted from data using ml models.

    Industry sensor data is interpreted and made actionable using ml models.

    Telecommunication Network fault prediction and detection.

    Energy load prediction.

    …etc

    But you’re probably talking about is recent hype around llms which are models that are fantastically good at understanding language. Which opens up a whole new field of possibilities when you can combine the ability to understand language with the predictability and reliability of “classic” ML models.