• 2 Posts
  • 20 Comments
Joined 1 year ago
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Cake day: June 19th, 2023

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  • Your question:

    what things did the LHC discover that have real practical applications right now other than validating some hypothesis

    Is really multiple questions:

    1. Is doing fundamental research with no application in mind useful?

    2. Has the LHC led to practical applications usable today

    The answer to question 1 is yes.

    There’s different types of research programs made to target different goals. Some aim for short or medium term applications, and others are just pure fundamental research.

    Just because pure research doesn’t have an application in mind, doesn’t mean it’s not useful. The application isn’t the goal, the expansion of our knowledge base is. Everyone who ever thought up of an application for something did so based on their own knowledge base. If the knowledge base never expands, then we run out of applications to think up. This is why pure research is useful.

    And all of history supports this:

    • The discovers of rays shooting off cathode-ray-tubes in the 1800s were just doing pure research and had no idea it would lead to TVs
    • particle accelerator research lead to invention of cat scans
    • chemists trying to research heavier elements leading to the discovery of nuclear fission, leading to nuclear power
    • electrolysis research lead to the invention of lead (and rechargeable) batteries
    • etc…

    The answer to question 2 is also yes:

    The obvious ones are:

    • improved manufacturing processes
    • improved supercooled superconductors
    • improved large scale vacuum chambers
    • Improved data processing
    • Trained a new cohort of experienced scientists/engineers/workers/etc (who can now work on new projects outside of the LHC)

  • I have yet to be given an example of something a “general” intelligence would be able to do that an LLM can’t do.

    Presenting…

    Something a general intelligence can do that an LLM can’t do:

    Play chess: https://www.youtube.com/watch?v=kvTs_nbc8Eg

    Why can’t it play it? Because LLM’s don’t have memory, so they can’t work with logic. They are the same as the little “next word predictor” in your phone’s keyboard. It just says what it thinks is the most probable next word based on previous words, it’s not actually thinking or understanding anything. So instead, we get moves that don’t make sense or are completely invalid.








  • Yeah, the obvious way would be to draw the text on a canvas, but you wouldn’t get sharp text then.

    I could nest a span with a negative translate or negative margin to overlap. It could be worth it to print each letter in a css grid (which would work since all the text is monospace) making it super easy to overlap text.

    There may be a more hacky/elegant solution which would be to use weird unicode to overlap characters, but I’m not sure how feasible it would be.