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Joined 1 year ago
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Cake day: July 28th, 2023

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  • From The One Sentence Persuasion Course by Blair Warren: “People will do anything for those who encourage their dreams, justify their failures, allay their fears, confirm their suspicions, and help them throw rocks at their enemies”

    I’ve found this helpful when trying to convince anyone of anything. The book breaks it down more, of course, but is probably not worth reading Vs the various summaries you can find online.

    My summary, at least what I took from it is that you must try to understand the person you are negotiating with/pursuading. Figure out what they want, or what they’re afraid of, and offer that.



  • Base 10 on your hands is really base 1. Every finger is either 0 or 1 and we just count them! Base 12 we do have 12 positions each representing a digit, and two potential digits from our hands.

    Binary is so much more efficient because you have 10 digits, just like in base 1, but you use them more efficiently.

    The next logical step is trinary, if we can incorporate enough fingers it would go higher than binary. Wikipedia suggests three positions of your fingers - up, down, and somewhere in between, or folded - but I’d be surprised if anyone can realistically do that with all their fingers. However, using four fingers on each hand and pointing them at different knuckles/the tip of your thumb gets you 8 digits of base 4 (including not pointing at the thumb at all as 0)… And actually doesn’t tangle your fingers up too bad.


  • If only we could combine the two and get to 2^12… Sadly, this would require 12 thumbs.

    Ooh, actually you can get to 2^8 without worrying about those pesky tendon issues by putting your fingertips against your thumb instead of trying to extend your fingers… Hmmm… Maybe we can even go to 2^10 this way by incorporating knuckles. Might lose some time today figuring out more hand counting systems. I wonder if anything higher than 2^10 is possible…









  • This kind of thing is where ML/AI can really shine. Data which is consistent, regular, where there are deep, hidden patterns that are not easy for humans to recognise. It’s very interesting that this came from an LLM, there are so many interesting and surprising applications of them that go beyond asking ChatGPT to write python for you.

    I saw a talk at a conference about a ML model designed to write chemical synthesis instructions. We have tons of systems able to predict synthetic pathways and the like, but not necessarily to predict the best solvents, extraction techniques, etc… and an LLM might provide a way to get there, which I think is amazing.


  • This falls into a common trap. Because we cannot succinctly define a salad in one sentence we decide that it cannot be defined at all. This argument effectively reducto ad absurdums itself by coming to the conclusion that all foods are salad.

    If we start from a position where we discount nothing from being a salad, and we have only salads (and soup, seemingly) to base our analysis on, how can we ever identify the boundaries of salad? The whole argument is based on the flawed premise that anything could be a salad.

    I realise that I am thinking too hard about this.




  • It’s an interesting idea. A simulated version of me dates simulated versions of everyone else, and then tells me which ones were any good… It would save the hassle, for sure. Could reintroduce some honesty into hookups, too, less dancing around trying to figure out if that’s what you’re both after.

    I’m not at all convinced that any company can convincingly simulate my personality though… and there are too many layers of abstraction here, do I really trust that the AI simulated opinions of the AI simulated version of the person thst only had a simulated conversation with simulated me is really going to reflect the real situation? I doubt it.