• 6 Posts
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Joined 1 year ago
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Cake day: July 4th, 2023

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    1. First furious madman scribbling: I had a toy was a “quizz” machine with “A, B, C, D” buttons, that read colorful perforated cards and a speaker of a “ding-dong” sound for a correct answer, I worked out what set of holes corresponded to what answer (which to the toymaker’s credit, each card with the same answer did not have exactly the same holes) so I could always answer correctly. [The way I remember it I wanted to make custom cards, but maybe I was just a little cheater ^^]
    2. First program: One fond memory from middle-school, where our introduction to programming was writing GCM and LCM programs using TI-BASIC (or Casio, but the school really pushed the TI models forward). Also having access to a “worms” (somehow in basic and not assembly) clone copied from a friend’s calculator, I reverse engineered the more easy aspects of graphical display, and input handling make a tic-tac-toe program. Since I didn’t know about lists yet, inspired by the GCM and LCM bits, I used prime numbers to store the state of the board, and used divisibility tests to check it. (Some years later i would refactor it, to discover that lists are much much slower in non-assembly TI-BASIC, so it was accidental optimization) I also miscoded the bot, which was vulnerable to exactly one fork attack, but decided to leave it in because it was more fun that way.
    3. First hack: Discovering that the highschool’s poorly designed web portal, for sharing homework and assignments, allowed forced browsing, which the files uploaded by anyone was fun. [I reported it to the school’s sysadmin team, I swear]
    4. Cringe blog: Following in my geeky dad’s footsteps I had a very teenager cringe website, that I look fondly on, with garish colors, self-made HTML, css and animated gifs.







  • Also a subjectively bad one at that—given his america-brained position on wanting to maintain a single executive not that suprising but:

    • Why do you even need to default to winner-take-all?
    • Under winner-take-all dont you inherit most of the downside of FPTP? Sure there might be less wasted votes, but doesn’t actually make harder for 5% parties to get representation, since dominant parties have less of an incentive to negotiate and/or coallition build. (Though I guess subjective given Yud’s apparent dislike of many party working together in a coalition)
    • For a “runoff” system, the STAR system has the dubious distinction of allowing the condorcet loser—a candidate that would lose 1 vs 1 matchup against every other candidate in the field—to win, because a very enthiusastic minority can give a bunch of 5-star ratings.
    • At least FPTP has simplicity going for it, and not trying to arbitrarily compare not completely informed star ratings from voters.



  • Haven’t read the whole thing but I do chuckle at this part from the synopsis of the white paper:

    […] Our results suggest that AlphaProteo can generate binders “ready-to-use” for many research applications using only one round of medium-throughput screening and no further optimization.

    And a corresponding anti-sneer from Yud (xcancel.com):

    @ESYudkowsky: DeepMind just published AlphaProteo for de novo design of binding proteins. As a reminder, I called this in 2004. And fools said, and still said quite recently, that DM’s reported oneshot designs would be impossible even to a superintelligence without many testing iterations.

    Now medium-throughput is not a commonly defined term, but it’s what DeepMind seems to call 96-well testing, which wikipedia just calls the smallest size of high-throughput screening—but I guess that sounds less impressive in a synopsis.

    Which as I understand it basically boils down to “Hundreds of tests! But Once!”.
    Does 100 count as one or many iterations?
    Also was all of this not guided by the researchers and not from-first-principles-analyzing-only-3-frames-of-the-video-of-a-falling-apple-and-deducing-the-whole-of-physics path so espoused by Yud?
    Also does the paper not claim success for 7 proteins and failure for 1, making it maybe a tad early for claiming I-told-you-so?
    Also real-life-complexity-of-myriads-and-myriads-of-protein-and-unforeseen-interactions?


  • Another dumb take from Yud on twitter (xcancel.com):

    @ESYudkowsky: The worst common electoral system after First Past The Post - possibly even a worse one - is the parliamentary republic, with its absurd alliances and frequently falling governments.

    A possible amendment is to require 60% approval to replace a Chief Executive; who otherwise serves indefinitely, and appoints their own successor if no 60% majority can be scraped together. The parliament’s main job would be legislation, not seizing the spoils of the executive branch of government on a regular basis.

    Anything like this ever been tried historically? (ChatGPT was incapable of understanding the question.)

    1. Parliamentary Republic is a government system not a electoral system, many such republics do in fact use FPTP.
    2. Not highlighted in any of the replies in the thread, but “60% approval” is—I suspect deliberately—not “60% votes”, it’s way more nebulous and way more susceptible to Executive/Special-Interest-power influence, no Yud polls are not a substitute for actual voting, no Yud you can’t have a “Reputation” system where polling agencies are retro-actively punished when the predicted results don’t align with—what would be rare—voting.
    3. What you are describing is just a monarchy of not wanting to deal with pesky accountability beyond fuzzy exploitable popularity contest (I mean even kings were deposed when they pissed off enough of the population) you fascist little twat.
    4. Why are you asking ChatGPT then twitter instead of spending more than two minutes thinking about this, and doing any kind of real research whatsoever?

  • BasicSteps™ for making cake:

    1. Shape: You should chose one of the shapes that a cake can be, it may not always be the same shape, depending on future taste and ease of eating.
    2. Freshness: You should use fresh ingredients, bar that you should choose ingredients that can keep a long time. You should aim for a cake you can eat in 24h, or a cake that you can keep at least 10 years.
    3. Busyness: Don’t add 100 ingredients to your cake that’s too complicated, ideally you should have only 1 ingredient providing sweetness/saltyness/moisture.
    4. Mistakes: Don’t make mistakes that results in you cake tasting bad, that’s a bad idea, if you MUST make mistakes make sure it’s the kind where you cake still tastes good.
    5. Scales: Make sure to measure how much ingredients your add to your cake, too much is a waste!

    Any further details are self-evident really.



  • I realize it’s probably a toy example but specifically for “cats” you could achieve the similar results by running a thesaurus/synonym-set on your stem words. With the added benefit that a client could add custom synonyms, for more domain-specific stuff that the LLM would probably not know, and not reliably learn through in-prompt or with fine-tuning. (Although i’d argue that if i’m looking for cats, I don’t want to also see videos of tigers, or based on the “understanding” of the LLM of what a cat might be)

    For the labeling of videos itself, the most valuable labels would be added by humans, and/or full-text search on the transcript of the video if applicable, speech-to-text being more in the realm of traditional ML than in the realm of GenAI.

    As a minor quibble your use case of GenAI is not really “Generative” which is the main thing it’s being sold as.