rguzman

i, like the author, tend to find the theories of how/why music works unsatisfactory. in a sense, it has to be some kind of side-effect of capabilities that evolved via natural selection, but i find explanations for visual art operating that way more satisfying than music operating that way. music seems to be better analogized to the written word. we can engage with the written word "visually" (eg graffiti) but most of the time we don't quite do that -- what we do (stare at pieces of paper with funny squiggles in them and hallucinate) is far more abstract. music seems to be like that, too.

i think the distinction is between ads that google sells vs software infrastructure for 3rd part ads (ad tech). ie the revenue's from google's ads on search, maps, youtube, etc are still huge and important -- that's google's advertising business, the eyeballs they sell, if you will. ad tech is google's business brokering ads on other sites, helping others sell their eyeballs.

at least this is how i understand it currently, but i don't know very much. happy to be corrected by someone who does.

> However, for some reason, both Gemini and ChatGPT tend to argue with me so heavily and inject their own weird stupid ideas on things

do you have examples of this?

asking because this is not what happens to me. one of the main things i worry about when interacting with the llm is that they agree with me too easily.

one issue that comes to mind is the nature of the determinant. when one considers the determinant defined by the recursive definition, it seems like a highly contrived object that is difficult to work with (as it is from that definition!). avoiding that confusion requires that a lot more scaffolding be built (ala Axler in the "Done Right" book). either way you have some work: either to untangle the meaning of the weird determinant or get to the place where you can understand the determinant as the product of the eigenvalues.

it really depends on what you mean by rich: the surest path to end up with $2-5M over ~10 years is job at ~FAANG, do it well to get promoted, and manage your savings/investments well. that path is very unlikely to get you to $10-100M in the same 10 years, and starting a startup seems to be one of the best ways to do that.

3:16 Bible Texts Illuminated by Donald Knuth

i was going to sit this one out, but i want to +1 the above with more than just an upvote. Austen seems to be arguing and explaining all the happenings in good faith with someone who appears to be hell-bent on "catching" him with something by misconstruing things.

i have never understood why Lambda/Bloomtech has so many haters but the other commenter here appears to me to be in that camp.

this is all accurate and i'd add that it is deceivingly hard to make something that sustains itself via advertising. when youtube was acquired google had a large part of that already figured out.

one of the things that helps generate new ideas that can be cultivated is the ability to be playful. once a given problem or subject is sufficiently loaded onto a brain, if that person can relax and have child-like naivete about poking and prodding, novel insight is usually not far.

cultivating this ability is fairly well understood in a lot of domains, i think. two examples that are top-of-mind are improv and jazz.

> The author of this article was paid $42 million last year. Uber's top 7 executives received: "$11.4 million in salary and cash bonus, plus $71 million worth of equity awards."

it's misleading to call equity compensation "getting paid". there's a strong argument that executives are being over-payed, but say the CEO receiving a salary of ~1.6M (11.4/7) is a lot less egregious than them being paid $42M. surely the equity conferred to the execs gets them some cash availability in various ways, but it isn't exactly the same as just giving them money (eg what would happen if the CEO uber sold off all of his stock?).

maybe the cash portion of exec salaries ought to be much lower or maybe their equity compensation ought to be much lower, but i don't think either of these things by itself or in combination is going to solve the structural problems of the american economy such as healthcare being tied to employment.

i agree wholeheartedly with the spirit of your comment, but saying "nutritional science is complex" or "the dosage alone makes it so that a thing is not a poison" does not help people figure out what foods to choose or how much to consume.

looking at the glycemic index is a useful heuristic and some of the research on canola oil makes me skeptical of it, and i think it is good for the author to point that out, as it suggests that oat milk might not be as safe as it is marketed to be.

another heuristic is biasing in favor of food that is processed less eg eating a bowl of oats is probably a better idea than drinking the analogous amount of oatly. similarly, it is a good idea to eat foods that people like you have been eating for long times, which in the oats vs oatly example favors the oats.

the precautionary principle suggests that the onus is to verify the safety of a given new food, not to prove that it is unsafe.

i was a physics PhD student once and i might have some thoughts on how to learn physics, but i think the parent commenter is spot on -- the only reliable way we have is to have an apprenticeship with someone who works well with you.

there are a tons of posts along the lines of this one, which are largely lists of books that people like to romanticize or as the parent comment says, lists of things that someone thinks you should know.

the Feynman lectures are a good example of that, actually. i've read them a couple of times and they are wonderful -- like most things Feynman. but very unhelpful. even Feynman was disappointed at how the students they were given to weren't quite learning the physics. Feynman is to explaining science as, eg Joshua Bell is to performing music for the violin. but in terms of actually trying to learn what a physical theory says, to what degree it holds, what are the current open problems with it, and what might be good approaches to solving them, Feynman explanations outside of highly technical works (like his papers or maybe his lecture notes on statistical mechanics) are not too useful. and the more technical works are very difficult to approach by yourself, you'll need a mentor.

it is pretty clear, but the conclusion of the parent is still pretty strong:

> Sounds like a logistical nightmare.