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

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.

Comments URL: https://news.ycombinator.com/item?id=43281423

Points: 6

# Comments: 1

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

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.

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.

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.

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.

> Sounds like a logistical nightmare.

[1]: https://www.worldometers.info/coronavirus/coronavirus-age-se...

this comment is right on the money on several fronts:

- the Feynman lectures are great after you already understand some of the mechanics of "doing" physics and have some other exposure to the topics, Halliday & Resnick is a better place to start on any one topic

- with infinite time, i'd always follow the approach of learning the math first and then the physics, the book by Boas is pretty good for self study of the minimum necessary math

- there's no real reason to follow a traditional grad school curriculum ala Fowler unless you need to pass quals in a traditional grad school setting

- simulating physical systems on computers is a pretty good exercise, but very time-consuming, avoid if you already spend a lot of time in front of computers

and some thoughts of my own:

- "get a strong foundation in Physics" is a bit too vague to be a useful goal, some examples of potentially better goals: "be able to pass a classical mechanics qual in the allotted time", "be able to write down the standard model and explain it", "be able to grok N papers from the X section of arxiv per week", "be able to write down toy classical field theories and calculate their predictions", ...

- if you are looking to avoid computers, try supplementing your reading with simple experiments either by buying educational kits or by hacking together things

- the books by David Griffiths (esp the E&M one) are awesome

- try to follow curiosity instead of a program: trying to answer "how do superconducting materials work?" for yourself is better than "follow the grad intro to condensed matter that's available online"

- use the physics stackexchange and other forums: asking and answering questions can be very helpful

everything below is me spitballing -- weakly held:

my thinking is that we should err on the side of caution, which means that if anything, in terms of flattening the curve, we haven't done enough, yet, but there is also that any it takes ~1-2 weeks to see the effects of any one action. once the curve is flattening, i think we ought to relax on this front as to minimize the economic damage.

in terms of structural changes to medical system (think FDA approvals), i think that we're also under-reacting, but i don't know enough to really say.

in terms of stimulating the economy, i think we've also under-reacted so far, though the latest bills look a bit promising on this front and i think if they pass they are of about the right magnitude.

this doesn't seem true to me. at least the brand loses value over the pandemic, and there's likely complications from cashflow that eat into other assets.