What if you are not a person, but a computer, converting a string into an integer? In that case, having a simpler and faster algorithm is important, having to start with only the beginning of a string (what the user has typed so far) is plausible, and knowing the number's approximate value is useless. So in this case the little-endian algorithm is much better than the big-endian one.

For the most part this is irrelevant. If you are a computer with only partial input, recieving the rest of the input is so much slower than parsing it that it literally does not matter which algorithm you use. If you have all the input, either is equally fast. Also, most of the complexity is going to be validating the input and handling edge cases (e.g commas Vs decimal points), not keeping track of the total.

There could be some weird edge cases, where you're reading a huge number, for some reason stored as a string, in a known format, don't require validation, from an extremely fast storage mechanism, e.g. RAM or an SSD. In that case you might care about performance of keeping track of the running total, but weird edge cases shouldn't decide which format to use (and in practice I guess they'd both be essentially identically fast here too).

Computers also need to decide whether to use big Indian or little Indian for their native representation of numbers. But either way they'll be using specialized hardware to operate on them, and both will be equally fast (and for the most part invisible to the user).

As Gregor Samsa awoke one morning from uneasy dreams he found his wife transformed in his bed into a gigantic insect...

...but he concluded that since ontologically this insect was not his wife, his marriage vows no longer applied. He squashed it under his boot as he walked out.

Might this be an issue even for people without this gene? What is the risk that constantly producing low levels of ethanol can cause oral cancer for ordinary people?

I think this is a really interesting question since it seems like it should neatly split the "LLMs are just next token predictors" crows from the "LLMs actually display understanding" crowd.

If in order to make statements about chairs and tables an LLM builds a model of what a chair and a table actually are, and to answer questions about fgeyjajic and chandybsnx it builds a model of what they are, it should be able to notice that these models correspond. At the very least it should be surprising if it can't do that.

If it can't generalize beyond stuff in the training set, and doesn't display any 'true' intelligence, then it would be surprising if it can translate between two languages where it's never seen any examples of translation before.

Taking a thirder position:

The reason you don't usually accept a bet which you can only accept at most once is that you have a 2/3s credence the coin is tails, but given that the coin is tails there's a 50% chance the bet is fake (since you've already accepted it the first time you woke up). This halves your expected earnings, so the bet is net negative.

But this gives you a way to break the symmetry. You only take the bet if the room is blue, which means your expected takings are now = 1/3  * -$200  + 2/3  * $100 = $0. So you still don't take the bet, but would if slightly better odds are available.


Taking a halfer position:

When you wake up and see the wall is blue, your credence that the coin was tails must remain %50 (by conservation of expected evidence - you knew the wall would be either red or blue before you opened your eyes). So why should you take the bet?

The correct answer is that there is a better strategy than always refusing the bet. Namely: choose either Red or Blue beforehand and bet Tails only when you see that the room is in this color. This way the Beauty bets 50% of time when the coin is Heads and every time when it's Tails, which allows her to systematically win money at 2:3 odds.

You place $200 down, and receive $300 if the coin was indeed tails.

If the coin toss ends up heads, you have a 50% chance of losing $200 - expected utility is $-100.

If the coin toss is tails, you have a %100 chance of gaining $100 - expected utility is $100.

So you end up with expected 0 utility.

The point stands, but the odds have to be better than 2:3.

I don't see why the colour makes a difference...

So I refuse the bet same as in regular sleeping beauty.

Could be, but South Korea and Taiwan are in similarly precarious situations and have abysmal fertility rates.

When you look at other countries which are constantly at, threatened by, or threatening war they also don't necessarily look great: Ukraine, Russia, Iran, China, North Korea, Finland, etc.

That's not to say this isn't a factor, but I think you'll need to add in enough extra details to differentiate from other countries that it will be very difficult to prove one way or another.

The way the auditing works in the UK is as follows:

Students will be given an assignment, with a strict grading rubric. This grading rubric is open, and students are allowed to read it. The rubric will detail exactly what needs to be done to gain each mark. Interestingly, even students who read the rubric often fail to get these marks.

Teachers then grade the coursework against the rubric. Usually two from each school are randomly selected for review. If the external grader finds the marks more than 2 points off, all of the coursework will be remarked externally.

The biggest problem with this system is that experienced teachers will carefully go over the grading rubric with their students, and explain precisely what needs to be done to gain each mark. They will then read through drafts of the coursework, and point out which marks the student is failing to get it. When they mark the final coursework they will add exactly one point to the total.

Meanwhile less experienced teachers don't actually understand what the marking rubric means. They will pattern match the students response to the examples in the rubric, and give their students a too high mark. It will then be regraded externally and the students will end up with a far lower grade than they had expected.

Thus much of the difference in grades between schools is explainable by the difference in teacher quality/experience. This is bad for courses which are mostly graded in coursework, but fortunately most academic subjects are 90% written exams.

I believe that the US is nearly unique in not having national assessments. Certainly in both the UK and Israel most exams with some impact on your future life are externally marked, and those few that are not are audited. From my perspective the US system seems batshit insane, I'd be interested in what a steelman of "have teachers arbitrarily grade the kids then use that to decide life outcomes" could be?

Another huge difference between the education system in the US and elsewhere is the undergraduate/postgraduate distinction. Pretty much everywhere else an undergraduate degree is focused in a specific field, and meant to teach you sufficiently well to immediately get a job in that field. When 3 years isn't enough for that the length of the degree is increased by a year or 2 and you come out with a masters or a doctorate at the end. For example my wife took a 4 year course and now has a master's in pharmacy, allowing her to work as a pharmacist. Friends took a 5 or 6 year course (depending on the university) and are not Doctors. Second degrees are pretty much only necessary if you want to go into academia or research.

Meanwhile in the US it seems that all an undergraduate degree means is you took enough courses in anything you want to get a certificate, and then have to go to a postgraduate course to actually learn stuff that's relevant to your particular career. 8 years total seems like standard to become a doctor in the US, yet graduate doctors actually have a year or 2 less medical training than doctors in the UK. This seems like a total dead weight loss.