EHeller

It wouldn't have made a lot of sense to predict any doublings for transistors in an integrated circuit before 1960, because I think that is when they were invented.

This claim doesn't make much sense from the outset. Look at your specific example of transistors. In 1965, an electronics magazine wanted to figure out what would happen over time with electronics/transistors so they called up an expert, the director of research of Fairchild semiconductor. Gordon Moore (the director of research), proceeded to coin Moore's law and tell them the doubling would continue for at least a decade, probably more. Moore wasn't an outsider, he was an expert.

You then generalize from an incorrect anecdote.

I'm not sure the connotation of the term (i.e. a black person being successful at anything is so shocking it's entertainment value all on it's own) makes the statement any better. Especially when discussing, say, one of the most important American musicians of all time (among others).

I thought the heuristic was "if I think I passed the hotel, I was going too fast to notice. I better slow down so I see it when I come up on it, or so I might recognize a landmark/road that indicates I went too far." We slow down not because we are splitting the difference between turning around and continuing on. We slow down to make it easier to gather more information, a perfectly rational response.

Sure, not 100% unique to academia, there are also industrial research environments.

My phd was in physics, and there were lots of examples. Weird tricks for aligning optics benches, semi-classical models that gave good order of magnitude estimates despite a lack of rigour, which estimates from the literature were trust worthy (and which estimates were garbage). Biophysics labs and material science lab all sorts of rituals around sample and culture growth and preparation. Many were voodoo, but there were good reasons for a lot of them as well.

Even tr... (read more)

In STEM fields, there is a great deal of necessary knowledge that simply is not in journals or articles, and is carried forward as institutional knowledge passed around among grad students and professors.

Maybe someday someone clever will figure out how to disseminate that knowledge, but it simply isn't there yet.

No, the important older theories lead to better theories.

Newton's gravitational physics made correct predictions of limited precision, and Newton's laws lead to the development of Navier-Stokes, kinetic theories of gasses,etc. Even phlogiston lead to the discovery of oxygen and the modern understanding of oxidation. You don't have to be 100% right to make useful predictions.

Vitalism, on the other hand, like astrology, didn't lead anywhere useful.

But quantum theory also makes correct predictions, and mainstream physics does not en masse advocate quackery. Vitalism never worked, and it lead the entire medical community to advocate actively harmful quackery for much of the 19th century.

No, vitalism wasn't just a dead end, it was a wrong alley that too many people spent time wandering down. Vital theories were responsible for a lot of the quack ideas of medical history.

I don't think that is true? There is a huge contingent of evangelicals (last I checked, a bit under half of Americans believe in creationism), it only takes a few non-creationist but religious Christians to get to a majority.

There is a lot of statistical literature on optimal experimental design, and it's used all the time. Years ago at Intel, we spent a lot of time on optimal design of quality control measurements, and I have no doubt a lot of industrial scientists in other companies spend their time thinking about such things.

The problem is, information is a model dependent concept (derivatives of log-likelihood depend on the likelihood), so if your prior isn't fairly strong, there isn't a lot of improvement to be had. A lot of science is exploratory, trying to optimize ... (read more)

I don't understand the improvement you think is possible here. In a lot of cases, the math isn't the problem, the theory is known. The difficulty is usually finding a large enough sample size,etc.

You'd think so, but office hours and TA sections without attendance grades are very sparsely attended.

How hard your quals are depends on how well you know your field. I went to a top 5 physics program, and everyone passed their qualifying exams, roughly half of whom opted to take the qual their first year of grad school. Obviously, we weren't randomly selected though.

Fellowships are a crapshoot that depend on a lot of factors outside your control, but getting funding is generally pretty easy in the sciences. When you work as an "RA" you are basically just doing your thesis research. TAing can be time consuming, but literally no one cares if... (read more)

I don't think medicine is a junk investment when you consider the opportunity cost, at least in the US.

Consider my sister, a fairly median medical school graduate in the US. After 4 years of medical school (plus her undergrad) she graduated with 150k in debt (at 6% or so). She then did a residency for 3 years making 50k a year, give or take. After that she became an attending with a starting salary of $220k. At younger than 30, she was in the top 4% of salaries in the US.

The opportunity cost is maybe ~45k*4 years, 180k + direct cost of 150k or so.... (read more)

I don't see how Eliezer is correct here. Conservation of energy just isn't deeply related to the deeper structure of quantum mechanics in the way Harry suggests. It's not related to unitarity, so you can't do weird non-unitary things.

Hold on- aren't you saying the choice of experimental rule is VERY important (i.e. double blind vs. not double blind,etc)?

If so you are agreeing with VAuroch. You have to include the details of the experiment somewhere. The data does not speak for itself.

My point was only that nothing in the axioms prevents macroscopic superposition.

The part that is new compared to Cromwell's rule is that Yudkowsky doesn't want to give probability 1 to logical statements (53 is a prime number).

Because he doesn't want to treat 1 as a probability, you can't expect complete sets of events to have total probability 1, despite them being tautologies. Because he doesn't want probability 0, how do you handle the empty set? How do you assign probabilities to statements like "A and B" where A and B are logical exclusive? (the coin lands heads AND the coin lands tails).

Removing 0 and 1 from the math of probability breaks most of the standard manipulations. Again, it's best to just say "be careful with 0 and 1 when working with odds ratios."

I think the issue at hand is that 0 and 1 aren't special cases at all, but very important for the math of probability theory to work (try and construct a probability measure where some subset doesn't have probability 1 or 0).

This is incredibly necessary for the mathematical idea of probability ,and EY seems to be confusing "are 0 and 1 probabilities relevant to Bayesian agents?" with "are 0 and 1 probabilities?" (yes, they are, unavoidably, not as a special case!).