EHeller

Karma: 1,282

EHeller 1 Feb 2016 3:11 UTC
0 points
in reply to: V_V’s comment on: [Link] AlphaGo: Mastering the ancient game of Go with Machine Learning
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.

EHeller 30 Jan 2016 0:04 UTC
0 points
in reply to: Houshalter’s comment on: [Link] AlphaGo: Mastering the ancient game of Go with Machine Learning
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.

EHeller 25 Jan 2016 4:21 UTC
12 points
in reply to: Jiro’s comment on: Rationality Quotes Thread January 2016
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).

EHeller 16 Jan 2016 6:12 UTC
9 points
on: The correct response to uncertainty is *not* half-speed
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.

EHeller 10 Jan 2016 6:49 UTC
3 points
in reply to: btrettel’s comment on: LessWrong 2.0
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 tricks for using equipment- such and such piece of equipment might need really good impedance matching at one connection, but you could get by being sloppy on other connections because of reasons A, B and C,etc.

A friend of mine in math was stuck trying to prove a lemma for several months when famous professor Y suggested to him that famous professor Z had probably proven it but never bothered to publish.

EHeller 9 Jan 2016 20:51 UTC
4 points
in reply to: Risto_Saarelma’s comment on: LessWrong 2.0
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.

EHeller 27 Nov 2015 22:54 UTC
3 points
in reply to: Gunnar_Zarncke’s comment on: Rationality Quotes Thread November 2015
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.

EHeller 27 Nov 2015 1:01 UTC
5 points
in reply to: Gunnar_Zarncke’s comment on: Rationality Quotes Thread November 2015
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.

EHeller 26 Nov 2015 2:36 UTC
0 points
in reply to: ChristianKl’s comment on: Rationality Quotes Thread November 2015
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.

EHeller 22 Nov 2015 4:26 UTC
1 point
in reply to: Jiro’s comment on: Rationality Quotes Thread October 2015
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.

EHeller 14 Nov 2015 7:07 UTC
0 points
in reply to: PhilGoetz’s comment on: The Power of Noise
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 the experimental design is premature.

Either way, this isn’t stuff you need an AI for at all, it’s stuff people talk about and think about now, today, using computer assisted human intellect.

EHeller 14 Nov 2015 6:57 UTC
0 points
in reply to: johnswentworth’s comment on: The Power of Noise
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.

EHeller 12 Oct 2015 19:04 UTC
4 points
in reply to: gjm’s comment on: Deliberate Grad School
You’d think so, but office hours and TA sections without attendance grades are very sparsely attended.

EHeller 8 Oct 2015 3:48 UTC
6 points
in reply to: Curiouskid’s comment on: Deliberate Grad School
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 you do it poorly, so it’s not high pressure.

But this is a red flag:

Let’s assume you have the financial aspect of your PhD taken care of (e.g. You have an easy/enjoyable TA job). What other requirements are there other than passing Quals? Could I read interesting books indefinitely until I find something interesting to publish?

That isn’t how research works, at least in the sciences. Research is generally 1% “big idea” and 99% slowly grinding it out to see if it works. Your adviser, if he/she is any good, will help you find a big idea that you can make some progress on and you’ll be grinding it out every week and meeting with your adviser or other collaborators if you’ve gotten stuck.

That said, a bad adviser probably won’t pay any attention to you. So you can do whatever you want for about 7 years until people realize you’ve made no progress and the wheels come off the bus (at which point they’ll probably hand you a masters degree and send you on your way).

EHeller 14 Sep 2015 5:43 UTC
7 points
in reply to: Anders_H’s comment on: Welcome to Less Wrong! (8th thread, July 2015)
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.. So $330k “lost to training,” however 35+ years of making 100k a year more than some alternative version that didn’t do medical school. Depending on investment and loan decisions by 5 years out you’ve recouped your investment.

Now, if you don’t like medicine and hate the work, you’ve probably damned yourself to doing it anyway. Paying back that much loan is going to be tough working in any other job. But that is a different story than opportunity cost.

EHeller 4 Sep 2015 0:42 UTC
1 point
in reply to: Douglas_Knight’s comment on: Typical Sneer Fallacy
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.

EHeller 31 Aug 2015 5:41 UTC
5 points
in reply to: Cyan’s comment on: Beautiful Probability
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.

EHeller 29 Aug 2015 22:21 UTC
1 point
in reply to: TheAncientGeek’s comment on: If Many-Worlds Had Come First
My point was only that nothing in the axioms prevents macroscopic superposition.

EHeller 20 Aug 2015 17:44 UTC
3 points
in reply to: Wes_W’s comment on: 0 And 1 Are Not Probabilities
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.”

EHeller 20 Aug 2015 17:14 UTC
4 points
in reply to: Wes_W’s comment on: 0 And 1 Are Not Probabilities
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!).