dvasya

Karma: 445

dvasya Mar 27, 2012, 7:58 PM
2 points
on: Memory in the microtubules
This paper is pure speculation aimed at supporting a conclusion that was made long ago based on less than trustworthy reasoning. Also, it is in a pay-to-publish journal with very weak peer-review standards, which does not add much to its perceived importance...

dvasya Mar 16, 2012, 10:05 PM
4 points
on: The Futility of Intelligence

Before: The AI is going to take over the world by using its superhuman intelligence to invent nanotechnology. After: The AI is going to take over the world by inventing nanotechnology.

This trick works only because you already know how exactly the AI going to take over the world, so it doesn’t even need to switch its intelligence on. If, however, you change this for

Before: The AI is going to take over the world by using its superhuman intelligence to do something totally unforeseeable by us meatbags.

After: The AI is going to take over the world by doing something totally unforeseeable by us meatbags.

then there seems to be important distinction. There are lots of things that we can’t foresee, but only some of those would lead the AI to take over the world, and finding this subset would require something of the AI, and we need a name for that something.

Back to the original point, I am quite fond of a metaphor by Marvin Minsky, where he compares intelligence to the concept of “the unexplored regions of Africa,” which makes perfect sense, even though they disappear as soon as we discover them.

dvasya Mar 7, 2012, 10:33 PM
−1 points
in reply to: Morendil’s comment on: Causal diagrams and software engineering
Okay, how about this then? :)

Always make sure to write down your predictions in advance.

dvasya Mar 7, 2012, 8:32 PM
1 point
on: Causal diagrams and software engineering
Would this be an appropriate tl/dr summary?

To avoid hindsight bias, always make sure to write down your predictions in advance.

dvasya Feb 24, 2012, 3:08 PM
2 points
in reply to: Eugine_Nier’s comment on: [link] Faster than light neutrinos due to loose fiber optic cable.
Technically, when viewed on the log-odds scale, it is exactly the same amount of evidence for either hypothesis.

On the (0;1) scale of probabilities it is, however, stronger evidence for flawed experiment. E.g. if we had a null hypothesis H0 at a prior P of 0.25 and two hypotheses H1 and H2 at 0.25 and 0.5, respectively, and we see evidence that has a likelihood of 5:1 for each of these hypotheses over H0. Then we have posterior P(H0|D)/P(H1|D)=1/5 and P(H0|D)/P(H2|D)=1/10, and after normalization, P(H0)=1/16, P(H1)=5/16, P(H2)=10/16. So, in this situation, P(H2) has increased by ²⁄₁₆ and P(H1) only by ¹⁄₁₆. Which is what I meant in my comment: the probability of the more likely hypothesis increases faster, so H2 becomes more more probable than H1 :) Although on the log-odds scale, of course, both H1 and H2 received the same amount of evidence.

dvasya Feb 24, 2012, 1:21 AM
5 points
on: [link] Faster than light neutrinos due to loose fiber optic cable.
One more example of misapplied statistics. You see a 5-standard-deviation signal for faster-than-light neutrinos and reason like this:

“Well, prior to seeing these data I would rate the odds of neutrinos traveling FTL as, say, 1:1000, but this is full 5 standard deviations so the likelihood ratio is about 3.5 million for them going FTL after all, so I must revise my belief and now accept that those neutrinos travel FTL with ~3500:1 odds.”

...which, of course, only happens because you have oversimplified by only considering two hypotheses. Whereas in reality you should also have thrown in some other possibilities, like e.g. some undiscovered flaw in the measurements. Which I would, prior to seeing the data, assign a higher probability, say, odds of 1:100 (a mere 1% probability of faulty experiment, just to be generous to the experimenters). Now after seeing the data we also have to revise this probability, and it comes out as ~35000:1 odds for faulty experimental design.

In other words, the more “statistically significant” is the result in such an experiment, the more it is evidence for faulty measurement and against the experimenters’ claim (here, FTL neutrinos).

dvasya Feb 24, 2012, 12:56 AM
−2 points
on: Superintelligent AGI in a box—a question.
Heh heh, this reminds me of Charles Stross’s Accelerando character, Aineko.

dvasya Feb 22, 2012, 3:05 AM
2 points
in reply to: asr’s comment on: Feed the spinoff heuristic!
That’s the point: what people use is normal equilibrium or close-to-equilibrium thermodynamics. Even in situations that seem far out of the scope of equilibrium thermodynamics and where one would normally expect Prigogine physics to be the perfect candidate—one example being CVD or VLS growth of various nanotubes/nanowires/etc. - I have never seen the latter applied. Everybody just goes with good old (near-)equilibrium chemical thermodynamics. Now this might be just a manifestation of Maslow’s hammer, and Prigogine physics is hard, but for what it’s worth, here’s one example of a big hole that should be covered by the theory but is, in fact, not.

dvasya Feb 21, 2012, 4:39 AM
0 points
in reply to: [deleted]’s comment on: SI wants to hire a remote LaTeX guru
LyX a great tool, I can testify to that.

dvasya Feb 21, 2012, 4:08 AM
0 points
on: Longevity Insurance
And then if you die, the insurance company could have you frozen to avoid paying out however much is left in your coverage. Of course, they would first have to lobby for cryopatients to be legally recognized as non-dead.

But then again they would have little incentive to reanimate you later.

dvasya Feb 14, 2012, 11:42 PM
1 point
on: Meetup : Moscow 11 February meetup
So, did it go well? Who was attending?

dvasya Feb 9, 2012, 6:50 PM
4 points
on: Feed the spinoff heuristic!
Physicist Ilya Prigogine developed his famous theory of dissipative systems which was expected to explain a lot of things from thermodynamics of living systems to the nature of the arrow of time. It is a very well-developed and deep theory. Yet, in my scientific life, I have never seen an actual numerical calculation of a measurable quantity utilizing any of Prigogine’s concepts such as “rate of entropy production”. Looks definitely like a missing spinoff!

dvasya Feb 9, 2012, 3:21 AM
0 points
in reply to: Matvey_Ezhov’s comment on: lesswrong.ru domain for translation project?
I like this, too. Why not both have lesswrong.ru and ru.lesswrong.com pointing to the same site?

dvasya Feb 1, 2012, 12:12 AM
0 points
in reply to: Vaniver’s comment on: Terminal Bias
First, concave utility function is just a model for risk aversion which is “the reluctance of a person to accept a bargain with an uncertain payoff rather than another bargain with a more certain, but possibly lower, expected payoff.” (wiki)

Second, the certainty effect is indeed one of the effects that is captured by my preferred model, but of course it’s not limited to it, because it’s possible to behave in a risk-averse manner even if none of the offered bets are certain.

dvasya Jan 31, 2012, 5:15 PM
0 points
in reply to: bryjnar’s comment on: Terminal Bias
Unfortunately, under your new “fixed” utility function there will again be a point of indifference at some slightly different probability/payoff combination, where you, being risk-averse, have to go for the sure deal, so you will end up stuck in an infinite recursion trying to adjust your utility function further and further. I tried to explain this more clearly here.

Risk aversion vs. concave utility function

dvasyaJan 31, 2012, 6:25 AM

3 points

35 comments3 min readLW link

dvasya Jan 31, 2012, 4:54 AM
0 points
in reply to: thelittledoctor’s comment on: Terminal Bias
Sorry, I made a mistake in the example, it’s of course 16 not 15. Edited to correct.

dvasya Jan 31, 2012, 4:40 AM
0 points
in reply to: Vaniver’s comment on: Terminal Bias
Rational agents should be. Irrational agents—in this case, prone to risk aversion—would instead be willing to pay a finite cost for the bet to be replaced with the sure deal, thus losing utility. You can fix this by explicitly incorporating risk in the utility function, making the agent rational and not risk-averse any more.

dvasya Jan 31, 2012, 4:37 AM
0 points
in reply to: thelittledoctor’s comment on: Terminal Bias
Yes, the agent should—given the defined utility function and that the agent is rational. If, however, the agent is irrational and prone to risk aversion, it will consistently prefer the sure deal to the bet, and therefore be willing to pay a finite cost for replacing the bet with the sure deal, hence losing utility.

dvasya Jan 31, 2012, 4:23 AM
0 points
in reply to: Vaniver’s comment on: Terminal Bias

“Risk Aversion,” as a technical term, means that the utility function is concave with respect to its input

Risk aversion is separate from the properties of utility function. Being risk-averse rather means preferring a guaranteed payoff to a bet with the same expected utility. See here for a numerical example. It is possible to be risk averse even with a convex utility function.

dvasya

Risk aver­sion vs. con­cave util­ity function

Risk aversion vs. concave utility function