kim0

Karma: −39

kim0 25 Dec 2013 20:54 UTC
−10 points
on: Critiquing Gary Taubes, Part 1: Mainstream Nutrition Science on Obesity
Taubes understand the value of falsification, such as mice starving to death while getting fat from little eating. This falsifies the “calories in, calories out” hypothesis, which was quite ambiguous anyway. His talks, and writings, have many falsifications like this. The main post here has none.

kim0 22 Jan 2012 17:00 UTC
0 points
in reply to: orthonormal’s comment on: The Savage theorem and the Ellsberg paradox
And yet again I am reminded why I do not frequent this supposedly rational forum more. Rationality swishes by over most peoples head here, except for a few really smart ones. You people make it too complicated. You write too much. Lots of these supposedly deep intellectual problems have quite simple answers, such as this Ellsberg paradox. You just have to look and think a little outside their boxes to solve them, or see that they are unsolvable, or that they are wrong questions.

I will yet again go away, to solve more useful and interesting problems on my own.

Oh, and Orthonormal, here is my correct final answer to you: You do not understand me, and this is your fault.

kim0 19 Jan 2012 7:55 UTC
−3 points
in reply to: orthonormal’s comment on: The Savage theorem and the Ellsberg paradox
Bayesian reasoning is for maximizing the probability of being right. Kelly´s criterion is for maximizing aggregated value.

And yet again, the distributions of the probabilities are different, because they have different variance, and difference in variance give different aggregated value, which is what people tend to try to optimize.

Aggregating value in this case is to get more pies, and fewer boots to the head. Pies are of no value to you when you are dead from boots to the head, and this is the root cause for preferring lower variance.

This isn´t much of a discussion when you just ignore and deny my argument instead of trying to understand it.

kim0 18 Jan 2012 13:55 UTC
2 points
in reply to: orthonormal’s comment on: The Savage theorem and the Ellsberg paradox
No, because expected value is not the same thing as variance.

Betting on red gives ¹⁄₃ winnings, exactly.

Betting on green gives ¹⁄₃ +/- x winnings, and this is a variance, which is bad.

kim0 17 Jan 2012 9:23 UTC
0 points
on: The Savage theorem and the Ellsberg paradox
Preferring red is rational, because it is a known amount of risk, while each of the other two colours have unknown risks.

This is according to Kellys criterion and Darwinian evolution. Negative outcomes outweigh positive ones because negative ones lead to sickness and death through starvation, poorness, and kicks in the head.

This is only valid in the beginning, because when the experiment is repeated, the probabilities of blue and green become clearer.
What links here?
- thomblake's comment on The Savage theorem and the Ellsberg paradox by fool (18 Jan 2012 15:26 UTC; 1 point)

kim0 8 Feb 2011 7:59 UTC
23 points
1
in reply to: Elizabeth’s comment on: Procedural Knowledge Gaps
There often is not any difference at all between flirting and friendliness. People vary very much in their ways. And yet we are supposed to easily tell the difference, with threat of imprisonment for failing.

The main effects I have seen and experienced, is that flirting typically involve more eye contact, and that a lot of people flirt while denying they do it, and refusing to to tell what they would do if they really flirted, and disparaging others for not knowing the difference.

My experience is also that ordinary people are much more direct and clear in the difference between flirting and friendship, while academic people muddle it.

kim0 3 Sep 2010 8:19 UTC
3 points
in reply to: Daniel_Burfoot’s comment on: Less Wrong: Open Thread, September 2010
Most places I have worked, the reputation of the job has been quite different from the actual job. I have compared my experiences with those of friends and colleagues, and they are relatively similar. Having a M.Sc. in physics and lots of programming experience made it possible for me to have more different kinds of engineering jobs, and thus more varied experience.

My conclusion is that the anthropic principle holds for me in the work place, so that each time I experience Dilbertesque situations, they are representative of typical work situations. So yes, I do think my work situation is typical.

My current job doing statistical analysis for stock analysts pay $ 73 000, while the average pay elsewhere is $ 120 000.

kim0 1 Sep 2010 9:08 UTC
4 points
in reply to: Daniel_Burfoot’s comment on: Less Wrong: Open Thread, September 2010
I am, and I am planning to leave it to get a higher more average pay. From my viewpoint, it is terribly overrated and undervalued.

kim0 22 Jun 2010 7:34 UTC
0 points
on: Applying Behavioral Psychology on Myself
That was a damn good article!

It was short, to the point, and based on real data, and useful as well. So unlike the polite verbiage of karma whores. Even William of Ockham would have been proud of you.

Kim0+

kim0 2 May 2010 12:52 UTC
3 points
in reply to: Jack’s comment on: Open Thread: May 2010
I wondered how humans are grouped, so I got some genes from the world, and did an eigenvalue analysis, and this is what i found:

http://kim.oyhus.no/EigenGenes.html

As you can see, humans are indeed clustered in subspecies.

kim0 2 Apr 2010 6:59 UTC
0 points
on: Open Thread: February 2010
Many-Worlds explained, with pretty pictures.

http://kim.oyhus.no/QM_explaining_many-worlds.html

The story about how I deduced the Many-Worlds interpretation, with pictures instead of formulas.

Enjoy!

kim0 30 Mar 2010 21:24 UTC
−5 points
in reply to: wedrifid’s comment on: Newcomb’s problem happened to me
You all are quite good at picking up the implications, which means my post worked.

kim0 30 Mar 2010 9:54 UTC
0 points
in reply to: Matt_Simpson’s comment on: Even if you have a nail, not all hammers are the same
Yes. Quadratic regression is better, often. The problem is that the number of coefficients to adjust in the model gets squared, which goes against Ockhams razor. This is precisely the problem I am working on these days, though in the context of the oil industry.

kim0 30 Mar 2010 9:33 UTC
2 points
on: Even if you have a nail, not all hammers are the same
Thank you for a very nice article.

kim0 30 Mar 2010 9:19 UTC
−12 points
on: Newcomb’s problem happened to me
More realistic:

Kate wants to increase her status by getting Joe to commit. She then becomes complacent, and then fat, lazy, and bitchy, and looses her respect for Joe since she was able to manipulate him. She never understands any of this, and accuse Joe of her shortcomings.

Joe never understands it either, and gets more remote, stressed, tired, workaholic, lonely, and subdued. They are both miserable.

And if anyone describes anything resembling this typical story to them, they immediately attack with accusations of political incorrectness, misogyny, discrimination, etc.

This bears on why I do not find Newcombs problem and similar of much interest:

Reality is so dominated by myriads of effects that models containing beeings like Omega or similar are far too unrealistic. Just collecting data and making simple models gets one much further.

kim0 19 Jan 2010 8:29 UTC
1 point
in reply to: kim0’s comment on: Advice for AI makers
I guess you down-voters of me felt quite rational when doing so.

And this is precisely the reason I seldom post here, and only read a few posters that I know are rational from their own work on the net, not from what they write here:

There are too many fake rationalists here. The absence of any real arguments either way to my article above, is evidence of this.

My Othello/Reversi example above was easy to understand, and a very central problem in AI systems, so it should be of interest to real rationalists interested in AI, but there is only negative reaction instead, from people I guess have not even made a decent game playing AI, but nevertheless have strong opinions on how they must be.

So, for getting intelligent rational arguments on AI, this community is useless, as opposed to Yudkowsky, Schmidhuber, Hansen, Tyler, etc. which has shown on their own sites that they have something to contribute.

To get real results in AI and rationality, I do my own math and science.

kim0 18 Jan 2010 23:39 UTC
−5 points
in reply to: orthonormal’s comment on: Advice for AI makers
The real dichotomy here is “maximising evaluation function” versus “maximising probability of positive evaluation function”

In paperclip making, or better, the game of Othello/Reversi, there are choices like this:

80% chance of winning 60-0, versus 90% chance of winning 33-31.

The first maximises the winning, and is similar to a paperclip maker consuming the entire universe. The second maximises the probability of succeeding, and is similar to a paperclip maker avoiding being annihilated by aliens or other unknown forces.

Mathematically, the first is similar to finding the shortest program in Kolmogorov Complexity, while the second is similar to integrating over programs.

So, friendly AI is surely of the second kind, while insane AI is of the first kind.

kim0 18 Jan 2010 20:39 UTC
−4 points
in reply to: wedrifid’s comment on: Advice for AI makers
You got voted down because you were rational. You went over some peoples heads.

These are popularity points, not rationality points.

kim0 18 Jan 2010 20:28 UTC
−10 points
in reply to: timtyler’s comment on: Advice for AI makers
Yes. To me it seems like all arguments for the importance of friendly AI are based on the assumption that its moral evaluation function must be correct, or it will necessarily become evil or insane, due over optimization of some weird aspect.

However, with uncertainty in the system, as limited knowledge of the past, or as uncertainty in what the evaluation function is, optimization should take this into account, and make strategies to keep its options open. In the paperclip example, this would be avoiding making people into paperclips because it suspects that the paperclips might be for people.

Mathematically, an AI going evil insane corresponds to it seeking the most probable optimization, while doing multiple strategies corresponds to it integrating the probabilities over different outcomes.

kim0 28 Sep 2009 7:04 UTC
−1 points
on: The Anthropic Trilemma
I have an Othello/Reversi playing program.

I tried making it better by applying probabilistic statistics to the game tree, quite like antropic reasoning. It then became quite bad at playing.

Ordinary minimax with A-B did very well.

Game algorithms that ignore density of states in the game tree, and only focus on minimaxing, do much better. This is a close analogy to the experience trees of Eliezer, and therefore a hint that antropic reasoning here has some kind of error.

Kim0