That depends on whether you wish to see more April fool’s jokes, or fewer.
wnoise
http://groups.google.com/group/alt.language.artificial/msg/69250bac6c7cbaff?pli=1
The tailbit of Poul Anderson’s “Uncleftish Beholding”:
Some of the higher samesteads are splitly. That is, when a neitherbit strikes the kernel of one, as for a showdeal ymirstuff-235, it bursts into lesser kernels and free neitherbits; the latter can then split more ymirstuff-235. When this happens, weight shifts into work. It is not much of the whole, but nevertheless it is awesome.
With enough strength, lightweight unclefts can be made to togethermelt. In the sun, through a row of strikings and lightrottings, four unclefts of waterstuff in this wise become one of sunstuff. Again some weight is lost as work, and again this is greatly big when set beside the work gotten from a minglingish doing such as fire.
Today we wield both kind of uncleftish doings in weapons, and kernelish splitting gives us heat and bernstoneness. We hope to do likewise with togethermelting, which would yield an unhemmed wellspring of work for mankindish goodgain.
Soothly we live in mighty years!
Wait—Bayesians can assign probabilities to things that are deterministic? What does that mean?
Absolutely!
The Bayesian philosophy is that probabilities are about states of knowledge. Probability is reasoning with incomplete information, not about whether an event is “deterministic”, as probabilities do still make sense in a completely deterministic universe. In a poker game, there are almost surely no quantum events influencing how the deck is shuffled. Classical mechanics, which is deterministic, suffices to predict the ordering of cards. Even so, we have neither sufficient initial conditions (on all the particles in the dealer’s body and brain, and any incoming signals), nor computational power to calculate the ordering of the cards. In this case, we can still use probability theory to figure out probabilities of various hand combinations that we can use to guide our betting. Incorporating knowledge of what cards I’ve been dealt, and what (if any) are public is straightforward. Incorporating player’s actions and reactions is much harder, and not really well enough defined that there is a mathematically correct answer, but clearly we should use that knowledge in determining what types of hands we think it likely for our opponents to have. If we count as the dealer shuffles, and see he only shuffled three or four times, in principle we can (given a reasonable mathematical model of shuffling, such as the one Diaconis constructed to give the result that 7 shuffles are needed to randomize a deck) use the correlations left in there to give us even more clues about opponents’ likely hands.
What would a Bayesian do instead of a T-test?
In most cases we’d step back, and ask what you were trying to do, such that a T-test seemed like a good idea.
For those unaware, a t-test is a way of calculating the “likelihood” for the null hypothesis, which measures how likely the data are given that model. If the data is even moderately compatible, Frequentists say “we can’t reject it”. If it is terribly unlikely, the Frequentists say that it can be rejected—that it’s worth looking at another model.
From a Bayesian perspective, this is somewhat backwards—we don’t really care how likely the data is given this model P(D|M) -- after all, we actually got the data. We effectively want to know how useful the model is, now that we know this data. Some simple consistency requirements and scaling constraints means that this usefulness has to act just like a probability. So let’s just call it the probability of the model, given the data: P(M|D). A small bit of algebra gives us that P(M|D) = P(D|M) * P(M)/P(D), where P(D) is the sum over all models i of P(D|M_i) P(M_i), and P(M_i) is some “prior probability” of each model—how useful we think that model would be, even without any data collected (But, importantly, with some background knowledge).
In this framework, we don’t have absolute objective levels of confidence in our theories. All that is absolute and objective is how the data should change our confidence in various theories. We can’t just reject a theory if the data don’t match well, unless we have a better alternative theory to which we can switch. In many cases these models can be continuously indexed, such that the index corresponds to a parameter in a unified model, then this becomes parameter estimation—we get a range of theories with probability densities instead of probabilities, or equivalently, one theory with a probability density on a parameter, and getting new data mechanically turns a crank to give us a new probability density on this parameter.
There are a couple unsatisfying bits here:
First it really would be nice to say “this theory is ridiculous because it doesn’t explain the data” without any reference to any other theory. But if we know it’s the only theory in town, we don’t have a choice. If it’s not the only theory in town, then how useful it is can really only coherently be measured relative to how useful other theories are.
Second, we need to give “prior probabilities” to our various theories, and the math doesn’t give any direct justifications for what these should be. However, as long as these aren’t crazy, the incoming data will continuously update these so that the ones that seem more useful will get weighted as more useful, and the ones that aren’t will get weighted as less useful. This of course means we need reasonable spaces of theories to work over, and we’ll only pick a good model if we have a good model in this space of theories. If you eventually realize that “hey, all these models are crappy”, there is no good way of expanding the set of models you’re willing to consider, though a common way is to just “start over” with an expanded model space, and reallocated prior probabilities. You can’t just pretend that the first analysis was over some subset of this analysis, because the rescaling due to the P(D) term depends on the set of models you have. (Though you can handwave that you weren’t actually calculating P(M_i|D), but P(M_i|D, {M}), the probability of each model given the data, assuming that it was one of these models).A sometimes useful shortcut is rather than working directly with the probabilities, and hence needing the rescaling is to work with the likelihoods (or more tractably, the log of them). The difference of the log likelihoods of two different theories for some data is a reasonable measure of how much that data should effect their relative ranking. But any given likelihood by itself hasn’t much meaning—only in comparison to the rest in a set tells you anything useful.
Humans in general punish because we are built to enjoy properly punishing others, not just because we think it deters. Punishment is an adaptation we execute. When we execute this adaptation, it does indeed deter crime. And evolutionarily speaking (both genetically and culturally) that is its purpose.
That’s precisely why it is arbitrary—it’s a cultural artifact, not an inherently meaningful level.
European Philosophers Become Magical Anime Girls
Author Junji Hotta has blessed the world with “Tsundere, Heidegger, and Me”, a tour de force of European philosophy… in a world where all the philosophers are self-conscious anime girls. The books went on sale September 14.
http://aya.shii.org/2011/09/17/european-philosophers-become-magical-anime-girls/
- 29 Sep 2011 4:17 UTC; 2 points) 's comment on Rationality Quotes With Attributions Hidden: from Mein Kampf to Men****x by (
Just visualize n dimensions, and then set n = 4.
In an infinite universe, there are infinitely many copies of you (infinitely many of which are Boltzmann brains).
This is a meme I keep seeing, and it’s just not true. You need a lot more assumptions to justify that, such as “randomly generated”, or very very strong versions of the cosmological principle.
The real line is infinite, but there’s only one copy of the number 7.
The thermodynamic theory of metabolism is a fucking lie.
Not so much a lie as ‘inapplicable’. Energy balance and mass balance are still true. What happens so that that balance is maintained is highly variable.
Yes, and it’s widely regarded as a problem—for someone with rare skills or knowledge, it is usually far more valuable for them to donate money to buy time from others, rather than to donate their own time. A computer programmer really should not be making and serving soup at a homeless shelter. The same amount of time spent coding could pay for several people capable of doing the same thing.
Wikipedia can directly harness those with rare knowledge, and can do so piecemeal, in five-minute intervals, rather than by taking days at a time as even extremely short employment would require. For them it doesn’t make sense to pay someone to write an article on an obscure topic. It does seem to make sense for them to pay for servers and sysadmins.
(It’s true that their treatment of experts really could be better. They have managed to drive several experts away because dealing with some of the editors is just not worth the time.)
Are there other areas where it actually makes sense to have volunteered time rather than donating money?
Is that an emoticon of a partially unbent paperclip? How gruesome!
I have said before “I’m a moderate on abortion—I feel it should be okay up to the fifth trimester.” While this does shock people into adjusting what boundaries might be considered acceptable, I no longer think it is something useful to say in most fora. Too much chance of offending people and just causing their brains to shut off.
I prefer the teddy bear, because then you can refer to it as the “bug bear”.
anonymous internet posters
Pseudonymous. There are many similarities, but having a long-standing name does have significant differences, even if the name isn’t tied to one’s “real-life” name.
Excepting other humans.
Here the optimal strategy is to choose “yea” with a certain probability p, which I don’t have time to calculate right now
The expected value is $1000 (10 * p − 10 p^ 10). Maximums and minimums of functions may occur when the derivative is zero, or at boundaries.
The derivative is $1000(10 − 100 p^ 9). This is zero when p = 0.1^(1/9) ~= 0.774. The boundaries of 0 and 1 are minima, and this is a maximum.
EDIT: Huh. This simple calculation that mildly adds to the parent is worth more karma than the parent? I thought the parent really got to the heart of things with: “(because there’s no reliable way to account for the decisions of others if they depend on yours)” Of course, TDT and UDT are attempts to do just that in some circumstances.
Voting up specifically for:
If people are so keen to donate time rather than money to charities, this suggests the creation of charities specifically designed to harness that.
I think this works better as “lose an argument with a Bayesian”. Because then the Bayesian really does hand you your new belief.
You are thereby signalling that not only do YOU read Scots Gaelic (fluently, of course), but you expect everyone you come into contact with socially to ALSO be fluent in Scots Gaelic.
Scots Gaelic is not Scots (is not Scottish English, though modern speakers of Scots do generally code switch into it with ease, sometimes in a continuous way). Scots Gaelic is a Gaelic, Celtic language. Scots is Germanic. Burns wrote in Scots.
It can be hard to tell the difference, and it can be easy to mess up when trying to flirt back, but it takes rather more than than simply not telling the difference between flirtation and friendliness for imprisonment. There has to be actual unwelcome steps taken that cross significant lines.
The way the mating dance typically goes is as a series of small escalations. One of the purposes this serves is to let parties make advances without as much risk of everyone seeing them turned down, and lose face. It also lets people make stronger evaluations and back out in the middle gracefully.
Flirtatious talk is not an open invitation for a grabby hands. It is an invitation for further flirtatious talk. It may be an invitation for an invasion of personal space and increasing proximity. This in turn can be invitation for casual, brief, touches on non-sexual body areas. The point of no return, where it’s hard to gracefully back out and pretend nothing was happening, is usually the kiss. That’s usually done as a slow invasion of space, by the initiator, who must watch for the other to either lean in and take position, or lean and turn away. (or occasionally sit wide-eyed and frozen like a deer in the headlights).
Don’t take the example order above too seriously. It’s more complicated than a straight progression as laid out here. In addition to varying cultural attachments of these behaviors, all of them can vary continuously from completely innocent to drenched in erotic meaning, and escalation can happen in any of them at a given time. A clasp-and-release on the upper arm is an escalation from not touching, but far below resting a hand on the thigh.
And really, you can talk and ask for clarification from people you’re flirting with. Heck, asking “are you flirting with me” is itself a reasonable flirt-and-escalate move. Being explicit can kill the mood for some people, but if you’re not actually sure where in this dance you are or which direction it’s headed, it’s generally safer than risking unwanted boundary crossing.
I should also say that with strangers (in a bar say), this whole thing usually starts earlier with looks at someone punctuated with looks away when you see them looking back.