Open thread, Dec. 22 - Dec. 28, 2014

This article seems to mostly avoid the problems Yvain listed with AI reporting. It does talk about economic impacts, but it treats those as a short-term problem instead of the main problem.

Also, I still can't believe that a news anchor mentioned a paperclip maximizer on the air.

I suggest you make it happen. Start with a discussion level post suggesting habits, then a week later, make a discussion level post asking everyone to rank them.

I strongly suspect the real list of most important habits and skills fall within running, weight training, and cooking, but this is not the forum I'd typically go for advice on those topics.

This is a great book on habits and includes a list of habits to consider forming.

Are you looking for a list of habits or a list of skills?

What Nootropics do people take?

It might be useful to look at what happens in mathematics. What, for example, is a "number"? In antiquity, there were the whole numbers and fractions of everyday experience. You can count apples, and cut an apple in half. (BTW, I recently discovered that among the ancient Greeks, there was some dispute about whether 1 was a number. No, some said, 1 was the unit with which other things were measured. 2, 3, 4, and so on were numbers, but not 1.)

Then irrationals were discovered, and negative numbers, and the real line, and complex numbers, and octonions, and Cayley numbers, and p-adic numbers, and perhaps there are even more things that mathematicians call numbers. And there are other ways that the ways that "numbers" behave have been generalised to define such things as fields, vector spaces, rings, and many more, the elements of which are generally not called numbers. But unlike philosophers, mathematicians do not dispute which of these is the "right" concept of "number". All of the concepts have their uses, and many of them are called "numbers", but "number" has never been given a formal definition, and does not need one.

For another example, consider "integration". The idea of dividing an arbitrary shape into pieces of known area and summing their areas goes back at least to Archimedes' "method of exhaustion". When real numbers and functions became better understood it was formalised as Riemann integration. That was later generalised to Lebesgue integration, and then to Haar measure. Stochastic processes brought in Itô integration and several other forms.

Again, no-one as far as I know has ever troubled with the question, "but what is integration, really?" There is a general, intuitive idea of "measuring the size of things", which has been given various precise formulations in various contexts. In some of those contexts it may make sense to speak of the "right" concept of integration, when there is one that subsumes all of the others and appears to be the most general possible (e.g. Lebesgue integration on Euclidean spaces), but in other contexts there may be multiple incomparable concepts, each with its own uses (e.g. Itô and Stratonovich integration for stochastic processes).

But in philosophy, there are no theorems by which to judge the usefulness of a precisely defined concept.

Scott Aaronson has formulated it in a similar way (quoted from here):

whenever it’s been possible to make definite progress on ancient philosophical problems, such progress has almost always involved a [kind of] “bait-and-switch.” In other words: one replaces an unanswerable philosophical riddle Q by a “merely” scientific or mathematical question Q′, which captures part of what people have wanted to know when they’ve asked Q. Then, with luck, one solves Q′.

Of course, even if Q′ is solved, centuries later philosophers might still be debating the exact relation between Q and Q′! And further exploration might lead to other scientific or mathematical questions — Q′′, Q′′′, and so on — which capture aspects of Q that Q′ left untouched. But from my perspective, this process of “breaking off” answerable parts of unanswerable riddles, then trying to answer those parts, is the closest thing to philosophical progress that there is.

…A good replacement question Q′ should satisfy two properties: (a) Q′ should capture some aspect of the original question Q — so that an answer to Q′ would be hard to ignore in any subsequent discussion of Q, [and] (b) Q′ should be precise enough that one can see what it would mean to make progress on Q′: what experiments one would need to do, what theorems one would need to prove, etc.

It is almost completely uncontroversial that meaning is not determined by the conscious intentions of individual speakers (the "Humpty Dumpty" theory is false). More sophisticated theories of meaning note that people want their words to mean the same as what other people mean by them (as otherwise they are useless for communication). So, bare minimum, knowing what a word means requires looking at a community of language users, not just one speaker. But there are more complications; people want to use their words to mean the same as what experts intend more than they want to use their words to mean the same as what the ignorant intend. Partly that may be just to make coordination easier, but probably an even bigger motive is that people want their words to pick out useful and important categories, and of course experts are more likely to have latched on to those. A relatively uncontroversial extension of this is that meaning needn't precisely match the intentions of any current language speaker or group of language speakers; if the intentions of speakers would point to one category, but there's a very similar, mostly overlapping, but much more useful and important category, the correct account of the meaning is probably that it refers to the more useful and important category, even if none of the speakers know enough to pick out that category. That's why words for "fish" in languages whose origins predate any detailed biological knowledge of whales nonetheless probably shouldn't be thought to have ever included whales in their reference.

So, people can use words without anybody knowing exactly what they mean. And figuring out what they mean can be a useful exercise, as it requires learning more about what you're dealing with; it isn't just a matter of making an arbitrary decision. All that being said, I admit to having some skepticism about some of the words my fellow philosophers use; I suspect in a number of cases there are no ideal, unambiguous meanings to be uncovered (indeed, there are probably cases where they don't mean anything at all, as the Logical Positivists sometimes argued).

You think that words can be defined and then the definition if you look at a sentence and know the gramatical rules and the definition of those words you can find out what the sentence means. That belief is wrong. If reasoning would work that way, we would have smart AI by now. Meaning depends on context.

I like the concept of phenomelogical primitives. Getting people to integrate a new phenomelogical primitives into their thinking is really hard. I even read someone argue that it's impossible in physics education to teach new primitives.

Teaching physics students that a metal ball thrown on the floor bounces back because of springiness that lets the ball contract when it hits the floor and then expands again is hard. It takes a while till students don't reason anymore that the floor somehow pushes the ball back but that a steel ball contracts.

In biology there the concept of a pseudogene. It's basically a string of DNA that looks like a gene that codes for a gene but that's not expressed into a protein.

On the first instance that seems like a fine definition, on second investigation different biologists differ about what "looking like a gene" means. Different bioinformaticians each write their own algorithms to detect genes and there are cases where one algorithm A says that D is a pseudogene but algorithm B says that D isn't.

Of course changing the trainings data on which the algorithms runs also changes the classification. A really deep definition of a particular concept of a pseudogene would probably mention all the trainings data and the specific machine learnine algorithm used.

There are various arguments complicated arguments to prefer one algorithm over another because the resulting classification is better. You can say it's okay that the algorithm doesn't notice that some strings are genes because they don't look like genes are supposed to look or you can say that you really want that your algorithm detects all genes that exist as genes. As a result the amount of pseudogenes changes.

You could speak of pseudogene_A and pseudogene_B but in many cases, you don't need to think about those details. and abstract them away. It okay if a few people figure out a decent definition of pseudogene that behaves like it's supposed to and then others can use that notion.

In philosophy the literature and how the literature handles various concepts could be thought as training data for the general human mental classification algorithm. A full definition of a concept would have to conclude what the concept does in various edge cases.

On LW we have our jargon problem. We can use an existing word for a concept or we can invent a new term for what we speak about. We have to decide whether the existing term is good enough for our purposes or whether we mean something slightly different that warrants a new term. That's not always an easy decision.

To repeat a cliche: "There are only two hard things in Computer Science: cache invalidation and naming things" Naming is also hard outside of computer science.

I recently asked a question that I think is similar to what you're discussing. To recap, my question was on the philosophical debate about what "knowledge" really means. I asked why anyone cares - why not just define Knowledge Type A, Knowledge Type B, etc. and be done with it? If you would taboo the word knowledge would there be anything left to discuss?

Am I correct that that's basically what you're referring to? Do you have any thoughts specifically regarding my question?

I think the approach you describe is valid but dangerous.

It's valid because occasionally (and maybe even frequently) you want to think about something that you cannot properly express in words and so cannot define precisely and unambiguously. Some people (e.g. Heidegger) basically create a new language to deal with that problem, but more often you try to define that je ne sais quoi through, to use a geometric analogy, multiple projections. Imagine that you want to think about a 6-dimensional manifold. Human minds, alas, are not well suited to thinking in six dimensions, so you need to construct some projections of that manifold into a 3-dimensional space which humans can deal with. You, of course, can construct many different projections and you will feel that some of them are more useful for capturing the character of that 6-dimensional thing, and some not so much. But other people may and probably will disagree about which projections are useful and which are not.

It's also dangerous for obvious reasons, starting with the well-know tale of the blind men and the elephant...

There are lots of examples where this struggle with definitions has been fruitful. In the early 20th century in the boundary between philosophy and mathematics there were debates about the meanings of "proof" and "computation." It is true that the successful resolution of these debates has largely turned the subject from philosophy into math, although that has little do with the organization of academic departments.

Well, you could invest your own money. Most strategies benefit from using small amount of cash, since being able to take advantage of small volume opportunities often trumps higher relative execution costs. Register your track record and start recruiting investors.

You can also trade with your own strategies at companies that let you use a mis of your money and theirs, and provide some resources. Typically, traders at these companies aren't executing pure softwares strategies, so "stealing" their methods doesn't have much point.

You could also go to people with established reputations in academic or quantitative finance and show them enough of your method to convince them you're legit, but not so much they can copy it, then have them lend their reputation.

A superhuman AGI could accumulate tremendous financial resources; to do so most effectively it would need access to as many feeds and exchanges as possible, so some kind of shell company would buy those for it. I'm not sure to what extent a finance-specialist AI that achieves superhuman performance is really easier to make than a superhuman AGI; and bear in mind that it could lose its edge quickly.

even if you could, you would be better off working for a bank, rather than risking your own money.

That depends on the particulars. In any case, this is more the bailiwick of hedge funds rather than banks nowadays.

suppose I had discovered an entirely novel technique for predicting the market

You would have to demonstrate that it works and convince people with money to give some of that money to you to trade.

You can try to persuade people with just your technique (and backtesting results) under an NDA, but without a track record it will be hard -- or the deals offered to you won't be good. You also can trade your own money -- in whatever amounts you have -- for a while in a separate audited account. A good track record and a demonstrated willingness to risk your own money on your idea will help you persuade other people that the idea works.

Remember, you don't have to mathematically prove anything, all you have to do is convince people with money to give you some :-)

how easy it is for AI to acquire massive resources by dominating the world's financial markets.

For a fully developed AI it will be easy, but I am not sure why would it bother. And if you're thinking about trading "AIs" developed on Wall St. and such, these are very likely to be narrow tool-like AIs with very specific and limited goals.

I changed the link.

If this is possible, I think it would also be nice to have a link I can bookmark which takes me straight to the most recent open thread's comments.

When it comes to dumb animals it's because falling in love requires a courtship ritual with multiple steps. If any of the partners doesn't follow the steps of the ritual then the other animal doesn't feel the emotions to go to the next step of the ritual.

If a male pig emits enough androsterone, a female pig goes directly into mating position.

When it comes to humans on the other hand it's possible to do fall in love quite randomly without it being bidirectional. Humans also don't have an a mating season and do mating quite randomly.

At the same time it's not so random that old impulses that make it more likely that love is bidirectional don't exist. Rapport between humans get's facilitated through mimikry where people who like each other copy movement of the other person. Breath syncs.

There are also things that happen on a deeper level and that are more difficult to explain. Sunday at the end of the Leipzig Solstice I had a conversation that was on a very deep emotional level. It wasn't love but still deep emotions. The woman I was talked to left the room because by empathizing with me about an issue that's for me painful, because she felt very strong pain in her heart.

Given my current understanding of emotional mimikry and emotions I consider bidirectional love at first sight to be quite plausible even if it doesn't happen to most people.

It also happens that people have sex before they are fully in love. Feeling pleasure during sex then get's associated with the sex partner and increases the feelings towards that partner.

it seems implausible that romantic love is often (usually?) bidirectional

I think you are correct on this one.

why do people usually fall in love with someone who is likewise in love with them?

I have a two-way answer. First: they don't. Unreciprocated love is quite a theme in Western culture, and I suspect in other cultures too, because as a situation is both extremely common and much dramatic. Second: there's also an active selection effect, where we tend to like people that like us and that we are more familiar with. Regarding social circles and romantic interests, it's an exploration / exploitation tradeoff, but the important thing is that there's an exploitation choice in the first place.

"Falling in love" isn't this sudden thing that just happens, it's a process and it's a process that is assisted if the other person is encouraging and feels likewise. Put another way, when the object of your affection is uninterested, that's often a turnoff, and so one then looks elsewhere.

Ok. Reading the replies to this, I feel like my model of how dating works is fairly divergent from the norm.

Do people date (some people: I know that people date for all sorts of reasons) in the hopes of falling in love with each other? You pick someone who is reasonably attractive to you, then go through the motions of having a relationship (which may include eating together or having sex together, among other things) until you fall in love?

The behaviors precede the feelings?

That is not at all the model I am working from.

Unrequited love is a thing that exists, and breakups where only one side feels the relationship should end are common. In fact, one reason that people decide to stop dating is because the other person is falling / has fallen in love with them, and they don't feel that strongly towards that person (or see themselves likely to do so soon) and therefore call it off to let both people go on to find other partners (EDIT: polyamory mitigates this problem to a degree but you will still have a problem if there is severely unequal attachment between partners). I have no statistics for the number of people who end up with staying with the first person they said "I love you" too, or with the first person who said "I love you" to them, but I expect it (90%) to be under 50%, and wouldn't be surprised (50%) if it's 25% or lower, for either direction. People do not "usually fall in love with someone who is likewise in love with them".

You can quibble over definitions of what constitutes "love"; people, including those in relationships, do it constantly. If you simply take it as "capacity to be in a strong romantic relationship with a person for a period of years" then for most people there are a huge number of people they could fall in love with, and if they spend a lot of time with one of those people and mutually engage in displays of closeness, affection, desire, and pleasure in spending time together, many of those people will mutually fall in love.

Don't believe in the myth of "the one for me"; high standards are good, but if you spend a lot of time with somebody who you really like and who really likes you, you will probably find that the characteristics you're looking for in a love and the way you view the other person will become more aligned. That applies to both (or potentially "all", for cases of more than two people) parties. Definitely don't believe in "love at first sight"; you may well fall in love with somebody who you felt you loved from the moment you met them, but you're far more likely to fall in love with somebody who you got to know and discovered a mutual attraction and desire for each other's affection and presence in your/their life.

I was never a prominent poster, but I recently switched accounts for idiosyncratic reasons. I noticed only one other recent deletion (the first case that you mention).

Not sure there is a common pattern. The former case had to do with certain privacy realizations, I think, and the latter case was a lack of fit between the person and the local culture.

Self-driving cars offer a straightforward, practical way to talk about AI ethics with people who've never written a line of code.

For instance, folks will ask (and have asked) questions like, "If a self-driving car has to choose between saving its owner's life and saving the lives of five pedestrians, which should it choose?" With overtones of distrust (I don't want my car to betray me!), class anxiety (I don't want some rich fuck's car to choose to run my kids over to save him!), and anti-capitalism/anti-nerdism (No matter what those rich dorks at Google choose, it'll be wrong and they should be sued to death!).

And the answer that Google seems to have adopted is, "It should see, think, and drive well enough that it never gets into that situation."

Which is exactly the right answer!

Almost all of the benefit of programming machines to make moral decisions is going to amount to avoiding dilemmas — not deciding which horn to impale oneself on. Humans end up in dilemmas ("Do I hit the wall and kill myself, or hit the kids on the sidewalk and kill them?") when we don't see the dilemma coming and avoid it. Machines with better senses and more predictive capacity don't have to have that problem.

Not a book but: http://sqapo.com/

Try The Philosophy Book

I like this series; it's fun, well-designed pop-social science surveys. Of course, this type of survey has a big historical element; you may not like that but I think it's fun to read.

I haven't read this book myself, but I've read other books in this series and would recommend them:

http://www.amazon.com/Philosophy-Short-Introduction-Edward-Craig/dp/0192854216/

I like the idea of directing him to the Less Wrong sequences as he would probably benefit more from that. It's available in pdf and other print-suitable forms here so you could print it out and put it in a fancy binder or something:

http://lesswrong.com/lw/37v/sequences_in_alternative_formats/

The general Effective Altruism idea is that you shouldn't go for a very tiny chance of influencing a major cause. Instead on focusing on causes you should seek for opportunities that are effective at producing change.

Well, somewhat, but at least unlike a lottery it's not capped so that the house always wins.

Not a lottery, more like an insurance policy (which it usually is, literally) without a clear description of benefits. On a related note, I'd take a zombie who thinks it is me over no traces of me any day.

Instead of "unknown" pick a number. What the percentage that you believe it would work? Then go and calculate expected payoffs based on the price.

Stupid questions time:

NSI-189 has been shown to increase the hippocampal volume of adult mice by 20%

Given that there is only a certain amount of room inside the skull, how can this be true in adult mice? I can understand how it might increase density, or increase hippocampal volume when administered in adolescence and the skull has not finished growing, but unless there are holes in the brain I can't see how this could be true in adults.

I suppose maybe the amount of cerebospinal fluids could decrease, increasing intelligence at a cost of decreasing ability to withstand blows to the head.

I'd be more interested in behavioral changes in the mice. For some reason not all people with tiny hippocampuses or generally atrophied brains have problems with memory (or mood), and we still can't reliably diagnose progressive memory disorders, or many other neurological disorders for that matter, via brain scans alone.

I've noticed that watching Herman's Head (you can find most of the episodes on YouTube) helped me model my mind as a dialogue between competing agents.

There's a large range between excellent company and scam company. Many companies are earnestly but poorly run, or not-scams-per-se but concealing financial issues. Others seem too-good-to-be-true but really are that good.

As a rule, companies make offers that are just good enough to get a yes. My prior would be that too-good-to-be-true always deserves extra scrutiny, and is probably somehow deceptive or high-risk if the terms don't make a guarantee (for instance, equity and deferred compensation in a job offer could never materialize). The other possibility is that they believe you are more valuable to them than other companies do. The question is why? (A final possibility is that you have a poor understanding of the job market, and the other companies are lowballing you).

Tentatively, how much too good to be true is it? Does resemble past scams? Do the people making the offer get angry when they're asked about details?

What should my prior be for an offer that looks too good to be true to be actually true?

Recall the old poker wisdom: every game has a mark. If you are sitting in a poker game and you don't know who the mark is, chance are it's you.

Can you give some more background?

Stuff like: What occupation? Do you have a goal or application already in mind? Are there any programming-related things you can think of right now that seem fun, (writing a video game, a program to play chess, solving math puzzles, doing data analysis, etc)?

In addition to what is4junk suggested, you might want to check out Codecademy.

Learn Python the Hard Way is a pretty solid resource, though I used it before Codecademy came out. Both are excellent practice-based resources for starting programming.

After that, just get python books and work through them. Tools like Flask and Django if you want to do web development, other stuff if you want to do other stuff. If you don't know if you

Stackoverflow is usually where google will take you when you look for answers to your questions, so you might as well bookmark it.

And if you don't have something in mind you want to make, but you want to keep practising, try doing some ProjectEuler problems.

What is your occupation and what are you looking to program?

Coursera and edx have several free courses.
https://www.coursera.org/ https://www.edx.org/

Code Academy: http://www.codecademy.com/

Harvard's CS50 course: https://cs50.harvard.edu/

You can also take CS50 through edX, which grants certificates: https://www.edx.org/course/introduction-computer-science-harvardx-cs50x#.VJjeyf8AAA

If you're interested in learning web development, I've been going through a great resource called The Odin Project. It pulls together a bunch of different free resources to take you from knowing nothing to being hired.

It's just an example of lousy reporting. But first, some background. Whether a 'particle' or 'wave' approximation is more accurate depends on energy density. When the density of energy is relatively low compared to the energy of the photons (such as gamma rays coming off from a sample of radioactive material), the particle approximation is far more appropriate. When the energy density is high relative to the energy of the photons (like in a microwave oven), the wave approximation fits better. This is what was traditionally meant by 'wave-particle duality'.

This idea is indeed connected with the fact that the more localized a wavefunction is, the more spread is spectrum of momenta is (uncertainty principle). This is widely known and is nothing new. What they've done in this paper - which despite the lazy reporting of the paper is actually a thought-provoking bit of work - is consider 'wavefunction collapse', which is just the process of entanglement of the 'observer' wavefunction with the 'experiment' wavefunction. They've essentially shown that the amount of information that can flow from the 'experiment' to the 'observer' when the wavefunctions become entangled has an entropic bound. This idea has been thrown about for years; here they claim to have finally found a satisfying proof.

I'm not a physicist but I think it's been well-known for a while that wave-particle duality arises from the uncertainty principle.

Imagine you build a computer model, and it has an ontology. Ontolgy 1.

This computer model simulates the behavior or particles. These particles and their interactions form another computer. A computer inside a computer simulation. The internal computer has its own ontology. Ontology 2. The internal computer performs measurements of its world.

Basically, the idea is that Ontology 2 is what the computer model knows about itself. And that the uncertainty principle applies to our measurements, which in the model are represented by Onotology 2.

That means Ontology 1 literally does not have to follow the laws of physic that we observe, merely produce observations that are consistent with the laws of physics we observe.

Glancing at the comments, I see one of them addressed to "nyan", so I'm guessing it's Nyan Sandwich, who left when More Right was formed.

Yes, it was Nyan_Sandwich, before he turned to the Dark Side.

Rework a few lyrics on "I'm a Believer"?

As always, everything can be said with Alanis Morissette.

Same webcomic, on the same theme: Kant's Birthday

Interpretations of quantum mechanics are not really something that a lot of physicists worry about and, in my humble opinion, they aren't that interesting anyway. The idea of 'interpretations' is mostly a relic from the days of Bohr and Einstein. Their approach to physics was quite different from today. Virtually everyone agrees that the act of measurement is nothing more than the entanglement of the 'experiment' system with the 'observer' system, and that as far as physics is concerned, that's the only thing that matters. You can call it 'wavefunction collapse' or 'choosing a world' or whatever you want, you're talking about the same idea. In fact physicists often use these various metaphors interchangeably.

There are a few slightly more interesting concepts that are related to interpretations, such as if hidden variable theories are plausible (they'd have to be non-local and super-deterministic to be plausible) or if Bohmian pilot wave mechanics is an adequate mechanism for reality (it's not yet known whether it can incorporate special relativity, and that's really really important for modern physics since the standard model is intimately tied with special relativity).

I guess you could say that the many-worlds interpretation is the closest to a 'consistent' interpretation. But there's a danger here. Just because it's a consistent interpretation doesn't mean that there must actually be an infinite number of 'worlds'. At the end of the day, it could turn out that quantum mechanics is just the result of some unknown, deeper theory, and that there is just a single world.

You haven't seen that one big sequence that mostly argues for one of the QM interpretations, have you?

I know you retracted that comment, but if you're still looking for someone to talk to, you could make a post in the Discussion section. If that seems a bit too public or off-topic or whatever, Tumblr might be worth a shot; there are quite a few LWish people there too, and commiseration about personal crises isn't exactly rare on Tumblr.

I almost never have more important stuff to do but I can't guarantee useful advice.

You might check IRC - #lesswrong, maybe #slatestarcodex, someone is probably willing to help, and you might make a friend.

I suspect this describes the wife's cryopreservation:

I doubt it. The subject of that document was 46 when she died. Chay's wife was 52, according to news reports.

I suspect the O Administration won't make a big deal out of it because Chay's case involves a relatively small amount of money as financial malfeasance goes, and it lacks a racial angle to exploit.

I'm not as opposed to political discussion on this site as many are, but I do think the original point of EY's "Politics is the Mindkiller" post is worth keeping in mind. Inserting this kind of mind-killing aside in an otherwise non-political comment is needlessly inflammatory and distracting. I don't want to see this sort of thing on LW.