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Amusingly enough, I got into the conference this year early. This seems to be a small piece of evidence for my hypothesis that these sorts of applications often work as lotteries.
I was able to get a copy of this via interlibrary loan some time ago, after finding much better citations.
Got this from a website that sells copies of Russian dissertations.
I definitely pulled out all the stops on this dissertation, and learned a fair amount in the process. If you're not living in Russia, and looking for a Russian dissertation, I would be a good person to contact. I can't get you the dissertation but I can put you in contact with people who can.
I don't see how that would be a problem. Perhaps I'm missing something, so if you could explain I'd be appreciative.
Usually the problem is that wavelengths smaller than the grid size obviously can't be resolved. A class of turbulence modeling approaches can help with that to a certain extent. This class of methods is called "large eddy simulation", or LES for short. You apply a low pass filter to the governing equations and then develop models for "unclosed" terms. In practice this is typically done less rigorously than I'd like, but it's a valid modeling approach in general that should see more use in other fields. (Turbulence modeling is an interesting field in itself that a rational person might be interested in studying simply for the intellectual challenge.)
You'd be more likely to get some kind of waves that propagate at fixed speed along the grid, giving you a privileged rest frame, like in the old discredited theories of aether.
I'll try to steelman Florian_Dietz.
I don't know much anything about relativity, but waves on a grid in computational fluid dynamics (CFD for short) typically don't have the problem you describe. I do vaguely recall some strange methods that do in a Lagrangian CFD class I took, but they are definitely non-standard and I think were used merely as simple illustrations of a class of methods.
Plus, some CFD methods like the numerical method of characteristics discretize in different coordinates that follow the waves. This can resolve waves really well, but it's confusing to set up in higher dimensions.
CFD methods are just particularly well developed numerical methods for physics. From what I understand analogous methods are used for computational physics in other domains (even relativity).
I only skimmed this post, but I want to point out that most computational physics (and engineering) uses discretized space and time much as you've described. This is not new, just how things are often computed in practice.
Whether or not reality is discrete in this sense is beyond my knowledge as an engineer, but I have had conversations with physicists about this. (As I recall, it's possible, but the spatial and temporal resolution would be very small.)
Also, there are some exact solutions for discretized physics like this, but in general it's harder to do. Plus, because physical laws tend to be written in continuous form, very few people look for exact solutions like this.
makes all the contradictions go away
Not really. In computational fluid dynamics, converting to discrete equations can introduce major problems. One important problem is conservation. Depending on how you formulate your discrete equations, mass, energy, etc., may be no longer conserved and might not even be approximately conserved. "Equivalent" continuous equations would not have the same problem. And I would not say solving this problem is trivial by any means, though I know at least one way to do it.
I can see that I misremembered the lecture. Seems to be an application of Bayes as Lumifer suggested for the basic approach. Other more complex approaches were also discussed.
While I don't have my notes in front of me, I do recall from the decision analysis class I recently took that log score is related to the weight one would give to one forecaster among several when combining forecasts. Unfortunately it does not appear that the professor uploaded the slides on ensemble forecasting, so I can't provide any more right now. I am emailing the professor. Thought this would help in the meantime.
Thanks for pointing out that post by nostalgebraist. I had not seen it before and it definitely is of interest to me. I'm interested in hearing anything else along these lines, particularly information about solving this problem.
Citation: Богданович И. И. Влияние подготовки топлива в форсунке на тонкость распыла. Дисс. канд. техн.наук. М., 1948, 136 с. (Bogdanovich I. I. Influence of fuel preparation in the nozzle on the spray fineness. Diss. cand. Technical Sciences. Moscow, 1948, 136 pp.)
library URL: http://search.rsl.ru/en/record/01000176055
Old Russian dissertation. As far as I can tell, this is only available at the Russian State Library. If anyone could visit that library and scan the dissertation, I'd be appreciative.
I'd be more than willing to fulfill a similar request of anyone who could visit this library and get a good quality scan.
What I have tried: Google, Worldcat, Libgen, and other search engines have not returned this dissertation. My university interlibrary loan office participates in a special program to obtain foreign dissertations (usually on microfilm). They were unable to get a copy of this. I have also tried purchasing this dissertation on disserCat, but there is no scan of the dissertation available at present, so it is not for sale. I also emailed another Russian website which claimed to be able to sell the dissertation, but I never received a reply.
See also:
The author was kind enough to scan their thesis and email me a copy.
While only having read the abstract at the moment, this seems to confirm my belief that one should generate a large amount of hypotheses when one wants a more rigorous answer to a question. I've started doing this in my PhD research, mostly by compiling others' hypotheses, but also by generating my own. I've been struck by how few researchers actually do this. However, the researchers who indeed do consider multiple hypotheses (e.g., in my field one major researcher who does is Rolf Reitz) earn greater respect from me.
Also, hypothesis generation is definitely non-trivial in real scientific domains. Both generating entirely new hypotheses and steelmanning existing hypotheses are non-trivial. It doesn't matter if your scientific method will converge to the right hypothesis if it's in your considered set if most sets don't contain the "correct" hypothesis...
Very interesting paper. I will be reading this closely. Thanks for posting this link.
Poetry, along with some other art forms, always struck me as inherently uninteresting to the point where I find it hard to believe anyone actually enjoys it. I see some people who are obviously moved by poetry, so clearly I'm just at one end of the spectrum. To each their own.
Visited the Library of Congress this past Wednesday. I'll be going to the Library of Congress several times this summer, so reply to one of my comments here if you want anything in particular at the Library of Congress.
It was a fairly productive day, as I think I've found a good strategy for avoiding the phone book people at the scanner. For some reason, there's often a ton of people who do nothing other than look at old phone books. I assume this is for some sort of private investigator business or something along those lines. I never asked. Anyway, they tend to procrastinate and use the one overhead scanner starting around 2 to 3 pm, so it's best to do as much book scanning before them. My current strategy is to do my book scanning before 2 and then switch to microfilm, as I rarely ever see anyone using the microfilm viewers or scanners.
I hoped it would be possible to extract the data from the diagram, but no, the jpg in the pdf is sufficiently low-resolution that it doesn't work.
I have been compiling a lot of data for part of my PhD and this is a lot more common than I am comfortable with. Personally, as a reviewer I've decided to outright reject papers that don't allow one to extract the data. My preference would be requiring publishing the data straight up, but I can see an editor viewing this as unreasonable, or an author not knowing how to publish data.
With this being said, it's worth asking authors for raw data. My prior on receiving raw data from an author is low, particularly if the study is older. You have nothing to lose, however, and you will sometimes gain respect for helpful researchers. One professor I emailed for about 25 year old data searched his office thoroughly, found the data I wanted on some old floppy disks, got a floppy drive working, and emailed me the files. That was a not insignificant amount of their time, and I'm very appreciative for it.
Also, frequently theses and dissertations have tabulated data. Beware of typos in the tables. Always perform some sort of sanity checks on the data. Checking the tables against the figures is one approach.
r/UCDavis has confirmed that this can't be downloaded from HathiTrust if you are a UCD student. Someone there pointed out a copy at UC Berkeley that might be obtainable. Trying that now.
I'll be visiting the Library of Congress next week for one day. Let me know here if there's anything in particular you might want me to look at or scan there.
To keep this manageable, I'll only accept requests that appear difficult to obtain elsewhere. If it looks like you can get what you want via interlibrary loan, try that rather than asking me. If you are not affiliated with a university then I'd recommend talking to a librarian at a public library about this. Seems many public libraries will do interlibrary loan for free or a fee.
Likely I'll make a second trip to the Library of Congress in August, too.
This reminds me of something my father, a retired patent examiner, told me once. For a certain legal procedure the US Patent Office has a form letter a lawyer can use that contains all of the relevant information in a convenient format. My father was amazed by lawyers who refused to use it and instead wrote their own version of it. This seems like a waste of time for both the lawyer and examiner. When my father asked why, at least one lawyer told him that they believed the standard form had legal implications they didn't like, though my father insisted that case law made it clear that was wrong here.
Another (cynical) hypothesis is that these lawyers are paid by the hour and that they actively wanted to waste time.
R. D. Monson, "Experimental studies of cylindrical and sheet jets with and without forced nozzle vibrations" M.S. thesis, Dept. of Mech. Engr., Univ. of Calif., Davis (December 1980).
UC Davis refuses to loan this for unknown reasons. What I find odd is that it has already been digitized. UC Davis students might be able to download it here. Let me know if you can download it.
Good point. Ideal would be entering a number. If I recall correctly the actual guidelines are written in terms of MET-minutes, a weird exercise specific unit of energy. The entire "moderate intensity exercise" thing is a simplification of the actual recommendation. I'm not sure how much participation would decrease if we generalized from binary in this way.
I'd be interested in a question about aerobic fitness. My impression is that most rationalists severely underrate aerobic physical activity compared against anaerobic, which is surprising because anaerobic doesn't help cardiovascular capacity much. Presumably given the interest in cryonics and whatnot here, rationalists are interested in living longer. Cardiovascular capacity (VO2max, typically) is strongly correlated with longevity, and it's easy to see the direction of causation.
Possible question: "Over the past month, have you typically met the US federal guidelines for aerobic physical activity? This means at least 150 minutes (2 hours and 30 minutes) a week of moderate-intensity, or 75 minutes (1 hour and 15 minutes) a week of vigorous-intensity aerobic physical activity, or an equivalent combination of moderate- and vigorous-intensity aerobic activity. See health.gov for more information."
There's a lot of data on this question, so it will be easy to compare LessWrongers against other groups.
If you think in terms of QALYs, that could be one reason to prefer interventions targeted at children. Your average child has more life to live than your average adult, so if you permanently improve their quality of life from 0.8 QALYs per year to 0.95 QALYs per year, that would result in a larger QALY change than the same intervention on the adult.
This argument has numerous flaws. One which comes to mind immediately are that many interventions are not so long lasting, so both adults and children would presumably gain the same. It also is tied to particular forms of utilitarianism one might not subscribe to.
Omnilibrium was nominally supposed to be a rationalist political discussion website, but it seems to have died.
I have been too busy to participate much, but I did find my brief time there to be valuable, and would be interested in seeing the website become more active again.
I spidered his site with wget at one point. I'd be happy to provide a copy to anyone who wants it, but I'm afraid wget did not get everything, e.g., the image in question here would probably not have been found by wget.
Romashka, I appreciate the reply.
Yes, I remember that post. It was 'almost interesting' to me, because it is beyond my actual knowledge. So, if you could just maybe make it less scary, we landlubbers would love you to bits. If you'd like.
If you don't mind, could you highlight which parts you thought were too difficult?
Aside from adding more details, examples, and illustrations, I'm not sure what I could change. I will have to think about this more.
re: errors. I mean that it seemed to me (probably wrongly) that if you measure a bunch of variables, and try to make a model from them, then realise you only want a few and the others can be screwed together into a dimensionless 'thing', then how do you know the, well, 'bounds of correctness' of the dimensionless thing? It was built from imperfect measurements that carried errors in them; where do the errors go when you combine variables into something new? (I mean, it is a silly question, but i haz it.)
This is an important question to ask. After non-dimensionalizing the data and plotting it, if there aren't large gaps in the coverage of any dimensionless independent variable, then you can just use the ranges of the dimensionless independent variables.
I could add some plots showing this more obviously in a discussion post.
Here are some example correlations from heat transfer. Engineers did heat transfer experiments in pipes and measured the heat flux as a function of different velocities. They then converted heat flux into the Nusselt number and the velocity/pipe diameter/viscosity into the Reynolds number, and had another term called the Prandtl number. There are plots of these experiments in the literature and you can see where the data for the correlation starts and ends. As you do not always have a clear idea of what happens outside the data (unless you have a theory), this usually is where the limits come from.
Sure, I'd be interested in writing an article on dimensional analysis and scaling in general. I might have time over my winter break. It's also worth noting that I posted on dimensional analysis before. Dimensional analysis is not as popular as principal components analysis, despite being much easier, and I think this is unfortunate.
I don't know what a "ribbon-shaped population" is, but I imagine that fern spores are blown off by wind and then dispersed by a combination of wind and turbulence. Turbulent dispersion of particles is essentially an entire field by itself. I have some experience in it from modeling water droplet trajectories for fire suppression, so I might be able to help you more, assuming I understand your problem correctly. Feel free to send me a message on here if you'd like help.
And even worse, I had a weird feeling like 'oh this has to be so noisy, how do they even know how the errors are combined in these new parameters? Surely they don't just sum.'
Could you explain this a little more? I'm not exactly following.
Because dimensional homogeneity is a requirement for physical models, any series of independent dimensionless variables you construct should be "correct" in a strict sense, but they are not unique, and consequently you might not naively pick "useful" variables. If this doesn't make sense, then I could explain in more detail or differently.
The test labeled me as a "rationalist".
Glad to help. I'll go through your recommendations later this month when I have more time.
Thanks for the detailed reply, sen. I don't follow everything you said, but I'll take a look at your recommendations and see after that.
I can probably give a better answer if I know more precisely what you're referring to. Do you have examples of fluid dynamicists simplifying equations and citing group theory as the justification?
Unfortunately, the subject is rather disjoint. Most fluid dynamicists would have no idea that group theory is relevant. My impression is that some mathematicians have interpreted what fluid dynamicists have done for a long time in terms of group theory, and extended their methods. Fluid dynamicists call the approach "dimensional analysis" if you reduce the number of input parameters or "similarity analysis" if you reduce the number independent variables of a differential equation (more on the latter later)
The goal generally is dimension reduction. For example, if you are to perform a simple factorial experiment with 3 variables and you want to sample 8 different values of each variable, you have 8^3 = 512 samples to make, and that's not even considering doing multiple trials. But, if you can determine a coordinate transformation which reduces those 3 variables to 1, then you only have 8 samples to make.
The Buckingham Pi theorem allows you to determine how many dimensionless variables are needed to fully specify the problem if you start with dimensional quantities. (If everything is dimensionless to begin with, there's no benefit from this technique, but other techniques might have benefit.)
For a long list of examples of the dimensionless quantities, see Wikipedia. The Reynolds number is the most well known of these. (Also, contrary to common understanding, the Reynolds number doesn't really say anything about "how turbulent" a flow is, rather, it would be better thought of as a way to characterize instability of a flow. There are multiple ways to measure "how turbulent" a flow is.)
For a "similarity variable", I'm not sure what the best place to point them out would be. Here's one example, though: If you take the 1D unbounded heat equation and change coordinates to \eta = x / \sqrt{\alpha t} (\alpha is the thermal diffusivity), you'll find the PDE is reduced to an ODE, and solution should be much easier now. The derivation of the reduction to an ODE is not on Wikipedia, but it is very straightforward.
Dimensional analysis is really only taught to engineers working on fluid mechanics and heat transfer. I am continually surprised by how few people are aware of it. It should be part of the undergraduate curriculum for any degree in physics. Statisticians, particularly those who work in experimental design, also should know it. Here's an interesting video of a talk with an application of dimensional analysis to experimental design. As I recall, one of the questions asked after the talk related the approach to Lie groups.
For an engineering viewpoint, I'd recommend Langhaar's book. This book does not discuss similarity variables, however. For something bridging the more mathematical and engineering viewpoints I have one recommendation. I haven't looked at this book, but it's one of the few I could find which discusses both the Buckingham Pi theorem and Lie groups. For something purely on the group theory side, see Olver's book.
Anyhow, I asked about this because I get the impression from some physicists that there's more to applications of group theory to building models than what I've seen.
Consider that the !∘sqrt∘ln of a dimensionless quantity is also technically a dimensionless quantity while also being almost-certainly useless and uninterpretable.
This is an important realization. The Buckingham Pi theorem doesn't tell you which dimensionless variables are "valid" or "useful", just the number of them needed to fully specify the problem. Whether or not a dimensionless number is "valid" or "useful" depends on what you are interested in.
Edit: Fixed some typos.
Creativity is another big area that seems neglected. I've read a fair amount on the subject, but feel I have barely touched the surface.
I also feel it probably is relevant to AI, so I'm somewhat surprised to see so little discussion of it here. (By "AI" I mean a number of things here. Might be easiest to see it as application of computers to solve problems.) At the moment, AI works when the actions one can take are clear (e.g., small number of valid moves in a game). When the possible actions are not precisely specified, the specification becomes the issue. Generating these possibilities is not trivial, and frequently this is what creativity is.
Is there a single book or resource you would recommend for learning how group theory/symmetry can be used to develop theories and models?
I work in fluid dynamics, and I've mainly seen group theory/symmetry mentioned when forming simplifying coordinate transformations. Fluid dynamicists call these "dimensionless parameters" or "similarity variables". I am certain other fields use different terminology.
The Library of Congress does not have these proceedings, unfortunately.
As a cyclist, I'd be interested in seeing these articles as well.
Unfortunately my university doesn't have any of these. I could request them by interlibrary loan, but I suspect I'd be on break by the time they come in.
I usually visit the Library of Congress when visiting my parents on breaks, and I'll check their catalog to see if they have these proceedings later. Their online catalog is not working at the moment. I'll make a new reply to your comment when I do.
I've had good experience with MyFitnessPal with respect to speed, and find the features sufficient for my purposes. I manually enter my exercise data, so I can not comment on automatic exercise tracking.
I found FitDay to be annoyingly slow, but I used the site for years before MyFitnessPal.
Learning of the reputation of the journal from someone knowledgeable about its field is the most reliable way I can think of for someone outside the field of interest.
Impact factors seem inappropriate to me, as they can vary wildly between fields and even wildly among subfields. A more specialized, but still high quality, journal could have a much lower impact factor than a more general journal, even if the two are at roughly the same average quality. Also, some foreign language journals can be excellent despite having low impact factors for the field of the journal. This unfortunately is true even for cover-to-cover or partial translations of those foreign language journals.
You also could learn what signs to avoid. Some journals publish nonsense, and that's usually pretty obvious after looking at a few articles. (Though, in some fields it can be hard to separate nonsense from parody.)
Beyond the previous recommendations, it's probably better to focus on the merits of the article rather than the journal. I can immediately think of one article in particular which has a non-obvious major flaw that is published in a small journal that I consider excellent. This error should have been caught in review, but it was not, probably because catching the error requires redoing math the authors skipped over in the article. (In intend to eventually publish a paper on this error after I finish my correction to it.)
I want to show that fighting aging is underestimated from effective altruistic point of view. I would name it second most effective way to prevent sufferings after x-risks prevention.
I'd be very interested in seeing this.
I think life extension should be discussed more here.
Many rationalists disappointment me with respect to life extension. Too many of them seem to recognize that physical conditioning is important, yet very few seem to do the right things. Most rationalists who understand that physical conditioning is important think they should do something, but that something tends to be almost exclusively lifting weights with little to no cardiovascular exercise. (I consider walking to barely qualify as cardiovascular exercise, by the way.) I think both are important, but if you only could do one, I'd pick cardio because it's much easier to improve your cardiovascular capacity that way. (Cardiovascular capacity/VO2max correlates well with longevity, as discussed here.) I'm not alone in the belief that cardio is much more important; similar things have been said for a long time. I'd recommend Ken Cooper's first book for more on this perspective.
The inability for rationalists to regularly do cardiovascular exercise probably stems from similar problems that cause cryocrastination. I'd like to see more on actually implementing cardiovascular exercise routines. I have some notes on this which could help. Off the top of my head I can remember that there's evidence morning runners tend to maintain the habit better and that there's evidence that exercising in a group helps with compliance. I personally find Beeminder to help a little bit, but not much.
A big gap I see is memory. Having read a few books on learning and memory, I think what's been posted on LessWrong has been fragmented and incomplete, and we're in need of a good summary/review of the entire literature. There's a lot of confusion on the subject here too, e.g., this article seems to think spaced repetition and mnemonics are mutually exclusive techniques, but they're not at all. When I used Anki I frequently used mnemonics as well. The article seems to be an argument against bad flash cards, not spaced repetition in general. Probably over a year ago I did start writing a sequence on memory enhancement, but it is a low priority task for me it and do not anticipate completing it any time soon.
Some sort of emoticon could work, like what Facebook does.
Personally, I find the lack of feedback from an upvote or downvote to be discouraging. I understand that many people don't want to take the time to provide a quick comment, but personally I think that's silly as a 10 second comment could help a lot in many cases. If there is a possibility for a 1 second feedback method to allow a little more information than up or down, I think it's worth trying.
Integration with predictionbook or something similar, to show a user's track record in addition to upvotes/downvotes. Emphasis on getting many people to vote on the same set of standardized predictions
This would be a top recommendation of mine as well. There are quite a few prediction tracking websites now: PredictionBook, Metaculus, and Good Judgement Open come to mind immediately, and that's not considering the various prediction markets too.
I've started writing a command line prediction tracker which will integrate with these sites and some others (eventually, at least). PredictionBook and Metaculus both seem to have APIs which would make the integration rather easy. So integration with LessWrong should not be particularly difficult. (The API for Metaculus is not documented best I can tell, but by snooping around the code you can figure things out...)
I'll second the suggestion that we should consider other options. While I know Vaniver personally and believe he would do an excellent job, I think Vaniver would agree that considering other candidates too would be a wise choice. (Narrow framing is one of the "villians" of decision making in a book on decision making he suggested to me, Decisive.) Plus, I scanned this thread and I haven't seen Vaniver say he is okay with such a role.
According to 538's survey more people reported that they comment to fix errors than anything else.
This doesn't mean that you're wrong, though, because it doesn't seem 538 asked why people stop commenting (based on my skim of the article; feel free to correct me).
Good point about regulatory issues. I've been thinking a lot about working on standards committees and whatnot as they actually have influence and many standards/regulations/codes are bad.
Using waste streams is one of the more basic efficiency engineering approaches, and at this point I think if large gains were to be had from those, we'd have them already.
As for condensing CO2, there are tons of ideas along those lines, but I'm not sure carbon capture is worthwhile. I'd need to see more economic analysis of those ideas, or better yet, test implementations. That's more or less my point. There are a ton of ideas, many of which could work technologically, but which would work economically/socially/etc. as well?
Let's go back to biological systems. Even assuming that most people driving is a good idea (I don't assume this), cars are somewhat irrational for that purpose. You can cut down drag (and consequently increase efficiency) a lot with relatively basic (and well known) modifications, e.g., boat tailing. It seems to me that cars aren't built that way in the first place because even though people say they want fuel economy, etc., cars built that way won't sell.
There used to be a really interesting interview along those lines with Bob Lutz (a well known car company executive) here, but it seems to have since gone offline. Here's what I have quoted in my notes:
AlixPartners: I would love to hear your point of view on design. Is it becoming even more important or not?
Bob Lutz: If you look at the [auto] companies that are really successful today, they are heavily design-focused.
In an era of levelness in almost everything else—fuel consumption, safety (which is all mandated anyway), cost, et cetera, et cetera, et cetera—the one thing that sticks out that can give you a huge competitive advantage is design.
AlixPartners: There's always a trade-off between the design side and the engineer. What are some of the key lessons you might want to pass on about that give and take?
Bob Lutz: Well, my key lesson learned, and I pass on to anybody who is in any position of responsibility in the automobile business, is if you look at the automobile as a collection of rational traits, like fuel economy, shoulder room, elbow room, hip room, rear H-point to dash, et cetera, et cetera, et cetera--and you get all that down on paper and the car is totally defined dimensionally, and then you hand it to the designers and say, “Put a wrapper on this, please,” you're going to get a car that meets every rational, stated desire on the part of a potential customer—but nobody's going to buy it! Because it is a fundamental mistake to look at cars and their attributes in a rational way.
We're all rational people. but looking at cars as fulfilling rational needs and then designing to that is about as smart as designing men's wristwatches for function only. They're just not going to sell.
And it's the same with cars. Tumblehome, side sloping in, fast windshield, roof height—[it was usually a] struggle to get what the designers wanted, in terms of not having a very stiff-looking car. And [the engineers would often] say, “Well, but what you're doing is it's going to deteriorate head swing lateral [if we] go down another half inch in roof height.”
And I would say, “Have you ever seen people in a showroom with tape measures, where the husband and wife are in there measuring and finally one of them says, ‘You know honey, this Chevrolet has a half inch less [room] than the Toyota Camry we saw before. Let's go buy it.’”
That's just not the way people behave. People won't even be in the showroom unless the car fascinates them visually from ads or as seen on television or seen in the street, or whatever.
I'm interested in predicting future events to prioritize technology research. I've been thinking about getting speakers with expertise in the future of computing, trends of resource availability and utilization, climate change, and clean energy to start.
Previously I thought futurism was all about making optimistic predictions, but since then I've found more futurists who make predictions I think are credible. I track my own on PredictionBook and am going to start using Metaculus and GJOpen soon.
And despite working on a PhD in engineering, I'm actually quite skeptical of technology. Technological solutions to problems don't have as good a track record as most believe, and I think this influences where I should focus my research. For example, I used to think clean energy research was very important, but I've since come to the conclusion that energy and climate change are social/economic, political, or even aesthetic problems, not so much technical problems. That's not to say technology won't play a role, but due to things like the Jevons paradox, technology's role isn't as obvious as people think it is. Improving efficiency can increase usage, not that even maximally efficient systems will necessarily solve the problem. You should get some idea of what the actual effect of the research will be rather than assuming the effect will be what you want. Similar things are frequently said about starting a business: Check if the market exists before starting the business.
Thanks. I agree that those examples are problematic. Do you have the link for Trump being the most significant current existential risk? I think he's a major risk, but relatively less important than many other things.
The biggest risk from him is starting a major war and/or using nuclear weapons, but as I recall from speaking with Vaniver, not everyone thinks he's a higher risk than Clinton would be in that area.
I would have liked to, but they rejected my application. (Edit: I imagine I'm getting downvoted because I mentioned this. Note that this is not complaining. I tend to view application processes as close to lotteries, so I don't take this personally.)
The topics of the conference interest me greatly. Right now I'm planning on hosting some futurist related discussions through the Austin LessWrong group while coordinating with a local futurist group.
If you will attend and have the opportunity, I'd be interested in seeing a summary of your experiences at the conference.
Can you give some examples? I haven't paid much attention to this.
While we're on the topic, "politics is the mind-killer" isn't sufficiently broad in my opinion. People can frequently are "mind-killed" in other areas, especially when conflicts of interest are involved. My experience suggests certain topics like diet tend to go just as poorly as politics.
So I meant "p/s works" = "splitting sleep into multiple phases in certain ways does increase efficiency and makes you require less sleep"
This appears to be true if you must be sleep deprived. That is, if you want to operate at X% function, where X is less than 100, likely less than 70 or so, you would need to sleep a shorter duration on a polyphasic schedule than you would on a monophasic schedule. ("X% function" is somewhat vague, but I trust you understand what I mean.)
However, if you want high X% function (say, higher than 90%) then the required sleep durations appear to be the same in either case. This could easily make polyphasic sleep likely less efficient considering logistics (time spent getting into bed, etc.) and time to fall asleep.
I'd recommend taking a look at Stampi's book for more information on polyphasic sleep being efficient for sleep deprivation but not so for normal levels of sleep. I also want to note that the estimated percentages I gave above are for illustration only. Look at Stampi's book for more accurate information. I do not have a copy any longer.
You're mixing things together. If I adapted a polyphasic schedule and also fixed real issues in the process, and have now significantly better sleep due to fixing those, then I am not "mildly deluded yourself and are avoiding disconfirming evidence." [...] Instead, I am correctly observing better sleep and am just attributing it incorrectly. So those are different things.
You are correct. This is exactly what I meant by "I should have given these possibilities more consideration as well, and I do now.". I should have also changed the earlier part of my post to back away more from the placebo and wishful thinking statements. The purpose of the elaboration was to explain my earlier statements in greater detail.
(note also that I am not avoiding any evidence because I have never encountered any evidence against p/s until today).
That is not what I meant. As an example, consider that you dropped a glass of water. Someone who was tired might attribute that to being tired, but someone who very strongly wanted to believe that polyphasic sleep worked would probably try to find an explanation other than that they were tired.
The argument is circular. You say that [...]
No, I think you are putting words into my mouth. My assessment of the weakness of evidence for short polyphasic sleep schedules is based primarily on the a) evidence that it does not work, including self-reported evidence (most people completely fail, and I see no reason to believe they all are "doing it wrong", etc.) and b) the fact that the standard mechanisms by which it could work are not plausible. I actually started investigating polyphasic sleep thinking the idea was plausible, but the more evidence I encountered, the less I believed.
I believe I have discussed a in sufficient detail.
For b, polyphasic sleep proponents used to claim that polyphasic sleep allows you to go into REM quickly, and REM was all you need, therefore polyphasic sleep was more efficient. To be fair, some of this is true, but the general message is false. The studies I linked to in my posts from 2014 suggest that deep sleep is the most important, but there's reason to believe all stages are important. With that said, as I recall (will need to dig up the study for this), certain antidepressants completely suppress REM and those people are doing fine best I can tell (at least compared against other folks on similar antidepressants without REM suppression). The technical term for a sleep period where one goes in to REM fast is SOREMP and it's taken as a symptom of either severe sleep deprivation or narcolepsy, and not regarded as good thing.
So, a better argument would be that polyphasic sleep allows one to get the same or greater amount of deep sleep, while reducing time in less important stages of sleep. This by itself seemed plausible to me in 2014, so I looked more into it. Unfortunately, as I stated in my 2014 posts, in actual polyphasic sleep, you experience each stage of sleep in relatively the same proportion as you did before. Both REM and deep sleep decrease. (Please note that this is contrary to what the Polyphasic Society claims! Their claims: "The body can also change the first portion of a ‘core sleep’ from mostly stage 1 and 2, to mostly stage 3 (SWS)" and "Because you are sleeping more often and getting dream-full REM in your multiple sleeps, you will be dreaming more!")
There are also some arguments like "this is how our ancestors slept, therefore it's how you should sleep too". There are a few things I think about this. First, it does seem that many of our ancestors did do some sort of biphasic sleep, either with a gap in the middle of the night or a nap in the afternoon. I don't think this was done to reduce sleep time, so it's not an argument for those sorts of schedules. Also, while evolutionary arguments are okay for generating hypotheses, they also need to fit the evidence, and as I said, the evidence really isn't a point in polyphasic sleep's favor.
Consider my perspective for a moment. Polyphasic Society prophesied a bunch if one does X , I estimated that they were credible based on presentation, I did X, I got pretty much exactly what was promised in about as much time as I thought it would take. Now you come telling me that all improvements are due to side effects and p/s has actually zero benefits. That's not impossible, but clearly less plausible. Why should I believe it?
You should believe me because the Polyphasic Society's arguments are based on faulty understandings of sleep, and are contradicted by empirical studies, many of which were conducted by someone they hold in high regard, Claudio Stampi. See here for additional details.
And what is it about the presentation of the Polyphasic Society that makes them seem credible? Their assertions generally have no citations. They seem like your standard alt-med website, which I don't consider credible.
If polyphasic sleep worked, you would see it advocated by sleep doctors and researchers, and also used by the military. These people are not unfamiliar with the idea. As I recall, the military is very interested in optimizing sleep, but they focus on things that actually work, like good sleep hygiene and getting physical exercise.
- The paragraph reads stronger than the arguments actually are. Let me untangle them [...]
There are a very large number of possibilities. I mentioned consolidated sleep as an example because I know many people wake up frequently and this prevents them from having good sleep quality. Look up sleep hygiene. Any number of those pieces of advice could have had a big effect. Personally, I find having a regular schedule to be of the greatest help to me, but that might not be the case for others. I can not pin down what's happening to you other than that I do not believe polyphasic sleep by itself is helping.
Honestly, this just seems silly. The experience of tiredness is subjective. What matters is how tired I feel, and I feel significantly less tired than previously (except in the morning, as I've said already, and this is improving).
Experience is subjective by definition. Why being tired is bad is not necessarily subjective, however. Does it matter if you subjectively "feel" awake if you'll fall asleep if you sit down for 10 minutes? Does it matter if you subjectively "feel" awake if your cognitive performance is reduced?
See, you're assuming here that the number is lower than what should be expected, and that needs explaining. I don't think that's true.
In my 2014 posts, I used a success rate which was based on numbers from a major polyphasic sleep proponent. Personally, I think this number is very high (i.e., the failure rate is lower than I would put it at), but I have not done the polyphasic sleep census I think would be necessary to figure out it more precisely. I choose this number as it was the only one I saw available, and I thought it would be hard to accuse me of trying to paint polyphasic sleep in a bad light if I used a number from a proponent, but I guess I was wrong.
– Most people try harder ones first (that already gives you a majority that'll almost unanimously fail)
I am unsure. My own experience suggests that people gravitate towards the less extreme forms, as you did. I'm not aware of any polyphasic sleep census which would allow one to determine this.
– Most people probably don't do it correctly
I've seen a wide variety of reasons given for why people fail, and it seems to be to basically be variations of the No true Scotsman fallacy or even straight up cherry picking. Sure, I'd expect many people who attempted polyphasic sleep to have done it wrong. I, however, see no reason to conclude that almost everyone who tried it did it wrong. The procedure does not seem that complicated and I do not think it's particularly sensitive to many variables. The base rate for success for these sorts of things in general seems to be higher. I need a better explanation than just asserting that the majority of people do it wrong. Evidence for this assertion would be appreciated.
– Most people probably don't try that hard (more controversially, most people are lazy to begin with)
I definitely do not believe that most people who try polyphasic sleep don't try that hard. I've skimmed blogs where people tried this and the overwhelming impression I got was that they tried really really hard. And usually they seemed to think it would work up until they quit. This was my impression. I'd like to see some sort of polyphasic sleep census to help answer these questions, as I've said, that doesn't exist.
One person I know tried polyphasic sleep, and as I recall, they definitely tried hard, but ultimately failed.
(addressing the [[]]): Now that's a really bold statement. Do you have evidence?
I do not think this is a bold statement at all. It comes from my reading about polyphasic sleep over the years. I got the impression from people who failed that they did do exactly as they were told (or nearly so) and did try hard. That's what I meant. Again, absent a polyphasic sleep census, I can't give stronger evidence than pointing out a few of the blogs I recall skimming through. I'd be happy to do a few minutes of digging if you are interested.