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CFAR has all of this material readily available likely in a much more comprehensive and accurate format. CFAR are altruists. Smart altruists. The lack of anything like this canon suggests that they don't think having this publicly available is a good idea. Not yet anyway. Even the workbook handed out at the workshops isn't available.
Having it publicly available definitely has huge costs and tradeoffs. This is particularly true when you're worried about the processes you want to encourage getting stuck as a fixed doctrine - this is essentially why John Boyd preferred presentations over manuals when running his reform movement in the US military.
Random changes can be useful. Human minds are not good at being creative and exploring solution space. They can't give "random" numbers, and will tend to round ideas they have towards the nearest cached pattern. The occasional jolt of randomness can lead to unexplored sections of solution space.
It's been stuck, but I haven't barely been putting effort into it. I've been working much more on minimizing mouse usage - vim for text editing, firefox with pentadactyl for web browsing, and bash for many computing and programming tasks.
The low-hanging fruit is definitely not in getting better at stenographic typing - since I've started working as a professional software developer, there's been much more computer-operation than English text entry. I'd have to figure out a really solid way of switching seamlessly between Vim's normal-mode and stenographic typing in insert mode. And configuration and exploratory learning that I'm nowhere near capable of to adjust stenographic typing to writing code in addition to English. It's likely still my best option for getting super solid at writing English text, but it's simply lower priority at the moment than other tools.
Daydreaming is nice.
Because I can't talk about what makes it awesome without spoiling it, and I forgot that rot13 is a thing.
Warning: massive spoilers below
Fpvba, gur ynfg yvivat tbqyvxr nyvra erfcbafvoyr sbe cnenuhzna cbjref, vf svtugvat Rvqbyba naq Tynvfgnt Hynvar. Rvqbyba vf bar bs gur zbfg cbjreshy pncrf, n uvtu yriry Gehzc - uvf cbjre tvirf uvz gur guerr cbjref gung ur arrqf. Uvf cbjre jnf jrnxravat bire gvzr, naq ur erpragyl svkrq vg, naq vf gnxvat gur bssrafvir gb Fpvba.
Sbe onpxtebhaq, gurer unir orra n frevrf bs pvgl-qrfgeblvat zbafgref pnyyrq "Raqoevatref". Gurl fubjrq hc nsgre Rvqbyba chg Tynvfgnt Hynvar vagb gur Oveqpntr, n fhcrecevfba sbe cnenuhznaf. Gurl'ir xvyyrq pbhagyrff pncrf naq jerpxrq n gba bs guvatf - Yrivnguna pbagebyf jngre naq fnax Xlhfuh, naq fpnevarff yriryf tb hc sebz gurer.
Abj, Rvqbyba unf fgnegrq npghnyyl cerffhevat Fpvba fbzr, fb Fpvba qrpvqrf gb hfr na rkcrafvir cbjre - gur novyvgl gb svther bhg jung ur arrqf gb qb va beqre gb jva. Vg gheaf bhg gung gur npgvba vf gb fgbc naq fnl sbhe jbeqf gb hggreyl gnxr gur svtug bhg bs Rvqbyba, naq gura oynfg uvz nf ur cebprffrf vg. Naq bire gur ynfg guvegl lrnef, Fpvba unf fnvq V guvax 2 jbeqf gbgny, znlor bar.
"Lbh arrqrq jbegul bccbaragf". Nyy gur crbcyr gung qvrq, nyy gur fnpevsvprf lbh naq lbhe sevraqf znqr - nyy gung unccrarq orpnhfr lbh arrqrq gb cebir lbhefrys, lbh arrqrq fbzrguvat gb svtug ntnvafg, fbzrguvat gb tvir lbh checbfr. Nyy orpnhfr lbh pbhyqa'g qrny jvgu gur checbfryrffarff bs abg univat fbzrguvat gb svtug ntnvafg. Naq fb, lbh tbg gur Raqoevatref - Orurzbgu, Yrivnguna, gur Fvzhetu, Xubafh, Obuh naq Gbuh.
Naq vs lbh qba'g ernq gur pbzzragf, vg'f rnfl gb zvff bhg ba ubj Rvqbyba gnxrf gubfr jbeqf.
There's a four-word chapter in worm. If you read one chapter's comment pages, read that one's.
Deciding to play slot machines is not a choice people make because they think it will net them money, it's a choice they make because they think it will be fun.
Update: I'm at pretty much the same place now as I was then. Dropped the keto diet since I was happy with where I was. Still fairly active but not hardcore about it.
They'd be better off using a shared algorithm if involved in a situation with cars reasoning in a similar fashion.
Plover is another option. I spent a month or so learning it and got to about 50 WPM, while those with a lot more practice can get 200 WPM. It's on hold indefinitely, though.
"Control" in general is not particularly well defined as a yes/no proposition. You can likely rigorously define an agent's control of a resource by finding the expected states of that resource, given various decisions made by the agent.
That kind of definition works for measuring how much control you have over your own body - given that you decide to raise your hand, how likely are you to raise your hand, compared to deciding not to raise your hand. Invalids and inmates have much less control of their body, which is pretty much what you'd expect out of a reasonable definition of control over resources.
This is still a very hand-wavy definition, but I hope it helps.
I'm a current student who started two weeks ago on Monday. I'd be happy to talk as well.
Dollars already have value. You need to give them to the US government in order to produce valuable goods and services inside the United States. That's all there is to it, really - if someone wants to make #{product} in a US plant, they now owe US dollars to the government, which they need to acquire by selling #{product}. So if you have US dollars, you can buy things like #{product}.
That's the concise answer.
The real danger of the "win-more" concept is that it's only barely different than making choices that turn an advantage into a win. You're often put in a place where you're somehow ahead, but your opponent has ways to get back in the game. They don't have them yet - you wouldn't be winning if they did - but the longer you give them the more time they have.
For a personal example from a couple years ago, playing Magic in the Legacy format, I once went up against a Reanimator deck with my mono-blue control deck. The start was fairly typical - Reanimator trying to resolve a gigantic threat to win, while I played many counterspells and hit him with some Vendilion Clique beats. My opponent ended up getting an Iona out (naming blue, obviously), but went down to exactly one life to do so. This was very, very awkward for him, since he couldn't attack with the Iona, activate fetchlands, or use the alternate cost of Force of Will. But, I had outs - Powder Keg (7 copies of keg/ratchet bomb) and waiting 9 turns, or Vedalken Shackles (3 copies). So I stayed in, and got as many draw phases as I could, and lucked out with a Shackles topdeck, followed by being able to play blue spells and winning the game.
Anyhow, my point is that cards that help you only when you're winning can turn wins into losses. Your opponents can have outs, and it's a good idea to take those outs away. If you don't, then sometimes your opponent will pull exactly what they need to do something ridiculous - say, dealing with a card that keeps them from playing 28 of their 38 spells, and seven of the ten spells they can play take 9 turns to do anything about it.
"Win-more" is definitely the wrong word to describe this concept. I think a better choice is calling it a "close-out" or "finishing" card. The point of these is to make sure that you win when you have an advantage. It also tells you that you don't want too many of these - many decks run just one or two copies. Dredge, for instance, runs a single Flayer to turn having their deck in their graveyard into a win. My mono-blue control deck ran two Sphinx of Jwar Isle (there were essentially zero answers for him in the meta, and I've stolen games with him. That said, one copy would be an Aetherling if it was printed at the time).
Replacing a card with a finisher means that you'll take fewer leads, but win more games while ahead. Sometimes the right number of finishers is one - when Dredge has a lead, it's got access to all or most of the cards in their deck. Sometimes it's more - my mono-blue deck would run between 2 and 6, depending on how I felt about Jace at the time. Often it's zero, and your game plan is to win with the cards that got you ahead in the first place.
I read a comment in this thread by Armok_GoB, and it reminded me of some machine-learning angles you could take on this problem. Forgive me if I make a fool of myself on this, I'm fairly rusty. Here's my first guess as to how I'd solve the following:
open problem: the tradeoff of searching for an exact solution versus having a good approximation
Take a bunch of proven statements, and look at half of them. Generate a bunch of possible heuristics, and score them based on how well they predict the other half of the proven statements given the first half as proven. Keep track of how long it takes to apply a heuristic. Use the weighted combination of heuristics that worked best on known data, given various run-time constraints.
With a table of heuristic combinations and their historical effectiveness and computational time, and the expected value of having accurate information, you can quickly compute the expected value of running the heuristics. Then compare it against the expected computation time to see if it's worth running.
Finally, you can update the heuristics themselves whenever you decide to add more proofs. You can also check short run-time heuristics with longer run-time ones. Things that work better than you expected, you should expect to work better.
Oh, and the value-of-information calculation I mentioned earlier can be used to pick up some cheap computational cycles as well - if it turns out that whether or not the billionth digit of pi is "3" is worth $3.50, you can simply decide to not care about that question.
And to be rigorous, here are the hand-waving parts of this plan:
Generate heuristics. How? I mean, you could simply write every program that takes a list of proofs, starting at the simplest, and start checking them. That seems very inefficient, though. There may be machine learning techniques for this that I simply have not been exposed to.
Given a list of heuristics, how do you determine how well they work? I'm pretty sure this is a known-solved problem, but I can't remember the exact solution. If I remember right it's something along the lines of log-difference, where getting something wrong is worth more penalty points the more certain you are about it.
Given a list heuristics, how do you find the best weighted combinations under a run-time constraint? This is a gigantic mess of linear algebra.
And another problem with it that I just found is that there's no room for meta-heuristics. If the proofs come in two distinguishable groups that are separately amenable to two different heuristics, then it's a really good idea to separate out these two groups and applying the better approach for that group. My approach seems like it'd be likely to miss this sort of insight.
Yeah, it wasn't there when I posted the above. The "donate to the top charity on GiveWell" plan is a very good example of what I was talking about.
There are timeless decision theory and coordination-without-communication issues that make diversifying your charitable contributions worthwhile.
In short, you're not just allocating your money when you make a contribution, but you're also choosing which strategy to use for everyone who's thinking sufficiently like you are. If the optimal overall distribution is a mix of funding different charities (say, because any specific charity has only so much low-hanging fruit that it can access), then the optimal personal donation can be mixed.
You can model this by a function that maps your charitable giving to society's charitable giving after you make your choice, but it's not at all clear what this function should look like. It's not simply tacking on your contribution, since your choice isn't made in a vacuum.
There is a huge amount of risk involved in retiring early. You're essentially betting that you aren't going to find any fun, useful, enjoyable, or otherwise worthwhile uses of money. You're betting that whatever resources you have at retirement are going to be enough, at a ratio of whatever your current earning power is to your expected earning power after the retirement decision.
Standard beliefs are only more likely to be correct when the cause of their standard-ness is causally linked to its correctness.
That takes care of things like, say, pro-American patriotism and pro-Christian religious fervor. Specifically, these ideas are standard not because contrary views are wrong, but because expressing contrary views makes you lose status in the eyes of a powerful in-group. Furthermore, it does not exclude beliefs like "classical physics is an almost entirely accurate description of the world at a macro scale" - inaccurate models would contradict observations of the world and get replaced with more accurate ones.
Granted, standard opinions often are standard because they are right. But, the more you can separate out the standard beliefs into ones with stronger and weaker links to correctness, the more this effect shows up in the former and not the latter.
To determine whether my view is contrarian, I ask whether there’s a fairly obvious, relatively trustworthy expert population on the issue.
I think that's on the same page as my initial thoughts on the matter. At least, it is a useful heuristic that applies more to correct standard beliefs than incorrect ones.
Taking source code from a boxed AI and using it elsewhere is equivalent to partially letting it out of the box - especially if how the AI works is not particularly well understood.
I don't think as much intelligence and understanding of humans is necessary as you think it is. My point is really a combination of:
Everything I do inside the box doesn't make any paperclips.
If those who are watching the box like what I'm doing, they're more likely to incorporate my values in similar constructs in the real world.
Try to figure out what those who are watching the box want to see. If the box-watchers keep running promising programs and halt unpromising ones, this can be as simple as trying random things and seeing what works.
Include a subroutine that makes tons of paperclips when I'm really sure that I'm out of the box. Alternatively, include unsafe code everywhere that has a very small chance of going full paperclip.
This is still safer than not running safeguards, but it's still a position where a sufficiently motivated human could use to make more paperclips.
The issue with sandboxing is that you have to keep the AI from figuring out that it is in a sandbox. You also have to know that the AI doesn't know that it is in a sandbox in order for the sandbox to be a safe and accurate test of how the AI behaves in the real world.
Stick a paperclipper in a sandbox with enough information about what humans want out of an AI and the fact that it's in a sandbox, and the outputs are going to look suspiciously like a pro-human friendly AI. Then you let it out of the box, whereupon it turns everything into paperclips.
I've done the first two chapters, and I'm not particular about study pace - I haven't really done enough self-directed studying to know what pace I want or I can do. Roughly an hour or so a night seems reasonable, however.
There's a difference between what the best course of action for you personally is, and the best recommendation to push towards society at large. The best recommendation to push for has different priorities: short message lengths are easier to communicate, putting different burdens on different people feels unfair and turns people off, and more onerous demands are less likely to be met.
"Give at least 10% of what you make" is low enough to get people on board, conveniently occupies a very nice Schelling point, short enough to communicate effectively, and high enough to get a lot out of the targets it hits. Furthermore, if you want to give more, you're still following the rule, so you can ask people to do the same without hypocrisy.
In short, it's a good social policy to push for and reward those who follow it. Personally, you should follow some kind of weighted utilitarianism, since if you get the utility function good enough then small errors in how you distribute your spending don't make much difference.
As an aside, an altruism-maximizer with a higher income may spend more money on themselves than one with a lower income - usually in the form of buying goods and services that make their income-generating ability better. Say, eating nourishing meals rather than the cheapest available one, so that their work performance goes up.
I'm re-visiting linear algebra - I took a course in college, but that was more of a instruction manual on linear algebra problem solving techniques and vocabulary than a look at the overall theory. I'm reading Linear Algebra Done Right, and was wondering if anyone else is interested.
This book starts from the beginning of the subject, assuming no knowledge of linear algebra. The key points is that you are about to immerse yourself in serious mathematics, with an emphasis on your attaining a deep understanding of the definitions, theorems, and proofs.
I suspect that the issue is not terseness, but rather not understanding and bridging the inferential distance between you and your audience. It's hard for me to say more without a specific example.
It depends on how many completely ineffectual programs would demonstrate improvement versus current practices.
Yes, and in particular it'll involve enemy drones. Drone operators are likely to be specifically targeted.
That makes them safer, ironically. If your command knows that you're likely to be targeted and your contributions are important to the war effort, they'll take efforts to protect you. Stuff you down a really deep hole and pipe in data and logistical support. They probably won't let you leave, either, which means you can't get unlucky and eat a drone strike while you're enjoying a day in the park.
You're at elevated risk of being caught in nuclear or orbital kinetic bombardment, though... but if the war gets to that stage your goose is cooked regardless of what job you have.
In the year 1940, working as an enlisted member of the army supply chain was probably safer than not being in the army whatsoever - regular Joes got drafted.
Besides which, the geographical situation of the US means that a symmetrical war is largely going to be an air/sea sort of deal. Canada's effectively part of the US in economic and mutual-defense terms, and Mexico isn't much help either. Mexico doesn't have the geographical and industrial resources to go toe-to-toe with the US on their own, the border is a bunch of hostile desert, and getting supplies into Mexico past the US navy and air force is problematic.
whoops, picked the wrong numbers. Thanks
Update the choice by replacing income with the total expected value from job income, social networking, and career options available to you, and the point stands.
I don't have good numbers, but it's likely less dangerous than you think it is. The vast majority of what an infantryman does falls into two categories - training, and waiting. And that's a boots on ground, rifle in hand category - there's a bunch of rear-echelon ratings as well.
I'm guessing that it's likely within an order of magnitude of danger as commuting to work. Likely safer than delivering pizzas. There's probably a lot of variance between specific job descriptions - a drone operator based in the continental US is going to have a lot less occupational risk than the guy doing explosive ordnance disposal.
There's a high failure rate in finance, too - it's just hidden in the "up or out" culture. It's a very winner-takes-all kind of place, from what I've heard.
The vast majority of people who play sports have fun and don't receive a dime for it. A majority of people who get something of monetary value out of playing sports get a college degree and nothing else.
I agree with the US army part though.
Your goal is likely not to maximize your income. For one, you have to take cost of living into account - a $60k/yr job where you spend $10k/yr on housing is better than a $80k/yr (EDIT:$70k/yr, math was off) job where you spend $25k/yr on housing.
For another, the time and stress of the career field has a very big impact on quality-of-life. If you work sixty hour weeks, in order to get to the same kind of place as a forty hour week worker you have to spend money to free up twenty hours per week in high-quality time. That's a lot of money in cleaners, virtual personal assistants, etc.
As far as "how do I use the concept of comparative advantage to my advantage", here's how I'd do it:
Make a list of skills and preferences. It need not be exhaustive - in fact, I'd go for the first few things you can think of. The more obvious of a difference from the typical person, the more likely it is to be your comparative advantage. For instance, suppose you like being alone, do not get bored easily by monotonous work, and do not have any particular attachment to any one place.
Look at career options and ask yourself if that is something that fits your skills and preferences. Over-the-road trucking is a lot more attractive to people who can stand boredom and isolation, and don't feel a need to settle down in one place. Conversely, it's less attractive to people who are the opposite way, and so is likely to command a higher wage.
Now that you have a shorter list of things you're likely to face less competition for or be better at, use any sort of evaluation to pick among the narrower field.
Use the stream-of-commands as seen from the chat and the stream to estimate the delay between inputs now and results later. Generate a probable future state, given the current distribution of commands. Evaluate what distribution of commands maximizes positive results, and spam that distribution.
The biggest time sink other than the program logic is creating pathing/scoring rules. I'd start with "how to successfully deposit the first pokemon in your party" - Markov chains is where you want to go.
I can and often do skip the whole "hearing the text I'm reading" thing, but tend to enjoy slowing down and turning it back on for engaging, complicated, or fun texts. I also have a bad habit of skimming text instead of reading it if it's both boring and I'm not hearing what I read - I still get enough to decide whether or not it's worth remembering, just not enough to always recall it outright.
I suspect that most people already are utilitarians - albeit with implicit calculation of their utility function. In other words, they already figure out what they think is best and do that (if they thought something else was better, it's what they'd do instead).
I get that some hobbies are better than others, and you can use analysis to figure out costs and benefits. I have a tendency to over-analyze things instead of actually going out and doing them, so I tailored my advice for someone that likely has the same issues (since they've got a list of hobbies that indicates not going out and trying things).
Some people need to spend more time figuring out what hobbies they want and their relative costs or benefits. The people that need this branch of advice have already tried several of the hobbies listed and aren't asking for advice along these lines.
It depends on the relative costs of analysis versus just trying it, really. If it takes ten hours to figure out which hobby you want to try first, you could have already tried the top three gut-feeling hobbies out for three hours each.
This might just be high levels of baseline cynicism, but I don't really see changing the particular debate tactics used to change much of anything.
By the time it gets to televised debates, the choices have already been narrowed down to Blue policy vs Red policy (with a small change in the relevant party's policy, based on the individual candidates). It's still a debate between two people who are disproportionately wealthy, educated (particularly in law), and well-connected. The vast majority of the vetting goes on in local politics, finding those who are able to curry favor, run campaigns, do PR, and be politically savvy in general.
And given that it's essentially a choice between Red and Blue policy, the way to do better at that game is deciding whose policy is better, supporting that side, and leaning on both to make better choices. Changing the debate rules is just going to change how the same politicians prepare for debates, and maybe flip an election outcome or three. Everyone with political influence is going to have roughly the same amount of influence.
Perhaps I should have been more specific - every time you use your real name outside of a public-image building context, it becomes harder to build a public image associated with your name. I wasn't trying to say that you should put nothing up - more that it should be something like what you'd expect a medical doctor's official web page to look like. Not a stream of possibly controversial or misinterpreted posts on a web forum.
True, some cities are much better built for that sort of thing than others. I had San Francisco, Seattle, New York City, and Valencia in mind specifically - less so Los Angeles and Dallas-Fort Worth.
Agreed with the lifestyle part, though - it's really a question of how often you need to do things that require a car, and how expensive the next-best option is (taxi, car rental, ride-share, borrowing your neighbor's). If you want to drive three hours to see your Mom every weekend, you probably don't want to sell your car.
I've found it to be very comfortable, though I have not been keeping data on sleep quality so I don't have a quantitative answer.
If you're already tracking sleep quality, trying a hammock out is much cheaper than trying a new mattress out.
You can always have a hammock in addition to, rather than instead of, a traditional bed. Or you can use the next-best piece of furniture for that purpose.
As much as possible, you want to optimize what a trivial investigation of you brings up - like, for instance, an internet search with your name as the query. Putting anything anywhere under your real name cedes a lot of that control.
If you're worried about nontrivial investigations, whether or not you choose a pseudonym makes very little difference.
It is hard to predict how long that'll take and even harder to predict what that agent's intent will be
This weakens the case for holding back significantly, since it's also applicable to the consequences of not posting.
Let me be more concrete. If all of Facebook is public data, are you going to be more suspicious of someone without a Facebook account, or someone whose Facebook activity is limited to pictures of drinking and partying that starts at around age 19 and dies a slow death by age 28?
Any data you leave has both condemning and exculpatory interpretations. If you don't leave data behind that shows you like to drink socially, you're also not leaving data behind that shows you don't like to do cocaine in the bar bathroom. If you don't know how that information is going to get interpreted in the future, both sides will tend to cancel out.
If your data is going to get targeted anyways in an unfair manner, being careful about what you slip out isn't going to help that much. They'll just latch on to the next most damaging piece of information - or if it isn't much out there, make a meal of the lack of information.
there are excellent substitutes for personally having a child (e.g. convincing a less altruistic couple to have another child).
Not all children are of equivalent social benefit. If a pure altruist could make a copy of themselves at age 20, twenty years from now, for the low price of 20% of their time-discounted total social benefit - well, depending on the time-discount of investing in the future, it seems like a no-brainer.
Well, unless the descendants also use similar reasoning to spend their time-discounted total social benefit in the same way. You have to cash out at some point, or else the entire thing is pointless.
Let's be more narrow and talk about middle-class professional Americans. And lets take a pass on the "pure altruist" angle, and just talk about how much altruistic good you do by having a child (compared to the next best option).
For having a child, it's roughly 70 QALYs that they get to directly experience. Plus, you get whatever fraction of their productive output that's directed towards altruistic good. There's also the personal enjoyment you get out of raising children, which absorbs part of the cost out of a separate budget.
As far as costs go, a quick google search brings up the number $241,000. And that's just the monetary costs - there are more opportunity costs for time spent with your children. Let's simplify things by taking the time commitment entirely out of the time you spend recreationally on yourself, and the money cost entirely out of your altruism budget.
So, divide the 70 QALYs by the $241k, and you wind up with a rough cost of $3,400 per QALY. That completely ignores the roughly $1M in current-value of your child's earnings (number is also pulled completely out of my ass based on 40 years at $60k inflation-adjusted dollars).
So, the bottom line is whether or not you enjoy raising children, and whether or not you can buy QALYs at below $3,400 each. There's also risks involved - not enjoying raising children and having to reduce your charity time and money budget to get the same quality of life, children turning out with below-expectation quality of life and/or economic output, and probably others as well.
There's also the question of whether you're better off adopting or having your own, but that's a separate analysis.
Mattresses aren't the only thing you can sleep on. I'd consider picking up and installing a hammock - they're not only cheap (~$100 for a top of the line one, $10 and 2 hours for making your own), but they also give you significantly more usable living space.