Here is something I’d like to see: You give the machine the formally specified ruleset of a game (go, chess, etc), wait while the reinforcement learning does its job, and out comes a world-class computer player.
DanielVarga
Here is one reason, but it’s up for debate:
Deep learning courses rush through logistic regression and usually just mention SVMs. Arguably it’s important for understanding deep learning to take the time to really, deeply understand how these linear models work, both theoretically and practically, both on synthetic data and on high dimensional real life data.
More generally, there are a lot of machine learning concepts that deep learning courses don’t have enough time to introduce properly, so they just mention them, and you might get a mistaken impression about their relative importance.
Another related thing: right now machine learning competitions are dominated by gradient boosting. Deep learning, not really. This says nothing about starting with deep learning or not, but a good argument against stopping at deep learning.
In the last two days I alone wrote a prototype that can take a whiteboard photo, and automatically turn it into a mindmap-like zoomable chart. Pieces of the chart then can be rearranged and altered individually:
https://prezi.com/igaywhvnam2y/whiteboard-prezi-2015-12-04-152935/
This was part of a company hackathon, and I had some infrastructure to help me regarding the visualization, but with the shape recognition/extraction, it was just me and the nasty python bindings for OpenCV.
Oh my god, look at 0-4-year old assaults, both ED visits and deaths. (Assault is the leading TBI-related cause of death for 0-4-year olds.) Some of those falling 4 year olds were assaulted.
There are worse fates than not being able to top your own discovery of general relativity.
That’s not a top-level comment, so it’s excluded by my script from this version. I won’t manually edit the output, sorry. There’s another version where non-top-level comments are kept, too. Your quote is in there:
Top quote contributors by statistical significance level:
0.00000 (23.11 in 45): Alejandro1
0.00007 (17.98 in 63): James_Miller
0.00016 (19.02 in 43): Stabilizer
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0.00020 (18.69 in 45): GabrielDuquette
0.00052 (26.91 in 11): Oscar_Cunningham
0.00142 (24.33 in 12): peter_hurford
0.00183 (50.50 in 2): Delta
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0.00290 (19.35 in 23): Yvain
0.00352 (66.00 in 1): westward
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0.00591 (41.00 in 2): VincentYu
0.00604 (60.00 in 1): RomeoStevens
0.00719 (24.00 in 8): philh
0.00725 (19.28 in 18): Tesseract
0.00780 (57.00 in 1): Zando
0.00820 (39.00 in 2): sediment
0.00830 (23.62 in 8): Qiaochu_Yuan
0.00871 (23.50 in 8): Maniakes
0.00993 (32.00 in 3): benelliott
0.01012 (15.17 in 64): Jayson_Virissimo
0.01226 (26.00 in 5): Ezekiel
0.01359 (49.00 in 1): Liron
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0.01711 (45.00 in 1): Mycroft65536
0.01816 (34.00 in 2): summerstay
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369 James_Miller
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181 Stabilizer
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117 Kaj_Sotala
117 B_For_Bandana
116 NancyLebovitz
110 Pablo_Stafforini
107 Gunnar_Zarncke
100 Eugine_Nier
97 aarongertler
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90 Azathoth123
88 EGarrett
84 elharo
81 Benito
79 Torello
74 MattG
74 AspiringRationalist
73 satt
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73 27chaos
67 Tyrrell_McAllister
66 Vulture
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52 Vaniver
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1394 RichardKennaway
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1037 [deleted]
978 gwern
971 Jayson_Virissimo
847 lukeprog
846 Eugine_Nier
841 GabrielDuquette
827 Eliezer_Yudkowsky
818 Stabilizer
775 Rain
750 MichaelGR
734 NancyLebovitz
628 Konkvistador
590 anonym
521 CronoDAS
479 arundelo
445 Yvain
434 RobinZ
431 Kaj_Sotala
404 dspeyer
372 Alicorn
357 Grognor
353 Vaniver
347 Tesseract
332 shminux
328 DSimon
296 Oscar_Cunningham
296 billswift
293 Pablo_Stafforini
292 peter_hurford
284 Nominull
277 jsbennett86
271 katydee
263 RolfAndreassen
262 Thomas
237 Kutta
229 roland
224 Cyan
Top original authors by karma collected:
894 Graham
603 Russell
534 Pratchett
489 Chesterton
475 Feynman
372 Dennett
343 Franklin
340 Munroe
306 Aaronson
294 Newton
282 Einstein
279 Nietzsche
270 Pinker
262 Friedman
252 Shaw
249 Egan
240 Bacon
239 Stephenson
236 Aristotle
235 Taleb
228 Heinlein
209 Kahneman
201 Silver
196 McArdle
187 Sagan
184 Voltaire
183 Wilson
183 Darwin
182 Plato
177 SMBC
173 Buffett
171 Milton
165 Mencken
162 Moldbug
160 Wittgenstein
160 Johnson
160 Hofstadter
158 Asimov
156 Dawkins
154 Winston
147 Godin
145 Marcus
141 Wong
140 Confucius
136 Descartes
133 Brandon
130 Orwell
129 Nielsen
127 Hayden
127 Georg
123 Minsky
123 Maynard
123 Bakker
121 Sowell
121 Razib
119 Hanson
117 Kaas
117 Churchill
116 Vulcan
112 Obama
111 Jaynes
107 Keynes
106 Tao
106 Hume
102 Greene
102 Deutsch
101 Saul
100 Screwtape
98 Lessing
98 Christoph
98 Botton
97 Watson
97 Carroll
96 Rollins
96 Marx
96 Kurt
96 Isn
96 Harris
96 Bostrom
94 Santa
94 Morris
93 Shera
93 Neumann
93 Holmes
93 Gawande
93 Dann
92 Vonnegut
92 Locke
92 Futurama
91 Adamek
90 Hoffer
Top original authors by number of quotes. (Note that authors and mentions are not disambiguated.)
Graham 47
Feynman 47
Russell 40
Taleb 39
Chesterton 37
Pratchett 35
Einstein 30
Dennett 29
Nietzsche 26
Aaronson 23
Heinlein 22
Johnson 21
Bacon 21
Shaw 19
Newton 19
Franklin 19
Wilson 18
Darwin 18
Kahneman 17
Wittgenstein 15
Munroe 15
Dawkins 15
Stephenson 14
Sowell 14
Silver 14
Pinker 14
Meier 14
Asimov 14
Aristotle 14
Sagan 13
Moldbug 13
Eliezer 13
Churchill 13
Voltaire 12
Minsky 12
Mencken 12
Maynard 12
Locke 12
Egan 12
Clark 12
SMBC 11
Plato 11
Orwell 11
Neumann 11
Marx 11
Holmes 11
Hofstadter 11
Hoffer 11
Descartes 11
Buffett 11
Aurelius 11
Turing 10
Screwtape 10
Peirce 10
Keynes 10
Jaynes 10
Hume 10
Harris 10
Gould 10
Friedman 10
Bakker 10
Schopenhauer 9
Huxley 9
Goethe 9
Deutsch 9
Wilde 8
Thoreau 8
Morgan 8
Montaigne 8
Leibniz 8
Greene 8
Godin 8
Crowley 8
Carroll 8
Brandon 8
Yudkowsky 7
Wong 7
Wolfgang 7
Vinci 7
Szabo 7
Munger 7
Mitchell 7
Medawar 7
McArdle 7
Lannister 7
Kant 7
Jefferson 7
Hobbes 7
Hanson 7
Diogenes 7
Dijkstra 7
Confucius 7
Carlyle 7
Calvin 7
Top short quotes (2009-2014) by karma per character:
60 A Bet is a Tax on BullshitAlex Tabarrok
45 Luck is statistics taken personally.Penn Jillette
35 Comic Quote Minus 37-- Ryan ArmandAlso a favourite.
42 I’ve got to start listening to those quiet, nagging doubts.Calvin
34 Nobody is smart enough to be wrong all the time.Ken Wilber
51 I will not procrastinate regarding any ritual granting immortality.--Evil Overlord List #230
34 A problem well stated is a problem half solved.Charles Kettering
26 “I accidentally changed my mind.”my four-year-old
27 “Most haystacks do not even have a needle.”—Lorenzo
50 He uses statistics as a drunkard uses a lamppost: for support, not for illumination.G.K. Chesterton
29 The greatest weariness comes from work not done.-Eric Hoffer
31 Doubt is not a pleasant condition, but certainty is absurd.Voltaire
32 If it’s stupid and it works, it’s not stupid.”Murphy’s Laws of Combat”
41 The Noah principle: predicting rain doesn’t count, building arks does.-Warren E. Buffett
41 Shipping is a feature. A really important feature. Your product must have it.-Joel Spolsky
25 What goes unsaid eventually goes unthought.Steve Sailer
40 People say “think outside the box,” as if the box wasn’t a fucking great idea.Sean Thomason
27 Procrastination is the thief of compound interest.-Venkatesh Rao
21 “A problem well put, is half solved.”—John Dewey
38 A raise is only a raise for thirty days; after that, it’s just your salary.-- David Russo
37 It’s easy to lie with statistics, but it’s easier to lie without them.-Fred Mosteller
32 If one does not know to which port one is sailing, no wind is favorable.-Seneca
25 The most practical thing in the world is a good theory.Helmholtz
35 It is the mark of a truly intelligent person to be moved by statistics.George Bernard Shaw
30 When the facts change, I change my mind. What do you do, sir?John Maynard Keynes
27 Part of the potential of things is how they break.Vi Hart, How To Snakes
32 Precise forecasts masquerade as accurate ones.-- Nate Silver, The Signal and the Noise
29 Writing program code is a good way of debugging your thinking.-- Bill Venables
15 Focusing is about saying no.-- Steve Jobs
34 “Working in mysterious ways” is the greatest euphemism for failure ever devised.TheTweetOfGod
35 However beautiful the strategy, you should occasionally look at the results.-- Winston Churchill
29 “Any sufficiently analyzed magic is indistinguishable from SCIENCE!”~Girl Genius
32 There is one rule that’s very simple, but not easy: observe reality and adjust.Ran Prieur
32 The Company that needs a new machine tool is already paying for it.-old Warner Swasey ad
34 Market exchange is a pathetically inadequate substitute for love, but it scales better.S. T. Rev
22 Things are only impossible until they’re not.-- Jean-Luc Picard
30 Truth is much too complicated to allow anything but approximations.— John Von Neumann
26 A scholar is just a library’s way of making another library.Daniel Dennett
30 “Erudition can produce foliage without bearing fruit.”—Georg Christoph Lichtenberg
27 Complex problems have simple, easy to understand wrong answers.— Grossman’s Law
25 The truth will set you free. But first, it will piss you off.Gloria Steinem
31 It’s a horrible feeling when you don’t understand why you did something.-- Dennis Monokroussos
29 We should be careful to get out of an experience only the wisdom that is in it.Mark Twain
27 It is easy to be certain....One has only to be sufficiently vague.Charles S. Peirce
26 Shouldn’t “it works like a charm” be said about things that don’t work?Jason Roy
12 Reality is not optional.Thomas Sowell
11 Death is the gods’ crime.Unsounded
25 Go down deep enough into anything and you will find mathematics.Dean Schlicter
23 It is better to destroy one’s own errors than those of others.Democritus
22 Most people would rather die than think; many do.– Bertrand Russell
28 Nature draws no line between living and nonliving.-- K. Eric Drexler, Engines of Creation
30 Now, now, perfectly symmetrical violence never solved anything.--Professor Farnsworth, Futurama.
26 The dream is damned and dreamer too if dreaming’s all that dreamers do.--Rory Miller
17 Statistics is applied philosophy of science.A. P. Dawid
19 Luck is opportunity plus preparation plus luck.--Jane Espenson
28 Nobody panics when things go “according to plan”… even if the plan is horrifying.The Joker
19 Being right too soon is socially unacceptable.Robert A. Heinlein
18 A sharp knife is nothing without a sharp eye.Klingon proverb.
25 We are built to be effective animals, not happy ones.-Robert Wright, The Moral Animal
27 Train your tongue to say “I don’t know”, lest you be brought to falsehood -Babylonian Talmud
22 The only road to doing good shows, is doing bad shows.Louis C.K., on Reddit
17 Nothing is so obvious that it’s obvious.— Errol Morris
20 Everybody has a plan until they get punched in the mouth.--Mike Tyson
22 Forget Jesus. The stars died so that you could be here today.Lawrence Krauss
28 My brain technically-not-a-lies to me far more than it actually lies to me.-- Aristosophy (again)
26 “Anything left on your bucket list?”“Not dying...”-Bill Gates in his AMA on reddit.
20 Better our hypotheses die for our errors than ourselves.-- Karl Popper
27 If knowledge can create problems, it is not through ignorance we can solve them.-- Isaac Asimov
23 “Convictions are more dangerous enemies of truth than lies.”—Friedrich Nietzsche
26 A man who says he is willing to meet you halfway is usually a poor judge of distance.Unknown
20 I honestly don’t know. Let’s see what happens.-- Hans. The Troll Hunter
26 Truth would quickly cease to be stranger than fiction, once we got as used to it.H.L. Mencken
27 The first rule of human club is you don’t explicitly discuss the rules of human club.Silas Dogood
18 Good things come to those who steal them.-- Magnificent Sasquatch
14 “Anything you can do, I can do meta” -Rudolf Carnap
17 Mind is a machine for jumping to conclusions—Daniel Kahneman
20 The singularity is my retirement plan.-- tocomment, in a Hacker News post
26 If Tetris has taught me anything it’s that errors pile up and accomplishments disappear.-Unknown
26 A faith which cannot survive collision with the truth is not worth many regrets.Arthur C. Clarke
21 Know the hair you have to get the hair you want.-Pantene Pro-V hair care bottle
14 I intend to live forever or die trying—Groucho Marx
26 We shall not grow wiser before we learn that much that we have done was very foolish.-- F. A. Hayek
22 Those who can make you believe absurdities can make you commit atrocities.-- Voltaire
19 In general, we are least aware of what our minds do best.— Marvin Minsky
19 He who knows only his own side of the case, knows little of that.J.S. Mill
25 A man who has committed a mistake and doesn’t correct it, is committing another mistake.-Confucius
20 No matter how far you’ve gone down the wrong road, turn back.-- Turkish proverb
25 If you were taught that elves caused rain, every time it rained, you’d see the proof of elves.Ariex
16 Keep your solutions close, and your problems closer.afoolswisdom
15 History doesn’t repeat itself, but it does rhyme.-Mark Twain
11 Whenever you can, count.--Sir Francis Galton
19 God created the Earth, but the Dutch created the Netherlands.-- Dutch proverb
Nice. If we analyze the game using Vitalik’s 2x2 payoff matrix, defection is a dominant strategy. But now I see that’s not how game theorists would use this phrase. They would work with the full 99-dimensional matrix, and there defection is not a dominant strategy, because as you say, it’s a bad strategy if we know that 49 other people are cooperating, and 49 other people are defecting.
There’s a sleight of hands going on in Vitalik’s analysis, and it is located at the phrase “regardless of one’s epistemic beliefs [one is better off defecting]”. If my epistemic belief is that 49 other people are cooperating, and 49 other people are defecting, then it’s not true that defection is my best strategy. Of course, Vitalik’s 2x2 matrix just does not allow me to have such refined epistemic beliefs: I have to get by with “attack succeeds” versus “attack fails”.
Which kind of makes sense, because it’s true that I probably won’t find myself in a situation where I know for sure that 49 other people are cooperating, and 49 other people are defecting, so the correct game theoretic definition of dominant strategy is probably less relevant here than something like Vitalik’s “aggregate” version. Still, there are assumptions here that are not clear from the original analysis.
I don’t know too much about decision theory, but I was thinking about it a bit more, and for me, the end result so far was that “dominant strategy” is just a flawed concept.
If the agents behave superrationally, they do not care about the dominant strategy, and they are safe from this attack. And the “super” in superrational is pretty misleading, because it suggests some extra-human capabilities, but in this particular case it is so easy to see through the whole ruse, one has to be pretty dumb not to behave superrationally. (That is, not to consider the fact that other agents will have to go though the same analysis as ourselves.)
Superrationality works best when we actually know that the others have the same input-output function as ourselves, for example when we know that we are clones or software copies of each others. But real life is not like that, and now I believe that the clean mathematical formulation of such dilemmas (with payoff matrices and all that) is misleading, because it sweeps under the rug another, very fuzzy, hard to formalize input variable: the things that we know about the reasoning processes of the other agents. (In the particular case of the P+epsilon attack, we don’t have to assume too much about the other agents. In general, we do.)
They’re running on the blockchain, which slows them down.
They can follow the advice of any off-the-blockchain computational process if that is to their advantage. They can even audit this advice, so that they don’t lose their autonomy. For example, Probabilistically Checkable Proofs are exactly for that setup: when a slow system has to cooperate with an untrusted but faster other. There’s the obvious NP case, when the answer by Merlin (the AI) can be easily verified by Arthur (the blockchain). But the classic IP=PSPACE result says that this kind of cooperation can work in much more general cases.
The primary decision-making mechanisms for them are going to basically be the same as can be used for existing organizations, like democracy, prediction markets, etc.
These are just the typical use cases proposed today. In principle, their decision-making mechanism can be anything whatsoever, and we can expect that there will be many of them competing for resources.
The thing that I think makes them interesting from a FAI perspective is the “autonomous” part. They can buy and sell and build stuff. They have agency, they can be very intelligent, and they are not human.
...Okay, that sounded a bit too sensationalist, so let me clarify. Personally, I am much more optimistic regarding UFAI issues than MIRI or median LW. I don’t actually argue that DAOs are dangerous. What I argue is that if someone is interested in how very smart, autonomous computational processes could arise in the future, this possible path might be worth investigating a bit.
An advanced DAO (decentralized/distributed autonomous organization), the way Vitalik images it, is a pretty believable candidate for an uncontrolled seed AI, so I’m not sure Eliezer and co shares Vitalik’s apparent enthusiasm regarding the convergence of these two sets of ideas.
I was unsurprised but very disappointed when it turned out there are no other posts tagged one_mans_vicious_circle_is_another_mans_successive_approximation. But Shalizi has already used the joke once in his lecture notes on Expectation Maximization.
Tononi gives a very interesting (weird?) reply: Why Scott should stare at a blank wall and reconsider (or, the conscious grid), where he accepts the very unintuitive conclusion that an empty square grid is conscious according to his theory. (Scott’s phrasing: “[Tononi] doesn’t “bite the bullet” so much as devour a bullet hoagie with mustard.”) Here is Scott’s reply to the reply:
I have no problem with an arbitrary border. I wouldn’t even have a problem with, for example, old people gradually shrinking in size to zero just to make the image more aesthetically pleasing.
I think I misunderstand your definition. Let feature a be represented by x_1 > 0.5, and let feature b be represented by x_2 > 0.5. Let x_i be iid uniform [0, 1]. Isn’t that a counterexample to (a and b) being linearly representable?