381–390 of 428 posts
Earlier quoted context omitted.
That would be amazing if it could achieve the same levels (or higher) without the bootstrapping. The niggling thought in my mind was that AlphaGo's strength is built on human strength.
I suspect you will only be satisfied when AIs play each other at an incomprehensible game of their own devising.
My (long) commentary here: https://www.facebook.com/yudkowsky/posts/10154018209759228 Sample: At this point it seems likely that Sedol is actually far outclassed by a superhuman player. The suspicion is that since AlphaGo plays purely for probability of long-term victory rather than playing for points, the fight against Sedol generates boards that can falsely appear to a human to be balanced even as Sedol's probabili…
The problem with 'flag and footprints' demonstrations is precisely the same as their attraction - they are, in essence (even though that was not the intent), selected to be as misleading as possible about progress in solving the real problems. We put a man on the moon, which encouraged decades of optimism about the near-future colonization of space... unfortunately it turns out we are nowhere near solving the hard pr…
We put a man on the moon in 1969, and we are just now getting privately-funded spaceflight and satellites. We made the first computers in 1945; we got them on every desk in the 1980s. The first steamboat was built in 1783; the transatlantic shipping industry didn't transition to steam until the 1840s & 1850s.
Probably some kid who's watching AlphaGo's game today is the person who, late in life, invents the first strong AI.
Earlier quoted context omitted.
A case of life imitating AI koans: Uncarved block In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6. "What are you doing?", asked Minsky. "I am training a randomly wired neural net to play Tic-tac-toe", Sussman replied. "Why is the net wired randomly?", asked Minsky. "I do not want it to have any preconceptions of how to play", Sussman said. Minsky then shut his eyes. "Why…
It sounds like the point of this story is to illustrate by analogy that starting from first principles is sometimes a silly way to approach a problem, and by extrapolation that it's a silly way to make an AI that plays Go well. Making an AI that plays Go well is not (and has never been) the real goal. They're trying to learn how to build a AI that can solve any problem.
Earlier quoted context omitted.
Yeah, I think it's accurate to say that driving a car is harder in some sense than playing Go, based on the fact that the AI for Go came first. A lot of people have been working on self-driving cars for a long time now, and it's very monetizable, unlike Go.
Also, it should be noted that in Go, we're trying to beat the BEST human player, and have done so. In driving, we're just trying to be "good enough" or safe enough -- it doesn't have to be the safest driver in the world. Beating the average human Go player was probably accomplished decades ago, whereas it's not even clear if we're safer than the average human driver (under all conditions). These tasks are just wildly…
Earlier quoted context omitted.
I'm afraid I don't understand the point you're making with "computer says no". > Genetic algorithms have designed circuitry that we failed to even understand at first but that did work. This is an excellent example of what I think of as not machine intelligence. If humans can't understand it then it's something entirely different that we need a different word for - an "artefact", perhaps. Meaningfully contributing to…
https://en.wikipedia.org/wiki/Computer_says_no Savant literally means 'one who knows', and they're not required to explain to you how they know, it's up to you to verify that they do. Just like a chess grand master doesn't have to prove to you he or she is intelligent, it's enough that they beat you. They are under no obligation to prove their intelligence to you by teaching you the same (assuming you could follow in…
Though in all honesty, I think a lot of people just want to see a machine with emotional "instincts" and an understanding of tribal status-hierarchy dynamics such that you can empathize with it. A lot of people would consider a machine that accurately simulated a rather dumb chimpanzee to be "smart enough" to qualify as AI, even if it couldn't do any useful human intellectual labor.
We are indeed witnessing and living a historic moment. It is difficult not to feel awestruck. Likewise, it is difficult not to feel awestruck at how a wet 1.5 kg clump of carbon-based material (e.g. Lee Sedol brain) can achieve this level of mastery of a board game, that it takes such an insane amount of computing power to beat it. So, finally we do have a measure of the computing power required to play Go at the pro…
I don't think it is human prejudice, Deepmind can play Go and it cannot drive a car, Lee Sedol's brain can do both. Understanding the nature of cognition will open up new capabilities just as understanding the nature of genetics will open up new capabilities or understanding the nature of the cosmos Etc. What is most interesting for me is that the nature of solving the problem "how do I win at Go?" is one that has no…
Perhaps the last big question was whether AlphaGo could play ko positions. AlphaGo played quite well in that ko fight and furthermore, even played away from the ko fight allowing Lee Sedol to play twice in the area. I definitely did not expect that. Major credit to Lee Sedol for toughing that out and playing as long as he did. It was dramatic to watch as he played a bunch of his moves with only 1 or 2 seconds left on…
I think from a technological perspective there's very little question that AlphaGo could play ko. I would have imagined that AlphaGo would be better at ko than most human players since it's a question of balancing risk across the entire board. Human players might be more likely to be exhausted and choose suboptimally by the calculation deciding between different stakes on the board, but MCTS will correctly optimize f…
Earlier quoted context omitted.
One perfect-information game that's at least as hard: constructive mathematics. (Proof assistants even give it a sort of videogame-style UI.) I've been wondering about some kind of neural net for ranking the 'moves' coupled with the usual proof search.
I asked about this in /r/dependent_types yesterday. Apparently there's already a fair bit or research going on in this area. See the links: https://www.reddit.com/r/dependent_types/comments/49z1uc/usi...
Earlier quoted context omitted.
https://en.wikipedia.org/wiki/Computer_says_no Savant literally means 'one who knows', and they're not required to explain to you how they know, it's up to you to verify that they do. Just like a chess grand master doesn't have to prove to you he or she is intelligent, it's enough that they beat you. They are under no obligation to prove their intelligence to you by teaching you the same (assuming you could follow in…
I think you're indeed arguing a sensible definition of Artificial Intelligence , but it's not what most people (especially laymen) mean by the phrase. I think most actually equivocate AI with Artificial Sapience : some cognitive architecture that can—in theory, with the right training—do all the things humans do (socialize, write persuasive essays, create art, etc.) at least as well as the average human. Though in al…
Earlier quoted context omitted.
Computers will be able to compose symphonies very soon. If DeepMind started working on this problem, I am sure that they would succeed. At least, we would have some innovative mashups of Beethoven, Mozart and Tchaikovsky. But training a powerful AI on a massive dataset of all popular and classical music should produce some extraordinary results. Especially if the dataset was given as MIDI with separate instrument tra…
Composing an amazing symphony is probably about as hard as being the best go player in the world. But I think we're much further away than you think. AlphaGo needed a training set of perhaps a billion games to be as good as it is. The dataset of master Go games is perhaps a million games. So AlphaGo played at tons of games against a half-trained version of itself to reach the billion game mark. This doesn't work for…