You might be interested in the work of the artist Eva Hesse. She experimented with materials like latex and fiberglass to create sculptures that were almost organic, with skeletons and skin. These materials are decomposing quickly, and while I couldn't find a source for this online, I believe she was intentionally using industrial processes that led to more rapid chemical breakdown. So her creations are (not so) slowly dying, and some are already unable to be displayed publicly, only 60 years after they were made. Perhaps some are only still around because museum curators are "paying attention." But if they can't be put on display anyway, what's the point of the life-support? And is it against Hesse's artistic intentions?
I’m a big fan of Eva Hesse, but have never heard that she intentionally used the materials she did because of their limited shelf life, cutting short her works’ lifespan like her own.
It’s an interesting idea, however the cynic in me couldn’t help but notice that the domain you link to is for an end of life counseling organization. I wonder if their line of work makes them give this aspect of her work more significance than she would’ve during her lifetime.
If it's a shadowless first edition Charizard, I'll happily make you an offer. Collectors don't necessarily need the "complete set" just because the content creators continue to churn out new additions.
That quote would make sense if the quoted had say, isolated the medicinal properties of penicillin, but Vapnik invented Support Vector Machines which have solved generalized cases of classification but directly solved 0 problems (if you say something like running an OCR algo on documents whose purpose remain unamed that were: translated from human speech or thought, printed on paper, then scanned; is solving a problem directly I question your ability to speak of general and direct problem solving any further).
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After AlphaGo won the first three games, I wondered not if the computer had reached and surpassed human mastery, but instead how many orders of magnitude better it was. Given today's result, it may be only one order, or even less. Perhaps the best human players are relatively close to the maximum skill level for go, and that the pros of the future will not be categorically better than Lee Sedol is today.
Exactly what heuristics would they use to know how an omniscient being would play? Unless there are some strong arguments behind it, it sounds like arrogant BS.
Maybe they're extrapolating from relaxed instances that they've solved? If you know that humans can play pretty much optimally on, say, 11x11, and you know how much performance drops off with each expansion of the board?
Yudkowski argues that on the scale of intelligence, Einstein and a village idiot are basically right next to each other [1]. So once artificial intelligence gets close to matching the village idiot, it is not far from completely thrashing Einstein.
Now if that same picture held for Go, then a situation like this would seem to be impossible. Either the computer should be much worse than a human player, or much better. It would be an incredible coincidence that, at the end of six months of training, the computer happened to be of comparable skill to humans.
For the game of Go, at least, Yudkowski is wrong. What other aspects of intelligence are this way? Yudkowski's picture seems appealing, but perhaps it is wrong for many areas of intelligence.
AlphaGo is not an AI in the sense meant by Yudkowsky, I believe. He speaks more of a recursively self-improving AI, an AI which is capable of upgrading itself to be faster and more intelligent.
In the linked article, Yudkowsky even says "On the right side of the scale, you would find Deep Thought—Douglas Adams's original version, thank you, not the chessplayer." The implication is clear that these programs playing chess/Go are nothing like what he is talking about - general AI.
Or so I assume, from my less-than-complete understanding of Yudkowsky's writings.
Only if there's actual room to be much better. It's quite possible that 9p players are already pretty close to perfect play. Maybe a computer can get slightly closer still to that perfect play, but it's never going to be better than perfect play. There's not always room for improvement.
>> It would be an incredible coincidence that, at the end of six months of training, the computer happened to be of comparable skill to humans.
I don't think it's that incredible - By 18 years old a significant proportion of high school students know more about chemistry than the best scientists up to 1800 did, combined.
There's a lot of human games for AlphaGo to look at, but if it is to exceed human level of play, it'll have to figure how to do that by itself. Look at human level games, learn to play human level.
It's quick to get to the edge of human knowledge, and slower to go beyond it.
Yeah, I was waiting for AlphaGo to connect up 10 seemingly unrelated moves into some amazing unpredictable shape that wins the game. But now I think that maybe some humans actually have the ability to play a near-perfect game of Go. Maybe the most skilled human players have already nearly reached the peak of what is possible in a Go game.
The Telescope-esque UI is nicely done as well.