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Funny that up until 2016 go was regarded as one of the most difficult games that computers could master, and now that it is solved it becomes a PR stunt? Would

by mda 9y ago

Funny that up until 2016 go was regarded as one of the most difficult games that computers could master, and now that it is solved it becomes a PR stunt? Would you claim the same in 2015?

dsacco 9y ago
Ah, just like mathematics. Once proved, a result is trivial, but before it’s proved, a conjecture is a hard problem.
lkozma 9y ago
Yes, I think von Neumann made this claim somewhere already that AI is a moving target, because once some task is automated it doesn't seem intelligent anymore.
GuB-42 9y ago
It was a hard problem, and that's what makes it an effective PR stunt. Google was working on machine learning for some practical application like image classification, better targeted ads or whatever thing Google does. A bunch of people then came up with the idea: "hey, we have all that AI stuff, we may be able to use it for computer go". And Google replied with "OK, sounds like good publicity, here is a budget, we also have a bunch of servers and if you need help, feel free to ask our machine learning department". It is like making an industrial robot that can crush concrete blocks or whatever difficult but not that useful task. Maybe it is a huge deal because all previous attempts failed, but the point here is not that years of research in concrete crushing robots have payed out, but rather that recent advancement in practical engineering made it possible, and maybe even easy.
- fjsolwmv 9y ago
  That's not true though. Google bought a company whose main product was a Go machine, on the idea that potentially those smart people could do useful work also. Or just as PR cover for their unrelated AI work.
- deleted 9y ago
  [deleted]
marcosdumay 9y ago
Any game is a PR stunt, difficulty does not matter. It's not about how hard it is to solve, but on how many places you can apply them.
eli_gottlieb 9y ago
The problem with the AI Effect is that people keep expecting solving one toy problem or another to give us some insight into how to break Moravec's paradox for the general case. Statistical learning, especially deep learning, have been massive advances precisely because they at least allow us to break the paradox for specific problems, where we happen to have large datasets.
argonaut 9y ago
This is one of those catchy but actually unverified memes that gets endlessly propagated. "Nevertheless, I believe that a world-champion-level Go machine can be built within 10 years" - Feng-Hsiung Hsu, 2007 (researcher who worked on Deep Blue). https://spectrum.ieee.org/computing/software/cracking-go https://spectrum.ieee.org/computing/software/cracking-go

by mda 9y ago

Funny that up until 2016 go was regarded as one of the most difficult games that computers could master, and now that it is solved it becomes a PR stunt? Would you claim the same in 2015?

dsacco 9y ago

Ah, just like mathematics. Once proved, a result is trivial, but before it’s proved, a conjecture is a hard problem.

lkozma 9y ago

Yes, I think von Neumann made this claim somewhere already that AI is a moving target, because once some task is automated it doesn't seem intelligent anymore.

GuB-42 9y ago

It was a hard problem, and that's what makes it an effective PR stunt. Google was working on machine learning for some practical application like image classification, better targeted ads or whatever thing Google does. A bunch of people then came up with the idea: "hey, we have all that AI stuff, we may be able to use it for computer go". And Google replied with "OK, sounds like good publicity, here is a budget, we also have a bunch of servers and if you need help, feel free to ask our machine learning department". It is like making an industrial robot that can crush concrete blocks or whatever difficult but not that useful task. Maybe it is a huge deal because all previous attempts failed, but the point here is not that years of research in concrete crushing robots have payed out, but rather that recent advancement in practical engineering made it possible, and maybe even easy.

fjsolwmv 9y ago
That's not true though. Google bought a company whose main product was a Go machine, on the idea that potentially those smart people could do useful work also. Or just as PR cover for their unrelated AI work.
deleted 9y ago
[deleted]

marcosdumay 9y ago

Any game is a PR stunt, difficulty does not matter. It's not about how hard it is to solve, but on how many places you can apply them.

eli_gottlieb 9y ago

The problem with the AI Effect is that people keep expecting solving one toy problem or another to give us some insight into how to break Moravec's paradox for the general case. Statistical learning, especially deep learning, have been massive advances precisely because they at least allow us to break the paradox for specific problems, where we happen to have large datasets.

argonaut 9y ago

This is one of those catchy but actually unverified memes that gets endlessly propagated. "Nevertheless, I believe that a world-champion-level Go machine can be built within 10 years" - Feng-Hsiung Hsu, 2007 (researcher who worked on Deep Blue). https://spectrum.ieee.org/computing/software/cracking-go https://spectrum.ieee.org/computing/software/cracking-go