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Human Go Champion 'Speechless' After 2nd Loss To Machine (phys.org)
Reader chasm22 points to a Phys.org report about the second straight loss of Lee Sedol to AlphaGo, the program developed by Google's DeepMind unit. The human Go champion, Sedol found himself "speechless" after the showdown on Thursday. The human versus machine face-off lasted more than four hours, which to Sedol's credit is a slight improvement over his previous match, which had ended with him resigning nearly half an hour remaining on the clock.
"It was a clear loss on my part," Sedol said at a press conference on Thursday. "From the beginning there was no moment I thought I was leading." Demis Hassabis, who heads Google's DeepMind, said, "Because the number of possible Go board positions exceeds the number of atoms in the universe, top players rely heavily on their intuition."
Sedol will battle Google's AlphaGo again on Saturday, Sunday, and Tuesday.
I agree that this achievement by AlphaGo is extremely significant. However, I wonder if future experiments can focus more on the human vs. computer move selection algorithm comparison by minimizing tangential aspects. By tangential aspects, I'm referring to the other existing differences that perhaps reflect human failings more than strength of computation. In particular, I would like to see the removal of tournament rules because such rules were formulated to limit humans.
First, I would like to see time limits for moves eliminated. The computer can be augmented with extra hardware, higher clock frequencies, etc. to render time limits inconsequential for it, but the human cannot. As was seen in the 2nd match, time potentially impacted Mr. Lee by not only limiting his thinking time but more importantly by decreasing his emotional stability.
Second, I would like to see how the computer fares against a consensus of experts. By consensus, I'm imagining a group of 5-10 top players who discuss the best next move and then select the next move hopefully by consensus or at least by majority vote. Even the top players rarely maintain top play for every single move of a match. My hope is that a consensus of experts minimizes this human failing.
As a side note, I think that the setup for the human vs. computer experiment is extremely significant. As an example, the Watson triumph in Jeopardy was entirely expected but not very significant in terms of comparing human vs. computer thought. Rather, human buzzer pushing reflexes were compared against computer reflexes, and for that comparison, the computer should never lose. In Jeopardy, the buzzer impact is only minimized when one contestant knows more than the others. If all contestants know most of the answers, then the game devolves to a buzzer contest, which was the situation with Watson, Ken Jennings, and Brad Rutter. What would have been much more interesting would have been to allow Watson and the humans to each respond within a certain time window and to compare the percentage of correct responses without the impact of buzzers. Watson might have still won, but I would be shocked if the disparities were large. I.e., eliminate the tournament rules that are intended to impose artificial limits on humans that were crafted to maximize entertainment value and magnify the differences between actual skill.
Robots will be having debates on whether or not those pesky bald monkeys actually created them. They will be digging up old electronic waste and claiming that they evolved from the iPad and iPhone and the assembly line robots.
There will be debates about what to download to their children.
There will be the "Save the Humans" organizations to keep robots from indiscriminately killing the bald monkeys that inhabit their attics and basements. Human traps will be available at Robo*Mart.
And I have been watching waaaay too many Futurama episodes on Netflix. They took Doctor Who off! Bastards!
Li got slightly better against it; I'd wager a 10 or 20 game match would see him immediately competitive. The machine will eventually behave like an AI, and human go players will essentially learn how you think and counteract your particular behaviors. Li will eventually learn to manipulate the machine; it's *very* intelligent, but not creative or insightful.
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That's not how it happened with Chess. My prediction is that no human will ever beat the top Go AI again.
he's playing against it like it's a human opponent, he's playing against it like he's a go champion, he needs to play against it like he's a programmer. I would be curious as to how it deals with mirror play, or wildly suboptimal plays. I would wonder if it's overfit to go played well.
it's *very* intelligent
No it isn't. It has a lot of processing power and well-tuned set of heuristics allowing it to assign a score to each board position. That's not intelligence, it's data processing.
No sig today...
Food for though: couldn't you argue the same about a professional Go player?
Quite the opposite. Google actually expected that the AI would lose a couple of matches while it learned the kinds of moves that a really top go player made, and then improve. I expect that no one will ever beat this AI unless they come up with a completely novel strategy for how to play Go, and even then, they're unlikely to win.
It's a trained neural network and other machine learning techniques, not just a bespoke algorithm. It operates specifically by combining old knowledge to create novel knowledge. That's the fundamental of the algorithm.
It's not obvious why this "creativity" in the context of Go is fundamentally less effective than human "creativity" in the context of Go.