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Impressive work by Google research team. I'm both impressed and scared. This is our Deep Blue moment folks. a history is made.
Give credit where credit is due. This is DeepMind's research, and Google acquired them in 2014. Of course, Google gave them a lot of resources to train AlphaGo. But let's not bury the subsidiary, or I guess they would both be subs to Alphabet now making the two even less related.
I really like the moments when Alpha-Go would play a move and the commentators would look stunned and go silent for a 1-2 seconds. "That was an unexpected move", they would say.
In game 2 there was a point where Michael Redmond seemed to do a triple take and couldn't believe the move AlphaGo played.
At some point it figured that the Ko fight at the bottom was already won. Hence that white move at the top which nobody saw coming.
Another interesting moment was when Michael Redmond said "A human would typically not spend too much time thinking on this obvious move". This was the move on the right-hand side somewhere. What this tells me is that human players rush through some moves because they seem obvious but since Alpha-Go is a machine, it does not care about obvious and non-obvious. It's calculating the entire board through to the end and is not interested in "local fights".
What happens if you give the human player a handicap? I wonder if the games are really as close as the commentators say, or if it's just a quirk of the MCST algorithm.
It's important to remember that this is an accomplishment of humanity, not a defeat. By constructing this AI, we are simply creating another tool for advancing our state of being. (or something like that)
It is not a tool if you can't control it. Politicians fool countries delivering empty promises about better health, education and security. A supraintelligent AI could promise making humans rich, healthy and powerful, to then break its promise and dominate the world. https://en.wikipedia.org/wiki/AI_box
Basically, why would an AI want to dominate the world? Humans would have to both very stupidly give the AI values that encourage it to dominate the world and very luckily (or unluckily) give it values that actually converge to a horrible outcome against human intentions by random chance (since the AI designers certainly won't be tuning the value set for that outcome).
I am really curious about the reviews from An Youngil 8p and Myungwan Kim 9p. The commentary by Redmond always tend to leave something to be desired.
Myungwan Kim 9p and Cho Hyeyeon 9p's commentary on the American Go Association YouTube channel: Game 1: https://www.youtube.com/watch?v=6ZugVil2v4w Game 2: https://www.youtube.com/watch?v=EitoPhtGWJQ Game 3: https://www.youtube.com/watch?v=CkyVB4Nm9ac
I recall Andrew mentioning that Myungwan will be back to comment games 4 and 5?
As a Go player, I'm really excited to see what kind of play will come from that!
[1] http://www.theverge.com/2016/3/10/11192774/demis-hassabis-in...
It's important to remember that this is an accomplishment of humanity, not a defeat. By constructing this AI, we are simply creating another tool for advancing our state of being. (or something like that)
It is not a tool if you can't control it. Politicians fool countries delivering empty promises about better health, education and security. A supraintelligent AI could promise making humans rich, healthy and powerful, to then break its promise and dominate the world. https://en.wikipedia.org/wiki/AI_box
Of course, a cat is not conscious. But compared to an AI, we might also be considered pretty low consciousness beings, or at least beings in front of which you don't justify yourself.
Earlier quoted context omitted.
In game 2 there was a point where Michael Redmond seemed to do a triple take and couldn't believe the move AlphaGo played.
Yeah they seem to forget that Alpha-Go is looking deep into the future. I have not read the Nature paper but I assume it's playing out possible moves way into the future. At some point it figured that the Ko fight at the bottom was already won. Hence that white move at the top which nobody saw coming. Another interesting moment was when Michael Redmond said "A human would typically not spend too much time thinking on…
To some relatively small depth, right? I hear the estimate that all possible moves in a Go game probably can't be physically represented in the universe (unless we learn much more about the structure of games' evolution).
Super interesting to watch this unfold. So what game should AI tackle next? I've heard imperfect information games are harder for AI...would the AlphaGo approach not work well for these?
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.