Curious what you see as examples of this.
> Intuition is so poorly defined that depending on what you mean machines easily have it (heuristics, Bayesian inference, etc)
As a working scientist and a bayesian practitioner, I'm sceptical algorithms have intuition. From my perspective, almost all models that one codifies are extremely brittle and will produce catastrophic failures (or just nonsense) unless the user possesses enough expert knowledge or intuition to a-priori know not to use the model in this regime.
However, I agree with the spirit of the text... go is a well-defined game and adaptability and intuition will be highly limited. For instance, the human can't just turn the board over, or unplug the game!
For the AI, the result of the first match will result in one more game entered in the its database. If it's like chess history, it's probably slanted a little towards that player's history in particular.
But the human player is well aware of the machine studying his strategic history and weighting it. If he's well studied like the chess guys are (is that how go players study?) he could employ a strategy he thinks would be surprising to the AI, or even plan to switch strategies in the middle. If one knows they are playing a pattern matcher, you can try to lead it to a local minimum and then leave it there.
Just speculating :-)
No one can believe it. Myungwan Kim 9p says it's likely Lee Sedol feels like he could have won. He also says Alpha Go is likely stronger than he is.
"Person of interest":
The second game should be a doozy since Lee Sedol will definitely know what to expect and come in full force!
(cough) Ok best 2 out of three before it counts. (cough)
I used to play Go when I was a kid on televised matches in Korea during the 90s and have woken up early on saturdays watching every game live on tv. Then I'd go to these Go school after class and there'd be like 30 students studying and fighting.
Go is a hugely appealing game to intuitive people rather than logical people who prefer Chess. Go is an infinitely more complex and at these Pro levels a demigod like Lee Sedol have the same fanatic followings.
AlphaGo winning was the cherry on top but what was really even more intense was the actual battle in itself. It was like Lee Sedol was playing himself but a version of him that would get better and better each time Sedol attacked. AlphaGo surprisingly chose the right strategy which was to be aggressive right back.
Overall, I could identify with the commentator's excitement and sort of apprehension that the first battle against the Machines have begun and lost the first round.
Lee Sedol must have been taken back at how good AlphaGo is I think he seriously underestimated it because he had a lot of hubris and over confidence going in like 'yeah imma smack the shit out of alphago' and then it after the match is like 'damn gg'.
The biggest ground breaking realization is that deep learning has become so good that it is possible to outperform a human even in previously thought impossible problems....who would've thought a bunch of logic gates fast forward 40 years we have machines that beat us in our own games? 80 years from now what will things look like?
It's a real reckoning and I really feel the drive to learn deep learning just don't know where to start