Despite the fact that I am sure I come off as a total @ssh0le most of the time (and may be one, for all I know), there is nothing much I enjoy more than when this happens.
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AI Reaches A Long Sought Milestone
- Thread starter Revoltingest
- Start date
I vaguely recall you sometimes coming across as miffed & aggressive,
but hey, you're just normal in this regard. You've always been friendly,
mirthful & interesting to me. And you don't bully us lowly engineers.
That's why you shan't stay away too long.
I won't allow it!
Besides, too many of my other favorite scientists are away right now
(Painted Wolf, Meow Mix, & I forget a few others).
AlphaGo wins the first game....
http://www.independent.co.uk/life-s...nent-lee-sedol-in-landmark-game-a6920671.html
For those interested in the details.....
https://gogameguru.com/alphago-defeats-lee-sedol-game-1/
The above link has a move by move replay.
White won by resignation.
Black was ahead, but not enuf to overcome the komi.
It's interesting how close the game was, & that the advantage shifted a couple times.
http://www.independent.co.uk/life-s...nent-lee-sedol-in-landmark-game-a6920671.html
For those interested in the details.....
https://gogameguru.com/alphago-defeats-lee-sedol-game-1/
The above link has a move by move replay.
White won by resignation.
Black was ahead, but not enuf to overcome the komi.
It's interesting how close the game was, & that the advantage shifted a couple times.
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I expect that Lee should improve as he gains experience against AlphaGo.
The latter has already played a great many games to learn strategy, & likely
won't learn much from playing Lee. But Lee is learning how a machine
differs from his usual opponent, & is in a better position to improve during
this series of games.
Lee's view of the board looks difficult....I'd hover over it more. But then, my
memory & recognition are quite poor compared to his.
The latter has already played a great many games to learn strategy, & likely
won't learn much from playing Lee. But Lee is learning how a machine
differs from his usual opponent, & is in a better position to improve during
this series of games.
Lee's view of the board looks difficult....I'd hover over it more. But then, my
memory & recognition are quite poor compared to his.
Breaking news....AlphaGo wins 2nd game!
http://www.nytimes.com/aponline/2016/03/10/world/asia/ap-as-skorea-game-human-vs-computer.html?_r=0
http://www.nytimes.com/aponline/2016/03/10/world/asia/ap-as-skorea-game-human-vs-computer.html?_r=0
A short analysis of the first game......
AlphaGo wins 3rd game!
Yerda
Veteran Member
Lowly?
Every time I learn a new topic in maths I go straight for the engineering tutorials to find out how it really works.
That's because we engineers must find simple ways to understand things.
We're more like clerks, janitors & geologists......not theoretical physicists, you know.
Some very interesting commentary during the 2nd game....
https://gogameguru.com/alphago-2/
https://gogameguru.com/alphago-2/
That hurdle took mankind a long time to overcome.
Le Sedol (the human) wins the 4th game against AlphaGo !!!!!
https://gogameguru.com/lee-sedol-defeats-alphago-masterful-comeback-game-4/
https://gogameguru.com/lee-sedol-defeats-alphago-masterful-comeback-game-4/
Game 5 (the final one) commentary....
http://tse1.mm.bing.net/th?&id=OIP....c221c949c2H0&w=300&h=300&c=0&pid=1.9&rs=0&p=0
I know this level of detail doesn't interest many, but I just can't stop myself from offering it.
What interested computer geeks will find is some discussion of how to create a learning thinking machine.
- How the "mind"k is structured, ie, its components.
- How it trains & learns
- The large scale strategy it's programmed to use (focus upon highest probability of a win, rather than the greatest score), & the effect upon its game strategy.
- Its almost psychological looking flaws in some circumstances.
http://tse1.mm.bing.net/th?&id=OIP....c221c949c2H0&w=300&h=300&c=0&pid=1.9&rs=0&p=0
I know this level of detail doesn't interest many, but I just can't stop myself from offering it.
What interested computer geeks will find is some discussion of how to create a learning thinking machine.
- How the "mind"k is structured, ie, its components.
- How it trains & learns
- The large scale strategy it's programmed to use (focus upon highest probability of a win, rather than the greatest score), & the effect upon its game strategy.
- Its almost psychological looking flaws in some circumstances.
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