> I never thought the AI player had a 'deep understanding' of Go any more than I think string sort routines
It has a neural network trained on millions of games. Of course the model captures more than a sort routine which is non-parametric, in other words not trainable from data. The game of Go is complex enough that we can't code it up manually.
The fact that AI is implemented on matrix multiplication does not detract from it, humans are implemented in electro-chemical reactions. These reactions are all local, no single cell in our body has the big picture.
On the other hand, human understanding is also brittle - how many Go players still can't beat the AI even after this article has been posted? Blind spots/adversarial attacks exist in both humans and AI. It was AlphaGo that influenced the way Go is played at the top levels by introducing new strategies, techniques and moves that were previously considered unconventional or suboptimal by human players. AlphaGo found blind spots in our thinking first.
It has a neural network trained on millions of games. Of course the model captures more than a sort routine which is non-parametric, in other words not trainable from data. The game of Go is complex enough that we can't code it up manually.
The fact that AI is implemented on matrix multiplication does not detract from it, humans are implemented in electro-chemical reactions. These reactions are all local, no single cell in our body has the big picture.
On the other hand, human understanding is also brittle - how many Go players still can't beat the AI even after this article has been posted? Blind spots/adversarial attacks exist in both humans and AI. It was AlphaGo that influenced the way Go is played at the top levels by introducing new strategies, techniques and moves that were previously considered unconventional or suboptimal by human players. AlphaGo found blind spots in our thinking first.