In that regard, AlphaGo is a lot more impressive, not just because it is a vastly more complex problem to find a loss function for playing Go (compared to chess), but also because AlphaGo basically learned to play the game by itself without even having a model of the game rules initially (or so I've heard).

That said, I would still not consider it anything like generalized AI, if only because the set of possible (valid) actions at any point in the game is tiny, while in real-world problems it is basically infinite.