And they would have won none at all if deepmind had worked on the problem for one more year before showcasing it, even with this limitation. I don’t think it really matters.
For human players maintaining this map awareness is definitely the hardest part of starcraft. The micro isn't really that hard, you can train on special custom maps and get most of the tricks down pretty quickly. The build orders and meta level strategies aren't very hard to wrap your head around either, the possibility space is actually pretty small here.
What is hard is constantly task switching, not hyper focusing on a couple of units, knowing what you should be focusing on at any given point in time... Well, those are all pretty much the same, it is, "how should I spend my very limited attention".
If your opponent has infinite attention resources some strategies that work against humans dont really make sense. Drops for instance are balanced around the idea that if the opponent recognizes that they are being dropped they will be able to pretty easily defend against it. Against a computer that will instantly see the drop the millisecond it comes out of the fog of war... Well, you just gave away the hard part for free. A human player would either have to a) get lucky and happen to glance at the minimap in the small window to counter the drop. or b) anticipate the drop and make the conscious choice to spend precious attention rescources to catch it.
If it's so massive, why did their camera-limited agent have near-parity against their non-camera-limited agents?
The show off game: https://www.youtube.com/watch?v=cUTMhmVh1qs&t=2h31m22s
The bot is getting it's main force lured back to it's base by hit and runs for it's resource producers. Repeating the same mistake again and again. Later it acts confused and rather have it's main base wrecked than having a high risk fight with it's main force vs the players main force, even though it would auto-lose not doing so.
I've got a feeling these bots have a huge API advantage in "mechanical" skills versus humans. Eg. it has to be way faster to retrieve the "x ability used by y" event than seeing an animation unfold on the screen, leaking intention to bots earlier then human players.
Once alphastar was faced with a scenario that couldn't be brute forced with perfect micro it pretty much stopped working.
A far bigger factor is that this new agent simply trained for fewer days because they only implemented it recently and it was hot out of the oven. Give it another week of training and it would probably be a hard nut to crack again.
That said, the matches are played in a manner that gives the humans little time to look for idiosyncratic AI behavior that's exploitable. If they played several dozens of matches against the same set of 5 agents again and again they would probably figure out some cheesy strategy that the AI doesn't know to defend against.
We're not yet at the point where the AI can adapt to counter-adaptions in realtime.
[0] https://storage.googleapis.com/deepmind-live-cms/images/SCII...