In the last match they used a newer interface where the AI had the same restricted viewport as a human and had to decide where to move its camera to both see what's happening and make actions. The player and commentators both noticed that this resulted in more human like play, and the AI seemed less able to micro multiple armies stretching beyond the viewport like it had in earlier matches.
The deepmind people said the restricted viewport did slow down training, but in the end it was able to get to the same skill level as the previous ones in the end.
I find what you said interesting but I lack the context to understand it.
Camera management isn't part of that equation.
Though it is fair to conjecture that Mana may have won the earlier Blink Stalker vs Immortal game, if camera management were required.
Zooming out for a human player would be considered cheating. It would be easier to see hit and run attacks and react in time etc.
Yes this is a mass simplilfication of the game. There is a lot to resource management and production capacity to train/build/grow/call in more troops.
I cannot speak to the competitive side of it.
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:
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.
Watch this and learn a bit more about why they're doing Starcraft AI. The Deepmind guys first appear around 32:00.
So simulation is always a part of it, regardless of target execution environment. In which case, games make a lot of sense, since they’re already complex simulations (thus useful for learning how to train AI’s, and what parts of the simulation are worth having), make good PR, can be tested against quickly, and in the case of competitive games, have a set of “experts” that already study what the human-powered collective AI learned over time, and thus it comes with a set of known expectations of how the AI might fail, and what we expect it to learn.
So tldr; simulation vs real world is a red herring. It’s the same learning process, just different execution environments.
This was a failure on Deep Mind's part, not a success. The bot is not given remotely the same context as a person. It will lose in that context.
You can make a fighting game AI without deep mind that will parry every attack and punish with a perfect combo and always beat humans because of 0 reaction time and 0 execution flaws. Big whoop.
This is irritating clickbait.
All the model architectures and machine learning techniques that have been developed through the playing of these games, exponentially increasing in difficulty from Go to Starcraft, can be directly applied to real life tasks.
What is life anyways if not just a superset of sets of games to be played? Optimizing the output of a protein structure designed for chemical catalysts, teaching a car how to get from point A to point B while navigating a rule based obstacle emplaced environment, etc, etc. All merely simple games, and yet filled with pretty much infinite possibility.
Underestimate the power and potential of machines learning to play at your own folly.
I hope this AI hype cycle ends soon and funding gets diverted from tech to actual science in the medical field. But I guess that's unlikely. I see no obvious evidence for AI/ML etc to be less of a speculation hype than the already deflating self-driving car hype.
I don't doubt that ML will have its practical application given the amount of effort that is currently put in to it, but I do think it is wildly inflated. Not to mention that the spectrum of what kinds of software that counts as AI seem to get wider for every week.
That the AI hype is more or less entirely confined within an already hyped tech industry doesn't seem to me like a coincidence. An AI revolution hellbent on figuring out how intelligence works would surely include other fields than just tech?
Tthe first 2 and a half hours goes over the other 10 matches, which weren't played live on stream.