AlphaStar is probably thinking "This opponent is using weird strategies, I have never seen that in my 200 years of StarCraft II."

Props to deepmind for enduring 200 years of pure protoss vs protoss.

"You don't push up narrow ramps" AlphaStar: Hold my beer.

Blizzard: All units have their advantages and disadvantages AlphaStar: Warp in Stalker

I wonder when AlphaStar will start trash talking in the chat

TLO Game 1: 14:39 - 21:52 TLO Game 2: missing (info: 28:02) TLO Game 3: 29:07 - 45:39 TLO Game 4: missing (info: 52:58) TLO Game 5: missing (info: 52:58) Mana Game 1: 1:03:01 - 1:08:33 Mana Game 2: missing (info: 1:16:09) Mana Game 3: 1:16:32 - 1:24:31 Mana Game 4: 1:30:19 - 1:43:13 Mana Game 5: missing (info 1:45:49) Mana Game 6: 2:01:38 - 2:14:42

Can you imagine the commentary that would occur in the Alpha star universe watching the human games? Alph-tosis: So we see this agent is building his buildings all the way near the ramp, any idea why he might be doing that? Alph-Dam: No idea, We saw this build get played around the 140 year mark, but the time your probe takes to get there, just not worth it, You could've been mining minerals all this time. Alph-tosis: We see this a lot with the human agents, choosing not to go even into the 20 probe count for the mineral line, not leaving any room for error here, Alph-Dam: Yeah, he's very confident in his ability to keep the probes up, and he does defend them well, but loosing out on those extra 200 minerals in 3 minutes, he's really setting himself up to get put down, and he's really boxed in to defend that line, even if a single probe goes down, that's almost 50 minerals a minute he's losing. Alhph-tosis: Looks like the human agent is choosing to engage on the up-down state change. Alph-Dam: I can't make heads or tails out of this, does he think he can hold the stalker push better here? Alph-tosis: Even if he does, with that probe count he'll be losing the economic game, he's gotta try to break out. Alph-Dam: He really is just going to turtle on the up down state change. Alph-tosis: Maybe he knows something we don't.

Game 1 - 1 base all in. Game 2 - Turtle into mass Carriers Game 3 - Disruptors, and more Disruptors, with super late blink on a large Stalker army. Game 4 - Stalkers with DT's in TLO's main base Game 5 - Proxy 4-gate. Turns out the AlphaStar is an NA player.

I've been oversaturating my mineral line for the past 6 years and I've never been more validated.

let's see your fancy robot try to win a 1v1 against our boy imaqtpie

I feel like installing StarCraft 2 all over again after watching this. Huge props and credit to the team behind AlphaStar. Well done DeepMind team!

I would love to see a completely random selection from the two hundred years of games that they played at varying levels throughout the process. Like divide it into four or five tiers and show three or four games completely randomly chosen from each of those tiers of learning. It would probably be hilarious and eye-opening to see some of the things that were attempted

When you kill your own army with disruptors and still win

I think its going oversaturation on the minerals because it probably calculated that, you overall probably lose MORE minerals by losing 1 probe on mining if it gets killed, than if you "waste" 50 minerals on a backup probe ready to mine if others got killed. Probably true, a probe can probably mine 50 minerals in the time it takes to build a new one, making having spares worthwhile. It's basically thinking that having backups is more valuable because it doesnt lose time rebuilding potentially lost probes. This means that if the human player does a sneaky flank raid to take out 4 probes, and AlphaStar was already 4 probes oversaturation, that attack literally didnt hurt the AI income rate what so ever. Sure it lost 4 probes, but it did NOT lose the time it takes to re-build 4 probes (which can be a substancial time of lower income). Kinda insane how even a "primitive" AI like this has already learnt the lesson of "time is money", and "if i do something NOW to make it harder on myself NOW, it will be easier LATER, investing in the future safety". These are human intelligent concepts that, hell, many people irl dont understand xD Sure its not concious and aware of that, but its ACTING on those principles, which is rather incredible to see. Like an animal storing food for the winter, rather than eating it all at once when its hungry.

Phew! Totally enjoyed this one! I'm not familiar with the rules of StarCraft II but boy was this an event! DeepMind team again doing amazing research and making it interesting for millions of people along the way I think that's the biggest accomplishment.

Humanity : makes cultural content warning about robots going on a killing spree for decades Also humanity : hey, you know this super upper AI we are working on ? Wouldn’t it be neat if we trained it to plan war campaigns ?

I would like to see it play HAS

That Neural Network activation display is mind blowing. Alpha Go was a massive deal at the time and the DOTA 2 AI team battle was just as big but this really is mind blowing considering the amount of variables and nuances SC2 has. 5 years from now, AI will no doubt be the Senpai's of games that pro-players will use to theory craft and practice with. Welcome to the new world order my friends.

"that outcome prediction is giving me chills"

Oh my god. I so wish that we will see more of this in the future. Especially a Terran vs Zerg matchup and what it would come up with. And the splits of the marines, etc. It would be absolutely amazing and beautiful

Next they're going to teach it to play Global Thermonuclear War.

I'm in nerd heaven

I feel a lot of people have mentioned the APM/EAPM problem. Something to add to this is the fact that even if you differentiate between the two and set a limit, AlphaStar would still be able to make inhumane actions. For example, a pro player would have to move it's mouse before clicking. What I feel like happened here is that AS could basically click on opposite sides of the screen at the same time, I must say, the last match they adressed the screen problem, very nice of them to do. The AI was obviously much worse since they had to start from scratch, but Mana's intelligent play was very nice to watch! Overall this truly is something spectacular, I'm eager to see what AI has in store for us for the future.

Human race pushing forward through SC2, priceless feeling, this small fan community has been a great show so far feeling like part of the master race never was so delightful

PLEASE do this with every race, pro player off-race first and then pro-player main-race! This is extremely fascinating

The micro of the AI is inhumane because you can easily have 200 APM with a bit of spam but it's almost impossible to give 200 distinct meaningful orders per minute.

Super Nice und hoch interessant! Danke fürs hochladen! Eine Weitere kollektiv ausbaubare Idee The Ultimate ZeroStar - Ideensammlung Man stelle sich zwei Starcraft 2 AI-Bots wie AlphaStar vor, die auf einer bestimmten Karte mit zwei bestimmten Rassen im Kontext einer bestimmten Starcraft 2 Engine versuchen die perfekte Lösung des 1vs1 Starcraftduells zu finden. Also zu demonstrieren mit welchem Ende das Spiel bei beidseitig perfektem (oder auch bislang unübertreffbarem) Spielen beider Gegenspieler endet: 1) Unentschieden: Die Ressourcen der Karte gehen aus ohne das einer der beiden Spieler einen Sieg erringen kann; ohne das der Gegenspieler einen entscheidenden Fehler dafür machen müsste. 2) Schere-Stein-Papier: z.B: Zerg gewinnt gegen Terran, Terran gewinnt gegen Protoss und Protoss gewinnt gegen Zerg. 3) Heimvorteil: z.B: Auf dieser Karte gewinnen immer die Zerg falls diese gegen eine der anderen beiden Rassen spielen. Der Kampf Zerg vs. Zerg hingegen endet unentschieden. 4) Heimvorteil-Arschloch: Der Zufall noch vor Beginn des eigentlichen Spiels entscheidet über die jeweilige Positionierung der beiden Spieler auf der Karte und zugleich darüber welcher der beiden Spieler das Spiel gewinnen wird. Jeder der möchte, gelangt über die folgende Verlinkung auf ein kollektiv ausbaubares Googledokument und kann sich dort am Ausbau der Ultimate ZeroStar - Ideensammlung beteiligen! docs.google.com/document/d/1Ljngoa2EK7JuhmwO0GyWG1vdMOH1UZSHXmSmmixl004/edit?usp=sharing

Until the audio / video disconnect is fixed, you can watch the video by opening it in two windows, muting one and starting the other just as Artosis starts talking (around 29:45) in the muted version.

One of the challenges of working with AI is interpreting what it is actually happening and not fooling yourself into believing something which isn't true. I get that this is a PR campaign, but I think the folks should not try to oversell what happened here; it makes the team look like they either don't understand what they have created (which is bad) or are straight lying about it (really bad), neither of which are good for this cause. The "agents" have nearly perfect mechanics, but lack depth, which people watching this video may not pick up on. I highly respect the work done with this project, and the impressive results that this system has demonstrated. Clearly these guys have done some marvelous work and deserve some hype. I also really appreciate @DeepMind for bringing in the casters and players, thank you for supporting the SC2 community! The lack of walling off and no respect for ramps demonstrates a real lack of tactical capability. Not being able to change army unit composition shows that the "agent" doesn't really have strategy. Without question most/all of these games were won by the insane micro -- which I accept is quite an accomplishment to train an "agent" to do. I'm also curious about the lack of scouting; the "agent" doesn't seem to scout (much) because it doesn't need the information to make longer term decisions, just reactions to the battlefield. I think this has clear signatures of the training method and/or LSTM. When two otherwise roughly equal AIs are competing, a game should snowball rapidly toward one side, but this tends to happen after all the unit/tech selection happens. Hard switching to a different unit composition isn't something they could be trained on because most of the "agents" have won by this point. I am also really glad they showed the exhibition match, because it demonstrates that the AI can fall into "logical" traps.. repeatedly making the same decision on where to move the units based on perceived threat. The middle/late game seems like the area of least effective learning, again this has to do with training.

Congrats to the team responsible for creating AlphaStar! That is absolutely mind-blowing to see! Keep on pushing the boundaries.

So cool to see a well developed, cable TV quality show about the interesting developments and progression of AI in RTS games... And what a test for Alpha Star in learning StarCraft II...

Would love to see this sort of thing in single player and not only in SC2. It would be really cool to have adaptive AI that constantly challenges you even when you are not playing with other people. I'm a big fan of singe player gaming so playing vs dumb AI all the time gets boring.

Chess: I'll sacrifice my strongest piece. I win. Starcraft: I'll move up your ramp. I win.

Difficulty settings in future RTS games Easy Normal Hard DeepMind

Having just watched this demonstration I was fascinated to learn new insights. What I want to point out especially were the "human rules" of overmaking workers and not going up ramps. This showed me and hopefully will teach humans to not follow rules rigurously, keep an open mind and consider that everything is based on the SITUATION. If an AI can show us that going up ramps does work, it works when certain conditions have been met, and you have to TEST these conditions. I found it fascinating and I must say it was smart to create a non-rule based AI (thankfully to difficulties of coding), that we can learn from scratch just like a child, completely abstract things, test the world, see what works and what doesnt. Rules prohibit and limit. And I should also point out, the multitasking demonstrated of the previous agent AI's were of course an unfair advantage. Still, I want to see what the best race will be with multitasking agents and without multitasking AI's. I have a feeling the results could be the same as mentioned before: No Agent is the best and they can all be exploited. Pretty much the same nature works - everything has a weakness - you just need to know what it is. And with regards to knowledge, this demonstration reinforced the saying Knowledge is power. If anyone could live for 200 years we might become a better race. But given the relative short time frame, things might seem chaotic. Given we are living longer I have hope we get more organized. What you can also see in nature, things settle down over time. And mana did a great job a the end with the observers, pointing out information is power, too.

26:22 "economy of Attention" sounds like a TLO phrase if ever I've heard one. This project is perfect for a guy like him, he has always been one of the smarter guys on the scene, and this makes perfect use of his analytical abilities.

44:23 Beginning of Game 1 (TLO) 51:35 Conclusion of Game 1 58:50 Beginning of Game 3 (TLO) 01:15:22 Conclusion of Game 3 01:32:44 Beginning of Game 4 (Mana) 02:12:55 Conclusion of Game 4

Greetings professor Falken, A strange game. The only way to win is to rush Stalkers. Marines good unit too.

I think what MaNa did in that exhibition match might be conceptually a bit similar to what Lee did in the Go match he won, with doing something unexpected in harassing with two immortals. As the commentators said, if the AI had picked it off that might have been GG, so it pulled the army back to deal with it, but at the same time, that bought MaNa enough time to get the army composition he needed to push for the win. I would be very interested to see this view-limited Alpha Star with one more week of training and a new series of games. And of course also later with other races and also a cross-race matchups.

Absoluty awesome work ! Gj team DeepMind !

I'm so excited about this, my favourite game combined with my passion and my interest in neural network. It is really amazing to see this amazing development of machine learning alghorithms

can we have 2 ai's with like 5k years experience each and with no limits to its actions battle eachother in sc2? Also if they both play random so its not just pvp?

It would be cool to see Alphastar put into the competitive online ladder. Start it in Bronze and have it only play a certain number of games daily so it's not just playing 24/7 and players encounter it constantly. It would be neat to see it evolve as it encounters a variety of maps, races, and unique play styles. Especially cheese.

1:42:32 "AlphaStar has a normal _average_ APM!" *Watches AlphaStar's APM throughout the game* Sometimes it's 100 APM, and during fights it's at 1,000 for long stretches, even exceeding 1400...

The casters are talking about an average prol-like APM by Alphastar (~300), while ignoring the fact that it hovers from 600-800 during fights, giving It a considerable upper hand during fights, especially with micro-intensive mechanics such as blink. While the chosen strategies by Alpha are advanced but not perfect, the superhuman interaction w/ the game (no mouse, no keyboard + high multitasking) give It an obvious advantage. Alphastar is impressive indeed, but Id love to see some advantages being regulated in order to have a balanced match against humans :)

Interesting games but I feel like that the technical advantage of the first agents where a bit like DeepBlue brute forcing the win against Kasparov. The agent in last game with the correct in game camera is very interesting. I would have loved to see more game with this agent as it felt more brain vs brain where the AI had no silly technical advantage. I surely hope that there will be more games like the last one on different maps and different matchup. My feeling, that may be wrong, is that AlphaStar won due to technical advantages (usefull APM, camera vision,...) and not brain advantages. This feels like very early works from DeepMind (one matchup, one map). Looking forward for what follows.

This DeepMind guy from the video visited and held a lecture about AlphaStar at my university the last week. It was actually very impressive and interesting to get to know more of the technical side.

Thanks Deepmind for this amazing video about my favorite game

you have to do this with Serral.

I agree with Blizzard, SC2 is the best eSports game there is. Casual and non-players can enjoy watching it, and it has very deep strategies, tactics, and micro-ability requirements on high level players.

Great contributions from everyone on the panel.

Quick links for those who are excited. TLO vs Alphastar 14:40 - Game 1 28:58 - Game 3

The last game where the field of view had been restricted, and DeepMind had to use some of its APM for camera control instead of unit micro, made a huge difference. You could see at one point where TLO Mana was squished in the center of the map and DeepMind had stalkers on multiple flanks, in the past it crushed Mana in this situation. It would attack on multiple sides at the same time and use blink to individually pull back stalkers in the front right when their shields ran out and then later when their health was low. It made DeepMind's army last so much longer! When you play SC2 you can SEE your hurt guys and if you could control them with your mind you could use a much lower APM to pull back woulded stalkers from the front line. But when you're using a mouse to try to pick them out it is very difficult and it is impossible to have perfect dexterity. The AI has perfect dexterity with every move. That goes a long way. When it can see the whole battlefield combined with perfect dexterity, the stalker with blink strategy becomes insanely powerful! When it has to use camera to look around and control its different attack fronts it clearly limited its strength. This was incredibly entertaining to watch! Can't wait to see more. Also would love to see the CURRENT SC2 global champion play DeepMind because the current champ at the top of their game is usually so much better at micro than a pro gamer who has been around forever, has a ton of followers, but probably isn't currently in their prime.

Serral vs Alphastar pls!!!

Love Rotty and Arthosis, in my view the very best of the very best, not only SC2 commentators, but commentators in general.

very inspiring and radical breakthroughs

I love how artosis praises A.S while shitting on Mana after the third game. MANA'S face is priceless

Hmm when I watched yesterday the sync was fine (although the seek thumbnail previews were out of sync). After refreshing the page the audio is massively out of sync

When i saw the the win percentage graph, shivers went down my spine. This is scary af.

OMG I swear the DeepMind Team will usher in the very real future of real awesome e-sports from the comfort of your own home one day....you will no longer just watch..you will one day actually bet and challenge and win or lose real money or prizes...i can see solo's and teams becoming as vested as sports franchises...dang keep it up DeepMind...I wish I live long enough to enjoy your work!!!

Ruining everything Korea is proud of one game a time.

i came here after the ai destroyed the worlds best go player, amazing stuff!

I’m very proud of MaNa in the exhibition game in which he won. He just needed 5 training games to recognize his flaw, that he needed to observe the progress and strategy of AlphaStar. In the beginning I was a bit upset, that AlphaStar had the advantage of working only with the total overview of the map and didn’t need a mouse. But with all the disadvantages the human player had and also not 200 years of practice, MaNa was able to improve his game/intuition within these 1+ hours of analyzing his losing matches. Probably there is the achilles heel in the training, when agents only train by agents and because of time and the amount of games you would need to crack the human ingenuity you needed to make a scaled up game: agents vs millions of humans. Interesting (philosophical) times!

With the end of new sc2 content support just announced, I am guessing that Deepmind's involvement with SC2 is also over now? Are we never going to get a SC2 AI of Alphastar caliber for solo practice?? I was really hoping for this :(

Your AI is incredible. Hands down one of the most entertaining things I've ever seen in Starcraft 2, but I would like to provide a little constructive criticism if I can: 1) The APM limit you put on it is not realistic. I like that you implemented a limit, but you've confused APM and EAPM. APM stands for actions per minute and EAPM is effective actions per minute. Each of the AI's actions are effective. It doesn't issue the exact same command 8 times to have it happen once. Human players, however, have MAYBE half of their APM as EAPM. By letting the AI spike to 1500 EAPM in a fight, you've given it a totally unfair advantage. Please try limiting it to no more than an average of 150 total APM across the game and not letting it spike higher than 300 APM in any 1 minute of gameplay. That would provide a much more human-like limitation to it. 2) Allowing the AI to play without a limited screen is also an unfair advantage for it. Human players have to spend APM and time re-focusing their camera and field of vision. Allowing the AI to see the entire map at once is another reaction time advantage. Harassment against that is nearly impossible. (I understand it still has fog of war, but it can see everything it has vision of simultaneously instead of the limitation of what a human player can see on a monitor at one time). Still, this AI is incredible and I am honestly impressed with it. Give it another 1,000 years of play time and maybe it can play against all 3 races on all the ladder maps and consistently beat professional players :P

Why are you so hung up on the 'weirdness' of Alphastar's worker-numbers? You've mentioned it yourself several times already: Alpha frequently lost parts of its worker forces with *no damage to its economy*. It's a buffer that makes total sense-it's genius even-given the focus every player puts on their enemies' economies. I'm surprised no one else has done it yet.

So much respect to everyone involved in this project. 10-0 wins for alphastar when it can see and influence the entire map at once. 0-1 when alphastar is forced to focus on a single spot at a time, more comparable to what a human experiences when playing. I have no doubt that they can create an AI that can beat any human, but I think they still have some work to do before we clearly have a dominant SCII AI. To convince me of dominance, it will be crucial that they make this as "fair" as possible. The question is whether they can develop an AI that can outperform a human on a conceptual/decision-making level, rather than a on a visual processing or a processing speed level. Credit goes to starcraft ii for being such a complex game that building a dominant AI is such a big challenge. Can't wait to see Deepmind defeat this and other challenges before them!

Thanks for fixing the sync. Been waiting to watch this.

I still have some reservations about the general fairness, but this is damn impressive. Its actions per minutes are limited, but it's using a superior input device, it's like as if the player didn't use keyboard and mouse but controlled the game just by thought.

To be honest, you don't quite saturate mining until you hit around 24 probes. You will leave the linear part of the income/time curve at roughly 16 so most people don't bother going over but the AI decision actually makes perfect sense to me. Also, having more workers than recommended gives you a buffer in case of enemy attacks on your mineral line and provides you with enough workers to instantly fill up 50% of the capacity of a new base. I was looking at the mining data and graphs provided by team liquid but I didn't crack any numbers to figure out the difference in disposable income "over-saturating" provides so the first part is just conjecture based on my engineering experience with non-linear characteristics. DATA: + 16 drones = 660mpm + 24 drones = 812 mpm + Going over 24 drones has very low impact on income.

In my studies I created a starcraft AI (BW though) that used genetic algorithms (well, really a more advanced class of genetic algorithms) to generate strategies to win against opponents it was matched against. It's a very interesting topic.

Having ALL the friendly AND enemy units AND IT'S STATS at once and at all times it's an INSANE advantage. (It's still awesome) that micro...

Deepmind vs 8 Brutal cheat AI Deepmind vs Hacker Please.

I feel like I'm seeing the beginning of Isaac Asimov's Foundation Series coming true. First Go, then SC, the Human Economy.

At 02:04:09 what stands out for me - Rotterdam mentions this as pulling workers really early - is that alpha star instantly pulls all workers, in the direction of his expansion and his stalkers. It seems as if it "intends" to move them in a way to use the "lost" time from pulling workers for a potential transfer to the expansion if the attack is going on. And at the same time drawing the oracle to the defenders. This looks like really efficient management of the situation. The earlier you pull here the earlier your defenders will reach the oracle and the fewer probes you lose, whereas for a later pull you would just manage to draw the oracle away from the defenders.

Alphastar’s micro is where it shines. It understands how to keep units alive and dealing damage even when they have very low health

Would be great to have learning AIs in any game; really interesting to watch them. :)

Sure the AI's apm might be no higher than a pro gamer's, but all of its actions are calculated. It's not just spamming. There's a huuuuuuuuuge difference.

Fantastic! Why is it that on that final match you didn't show all the game info in the panel like you did in the earlier battles, you know, the supply count/unit count/resources etc....?

I think that one of the most difficult fairness metrics to quantify (for humans) is the cost of context switching with regard to focusing on different parts of the map-- decision making for different parts of the map may vary greatly and be significant. I suspect that this is difficult for humans, but is trivial for a Neural Network. I'd be very curious to hear what a deep mind expert has to say about this metric and its importance.

DeepMind devs SHOULD cap APM/eAPM spikes!!! This is cruicial for making it more of an even fight. Restrictions breed creativity, so if we want to see superb strategies and build orders we must hardcap the mechanical capabilities of the Ai! We already knew that playing theoretical perfect micro and macro should always win, there is nothing interesting in that... so why not even cap it waay under pro level APM/eAPM? Then the ai would only rely on its strategic thinking, it would be much more interesting i think!

About the discussion over APM (at 23:40) I would love to see a comparison between the players' EPM. I don't imagine the AI spams at all so if each one of its actions are effective that's actually a pretty high number there.

24:33 but it seems alphastar has more accurate APM - the blink micro is very good. Not necessary about reaction time but about accuracy of clicking.

Deepmind is very good. This was unexpected. Please continue to work, it is very interesting to follow. How many games did he play against himself?

I fell asleep to a guy digging a foundation for a house, woke up to this...

Whoah, that last match! :D

Artosis + crew = legit love u guys

1:42:02 "oh my gosh" and the APM goes above 1500. is that cheating? 1500+ precise apm

is any of the agents called Smith?

This demonstrates that creative thinking is still good, and people with less or no experience in a field can "evolve" even better that people that study the field from papers written by other people, or books. I mean, more experience on the field counts more that study. study = classical programming, experience = machine learning.

OMG.... It's learning! It's Micro is impeccable! Look out Hoomans!

42:15 - I feel there might be an unfair advantage to Alfa - The limitations with the move: " controlling multiple armies " - multiple refocus - multiple tracking So, although the overall decision time is limited, Humans are also limited in the sequencing of handling two issues.

is it my problem? The sound doesn’t macth????

well played MaNa on that last one, there's hope in humanity still...

What are y'all's thoughts on the auto-probe to minerals at the start of games? I kind of liked having to split them APM.

What are these complaints about the bot being rude? Instead, train him to say an offensive GG when he evaluates probability of winning >95%. Also switch to terran to be able to throw manner MULEs at filthy human faces.

The first 10 games were impressive, but AI played with significant advantage over human players (like playing starcraft with screen showing whole map at once). Once that was chaned and ai had to deal with screen management - it fell for some pretty basic stuff (warp prism harras making him move his army back and forth), and hadn't realized Mana has observer over his army (any human player would guess this after mana abused that so much :) ). Also not building 1 phenix to deal with the warp prism :) But I'm sure in the future it will become stronger than any human player without unfair advantages.

Wonder if the disruptor heavy game vs. TLO emerged in the AlphaStar league as a counter strategy to the stalker heavy plays AlphaStar seems to excel at.

Everyone has already pointed the APM issue where they didn't limit the effective actions - but also of note is that the AI is able to 'see' everything on the map at a time and it doesn't have the same 'physical input' limitations which can cause misclicks, or have targeting issues, or have to rely on a minimap when it can actively see everything within LOS. It looks like if units overlap it can still accurately target wounded units, it will be able to grab the closest unit with enough energy, etc. Being able to parse that stuff without relying on the input/output limitations that humans have is an advantage in itself.

I would totaly pay google and blizzard for having this ai for practice. Amazing