AI beats human players in StarCraft. Here’s why it matters

Last week, DeepMind made history as it introduced AlphaStar, the first artificial intelligence that defeated professional players, 10-1, in StarCraft II, a complex real-time strategy game.

I have been watching South Korea’s Global StarCraft II League for over seven years, and I agree with game commentators when they said that AlphaStar showcases impressive strategic thinking and skills that are comparable to the best players in the world.

There’s still room for improvement, and it’s fair that some passionate fans feel that machines have too much of an advantage with their superhuman reflexes, despite the developers’ attempt to limit the machine’s performance to human levels and level the playing field.

However, as much as I love StarCraft, the bigger question here is about AI’s significance and impact on technology and the world. So let us explore three profound implications beyond the world of StarCraft: the arrival of real-time AI, the shift beyond supervised machine learning, and the future of mutual learning between AI and humans.

1. Real-time AI has arrived

DeepMind’s AlphaGo ignited the world’s imagination in 2016 by beating Lee Sedol, one of the best Go players in history. In just three years, the DeepMind team has moved from a fully observable, turn-based game to a partially observable, real-time game.

As shown in the illustration below, AlphaStar “looks” at the screen, passes the information through a series of artificial neural networks (the machine’s brain), and executes actions in real time. It fights air and ground battles while building units at the same time, just like what MaNa – its professional human adversary – does.

Unlike Go, where the machine can take minutes to calculate a single next move, a game in StarCraft can be won or lost at a moment’s notice. Furthermore, the fog of war limits what players, including AlphaStar, can see. This means that AlphaStar has to make judgment calls every second based on imperfect information, exploration, and control over hundreds of different units and buildings.

Why does it matter?

Making good decisions under time pressure and with imperfect information in hand is one essential ability that differentiates humans from machines. However, AlphaStar shows that AI is closing in on that gap.

From optimizing and reducing traffic congestion in Hangzhou to delivering Amazon packages or searching and collating financial information, the potential applications of real-time AI will transform companies and even countries. Moreover, AI always performs at its peak – it does not get tired, distracted, or injured over time. This is why it can also assist in high-intensity work like surgeries, where precision, focus, and consistent good decision-making are required.

2. The shift beyond supervised machine learning has begun

Most StarCraft AI bots are terrible and employ a supervised machine learning approach. They execute moves from their playbook database, following rules set by human developers, and lack the capacity for big-picture strategic thinking.

They struggle to keep up with the average players in the Gold or Platinum league. The game is too complicated for developers to load the AI with solutions for every possible scenario. This explains why it’s a big deal that AlphaStar just defeated MaNa – a professional player in the top 0.05 percent – with a 5-1 score.

The difference in the quality of play between traditional StarCraft bots and AlphaStar is like that of your college basketball team versus NBA players. AlphaStar learns, adapts, responds to challenges, and comes up with new strategies, just like a top-level human player.

3. Mutual learning between AI and humans

So why should we care about this?