Technology 3 min read

AlphaStar Attains Grandmaster Level in Starcraft II

DeepMind's AlphaStar AI stunned the Esports world after achieving what only top 0.2% of Starcraft II players managed to accomplish: become a Grandmaster.

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Earlier in the year, we published news of Google’s AlphaStar, defeating the world’s best Starcraft II players. But the AI went a step further this summer.

According to recent reports, AlphaStar has successfully reached the level of Grandmaster, placing it among the top 0.2 percent Starcraft II players in the world.

In the past couple of years, we’ve seen AI programs that could beat their creators at competitive games. From board games like chess and backgammon to video games like Quake III, artificial intelligence is starting to dominate the gaming world.

In January, Google DeepMind’s AlphaStar AI defeated the world’s best player of the real-time strategy game, Starcraft II, 10-0. This was huge!

Millions of people across the planet play the real-time strategy game.

It’s an incredibly popular Esport that involves professional players competing for a prize. While the monetary award is enough incentive, the players often compete for the honor of attaining the highest rank of “Grandmaster.”

Last month, the DeepMind research team announced that AlphaStar achieved the coveted level this summer.

That means the program is better at Starcraft II than 99.8 percent of human players on the planet. What’s more, AlphaStar became the first Artificial Intelligence to reach the upper echelons of the real-time game.

Once again, this is a big deal. Here’s why.

Gaming Prowess of AlphaStar: Its Potential Applications

AlphaStar played with similar constraints as human players – for example, it couldn’t see the whole board. However, the limitation did not make the AI less formidable to opponents.

According to the DeepMind scientists, not only can AlphaStar adapt to new situations, but it can also multitask accordingly. As you can imagine, this ability represents a significant leap for machine learning.

The DeepMind team point out that the AlphaStar’s machine learning for multitasking has a wide range of application.

For example, it could create future self-driving cars that can adapt to new situations. Also, the algorithm could make virtual assistant smarter and more helpful than they currently are.

With that said, not everyone is optimistic about the potential application of the AI’s gaming prowess.

A machine learning expert from Dartmouth College, George Cybenko, admits that AlphaStar’s algorithm can boost recommendation systems. However, he points out that there’s a difference between being good at video games and solving real-world problems.

In an email to Business Insider, Cybenko said:

“Games like ‘StarCraft II’ are ‘closed worlds’ in the sense that the rules are fixed, the goals of the players are well-defined, and so on. The same is not true of ‘open-world’ applications such as autonomous driving, cybersecurity, military operations, finance, and trading, etc.”

Read More: Google DeepMind Develops AI to Play Hanabi Card Game

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Sumbo Bello

Sumbo Bello is a creative writer who enjoys creating data-driven content for news sites. In his spare time, he plays basketball and listens to Coldplay.

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