Google's DeepMind can control a robotic arm to beat mere mortals at table tennis, a new study reports, according to Live Science.

But professional tennis players can rest easy. The artificial intelligence (AI)-powered robot could only beat mediocre players, and only some of the time, according to the study, which was published to the preprint database arXiv and has not been peer-reviewed.

"Achieving human-level performance in terms of accuracy, speed and generality still remains a grand challenge in many domains," the researchers wrote in the study.

To overcome this limitation, the researchers combined an industrial robot arm with a customized version of DeepMind's ultrapowerful learning algorithm.

DeepMind uses neural networks, a layered architecture that mimics how information is processed in the human brain, to gradually learn new information.

As the AI learned, the researchers also collected data on its strengths, weaknesses, and limitations. Then, they fed this information back to the AI program, thus giving DeepMind's unnamed agent a realistic impression of its abilities. The system then picked which skills or strategies to use in the moment, taking into account its opponent's strengths and weaknesses, just like a human table-tennis player might. 

Then, they pitted their AI-controlled robot against 29 humans. DeepMind's robot arm beat all of the beginners and about 55% of the intermediate players, but it got trounced by advanced players. In an international rating system, it would be a solid amateur player.

DeepMind's robot arm did have some systematic weaknesses, however. For example, it struggled with high balls and, like many of us, found backhand shots more challenging than forehand ones.