The DeepMind team from Google developed a ping-pong-playing machine that is almost as good as an amateur human, which is quite a milestone for robotics and artificial intelligence. With its smart AI, this robotic arm can rival humans playing in real-time by changing strategy during the game and even beating them in some cases.
Key points
This robot consists of a mechanical arm mounted on tracks to allow it to move around freely. It has high-speed cameras that keep track of the ball and the player it's facing. The uniqueness of this robot lies in its “brain” –an advanced AI system that combines particular table tennis skills with decision making during gameplay.
In tests, 29 humans players were put against the robot at different levels of skill. Against beginners, it won all matches and 55% against intermediaries but was beaten by advanced players in all matches. In general, the robot managed to win 45% games proving its being useful for non-professional purposes.
Most interestingly, how did they train AI? Some computer simulations were combined with real-world data by researchers. They would start small with some tidbits about human play then let loose the robot to battle with actual people. Any new match provided more data which was fed back into simulation so as to improve further training. This process was repeated many times allowing the machine to become better and stronger adapting itself across various playing styles.
Strangely enough, even those who lost still enjoyed playing against this kind of robot. On another note; many considered it fun or enjoyable; thus indicating possible usefuless of AI in sports practice and amusement parks among others Nevertheless however, there are still some flaws within our bot: it doesn't handle really fast or high balls well; it finds intense spin difficult to read; and is weaker at backhand strokes.
However, their implication does not only revolve around table tennis but also cover wide range of robotic works requiring fast responses and adaptation to the uncertain human behavior. For instance, this could be used in manufacturing industries, healthcare among others where robots should interact with people with skill and safety.
While this is a remarkable achievement for a robot, its creators admit that it is only a step towards creating many different kinds of useful real-world robots that can do things as well as humans. There is still much progress required to reach human level performance across tasks and also develop robots that are safe and efficient in daily human settings.
In general, projects like this table tennis robot help to push the boundaries of what can be achieved as robotics and AI continue advancing, bringing us closer to an age when machines can assist or talk with humans more intelligently.