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Smart Chess Sets

The Centaur Smart Chess Set Adapts Its Difficulty to Player's Ability

— September 4, 2019 — Tech
A 25-year-old digital chess company called Digital Games Technology created the Centaur Smart Chess Set that is capable of learning a player's level of skill and adjust the kind of challenges it offers with each move accordingly. The chess set looks like a regular chessboard, complete with a physical board and tangible pieces, unlike games of chess that are only carried out on a computer.

To make people feel as if they are truly playing with another person, the smart chess board indicates its moves with an LED light, so that the pieces from the other side can be moved manually to the indicated area—or a different one if desired, so long as it is a legal move within the game.

The board also includes an e-paper display where the settings can be adjusted and hints can be received.
Trend Themes
1. Adaptive Chess Sets - The Centaur Smart Chess Set adapts its difficulty to a player's ability, offering a personalized gaming experience.
2. Physical-digital Hybrid Games - The Centaur Smart Chess Set combines the physicality of a traditional chess set with the interactive capabilities of a digital game, bridging the gap between traditional tabletop games and technology.
3. Intelligent Chess Boards - The Centaur Smart Chess Set utilizes artificial intelligence to analyze player skill levels and provide tailored challenges, revolutionizing the way chess is played.
Industry Implications
1. Gaming - The gaming industry can explore the potential of adaptive chess sets to create personalized gaming experiences and attract a wider audience.
2. Consumer Electronics - The consumer electronics industry can develop new physical-digital hybrid games that combine traditional gameplay with innovative technology, catering to the demand for interactive and immersive experiences.
3. AI and Robotics - The AI and robotics industry can leverage intelligent chess boards to showcase the capabilities of artificial intelligence and drive advancements in adaptive learning and problem-solving algorithms.
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