Miscellaneous

This video starts with a history background about the game chess and about
the computer chess machine . Also there is an explanation about the evolution
of computer chess. There is an explanation about the main algorithms that
are being used in computer chess, which are the minimax algorithm and the
alpha-beta pruning(steps,animations,etc).

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Robots from Intel Labs Seattle/UW CSE, Carnegie Mellon University, the University of Alabama, and Georgia Tech playing chess at AAAI 2010.

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Watch this fun animation of a humanoid robot featuring Robolink articulated joints from igus playing chess against itself.

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Watch how chess openings have changed in tournament games between 1850 and 2014.
Randy Olson

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Chief of Naval Operations Adm. John Richardson talks about the U.S. Navy's future incorporation of artificial intelligence tech, by discussing chess, during a discussion with leaders and researchers at the Institute for Defense Analyses.

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In this episode of the Fellowship of the things Creative Engineer Sarah builds two Chess boards that play over WiFi, so you can play someone on the other board from anywhere on a physical Chess board.

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Our goal is to allow people to connect and play board games with each other from anywhere in the world. By combing a physical board with modern technology, we hope to bring a more interpersonal experience that is not achieved through a computer screen. See our other videos for a look inside the system and how moves such as castling and en passant are handled.

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A view of the insides

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Positronics demonstration video of a robot programmed to play an interactive chess game against real people. Featuring a UR5 robot and Robotiq end effector.

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The question, “can a machine be made to think like a person?” has always been tied to strategy games. Games, with their clear rules and obvious winners and losers, were perfect proving grounds for early computer scientists, who could break them down into clearly defined problem sets. Audiences could marvel at the progress of man vs machine face offs, even if they didn’t fully understand the underlying technology.

The earliest AI game systems relied on a brute force, top-down approach: programmers downloaded every possible outcome into their AI systems, which were built around narrowly defined, rule-based criteria. In the 1950s, the earliest versions of neural networks and machine learning arrived. This represented a shift towards bottom-up programming, systems designed to determine the probability of various outcomes based on training data. One early system, a virtual rat solving a maze, was made up of vacuum tubes, motors, and clutches. As the rat navigated, the machine learned and shifted probabilities.

IBM debuted their first AI Grand Challenge — a multi-year effort meant to push the limits of artificial intelligence — in 1997. Deep Blue beat reigning chess world champion Gary Kasparov, and was seen as the final triumph for the top-down approach. In the last decade, advances in machine learning, deep learning, and natural language processing paved the way for AIs like Watson on Jeopardy!, AlphaGo, and Dota 2—increasingly complex systems that still existed within the framework of games.

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A robotic arm is not only a tool for assembly, palletizing, and other routine production tasks. It has endless possibilities for creative automation. Our chess robot is an example of such a creative project.

Together with the SIA, we developed a PULSE robot chess player.
The metal instructor is already installed in one of the Belarusian chess schools where it helps children learn one of the oldest board games.
Feel the PULSE of automation.

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Computer Chess Engines have gotten stronger each year with current engines like Alphazero, Stockfish, Komodo, and Leela Chess Zero reaching new levels of perfection monthly! Check out how computer engines have developed in the last 30+ years, from weak machines, easily dominated by humans, to monsters!

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