“There are more possible variations of chess games than there are atoms in the observable universe.”
Patrick Kiernan.
This is mindblowing !
That is, if you have a mind, of course. On the other hand, programs like chess engines are able to analyze huge amounts of data very quickly. As a result, they can make strategic decisions that no human players are able to make. Using brute force, they do not give humans a chance in this battle. In the past, chess AI was only able to beat amateur players. But now, they can beat even the best grandmasters in the world.
Grandmasters’ highest level related to their best year
Jean-Marc Alliot (2017) Who is the Master ?
Grandmasters’ highest level related to their birth year
Jean-Marc Alliot (2017) Who is the Master ?
According to Jean-Marc Alliot’s research article, Who is the Master ? (2017), in recent years, the game of chess has undergone a transformation. Thanks to the power of artificial intelligence, chess players have been able to reach new levels of skill and accomplishment. AI-powered chess engines can pick up on things that humans might miss by looking at past games and finding patterns.
Alliot developed a scoring system to study and compare chess players across the different eras. Prior to the advent of AI, the highest Alliot score achieved by a human player was 61.1, set by Wilhelm Steinitz in 1889. However, in 2013, Magnus Carlsen eclipsed this score with a 72-point performance. While it is certainly impressive that Carlsen was able to achieve such a feat, it is important to note that he had access to resources that Steinitz could only dream of. In particular, the use of computers has allowed Carlsen and other top players to significantly improve their game.
In the world of chess, there are some “outsiders” like Lasker, who was ahead of his time, and Anand, who reached his highest level late in his career. However, the trend is very clear : the later a Grandmaster is born, the higher his best level is. In 2010, the best level for Grandmasters was 71.8. This trend is due to a number of factors. First, over the past few years, chess has become more complicated, making it harder for older players to keep up their skills. Second, younger players are simply better at learning and retaining information. They are also more likely to be trained with cutting-edge chess engines and training methods. As a result, it is no surprise that the average best level for Grandmasters has been steadily rising in recent years.
AI is likely the key factor. By harnessing the power of computer analysis, chess players are now able to hone their skills to a razor-sharp edge. As a result, the game of chess has never been more exciting or competitive.
The timeline of artificial intelligence for chess players is fascinating!
In 1948, the first chess playing algorithm was created by Alan Turing and David Champernowne. They called it the Turochamp, but it was also known as “Turing’s paper machine”. At a time when the pair of mathematicians didn’t have access to a computer, Turing would execute his algorithm by hand, on a piece of paper. Each move took more than half an hour, but it worked ! Turochamp was able to beat fairly inexperienced human opponents, such as Champernowne’s wife herself.
Deep Blue, IBM’s chess-playing supercomputer, was ready to compete after six years of development. It beat Garry Kasparov, the world champion at the time, in 1997. This victory is very symbolic : AI has finally caught up to human intelligence by beating one of the greatest intellectual champions in human history.
In 2004, Freestyle chess was introduced by Ingo Althoefer and Timo Klaustermeyer with a Blitz tournament.
“To win blitz games with the help of chess engines (or friendly grandmasters) counts as cheating. Not so here! In our Freestyle Tournament teams of arbitrary composition are invited. If Kasparov happens to be sitting on the couch next to you, just ask him to help. Or use the analysis of Fritz, Shredder or Junior to decide on your moves. ”
Ingo Althoefer and Timo Klaustermeyer
This type of chess is played by teams which may consist of any combination of human players, computer players, or computer and human players. Sounds too good to be true ? Well, in 2004, participating teams had only 7 minutes (plus a 2 second bonus) per move !
“Komodo started in 2007 as a joint project by programmer Don Dailey and myself, grandmaster Larry Kaufman, when I was a member of the team that created Rybka 3, then the world’s strongest chess engine.”
Larry Kaufman
How is Komodo different from the rest of the chess programs ?
It uses more extensions than any other top engine when considering possible moves, allowing it to look deeper than the others despite a lesser search depth. Today, Komodo is considered by many to be one of the strongest chess software programs available.
Finally, in 2018, chess.com acquired Komodo. This strategic move gives chess.com access to the powerful Komodo engine and furthers its commitment to providing the best online chess experience for players of all levels.
🤖 How AI Has Revolutionized Chess
“Chess is not a game. Chess is a well-defined form of computation. You may not be able to work out the answers, but in theory there must be a solution, a right procedure in any position. Now real games, are not like that at all. Real life is not like that. Real life consists of bluffing, of little tactics of deception, of asking yourself what is the other man going to think I mean to do. And that is what games are about in my theory.”
John Newman
One of the most significant ways in which AI has changed chess is by introducing new strategies and game variations. Human players have always had to rely on their own creativity and intuition to come up with unexpected ways to win. On the other hand, AI programs can generate thousands of possible moves and variations in a matter of seconds. As a result, they have introduced a whole new layer of complexity to the game.
♟️Chess Training
AI is playing an increasingly important role in the world of chess training and competition. Some people worry that AI will eventually replace human chess coaches and make chess tournaments boring.
“We don’t work at chess anymore, we just look at the stupid computer, we follow the latest games and find small improvements. We have lost depth.”
Evgeny Bareev, grandmaster
Other experts believe that it will actually help people become better and stronger players.
“You have a unique chance of learning more about the game of chess with your computer than Bobby Fischer, or even myself.”
Garry Kasparov, grandmaster.
1. AI = Accommodating Partner
Computers are always ready to challenge their human opponents, no matter when or where they prefer to play or practice for competition. If the human player makes a mistake, the AI will simply point it out and provide immediate feedback useful for improvement. What’s the best part? It’s not such a bad thing to lose because the machine partner will never boast about it!
2. AI = Room for Error and Improvement
By being so accommodating, chess-playing computers give people the opportunity to fail as much as they need to. Yes, failure is a good thing ! It is actually a crucial part of any learning process.
“Mistakes are an inevitable and important part of promoting learning and deeper understanding.”
Thomas J. Wenzel
3. AI = Shorter Learning Curve
AI engines can analyze positions and offer strategic suggestions to players in real-time by analyzing vast databases of past games and the many moves still possible in the game, in a matter of seconds. Immediate feedback is crucial in the learning process. In fact, several studies show that we learn better and faster when we are instantly corrected.
4. AI = Lower Training Cost
The typical way of training involves having a human coach monitor and provide comments on the games. This, however, may be costly and time-consuming. Luckily, artificial intelligence has the ability to automate this process.
AI can provide chess players with unprecedented levels of analysis and feedback. Furthermore, AI-based chess training is frequently less expensive than traditional coaching, making it more accessible to a broader range of players. There are now numerous chess-playing programs available online, and anyone can use them to improve their skills.
5. AI = Personalized Learning Modes
Chess AI is becoming increasingly advanced in terms of mimicking human player behavior and adapting its level and style of play. A player’s talents and shortcomings can be taken into account to create a virtual opponent that is both challenging and rewarding at the same time. As a result, chess players can get training that is specifically tailored to target their own strengths and weaknesses, allowing them to progressively and continuously improve their level.
6. AI = Analytical Tool
Counterfactual Analysis
One of the benefits of using AI to study chess is that it can provide counterfactual analysis. This means that AI can be used to determine what would have happened if a different move had been made. It’s a kind of what if? analysis and is a useful way for testing cause-and-effect relationships. It can also be used to create new game variants. In general, counterfactual analysis is a powerful tool that can be used to improve our understanding of any system.
Understanding the Other Player’s Intentions
In the game of chess, understanding our opponent’s intentions is essential to making the right moves. But how can we guess what they’re thinking? Artificial intelligence may hold the key ! By analyzing a vast database of past games, some chess engines can identify patterns in a player’s strategy and make predictions about their next moves. Researchers recently showed that the latest AI chess technology can go as far as recognizing a specific playing style and figuring out who is actually playing.
🎯 From Tactical to Strategic Games
One of the most important and challenging aspects of chess is making the transition from tactical to strategic play. In the early game, players focus on developing their pieces and controlling key squares on the board. However, as the game progresses, they must begin to think several moves ahead, anticipating their opponent’s plans and preparing for a long-term battle.
This can be a difficult task for even the most experienced players, but new AI technology is beginning to change the landscape of chess. By looking at past games and finding patterns, it helps players decide how to approach the middle game and the end game in their own way. Yes ! Chess players of all skill levels can now use AI to help them plan their strategy and play beyond the implementation of simple tactics.
🧠 From Tactical to Psychological Games
There are several ways to win at chess. Checkmate is by far the most common answer. In that scenario, the king is put into a position where it cannot move without being captured. However, there are other ways to win, such as capturing all of the opponent’s pieces or putting them into a position where they cannot make a legal move.
AI has enabled people to discover and memorize many new game variants and strategies. Thanks to the Internet this information is available to everyone at any time. Some people think that AI has destroyed the game, taking all the fun out of it. Not so fast ! Let’s have a look at the match between Magnus Carlsen and Ian Nepomniachtchi on December 3rd, 2021 : it was awarded the world longest chess game, lasting 7 hours 45 minutes for 136 moves ! So, what is happening to the game of chess today ? Since players have access to the same database of tactics and strategies, winning eventually comes down to what AI cannot teach us : mental toughness.
“We’ll have to be more creative and more human, because that’s the way to make the difference.”
Garry Kasparov, grandmaster.
🧬 Towards Hybrid Games
It has now become clearer that computers master strategy while people specialize in psychology. So, who is the best player in the world today ? We would be tempted to answer Magnus Carlsen or even Deep Blue. We would be wrong ! It’s a group of amateur chess players (Anson Williams, Yingheng Chen, and Nelson Hernandez) and the computer programs they’ve built named “Intagrand.” Back in 2017, the team won 23 games, drew 27 games, and lost just one game. Against grandmasters, it had a perfect 2–0 record.
“With augmented intelligence, we harness both the computing power of machines and the power of human creativity to drive greater results and to free humans to do the creative labor at which we excel.”
Garry Kasparov
Chess is becoming even more challenging and exciting than ever before !
⚽ AI in Other Sports
Football is a complex sport that involves many different players’ physiologies, and as such, the need for an AI during their training is becoming increasingly important. In most team sports, each player has a specific role to play, filling a specific position that requires a unique set of skills.
As the game has evolved, so too have the strategies and tactics used by teams. This has made it increasingly difficult for human coaches to keep up with the evolution of the game. Football AI programs are able to quickly analyze large amounts of game data. It evaluates and develops strategies tailored to a team and each of its players, adapted to target the opponent team’s weaknesses.
🏇 AI and Horse Racing
Another area where AI is really starting to take off is in horse racing. Alezan.ai is an AI tech company that is taking the industry by storm. It provides products and services to broadcasters to improve punters’ experience in a big way. Building augmented reality with computer vision AI, its technology improves how people watch and wager on horse races.
- Alezan.ai changes the game when it comes to horse racing, making it more accessible and readable for everyone involved.
References
- Kiernan, Patrick. Which is greater? The number of atoms in the universe or the number of chess moves? | National Museums Liverpool | www.liverpoolmuseums.org.uk.
- Grafenauer, Anja (2020). At What Age Is It Harder to Learn? | Aging Greatly | www.aginggreatly.com
- Kasparov, Garry and Friedel, Frederic (2017). Reconstructing Turing’s “paper machine.” | www.easychair.org.
- Campbell, Murray, Hoane , A. Joseph and Hsu, Feng-hsiung (2001). | Deep Blue — ScienceDirect | www.sciencedirect.com
- ChessBase (2004). Freestyle Blitz Tournament | www.en.chessbase.com.
- ChessBase (2016). Komodo: Birth of a chess engine | www.en.chessbase.com.
- Alliot, Jean-Marc (2017). Who is the Master? | Download PDF Article
- Harmon, Hamy (2003). More Chess Players Use Computers for Edge.| www.archive.nytimes.com
- Holodny, Elena (2017). Kasparov on interplay between machine learning and humans | Business Insider | www.kasparov.com.
- Wenzel, Thomas J. (2002). Using mistakes as learning opportunities. | AC Educator | Download PDF Article.
- Stenger, Marianne. Meaningful Feedback for Students: 5 Research-Based Tips. | Edutopia| www.edutopia.org.
- Carbonell, Felipe Morales (2020). Game Counterpossibles. | Download PDF Article
- Hutson, Matthew (2022). AI unmasks anonymous chess players, posing privacy risks | Science | AAAS | www.science.org
- The 10 best places to play chess online — Chess Strategy Online. | www.chessstrategyonline.com
- Matuschek , Michael (2020). Using Adaptive AI to Improve the Gaming Experience | Bench Talk | www.mouser.com
- McIlroy-Young, Reid, Wang, Russell, Sen, Siddhartha, Kleinberg, Jon and Anderson, Ashton (2020). Learning Models of Individual Behavior in Chess. | Download PDF Article
- The Difference Between Strategy and Tactics in Chess | www.chessfox.com
- Pogonina, Natalia (2010). Chess Psychology | www.chess.com
- Holodny, Elena (2017). Kasparov on interplay between machine learning and humans | Business Insider | www.kasparov.com
- Sikka, Nikhil (2021). On chess and the value of strategic and tactical thinking in Analytics/AI teams | www.linkedin.com
- How artificial intelligence is empowering the actors of the football industry | Sia — Data Science Lab. |www.datascience.sia-partners.com
- Colle, Pierre (2022). What AI can do for horse-racing ? | Download PDF Article