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In 2021, Nikhil Kamath, founder of Zerodha, defeated five-time world champion Vishwanathan Anand in chess with the help of computers (he confessed later on) at a celebrity fundraiser. The controversy sparked discussions around the use of AI in the game of chess.

As India is all set to host the 44th edition of the Chess Olympiad in Mahabalipuram starting on July 28, lets look at how AI has impacted the game of chess.

The earliest mention of technology in chess can be traced back to the 18th century when Austrian empress Maria Theresa commissioned a chess-playing machine. Many players competed against the Mechanical Turk, thinking it was an automated machine. However, it turned out to be a scam. A human hidden inside the machine was operating it.

In the mid-1940s, British mathematician Alan Turing began theorising how a computer could play chess against a human. In 1949, Claude Shannon published a seminal paper describing a potential program to do exactly that. In 1950, Alan Turing created a program capable of playing chess. Soon after, the Dietrich Prinz and Bernstein chess program burst into the scene.

Computer chess appeared for the first time in the 1970s. MicroChess, the first commercial chess program for microcomputers, in 1976; Chess Challenger in 1977; and Sargon, which won the worlds first computer chess tournament for microcomputers, in 1978.

The robotic chess computers came about in the 1980s. Boris Handroid, Novag Robot Adversary and Milton Bradley Grandmaster are some examples. The most popular was Chessmaster 2000, which ruled the chess video and computer games industry for the next two decades.

As chess computers were gaining popularity in the 1980s, Gary Kasparov, the then world chess champion, claimed AI-driven chess engines could not defeat top-level chess grandmasters. However, in 1989 and 1996, Kasparov beat IBMs powerful chess engines, Deep Thought and Deep Blue.

Things started to change in the late 1990s. In 1997, Deep Blue defeated Kasparov. A year later, Kasparov came up with the idea of Cyborg chess or centaur chess, in which human and computer skills are combined to up the level of the game. The first cyborg chess was held in 1998.

In 2017, AlphaZero, a computer program developed by DeepMind, defeated the worlds strongest chess engine Stockfish. AlphaZero used the reinforcement learning technique in which the algorithm mimicked humans learning process to train its neural networks.

In 2018, TalkChess.com released Leela Chess Zero, developed by Gary Linscott (who also developed Stockfish). Without having any chess-specific knowledge, Leela Chess Zero learned the game based on deep reinforcement learning using an open-source implementation of AlphaZero.

In 2019, DeepMind came up with another algorithm based on reinforcement learning called MuZero.

Chess players use AI-driven chess engines to analyse their and competitors games. As a result, AI has helped in improving the quality of games.

Post pandemic a lot of chess competitions were moved online. In the European Online Chess Championship, as many as 80 participants were disqualified for cheating. FIDE, the international chess body, has approved an artificial intelligence-driven behaviour-tracking module for the FIDE Online Arena games. Chess.com, an internet chess server, uses a cheat detection system to assess the probability of a human player matching the moves of a chess engine or surpassing the games of some of the greatest chess players with the help of a statistical model. DeepMind is also working to develop a new cheat detection software.

AI has also brought down the cost and effort of training and helped develop new chess strategies.

AI has indeed changed the dynamics of the game. However, using AI in chess has raised a few issues. Computer chess engines have significantly improved gameplay. However, people have also raised concerns that players of this age depend too much on machine-driven analysis.

Even when it comes to detecting cheating, AI poses a few issues. First, there is a possibility a player might be wrongly red-flagged by AI. For example, a Chess.com player and grandmaster, Akshat Chandra, was banned after a win against Hikaru as his moves supposedly matched Komodo, a strong positional chess engine. Though Chandra has been proved innocent, his reputation took a hit.

Chess engines and deep learning-based neural networks present enormous possibilities. Moreover, the complex nature and the strategic orientation of the game have provided a ground for assessing any progress in the field of artificial intelligence. They (games) are the perfect platform to develop and test ideas for AI algorithms. Its very efficient to use games for AI development, as you can run thousands of experiments in parallel on computers in the cloud and often faster than real-time, and generate as much training data as your systems need to learn from. Conveniently, games also normally have a clear objective or score, so it is easy to measure the progress of the algorithms to see if they are incrementally improving over time, and therefore if the research is going in the right direction, said DeepMind cofounder Demis Hassabis.

More here:
Chennai Chess Olympiad and AI - Analytics India Magazine

Melanie Mitchell, an AI researcher at the Santa Fe Institute, is also excited to see a whole new approach. We really havent seen this coming out of the deep-learning community so much, she says. She also agrees with LeCun that large language models cannot be the whole story. They lack memory and internal models of the world that are actually really important, she says.

Natasha Jaques, a researcher at Google Brain, thinks that language models should still play a role, however. Its odd for language to be entirely missing from LeCuns proposals, she says: We know that large language models are super effective and bake in a bunch of human knowledge.

Jaques, who works on ways to get AIs to share information and abilities with each other, points out that humans dont have to have direct experience of something to learn about it. We can change our behavior simply by being told something, such as not to touch a hot pan. How do I update this world model that Yann is proposing if I dont have language? she asks.

Theres another issue, too. If they were to work, LeCuns ideas would create a powerful technology that could be as transformative as the internet.And yethis proposal doesnt discuss how his models behavior and motivations would be controlled, or who would control them. This is a weird omission, says Abhishek Gupta, the founder of the Montreal AI Ethics Institute and a responsible-AI expert at Boston Consulting Group.

We should think more about what it takes for AI to function well in a society, and that requires thinking about ethical behavior, amongst other things, says Gupta.

Yet Jaques notes that LeCuns proposals are still very much ideas rather than practical applications. Mitchell says the same: Theres certainly little risk of this becoming a human-level intelligence anytime soon.

LeCun would agree. His aim is to sow the seeds of a new approach in the hope that others build on it. This is something that is going to take a lot of effort from a lot of people, he says. Im putting this out there because I think ultimately this is the way to go. If nothing else, he wants to convince people that large language models and reinforcement learning are not the only ways forward.

I hate to see people wasting their time, he says.

See the article here:
Yann LeCun has a bold new vision for the future of AI - MIT Technology Review

2022 marks the 35th anniversary of one of the most iconic video game series of all time Street Fighter. It looks like the folks over at Capcom are celebrating with a slick new website focused on paying tribute to the franchise's legacy.

The special website has sprouted up and features a handful of cool things related to over three decades of fighting streets. Most notably on this site, however, is an impressive history log that includes initial release dates for seemingly every main Street Fighter game that has been released over these last 35 years.

As one might expect, this website is available in both Japanese and English, though portions of it are strictly in Japanese.

Those who visit are greeted with a message from the Street Fighter development team. What serves as a big thank you to fans also talks about the expansion of the series from a video game to other media and how more content is in the works for the 35th anniversary.

There are also news updates pertaining to Street Fighter here, and a few new pieces of artwork from classic Capcom artists to look over. On top of that, many of the main members of the development team have clickable cards where they've left their own words on the series' 35 years, though all of these messages remain in Japanese despite switching the language over.

The coolest thing about this website, though, is the title release timeline that starts with the original game on August 30, 1987 and runs all the way up to Street Fighter 6 in 2023.

It isn't often that we see all of these initial release dates gathered together like this, and it really is eye opening when you look it all over.

From what we can see, all of the main Street Fighter series are represented here. Street Fighter 1 - 6, Alpha (Zero), and some of the compilations / special releases are also included.

This history trek also notes the platforms each game was available on and on what day they launched.

If you're a fan of Street Fighter, it is definitely worth it to head to the new 35th anniversary website and have a look around.

See the rest here:
Special Street Fighter 35th anniversary website launched, features impressive timeline of game release dates over the years - EventHubs

With modern chess engines operating at hundreds of points stronger than the best human players, its clear we mere mammals are officially a relic of the past. While computer scientists and technological hobbyists push the limits of existing Artificial Intelligence to uncover as much of the infinite unknown hidden in a single game of chess, a new forefront of AI is emerging in the chess world.

Its not a meticulous exploration of a 300-move theoretical rook-bishop endgame between Leela and AlphaZero no, its a nightmarish, meme-driven flight of fancy powered by DALL-E mini, a free AI-based image generating program.

In a world of proliferating doctored images and deepfakes, this kind of tool could bend chess culture and history, especially in an age where reality and illusion blur more seamlessly each day. But at what cost may we wield such power?

In the name of science, we at Chess Life Online have decided to put DALL-E mini to the test to see what awaits us in this new frontier. The premise is simple: type in a prompt and DALL-E will create the image for you. Sometimes it gives you exactly what you want. Other times, well just look below.

We'll be sure to keep exploring this technology as it continues to evolve and inevitably haunts our dreams. Is there a prompt you'd want to see or have already tried? Share it with us below or tweet it to us @USChess.

Here is the original post:
The Nightmarish Frontier of AI in Chess - uschess.org

It had to happen sometime.

All four games were drawn today at the 2022 FIDE Candidates Tournament in Madrid, Spain. Some games like the 30 move snoozefest from GMs Teimour Radjabov and Ian Nepomniachtchi were limp affairs from the get-go.

Image Caption

courtesy FIDE / Stev Bonhage

Others, like the draw between GMs Fabiano Caruana and Jan-Krzysztof Duda, showed a bit of promise from the outset, but soon sputtered, never really getting going.

Image Caption

courtesy FIDE / Stev Bonhage

But GM Ding Liren will look back on Sundays third round as an opportunity lost. After gaining an edge in a topical Grnfeld, Ding struggled when GM Richard Rapport muddied the waters, and after finding the correct move on the 22nd move, he missed the critical continuations on moves 23 and 27, and the game was draw after the time control.

The game of the day was undoubtedly the battle between GMs Alireza Firouzja and Hikaru Nakamura. Our guest annotator GM Jacob Aagaard provides a pithy, accurate description of the encounter.

Nakamura has played this variation many times and so far held all the games against his colleagues. It is the most solid corner of his repertoire. Firouzja comes with an interesting idea, but does not manage to rattle Nakamura, who finds all the right moves. But low on time in the endgame, Black gets into some problems, which he had to solve with great accuracy to draw the game. This was definitely the best effort of the day.

Will this near-miss haunt Firouzja? Will it energize Nakamura? He seemed fairly chipper in his post-game recap for his YouTube channel, saying he was pleased with his play and the result.

Monday is a rest day in Madrid, the first of four during the event. Caruana and Nepomniachtchi lead at this first interval at 2/3, but of course no one (save perhaps Radjabov) is out of contention so early in the contest.

Play resumes Tuesday at 9 a.m. Eastern. Pairings are:

Rapport NakamuraNepomniachtchi FirouzjaDuda RadjabovDing Caruana

FIDE Candidates homepageUS Chess Candidates homepageCandidates Overview (including streaming links)Lichess analysis study (Aagaard)Round 1Round 2

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Four Draws in Round Three of 2022 Candidates | US Chess.org - uschess.org