At MLDS 2024, India’s biggest generative AI conference, Viswanathan Anand, spoke about AI and chess, and how he uses ChatGPT to make chess training exercises and explain moves.
“ChatGPT is essentially statistics applied to language,” said Anand, explaining that language is a fundamental way of how we learn anything. “That’s the key connection.”
Citing chess, he said that it [ChatGPT] gives you the correct answer as long as you specify the rules and the terms of the game. “Understanding this is very hard unless you are trained in chess,” he added.
He said it is difficult to learn from it, because the moves these AI systems show are typically hard to explain, and when amateur players copy those moves hastily it generally backfires on them.
On the bright side, he noted that if used wisely AI helps players save a lot of time in learning new moves, and understanding their opponent better.
Chess in the Era of AI
Now that everyone has access to tools such as ChatGPT and Bard that will push players towards being more creative in a game, and learn faster. How can one differentiate themselves to be a better player?
“So the first thing is extra familiarity and the next is asking more questions,” he explained. The better player, according to Anand, examines not only the best moves, but the next seven or eight moves which the opponent has neglected.
He said that this is a game of constant improvements, and one has to come up with entirely new systems. “What I believed to be the truth when I was younger is only maybe 52% true,” he said, stating that with AI, the game of chess has changed significantly.
Today the players have to be willing to sit there with the AI system, playing training games and willing to forget their comfort zone, Anand said. Instead they have to test individual positions and go over the new moves over and over again until it works.
Thanks to AI, there’s a lot of scope for doing things much faster. “Instead of spending hours just pulling up statistics about my opponent, I can instead use AI or ChatGPT for the details I need.”
AI in Chess
Anand said AI can never replace humans in chess, even though it is getting better at it. “Chess is still a human game.”
OpenAI chief Sam Altman also echoed similar views, at Davos WEF, said, “Chess has never been more popular than it is now, and almost no one watches two AIs play each other, we are very interested in what humans do.”
Anand said chess doesn’t have a finite number of sensible moves, and AI can never nearly solve chess. “There isn’t a finite number of steps in chess. I don’t think it will be solved given the large number of even the sensible moves to be analysed by the computer,” he added.
He said that he likes to play with humans over AI anyday, but uses AI to practise.
In 2016, AlphaGo beat Lee Sedol four times out of five. The efforts with chess go further back to 1985, when IBM’s Deep Blue first lost to Garry Kasparov but promptly came back next year to win.
But the general fear that this will take the fun away from games is overrated. We’ve evolved from Houdini and Rybka to AlphaZero progressively getting better at the game that effortlessly beat any Chess Grandmaster.
The most significant demonstration of AlphaZero’s capabilities was a series of games played against the popular chess engine Stockfish 8. The battle between the best human-designed chess engine and an AI system that had taught itself how to play was watched by millions of chess enthusiasts.
Not only chess, AI agents are making progress in beating humans in video games and even physical games.
Anand Intelligence (AI) in Chess
Anand was taught to play chess by his mother Sushila Viswanathan at the age of six. He continued playing at the Tal Chess Club in Chennai backed by Soviet funds, which is one of the reasons for Chennai becoming the capital of Indian chess.
The biggest difference between playing chess before, and after the advent of computer programs and then AI is the approach to the game. Anand said, “I’m not even trying to come up with new ideas myself now. The computer gives me the idea, I use it to navigate the lines of moves ahead and reason it out.”
This is very different from when he was a child he used to come up with the idea, check all the lines and implement it. “Now I don’t do anything. All I need to do is to keep asking questions. And so over, over a long enough time period, you suddenly look back and you realise you’re a completely different player,” he explained.
In the world championship in 2008 against Kramnik who had always won against Anand playing the white pieces. “Because of the computers which were still reasonably primitive then, I was able to pull out the statistics and practise the moves deviating from my usual King’s Pawn opening,” he said. Anand explained that previously it would have taken him years to work the trial and error method and practise a new opening and really familiarise himself with it without computers.
