The real world doesn’t resemble chess


When a computer beats the chess grandmaster, what comes next?

on may, 11th, 1997 garry kasparov — russian chess Grandmaster – gave the last game against IBM’s deep blue supercomputer. A normal high-level chess game lasts up to four hours, but Kasparov gave up after a careless mistake before an hour was up. The machine “played like a god,” he said. this victory provoked reactions from the public; if AI could beat the world’s sharpest chess mind, what’s next? Perhaps computers could soon overwhelm humans in various fields – something that has not happened, at least until now.

development began in 1985 at carnegie mellon university under the name chiptest. it then moved to IBM, where it was initially renamed Deep Thought. and then renamed “deep blue” again in 1989. To play chess, Deep Blue could predict a move, calculate possible moves from there, reject those that seemed hopeless, and take the profitable routes. and then repeat the process over and over again.

In February 1996, IBM thought it was finally ready to face Kasparov for the first battle. although deep blue won one game, kasparov won three and won the match. IBM called for a rematch, and his team spent the next year building even faster hardware. in may 1997, kasparov and deep blue met again to repeat the competition. Even though the computer was twice as fast as before, processing 200 million chess moves per second, IBM wasn’t sure it would win. After making a bad mistake early in the game, Kasparov was convinced he had no chance of winning. and then his performance got worse, resulting in him losing the fight.

after Garry Kasparov defeated Deep Blue in 1996, IBM asked him for a rematch, which was contested in New York City on an improved machine

Image by Adam Nadel © Review of MIT technology

The real world doesn’t resemble chess

Even after two wins and three draws against the chess grandmaster, scientists still doubted whether machines could ever really beat the human brain. Computers were better than humans at short-term movements. Deep Blue could easily find the best pick a few moves in advance. What the computer lacked, however, was strategy. and the people were still ahead of the pack. However, Kasparov’s wrong move that threw him into failure increased the company’s market cap to $11.4 billion in a single week.

sounds paradoxical, but this victory left nothing useful in its path. it had nothing to do with human thoughts. The rules were clear with no hidden information, and a computer didn’t even have to pay attention to what had happened on previous turns. it only evaluates the position of the characters at a given point in time. “It didn’t lead to the breakthroughs that made it possible [deep blue] AI will have a huge impact on the world,” says Campbell, one of the developers of Deep Thoughts. “There are very few problems where, like chess, you have all the information you need to make the right decision.” Campbell adds. “Most of the time there are unknowns. there is coincidence.’

knowledge of facts of the world could take AI a step further. The problem, as many computer scientists have come to suspect, is that nobody quite knows how to build neural networks that can think rationally or use common sense. Shortly after his loss to Deep Blue, the Russian chess grandmaster claimed that fighting an AI made no sense. The machine “thinked” in fundamentally inhuman ways and used brute force mathematics. it would always have a higher short-term tactical capability.

after his match against deep blue, kasparov argued that he sees the future of AI in working with human intelligence, rather than beating or replacing it.

However, unlike Deep Blue and Deep, newer AI systems like GPT-3, Gopher and others rely on multi-layer neural networks trained on vast amounts of data. To learn more about the evolution of AI, visit Review of MIT technology.

The history of AI reminds us: the real world is nothing like chess
Photo by Jent Jiang on unsplash

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