Isabella Kwai, At 5, She Picked Up Chess as a Pandemic Hobby. At 9, She’s a Prodigy. NYTimes, July 21, 2024.
Since learning chess during a pandemic lockdown, Bodhana Sivanandan has won a European title in the game, qualified for this year’s prestigious Chess Olympiad tournament, and established herself as one of England’s best players.
She also turned 9 in March. That makes Bodhana, a prodigy from the London borough of Harrow, the youngest player to represent England at such an elite level in chess, and quite possibly the youngest in any international sporting competition.
“I was happy and I was ready to play,” Bodhana said in a phone interview, two days after she learned that she had been selected for this year’s Olympiad, an international competition considered to be the game’s version of the Olympics.
The fourth-grader, who learned chess four years ago when she stumbled across a board her father was planning to discard, knows exactly what she wants to accomplish next. “I’m trying to become the youngest grandmaster in the world,” she said, “and also one of the greatest players of all time.”
Chess is one of the arenas in which prodigies emerge. Music and math are others. Why? I assume it has something to do with their brains. What?
I note also that playing chess has been central to the development of AI and that it is the first arena in which computers and equaled and then surpassed the best human performance. What can we make of that? I don’t know, but surely there’s something to be discovered here.
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Note the final paragraph of this post, On the significance of human language to the problem of intelligence (& superintelligence).
The question of machine superintelligence would then become:
Will there ever come a time when we have problem-solving networks where there exists at least one node that is assigned to a non-routine task, a creative task, if you will, that only a computer can perform?That’s an interesting question. I specify non-routine task because we have all kinds of computing systems that are more effective at various tasks than humans are, from simple arithmetic calculations to such things solving the structure of a protein string. I fully expect the more and more systems will evolve that are capable of solving such sophisticated, but ultimately routine, problems. But it’s not at all obvious to me that computational systems will eventually usurp all problem-solving tasks.
