Deep Thinking

Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins (2017) by Garry Kasparov and Mig Greengard is a book that looks at how machines eclipsed people in playing chess and what this means for humanity.

Kasparov is one of the greatest chess grand masters of all time and the last human to be the best chess player on the planet. In 1997 Deep Blue defeated him taking the crown for an activity that was once seen as the epitome of human intelligence.

The book looks at how computers play chess, how they were initially fairly week and how in the late 1980s they began to become as good as the best human chess players and finally beat them.

The story of the actual game shows that Kasparov believes, it appears with good reason, that his loss to IBM’s Deep Blue involved quite a bit of unfair play. The machine was allowed access to his back catalogue and was quite possibly altered during the game. However, he also makes it clear that if he had won that game he would have lost within a few years. Computers had become too good.

Kasparov goes on to reflect on how this has changed chess, how modern grand masters use computers very differently and how the combination of humans and chess computers is, for the moment, better than just computers on their own. He also reflects on how this doesn’t mean that the singularity is near and the book has a great quote from Andrew Ng, the Machine Learning expert from Stanford, Baidu and Google who says that worrying about super-intelligent computers is like worrying about overcrowding on Mars.

The book is very interesting in parts but also quite dull in parts. You’d really have to be a great chess aficionado and someone who is interested in what a smart, informed person has to say about AI to really appreciate it all. And even then you’d probably find it sags in the middle. However it certainly contains insights from someone with a unique perspective on chess and AI.


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