I would like to claim I thought similarly, but that’s such a milquetoast claim I don’t think anyone would remember. Chess is simply a search problem, trivially scalable if you just throw cash at the problem.
It was not viewed as so obviously tractable at the time. In the future, solving the game of Go will seem easy too, but it was unknown just a few years ago if we would ever solve it.
Perhaps that’s true. I also don’t see many claims with reason that go or chess is somehow a uniquely difficult problem, especially given the language turn of philosophy. NLP is the major problem moving forward with human intelligence, and this was known long before deep blue. People who talk otherwise are hyping milestones along the way, and neither chess nor go deal at all with semiotics.
I’d expect computers to best us (at some investment cost) at virtually all games moving forward except writing funny limericks. We can always have our grandmasters or whatever train the computer with their own heuristics, which recalls the paranoia of grandmasters decades ago. We understand computers better now—if you can formalize the game, the computer can beat you.
In many ways, programming is already the formalization of a human space problem. Ai will likely take more role in implementation in the future, but I can’t imagine an AI that does the formalization itself.
So this is particularly untrue for the game of Go. The game is in fact uniquely difficult as there are more board combinations than there are atoms in the universe. It is effectively impossible to brute force it as we did with chess, so a new approach had to be created. Until Deep Mind completes the task, even AI experts were genuinely unsure if we would ever solve it.
It really is a new advancement to be able to solve Go. It is not just a logical extension of work we had already done or something that would be automatically solved by faster computers. We had to invent a new approach.
I think it was fairly easy to predict the chess thing. You could even plot a graph of Elo rating of chess programs by year and see it would intersect the human max of 2800 or so at some point. I think some polish guy did that before Kurzweil and predicted 1988. Some of Kurzweil's stuff isn't that original and what it original with him is often a bit nutty. He's a good populariser though.
More controversially I'm not sure AGI is that hard to predict either. I wrote about it in my college entry essay 37 years ago and didn't thing it takes any great intellect to say if the brain is a biological computer and electronic computers get more powerful exponentially then at some point electronic ones will overtake. Of course a basic chess algorithm is fairly simple and an AGI one will be far more complicated but it can't be that mega complicated to fit in a limited amount of DNA building proteins building cells.
