Comment by drb91
8 years ago
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.