AI

Don't over-focus on chess. The Lesson is that if you take two identical machine-learning labs which currently have a working model today, and ask them to come back and show you how much they improved in a year or so, the lab which forward-ports the model to newer hardware will tend to outperform the lab which tries to tweak the model to fit the problem domain more precisely. Sheer amounts of compute dominate any sort of domain-specific (here, chess-specific) knowledge. Further, there's a suggested mechanism, Moore's Law, which is tapering off now but used to be exponential; how could a polynomial amount of effort ever compete with exponentially-better new hardware?