One talk in particular in which he focuses on this idea, including with facts and figures from research literature, is a talk he gave a while ago called "Theori

One talk in particular in which he focuses on this idea, including with facts and figures from research literature, is a talk he gave a while ago called "Theorizing from Data": http://www.youtube.com/watch?v=nU8DcBF-qo4 http://www.youtube.com/watch?v=nU8DcBF-qo4 . You should definitely watch it if you haven't seen it before. Norvig states his opinion slightly differently: of course being smart about algorithms is good. But until you get a lot of it, you often can't even fairly evaluate different algorithms. It's only when you're no longer getting significant gains from more data that you should then start thinking about being an algorithm smartypants.