A better way, when can do it: From basic game theory, each board game such a Go, chess, checkers, Nim, has an optimal strategy. Then the only issue left is wh

A better way, when can do it: From basic game theory, each board game such a Go, chess, checkers, Nim, has an optimal strategy. Then the only issue left is who moves first. If the advantage is to the player who moves first, then they should always win; similarly for the player who moves second. Details in, say, T. Parthasarathy and T. E. S. Raghavan, Some Topics in Two-Person Games. Well, such a strategy is known for Nim, e.g., Courant and Robbins, What Is Mathematics? So, when the strategy is known, then following the strategy stands to beat Hinton's AI. Or, Hinton's million node AI can learn and learn all it wants, millions of games, maybe against itself, and just a tiny computer program, if it has choice of who moves first, will always win (no ties in Nim). More generally, for now, when can solve a cleanly specified problem mathematically, that is, complete with theorems and proofs, then that is better than Hinton's AI. Maybe in time something like Hinton's AI will be able to do research in math and produce results as theorems and proofs, maybe find the optimal chess strategy, and then, with choice of who moves first, never lose at chess, etc. But here's Lesson 1: For now, when math can solve a problem, it is better than Hinton's AI. So, sure, for startups, here's Lesson 2: F'get about Hinton's AI. Instead, pick a cleanly specified problem where can do some math research and get a solid math solution. Then stand to beat intuition, Hinton's AI, and, in practice, about everything else. Are there some problems now where math can do better than Hinton's AI? Yup. Point 1: Whatever can be done with Hinton's AI broadly in the economy, one of the keys to a successful startup is being exceptionally good. Well, a way to never lose and usually to win, usually win big, is to have the best math solution. So, that's one of the criteria in picking what a startup is to do. Again, it's just crucial to be exceptional. Simple example: Hinton's AI would have one heck of a time competing with the simplex algorithm on realistic problems, say, from running an oil refinery, on linear programming. A worse time competing on non-linear programming, say, also for running an oil refinery. A worse time competing on stochastic optimal control. Really hopeless on competing with Issac's differential game theory in pursuit-evasion games. And there's lots more.