And this is even more true when considering elements in the formation of a robot that need to be handled before the AI: physics, metallurgy, engineering, computer hardware design, etc.
Without theory—good, workably-correct theory—the search space for innovations is just too large. The more correct the theory, the less space has to be searched for solution concepts. If you’re going to build a rocket, you sure as hell better understand Newton’s laws. But things will go much smoother if you also know some chemistry, some material science, and some computer science.
For a solid example of theory taking previous experimental data and massively narrowing the search space, see RAND’s first report on the feasibility of satellites here.
And this is even more true when considering elements in the formation of a robot that need to be handled before the AI: physics, metallurgy, engineering, computer hardware design, etc.
Without theory—good, workably-correct theory—the search space for innovations is just too large. The more correct the theory, the less space has to be searched for solution concepts. If you’re going to build a rocket, you sure as hell better understand Newton’s laws. But things will go much smoother if you also know some chemistry, some material science, and some computer science.
For a solid example of theory taking previous experimental data and massively narrowing the search space, see RAND’s first report on the feasibility of satellites here.