Indirectly, this raises a concern I have with so-called "Artificial Intelligence" or "Deep Learning". My first thought about this moving sofa problem is that i

Indirectly, this raises a concern I have with so-called "Artificial Intelligence" or "Deep Learning". My first thought about this moving sofa problem is that it would yield an answer to brute-force analysis. If not, then what about a long series of brute-force approximations to establish increasingly narrow upper and lower bounds? Which might yield an insight about the maximum pattern? And then this thought occurred to me: if we have such amazing tools nowadays, for doing pattern analysis, and Big Data analysis, how is that we are not able to find patterns in a problem such as this? I mean, could we not find patterns in the ways we find upper and lower bounds, and then use techniques of Artificial Intelligence to see some underlying pattern in the bounds? This problem is not like "What is the incidence of tuberculosis in Peru?" where we work with incomplete data. This moving sofa problem is an issue where we can work with perfect data. And yet out current Big Data tools are unable to find a pattern that would provide a conclusion about the maximum? Problems such as this help establish the limit on what our current Artificial Intelligence can do. If our pattern finding tools can not find patterns in numbers, where we work with perfect access to unlimited data, then we should not think that AI is going to achieve dramatic breakthroughs when working with imperfect data in the real world.