I think you are trivializing the field of RL research. Games are not a solved problem. Doing that efficiently in real-time is even more difficult and is highly relevant to real world applications.

Right, we have not even solved games in the non-real time environment, so why bother adding additional constraints like “on real hardware in real time”. This is exactly like Tesla trying to switch from LIDAR to cameras before self driving is even solved. It’s avoiding the real harder challenge and going off on inane tangents. John is essentially bike shedding.

In this case, John is going off on this inane tangent because of his prior experience with hardware and video games instead of challenging himself to solve the actual hard and open problems.

I’m going to predict how this plays out for the inevitable screenshot in one to two years. John picks some existing RL algo and optimizes it to run in real time on real hardware. While he’s doing this the field moves on to better and new algorithms and architectures. John finally achieves his goal and posts a vid of some (now ancient) RL algo playing some Atari game in real time. Everyone says “neat” and moves on. John gets to feel validated yet all his work is completely useless.