> If we have a computer program that is able to design better hardware, it can be improved by simply moving it to better hardware. This adds a constraint that

> If we have a computer program that is able to design better hardware, it can be improved by simply moving it to better hardware. This adds a constraint that the new hardware has to be able to run that program, which is an important source of friction in the design. Especially if you consider the case of neuromorphic AI, true improvements in hardware design may involve changes so extensive and so breaking that it wouldn't be possible for the original AI to function on it. In order to exploit the better hardware capabilities, new AI would therefore have to be trained from zero, which is a potentially expensive operation. So regardless of which way to go, you encounter significant friction: either you constrain your design to support prior software, which is hard, requires a lot of checks, and is severely suboptimal in the grand scheme of things. Or you don't, in which case you have to wait a while until new AI can be made to exploit the new architecture. It's not as simple as you think.