Like I mentioned, I have high hopes modelling vaguer aspects of customer preference can be incorporated by training a model on rendered generative design (e.g.

Like I mentioned, I have high hopes modelling vaguer aspects of customer preference can be incorporated by training a model on rendered generative design (e.g. with data from amazon turk), which can then be used as maybe some kind of penalization on the efficiency loss function, multiplied by a weight to give us a choice in the efficiency-comfort tradeoff-space. There are solutions that I think show potential out there. I don't think our future AI designed world necessarily need to ignore difficult-to-quanitify dimensions like aesthetics. (Though amazon turk is expensive, especially in developer man-hours, so I can understand if that won't always be done.)