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Which adds up to actually-not-that-much of the workforce since we still live in a society where the significant majority of workers have physical tasks, and the unpredictable failure modes blight any attempt at scaling because the things are incapable of debugging outputs like human programmers...

The issue is that it's still utterly beholden to the data-set in ways humans are not, because the underlying method cannot improvise, because the results are so statistically chaotic that it cannot be trusted to adapt in the field to anything without the model breaking. Again, it will require a...

No, the system doesn't understand concepts, because it's stuck as a Chinese Room. There is no internal contemplation anywhere in it, it is simply a very large formula generated by trial and error that we've slowly made less brute-force. The most successful physical use-case is just using it to...

The issue is that the technology in question is intrinsically limited to only "Chinese Room" outcomes. It cannot generalize in the fashion required to make much difference to how stuff gets made because there is too much "noise" for the wildly different failure modes to be cleared up. We need...