Since you are only changing the underlying model every so often instead of doing a large training loop when you setup the optical computer that can do inference it scales 2n+1 with clock speeds of to 100THz with only 100w of power vs traditional GPUs at 2GHZ with 1Kw for 15k cores.

sigh. (why? because now I have to guess how much is vague handwaving, or an AI trying to fit a square peg into a round hole, and how much is reality)

A) Why that means calculations can be imprecise - the weights are data stored in RAM, is the idea we'd use > N-bit weights and say it's effectively N-bit due to imprecision, so we're good? Because that'd cancel out the advantage of using < N-bit weights. (which, of course, is fine if B) has a strong answer)

B) A aside, why is photonics preferable?