I get the "AI uses < 32 bit weights sometimes" thing, intimately, but I feel like I'm missing:

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?

A) Wasn't the article suggesting that would be 4-bits end-to-end in this hypothetical photonic matrix multiplication co-processor? ie. the weights are 4-bits

B) Power consumption and speed. Essentially chips are limited by the high resistance (hence heat loss) of the semiconductor. Photonics can encode multidimensionally, and data processing is as fast as the input light signal can be modulated and the output light signal can be interpreted. I guess this would favour heavy computations that require small inputs and outputs, because eventually you're bottlenecked by conventional chips.