eml(x, y ) = exp(x) − ln(y) # 1 + x + y
eml(x, 1 ) = exp(x) # 2 + x
eml(1, y ) = e - ln(y) # 2 + y
eml(1, exp(e - ln(y))) = ln(y) # 6 + y; construction from eq (5)
ln(1) = 0 # 7
After you have ln and exp, you can invert their applications in the eml function eml(ln x, exp y) = x - y # 9 + x + y
Using a subtraction-of-subtraction to get addition leads to the cost of "27" in Table 4; I'm not sure what formula leads to 19 but I'm guessing it avoids the expensive construction of 0 by using something simpler that cancels: x - (0 - y) = x + y # 25 + {x} + {y}
The focus is placed on "AI Literacy", but it seems to use this to just mean 'volume of AI use'. The discussion of the Netflix case study is extra perplexing, since the summary here admits they didn't find any actual productivity improvement, just that only a few hours of "training" could induce on the order of $50/person/day on tokens.
That seems... the opposite of literacy?