  Denizens of Silicon Valley have called Moore's Law "the most important graph
in human history," and economists have found that Moore's Law-powered I.T.
revolution has been one of the most important sources of national productivity
growth. But data substantiating these claims tend to either be abstracted - for
example by examining spending on I.T., rather than I.T. itself - or anecdotal.
In this paper, we assemble direct quantitative evidence of the impact that
computing power has had on five domains: two computing bellwethers (Chess and
Go), and three economically important applications (weather prediction, protein
folding, and oil exploration). Computing power explains 49%-94% of the
performance improvements in these domains. But whereas economic theory
typically assumes a power-law relationship between inputs and outputs, we find
that an exponential increase in computing power is needed to get linear
improvements in these outcomes. This helps clarify why the exponential growth
of computing power from Moore's Law has been so important for progress, and why
performance improvements across many domains are becoming economically tenuous
as Moore's Law breaks down.
