It is possible that the ability to substitute away from specialized labor and towards capital
(that in principle could be rented or shared) may lower the “barriers to entry” in certain scientific
or research fields—particularly those in which the necessary data and algorithms are freely
available—while erecting new barriers to entry in other areas (e.g. by restricting access to data
and algorithms). As of yet, there are few if any organized markets for “trained” research tools or
services based on deep learning, and few standards to evaluate alternatives. Our analysis
suggests that the development of markets for shared AI services and the widespread availability
of relevant data may be a necessary precursor to the broad adoption and dissemination of deep
learning.
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