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Moore’s and Wright’s Law are the best approximations for the pace of technological progress

Wednesday, March 6, 2013 12:22
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From NextBigFuture.com

Moore’s Law and Wright’s Law — offer superior approximations of the pace of technological progress. The new research is the first to directly compare the different approaches in a quantitative way, using an extensive database of past performance from many different industries.

Some of the results were surprising, says Jessika Trancik, an assistant professor of engineering systems at MIT. The findings could help industries to assess where to focus their research efforts, investors to pick high-growth sectors, and regulators to more accurately predict the economic impacts of policy changes.

The analysis indicates that Moore’s Law is one of two formulas that best match actual technological progress over past decades. The top performer, called Wright’s Law, was first formulated in 1936: It holds that progress increases with experience — specifically, that each percent increase in cumulative production in a given industry results in a fixed percentage improvement in production efficiency.

To carry out the analysis, the researchers amassed an extensive set of data on actual costs and production levels over time for 62 different industry sectors; these ranged from commodities such as aluminum, manganese and beer to more advanced products like computers, communications systems, solar cells, aircraft and cars.

“There are lots of proposals out there,” Trancik says, for predicting the rate of advances in technologies. “But the data to test the hypotheses is hard to come by.”

The rates of change vary greatly among different technologies, the team found.

“Information technologies improve the fastest,” Trancik says, “but you also see the sustained exponential improvement in many energy technologies. Photovoltaics improve very quickly. … One of our main interests is in examining the data to gain insight into how we can accelerate the improvement of technology.”

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PLOS One – Statistical Basis for Predicting Technological Progress

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