Superexponential long-term trends in information technology
Moore's Law has created a popular perception of exponential progress in information technology. But is the progress of IT really exponential? In this paper we examine long time series of data documenting progress in information technology gathered by [1]. We analyze six different historical tre...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Elsevier
2016
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| Online Access: | http://hdl.handle.net/1721.1/105411 https://orcid.org/0000-0001-6305-2105 |
| _version_ | 1826217078563012608 |
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| author | Nagy, Béla Farmer, J. Doyne Gonzales, John Paul Trancik, Jessika |
| author2 | Massachusetts Institute of Technology. Engineering Systems Division |
| author_facet | Massachusetts Institute of Technology. Engineering Systems Division Nagy, Béla Farmer, J. Doyne Gonzales, John Paul Trancik, Jessika |
| author_sort | Nagy, Béla |
| collection | MIT |
| description | Moore's Law has created a popular perception of exponential progress in information technology. But is the progress of IT really exponential? In this paper we examine long time series of data documenting progress in information technology gathered by [1]. We analyze six different historical trends of progress for several technologies grouped into the following three functional tasks: information storage, information transportation (bandwidth), and information transformation (speed of computation). Five of the six datasets extend back to the nineteenth century. We perform statistical analyses and show that in all six cases one can reject the exponential hypothesis at statistically significant levels. In contrast, one cannot reject the hypothesis of superexponential growth with decreasing doubling times. This raises questions about whether past trends in the improvement of information technology are sustainable. |
| first_indexed | 2024-09-23T16:57:39Z |
| format | Article |
| id | mit-1721.1/105411 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T16:57:39Z |
| publishDate | 2016 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | mit-1721.1/1054112022-09-29T22:44:21Z Superexponential long-term trends in information technology Nagy, Béla Farmer, J. Doyne Gonzales, John Paul Trancik, Jessika Massachusetts Institute of Technology. Engineering Systems Division Trancik, Jessica Trancik, Jessika Moore's Law has created a popular perception of exponential progress in information technology. But is the progress of IT really exponential? In this paper we examine long time series of data documenting progress in information technology gathered by [1]. We analyze six different historical trends of progress for several technologies grouped into the following three functional tasks: information storage, information transportation (bandwidth), and information transformation (speed of computation). Five of the six datasets extend back to the nineteenth century. We perform statistical analyses and show that in all six cases one can reject the exponential hypothesis at statistically significant levels. In contrast, one cannot reject the hypothesis of superexponential growth with decreasing doubling times. This raises questions about whether past trends in the improvement of information technology are sustainable. Boeing Company National Science Foundation (U.S.) Science of Science and Innovation Policy (NSF Award Number: 0738187) 2016-11-22T17:35:11Z 2016-11-22T17:35:11Z 2011-09 2011-06 Article http://purl.org/eprint/type/JournalArticle 00401625 http://hdl.handle.net/1721.1/105411 Nagy, Béla, J. Doyne Farmer, Jessika E. Trancik, and John Paul Gonzales. “Superexponential Long-Term Trends in Information Technology.” Technological Forecasting and Social Change 78, no. 8 (October 2011): 1356-1364. https://orcid.org/0000-0001-6305-2105 en_US http://dx.doi.org/10.1016/j.techfore.2011.07.006 Technological Forecasting and Social Change Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier Prof. Trancik via Angie Locknar |
| spellingShingle | Nagy, Béla Farmer, J. Doyne Gonzales, John Paul Trancik, Jessika Superexponential long-term trends in information technology |
| title | Superexponential long-term trends in information technology |
| title_full | Superexponential long-term trends in information technology |
| title_fullStr | Superexponential long-term trends in information technology |
| title_full_unstemmed | Superexponential long-term trends in information technology |
| title_short | Superexponential long-term trends in information technology |
| title_sort | superexponential long term trends in information technology |
| url | http://hdl.handle.net/1721.1/105411 https://orcid.org/0000-0001-6305-2105 |
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