Superexponential long-term trends in information technology

Abstract 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.

[1]  R. Kurzweil,et al.  The Singularity Is Near: When Humans Transcend Biology , 2006 .

[2]  Christopher L. Magee,et al.  A functional approach for studying technological progress: Extension to energy technology , 2008 .

[3]  M.Nawaz Sharif,et al.  The Weibull distribution as a general model for forecasting technological change , 1980 .

[4]  Steve T. Jurvetson Transcending Moore ' s Law with Molecular Electronics and Nanotechnology , 2008 .

[5]  Anders Sandberg,et al.  An Overview of Models of Technological Singularity , 2013 .

[6]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[7]  R. Jain,et al.  Records , 1973, Tempo.

[8]  Joseph P. Martino,et al.  Using precursors as leading indicators of technological change , 1987 .

[9]  F. Meyer,et al.  The dynamics of long-term growth , 1975 .

[10]  H. Akaike A new look at the statistical model identification , 1974 .

[11]  Christopher L. Magee,et al.  The Progress in Wireless Data Transport and its Role in the Evolving Internet , 2008 .

[12]  Vernor Vinge,et al.  ==================================================================== the Coming Technological Singularity: How to Survive in the Post-human Era , 2022 .

[13]  D. Helbing,et al.  Growth, innovation, scaling, and the pace of life in cities , 2007, Proceedings of the National Academy of Sciences.

[14]  Edgar A. Pessemier Product Management: Strategy and Organization , 1982 .

[15]  Joseph P. Martino,et al.  Bayesian updates using precursor events , 1993 .

[16]  T. Toffoli,et al.  Fundamental limit on the rate of quantum dynamics: the unified bound is tight. , 2009, Physical review letters.

[17]  M. Kremer Population Growth and Technological Change: One Million B.C. to 1990 , 1993 .

[18]  Gordon E. Moore,et al.  Progress in digital integrated electronics , 1975 .

[19]  Joseph Paul Martino,et al.  Technological Forecasting for Decisionmaking , 1975 .

[20]  Kevin D. Kelly What Technology Wants , 2010 .

[21]  S. Frank The common patterns of nature , 2009, Journal of evolutionary biology.

[22]  D. Cox,et al.  An Analysis of Transformations , 1964 .

[23]  G. Schwarz Estimating the Dimension of a Model , 1978 .

[24]  D. Sornette,et al.  Finite-time singularity in the dynamics of the world population, economic and financial indices , 2000, cond-mat/0002075.

[25]  Joseph P. Martino,et al.  Probabilistic technological forecasts using precursor events , 1991, Technology Management : the New International Language.

[26]  Heinz von Foerster,et al.  Doomsday: Friday, 13 November, A.D. 2026 , 1960 .

[27]  William J. Padgett,et al.  Parametric and Nonparametric Inference from Record-Breaking Data , 2003 .

[28]  Robert U. Ayres,et al.  The Singularity is Near: When Humans Transcend Biology, Ray Kurzweil. Viking Penguin, New York (2005), 602 pages plus index; $29.95 , 2006 .

[29]  J. Corcoran Modelling Extremal Events for Insurance and Finance , 2002 .

[30]  C. Walter Kryder's law. , 2005, Scientific American.

[31]  John F. Muth,et al.  Search Theory and the Manufacturing Progress Function , 1986 .

[32]  Sidney Redner,et al.  Role of design complexity in technology improvement , 2009, Proceedings of the National Academy of Sciences.

[33]  G.E. Moore,et al.  Cramming More Components Onto Integrated Circuits , 1998, Proceedings of the IEEE.

[34]  W. Nordhaus Two Centuries of Productivity Growth in Computing , 2007, The Journal of Economic History.

[35]  Christopher L. Magee,et al.  A functional approach for studying technological progress: Application to information technology ☆ , 2006 .

[36]  R. Kurzweil,et al.  The law of accelerating returns , 2008 .

[37]  Joseph P. Martino,et al.  Technological forecasting for decision making , 1983 .