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 Koh and Magee (2006). 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.

Exponential Self-Organization and Moore’s Law: Measures and Mechanisms

“…We broaden the system of interfunctions including the action efficiency and total amount of action in a complex system, based on a system of ordinary differential equations: (i) which leads to exponential growth with time, and (ii) establishes a power relation between the two, with measures such as the total flow of events, which is the number of computations for the CPUs and the number of transistors. Our study can also explain the origin of the observed exponential change in technology, noticed empirically by Moore [26], Kurzweil [27], Nagy et al [28], and Kelly [29]. This understanding can help describe, quantify, measure, manage, design and predict future behavior of complex systems to achieve the highest rates of self-organization to improve their quality.…”

Mechanism of organization increase in complex systems

“…In this paper we find that the positive feedback between the least unit action and the maximum total action leads to a process of exponential growth in time of both of them and a power law relation between them characterizing developing systems and is ubiquitous in nature [27][28][29][30]. The effect of system's size on its efficiency also supports this observation [31][32][33] as do the processes of growth and efficiency in information and other technologies [34][35][36]. Development and evolution in different systems have been studied through the dynamics of complex systems in great detail, and some projections about the future of this trajectory have been made [37][38][39][40][41][42].…”

Information in the Biosphere: Biological and Digital Worlds

“…Technological progress shows signs of being super-exponential when examined across technological paradigms [86]. New computational platforms, from nano-technological modelling of neurons [87], to developments in quantum computing [88], provide justification that artificial processing might maintain its exponential growth even beyond its silicon basis.…”