  Using time series of US patents per million inhabitants, knowledge-generating
cycles can be distinguished. These cycles partly coincide with Kondratieff long
waves. The changes in the slopes between them indicate discontinuities in the
knowledge-generating paradigms. The knowledge-generating paradigms can be
modeled in terms of interacting dimensions (for example, in
university-industry-government relations) that set limits to the maximal
efficiency of innovation systems. The maximum values of the parameters in the
model are of the same order as the regression coefficients of the empirical
waves. The mechanism of the increase in the dimensionality is specified as
self-organization which leads to the breaking of existing relations into the
more diversified structure of a fractal-like network. This breaking can be
modeled in analogy to 2D and 3D (Koch) snowflakes. The boost of knowledge
generation leads to newly emerging technologies that can be expected to be more
diversified and show shorter life cycles than before. Time spans of the
knowledge-generating cycles can also be analyzed in terms of Fibonacci numbers.
This perspective allows for forecasting expected dates of future possible
paradigm changes. In terms of policy implications, this suggests a shift in
focus from the manufacturing technologies to developing new organizational
technologies and formats of human interactions
