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    Om innovasjonspolitikk og verdiskaping

    17. februar 2017

    Advanced algorithms may make innovation processes more effective. (Photo: Allvisionn)

    Dag H. Zeiner-Gundersen argues that companies and research institutions may innovate more effectively using advanced algorithms and Artificial Intelligence.

    By Guest Writer Dag H. Zeiner-Gundersen, Ph.D D.Sc, Founder of Norrønt AS

    The need for systematic and complexinnovation

    Successful innovation processes must bridge the gap between technological challenges and marketing challenges, leading to viable products and services. Most of the current theories on innovations and innovation processes address, however, the topic of innovation with very simple tools and from a general historic and macroeconomic point of view.

    The human innovation process is driven by creativity. To understand the innovation processes we have to assess human learning and creativity. We must effectively use all available results of inventive principles and solutions used throughout history, methodically and in efficiently. This alsoincludes the need for crosslinking between sciences, and pushing the boundary methodically with the help of algorithms Artificial Intelligence (AI).

    Companies innovating need to ensure that the innovation process, and the resources used, correlates with the expected outcome. I would therefore argue that we must focus more on details and logical methods, specific principles and standards and algorithms required to achieve precise and detailed results.

    The author has through several years been judge at international innovation competitions and observed the increasing speed, momentum, and focus within international innovation. One example: During the innovation competition for renewable energy in Astana October 2016, 17 out of 100 companies that participated were from Israel, none from Norway.

    Becoming more methodical

    The low hanging fruits that create real disruptive solutions are becoming less and less common within the field of innovation. Complex innovation is a very detailed oriented, ‘brain-draining’ and demanding exercise. The science and engineering communities should become more methodical and less dependent on random occurrences of creativity and non-structured inventive methods (including attempts at finding the optimum result through “Googling”).

    Methods based on algorithms and associated principles and standards can be very precise tools. They introduce a kind of accuracy not found in most innovation methods. Such methods can be combined with the use of artificial intelligence for the development of more disruptive solutions.

    A typical example on using a fast algorithms addressing a design dilemma may be theattachment of blades/profiles onto a vertical turbine axis, whereby the algorithm will propose the use of preloaded solutions. In this way mechanical life of the turbines can be increased by multiple factors of 10, by avoiding/reducing cyclic tension and compression stress variations.

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