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On the Basis of Brain: Neural-Network-Inspired Change in General Purpose Chips

Author

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  • Ekaterina Prytkova

    (Friedrich Schiller University Jena, Department of Economics and Business Administration)

  • Simone Vannuccini

    (Science Policy Research Unit, University of Sussex Business School, University of Sussex)

Abstract

In this paper, we disentangle the changes that the rise of Artificial Intelligence Technologies (AITs) is inducing in the semiconductor industry. The prevailing von Neumann architecture at the core of the established “intensive” technological trajectory of chip production is currently challenged by the rising difficulty to improve product performance over a growing set of computation tasks. In particular, the challenge is exacerbated by the increasing success of Artificial Neural Networks (ANNs) in application to a set of tasks barely tractable for classical programs. The inefficiency of the von Neumann architecture in the execution of ANN-based solutions opens room for competition and pushes for an adequate response from hardware producers in the form of exploration of new chip architectures and designs. Based on an historical overview of the industry and on collected data, we identify three characteristics of a chip — (i) computing power, (ii) heterogeneity of computation, and (iii) energy efficiency — as focal points of demand interest and simultaneously as directions of product improvement for the semiconductor industry players and consolidate them into a techno– economic trilemma. Pooling together the trilemma and an analysis of the economic forces at work, we construct a simple model formalising the mechanism of demand distribution in the semiconductor industry, stressing in particular the role of its supporting services, the software domain. We conclude deriving two possible scenarios for chip evolution: (i) the emergence of a new dominant design in the form of a “platform chip” comprising heterogeneous cores; (ii) the fragmentation of the semiconductor industry into submarkets with dedicated chips. The convergence toward one of the proposed scenarios is conditional on (i) technological progress along the trilemma’s edges, (ii) advances in the software domain and its compatibility with hardware, (iii) the amount of tasks successfully addressed by this software, (iv) market structure and dynamics.

Suggested Citation

  • Ekaterina Prytkova & Simone Vannuccini, 2020. "On the Basis of Brain: Neural-Network-Inspired Change in General Purpose Chips," SPRU Working Paper Series 2020-01, SPRU - Science Policy Research Unit, University of Sussex Business School.
  • Handle: RePEc:sru:ssewps:2020-01
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    Cited by:

    1. Ekaterina Prytkova, 2021. "ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links," Jena Economics Research Papers 2021-005, Friedrich-Schiller-University Jena.
    2. Lijuan Yang, 2023. "Recommendations for metaverse governance based on technical standards," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    3. Mauro Lombardi & Simone Vannuccini, 2021. "A paradigm shift for decision-making in an era of deep and extended changes," SPRU Working Paper Series 2021-05, SPRU - Science Policy Research Unit, University of Sussex Business School.
    4. Simone Vannuccini & Ekaterina Prytkova, 2021. "Artificial Intelligence’s New Clothes? From General Purpose Technology to Large Technical System," SPRU Working Paper Series 2021-02, SPRU - Science Policy Research Unit, University of Sussex Business School.

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    More about this item

    Keywords

    neural network; Artificial Intelligence; technological trajectory; semiconductor industry; hardware; software;
    All these keywords.

    JEL classification:

    • L63 - Industrial Organization - - Industry Studies: Manufacturing - - - Microelectronics; Computers; Communications Equipment
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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