On the basis of brain: neural-network-inspired changes in general-purpose chips

Ekaterina Prytkova and Simone Vannuccini
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Ekaterina Prytkova: University of Sussex

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Abstract: In this paper, we disentangle the changes that the rise of artificial intelligence (AI) technologies is inducing in the semiconductor industry. Chips based on the von Neumann architecture are struggling to deliver performance across a wide range of applications, and the new AI segment is only adding to this struggle. This poses a new challenge to chip design, with flexibility of computation at its core, i.e., hardware's ability to support a large software variety, rather than computation speed. We identify and analyze forces and mechanisms at work and discuss the product configurations which could characterize the future of the semiconductor industry. We outline two possible scenarios: (i) fragmentation of the semiconductor industry into submarkets with dedicated chips and (ii) the shift of the industry to a system-on-a-chip-based dominant design with the emergence of a new platform chip. We rationalize the unfolding situation by modeling consumer choice between computing systems based on their crucial characteristics—speed, flexibility, and energy efficiency.

Date: 2022-08-01
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Published in Industrial and Corporate Change, 2022, 31 (4), pp.1031-1055. ⟨10.1093/icc/dtab077⟩

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Related works:
Journal Article: On the basis of brain: neural-network-inspired changes in general-purpose chips (2022)
Working Paper: On the Basis of Brain: Neural-Network-Inspired Change in General Purpose Chips (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-04012987

DOI: 10.1093/icc/dtab077

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