Concentrating Intelligence:Scaling and Market Structure in Artificial Intelligence

Anton Korinek and Jai Vipra
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Jai Vipra: University of Virginia and Centre for the Governance of AI

No inetwp228, Working Papers Series from Institute for New Economic Thinking

Abstract: This paper examines the evolving structure and competition dynamics of the rapidly growing market for foundation models, focusing on large language models (LLMs). We describe the technological characteristics that shape the industry and have given rise to fierce competition among the leading players. The paper analyzes the cost structure of foundation models, emphasizing the importance of key inputs such as computational resources, data, and talent, and identifies significant economies of scale and scope that may create a tendency towards greater market concentration in the future. We explore two concerns for competition, the risk of market tipping and the implications of vertical integration, and use our analysis to inform policy remedies to maintain a competitive landscape.

Keywords: Artificial Intelligence; economic concentration; vertical integration; AI regulation. (search for similar items in EconPapers)
JEL-codes: D43 K21 L40 L41 L86 O33 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2024-10-02
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https://doi.org/10.36687/inetwp228 First version, 2024 (text/html)

Related works:
Journal Article: Concentrating intelligence: scaling and market structure in artificial intelligence* (2025)
Working Paper: Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:thk:wpaper:inetwp228

DOI: 10.36687/inetwp228

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