cover image: Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence

Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence

7 Nov 2024

This paper examines the evolving structure and competition dynamics of the rapidly growing market for foundation models, with a focus on large language models (LLMs). We describe the technological characteristics that shape the AI 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 we evaluate policy remedies that aim to maintain a competitive landscape. Looking ahead to increasingly transformative AI systems, we discuss how market concentration could translate into unprecedented accumulation of power, highlighting the broader societal stakes of competition policy.
industrial organization corporate finance microeconomics other antitrust law and economics development and growth productivity, innovation, and entrepreneurship market structure and distribution industry studies innovation and r&d

Authors

Anton Korinek, Jai Vipra

Related Organizations

Cornell University
European Commission
European Parliament
European Union
New York Times
Princeton University
University of Pennsylvania
Acknowledgements & Disclosure
This is a revised version of a paper presented at the 79th Economic Policy panel meeting in Brussels in April 2024. We thank Susan Athey, Emma Bluemke, Claire Dennis, Avi Goldfarb, Aidan Kane, Pia Malaney, Sarah Myers West, Sanjay Patnaik, Nicholas Ritter, Max Schnidman, Eli Schrag, Rob Seamans and Joseph Stiglitz as well as our editors, Emilio Calvano and Giacomo Calzolari, our discussant Doh-Shin Jeon, and two anonymous referees for thoughtful comments and conversations. Any remaining errors are our own. Korinek gratefully acknowledges financial support from the Center for Innovation, Growth and Society of the Institute for New Economic Thinking (INET-CIGS, grant no INO21-00004). Jai Vipra gratefully acknowledges financial support as a Winter Fellow from the Centre for the Governance of AI. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research or of the other institutions that the authors are affiliated with. An earlier version of this paper was circulated under the title “Market Concentration Implications of Foundation Models: The Invisible Hand of ChatGPT.”
DOI
https://doi.org/10.3386/w33139
Pages
31
Published in
United States of America

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