Artificial intelligence agents and superstar effects
Abstract
The paper models AI-services market competition in the presence of superstar effects. By modifying the original Rosen’s setup consistently with recent advancements of superstar theory, we discuss the role of scale-related technical change in the advent of superstar artificial intelligent agents and the main consequences of superstar effects on competition between AI-based systems. Furthermore, we outline how to extend the model for addressing three issues: (i) positive feedback loops from data accumulation; (ii) the co-evolution of artificial intelligence agents’ capabilities and market size; and, (iii) the “winner-takes-all” dynamics triggered by superstar effects.
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