The Social Efficiency of Competition in AI

This project explores the efficiency of investments in AI. Large language models involve massive investments in building data centers and training models that consume real resources. Canonical economic models argue that such entry or investment decisions in oligopoly markets are generically inefficient. This project seeks to quantify the efficiency or inefficiency of investments in AI from a social point of view.