Overview
This book examines competition dynamics and power concentration in artificial intelligence, with a focus on computation and the concentration of computational resources.
Structure of This Book
We make progress on these questions by investigating:
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Background on competition: The role of resource monopolization in competition analysis, including alternative drivers of concentration that may better explain both the concentrated space of the market (vertical integration) and the unbalanced state of the price of AI (common ownership of drivers of computationally intensive AI by a few actors, assuming a balanced price would be driven way down by the less intensive options).
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Cost analysis: The cost of AI systems, both training and running, under different metrics (market cost of hosting infrastructure, subscriptions, token cost for hosted solutions) and technology types (large models, fine-tuned small and tiny models).
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Market demand analysis: The demand for and concerns about AI expressed by companies across the entire S&P 500 in their earning calls and 10K filings up to FY2024. In particular, investigating whether current demands account for the scale of investment in compute resources, and whether companies have resources to develop their own AI solutions without relying on supply from the largest actors; which would help them escape monopoly prices imposed by the larger actors.
Preliminary Findings
From preliminary numbers, we find that while the interest for and concerns about AI have sharply risen across S&P 500 companies, these same companies do have the resources to meet their own needs without paying inflated prices to the centralizing actors.