The author argues that the AI bubble may not exist, citing the high upfront costs of building data centers as a one-time expense rather than a regular operating cost, and the potential for AI to be profitable once these costs are paid off. The author suggests that the high spending of AI companies is not necessarily a sign of an impending bubble, but rather a necessary investment in infrastructure. According to the author, Anthropic's S-1 filing shows that they make $2.08 for every $1 of compute cost, indicating that AI can be profitable once infrastructure costs are covered.

A science fiction author analyzed how accurately various stories predicted the development of AI, specifically the transformer model and its applications. The author found that Ted Chiang's 'The Lifecycle of Software Objects' was the closest to accurately describing the process of creating and maintaining AI, including teaching, maintaining, and selling it. Other stories had some predictions correct, but not the specifics of the transformer model or its rapid adoption.