History shows that transformative technologies like aviation created immense societal value without concentrating wealth in a few companies. AI could follow this path, with its benefits being widely distributed through commoditization, challenging the multi-trillion dollar valuations of today's leading firms.

A technology like AI can create immense societal value without generating wealth for its early investors or creators. The value can be captured by consumers through lower prices or by large incumbents who leverage the technology. Distinguishing between value creation and value capture is critical for investment analysis.

Not all seminal technologies create a small number of trillion-dollar companies. Industries like jet transportation, PCs, and vaccines have been transformative for society but have collectively generated little to no net profit for shareholders over time. AI could follow this path, benefiting users immensely without creating massive company valuations.

While immense value is being *created* for end-users via applications like ChatGPT, that value is primarily *accruing* to companies with deep moats in the infrastructure layer—namely hardware providers like NVIDIA and hyperscalers. The long-term defensibility of model-makers remains an open question.

History shows that transformative innovations like airlines, vaccines, and PCs, while beneficial to society, often fail to create sustained, concentrated shareholder value as they become commoditized. This suggests the massive valuations in AI may be misplaced, with the technology's benefits accruing more to users than investors in the long run.

The argument that AI will reduce inequality is flawed because democratizing access to tools doesn't democratize the economics. Technology markets naturally consolidate power and wealth, as seen with search engines and social networks. The financial benefits of AI are likely to concentrate at the top.

During major platform shifts like AI, it's tempting to project that companies will capture all the value they create. However, competitive forces ensure the vast majority of productivity gains (the "surplus") flows to end-users, not the technology creators.

The utopian vision of AI-driven abundance is shadowed by the practical reality of wealth concentration. A key challenge for society will be developing mechanisms to redistribute the immense value generated by AI so its benefits are shared broadly.

If AI makes intelligence cheap and universally available, its economic value may collapse. This theory suggests that selling raw AI models could become a low-margin, utility-like business. Profitability will depend on building moats through specialized applications or regulatory capture, not on selling base intelligence.