AI infrastructure leaders justify massive investments by citing a limitless appetite for intelligence, dismissing concerns about efficiency. This belief ignores that infinite demand doesn't guarantee profit; it can easily lead to margin collapse and commoditization, much like the internet's effect on media.

Foundational AI models will commoditize into a utility layer where companies buy "intelligence on the fly." The real, sustainable profit will be captured by application companies that leverage various models to solve specific business problems, as most enterprises lack the expertise to use raw models effectively.

Massive investments in AI hyperscalers are not the end game. They are laying foundational infrastructure, like the 19th-century electrical grid, which will enable a future explosion of derivative applications across all industries.

Sam Altman's vision for OpenAI's business is not complex software licensing but selling intelligence as a fundamental utility. The model is to "sell tokens" on a metered basis, much like a power company sells electricity, aiming to make intelligence abundant and accessible on demand.

Mobile networks built expensive global infrastructure with massive usage but captured little value as profits moved "up the stack" to apps. Foundation models, despite huge CapEx, face a similar risk of becoming a commoditized infrastructure layer with low pricing power.

Comparing AI to 1995-era internet bandwidth, the hosts argue that selling raw 'intelligence' is a low-margin, commodity business. The significant financial upside will be captured not by the infrastructure providers, but by the creators who build novel applications and experiences using that intelligence as a building block.

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.

Much like 'big data' evolved from a competitive advantage into a widely available commodity, AI models will likely follow the same path. So many sources will offer powerful models that they will cease to be a unique differentiator or a durable moat for businesses.

Unlike cable or power companies that benefit from regional monopolies, AI intelligence is a globally competitive, frictionless market. This dynamic is 'so much worse' for business because it allows for perfect arbitrage, driving the price of intelligence toward zero and making it incredibly difficult to build a sustainable, high-margin business on the infrastructure layer.