AI is a platform shift

Yesterday, I skirted along the edge of the atmosphere at four-fifths the speed of sound, traveling from London to New York in seven hours. The least expensive tickets were $400. Jet transport technology has changed the world. Sixty years ago, my mother crossed the Atlantic in a steamship: It took seven days and cost 4x what flying does today. Commercial aviation has created enormous value. However, the vast majority of that value has been captured by consumers and society, vs. airlines. Since 1945 the industry has experienced years of low-margin profitability only to have its gains wiped out by periods of huge losses (e.g., $128b in 2020).

Yet some technological innovations, though societally transformative, generate little in the way of new wealth; instead, they reinforce the status quo. Fifteen years before the microprocessor, another revolutionary idea, shipping containerization, arrived at a less propitious time, when technological advancement was a Red Queen’s race, and inventors and investors were left no better off for non-stop running.

And because there is no economic profit during perfect competition, there is no money to be made by innovators during maturity. Like containerization, the introduction of AI did not lead to a period of protected profits for its innovators. It led to an immediate competitive free-for-all.

While Steve Jobs was telling investors that every household would someday have a personal computer (a wild underestimate, as it turned out), others questioned the need for personal computers at all. As late as 1979, Apple’s ads didn’t tell you what a personal computer could do—it asked what you did with it.

Scientists can already do incredible things with the augmented intelligence gains from today's AI models. These gains will compound over a decade through better scaffolding (software that directs the AI to be more useful). So we'll still get incredibly valuable leverage from augmented intelligence.  But it won't be “AGI” like it’s been sold to us so far; according to Karpathy, there’s nothing “general” or “intelligent” about today’s language models, really. So reset your expectations: no AGI until 2035. - 😺 Karpathy: No AGI til 2035?

The high capex of AI companies will primarily be spent with the infrastructure companies. These companies are already valued with this expectation, so there won’t be an upside surprise. But consider that shipbuilding benefited from containerization from 1965 until demand collapsed after about 1973. If AI companies consolidate or otherwise act in concert, even a slight downturn that forces them to conserve cash could turn into a serious, sudden, and long-lasting decline in infrastructure spending. This would leave companies like Nvidia and its emerging competitors—who must all make long-term commitments to suppliers and for capacity expansion—unable to lower costs to match the new, smaller market size. Companies priced for an s-curve are overpriced if there’s a peak and decline.

Which will entail a corresponding distribution shift

Which will hinge on personal context as the moat

Imagine a protocol, similar to MCP, that stores the context in your device (ie apple secure enclave) and allows apps or models to tap into that to personalize your experience. Then the moat is probably not the processing context anymore and shifts to the storage and the ability to execute over it. - Tomás Soracco