Comment Re:speaking of railroads (Score 1) 38
To use a tech metaphor, think of how many viable phone brands were in a phone store in 2005, and how much brand diversity you see now. Same goes for PC/laptop brands, even tablets. Money moves to find early leaders and funds them, until it's no longer profitable. Then there's a consolidation period, and monopolization of supply chains.
Although there's specific hardware underneath, AI is an app. What are the lifecycle of apps? Take a look at early office app consolidation. Anyone remember dBase? When Oracle's SQL had maybe three viable competitors? How many early cloud hosting facilities were bought up, and made into consolidated platforms? Does anyone remember Sprint, MCI, AT&T, and the wars that lead to Level 3, who is also now gone? Rackspace?
Training source data is one problem, evolving AI APIs are another. Interlinking intelligence still another. Hype for the sake of someone buying your early terms sheet, still another.
The lack of QA, model integrity, highly publicized hallucinations, lack of boundaries and effective controls, specific training data revelations, all these seem like opportunity to do better than the next competitor, except they fail, too. Dump trucks full of cash is a hallowed way of burning money to find longer-term returns.
The enshitifcation point, where good work turns into creating only vaguely iterative successes seems closer than it should.
These aren't bubbles, they're cycles we've seen before, whose energy burst like a bubble. Then we moved on.