I am really digging the railroad analogies in this discussion! There are some striking similarities if you do the right mappings and timeframe transformations.
I am an avid rail-to-trail cycler and more recently a student of the history of the rail industry. The result was my realization that the ultimate benefit to society and to me personally is the existence of these amazing outdoor recreation venues. Here in Western PA we have many hundreds of miles of rail-to-trail. My recent realization is that it would be totally impossible for our modern society to create these trails today. They were built with blood, sweat, tears and much dynamite - and not a single thought towards environmental impact studies. I estimate that only ten percent of the rail lines built around here are still used for rail. Another ten percent have become recreational trails. That percent continues to rise as more abandoned rail lines transition to recreational use. Here in Western PA we add a couple dozen miles every year.
After reading this very interesting discussion, I've come to believe that the AI arms race is mainly just transferring capital into the pockets of the tool vendors - just as was the case with the railroads. The NVidia chips will be amortized over 10 years and the models over perhaps 2 years. Neither has any lasting value. So the analogy to rail is things like dynamite and rolling stock. What in AI will maintain value? I think the data center physical plants, power plants and transmission networks will maintain their value longer. I think the exabytes of training data will maintain their value even longer.
What will become the equivalent of rail-to-trail? I doubt that any of the laborers or capitalists building rail lines had foreseen that their ultimate value to society would be that people like me could enjoy a bike ride. What are the now unforeseen long-term benefit to society of this AI investment boom?
Rail consolidated over 100 years into just a handful of firms in North America, and my understanding is that these firms are well-run and fairly profitable. I expect a much more rapid shakeout and consolidation to happen in AI. And I'm putting my money on the winners being Apple first and Google second.
Another analogy I just thought of - the question of will the AI models eventually run on big-iron or in ballpoint pens. It is similar to the dichotomy of large-scale vs miniaturized nuclear power sources in Asimov's Foundation series (a core and memorable theme of the book that I haven't seen in the TV series).