We've seen speculative over-growth with a good legacy at least three times in the last three decades. First was the dot-com boom. Overpromotion made it necessary for every business to have a web site. That wasn't pre-ordained. The Web could have maxed out as a distribution system for catalogs, data sheets, academic papers, and similar business to business info. Overpromotion created the business to consumer web, which turned out to be useful.
The second overbuild was long-haul fiber optics. Look up Global Crossing. So much fiber was put into the ground and water that intercontinental spam is not a problem. That didn't have to happen. If traffic was billed, it wouldn't have happened. It turned out to be useful, but was not pre-ordained from the economics.
A third overbuild was the solar panel industry, especially in China. So much money was thrown at solar panel manufacturing that the price became very, very low. Solar deployment accelerated and started to take over, after decades of panels costing too much. Now China has a solar panel glut. They're dealing with it intelligently - minimum efficiency standards are coming into effect, and pollution controls on panel manufacturing are being tightened.
A few notes:
1. This assumes that there is notable ROI on 'AI labor'. That is still up for debate.
2. This assumes that the interests are currently falling, unless I misread the paper.
3. This affirms that we are in an over valuated, speculative bubble which will inevitably correct; but it needs to "correct" at the exact right time defined by multiple factors.
First, "correction" can be an euphemism for a disastrous financial crisis. It could take years and years for most people to see the end of the tunnel. I don't know if the end justify the means.
Do we really need to engineer a financial crisis to build more energy facilities? And will they be built the 'right way', using renewable energy for example? What if we invested half of those trillions directly in socially impactful measures, instead of having the money flow through a speculative bubble first?
Finally, I am not an economist, but I wonder how accurate a mathematical model is to the real world - i.e. what happens to the model when Donald posts a picture of him as the "doctor" or keep changing the opening hours of the Hormuz?
It does feel a bit like trying to read tea leaves to me. This reminds me of Hari Seldon's psychohistory:
> In Foundation (1951), famed mathematician and psychologist Hari Seldon has developed the science of psychohistory, which uses sophisticated mathematics and statistical analysis to predict future trends on a galactic scale. He has predicted the unavoidable and relatively imminent fall of the Galactic Empire, and intends to establish the Foundation, "a repository of crucial, civilization-preserving knowledge" that will enable society to revive itself more quickly and efficiently [...] [1]
---
[1](https://en.wikipedia.org/wiki/Foundation_universe#Psychohist...)
If enough capital has been installed before learning removes the wedge, the economy lands in the high-capital state,
Truly dismal science of an Economics professor at MIT.
cmiles8•1h ago
A temporary overvaluation can build enough real capital that the economy lands in a permanently higher-capital equilibrium, even after the inflated valuations correct. The future for AI companies may look rather iffy, but the whole economy may not be as screwed as some fear.
vmesel•50m ago
aureate•47m ago
If the "higher capital" that results from an AI boom consists of massively parallel computational resources that currently can only be fully utilised by AI and crypto, and if those things turn out to be a bust, the "higher capital" only has value if we find something else to do with it.
Maybe we will...
largbae•37m ago
The model in my head is more like DotCom telecom. The massive overbuild in fiber was eventually used and even used for the purpose that it was imagined for during the boom. It's just that the companies that built it mostly went under and new owners acquired it at a profit-supporting price.
Retric•31m ago
Data centers and electrical infrastructure has a similar long term value, but most of the AI investment is in compute/manufacturing capacity for current nodes which doesn’t age nearly as well.
altcognito•21m ago
I mean, compute depreciates, but I think there is zero chance that the value of inference or training is going to fall to zero. Market discovery will find the right price provided the market has the right degree of freedom. Given the type of market it is, I don't see how that won't be the case.
jaggederest•52s ago
That implies to me that in the future we'll have models as good or perhaps better than the state of the art at the moment, but on hardware chips that can be put in places where you can't currently locate a datacenter, and operating at hundreds of times better power efficiency, which sounds pretty great.
chongli•47m ago
It's like the tulip bubble of the 17th century [1]. Having a bunch of money tied up in useless tulip bulbs didn't do anything productive after the collapse.
[1] https://en.wikipedia.org/wiki/Tulip_mania
elefanten•33m ago
And beyond physical infrastructure there are the intangible assets: the learning and the process innovation across multiple fields.
The upfront price for all that may end up steep, or fair, or even cheap… the truth is no one knows yet
chongli•27m ago
It's like comparing a railway line from a mine to a smelter with a city's road network.
whimsicalism•24m ago
Avicebron•44m ago
Mistletoe•40m ago
https://en.wikipedia.org/wiki/Minsky_moment