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Notes -
AI is Too Big to Fail
I don't have the expertise needed to evaluate the economic arguments, so I'm mainly posting this here to solicit feedback on the linked article.
It's probably too late to avoid a future of "brutal serfdom" regardless of what happens, even if we reach singularity escape velocity. Power will do what it always has done, which is centralize in the hands of a few to the detriment of the many; turning every human into a cyborg god won't change that (you simply have the problem of organizing the coexistence of cyborg gods rather than the problem of organizing the coexistence of baseline humans). To think otherwise is to implicitly rely on a Rousseauean (and anti-Hobbesean, channeling Hlynka) presupposition that people are basically good and just and suffering is merely an incidental byproduct of material lack, which we have reason to be skeptical of. The second half of the 20th century provided what were probably the most fertile material and social conditions for freedom that have ever been seen in human history; regardless of wherever we're going now, we're leaving freedom in the rear-view mirror.
it could well be similar to how the dot-com investments worked out. lots of duds and even scams but on average i think the return on investing during that era was good and what it ended up producing was good. the problem is all of this is very risky and there is going to be a lot of failed investments in order to have some big payoffs. and of course the big players and everyone who thinks they have a chance is going to try and get the government to step in to subsidise their losses. but that doesn't mean the idea of AI is terrible or that we shouldn't be doing it.
Dotcom bubble was a bubble because there were no users. The reasoning was along the lines of 20% of all shoe sales in 2010 will be online. Company x has started to sell shoes online so in 10 years they will make billions. They had no sales and no where close to amazon's supply chain.
Chatgpt has millions of daily users. This is more akin to the boom of companies created when the world got smart phones. Those companies made money.
That really isn’t true. Plenty of dotcom companies like Yahoo had huge numbers of users; Yahoo had 400 million registered users at the peak in 2000 with 60 million monthly users (double the previous year’s figure). Many other dotcom companies had large user numbers too.
And if you look at the non-dotcom companies that still saw huge stock price crashes after the bust, many were businesses with big revenue, like Microsoft ($23bn in revenue in 2000, down 70%+ during the crash, didn’t recover until 2016) and Intel ($34bn in revenue in 2000, down 80%+ during the crash, didn’t recover until 2020). Both Intel and Microsoft were also extremely profitable during this period, contrary to boosters who say all tech stocks at this time lost money or whatever.
The bizarre myth that dotcom was all money into worthless internet businesses with 10 users and inflated traffic figures on zero revenue is peddled by exactly the same people trying to claim that “this time is different”.
It's even worse than that, because at least Yahoo and Microsoft had viable business plans and are still around years later. ChatGTP and other AI-only companies are more similar to Pets.com than the boosters want to realize. The news stories about the site's downfall always focused on the amount they spent on advertising, but they were selling the stuff they bought for less than what they paid for it, plus free shipping, in a bid to corner the market. ChatGTP is even worse because 97% of the users aren't paying anything, there is no advertising on the platform (and banner ads aren't going to cut it), and the 3% who do pay are likely power users who get more than their money's worth. So it's like if Pets.com gave 97% of their stuff away for free, sold the remaining 3% at a discount, and justified it by assuming that online shopping would be revolutionary and everyone would buy everything online. They were essentially right, they just went about it the wrong way to keep the spigot flowing. Add in spending large sums on infrastructure (i.e. warehouses vs. data centers) and the parallels are all too clear.
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