- cross-posted to:
- hackernews@lemmy.smeargle.fans
- cross-posted to:
- hackernews@lemmy.smeargle.fans
Take it directly from the horse’s mouth (some silicon VC):
In September 2023, I published AI’s $200B Question. The goal of the piece was to ask the question: “Where is all the revenue?”
At that time, I noticed a big gap between the revenue expectations implied by the AI infrastructure build-out, and actual revenue growth in the AI ecosystem, which is also a proxy for end-user value. I described this as a “$125B hole that needs to be filled for each year of CapEx at today’s levels.”
This week, Nvidia completed its ascent to become the most valuable company in the world. In the weeks leading up to this, I’ve received numerous requests for the updated math behind my analysis. Has AI’s $200B question been solved, or exacerbated?
If you run this analysis again today, here are the results you get: AI’s $200B question is now AI’s $600B question.
Other interesting parts include the admission (honestly less of an admission than “the thing these people say repeatedly”) that I first read in Peter Thiel’s book Zero to One that capitalists aren’t seeking out competitive markets, they’re seeking out monopoly markets:
In the case of physical infrastructure build outs, there is some intrinsic value associated with the infrastructure you are building. If you own the tracks between San Francisco and Los Angeles, you likely have some kind of monopolistic pricing power, because there can only be so many tracks laid between place A and place B. In the case of GPU data centers, there is much less pricing power. GPU computing is increasingly turning into a commodity, metered per hour. Unlike the CPU cloud, which became an oligopoly, new entrants building dedicated AI clouds continue to flood the market. Without a monopoly or oligopoly, high fixed cost + low marginal cost businesses almost always see prices competed down to marginal cost (e.g., airlines).
One final interesting quote:
Speculative frenzies are part of technology, and so they are not something to be afraid of. Those who remain level-headed through this moment have the chance to build extremely important companies. But we need to make sure not to believe in the delusion that has now spread from Silicon Valley to the rest of the country, and indeed the world. That delusion says that we’re all going to get rich quick, because AGI is coming tomorrow, and we all need to stockpile the only valuable resource, which is GPUs.
Didn’t know this was an actual mindset in the industry, god damn.
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Machine learning definitely has a place in modern science/tech but it seems to be plateauing rather than growing exponentially. Actually getting to AGI is going to require a fundamentally different approach and/or significantly more powerful computers.
I still see Seek and Merlin are starting points for imagining what ML could be under communism. As a birder/nature lover, these apps enhance my understanding of the natural world - and make it easier fo me to learn bird song, etc., rather than necessarily replacing that interaction I have with nature. The research possibilities are incredible too - being able to automatically track overnight bird migration paths, for instance.
It’s just the crypto mining hype wave with new buzzwords. They still use ‘tokens’ but it has a different meaning now. Mining datasets and playing LLM roulette.
This article feels like the author got hit over the head with a brick r9ght when they were about to announce that AI is a sham. And then the perp quickly scribbled in that everything will be alright at the end, before slipping away, pockets full of AI company cash.
chanting: COLLAPSE COLLAPSE COLLAPSE COLLAPSE COLLAPSE
Didn’t know this was an actual mindset in the industry, god damn.
capitalists aren’t seeking out competitive markets, they’re seeking out monopoly markets
The glaring hole in Thiel’s thinking is imagining the dialectical opposite. If you become a monopoly, it also means you monopolize the attacks against you. Consider SEO; as Google grew in search marketshare, so too did SEO optimize towards Google search, which itself waters down Google’s search and erodes their monopoly dominance. Microsoft Windows is another case study in how monopolization causes attack monopolization.
Without a monopoly or oligopoly, high fixed cost + low marginal cost businesses almost always see prices competed down to marginal cost (e.g., airlines).
true but the airline industry still consolidated into an oligopoly through control of their own currencies (redeemable miles)
might see something similar with gpu computing where the nominal prices are driven down to marginal cost but the real profit comes from control of the supply of tokens that can be redeemed for gpu time
but that still assumes there’s a real profitable use for this shit besides ever more individually targeted advertising and various flavors of outright fraud
