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Yes, but we aren't quite there yet. Not even close, in my opinion, at least when we're talking about serious job displacement. Unless there's a phase change, were looking at years of more insane capex and opex.
And those trillions will need to be payed back with interest. We're not talking about a Netflix or Office 365 licence that every office drone just has. For millions of workers, access to those tools will rival transportation and housing in ongoing cost.
No problem, if your employer already has half the staff on SolidEdge/Ansys/ect licenses and generally does not care what toolboxes everybody gets. For the rest? Small business, low productivity labor, labour limited by hardware throughout (classic example: radiology)? They won't really contribute to paying off that debt, so they won't get a lot of tokens, and none from the good models.
We've gotten used to tech, especially software, being cheap. For the current economics to make any sense, this will come to a hard stop. On the cost side, AI is much more like an excavator than like a shovel, and it really needs to replace just as many workers to make sense building them.
And I can well imagine this never happening. Maybe they'll never get reliable enough for that much unsupervised work, especially work you can't write unit tests for.
I should have said "post bankruptcy, the AI Labs could be happy fat inference providers. I actually think the current SOTA models, if we worked on improving harnesses, etc a lot, could still be a huge change on their own. Obviously smarter model = better, but just what we have now with a ton of scaffolding can do a lot.
But yes, the amount of capex they have all spent means they now need something way better than "excel helper" to pay it back. But in a non-hyperscale world, LLMs as a normal technology could a profitable medium/large SAAS industry.
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