Ah, this from the same David Siegel who said almost 2 yrs ago (in a talk found here: https://youtu.be/0z60xUDo-NI?si=PTDe11-sn2P53qo5&t=420) that the AI data center buildout was premature because:

> Even if the current approaches will continue to scale, this would be as if in the early days of computing, perhaps someone invented a bubble sort for sorting numbers (an n-squared algorithm), and the tech companies at the time decided they were going to build vast data centers to sort numbers and not bother to figure out that there's an n-log-n way of doing it <laughs>

...to which I have to say: yes, definitely! And he's right about open-source AI too.

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NitpickLawyer a day ago | parent [-]

> AI data center buildout was premature

Ask Amodei how he feels about going to spaceman bad for compute that he couldn't find anywhere else in the market.

	▲	thoughtpeddler 3 hours ago \| parent [-]
		Yes, there's a present shortage of usable frontier compute, but that doesn't establish that every proposed data center will earn a decent return, or that today’s hardware + model architecture will remain economically competitive, or more to Siegel's point, that algorithmic efficiency could not dramatically reduce compute requirements. To borrow a real example from a prior boom, railroads were congested during the initial build-out while people simultaneously funded and built too many railroads for future demand. Likewise, Anthropic et al can be compute-starved now while the industry as a whole is overbuilding expensive, depreciating infrastructure.