Double the hardware, double the AI researchers
Carl ShulmanCarl Shulman (Pt 1) — Intelligence explosion, primate evolution, robot doublings, & alignmentat 7:00
From the conversation
So far I've talked about hardware as an initial example because we had good data about a past period. You can also make improvements on the software side and when we think about an intelligence explosion that can include — AI is doing work on making hardware better, making better software, making more hardware. But the basic idea for the hardware is especially simple in that if you have an AI worker that can substitute for a human, if you have twice as many computers you can run two separate instances of them and then they can do two different jobs, manage two different machines, work on two different design problems. Now you can get more gains than just what you would get by having two instances. We get improvements from using some of our compute not just to run more instances of the existing AI, but to train larger AIs. There's hardware technology, how much you can get per dollar you spend on hardware and there's software technology and the software can be copied freely. So if you've got the software it doesn't necessarily make that much sense to say that — “Oh, we've got you a hundred Microsoft Windows.” You can make as many copies as you need for whatever Microsoft will charge you. But for hardware, it’s different. It matters how much we actually spend on the hardware at a given price.…
Summary
Doubling the amount of hardware directly doubles the number of AI worker instances that can run, allowing those instances to perform proportionally more work. This hardware scaling dynamic provides a straightforward mechanism for an intelligence explosion, where AI systems contribute to producing more hardware, better software, and additional compute. The substitutability of AI workers for human researchers means that scaling hardware translates directly into scaling the effective AI research workforce.
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