Carl Shulman: prediction

Transcript context

…I guess there's a lot of questions you can delve into in terms of whether you would expect a similar scale with AI and whether it makes sense to think of AI as a population of researchers that keeps growing with compute itself. Actually, let's go there. Can you explain the intuition that compute is a good proxy for the number of AI researchers so to speak? 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. And if we look at the changes that have been driving AI recently, that is the thing that is really off-trend. We are spending tremendously more money on computer hardware for training big AI models. Okay so there's the investment in hardware, there's the hardware technology itself, and there's the software progress itself. The AI is getting better because we're spending more money on it because our hardware itself is getting better over time and because we're developing better models or better adjustments to those models. Where is the loop here?…

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