Michael Nielsen: belief

Transcript context

…What is your interpretation then of this empirical phenomenon where whatever input you consider into the scientific process or technological progress… Economists have studied this a million ways. It just seems to require a very consistent rate of X percent more researchers per year. There’s this famous paper from a couple years ago by Nicholas Bloom and others where they say, “How many people are working in the semiconductor industry, and how has it increased over time through the history of Moore’s law?” I think they find that Moore’s law means transistor density increases 40% a year, but to keep that going the number of scientists has increased 9% a year, in the semiconductor industry. They go through industry after industry with this observation. Is your view that there are these deep ideas, but they keep getting harder to find? Or is there another way to think about what’s happening with these empirical observations? First of all, all of their examples are narrow. They pick a particular thing, and then they look at a particular metric. GPUs don’t show up there. All of a sudden you get this ability to parallelize, and that’s really interesting. There are a lot of external consequences. Basically they have these simple quantitative measures. They look at it in agricultural productivity. They look at it in a whole lot of different ways, but you do have to focus narrowly. I’m certainly interested in the fact that new types of progress keep becoming possible. But I think even there, there does still seem to be some phenomenon of diminishing returns. Is that intrinsic? Is that something about the structure of the world? What is it? One thing which hasn’t changed that much is the individual minds which are doing this kind of work. Maybe those should be improved as well, or some feedback process going on there. Maybe that changes the nature of things. I look at scientific progress up until, let’s say, 1700, and it was very slow, and also very irregular. You had the Ionians back five centuries before Christ doing these quite remarkable things, and so much knowledge would get lost, and then it would be rediscovered, and then it would be lost again. You’d have to say that progress was very slow. It’s partially just bound up with the fact that there were some very good ideas that we just didn’t have. Even once you’ve had the ideas, you need to build institutions around them. You actually need to solve a whole lot of different problems about training, allocation of capital, and all these kinds of things. Even just basic security for researchers, so they’re not worried about the Inquisition or things like that. There are all these complicated problems. You solve all those complicated problems, and then all of a sudden, boom, there’s a massive burst of scientific progress. If there’s some kind of stagnation, if you’re not changing those external circumstances, yes, you may start to get diminishing returns again. But that doesn’t mean there’s anything intrinsic about the situation. Maybe something external needs to change again. Obviously, a lot of people think AI is potentially going to be a driver. It certainly will at some level. To that extent, you can think of a lot of modern scientific instrumentation as really, at some level, robots. What is the James Webb Space Telescope? It’s unconventional maybe to describe it as a robot, but it’s not completely unreasonable either. It is an example of a highly automated, very sophisticated system with electronically mediated sensors and actuators, where machine learning is being used to process the data. In that sense, we’re already starting to see that transition. We’ve been seeing it for decades. I have this “smoke a joint and take a puff” thought, which—…

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