I think this is a classic potential “correlation” problem. Probably Open AI just cherry picked data which looks good for them. They didn’t pick a hypothesis to test, just put 2 graphs next to each other that look the same which is very weak data interpretaiton. Sure both compute and revenue might have increased at 3x a year for 2 years, but that doesn’t tell us much. It doesn’t mean they have that much to do with each other directly. My guess is that of course there’s some relationship between increased compute and revenue, but how much we just don’t know. I think Open AI are reading too much into the data. At least they state a falsifiable theory of change and we’ll see if the trend continues.
”Stronger models unlock better products and broader adoption of the OpenAI platform. Adoption drives revenue, and revenue funds the next wave of compute and innovation. The cycle compounds.”
If I made this claim from this data in the global health world I would get a shug and a “that’s a nice theory, make a hypothesis and test it over the next 2-3 years then we might take you seriously”
My prediction is that you never see this graph again because this correlation trend will not continue. Open AI will just pick other graphs which look good for them next year. If it was really strongly “causally” related something similar would continue for the next 2-3 years as well.
re: “I think Open AI are reading too much into the data”, to be perfectly honest I don’t think they’re reading into anything, I just interpreted it as marketing and hence dismissed it as evidence pertaining to AI progress. I’m not even being cynical, I’ve just worked in big corporate marketing departments for many years.
I agree — a bunch of the arguments read like marketing that is greatly simplifying the real picture and not seeming very interested in digging deeper once a convenient story was found.
I think this is a classic potential “correlation” problem. Probably Open AI just cherry picked data which looks good for them. They didn’t pick a hypothesis to test, just put 2 graphs next to each other that look the same which is very weak data interpretaiton. Sure both compute and revenue might have increased at 3x a year for 2 years, but that doesn’t tell us much. It doesn’t mean they have that much to do with each other directly. My guess is that of course there’s some relationship between increased compute and revenue, but how much we just don’t know. I think Open AI are reading too much into the data. At least they state a falsifiable theory of change and we’ll see if the trend continues.
”Stronger models unlock better products and broader adoption of the OpenAI platform. Adoption drives revenue, and revenue funds the next wave of compute and innovation. The cycle compounds.”
If I made this claim from this data in the global health world I would get a shug and a “that’s a nice theory, make a hypothesis and test it over the next 2-3 years then we might take you seriously”
My prediction is that you never see this graph again because this correlation trend will not continue. Open AI will just pick other graphs which look good for them next year. If it was really strongly “causally” related something similar would continue for the next 2-3 years as well.
re: “I think Open AI are reading too much into the data”, to be perfectly honest I don’t think they’re reading into anything, I just interpreted it as marketing and hence dismissed it as evidence pertaining to AI progress. I’m not even being cynical, I’ve just worked in big corporate marketing departments for many years.
I agree — a bunch of the arguments read like marketing that is greatly simplifying the real picture and not seeming very interested in digging deeper once a convenient story was found.
makes sense. But at least they appear to be reading too much into the data lol.