Dario Amodei: uncertainty

Transcript context

…Only to decrease the profit. The effect of your entering is that profit margins go down. So, we have equilibria like this all the time in the economy where we have a few players. Profits are not astronomical. Margins are not astronomical, but they’re not zero. That’s what we see on cloud. Cloud is very undifferentiated. Models are more differentiated than cloud. Everyone knows Claude is good at different things than GPT is good at, than Gemini is good at. It’s not just that Claude’s good at coding, GPT is good at math and reasoning. It’s more subtle than that. Models are good at different types of coding. Models have different styles. I think these things are actually quite different from each other, and so I would expect more differentiation than you see in cloud. Now, there actually is one counter-argument. That counter-argument is if the process of producing models, if AI models can do that themselves, then that could spread throughout the economy. But that is not an argument for commoditizing AI models in general. That’s kind of an argument for commoditizing the whole economy at once. I don’t know what quite happens in that world where basically anyone can do anything, anyone can build anything, and there’s no moat around anything at all. I don’t know, maybe we want that world. Maybe that’s the end state here. Maybe when AI models can do everything, if we’ve solved all the safety and security problems, that’s one of the mechanisms for the economy just flattening itself again. But that’s kind of far post-”country of geniuses in the data center.” Maybe a finer way to put that potential point is: 1) it seems like AI research is especially loaded on raw intellectual power, which will be especially abundant in the world of AGI. And 2) if you just look at the world today, there are very few technologies that seem to be diffusing as fast as AI algorithmic progress. So that does hint that this industry is sort of structurally diffusive.…

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