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>"This is a bit of a meta-comment, but reading through the responses to a post like this is really interesting because it demonstrates how our collective response to this stuff is (a) wildly divergent and (b) entirely anecdote-driven."

People having vastly different opinions on AI simply comes down to token usage. If you are using millions of tokens on a regular basis, you completely understand the revolutionary point we are at. If you are just chatting back and forth a bit with something here and there, you'll never see it.






So this is interesting because it's anecdotal (I presume you're a high-token user who believes it's revolutionary), but it's actually a measurable, falsifiable hypothesis in principle.

I'd love to see a survey from a major LLM API provider that correlated LLM spend (and/or tokens) with optimism for future transformativity. Correlation with a view of "current utility" would be a tautology, obviously.

I actually have the opposite intuition from you: I suspect the people using the most tokens are using it for very well-defined tasks that it's good at _now_ (entity extraction, classification, etc) and have an uncorrelated position on future potential. Full disclosure, I'm in that camp.


Token usage meaning via agentic processes. Essentially every gripe about LLMs over the last few years (hallucinations, lack of real time data, etc.) was a result of single shot prompting directly to models. No one is seriously doing that for anything at this point anymore. Yes, you spend ten times more on a task, and it takes much longer. But your results are meaningful and useful at the end, and you can actually begin to engineer systems on top of that now.

It's a tool and like all tools, it's sensitive to how you use it, and it's better for some purposes than others.

Someone who lacks experience, skill, training, or even the ability to evaluate results may try to use a tool and blame the tool when it doesn't give good results.

That said, the hype around LLMs certainly overstates their capabilities.




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