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Jason, you talked about summarizing a document. May take 20,000 cheap tokens to do. Of course, shoot that to a
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lagging model or an open-source model. But if you're talking about replacing a software engineer for 2 hours, that may
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take 2 million expensive tokens. And the consequence of using something that's 95% as good is really high,
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right? Because you have a long-running task, and if the task breaks early, or it breaks in the middle, or breaks at
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the end, there's a huge cost to that. So >> You still pay >> the tokens, right? You And back to this
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analogy I was using, you're pulling the slot machine and you lose. >> And the time and the compute. So, if an
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AI agent is replacing a $200 an hour consultant, right? Take that as an example. So, three consulting firms,
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they're competing, they need the smartest consultant. If they're charging 200 bucks an hour, the difference
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between spending three bucks on a cheap model or 15 bucks on an expensive model to replace a $200 an hour consultant,
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it's just irrelevant. That inference cost difference is irrelevant. If you're getting something that's bulletproof for
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15 bucks, and so I think that's what we're seeing play out. The best evidence for all of this is just revenue growth.
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I'm talking about what is Anthropic's revenue growth compared to OpenAI, compared to the open-source models.
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Millions of independent actors are choosing every single day. The open-source companies are growing,
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right? >> Yeah. >> But they're growing selling something that is really, really cheap. And
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there's room in every single market for premium products, for mid-tier products,
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and for commodity products. And I think we see a lot of this token growth. People are speculating that the
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intelligence gap between that commodity stuff and the frontier stuff is going to
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collapse to the point that people won't pay for the frontier stuff. There is no evidence of that on the field today.