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Karina· @karinanguyen · X·· 15 小时前AI 评分45
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关于模型定制的经济学: "基于在线实验结果,反欺诈带来的预计节省约为推理成本的3倍"

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On modelcrafting economics:

"Based on the online experiment results, projected savings from fraud prevention were roughly three times the estimated inference cost"

引用Brian Armstrong@brian_armstrong
We were able to fine tune an open weight model (Qwen3.5-9B) on proprietary internal data at @coinbase, and it out performed frontier models, at much lower cost and speed, for a specialized task (fraud prevention in this case). I think we'll see more of this pattern inside companies. The frontier models are amazing generalists. But increasingly you'll see specialist models out perform on more narrow tasks, either working on teams, or by themselves. We're making it easy to fine tune models internally for our employees. We even have a skill for it in our internal harness that makes it easy to spin these up and start training them: "/fine-tune-and-serve-llm I want to fine-tune Qwen for payments risk review. help me get started" I imagine we'll have some backend services that could be replaced entirely by this new architecture.
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来源:Karina · x.com