nafyi.安东·莱希特谈AI部署、经济颠覆与风险
原始摘录
we have a big lag in terms of deploying even the current level of capabilities to the economy. And I think if we switched all the compute that exists in the West right now to only inference, we'd find economic, productive applications for all the models that would allow us to justify the investment on all the frontier models
翻译 · 非原文措辞
我们在将当前水平的能力部署到经济中的过程中存在很大的滞后。我认为，如果我们把西方现有的全部算力都切换到只做推理，我们会为所有这些模型找到具备经济与生产价值的应用场景，从而让我们能够证明对所有前沿模型的投资是合理的。
上下文
那么股市呢？我想就此再追问一点。我目前的理论是，暂停实际上对股市未必有那么糟，因为模型已经足够聪明，真正制约需求的不是它们的能力，而是人类有效部署它们的能力。所以它们在千禧年大奖难题上的成功率是10%还是30%其实并不重要——更关键的是，会计部门的Bob能做什么，才能一个人完成两个人的工作量？你怎么看？我认为相关公司的估值——无论是未上市公司，还是AI供应链中的上市公司——很可能建立在我们能做到远超于此的预期之上。它们或许并未完全陷入AGI狂热，但我确实认为，其估值所预期的每GPU推理价格（或不管那是什么），远高于让会计部门的Bob为Fable 5.1付费所合理的价格。如果你想合理解释这些估值，如果你想合理解释建设的规模、你所预期的合同形态和需求形态，那它更像是与制药和材料科学等领域签订数百万乃至数千万美元的研发加速合同，在这些领域AI能做出重大贡献并帮助你发现极其有利可图的新药——诸如此类。你可能还预期会有进一步的内部效能提升，以及真正具备市场竞争力的自动化AI研发用途——能够索要高得多的价格的编程智能体。
原始上下文
How about the stock market? I wanted to do one follow-up on that. My theory right now is that a pause wouldn't actually be that bad for the stock market, because the models are smart enough that demand isn't really limited by their capability, but by human ability to deploy them effectively. So it doesn't really matter if they succeed 10% of the time or 30% of the time on Millennium Prize problems — it's much more like, what can Bob in accounting do to get two people's worth of work done as one person? What do you think? I think the valuations of the companies — both the non-IPO companies and the publicly listed companies that are in the AI supply chain — probably rest on us doing more than that. They're probably not entirely AGI-pilled, but I do think they expect a per-GPU inference price, or whatever that is, that's a lot higher than what would make sense for Bob from accounting to pay for even Fable 5.1. If you want to make sense of the valuations, and if you want to make sense of the scale of the build-out, the shape of contract and the shape of demand you're expecting is more like millions and millions of dollars in R&D acceleration contracts with pharma and material science and so on, where they can make major contributions and help you find extremely profitable new drugs — that kind of thing. You're probably also expecting further internal uplift and actually competitively priced automated AI R&D uses — coding agents that are able to ask for much, much higher prices.
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