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Evangelos Simoudis

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1 份资料 · 3 条观点 · 3 个话题

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Evangelos Simoudis 关于AI 辅助知识工作评估、AI 知识产权保护、政府数据整合的观点。 按话题阅读 3 条观点,核对 1 个来源中的证据。

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按来源发布日期整理的个人观点,仅反映这些材料中的表达,不代表其全部立场。

译文仅辅助阅读;核查观点请以原始摘录为准。

AI 知识产权保护

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AI 知识产权保护

企业需要考虑向 AI 实验室暴露多少知识产权

Simoudis 表示,关于中国模型从美国模型获取知识的说法,其影响超出了美国各实验室之间的竞争范畴。他表示,这促使企业仔细考虑向这些实验室暴露多少自身知识产权。

支持这项说法

当每个人的生产力都提高 10 倍时,就没有人真正提高了

坦白说,这让我想到了一些影响:围绕中国模型发生的一切,或者关于中国模型的说法——即它们通过蒸馏或其他手段从美国模型获取知识。所以这就是为什么这个故事对我来说极其重要,它的影响不仅限于美国各实验室之间的竞争,还涉及更广泛的层面。正如你所说,这促使企业非常谨慎地思考,他们向那些“neo-labs”开放了多少知识产权。

原始摘录
That has implications, frankly, for where my mind went: everything that is happening with Chinese models, or what is being claimed about Chinese models—that they are taking, whether through distillation or other means, knowledge from U.S. models. So this is what makes this story extremely important to me, with implications not only for what’s happening in the competition among U.S. labs, but for what’s happening more broadly. And that makes corporations, to your point, think very carefully about how much of their IP they open up to those neo-labs.
上下文

所以这里有趣的地方在于。如你所知,我经常采用企业的视角。关于 Anthropic 模型的质量和性能、为何被更广泛采用、这对 Anthropic 的收入有何影响,以及这如何让该公司准备好在年底前上市,外界已经有很多讨论。但你现在看到的是两位研究人员,其中一位显然与 Anthropic 有关联,却在使用 OpenAI 的 Codex。这是第一点。第二点是,正如你所说,OpenAI 正在接收这些提示词并用它们来改进自己的模型。我的意思是,他们已经开始接受这种说法了。

原始上下文

So here’s why it’s fascinating. As you know, I take the corporate approach a lot. There has been so much noise about the quality and performance of Anthropic’s models, why they are being adopted more broadly, how that has implications for Anthropic’s revenue, and how it makes the company ready to become public before the end of the year. Yet here you have two researchers, one of whom is clearly associated with Anthropic, using OpenAI’s Codex. That’s point number one. Point number two is the fact that OpenAI is taking these prompts, as you say, and using them to improve their model. I mean, they started accepting some of that narrative.

AI 辅助知识工作评估

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人类协调者必须解释 AI 生成的工作是如何产生的

在 AI 增强的知识工作中,人类充当协调者,必须理解并能够解释 AI 生成的输出是如何产生的;无法做到这一点则表明存在质量问题。

支持这项说法

当每个人的生产力都提高 10 倍时,就没有人真正提高了

再说一次,在我看来,能够做到这一点意味着人类是协调者。但作为协调者,你需要能够理解其中的关联。即使机器没有明确给出这些关联,你也最好能说出:“这个东西是这样得出的。”如果你做不到,我认为你的工作质量就有问题。

原始摘录
Being able to do this, again, to me, is the human as orchestrator. But as orchestrator, you need to be able to understand the connections. Even if the machine doesn’t give you the connections explicitly, you better be able to say, “Here’s how this thing was arrived at.” If you cannot, I think there are issues with the quality of your work.
上下文

是的。

原始上下文

Yeah.

政府数据整合

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政府数据整合

Simoudis 回顾了 9/11 之后对更广泛数据连接的需求

Simoudis 表示,对导致 9/11 事件的分析凸显出,需要在可用数据之间建立更广泛的连接,并对所建立的链接进行分析。

支持这项说法

当每个人的生产力都提高 10 倍时,就没有人真正提高了

分析9/11事件成因后,我们认识到:必须更广泛地连接所掌握的数据,并对已建立的关联开展后续分析。

原始摘录
the big realization from the analysis of what led to the events of 9/11 was that we really needed much broader connectivity among the data we had, and subsequent analysis of the links that were established.
上下文

实际上,我想说,对我而言,在这一转型过程中(如果可以这么说的话)相当核心的一点是,政府认识到了使用商业工具进行关联分析的重要性。很多很多年前,我曾在一个开发高度专有工具以支持此类任务的环境中工作。结果就是到处都是孤岛。我认为 这后来成为一种非常重要的方法,也进入了商业运营领域,并催生了大数据以及大规模分析我们能够整合的此类数据的技术。我认为 9/11 对数据分析的推动作用,远超我们在 1990 年代通过数据仓库及类似技术所取得的成果。它表明了整合联邦式和异构数据库的重要性。

原始上下文

Actually, I would say that, for me, what was quite central in that transition, if you will, was the realization by the government of the importance of link analysis using commercial tools. Many, many years ago, I had worked in an environment that was developing very proprietary tools to support those types of missions. As a result, there were silos galore. I think That then became a very important approach that found its way into commercial operations as well and led to big data and techniques to massively analyze that type of data that we were able to bring together. I think 9/11 did much more for data analysis than what we had previously in the 1990s with data warehousing and those kinds of technologies. It showed the importance of bringing together federated and disparate databases.

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