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The Data Exchange ·

Ben Lorica and Evangelos Simoudis discuss AI-assisted knowledge work. Simoudis raises concerns about how much intellectual property corporations expose to AI labs, describes the human orchestrator’s responsibility to explain generated work, and recalls lessons about link analysis after 9/11. Lisez 3 points de vue avec leurs éléments à l’appui et les liens vers les sources.

Ben LoricaEvangelos Simoudis
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En un coup d’œil

  • Corporations need to consider how much IP they expose to AI labs

    Simoudis says claims about Chinese models obtaining knowledge from U.S. models have implications beyond competition among U.S. labs. He says this makes corporations consider carefully how much of their intellectual property they expose to these labs.

    Lire le moment probant · Publisher transcript paragraph 7

  • The human orchestrator must explain how AI-generated work was produced

    In AI-augmented knowledge work, the human acts as an orchestrator who must understand—and be able to explain—how AI-generated outputs were produced; inability to do so signals quality issues.

    Lire le moment probant · Publisher transcript paragraph 42

  • Simoudis recalls a need for broader data connectivity after 9/11

    Simoudis says analysis of the events leading to 9/11 highlighted a need for broader connectivity among the available data and analysis of the links established.

    Lire le moment probant · Publisher transcript paragraph 77

Moments clés3

Extraits courts et attribués, avec le contexte permettant de les vérifier. La conversation complète reste chez son éditeur.

Publisher transcript paragraph 7 (s’ouvre dans un nouvel onglet)
AI intellectual property protection

Corporations need to consider how much IP they expose to AI labs

Extrait original

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.
Evangelos Simoudis·
Contexte

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.

Publisher transcript paragraph 42 (s’ouvre dans un nouvel onglet)
AI-assisted knowledge work evaluation

The human orchestrator must explain how AI-generated work was produced

Extrait original

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.
Evangelos Simoudis·
Contexte

Yeah.

Publisher transcript paragraph 77 (s’ouvre dans un nouvel onglet)
government data integration

Simoudis recalls a need for broader data connectivity after 9/11

Extrait original

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.
Evangelos Simoudis·
Contexte

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.

Source et méthodologie

Ces points de vue renvoient à leurs sources originales. Les reformulations sont signalées et ne sont pas des citations mot à mot.

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