The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Sam Altman no published score: only 1 usable exchange on raw tape, and a fair score needs 8+ record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

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Redirected raw tape D 2 · C 4 · P 3 · Cm 3 3.00

Q the, the, the experience of creating, uh, these assets is, uh, wildly innovative. We saw stories get cloned. We saw, saw, uh, you know, algo video short form feeds get cloned. I, I expect many other platforms to be looking at this functionality and realizing that this might be, uh, the future. You guys certainly believe, uh, that, that it could be, uh, important, so. How quickly do you think?

A We're actually totally okay with a world where we do the product innovation and everybody else copies, and I don't think it works for them as well as they think it does. Like the, the, you know, a lot of people have tried copying ChatGPT, uh, in, you can go look at some of our competitors' apps, and they even copy the mistakes. They even copy the design decisions we really wish we hadn't made. And maybe it's worked well for them. I guess I kind of hope it has, but it's been fine for us. I, I think like the, the, the, the key to this is not any one innovation, but it's repeatedly Putting them out again and again, and being first to come up with them and put them into a cohesive offering, and you know, that's what we want to be good at. And if other people want to clone the stuff that works, we also sometimes clone stuff that works. That's fine. But, but mostly we want to be able to drive the innovation, and I think Bill and his team have done an incredible job of figuring out how people actually want to use these video models, what the models need to do. Really, they've approached this as a full stack problem from How do you train the video model to how do you make this enjoyable for users? But cameos are one out of many ideas they have from here on the journey to like the product that we hope to eventually build. And so if people take some inspiration from us and copy us along …

AI assessment note: “We're actually totally okay with a world where we do the product innovation and everybody else copies”

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