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 →

Greg Kamradt 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.

clear all ✕
1exchanges match
1on raw tape
0redirected or not addressed
Answered raw tape D 4 · C 4 · P 4 · Cm 4 4.00

Q What has been the most surprising thing working on it for you in the last year or so? Like you went from underrated to obviously, as Sean said, very popular. Do you think there's something fundamentally different about either the models that you're testing against or people's interests or just right time the space is growing?

A Well, I think nothing happens in the vacuum right time. The space is growing. However, the way that we think about our company is if we were a company or nonprofit, if we're going to equate it to a startup, the product That we have is the benchmark. And so you're not going to convince the community. You can't BS your way through a poorly, inappropriately designed benchmark. And so the great work that Francois did, like the foundational research that he did in the flag he put in the ground, that is what the differentiator was for it. And so in 2024, um, we were solving for awareness and we're very happy where that ended at the end of last year. Um, we left, uh, 2024 with open AI, uh, inviting us to come join them on. Their O three model, uh, preview for it and like, and, uh, and not co-announcing the results for that. So, um, solve for awareness and now we have to solve for a whole lot more.

AI assessment note: “nothing happens in the vacuum right time. The space is growing. However”

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