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 →

Sean Moore no published score: no usable exchanges 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
0on raw tape
0redirected or not addressed
Answered produced feed D 5 · C 5 · P 5 · Cm 5 5.00

Q All right. So talk to us. What is true face doing? And is it a pure place, at least a SAS model in terms of how you're making money?

A It was, and we've transitioned out of that into a couple of different ways of making money. One is through proof of concepts or just general proof that the technology works in the environments in which we're seeing demand for. The second then is production licensing, and a third is professional services. So one of the interesting things to note about computer vision right now is it's still very early on in the industry's adoption, and so a lot of these Fortune 500 companies or governments that we work with don't have the capacity or engineering talent To take this technology, implement it quickly and, and show ROI. And so, you know, we are having to do a lot of that handholding and it's becoming helpful for us because then we can dictate our, it helps us dictate how we build our products based on the demands of the actual customers.

AI assessment note: “It was, and we've transitioned out of that into a couple of different ways”

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