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 →

Alexis Le-Quoc 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
Partly raw tape D 3 · C 3 · P 3 · Cm 2 2.85

Q And how quickly does that work? How much do you need to train?

A So, uh, the, the good thing is, it's, these are, sort of, uh, don't require any, so in the case of signal processing, it doesn't require any training, but, um, if only, well, it does require training of, of the user, so we, we provide them with, like, there, it's a class of two or three parameters, and, um, so we've essentially tuned the, tuned them, um, Um, with, so that the defaults mostly work. Um, the, the difficulty with, um, something I didn't really touch on with, with this problem. So imagine we're talking about monitoring, which means that when we trigger an alert, we ring the phone, whatever the time of day or night it is. So any false positives, our, our users are like, ah, um, luckily it doesn't happen too often, but it's just sort of a, a high, highly emotional response to our product. Um, Especially from the part of the spouses when it's three a.m. So, so we spent, and it's really the hard part about the, the science part of it is the quality is a really difficult problem. So even if we do a, um, which I like to think we're getting close to, but if we do a perfect job, you're just meeting your customer's expectations. So it's a, there's a lot of pressure behind that. That's why we invest a lot of time and money to try to figure out, well, how do we crack that?

AI assessment note: “in the case of signal processing, it doesn't require any training”

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