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 →

Raj De Datta 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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1exchanges match
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Answered raw tape D 4 · C 4 · P 4 · Cm 4 4.00

Q Wonderful. Wonderful. Thank you. How do you train them? How do you take, uh, engineers and turn them into machine learning engineers?

A Yeah, you know, I mean, I think, first of all, um, the number of engineers taking courses on the side is like a hundred percent. You know, especially in machine learning. In machine learning, right? So, you don't need a, you actually, they're pretty self-motivated individuals in the first place. And the second is, of course, anybody who is, who is, Thought about this problem realizes, like, the pre-processing and the post-processing is a much bigger part of the problem than the actual modeling itself, much of which exists in open source domains. It's the practical application of that. So, you know, when you start getting into problem areas, you start to find that really that what you need to solve a practical problem is like, 20% algo and 80% systems, you know, in many cases. Um, and, and so we have found that just good back-end engineering skills With mentorship, and application against a problem, and self-motivation is a pretty effective combination.

AI assessment note: “good back-end engineering skills With mentorship, and application against a problem”

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