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 →

Raymie Stata 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 5 · C 5 · P 5 · Cm 4 4.85

Q No feedback. All right. Uh, thank you for telling me that. So, uh, you, you alluded to some of this, but could you, um, maybe tell us more about AltaScale, what you guys built, and the story of the company, and all the things?

A Yeah, well, so my, my role at AltaVista and later on at, at Yahoo was to build more of the systems infrastructure than to do the machine learning. I knew enough to be dangerous as far as, say, relevance science was concerned, but, but my job was to take, The sophisticated algorithms and implement them at, at, at scale, and then to build the, the data infrastructure that the data scientists used to, to actually run these experiments that we talked about. So I did that, you know, again at AltaVista later on at Yahoo. Um, and, you know, Hadoop at Yahoo became kind of our standard infrastructure, and we made a large, large investment in that. Um, you know, through the spin out of, of Hortonworks, you know, that I was involved in as, as the CTO at the time, I kind of, We got a glimpse at how larger non-internet companies were struggling with the adoption of Hadoop. Um, you know, their clusters were kind of subscale. The, the people operating them were kind of operating them, and 10 other things at the same time. They'd have two people, not a hundred, using it, so if they, anybody got stuck, they'd immediately have to go search the web, you know, Stack Overflow to figure out what these stack traces mean. Um, and that, that was hugely unproductive. So, you know, at AltScale we said, hey, let's, you know, let's deliver Hadoop as a service And the way it's experienced at a Facebook or Y…

AI assessment note: “at AltScale we said, hey, let's, you know, let's deliver Hadoop as a service”

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