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 →

Jake Flomenberg 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 5 · C 5 · P 4 · Cm 4 4.60

Q Alright, great, thank you. So we're gonna talk about big data, we're gonna talk about AI, but like taking things, uh, sequentially, um, what do you, and at a very high level, what do you, what do you find interesting about big data as a trend? Where are we in the cycle? What has been done? What needs to be done? Whoever wants to jump in first.

A Sure, so, um, I, I think we're hopefully in a little bit of a period of consolidation. I think we've seen the proliferation of a whole bunch of data management systems, a whole bunch of ways to deliver data, a whole bunch of ways to prepare data, a whole bunch of ways to do BI on, on data at these new scales with, you know, these different properties, um, and certainly there's room for others, um, but I think that ecosystem is, is starting to mature, and as we look at all these companies, in order for some of them to Aspire to be the next Oracle, the, the next, you know, decabillion dollar company in the enterprise space, what we need is the apps on top, right? Um, it was a lot simpler back in the day when everyone agreed, everyone just speak this ANSI SQL thing, and you can do great stuff on top, now we have 80 different ways to communicate, so it's gotten a lot harder in some sense, but the opportunity for teams of people that have deep domain expertise and know how to use this modern data infrastructure, um, I think is really interesting, and if there can be a couple winners at each layers of the stack, That we just described. There's room for, you know, a hundred winners across every different facet of application-facing enterprise software.

AI assessment note: “we're hopefully in a little bit of a period of consolidation.”

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