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 →

Ping Li 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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Partly raw tape D 3 · C 4 · P 4 · Cm 3 3.55

Q experience that, you know, from your portfolio, portfolio companies of, um, uh, where we are in the level of awareness on the customer side? So let's talk about enterprise adoption. Is there a lot of evangelization going on, um, and how do they sell? Is there a lot of discussions around ROI, and if so, how do you establish the ROI of a big data, um, you know, software solution?

A I think the thing that I would say on that is enterprises are not new to data, so I think this whole big data thing is sometimes people think it's some sort of new phenomenon that no one's ever thought about how to extract value from data and, you know, make smart business decisions, so I think enterprises understand about, you know, we're sitting at Bloomberg, right? You guys understand data and healthcare companies and Pharmaceutical companies, they all understand the, the value of data. I think what's changed is their ability to actually manipulate larger scale data, do more interesting things with the data they couldn't do before, right? So I think the value of data has gotten bigger, and I think that, for me, big data has nothing to do with the size. It's actually the value of the data people are extracting. It doesn't have to be large data sets. In fact, you know, most of the Hadoop clusters you see in the enterprise are not that big, but it's they're doing things they couldn't do before because they're taking unstructured data and mixing it with other relational data and actually doing More fundamental analysis that they couldn't do before. So I think a lot of the enterprises get it, and one of the things I find particularly interesting is so many of the technologies that we talk about, ah, ah, in these big data world is actually coming out of the internet data centers, …

AI assessment note: “a lot of the enterprises get it”

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