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 →

Mike Dauber 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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Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q so, you know, AI is obviously the theme of the, of the, of the day of the year, um, the hot topic of the moment. Um, how do you guys, uh, think about this in terms of trend? Is this now for real versus the prior, uh, incarnation of AI? Can we build businesses, uh, Uh, successfully, uh, you know, will the next billion dollar company be an AI company?

A I think it's unquestionably real. I, I mean, I, I, we have a portfolio company in the med tech space where, you know, my dad was a pathologist, and when I was a kid, it would take him, uh, 20 minutes to analyze a case, uh, to determine whether or not you had cancer. Um, You know, I think in a minute, ah, these guys can analyze half a million cases at 10% better accuracy than my dad could after, you know, 10 years as a resident and 20 years as a doctor. Um, now the FDA doesn't approve stuff like this, so you have to find different use cases for it, but from a, from a capability perspective, I remember when we were investing in the company two and a half years ago, people were kind of doing eye rolls, like, yeah, yeah, yeah. Like, ah, a machine is gonna diagnose whether or not you have breast cancer, and now it does. Um, so I, I, I think I think this is one of these things where it, it's completely overhyped. I, I agree with you. I, I mean, a number of dot AI pitches that we see are, where AI and ML are weaved into the pitch. Reminds me of green eight years ago, and cloud, or docker, or low power, all sorts of things we saw over the last decade, or obviously big data, um, but it's, it's driving such giant efficacy in certain areas. I think it's, it's, the hype is justified. It's just finding the right mix.

AI assessment note: “I think it's unquestionably real.”

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