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 →

Ramin Hasani 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 4 · P 4 · Cm 4 4.30

Q So we're in a very secret location that has no AC, but we can't say anything more than that. What are you so excited about, or why are you so excited about RAISE this year? And tell us about Liquid AI.

A Definitely. So I feel like this year they have exponentially kind of, uh, improved the quality of like their guests, you know, that's what I can say. And then the structure is much more mature. Like, uh, as I've seen it like before, like there's like multiple conferences happening at the same time. There's Makina, you know, and then there's raise and, uh, everything is related to the, to the, to the stuff that we do. We are in, we are bringing foundation models to the physical world. You know, so physical AI is extremely important for us, and, um, that space is becoming more and more, um, interesting. We're building foundation models that are so cheap that you can bring them on raspberry pies, for example, so you can host them on any kind of device that is on the planet.

AI assessment note: “improved the quality of like their guests... We are bringing foundation models”

page 1
Made with StarZero

Turn any episode into a week of clips.

This entire site, over 160 episodes transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.