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 →

Thomas Sohmers 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 4 · C 4 · P 4 · Cm 4 4.00

Q so to speak, to go from FPGA to ASIC? And then there's kind of the question of, well, maybe I should just get an ASIC for like the actual model in it, which I think obviously You shouldn't do it because the models evolve and all of that, but what are you exactly burning on the ASIC? And then what are you giving up by moving away from FPGA model?

A Yeah, so I would say another big difference between us and, you know, there's other startups out there that have, you know, said that they're burning or, you know, etching the transformer architecture into silicon, and that's their approach. We're very opposed to that kind of philosophy. Like, fundamentally, what Positron has built is a linear algebra accelerator, which is optimized for matrix vector math in particular. And I would say, you know, more importantly, the fact that You know, we achieve this, this, uh, you know, massive memory bandwidth, um, to that pretty general compute, uh, architecture. So, like, I think it's pretty foolish for anyone in the industry right now to be saying that, like, transformers are going to be absolutely a hundred percent the thing that gets us to AGI, or even if they do, that there isn't a better architecture. And, you know, doing any of that, like, hardening for specific Model things. I, I don't think lasts more than, you know, two or three months at the rate that the industry moves at. And so, but the thing that I would, you know, be willing to bet, you know, uh, you know, good money, you know, the company on.

AI assessment note: “fundamentally, what Positron has built is a linear algebra accelerator”

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