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 →
Answered raw tape
D 5 · C 5 · P 4 · Cm 4 4.60
Q Yeah. No, no, which is going back to the point that we made on open source, but if you know in the back of your mind that there's something that's 90% as good, but it's 90% cheaper, how does that factor in? Because we've also never had that, that factor as we're going through this growth curve.
A I mean, since, almost since we started the pod, you know, I've, I've routinely highlighted that the steepness of that price curve on, you know, As you, as it kind of becomes, you know, less, less cutting edge is something I've never seen before. I've never, ever seen it. And I'm sure that a lot of, um, people sit around and say, well, it's okay if I'm losing money here because, you know, six months from now, I'll just use the older model. And we also talked in the past about how in the internet age, all the startups began with Oracle and Sun. And eventually they all moved to Linux and MySQL. And so there was a, there was a, we got to win it all cost phase. And then there was a phase where you started worrying about cost and optimization. And so one day, one day we'll likely, you know, make that, make that move. And, and, and I, a few of the companies I've talked to that are running inference at scale, they are already starting to think that way. Like they're looking, they're looking at it, you know, from that way. From that lens.
AI assessment note: “it's okay if I'm losing money here because, you know, six months from now”
Redirected raw tape
D 2 · C 4 · P 4 · Cm 3 3.25
Q Yep. But that's probably where most of their tokens are being processed anyways at this point, Bill, right? Like transcribing YouTube videos and, you know, all you can Google meet, you can turn it on and all those searches.
A I was just inferring in your question, maybe I shouldn't have been that, that they'll have an advantage for Google cloud. And in, in order for that to be true, they need to, to have this crossover moment. One quick thing Brad on, on open AI, you know, I'm, I've, I've been writing a book which I've talked about frequently, and I've been quite, ah, although I guess there's some privacy things now you need to be worried about, but I've been quite open with OpenAI about the book and doing research, you know, along the way. It knows a tremendous amount about my book right now, and I can ask follow-up questions without having to put the whole book back in the prompt again. Um, because of that. And so, I can, I would, I would continue to believe that OpenAI's, um, most likely chance to long-term, um, success comes from switching cost and lock-in more than it will come from staying on the edge of the, of the model race. Because I think.
AI assessment note: “One quick thing Brad on, on open AI”
Not addressed raw tape
D 1 · C 4 · P 3 · Cm 3 2.70
Q in scaling like that because I've already got the compute. Um, you know, I can go from ten million to hundred million billion to ten billion dollars on reasoning in such a quick succession. And so this, this, the performance improvements we'll get out of these models is, is humongous, right? In, in the coming, you know, six months to a year in certain benchmarks where you have functional verifiers.
A Um, quick question, and we promised we'd go to these alternatives, so we'll have to get there eventually, but, um, if you go back, we've, we've used this internet wave comparison multiple times. When all of the venture-backed companies got started on the internet, they were all on Oracle and Sun. And five years later, they weren't on Oracle or Sun. And some have argued that went from a development sandbox world to a optimization world. Is that likely to happen? Is there an equivalency here or not? And if you could touch on why the, the, the back end is so steep and cheap, like, you know, just, you, you go a model, you know, behind, or you, you, like, the, the token, the price you can save by just backing up a little bit is nutty.
AI assessment note: “quick question, and we promised we'd go to these alternatives”
