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 5 · Cm 4 4.85
Q Amazing. And the gas turbines, those were a blocker for a while too, huh?
A Uh, they still are. I mean, you know, gas turbines are, are a massive supply chain constraint. Um, as people look to energize compute infrastructure, I think a lot of people, we were really one of the first groups to be focused on, ah, you know, natural gas powered data centers, doing things behind the meter, off grid, ah, and I think a lot of people have sort of followed this pathway, ah, which has created a lot of supply chain challenges, ah, with some of the major producers, folks like GE Vernova, you know, Caterpillar has a company called Solar that we work with very closely, ah, you know, Siemens, Mitsubishi, ah, and we actually recently did something with, ah, an incredible company, Boom Supersonic,
AI assessment note: “Uh, they still are. I mean, you know, gas turbines are, are a massive supply chain constraint.”
Answered raw tape
D 5 · C 5 · P 4 · Cm 4 4.60
Q How did, did that occur because you had anticipated buying a bunch of H-one hundreds before everybody else and you had the inventory? How did that start that you got such a good lead?
A Well, so we had started well before Hopper, uh, came out. You know, we were, uh, you know, Crusoe's a business that's always taken this very energy first approach to developing computing infrastructure, um, and really changing, uh, you know, the, the, the, the, the motion from, uh, trying to find, trying to co-locate, uh, Compute in these, in these network hubs and, and really focusing on where we can access abundant, uh, energy. So, um, you know, we, uh, uh, you know, we're experimenting a lot with, you know, the amper generation, which preceded hopper. So a lot of a 100, uh, we built out this, you know, high performance cloud platform that was meant to enable AI innovators to, you know, do incredible work. Uh, you know, we launched, uh, before chat GPT came out, And so, uh, you know, sometimes you're in the right place at the right time.
AI assessment note: “we had started well before Hopper, uh, came out.”
Answered raw tape
D 5 · C 5 · P 4 · Cm 4 4.60
Q Has that informed some of your thinking? Yeah.
A Oh, absolutely. I mean, you know, he's been an inspiration from, you know, building the Gigafactory to everything he's done at, you know, uh, SpaceX and, Uh, Starbase, you know, it's all, all incredibly inspiring, and, you know, we try to channel that same sense of incredible urgency, uh, you know, parallelizing a lot of the work, uh, you know, we, we, we self-perform a lot of, you know, procurement functions and engineering functions, uh, and then, you know, work with a, a lot of, you know, very ambitious folks on the, on the construction side. Uh, there's actually a bunch of folks that worked on the Tesla Gigafactory, uh, Your new hometown in Austin. Yeah. Um, that are working on our campus in, in Aveline, Texas. So, um, there's a lot of, uh, overlap in sort of methodologies.
AI assessment note: “Oh, absolutely. I mean, you know, he's been an inspiration”
Partly raw tape
D 3 · C 4 · P 4 · Cm 3 3.55
Q give credits to startups, and maybe you could talk a little bit about how you made that decision to play the long game, because I would think there's probably some people on your board or in your own organization says, hey, hey, listen, we got some big fish here. We got whales. What are we doing with the minnows? You're specifically targeting up and coming startups to be their provider.
A Yeah. So, you know, I really think about Crusoe, you know, being a vertically integrated business is like we offer three core things, right? We can, we can build the data centers and we can rent those to, to customers. We really only focused on a small subset, maybe five customers, these very big tech, uh, tech companies. Um, and that's really their key bottleneck, right? That that's, that's their key pain point. They're not, you know, renting out capacity from clouds because, you know, Meta doesn't know how to run a GPU cluster. Like they, of course they know how to run, you know, big clusters of GPUs. They need data centers, right? So we're trying to unblock that critical pain point for them. Um, on our, uh, AI cloud platform and our infrastructure as a service platform, we offer managed clusters of high-performance GPUs, and we're a very large partner with NVIDIA, and that's really critical infrastructure for the startups that you're talking about. This is the development of new AI native applications, uh, you know, coding assistant tools, uh, you know, managed inference solutions, video generation, image generation, Uh, you know, all sorts of chatbots and, uh, you know, AI applications that are sort of, uh, proliferating in the world. Um, you know, we offer great, uh, sort of managed GPU clusters there, and then we also offer serverless, uh, AI services, like our managed in…
AI assessment note: “that's really critical infrastructure for the startups that you're talking about.”
