Latent Space / episode intelligence
Speakers in the public record
Claim mix
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
27 published records
01 / belief
“Total. And I think, you know, stuff like BD for example, you wouldn’t usually need BD when you were seed stage trying to get market biz Devrel.”
02 / belief
“I think the other piece, maybe just to add onto this, and I’m gonna quote Martine in front of him, but this is probably also a unique time in that.”
03 / belief
“Uh, you know, obviously they should share it themselves, but, um, they’ve, you know, I think when you bring a team of that caliber together, there’s special things that happen.”
04 / belief
“I think co, CO two, kla, gc, I mean these are all invested in in Harvard companies.”
05 / commitment
“If I can raise more money than the aggregate of everybody that’s using it, I will consume them whether I’m a GI or not.”
06 / belief
“Um, cool. But, you know, if you go back to, let’s say March, 2024, that period, it felt like a, I think an open source model with an, like a, you know, benchmark leading capability was sort of launching on a daily basis at that point.”
07 / belief
“Sorry, what am I, one more thing I think is, is underused in all of this is like, to what extent every task is a GI complete.”
08 / belief
“Maybe decade, but, uh, uh, just like I, I think, you know, I, I just going back to the discussion about how a GI would just kind of consume everything.”
09 / belief
“Every domain has a specialist, and we think if you can win that, you become very large, very quickly, and that’s actually played out in the numbers.”
10 / belief
“I think from a, but I think from the intern that that’s sort of like where the companies are headquartered.”
11 / belief
“I, I mean, to me, like, you know, philanthropic, like building on cloud code, I think, uh, it makes sense to me the, the real.”
12 / belief
“I, I think that, uh, you know, speaking about ad there’s, there’s a really like interesting tie in that obviously you guys are hit on, which is like these sort, this sort of like America first movement or like sort of re industrialized here.”
13 / belief
“Um, where I think, I think for some of the later stage rounds, the companies don’t need that much help.”
14 / belief
“My, my, uh, sort of, uh, thesis, which we’re not gonna have to go into here is actually I think a, um, what I’ve been calling Agent Labs, which are [00:54:00] people who build on top of, uh, all the other models.”
15 / belief
“Like actually just like be aware of how much of the interaction has nothing to do with coding and it just turns out to be a large portion of it. And so like, you’re, I think like, like the best Soto ish model.”
16 / commitment
“I will say this is the furthest, so we have a very privileged position on the boards of these companies, and like I’ll say, I’ve never seen.”
17 / belief
“Um, and I think a lot of the big, I think, you know, opening eyes, feeling that, um, anthropic if they haven’t started, you know, felt it, certainly given the success of their products, they may start to feel that soon.”
18 / observation
“You know, I think right now there’s almost a barbell, like you’re like the hot thing on X, you’re deep tech.”
19 / evaluation
“I, I agree. So it feels so, it feel, it feels this way to me too. It’s like, it is like, basically Zuckerberg kind of came out swinging and then now he’s kind of back to building.”
20 / recommendation
“We’d, everybody would be happy with these returns, but we’ve got this kind of mania on these, these strong growths. And so I would say that that’s probably the most underinvested sector.”
21 / preference
“I think like it’s important to hear you guys’ perspective because the rest of us are just kind of looking at headlines and not knowing how to make sense of any of this.”
22 / recommendation
“You start with a foundation model and then you verticalize up, or you start with the app and all of the product data and you go down and they’re the ones that are doing that. I think any company that’s doing an app has to ask the margin question.”
23 / prediction
“Like I think that’s, you know, but like the most a GI complete model will is win independent of the task.”
24 / evaluation
“Clearly from the AV wave deep map, clearly from the AV wave, I would say scale AI was actually a horizontal one for That’s fair, you know, for robotics early on.”
25 / evaluation
“My belief is if you actually look at the numbers of these companies, so generally if you look at the numbers of these companies, if you look at like the amount they’re making and how much they, they spent training the last model, they’re gross margin positive.”
26 / evaluation
“Like you can’t build an app like it, it necessarily goes down just because there are no abstractions.”
27 / prediction
“There could be a, a systemic situation where the soda models can raise so much money that they can out pay anybody that bills on top of ‘em, which would be something I don’t think we’ve ever seen before just because we were so bottlenecked in engineering, and this is a very open question.”