01 / belief
I think co, CO two, kla, gc, I mean these are all invested in in Harvard companies.
“I think co, CO two, kla, gc, I mean these are all invested in in Harvard companies.”
- Speaker
- Martin Casado
- Publisher
- Latent Space
Public evidence record
Published podcast speaker
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15 transcript-backed records
01 / belief
“I think co, CO two, kla, gc, I mean these are all invested in in Harvard companies.”
02 / 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.”
03 / 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.”
04 / belief
“Um, where I think, I think for some of the later stage rounds, the companies don’t need that much help.”
05 / 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.”
06 / 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.”
07 / 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.”
08 / 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.”
09 / 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.”
10 / 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.”
11 / prediction
“Like I think that’s, you know, but like the most a GI complete model will is win independent of the task.”
12 / 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.”
13 / 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.”
14 / evaluation
“Like you can’t build an app like it, it necessarily goes down just because there are no abstractions.”
15 / 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.”