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0/1 resolved calls right
1 scored · avg 65
single source
7
companies · 36 data points
Nvidia will face competitive pressure on its prices and profit margins that will begin to impact the company within one to two years.
What happened: Nvidia began to feel pricing pressure and a slight drop in profit margins as competitors such as AMD, Apple, and in‑house silicon from cloud providers entered the high‑end GPU market; this pressure was evident in Nvidia’s 2025–2026 earnings reports, though the impact was less severe than the prediction implied.
Verify at source ↗I think it's kind of, it's less politically easy, right? Like it's kind of like everybody loves their iOS phone. And, you know, there's, there's less of a blue and red, you know, kind of combo tackle. Where, you know, the, the blue feet, people are like, hate big companies. Apple's less offensive, basically.
I think that the prime candidate is likely to be, and I'm speaking as an individual and as a venture capitalist here, is Apple with the App Store.
And that's part of what the bet that OpenAI and Anthropic and the hyperscalers are all making is that that return to scale.
when I was involved in those conversations at OpenAI, they agreed with that. Microsoft certainly agrees with that in terms of, you know, how do we make sure that economics are fairly apportioned and so forth for, you know, what we're doing for, you know, this phase of, you know, and ongoing
I didn't get any shares for the 10 million that I put in. And by the way, it's not just legal technicalities. Right. Um, and so, you know, and the 501C3 continues to, you know, control the kind of control the, the, the, the mission and destiny and so forth.
I, by the way, I put in 10 million at the same time and I don't have any shares from those 10 million.
I think it's without, without basis, without merit.
the Microsoft OpenAI deal came together with, you know, converting the LP into a subsidiary of the nonprofit
I led the first commercial series, first commercial round.
Now, in the pure model competition, the question is, when do we start seeing a asymptote to scale? And my guess is, and, you know, kind of the GPT landmarks is each order of magnitude, my guess is the soonest will be GPT-6. And it might not even, it may even be after that. And that's part of what the bet that OpenAI and Anthropic and the hyperscalers are all making is that that return to scale.
I was claiming it was going to be, once safety, open access and not differential or controlling access. For that. And I think they stayed true to that principle, which is, I think, the genesis of the word open is there.
Yeah. Look, from the very founding of OpenAI, I was never claiming it was going to be open source.
Microsoft certainly agrees with that in terms of, you know, how do we make sure that economics are fairly apportioned and so forth for, you know, what we're doing for, you know, this phase of, you know, and ongoing, but like, you know, there's a current tech, new technological wave that's coming and how do you do that?
the Microsoft OpenAI deal came together with, you know, converting the LP into a subsidiary of the nonprofit, you know, kind of saying, look, there's all kinds of benefits that both OpenAI and Microsoft can get from a business deal.
one of the really great technical papers that I love from Microsoft is, you know, all you need is textbooks.
I think Satya is like the best public market CEO of our generation. I think he is stunning in kind of blending combination of strategic insight with also kind of being, you know, kind of return on capital, you know, sensible risk taking, et cetera. And so, the actual thing between your guys' questions in terms of, because I can comment on how Satya thinks with this stuff, is he's both thinking about, like, it's a platform change and you have to be there for the platform change, for productivity,
So I think it's not sustainable. The pure heat is not sustainable. But I think it's, you know, NVIDIA has got a very strong position.
You know, NVIDIA has a very sharp, you know, lead on the importance of the chips for the training clusters. You know, they're effective on inference. But I do think that as you kind of scale the demand, there'll be a lot of inference chips coming in. You know, I think, Chamath, you're invested in one of those. And I think there's going to be a bunch of those kind of coming in and the bulk of the demand will be on the inference side. And then NVIDIA will have this challenge of, do I try to keep m
And I basically told them to say, hey look, it's sustainable for two years, which for you guys means forever. Yeah.
And we do this merger with X.com and and, you know, like pre the merger closing, you know, Elon is saying, oh, I got the CEO, Bill Harris. He's best ever. That's part of the reason why you should give so much percentage of the company to X.com and the merger, you know. And then after the merger, literally the first meeting I had with Elon, it's Bill Harris, a complete disaster. We need to fire him right away. Like before we get to the first board meeting, we need him fired.
Peter and Max recruited just a tremendous focus on on like intense learning curves. So, you know, it was one of the things that Peter later is like, OK, I guess you have to interview for being on sports teams and so forth because this teamwork thing does matter. But like high performers and it was kind of like a like and that was part of the reason why there was such intense, you know, kind of innovation and capability.
David very quickly, because he, you know, has a strong learning curve as he plays these things, kind of got the instinct of what the game we were playing with PayPal was. And it's part of the reason why I think, you know, each of the execs have, you know, kind of key contributions to making, you know, kind of PayPal successful. And David's was this kind of, like, maniacal focus on the kind of the cycle of how the product worked on eBay.
if you look at kind of chat GBT, it's, it's oriented at, like, kind of more of equivalent of a kind of a search engine, like, here's, here's a list answer to every question. It's an instant Wikipedia like answer.
there's a ton of stuff that businesses need, human beings needs over that, that open AI is not going to do directly.
if you're your theory of the game is, I'm going to directly compete with open AI, you better have a good theory of the case, just a little bit like if you say, well, I'm going to launch a desktop search engine, you better have a good theory of the case, it's not impossible to do. It's just, you know, it's a challenging Everest mountain, better come equipped, have a good competitive theory, good risk theory, a good reason why you're doing something that they won't be doing.
they're one company of 450 people, they have a nonprofit primary research agenda on beneficial artificial intelligence and AGI specifically to do this. And they're not in, they're not trying to create a whole bunch of business stuff.
They're going to be providing API's across a number of things. So you know that those API's then create kind of an open access to a whole bunch of developers and a whole bunch of consumers and a variety of tech, but then other companies that might want to be a monopolist in that area can't do it.
open AI is definitely an 800 pound gorilla. Awesome. They have a great mission, a great team, a bunch of other things.
the open AI mission stays the same, which is open access and open provisioning for as broad a range of humanity as you can do consumers, developers, etc. It was never necessary of necessity open source. That was how other people were hearing it. And I think the organization was neutral on the question. It's like, Look, if we can do it open source, and make it safe, totally happy to do it. That's part of making the mission. But it was like, Well, we don't know if we'll be able to do that. And so
I believe what we will have a personal assistant for any professional informational task, which is professional task. I process information, you do something with you make an investment decision, write a memo, write a prescription, something like that. Two to five years for every professional activity.
it gave what was like, kind of I call it an MBA professors, you know, business school professors, analysis that doesn't really very smart person, but doesn't really understand venture capital. So it's like, right, well, you would look at the areas that have the largest TAMs. And you look at which products and services had the greatest substitution or alternative impact because of this AI technology, then you go find teams that were capable of addressing that, and then you would invest in those t
I remember when I was playing with GBD four, uh, last year, uh, July and August, you know, I was on the board of open AI. And I started like doing prompts and questions and I was like, oh, this is good. This is amazing.
pitched airbnb as couch surfing but they said oh it's it's a great thing because you can rent people's couches and i went oh that's a terrible idea i'm not a terrible idea yeah
because it's kind of like the it's ebay but for space on this whole range and it goes of course you can include a couch but include a room an apartment a castle the whole thing
i'm gonna make you an offer to invest let's spend the rest of this time working together so you get a sense of me let's bring bring your challenges out put it down on on the table
unfortunately not to have been uh an investor and and and along the ride with a spectacular team doing an amazing transformation in the world