Nvidia

“Everything in AI is going to require NVIDIA, and AMD is not, AMD is good, but it's not like, it can't compete with CUDA. It's good for consumer devices, right? But somebody building the next LLM, you're locked into Nvidia for the time being, right?”

“You went in on a leverage basis and you made, you know, I think the number was, you know, kind of probably at least four times your money, which is a great result, but. It could have been 25, 30 times his money.”

“Nvidia is the poster child, right? I mean, that's the one everyone talks about in Nvidia. Again, I haven't looked at that. Don't look, I don't follow stocks on a daily basis, by the way, I'm not a research analyst or a portfolio manager, but at 35 to 40 times …”

“And Silicon Graphics at that time was what the open AI of today is. Yes. Nvidia, open AI, any one of those”

“But because they're only game in town, they can charge 20,030 thousand dollars per, per module.”

“I always believe that you can't hold like 90% market share in anything. Right. So eventually, yes, you know, I know how quickly it is, you know, anybody's guess.”

“If AI was not there, you know, NVIDIA would not have been able to survive in the long term, right?”

“The reason why NVIDIA is successful is because they actually had this software, AI software, they call it CUDA, right? So now they had that hardware that runs this CUDA very, very efficiently.”

“Krutrim is one of them. So ambitious. You know, it is effectively open AI plus Nvidia plus your Microsoft or AWS all in one, right?”

“I wouldn't know this hundred X, but I think it is much larger, but you would say investments. If you look at in terms of pure investment is much larger. I mean, you look at it the way Nvidia stock has gone up. Right. So it's from pure investment perspective is…”

“You want to each 100 is four to six weeks. It takes time. It used to take six months. Now it takes four to six weeks. Now, of course the new black belt series takes six months”

“I always say that when you a solution coming out of India will be completely different for the same problem. Let's say you give a problem to, you know, to Nvidia and to a local company here, right? The solution will be different, right? And I think our solutio…”

“NVIDIA is one of the few companies in the Bay where the average employee tenure is probably closer to double digits than single digits, at least when I was working. Primarily because of the loyalty which the leadership team And Jensen engenders in the entire w…”

“So they imagined a world where you know, you kind of needed the complexity Of semiconductors. And the entire stack. Even back in 2016. Which is why NVIDIA is at the forefront of technology, even today. AMD and others are just catching up.”

“I think even things like communication speeds on chip interconnects, like we were going way ahead of what the rest of the industry was doing. It seems like a small little thing, but that made all the difference when it comes to working with the kind of workloa…”

“He says, one-on-one means politics, because I say something in a different context to one person, they go off and use that context to get things done. And sometimes reality of what our conversation was and what happens is different. So he says, when I get a re…”

“He has 60 reports. I don't know any CEO who can manage 60 reports, but I think Jensen can.”

“And we go right to the level of The NVIDIA architecture to even write our own kernels. So we are not scared of touching any part of the stack.”

“And media chips are generally very bad for voice inference. Like if you have 40 gigabytes of RAM in a NVIDIA GPU, you can generally, if you want to do real time, like a hundred milliseconds, you can use maybe two or four gigabytes of it for our models. And bey…”

“What he did do is stand up an entire data center and, you know, work with NVIDIA and get all the chipsets necessary to go stand up something in eight months, which Mark Zuckerberg himself said that he thought it'll take three years.”

“And I think all the labs are scaling this up, and we are constrained by algorithmic research, compute, and data, and companies like Turing Advance the data pillar, NVIDIA advances the compute pillar, and of course the labs advance the algorithmic research pill…”