Nvidia, every mention

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Verbatim, from the transcripts: the passages where Nvidia comes up

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▶ 25:31 May Habib We've got great partners, and NVIDIA's a great customer and partner, and Jensen's awesome.

▶ 24:09 Nathan Benaich Um, all these authors on it that have now gone on to found, uh, you know, Anthropic, like, Adapt, uh, they lead teams at NVIDIA, et cetera.
▶ 41:29 Nathan Benaich Um, yeah, I mean, one of the major predictions I think we, we got right like a few years ago, uh, was that when Arm and NVIDIA announced that they were going to merge, we're like, this is not going to happen for competition grounds. 9 times in the scene
▶ 44:31 Nathan Benaich So for example, last year, the most popular chip was the V-one hundred, which was released almost like six or seven years ago. 2 times in the scene

▶ 5:08 Matt Turck First, and then he announced just a few days ago that he had doubled that, or he was in the process of doubling that to 200,000 NVIDIA GPUs, and apparently the plan is to get to 300 Blackwell GPUs when they come online.
▶ 5:08 Matt Turck First, and then he announced just a few days ago that he had doubled that, or he was in the process of doubling that to 200,000 NVIDIA GPUs, and apparently the plan is to get to 300 Blackwell GPUs when they come online.
▶ 7:02 Matt Turck Uh, so, you know, obviously the company everybody loves is Nvidia. 6 times in the scene
▶ 25:24 Matt Turck Both Nvidia and TSMC were saying publicly recently that the demand for Blackwell chips was absolutely insane.
▶ 38:02 Matt Turck We talked about NVIDIA. 2 times in the scene

▶ 2:45 Matt Turck Nvidia, Model Labs, Grok, Lambda, CoreWeave, all those companies.
▶ 7:35 Erik Bernhardsson Like, you know, traditionally all these like LM inference, you know, providers obviously been building on H 100 or, you know, Nvidia GPUs, but
▶ 7:35 Erik Bernhardsson Like, you know, traditionally all these like LM inference, you know, providers obviously been building on H 100 or, you know, Nvidia GPUs, but
▶ 35:03 Erik Bernhardsson Like, for a while, like, each 100 prices were, like, almost, like, going up, and then they were kind of still for a while, and then now they're, like, actually going down quite a lot, like, you know, what I'm seeing in the market, right?

▶ 52:58 Clement Delangue So when you think about, about Microsoft, when you think about NVIDIA, uh, all, all these companies are, uh, massive customers of, of ours. 2 times in the scene

▶ 27:37 Richard Socher And, um, you know, there's also a lot of hardware companies are trying to say, oh, we're a hundred X better than this NVIDIA GPU. 2 times in the scene

▶ 35:39 Matt Turck You know, a part of the NVIDIA rise, but also Dell and, you know. 2 times in the scene

▶ 15:18 Sharon Zhou Uh, but essentially you can think of that as, um, I think, uh, NVIDIA's NIMS server, Triton inference server also does that.
▶ 15:18 Sharon Zhou Uh, but essentially you can think of that as, um, I think, uh, NVIDIA's NIMS server, Triton inference server also does that.
▶ 17:47 Sharon Zhou I think there's a graph of this showing that a 100 in particular are pretty available.
▶ 17:58 Sharon Zhou Um, H 100 still kind of.
▶ 18:23 Sharon Zhou Um, well, today we did announce something with, uh, NVIDIA. 2 times in the scene

▶ 11:34 Tomasz Tunguz Kind of like a REIT, a real estate investment trust, and that you'll, you'll produce really good profits, but you need a lot of debt, and you need special relationships with NVIDIA and the other GPU vendors to compete.

▶ 33:28 Matt Turck And you, uh, partner with NVIDIA as well, right? 6 times in the scene
▶ 33:53 Renen Hallak We're leveraging their GPUs to accelerate our database abilities with Rapids, and so many, many different touch points, both in engineering and on the go-to-market side with NVIDIA.

▶ 13:32 Cris Valenzuela So, um, there's one engineer, for example, um, he fine-tuned a version of stable efficient with, like, his own Forty-Night-y incredible work, and he figured out things that no researcher had figured out at the time.

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