The Ledger, every show

“You don't talk about the field failure rate of your products, which are massive. Rather you sort of keep talking about the future in an effort to convince people to wait, to make a good decision rather than go with technology that's, that that's better and pre…”

“And after we did it Elon tried Dojo and they failed.”

“In inference, it's not real at all. There's no CUDA lock-in in inference. None. Well, you can move from OpenAI on an NVIDIA GPU to Cerebrus to Fireworks Service on something else to Together to perplexity with 10 keystrokes. I mean, anybody who actually uses A…”

“Unwaveringly better for business. You know, there are things I agree with, there are things I disagree with in this administration, but unwaveringly better for business.”

“I think two years ago every state of the art model was trained in a Cuda flow. And right now, Gemini is trained without Cuda. Anthropical is trained without Cuda. Open AI as strange as could. So in a one or two year period, they lost 70% share. Of training mod…”

“I think the business of dashboarding and the business, the AI doesn't the damages doing the SAS is, I think, unreparable. You could ask your AI, build me a tool like Salesforce. 30 seconds later, you have a working tool.”

“They had available capacity because the Grok model wasn't used very much. So they had these GPUs that were sitting around and that's a bad idea. And so they sold a whole block of them or released a whole block of them to Anthropic.”

“There are ways for NVIDIA to use their balance sheet to limit competition, right? That if they invest in, in a NeoCloud, right? The NeoCloud is less likely to use a non-NVIDIA chip. If they invest in a model builder there's pressure not to use other people's c…”

“I think it has been NVIDIA's strategy to try and create competitors for the traditional hyperscalers. They have funded and backstopped and over allocated to the neoclouds. They have created a dependence, which is probably not healthy.”

“They got H 100. They didn't get the B 200. They didn't get the most current. They are a generation and a half, maybe two generations behind. So the, this was not a great deal. It was a good deal for Elon. He had them sitting around, but they were forced to tak…”

“I think to date, most of the layoffs were AI washed. They were, because we did boneheaded hiring, During COVID. It is actually because a great deal of productivity gains has been, have occurred over the years that we're just now harvesting. The ability to gath…”

“If we sell leading edge technology to China, will their military use it? Everybody says yes. There is no debate on that point. Their military will use it. You ask a second question, which is, if you sell our leading edge technology, will they, will their gover…”

“I would allow TSMC and Samsung both to a 20 year period free from all local and legal, local ordinances, all of them, to build fabs in their desired location in the US.”

“There has emerged in Europe a sort of be afraid of it, then regulate it, tax it, or sort of mentality that works against entrepreneurship.”

“No company ever went bankrupt by paying extraordinary people too much.”

“No, we're faster on both, but the software challenges In training are real.”

“In inference, the truth is, nobody cares about CUDA. Nobody even cares about PyTorch. All right. What they want is an API.”

“I think it's confusing. And on net, it's probably more to help. The Biden administration was misguided and afraid. And I think the Trump administration, I think to his credit, they surrounded himself with some smart people and in the AI space. And I think they…”

“The silicon industry is not a place for twenty-five-year-old CEOs, no matter how smart you are. The returns to having built parts before in what we do are enormous.”

“Really focused on performance, both for training and for inference. You think 20 times faster than Nvidia B 200 GPUs and it's been an amazing run.”

“The fundamental architecture of the GPU with off-chip memory is not great for inference. Now, they will continue to do well in inference, but it can be beaten, and I think they know it.”

“And that had never been done in a computer before, and that's at the heart of our architecture. That allowed us to yield and deliver whole wafers. Nobody had ever been able to do that in the seventy-year history of our industry.”

“ChatGPT was not really a technical innovation. It was a user interface invention.”

“You, ah, sought to limit Chinese access to EDA tools to delay the growth of a Chinese chip market. And so U.S. Venture capitalists backed tons of Chinese companies in Shenzhen to build EDA tools, right?”

“A hundred percent. I think, and it is one of the most obvious and frequent errors in judgment. Is that you underestimate the other side. I think, ah, you have to look carefully at what they're doing, and their investment in infrastructure has been extraordinar…”

“I think they're now in a situation where they're extorting customers. They're extremely expensive. They're unable to ship. And that has, among other things, opened the door for many of us who have alternatives.”

“And we were the fastest at it, and the largest, and, you know, our sales were more than 10 times the Grox, and they paid twenty billion dollars for the number two collector.”

“Remember, we did a huge deal. This is probably the largest deals in Silicon Valley history north of twenty billion dollars.”

“They are behind in chips. But their approach was at the next level is open source models where they're producing some extraordinary models. Not as good as GPT or Anthropic or Google's Gemini, but very good.”

“And so, as we do more and more AI work, and more and more agentic work, we're making more and more calls to CPUs, and therefore the demand for CPUs is through the roof.”

“In inference in AI, it's the exact opposite. You move a huge amount of data, all the weights, from memory to compute, and you need one calculation to generate the next word. And then you have to do it again. So all the time is dominated by the movement of data…”

“And so the speed of moving waits to compute is about two and a half thousand times faster here than on a Wilben GP.”

“Obviously, what follows that Is video, because a video is just a collection of images. But that takes an enormous amount of compute right now. And that's one of the reasons it's been sort of set aside by the leading labs. So unbelievably computation intensive.”

“The deal is 760 megawatts, 250 megawatts in 26 on a multi-year lease. An additional 250 megawatts in 27, on a multi-year lease, and an additional in 28, a multi-year lease.”

“We'll be doing more than twenty billion dollars of hardware with, for them over the next several years.”

“And we're the fastest, not by a little bit, but by 20 x.”

“Look, I think that we have a chance for our children or the next generation, not only to not die from cancer, but to not know anybody who died from cancer. I think that is a real achievable goal in 25 years.”

“What we're talking about now are data centers that are in the next several years going to use more power than the previous 50 years on earth took.”

“And so, you know, we have a twenty five billion dollar backlog.”

“And my view is in the next 18 months will be way over two X.”

“There's a shot that our children, none of them, nor their people they love will die of cancer.”

“So if you build a GPU, the odds that you're better than NVIDIA in our view are approximately zero.”

“So when OpenAI uses us, we're 15 or 18 times faster than a GPU.”

“I think historically more money is made after IPO than before. I think every single study shows that there is more money to be made both in percentage and in, in what we care about, which is absolute.”

“Micron is producing numbers where they have 80, 85% gross margins. I mean, they're getting software gross margins on making memory.”

“Now, we are 15 x faster because of architectural reasons.”

“When Google or when Cerebris puts our equipment in our own data center, right, we have a significant advantage Over a NeoCloud, because NeoClouds are buying hardware with gross margins of 70, 80% for NVIDIA.”

“Why do we believe that inference will be any different? There'll be zero marking for slowing them.”