NVIDIA CEO has stated that even if AI didn't exist, his company would've still been huge, but says that he is happy for the fact that AI is a reality.
NVIDIA CEO Talks AI, Competition, China, & Supply Chain Moat In Podcast, Says Accelerated Computing Has Been Their Secret Sauce
In a podcast with Dwarkesh Patel, NVIDIA CEO Jensen Huang talked about several aspects of the company. He emphasized NVIDIA's strategy in becoming a global AI superpower, while also talking about the various aspects, such as the tightening competition from ASICs, the role of China, and the supply chain moat.
AI has been a big deal for NVIDIA in recent years; it's their biggest revenue maker, and continues to break record numbers. NVIDIA's GPUs and the entire CUDA ecosystem have been the enabler behind this, pushing NVIDIA from a GPU maker to an ecosystem provider, one that spans several chips, unparalleled & massive infrastructure, and lots of money. Each generation of GPUs costs several billion dollars in R&D costs, and each GPU generation pays the company back, with unprecedented growth and demand.
But what if we lived in a world without AI? Well, Jensen says that even if there weren't any AI, NVIDIA would still have been really big, but Jensen himself feels sad even thinking about that aspect. But what would he be doing then? The answer to this is Accelerated Computing.
You see, not everything that NVIDIA does is AI. NVIDIA's primary goal was and has been Accelerated Computing, combining its GPU and CUDA capabilities with a CPU to accelerate the workload of a processor. With GPUs being massively parallel, users can offload huge amounts of code and algorithms to them, giving a 100x - 200x speedup.
Q-My final question, suppose the deep learning revolution didn't happen, what would NVIDIA be doing?
A-Accelerated computing. The same thing we've been doing all along. The premise of our company is that Moore's law is going to... General purpose computing is good for a lot of things, but for a lot of computation, it's not ideal.
And so we combined an architecture called the GPU, CUDA, to a CPU so that we can accelerate the workload of the CPU. And so different kernels of code or algorithms could be offloaded onto our GPU. And as a result, you speed up an application by 100x, 200x. And where can you use that? Well, obviously, engineering and science and physics and data processing, computer graphics, image generation. I mean, all kinds of things. Even if AI doesn't exist today, NVIDIA will be very, very large.
Jensen Huang - NVIDIA CEO
On being asked about how he feels about selling chips to China, Jensen highlighted the growing energy demands of building AI infrastructure. The US has limited energy, while in comparison, China has limitless energy resources and plants. And on the question of compute, Jensen said that China's compute is super massive, in fact, much of their data centers are running all empty.
So, despite not having access to state-of-the-art EUV toolkits from ASML, which the US and others have access to, their scale of infrastructure is enormous, and what makes things more interesting is that even with the current generation of chips they have, they can simply pull up more compute by racking up more chips.
The amount of compute they have in China is enormous. I mean, you're talking about the country is the second largest computing market in the world. If they want to deploy, aggregate their compute, they got plenty of compute to aggregate. But is that true? I mean, there's people do these estimates and they're like, well, this is actually behind on the process.
No, it's a direct. I'm about to tell you the amount of energy they have is incredible, isn't that right? AI is a parallel computing problem, isn't it? Why can't they just put four, 10 times as much chips together?
Because energy is free. They have so much energy. They have data centers that are sitting completely empty, fully powered. You know, they have ghost cities, they have ghost data centers. They have so much capacity of infrastructure. If they wanted to, they just gang up more chips, even though there's some nanometer. And their capacity of building chips is one of the largest in the world. The semiconductor industry knows that they monopolize mainstream chips. They overcapacity, they have too much capacity.
And so the idea that China won't be able to have AI chips is completely nonsense. Now, of course, if you ask me, would the United States be further ahead if the entire world had no compute at all? But that's just not an outcome. That's not a scenario that's true. They have plenty of compute already. The amount of threshold they need for the concern you're worried about, they've already reached that threshold and beyond. And so I think you misunderstand that AI is a five-layer cake. And at the lowest layer is energy. When you have abundance of energy, it makes up for chips.
Jensen Huang - NVIDIA CEO
Jensen also talked a bit about his thoughts on missing out the initial deals with OpenAI and Anthropic, saying that this was the first time they were going to invest outside of the company, and they thought it was something that companies would approach VAs for, but in the end, these state of the art labs went to hyperscalers like Microsoft, Google and Amazon instead.
Despite that, Jensen acknowledged that this just showcases that these people who made the deals were great minds alike, and AI wouldn't have been the same if it weren't for such things to happen. But for the next time, Jensen says that he will be prepared & won't make such mistakes again.
About the author: A Software Engineer by training and a PC enthusiast by passion, Hassan Mujtaba serves as Wccftech's Senior Editor for hardware section. With years of experience in the industry, he specializes in deep-dive technical analysis of next-generation CPU and GPU architectures, motherboards, and cooling solutions. His work involves not only breaking news on upcoming technologies but also extensive hands-on reviews and benchmarking.
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