NVIDIA’s CEO, Jensen Huang, has acknowledged that while artificial intelligence (AI) has significantly bolstered the company’s growth, NVIDIA would still have thrived without it. Despite this, Huang expresses a positive sentiment about AI’s emergence.
NVIDIA CEO Shares Insights on AI, Competition, and Supply Chain Strategies
In a recent podcast with Dwarkesh Patel, Jensen Huang elaborated on NVIDIA’s aspiration to establish itself as a preeminent global force in AI. The discussion also touched on critical subjects including the intensifying competition with application-specific integrated circuits (ASICs), the role of China in the AI landscape, and NVIDIA’s strategic supply chain advantages.
AI has emerged as a pivotal revenue driver for NVIDIA, facilitating unprecedented growth and success. The company’s graphics processing units (GPUs) and the entire CUDA ecosystem have evolved NVIDIA’s role from a traditional GPU manufacturer to a comprehensive ecosystem provider. This encompasses advanced chips, expansive infrastructure, and considerable financial investment in research and development, which continues to yield significant returns.
When reflecting on the hypothetical scenario of a world without AI, Huang stated that Accelerated Computing would have remained NVIDIA’s primary focus. The concept behind Accelerated Computing is to merge the capabilities of GPUs with CPUs, allowing for the offloading of substantial workloads, resulting in phenomenal speed enhancements of up to 200 times.
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
Addressing concerns over selling chips to China, Huang pointed out China’s overwhelming energy capabilities in building AI infrastructure. While the U. S.faces energy constraints, China possesses virtually limitless resources for energy production, allowing it to operate data centers often at full capacity without utilization.
Despite lacking access to the latest extreme ultraviolet (EUV) tools from ASML available elsewhere, China’s vast infrastructure offers a unique edge. Huang emphasized that they can easily boost their computing power simply by adding more chips, underscoring the massive scale at which Chinese data centers operate.
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.
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.
Jensen Huang – NVIDIA CEO
Moreover, Huang revealed his regrets over missing initial investment opportunities with organizations like OpenAI and Anthropic, highlighting that NVIDIA’s first venture into external investment could have positioned the company differently in today’s market. Instead, these significant partnerships were secured by major hyperscaler firms such as Microsoft, Google, and Amazon.
Jensen regrets that when Anthropic and OpenAI first needed billions to scale, Nvidia wasn’t in a position to invest. So these labs went to hyperscalers like Microsoft, Google, and Amazon instead, and in return committed to using their compute.“I’m not going to make that same…” pic.twitter.com/1Fj7I156UA
— Dwarkesh Patel (@dwarkesh_sp) April 15, 2026
In conclusion, Huang recognizes the intelligence of companies that seized these opportunities and acknowledges the pivotal role these initial investments play in shaping the future of AI. He assures stakeholders that he will approach future opportunities with improved readiness.
Source & ImagesRelated Articles:
Microsoft Introduces Xbox Mode for All Windows 11 PCs, Merging Console and Desktop Gaming Experiences
20:22
Samsung Ends LPDDR4 Memory Production Amid 50x Profit Surge, Predicts Increasing Memory Shortages by 2027
19:07
Ultimate Guide to Windrose PC Performance Analysis and Tuning for Optimal PC Experience
18:18
Leave a Reply