NVDA CEO Jensen Huang Comments Q2 Earnings Call:
At the highest level of growth drivers would be the evolution, the introduction, if you will, of reasoning agentic AI. Where chatbots used to be one shot, you give it a prompt and it would generate the answer, now the AI does research. It thinks and does a plan, and it might use tools. And so it's called long thinking; and the longer it thinks, oftentimes, it produces better answers.
And the amount of computation necessary for 1 shot versus reasoning agentic AI models could be 100x, 1,000x and potentially even more as the amount of research and basically reading and comprehension that it goes off to do. And so the amount of computation that has resulted in agentic AI has grown tremendously. And of course, the effectiveness has also grown tremendously. Because of agentic AI, the amount of hallucination has dropped significantly. You can now use tools and perform tasks. Enterprises have been opened up. As a result of agentic AI and vision language models, we now are seeing a breakthrough in physical AI, in robotics, autonomous systems. So the last year, AI has made tremendous progress and agentic systems, reasoning systems is completely revolutionary.
Now we built the Blackwell NVLink 72 system, a rack scale computing system, for this moment. We've been working on it for several years. This last year, we transitioned from NVLink 8, which is a node scale computing, each node is a computer, to now NVLink 72, where each rack is a computer. That disaggregation of NVLink 72 into a rack scale system was extremely hard to do, but the results are extraordinary. We're seeing orders of magnitude speed up and therefore, energy efficiency and therefore, cost effectiveness of token generation because of NVLink 72.
And so over the next couple of years, you're going to -- well, you asked about longer term. Over the next 5 years, we're going to scale into with Blackwell, with Rubin and follow-ons to scale into effectively a $3 trillion to $4 trillion AI infrastructure opportunity. The last couple of years, you have seen that CapEx has grown in just the top 4 CSPs by -- has doubled and grown to about $600 billion. So we're in the beginning of this build-out, and the AI technology advances has really enabled AI to be able to adopt and solve problems to many different industries.
As you know, the CapEx of just the top 4 hyperscalers has doubled in 2 years. As the AI revolution went into full steam, as the AI race is now on, the CapEx spend has doubled to $600 billion per year. There's 5 years between now and the end of the decade, and $600 billion only represents the top 4 hyperscalers. We still have the rest of the enterprise companies building on-prem. You have cloud service providers building around the world. United States represents about 60% of the world's compute. And over time, you would think that artificial intelligence would reflect GDP scale and growth and so -- and would be, of course, accelerating GDP growth.
And so our contribution to that is a large part of the AI infrastructure. Out of a gigawatt AI factory, which can go anywhere from $50 billion to plus or minus 10%, let's say, $50 billion to $60 billion, we represent about $35 billion plus or minus of that and $35 billion out of $50 billion per gigawatt data center.
And of course, what you get for that is not a GPU. I think people -- we're famous for building the GPU and inventing the GPU, but as you know, over the last decade, we've really transitioned to become an AI infrastructure company. It takes 6 chips just to build -- 6 different types of chips just to build a Rubin AI supercomputer. And just to scale that out to a gigawatt, you have hundreds of thousands of GPU compute nodes and a whole bunch of racks. And so we're really an AI infrastructure company, and we're hoping to continue to contribute to growing this industry, making AI more useful and then very importantly, driving the performance per watt because the world, as you mentioned, limiters, it will always likely be power limitations or AI -- building limitations. And so we need to squeeze as much out of that factory as possible.
NVIDIA's performance per unit of energy used drives the revenue growth of that factory. It directly translates. If you have a 100- megawatt factory, perf per 100 megawatt drives your revenues. It's tokens per 100 megawatts of factory. In our case also, the performance per dollar spent is so high that your gross margins are also the best. But anyhow, these are the limiters going forward and $3 trillion to $4 trillion is fairly sensible for the next 5 years.
Let me conclude with this. Blackwell is the next-generation AI platform the world has been waiting for. It delivers an exceptional generational leap. NVIDIA's NVLink 72 rack scale computing is revolutionary, arriving just in time as reasoning AI models drive order of magnitude increases in training and inference performance requirement. Blackwell Ultra is ramping at full speed and the demand is extraordinary.
Our next platform Rubin, is already in fab. We have 6 new chips that represents the Rubin platform. They have all ticked up at TSMC. Rubin will be our third-generation NVLink rack scale AI supercomputer. And so we expect to have a much more mature and fully scaled up supply chain. Blackwell and Rubin AI factory platforms will be scaling into the $3 trillion to $4 trillion global AI factory build out through the end of the decade.
Customers are building ever greater scale AI factories from thousands of Hopper GPUs in tens of megawatt data centers to now hundreds of thousands of Blackwells in 100-megawatt facilities. And soon, we'll be building millions of Rubin GPU platforms, powering multi-gigawatt multisite AI super factories.
With each generation, demand only grows. One shot chatbots have evolved into reasoning agentic AI that research, plan and use tools, driving orders of magnitude jump in compute for both training and inference. Agentic AI is reaching maturity and has opened the enterprise market to build domain and company-specific AI agents for enterprise workflows, products and services.
The age of physical AI has arrived, unlocking entirely new industries in robotics, industrial automation. Every industrial company will need to build 2 factories: 1 to build the machines and another to build their robotic AI.
This quarter, NVIDIA reached record revenues and an extraordinary milestone in our journey. The opportunity ahead is immense. A new industrial revolution has started. The AI race is on. |
