Claims that China cannot build AI chips, cannot manufacture at scale, or is years behind the US are all false — China's chip and manufacturing capabilities are essentially caught up, not meaningfully behind.
Jensen dismisses the narrative that China can't build advanced AI chips or manufacture at scale, or that it lags the US by years, saying the gap is essentially gone ('nanoseconds') and the US must compete accordingly. ✦ AI generated
Jensen Huang · BG2 Pod · 2025-09-26 · original ↗
starts at this moment · 10:51
“now where do we stand today between Nvidia and China? And can you reiterate kind of what you think we as a country should be doing to put ourselves in a best position to win the AI race around the world?”
Some of the things I heard, they could never build AI chips. That just sounded insane. Two, that China can't manufacture. China can't manufacture. If there's one thing they could do is manufacture. And three, they're years behind us. Is it two years, three years? Come on. They're nanoseconds behind us. And so we've got to go compete.
verbatim transcript · starts at 10:51
10:49most important point that general general purpose computing is over and the future is accelerated computing and AI computing. >> That's the first point. >> And so the way to think about that is there's how much how many trillions of dollars of computing infrastructures in the world that has to be refreshed. >> Right. Right. And when it gets refreshed it's going to be accelerated comput. >> That's right. And so the first thing you
11:12have to realize is that general purpose computing and nobody disputes that. Everybody goes, "Yeah, we completely agree with that. General purpose computing is over. Moore's law is dead." People say these things. And so what does that mean? So general purpose computing is going to go to accelerated computing. Our partnership with Intel is recognizing that general purpose computing needs to be fused with accelerated computing to create opportunities for them.
11:33>> Is that right? And so one, >> general purpose computing is shifting to accelerated computing and AI. Two, the first use case of AI is actually already everywhere, >> right? >> It's in search recommener engines, >> isn't that right? In shopping. The basic hypers scale computing infrastructure used to be CPUs doing recommenders, right? >> Is now going to GPUs >> doing AI, >> right? >> So you just take classical computing,
12:04it's going to accelerated computing AI. You take hypers scale computing is going from CPUs to accelerated computing and AI and then now that's the second point just feeding the metas the Google's the bite dances the Amazons >> and take their classical traditional way of doing hyperscaling and moving into AI >> that's hundreds of billions of dollars >> and and because that may be four billion people on the planet today if you take
12:33Tik Tok meta into account >> that's Google into account who are already demanding workloads that are driven by accelerated comput. >> That's exactly right. And so there a simp without even thinking about AI creating new opportunities. It's about AI shifting how you used to do something to the way new way of doing something. Okay. And then now let's talk about the future. I just so far I've only spoken