# Nvidia’s Jensen Huang on the AI revolution, job losses and what drives him | Full interview

https://www.youtube.com/watch?v=XVoyL8rzhWs

[00:00] I hope to die on the job.
[00:03] The narrative that connects AI to job loss for many of the CEOs that are doing it, um, it is just too lazy.
[00:11] Well, China is going to be everybody's greatest rival.
[00:13] Jensen, thank you so much for joining us.
[00:16] Victoria, it's great to be with you.
[00:18] Yeah.
[00:20] You know, in today's world, it's hard to imagine AI without you and Nvidia.
[00:26] So can you share with us your vision of this AI revolution and where will we be five years from now?
[00:32] AI is a revolutionary technology.
[00:34] No, no question.
[00:35] Um just like the invention of uh information technology with IBM and the personal computer with Microsoft and Intel and of course Taiwan was central to that.
[00:48] um the internet uh mobile cloud and now here we are with artificial intelligence.
[00:53] The the big breakthrough of artificial intelligence is on multiple levels.
[00:56] On the one hand, it's a
[01:02] brand new uh technology that is able to enable a whole new class of applications.
[01:06] that were impossible before because you can now understand information, you can reason, you can plan to come up with a action plan and and even now with agentic AI, you can take action, use tools and so so the applications of artificial intelligence just like humans are quite vast and almost boundless in potential.
[01:30] But artificial intelligence is more important than that even you know unlike unlike um many new technologies.
[01:37] Artificial intelligence opens up a whole new industry and a good framework to think about for artificial intelligence is that AI is not just a model.
[01:44] AI is really a five layer cake to think about it um from the lowest level.
[01:51] It requires energy because AI is produced generated in real time just like you and I right now we need calories we need energy so
[02:03] that we can engage each other and produce generate intelligence generate answers based on the question you just asked me and and I'm and I can generate it for the very first time in this way.
[02:16] based on the fact that um I'm with the audience of CNA and I'm here in Taipei and so the context is different the the circumstances are different so the answer is different and so we need energy at the lowest level for this industry.
[02:30] the next level is chips this is where Nvidia is and where a lot of the companies in Taiwan are in and the layer above that is infrastructure land power data center as well as the cloud service software that turns the chips into a cloud service into a data center.
[02:52] the layer Above that is where most people think about when they think about AI which is models.
[02:56] ChatGBT was revolutionary.
[02:58] Um uh Claude code is now incredibly successful.
[03:02] Um but AI is much
[03:05] more than just human language.
[03:08] AI can process information of almost any kind.
[03:10] from English and Chinese um all the way to videos and images but very importantly proteins and chemicals and uh three-dimensional geometry which is really important for manufacturing which is important here in Taiwan.
[03:25] And so that's the model layer.
[03:28] Then above that ultimately that's the the most important which is how does all of these this AI technology impact society in a in a positive way and so that would be applications for uh information workers like ourselves and I use AI every day you probably use AI every day um but it's much more than that it's you know software engineers and chip designers and manufacturing managers and plant managers all the way to of course self-driving cars and robotics and healthcare and just about every large industry in the world is going to be impacted by this and it will be
[04:06] revolutionized by this.
[04:08] And so the the thing that's really really helpful for me is to take a step back and look at AI not in the context of just the model but look at it in the context of the whole industry.
[04:20] And when you do that, you come to realize that AI is reinventing every industry from energy all the way to all of the applications above.
[04:31] And you've talked about agentic AI.
[04:34] Now in simple terms, what is it and uh how will it change the game?
[04:39] Agentic AI is called agentic AI for its agency.
[04:43] Agency simply means it has the ability to do things autonomously with very little supervision or a lot of supervision just like just like people and so agentic agentic pipeline uh has several stages one it starts with what is the context what's the environment what's the circumstance and what is
[05:07] being asked of what are you asking this AI to do?
[05:10] and so you start with you are an excellent uh news reporter, you know, or you're an excellent software engineer and I would like you to uh access these files, use this as an example, and I would like you to write the software for example or write the story with me.
[05:31] And so that's the context in the request.
[05:35] From that, it has to understand the context.
[05:38] It has to plan its work.
[05:41] It has to use whatever tools that it uses.
[05:43] It could be a browser.
[05:47] It could be a word document, a word editor.
[05:49] It could be um a C compiler.
[05:51] It could be a Python, you know, editor.
[05:53] It could be it could be a a CUDA program, for example.
[05:56] And so it could figure out a way uh you could use these different tools and then it would perform and then it would evaluate, re-evaluate, replan, exercise, you know, act again, evaluate.
[06:08] and just keep iterating until it gets the job done.
[06:12] just like just like um just like we do.
[06:15] And so it performs the task autonomously which is the reason why we say it's agents.
[06:17] Agents has two forms.
[06:20] There's a there's the the digital version that we call AI agents.
[06:23] In the future, these AI agents would also run inside a physical body, for example, a robot.
[06:33] So a robot is essentially a physical AI agent.
[06:36] And so these two these two examples of autonomous systems will likely be highly generalized and very exciting.
[06:48] Could that make human lazier thinkers?
[06:53] Because if everyone has a powerful assistant, then what happens to mastery?
[06:57] Well, I think you could use history as a guide.
[07:00] Um when the personal computer came along, I think that everybody said uh is
[07:08] that going to make people lazier as a result because so much of work is going to be so many tasks will be automated.
[07:15] and then when the internet came along are are people going to stop being smart because all the information is at their fingertips.
[07:23] and and then before you know it mobile cloud came along so it's actually in our pocket so we don't have to remember anything anymore.
[07:29] And um uh we have so many automation capabilities the the performance of a computer increased by a million times during during this time.
[07:40] Do we find ourselves busier or less busy?
[07:43] And I think the answer is we found ourselves busier.
[07:47] And the reason for that is because we became more ambitious.
[07:49] The type of things that we could do is greater than ever.
[07:52] Our students today that are graduating, they're a hundred times smarter than when I graduated.
[07:59] The what they know, what they can do, their exposure to the world, the knowledge they have, the wisdom that they somehow imbued.
[08:06] Um, all
[08:10] of that all of that capability was made possible because of information technology,
[08:13] but it hasn't made them, you know, any less busy.
[08:16] I think you and I would admit we're busier than ever.
[08:21] And so I think the same thing is going to happen to artificial intelligence.
[08:24] We're we're in our jobs in our lives.
[08:27] We have many tasks and it's really a basket of tasks.
[08:31] You know, a job is like a basket of tasks, many small components of things that in totality brings meaning to our work.
[08:38] It allows us to achieve our purpose of our of our of our work.
[08:43] So for example, a radiologist looks at the images, the scans of maybe ultrasounds or CT or MRIs, but that's the task that they do.
[08:53] And now it's completely AI automated, but their purpose is really to diagnose disease, help patients get well, help them understand their disease better.
[09:06] So the purpose of a job is a collection of of
[09:10] tasks, a basket of tasks.
[09:13] Many of those tasks will be automated and my sense is that as a result um of automation, we can focus on the harder parts of our work and the harder parts of our work elevate is elevated as a result.
[09:27] We could be more ambitious.
[09:29] My guess is that we'll probably be busier.
[09:32] The opposite I just said the opposite of what most people say.
[09:36] And um I have live, you know, I'm living proof of it.
[09:38] You are living proof of it.
[09:40] And speaking of jobs, everyone is curious.
[09:42] U we are seeing more and more companies cutting jobs while they're investing heavily in AI.
[09:51] So on a scale of 1 to 10, how inevitable are job cuts because of AI?
[09:55] And what do you say to people who are afraid of losing their jobs to AI?
[10:01] I would say to the people who are worried about losing their jobs to AI to learn AI.
[10:05] You're not going to lose your jobs to AI.
[10:08] You're gonna lose your job to somebody who learned AI better than
[10:13] You.
[10:15] When the PC came along, the PC didn't take people's jobs.
[10:20] The people who didn't learn how to use PCs were left behind.
[10:22] You know, when the computers came along, the computer industry, I had the benefit of being swept along with this incredible growth of this industry.
[10:32] I could have of course rejected it and went to another field where the computers was not involved and I could have been left behind.
[10:41] And so my recommendation is don't allow yourself to be left behind by AI.
[10:44] Now let's talk about let's talk about what's going on.
[10:49] Um it is very it's more likely that the companies with ambition will be more productive.
[10:56] They will do things faster.
[11:00] Their company would increase in velocity.
[11:02] As a result, they become larger, more profitable.
[11:04] When they become larger and more profitable, they'll end up hiring more people.
[11:09] And and um uh of course, they'll use more
[11:14] AI, but they'll also hire more people.
[11:16] Nvidia today has AI all over our company.
[11:19] We're hiring more people.
[11:21] We're moving faster.
[11:23] We're more and more ambitious.
[11:25] The type of things that we used to think was going to take 10 years, I now think is going to take one or two years.
[11:28] And so your ambition has to be elevated by the technology of the time.
[11:35] If you don't engage the technology of your time, you'll just simply be left behind.
[11:40] And so my recommendation is to engage it.
[11:43] Now the future the future when people think about job loss and AI um there what they see is that that there's only so much work in the world world to do.
[11:55] There's so much only so many stories to write only so much code to write only so many products to design only so many things to enjoy and that is completely obviously false.
[12:09] the number the our ambition if great then
[12:16] automation and AI which is the ultimate version of automation would elevate your company would elevate GDP as a result
[12:25] you know we should be be able to bring more prosperity
[12:28] but what kind of jobs do you envision that AI would create
[12:32] well look at all the jobs that are being created already number one remember I gave you the framework of AI AI is a five layer
[12:42] It needs energy.
[12:45] The country, the company, the region, Taiwan, the island, if limited by by energy would simply be left behind.
[12:54] You need energy in order to enjoy this new industry.
[12:58] And when you have energ when you need them AI is now so much market driven uh initiatives so much market driven incentives that the amount of in investment going into the energy sector is upgrading our energy grid.
[13:11] It's investing in sustainable energy all by
[13:16] itself for the first time.
[13:18] All you have to do is look at the stock price of all of my partners, GE, Verova, you know, Mitsubishi, uh, Seammens, everybody, their anybody who's in the power generation, energy generation industry, their stock prices are going up, they're hiring more people, their revenues are increasing, the utilities um are seeing so many opportunities to invest in their power grid.
[13:42] The next layer up is chips.
[13:47] Every single partner of Nvidia stock price has tripled in just a couple of years.
[13:51] I'm so happy to see everybody's success.
[13:53] And so everything from AI chips to DRAMs to of course TSMC and packaging and power regulators and cooling systems and you name it.
[14:04] Even multi-layer ceramic ceram ceramic capacitors uh incredible success.
[14:09] And so you could see it's of course creating a lot of jobs.
[14:13] The next layer above that is
[14:17] infrastructure.
[14:20] Look at how many data centers are being built around the world.
[14:21] How much land being dedicated to building data centers.
[14:27] And so electricians and plumbers and construction workers, architects and designers and technicians and networking engineers, just the number of jobs be hundreds of thousands just in the United States alone.
[14:41] And so probably millions around the world.
[14:43] And then just keep going up every single layer.
[14:45] And then one more statistic.
[14:49] Last year was the single largest year of venture capital investments in human history.
[14:54] $100 billion in just one year went into AI native companies.
[15:01] Whole bunch of jobs being created.
[15:03] And so there's there's absolutely every single evidence that AI is creating jobs.
[15:07] And one of my favorites is literally radiology.
[15:11] If you look at radiology and all the radiologists looking at war stations, looking for disease, looking for anomalies in the scans, in the last 5
[15:20] years, in the last 10 years, it was predicted that it would be the first job to completely be wiped out.
[15:29] Well, the researcher who made that prediction was absolutely right.
[15:35] AI has completely revolutionized radiology.
[15:37] AI has integrated into radiology in every single respect.
[15:42] However, the number of radiologists grew, the demand for radiologists increased and the pay of radiologists went up.
[15:50] And so my point is it is very more it's more likely that AI will elevate your job, elevate the purpose of your job if you became expert at it.
[15:58] Try to engage it.
[16:01] Don't be afraid of it.
[16:04] Of course, the industry has to be really thoughtful about building AI in a safe way, in a guardrailed way, and make sure that it's deployed in a proper way, and that and that the end applications, whether it's in healthcare or transportation or manufacturing or you know, air travel or whatever it is that
[16:20] applies AI, those industries have lots of regulations already and they should re-evaluate the regulations to be AI ready, to be AI prepared.
[16:30] And so um everybody has to be part of this.
[16:33] You might remember some stories of the past.
[16:36] Um so for example when the automobile came along and of course there was a entire industry of horses and carriages and and that industry was quite large.
[16:50] Of course they've been around a long long time hundreds of years.
[16:52] And then of course the invention of the of the car of the automobile came along.
[16:56] Well, because it's so transformative, every infrastructure had to be reinvented.
[17:03] Number one, a whole bunch of new factories created a whole bunch of jobs.
[17:08] Every single road had to be enhanced.
[17:10] The old roads were problematic.
[17:14] New social norms.
[17:16] For example, for a while there uh it was believed that cars were killing children.
[17:20] Cars were somehow
[17:25] And what was discovered was because in the olden times children would literally play in the streets.
[17:31] I still remember when I grew up I just played in the streets.
[17:33] And so children would play in the streets.
[17:35] And of course when cars came along many of them uh didn't realize it and they were they were got themselves injured.
[17:41] And so new norms uh pedestrian laws pedestrian rules I guess sidewalks you know so on so forth.
[17:48] And so we built up all these different social infrastructure um uh and uh new technologies with self-breaking and so on so forth.
[17:57] All of these technologies and of course social norms to to know don't run into the streets you know and so so all of those different different um conditions had to be uh built up to support a whole industry.
[18:11] Electricity was the same way and so on so forth that artificial intelligence will be the same as well.
[18:16] And for all the parents out there, what do you suggest their kids should be studying in order to stay relevant in
[18:24] the age of AI?
[18:26] I think that it won't matter.
[18:28] All the things that used to matter are still things that are going to matter in the future.
[18:32] For example, uh uh broadcasts, news, newscasters.
[18:36] Uh it will be just as important to inform people as the past uh to know what questions to ask.
[18:42] You've prepared a lot of questions, but the best reporters and the best interviewers are the ones that are prepared, but you're also staying in the moment, listening to my question and picking up on something that maybe the audience would be interested in.
[18:58] And so, you're thinking about multiple things at exactly the same time, just like I'm doing right now.
[19:03] I'm thinking about the audience.
[19:06] I'm listening to the questions.
[19:08] I'm considering everything that's happening in the world at the moment.
[19:10] and the question the answers to my question has to be consistent with that and so all of that is completely true still the ability to tell a story for an audience um will remain um just as important in the future as it is today uh whether it's it's a uh arts the
[19:27] arts will be just as important
[19:29] wobbishabi the beauty of imperfection
[19:32] will probably be even more important in the future than today and so making movies um you know designing cars and making chips will all still be as important as you know as the past.
[19:43] Yeah. Yeah. So whatever you decide is your passion uh the only one thing that you have to do is to make sure that you ask yourself how can AI help elevate my learning my craft you know my purpose.
[19:58] Now let's talk about China. You were in Beijing with President Trump recently.
[20:03] Can you take us through your trip on Air Force One and the meetings on the ground?
[20:09] What are some of your biggest takeaways?
[20:11] First of all, it was a it was a great honor to represent the United States and it was a great honor for for me to accommodate accompany uh President Trump.
[20:20] He called me in the morning.
[20:22] He he didn't realize I wasn't going and um uh and he he insisted I get on the plane
[20:28] and uh go. And so I packed up in a
[20:31] hurry. He called me in the morning as he
[20:33] was leaving uh and uh he thought I was
[20:36] in Washington DC to jump on Air Force
[20:37] One, but I was in the West Coast. And so
[20:40] he he told me just you know uh meet me
[20:42] in Alaska. And so so I flew Alaska,
[20:45] jumped on Air Force One and uh went to
[20:48] China. Um I I was there I was there with
[20:51] 16 I think other CEOs and uh and it
[20:55] represents um quite a large collection
[20:58] of great companies um from uh consumer
[21:01] electronics of course to uh industrials
[21:04] and automotive and and all the way to
[21:06] financials and um and and biotech and
[21:11] and so it was a large large collection
[21:13] of industry that was represented and and
[21:16] the conversations were were um uh one uh
[21:21] really really welcomed uh uh President
[21:24] Xi um uh Premier Lee Chang were
[21:28] extremely welcoming and they spoke about
[21:31] uh cooperation and a stable relationship
[21:33] and um and that that um China would be
[21:38] an open market and even o more wide open
[21:41] than before uh encouraged investment and
[21:45] um uh and then that we were there to to
[21:47] really uh uh represent the United States
[21:50] support the president and um they had
[21:52] wonderful meetings. Uh they were they uh
[21:55] uh were extremely cordial. Um the uh the
[21:59] feelings were great and um uh and the
[22:02] pump and circumstance and uh all of the
[22:05] festiv festivities were were quite
[22:07] impressive. But that was it. That was
[22:09] basically it. I was there for a couple
[22:10] days. Uh we didn't sleep for a couple of
[22:13] days and and then I uh when President
[22:15] Trump left left to go go go back home uh
[22:19] I went went to uh went to uh Oldtown
[22:22] Beijing to enjoy some nice meals.
[22:25] >> How was that?
[22:26] >> It was great. It was great. Yeah, it was
[22:28] people were very nice and um
[22:31] uh and uh uh anyhow was it was a really
[22:35] really great experience. But reports
[22:38] suggest that China hasn't purchased any
[22:40] of the Nvidia's H200 chips um despite US
[22:45] export approval. Now um so you have also
[22:50] said that Nvidia has stepped back from
[22:52] China um as it pushes for its own chips.
[22:56] Could that actually um eventually make
[23:00] China your greatest uh rival?
[23:04] Um well, China is going to be
[23:06] everybody's greatest rival. I mean that
[23:07] that goes without saying because they
[23:09] have so they have such um such an
[23:12] extraordinary uh local market that is
[23:15] completely uniform just like United
[23:17] States uh every single state speaks
[23:19] English. uh China every province speaks
[23:21] Chinese and that's a a substantial
[23:24] advantage uh versus Europe where every
[23:27] single country speaks a different
[23:28] language and and or uh countries where
[23:32] where everybody spoke this speaks the
[23:34] same language but the market's not very
[23:36] big and so these two countries United
[23:38] States and China uh have a substantial
[23:41] advantage because of that reason large
[23:43] population very well educated um the the
[23:47] uh the science technology and math of of
[23:50] uh Chinese students is extraordinary and
[23:51] they produce it at very high volumes,
[23:54] large volumes. Uh Chinua universities
[23:56] and many of the other universities are
[23:58] worldclass in science and technology
[24:00] today and so so one you have to
[24:03] recognize uh the country is large. It's
[24:06] it's a has a uni uniform culture. Um and
[24:09] so uh uh and they they uh have really
[24:13] treasured and valued science and
[24:15] technology. The companies are very
[24:17] competitive, super vibrant.
[24:19] uh incredible companies from uh Alibaba
[24:22] to Xiaomi to Tencent uh BU and these
[24:25] amazing companies large and also so many
[24:27] small companies uh that are so vibrant
[24:30] and and so I think it goes without
[24:32] saying that that China's uh pace of
[24:36] innovation and um its own natural
[24:39] resources including its pe people and
[24:42] its culture u will will and will almost
[24:46] certainly uh guarantee that China will
[24:49] compete with every industry and they are
[24:51] very competitive and so so I think that
[24:54] goes without saying. Um with with um
[24:57] with respect to us I
[25:01] um we're not stepping back from China.
[25:04] Uh I I would say I would say that the
[25:06] Chinese government uh when we were
[25:08] banned from going to United going to
[25:10] China uh through export controls uh it
[25:13] left a vacuum that the Chinese companies
[25:16] were able to fill and uh as a result
[25:20] Huawei and many of the startup companies
[25:22] in in China had record years. uh they
[25:25] are now growing at an incredible pace
[25:28] and and in our absence uh even though
[25:31] Nvidia's technology is better uh it is
[25:34] in our absence um available technology
[25:36] is the best we can get and it's plenty
[25:38] good and so so I think I think um my
[25:42] only statement was that that the Chinese
[25:45] government is is um understandably um as
[25:48] every government would and should uh
[25:50] encourage and want to have conditions
[25:52] for their local companies to be
[25:54] successful. However, uh I also believe
[25:57] that Nvidia could add an enormous amount
[25:59] of value to the Chinese market and it's
[26:02] good for the United States and uh
[26:04] President Trump has been very clear that
[26:05] he wants uh uh American companies to
[26:08] succeed all over the world just as every
[26:10] every country should uh every country
[26:13] should maximize exports. every company,
[26:15] every country should um uh want their
[26:18] companies to succeed worldwide and and
[26:21] uh and so it's sensible that that United
[26:23] States would want Nvidia to go back to
[26:26] uh and serve serve every single market.
[26:28] Uh for China, Nvidia's technology uh
[26:32] competes with one layer of the five of
[26:34] the five layer cake. We compete with one
[26:37] layer of the five layer cake. But don't
[26:39] forget AI is a five layer cake. And so
[26:42] when when Nvidia is participating in
[26:44] China and serving the Chinese market as
[26:46] we have in the in the past, it supports
[26:48] the expansion of the other five layers.
[26:51] And so when you look at look at the
[26:54] market in a more holistic way and and I
[26:57] and I surely believe that the the the
[27:00] leaders uh will and the local markets
[27:02] will when you look at it in the holistic
[27:04] way, Infinity could be of great service
[27:06] to that industry and we could add a lot
[27:08] of value uh to the China market as well.
[27:10] And so so I think when when our when
[27:12] Nvidia grows, the entire supply chain
[27:15] grows. Uh when Nvidia grows, uh as you
[27:18] as you see, we lift all of Taiwan with
[27:20] us and and so uh Nvidia succeeding
[27:25] around the world will be great for the
[27:26] supply chain and it will be great for
[27:28] all the local markets. Well, would you
[27:30] say that we're seeing the rise of two
[27:33] separate AI u ecosystems, one led by the
[27:36] US and the other by China and can they
[27:39] coexist?
[27:41] >> Um it is possible that that uh two AI
[27:45] ecosystems are created but it's not
[27:47] wise.
[27:49] Uh AI is obviously very very uh uh
[27:53] capable technology. It's transformative
[27:55] technology and it's dual use. On the one
[27:58] hand, uh its incredible potential for
[28:02] good is unbelievable and its
[28:06] demonstration and transformative
[28:08] capabilities for good is already
[28:10] demonstrated to be incredible and and I
[28:13] and I have every confidence that it will
[28:15] continue to do so. On the other hand, it
[28:17] could also be used in all kinds of uh
[28:20] other ways. It could be used for uh ways
[28:23] that that um could bring harm. And so
[28:27] the more the more that the world leaders
[28:32] in technology as well as in in pol in in
[28:35] in uh uh social leaders and political
[28:38] leaders that the more that all the
[28:41] leaders uh work together,
[28:44] cooperate together to advance this
[28:47] technology uh in harmony and for good,
[28:50] the better it will be for the future.
[28:52] And so I I have every I believe that
[28:55] that uh China and United States should
[28:58] cooperate in AI, not just compete in AI.
[29:01] And it is possible to do both. I work
[29:03] with so many competitors today. They're
[29:07] competitors of mine, but I also compete
[29:09] with them on the one hand, and we c
[29:11] cooperate greatly on the other hand,
[29:13] because we want what's in the best
[29:15] interest of the industry. We want what's
[29:17] in the best interest of the market. We
[29:19] want what's best interest for society.
[29:21] And so therefore cooperating ensures
[29:24] that harmonious advance. And so I I
[29:28] think that um it is absolutely true for
[29:30] AI that on the one hand we compete on
[29:33] the other hand we should absolutely
[29:35] cooperate.
[29:36] >> And we know that Taiwan sits in the
[29:38] center of the global supply chain. And
[29:41] what do you what kind of role do you
[29:43] think Taiwan plays in the AI race and
[29:45] how long do you think Taiwan can
[29:47] maintain that advantage? Well, Taiwan
[29:51] has the letters AI in it. And so AI is
[29:55] at the center of Taiwan and this this uh
[30:00] the companies on this island are are
[30:02] incredible. As you know, the companies
[30:06] are at the epicenter of the uh the uh
[30:10] possibility of AI and the growth of AI,
[30:13] the advancement of AI. uh in the last
[30:16] several years uh several things are
[30:18] happening at the same time. On the one
[30:21] hand, supply chains have to be
[30:23] diversified because the world supply
[30:25] chain is so broad, so large and because
[30:27] AI, the computer is not just a tool for
[30:31] you and I anymore. the computer what
[30:34] Nvidia makes is now a factory
[30:38] and infrastructure for the world and and
[30:42] therefore the supply chain by nature
[30:45] would have to be more resilient more
[30:47] diversified because it's going to be so
[30:49] large and so on the on the one hand uh
[30:52] the supply chain is diversifying around
[30:54] the world fabs are being built all
[30:56] around the world chip plants packaging
[30:59] plants computer plants are being built
[31:01] all around the world on the one hand on
[31:03] the other hand it's growing incredibly
[31:05] here in Taiwan the energy pressure is
[31:08] high the land pressure is high and uh of
[31:12] course uh Taiwan is extraordinary at
[31:15] manufacturing
[31:17] and uh uh and I hope we talk about
[31:19] robotics and how robotics is going to
[31:21] revolutionize and transform Taiwan's
[31:24] ability to continue to grow at an
[31:27] incredible pace. uh no no no no no no
[31:30] region uh is is uh uh better prepared
[31:34] for the continued growth of AI than
[31:37] Taiwan. And I I I absolutely uh uh
[31:41] continue to expect Taiwan to grow at an
[31:44] outpaced, you know, at a very
[31:46] accelerated pace uh for many years to
[31:49] come. And um and and it's an investment
[31:51] of people, you know, of course um at the
[31:55] scale that we are today. Nvidia is a
[31:57] multiundred billion dollar company now.
[31:59] We're one of the largest companies in
[32:01] the world and we're growing at nearly
[32:03] 100% per year at the scale that we're
[32:06] talking about. And so the the the
[32:10] partnerships that we have here in
[32:11] Taiwan, how they've uh helped me grow
[32:14] and support our growth is incredible.
[32:17] And then but the the most important
[32:18] thing is the investment in people. Uh we
[32:21] have a very large site here and we're
[32:23] going to have a much much larger site
[32:24] here soon.
[32:25] >> Can you give us a sneak preview on the
[32:28] investment amount?
[32:30] >> Well, you know, it's not it's not just
[32:32] about, you know, the money. I mean, of
[32:34] course, of course, Nvidia spends
[32:38] at this point, you know, hundreds of
[32:42] billions of dollars
[32:44] in AI infrastructure and most of our
[32:46] spend is in Taiwan. And so, we've we've
[32:52] invested through the most the best form
[32:54] of investment, which is business, uh,
[32:57] hundreds of billions of dollars into
[32:59] Taiwan. And if you look at our next
[33:02] several years, uh, between Grace
[33:04] Blackwell and Vera Rubin, we have $1
[33:08] trillion of sales.
[33:11] One trillion dollars of sales is
[33:13] hundreds of billions of dollars of
[33:16] spending equipped revenues that will
[33:19] come into Taiwan. It's just an
[33:21] extraordinary number and the highest
[33:24] ever in history for Taiwan. And so so
[33:27] that's that's our our best form of
[33:29] investment. Uh we of course also invest
[33:32] in companies here. We support them with
[33:35] prepayments. We support them with
[33:37] investment in their capital. We support
[33:39] them with commitments in our purchase.
[33:42] And then uh my favorite form of
[33:44] investment is still ultimately people
[33:46] hiring a lot of engineers here and
[33:48] having a lot of uh great employees here
[33:50] in Taiwan. and also among all the
[33:52] business leaders in Taiwan. I know
[33:54] you're very close to Morris Chain, TSMC
[33:57] founder and can you describe your
[33:59] friendship and also what have you
[34:02] learned from him?
[34:03] >> I I learned from him every time I'm with
[34:04] him. I was with him last night. Uh
[34:07] Morris Morris and Sophie had my parents
[34:11] Lori and I and and Madison was with us
[34:13] as well. We were over to for dinner. We
[34:16] had a wonderful time together. Um, you
[34:19] know, of course Morris and I have a lot
[34:20] in common uh because because uh uh we
[34:24] grew, you know, I grew up uh with the
[34:27] support of Morris and and uh when I came
[34:30] to Taiwan
[34:32] uh for the first time after
[34:36] I left when I was five years go five
[34:38] years old. Uh I came back for the first
[34:41] time to see Morris and um I've I've been
[34:45] coming back a lot since then and so so
[34:48] um you know without without TSMC and
[34:51] Morris uh Nvidia wouldn't be here today
[34:54] and it was the support and the
[34:56] friendship and and the and the risk that
[34:59] they take and back in the old days when
[35:01] we were quite small um all all of the
[35:04] things that that and our growth together
[35:06] innovation together and and of course uh
[35:09] the creation of of the AI industry that
[35:11] we know today together. Um all of that
[35:14] all of our journey and all of our
[35:15] history uh are highly intertwined. And
[35:18] so we we you know we in a lot of ways um
[35:21] I grew up with the support of Morris and
[35:24] the support of TSMC. Uh we have a lot of
[35:26] interest in in how the industry is
[35:28] forming. Um we have a lot of we have a
[35:31] lot of interest in in uh ensuring the
[35:34] continued success uh of the industry.
[35:37] And of course, you know, we have a lot
[35:38] of a lot of wonderful life stories to
[35:40] share with each other. And uh he he's a
[35:42] he's an incredible uh avid reader. And
[35:45] so it's always fun to to hear about, you
[35:48] know, his his uh summaries of the books
[35:50] that he's read and and um you know, and
[35:53] and so all of all of that is great. I
[35:55] always I always treasure my time with
[35:57] him and he's he's doing great. Uh and um
[36:01] we always have a nice nice glass of
[36:03] whiskey together.
[36:04] >> That's nice. Um, now let's move on to
[36:07] the fun part. Let's talk about you. Um,
[36:09] born in Taiwan, lived in Thailand before
[36:12] moving to the US.
[36:14] >> How have those experiences shape who you
[36:17] are today and the way you lead?
[36:20] >> Uh, I I guess I guess we're all the
[36:22] products of our parents. Um, my father
[36:26] is is very technical. I very precise.
[36:31] uh does work perfectly and uh perfect
[36:35] handwriting, does everything perfectly,
[36:38] you know, his his level of craft and
[36:41] precision and just the way he does
[36:43] everything in his life um is something
[36:46] that I had the benefit of learning from
[36:48] and and uh on the other hand u my mom's
[36:52] uh obsession for details uh uh just a a
[36:57] deep obsession for for um you know she
[37:00] She has a personality that can't let
[37:02] anything go, you know, and and um in a
[37:06] lot of ways, I think I've picked up that
[37:08] part of her her uh her her behavior and
[37:11] and so, you know, I I can focus on
[37:13] something for a very long time like it
[37:15] for 33 years and uh and uh every day I'm
[37:19] equally obsessed and equally, you know,
[37:21] equally uh intense about about doing a
[37:24] good job and and so I think I had the
[37:26] benefit of of uh uh growing up uh with a
[37:30] lot of those Taiwanese characteristics,
[37:32] you know, um they're they're they're
[37:35] very much like a Taiwanese Taiwanese uh
[37:37] parent. Um I I also think that that we
[37:40] grew up they they sacrificed a lot uh
[37:44] leaving Taiwan and and uh left their
[37:47] left families behind and uh they went to
[37:50] Thailand with very little and they went
[37:52] to United States with nothing. And so um
[37:56] when they went to United States uh we
[37:58] were basically alone. Uh there were no
[38:01] friends, no family uh you know to be
[38:03] there with us and um
[38:07] and because they were they were so
[38:09] modest uh and we had so little uh and
[38:13] and uh uh living in the United States
[38:16] going from Taiwan is is very challenging
[38:19] because the cost of living is so much
[38:21] higher and and so I I think I think um
[38:25] our humble humble uh life and uh uh and
[38:31] just seeing my parents uh struggle and
[38:34] and um uh finding a place in in a
[38:37] strange world uh and the risks that they
[38:40] took so that we can we can grow up in
[38:42] America and enjoy the American dream uh
[38:45] and have the opportunities that led to
[38:47] led to uh Nvidia today and led to me
[38:49] today. uh that all of those sacrifices
[38:53] um uh instills instills a a character in
[38:58] you. And so uh I'm grateful for uh all
[39:02] the sacrifices and the hard work that
[39:04] they they uh uh they made so that I
[39:08] could be here and so but I think that
[39:11] that journey was really an important
[39:12] part. In your company, you're known to
[39:14] be a tough boss,
[39:16] >> and you've said that um you rather
[39:19] torture people to greatness than to fire
[39:22] them. How exactly do you do that?
[39:25] >> I Well, it's not it's not physical
[39:27] torture.
[39:29] It's it's the it's torture the same way
[39:32] that Taiwanese parents torture people,
[39:34] you know. You know, a Taiwanese parent,
[39:37] it nothing is ever good enough.
[39:39] Nothing is ever good enough. and and uh
[39:43] you can't go you can't go a day without
[39:46] without some criticism.
[39:49] And that's the Taiwanese way. And I'm
[39:52] kind of the same way. Uh you can't you
[39:55] can't show me something without me
[39:56] giving you some criticism. And and I
[39:59] guess in a lot of ways that that's
[40:00] that's my form of torture. You know, I I
[40:03] will I will give you my feedback um
[40:05] always always uh immediately. Um I'll
[40:09] never save it away.
[40:11] uh once I give you my feedback, just
[40:13] like a Taiwanese parent, once the
[40:15] feedback is given, you're back to loving
[40:17] the person again. And and so you're I'm
[40:20] I'm always uh I'm always uh uh critical
[40:24] of of everybody's work so that I can
[40:26] help them be better. I want them to be
[40:29] better. I know they could be better. And
[40:32] and so that's where where it's coming
[40:34] from. And uh you know, maybe maybe a lot
[40:36] of that is my Taiwanese parent. And how
[40:39] do they how do your employees respond to
[40:41] that?
[40:43] >> Well, you know, Nvidia's Nvidia's
[40:45] retention is the best in the world. Uh
[40:48] uh we have we have employees that have
[40:50] been with me now for 33 years. And so
[40:54] people don't people don't uh don't quit
[40:57] easily from from Nvidia. and and uh uh
[41:01] you know we my job is to create an
[41:04] environment where all of these amazing
[41:06] computer scientists and engineers and um
[41:09] supply chain experts can come to Nvidia
[41:12] to do their life's work and that's my
[41:14] job to create that condition so that
[41:17] they could realize their dreams just as
[41:19] that just as they've helped me realize
[41:21] my dreams and um I and I I think that
[41:25] that's ultimately the purpose of
[41:27] leadership is to create the conditions
[41:29] for other people to realize their
[41:31] dreams. Uh to to be part of yours, of
[41:34] course, and to be part of something
[41:36] bigger. Uh but to to be able to turn
[41:38] their their what is their job, their
[41:41] profession, their craft hopefully into
[41:43] their life's work. And um at NVIDIA, you
[41:46] could do that.
[41:48] >> And we know that you work seven days a
[41:50] week.
[41:50] >> Um what drives you dayto day and where
[41:54] exactly do you get all that energy?
[41:57] I'm exhausted all the time. Um,
[42:01] what what drives me uh I mean it's it's
[42:06] some it's several things. it it's on the
[42:08] one hand I I on the one hand it's as as
[42:13] basic as I don't want to fail and I
[42:15] don't want Nvidia to fail and uh I don't
[42:17] I don't want Nvidia to fail because we
[42:19] have too many uh too many people who who
[42:22] are counting on me and so uh you know
[42:25] it's employees as our partners as our
[42:27] ecosystem uh partners is you know all of
[42:31] my friends here in Taiwan I want
[42:32] everybody to succeed and so there's
[42:35] there's a there's a burden on on leaders
[42:40] uh that want everybody to to to flourish
[42:43] and to realize their dreams and to, you
[42:45] know, to hopefully uh succeed with us.
[42:48] And so there's a there's a there's a
[42:51] burden that comes with that and and um
[42:54] that gets me out of bed every day. Uh at
[42:56] the same time there's a there's a
[42:59] hopeful optimistic
[43:02] um uh ambitious part of me that that
[43:06] wants to build something that that uh
[43:08] makes an impact makes a contribution. Uh
[43:12] there's a there's a dreamer part of me
[43:14] that that wants to create that future
[43:16] and hope hope to see it in my lifetime.
[43:19] And so I'm in a hurry to to uh have it
[43:23] come true. Um and so it's simultaneously
[43:27] the burden of the burden of of uh of
[43:30] success and and wanting other people to
[43:33] come along. Uh the the fear of failure
[43:37] uh that that somehow because of how I
[43:41] was raised uh because Nvidia has enjoyed
[43:44] um and gone through a lot of very
[43:46] difficult time. It was not easy to build
[43:48] Nvidia. It was not easy to to uh uh to
[43:52] be here today. and and all of the
[43:54] struggles can never leave my body. You
[43:57] know, once once you've struggled as
[43:59] deeply as as Nvidia has and as I as I've
[44:02] had the the benefit of, it becomes part
[44:05] of your character and it never leaves
[44:06] you. And so, simultaneously, all of this
[44:09] is happening in my body, in my brain.
[44:11] And and so,
[44:14] you can't help but be, you know, always
[44:16] thinking about work. Mhm. And you uh
[44:18] some people have said that you still
[44:20] have another 30 years running Nvidia.
[44:23] What do you think about that? And what
[44:26] kind of leader do you think should
[44:27] succeed you?
[44:29] >> I I I would like to work as long as I
[44:31] can. You know,
[44:34] I hope to die on the job. That would
[44:37] that would be the that would be a dream
[44:40] come true.
[44:43] And so so uh um I can't imagine a a more
[44:48] meaningful life. I'm surrounded by my
[44:52] family, my kids. Uh both of them work in
[44:54] Nvidia and and I have the benefit of
[44:56] seeing them all the time and I'm proud
[44:57] of them and the company's proud of them
[44:59] and they love the company and so I get
[45:01] to see them all the time. Um, you know,
[45:04] Lori Lori's been with me for for a long
[45:06] time, our whole life. And and um I and
[45:10] she, you know, she's been part of Nvidia
[45:12] every step of the way. And aside from
[45:15] aside from Lori, I don't think anyone
[45:17] has been to every conference. And she's
[45:20] she's been to every conference, every
[45:21] speech, you know, and and um every
[45:24] moment of NVIDIA, she was there. And and
[45:27] so I I have the benefit
[45:30] of of uh me really meaningful work um
[45:34] and a company with incredible people and
[45:37] and employees that that can achieve
[45:40] almost anything and I'm surrounded by
[45:42] the love of my parents and my family
[45:43] that that you know are part of this
[45:45] journey with me and so so I can't
[45:47] imagine doing anything else frankly I
[45:50] can't imagine doing anything else more
[45:51] meaningful um with respect to the next
[45:53] generation uh leadership
[45:56] is about creating the conditions
[45:59] um for other people to be empowered. You
[46:02] know, NVIA is giant
[46:05] and yet we're small company. We are the
[46:07] world's smallest large company and and
[46:11] that's only possible because so many
[46:13] leaders at NVIDIA, so many people and
[46:15] empowered to do their to do the work.
[46:19] And so I constantly um uh explain our
[46:22] strategy transparently. I constantly
[46:25] reason about complicated situations in
[46:27] front of people so that they could help
[46:30] me doublech checkck my reasoning
[46:32] patterns and my reasoning logic. And um
[46:36] uh on the other hand, you're also
[46:37] exposing them through how you think
[46:40] through complicated and ambiguous
[46:43] uncertain circumstances. And so the
[46:45] combination of empowering people,
[46:47] letting them run, um, uh, aligning early
[46:51] on what our strategies are, our guard
[46:53] rails are, and then reasoning in front
[46:55] of people, uh, really helps everybody
[46:58] become more successful, become more
[47:00] empowered. Well, the next the next
[47:02] generation, the next leader of Nvidia is
[47:04] already working there and
[47:07] uh, it's my job to cultivate hundreds of
[47:11] amazing choices. And you just never know
[47:14] who the right next person is. And and um
[47:19] I and the and the reason for that is
[47:20] because we don't know what Nvidia is
[47:23] going to be like in 30 years or 10 or
[47:25] 20. And we don't know what the
[47:27] circumstances are in this future that
[47:30] artificial intelligence and that we're
[47:31] help creating. And so it would be it
[47:34] would be presumptuous and and arguably
[47:38] even arrogant to think that I would know
[47:40] what the perfect leader is going to be
[47:42] in 10 20 years. They're just we're just
[47:44] going to have to evolve until we we uh
[47:47] we know for certain. But the one thing
[47:49] that I will tell you is that the leader
[47:52] um for Nvidia would have to care about
[47:55] uh uh the employees, the ecosystem, the
[47:59] partners more than they care about
[48:01] themselves.
[48:03] And a great a great leader is selfless
[48:06] and uh always in service of of um uh of
[48:10] of the culture of the company, the
[48:11] mission of the company, the people of
[48:13] the company, always in service of other
[48:15] people. Uh it is very likely that that
[48:18] um uh that this this leader will will uh
[48:26] be in a in a in an era a time where
[48:30] intelligence is a commodity that the
[48:33] ability to write code, solve problems,
[48:36] um even scientific discovery is arguably
[48:39] completely automated. the one thing that
[48:42] we value so much in my generation which
[48:45] is knowledge and and technical skills
[48:47] and problem solving. Um the sciences,
[48:50] technologies, the maths um all of that
[48:53] is like likely going to be a commodity.
[48:56] And so therefore what remains what
[48:59] remains is ambition and character,
[49:02] imagination and um the empathy and
[49:06] generosity and kindness and you know the
[49:09] skills the soft skills that that defines
[49:13] a person
[49:15] beyond their intelligence and and so I I
[49:17] think those things will will likely
[49:19] become uh quite important. And then and
[49:22] then and I would say um may very well be
[49:27] uh the greatest asset of any leader
[49:30] which is the the desire of everyone
[49:32] around them to see them succeed. There
[49:35] are there are leaders that you just
[49:37] there are people that you just wish them
[49:39] to be more successful because they're
[49:41] kind to other people and they're
[49:42] generous to other people and you just
[49:44] want to see them succeed and there are
[49:45] people who are successful and you would
[49:47] hope to see them fail and and so so I I
[49:51] think that the future leaders are going
[49:52] to be the ones that somehow embody the
[49:55] the characters um the intangibles
[49:59] that that leads other people to want
[50:01] them to succeed and and and be led and
[50:04] to be part
[50:05] I see. I hope you don't mind me going
[50:07] back to the question about job cuts. How
[50:10] how would you say that job cuts are
[50:12] inevitable
[50:15] because of AI?
[50:17] >> It is very likely there will be more
[50:20] jobs in 5 years than there are today.
[50:23] Many more jobs.
[50:25] Some jobs will be different. Some jobs
[50:27] will be gone and many new jobs will be
[50:29] emerged. And I can say that with almost
[50:33] certainty and the reason for that is
[50:36] this. The world has been growing the GDP
[50:39] of the world has been growing at about
[50:41] 2% per year. 2% per year for 150 years.
[50:47] for 150 years where there was the
[50:49] industrial revolution with electricity,
[50:51] information technology, transportation,
[50:54] steam, you know, manufacturing equipment
[50:58] all the way to personal computers and
[51:00] internet and cell phones and so on so
[51:04] forth and artificial intelligence. It's
[51:06] been on a solid 2% per year and it's
[51:10] it's incredible. And um my sense is that
[51:13] well my belief is that that um all of
[51:16] those technologies at the time were
[51:19] transformative. Of course they were. How
[51:21] you and I live our lives today and how
[51:25] 150 years ago people live their lives,
[51:27] the industries, the companies,
[51:30] my goodness, uh completely different.
[51:33] And yet 2% per year. The number of jobs
[51:36] that have been created in the last 150
[51:38] years, incredible. The number of jobs
[51:41] that will be created in the next 150
[51:43] years is going to be utterly incredible.
[51:45] Of course, some jobs will be very
[51:48] different. Let's let's imagine that um
[51:52] prosperity
[51:53] uh AI has the opportunity to close the
[51:56] technology divide like no technology
[51:58] ever has. For example, you are a better
[52:01] user of computers today as a news
[52:04] reporter than at any time in history
[52:07] because you can program the computer to
[52:09] do whatever. If you want your own
[52:11] website, if you want your own broadcast,
[52:13] you can just ask the AI to help you
[52:15] create it.
[52:17] You're now a programmer just like I am a
[52:19] programmer. And so for the first time,
[52:22] AI has closed the technology divide. we
[52:25] have the opportunity to bring everybody
[52:27] along in this new technology revolution.
[52:30] That's a very big deal. The second,
[52:33] of course, AI will likely change the
[52:37] shape of the services industry, the
[52:40] manufacturing industry, and very also
[52:43] very importantly, the consumption
[52:44] industry, the entertainment industry. It
[52:47] is more likely that um people are going
[52:51] to consume more because we're more
[52:53] prosperous. And because we're going to
[52:55] consume more, it is very likely that the
[52:57] leisure industry and um you know the
[53:00] creation of content will enjoy more
[53:02] because we'll have more time to enjoy
[53:04] the content that you create. And uh
[53:07] hopefully we'll have the opportunity to
[53:08] travel more so that people are traveling
[53:12] around the world learning about
[53:13] different cultures and we can close the
[53:16] close the culture divides and you know
[53:19] and so there's a there's an optimistic
[53:21] future that uh that uh I imagine and
[53:26] facts would support my imagination of
[53:29] that future and um and and I think the
[53:33] the narrative that connects AI to job
[53:37] loss for many of the CEOs that are doing
[53:40] it. Um, it is just too lazy. It's just
[53:43] too lazy. AI has just arrived. How is it
[53:46] possible they're already losing jobs?
[53:48] You know, how is it possible that AI
[53:50] became productive and useful only six
[53:53] months ago and they were they were
[53:56] cancelling they were somehow laying
[53:58] people off two years ago because of AI.
[54:00] It doesn't make any sense. It was just
[54:02] it was just a way for them to sound
[54:04] smart. And I really hate that. Um I
[54:06] would I think we're scaring people and
[54:08] that's irresponsible. I think we should
[54:11] tell a balanced story, a balanced
[54:13] narrative about the potential of this
[54:16] cap of this technology, the importance
[54:19] of advancing it safely security
[54:22] guardrailed with necessary social,
[54:25] political, government, government,
[54:27] industrial policies to ensure that it
[54:30] advances safely. On the other hand, tell
[54:32] a story that's optimistic so that people
[54:34] want to be part of it. We want the young
[54:37] people of this generation to engage it.
[54:39] And so here's my test.
[54:42] Here's my s simple test for all the
[54:44] audience.
[54:46] What are you advising your children to
[54:48] do?
[54:50] Are you advising them
[54:53] to engage AI or to reject AI and be left
[54:58] behind?
[54:59] Are you advising them to use AI to
[55:03] elevate their learning, to elevate their
[55:06] profession when they can or are you
[55:10] telling them don't use this technology
[55:13] and let other people use it? And so all
[55:16] I have no question in my mind that every
[55:18] single parent is saying you have to
[55:20] learn about this technology, use it
[55:22] wisely, use it wisely, but use it to
[55:25] elevate yourself.
[55:27] if that is what they're advising their
[55:30] children for what reason are they not
[55:32] advising it for other people and so I
[55:35] would recommend that um uh I see a
[55:38] future that's op optimistic I see a
[55:40] future that is has more abundance
[55:43] abundance of intelligence abundance of
[55:46] labor abundance of goods um is going to
[55:49] therefore create opportunities for us to
[55:51] consume more
[55:53] >> you know so if you if you were a a
[55:55] connoisseur of fashion you're going to
[55:57] have a lot more a lot more opportunity
[56:00] to consume that.
[56:01] >> Thank you so much, Jensen. I really
[56:04] enjoy your conversation.
[56:05] >> Thank you very much, Victoria.
[56:07] >> Thank you.