‘We’re Losing the AI Race to China’ — NVIDIA CEO Jensen Huang Issues Stark Warning | AI1G

collection of colleagues here in physical space and we're going to have an interesting conversation with Jensen Hong. Um

Hong. Um I would waste your time by introducing him. You know, everybody knows Jensen,

him. You know, everybody knows Jensen, but um what you may not know is that he he started from fairly humble roots.

Your mom was a school teacher. Your dad

was a petroleum engineer. You and I share one thing in common is that's we both started off our first job was running a dishwashing machine in a res in a restaurant.

>> Denny's you >> what was what was your restaurant?

>> It was at Mount Rushmore when all you but you did better than I did. He became

he became a uh bus boy and later a waiter and then I guess led him to Nvidia. Nidia, you know, it's a

Nvidia. Nidia, you know, it's a remarkable story. It's I think it's the

remarkable story. It's I think it's the quitessential American story >> that uh you know we welcome people who

come with just energy and imagination and creativity and they make an astounding success and >> congratulations and thank you thank you

for joining us. We're going to uh we're going to have a very interesting conversation today colleagues and u you

know it's u nvidi is not only a huge economic success but it's a national security platform and I think we want to

talk about that today. I've been looking at your um at your website and you do talk about uh Nvidia as being a

platform. What does that mean?

platform. What does that mean?

>> A platform. A platform is something that you build other things upon. Nvidia is

the largest pure play technology company the United States has ever seen. In

fact, we're the largest pure play technology company the world's ever known. We create technology out of

known. We create technology out of nothing. Our final product is pure

nothing. Our final product is pure technology.

And in order to use it, you have to create software and applications for various industries above it. You know,

if you look at most of the technology companies today, some of it could be in social media, some of it could be in e-commerce, some of it could be in information search and and these are all amazing technology companies whose

business models are something else. Our

business model is purely technology. Now

the way that that AI works and and uh our technology works is that in the final analysis the technology platform is built in layers and that's one of the reasons why we think of it as a

platform. You're standing on top of it.

platform. You're standing on top of it.

An application or an industry stands on top of that platform. That platform

starts with energy on the bottom. One of

the reasons why why uh this administration uh has made such a huge difference right away if it's is this pro- energy growth initiative its attitude about energy is that if we

don't have energy we can't enable this new industry to thrive it is absolutely true so layer one is energy layer two are essentially the chips and systems

but the chips that's where Nvidia comes in layer three is a whole bunch of software and we build a whole bunch of software on top of our chips. And we're

well known for this piece of software called CUDA, but there's hundreds of different pieces of software that we create that enables people to do AI for different fields of science or language or images or whatever it happens to be,

robotics or manufacturing and such.

>> But that third layer is called infrastructure, basically software. Now

people historically have thought of infrastructure really as cloud but increasingly it's really important to realize that infrastructure includes

land power shell because these are and I'll speak about this in a second that this industry spawned another industry altogether and I'll come back to that but the third

layer is basically infrastructure and that infrastructure includes financial services because it takes an enormous amount of capital to do what we do And historically all of that software the

layer above that and this is where people largely focus on when they talk about AI which is the AI models. This is

the revolutionary of course chat GPT uh incredible work that anthropic does with claude and uh Google does with Gemini and uh what XAI does with Grock. But the

important thing to realize those are four of the 1 and a half million AI models in the world.

>> AI is not just intelligence that understands English or language, but it's AI that understands

genes, proteins, chemicals, the laws of physics. AI that understands quantum. AI

physics. AI that understands quantum. AI

that understands physical articulation, otherwise known as robotics. AI that understands patterns

robotics. AI that understands patterns across long sequence of time, financial services.

>> AI that understand longitudinally across multiple modalities, healthcare and so AI has all of these different reaches and domains. We talk about this one

and domains. We talk about this one area. We just have to be very careful to

area. We just have to be very careful to understand that AI ac spans basically every form of information across every field of science across every single

industry.

One and a half million AIs around the world. On top of that are all the

world. On top of that are all the applications and we never should forget that in the final analysis these AI models are technologies

but technologies are about enabling application and use whether you're in healthcare you know you could be in entertainment manufacturing self-driving cars

transportation each one of these industries have AIs that deeply affect them and these are the five layer stack

back. Nvidia is at the lower level, the

back. Nvidia is at the lower level, the platform level. The reason why we say

platform level. The reason why we say that, you know, we're AI company that works with every single AI company in the world is because we're the platform by which we are able to work with all of

these technology companies and all these application companies across all these industries. And so that is a platform

industries. And so that is a platform that we created. the mode that people describe, not so much a mode, but basically the the language by which all

of these different applications and these different technologies speak to us is an architecture we invented 25 years ago called CUDA. And on top of that, CUDA library is a whole bunch of

algorithms that we invented over the years. And that is basically Nvidia's

years. And that is basically Nvidia's platform. In the end, we don't build

platform. In the end, we don't build self-driving cars, but we work with every single self-driving car company in the world. In the end, we don't discover

the world. In the end, we don't discover drugs, but we just have, you know, we work with every single drug discovery company in the world. We're the platform by which they build their things. We're

platform company.

>> I I think half of I had a half a dozen young kids come up to me today say Nvidia gave them a better gaming experience. I mean you're all here.

experience. I mean you're all here.

>> Before I before we invented the AI industry, >> the first industry we created is the modern gaming industry. Yeah, you you don't know this. I'm very proud of this.

Nvidia is the world's largest gaming platform.

>> Yeah. And probably didn't know that there's most of the kids were talking to me about that today. I want to see them.

>> 300 million active users. Yeah. a 100

million of them Nintendo Switch. Yeah.

Nvidia's in that.

>> Okay. So, let me ask you. You said

something um recently that was quite provocative. You you said that China was

provocative. You you said that China was winning the AI race, the AI competition. Um

um I know that you've got a powerful, you know, competitor in Huawei and Huawei has a lot of um advantages you

don't have. Why don't you describe this

don't have. Why don't you describe this competition? Are we really losing?

competition? Are we really losing?

>> It was a very good headline.

>> It was a great headline. Yeah.

>> And and um apparently caught up a lot of attention.

uh uh the the as you know with headlines the disclaimer part uh the foundation part was left out of the headline but but the the way to think about that is that let me just

handicap it right now if you look at AI and go back to the first thing that we said AI is a five layer cake let's just simplify it's not it's not quite this simplistic but let's

simplify AI into a five layer cake energy chips infrastructure models and applications. Okay, I just

and let's handicap it across the from top from bottom to top at the lowest level energy. China has twice the amount

level energy. China has twice the amount of energy we have as a nation.

>> I want to ask about >> twice as much energy as we have as a nation and there our economy is larger than theirs. Makes no sense to me. We

than theirs. Makes no sense to me. We

also know that one of the most one of the most important initiatives, one of the most important policies of this administration and there was the first thing that President Trump said to me

when we met is listen, we need to reindustrialize America. We need to

reindustrialize America. We need to unshore manufacturing again. We need to make we need to help America make things again. It's going to create jobs. that

again. It's going to create jobs. that

part of the economy has been outshored on you and offshored uh and completely gutted the United States. We need to bring that back and he needs my help to

do so. And so so that entire sector of

do so. And so so that entire sector of the economy is missing and however without energy how do we build chip

plants, computer system plants and these AI data centers we call them AI factories. We're

building simultaneously three different types of factories in the United States.

Chip factories, supercomputer factories, and AI factories. They all require energy. Every single one of them. And so

energy. Every single one of them. And so

on the one hand, we want to re-industrialize the United States. How

do you do that without energy? And so

the fact that we vilified energy for so long, President Trump sticking his neck out and making taking it on the chin and helping this helping the country realize

that energy is necessary for our growth is one of the the really one of the greatest things he's done right off the bat. And so now at the energy level,

bat. And so now at the energy level, back to that stack, we're, you know, 50%.

And they're growing straight up. We're

kind of flat right now.

And so, number one, uh, energy. Number

two, chips. We're generations ahead.

We are generations ahead on chips. And I

think everybody recognizes that. Number

three, infrastructure. If you want to build a data center here in United States, from breaking ground to standing up a AI supercomputer is probably about three

years.

They can build a hospital in a weekend.

That's a real challenge. And so at the infrastructure layer, their velocity of building things because there are builders, their velocity of building things is extraordinarily high. Now,

really quickly on on ships, we're several generations ahead. But don't be complacent. Remember, semiconductors is

complacent. Remember, semiconductors is a manufacturing process. Anybody who

thinks China can't manufacture is missing a big idea.

But China discounts energy costs for a chip company by 50%.

>> That's right.

>> They they provide free transportation for employees to come out to the factory. That's right.

factory. That's right.

>> I mean, you don't you can't do that. I

mean, >> our energy cost is more expensive than theirs in the first place. And then they discounted 50%. And so it's probably

discounted 50%. And so it's probably we're probably call it four to eight times the cost. So tell me how do you feel about this this J this great

competition with China? I mean the the the government is putting enormous resources underneath their champion. We

don't do that in this country you know uh how do you feel about that?

>> Well before I get there don't don't let me not answer that question. I'm dying

to answer it but let me handicap the next two layers. the large the language the model layer the model layer United

States frontier models United are our frontier models are unquestionably world class we are probably call it six months

ahead however out of the 1.4 4 million models, most of them are open source. China is

well ahead, way ahead on open source.

Now, the reason why open source is so important is because without open source, startups can't thrive.

University researchers can't do research. You can't teach AI. Scientists

research. You can't teach AI. Scientists

can't use AI. Basically all of the industry around the your economy have no ability to fundamentally advance themselves unless you have open source.

Without Linux, where would we be?

Without Kubernetes, you know, without PyTorch, all of these different types of technologies that made AI thrive are all open source.

>> They are well ahead of us on open source.

>> And then the layer above that applications. If you were to do a poll

applications. If you were to do a poll of of um uh their society and ours and you ask them,

is AI likely to do more good than harm?

They're going to say in their case, 80% would say AI will do more good than harm. In our case, it'd be the other way

harm. In our case, it'd be the other way around. And so that tells you something

around. And so that tells you something that's very, very important. socially.

Socially, we need to be careful not to describe AI in these science fiction movie ways of describing AI and and causing people so much concern. Um, we

want to be concerned, but we also want to be practical. AI is about automation and that area. I think that we need to be careful not to fall behind in the

application and the diffusion of AI because in the end whoever applies the technology first and most wins that industrial revolution.

As you know, electricity was invented disco invented in the UK, but United States applied it faster more broadly and as a result, look where we are. And

so, we have to be a little mindful. So,

anyways, I just handicapped that stack.

Okay? And I don't think it's it's important when you're looking at AI not to see it as a holistic thing. It's

really not about chat GPT versus Deepseek. You have to look at it across

Deepseek. You have to look at it across all of the stacks and across all of the industries. Does that make sense? It's a

industries. Does that make sense? It's a

little bit more complicated than one simple answer, >> but do you feel you have a level playing field up against China putting their resources under Huawei?

Uh I f first of all America's technology industry just as

our financial financial services ind industry our military our technology industry we can all agree

are the mightiest in the world.

I am part of one of the mightiest technology, mightiest industries anyone in history has ever seen.

>> We have going toe-to-toe against anyone.

The American technology industry has nothing to fear. We are mighty. We're

fast. We're inventive. We'll take

anybody on.

However, we can't concede the market to them. As

you know, at the moment, Nvidia has been banned from going to China. Not to

mention, China has banned Nvidia going to China. So, so we're we're this I

to China. So, so we're we're this I think we're the first company in history that has been banned on both sides.

And so so I whoever whoever banned us uh going to China um them and China uh agree that Nvidia should not go to Now of

course I'm being a little I'm being a little cute here and I'll I'll be be a little bit more nuanced here in a second but at the moment we're simply not competing in China. Now what's going on?

We have conceded essentially the second largest AI market, the second largest technology market in the world. I don't

know >> China will it's not somebody has said to me well yeah okay well we're not in China but we're grow somewhere else

you're not going to replace China it's just as the world wanting to sell to America and they want to export to America if they don't export to America

you're not going to replace United States we are singular in the world we are absolutely singular and so in the case of China um we shouldn't concede the entire

entire market to them. They're

formidable, but conceding that entire market, uh, we ought to go compete for it. Having said that, we should also

it. Having said that, we should also acknowledge that Huawei is one of the most formidable technology companies the world has ever seen.

They deserve, although they have a lot of support, um, whatever support they have, they deserve all of the respect that everybody ought to give them. We

compete with this company. They're

formidable. They're agile. They move

incredibly fast. We said if United States was not in China, China's AI industry would be set back.

>> Yeah.

>> Absolutely has not happened. As a

result, their semiconductor industry has double double double. You know the semiconductor industry in the west around the world is growing at 20 30%

per year. growing 20 30% per year

per year. growing 20 30% per year compounded versus doubling every year compounded doesn't take long to catch up >> but you know they're starting on second

base and we're just going up to the batters box you know they've got a real advantage and that means we need to think about this can I ask ask you we um

at the G20 summit uh Lee Kashang you know the premier was there and he was offering

um opportunities for countries to be participants with China on AI. We didn't

even send a delegation. It doesn't feel like we're in the game.

They're smart about um technology proliferation.

>> Yeah. If we apply, if we use 5G as an example, they realize 5G is technology that's also a platform because on top of

5G, you build all kinds of services on top of it. Well, if you get there first, wherever you get first, if you get there first, just as Nvidia, I was there 25

years first. And so I had, you know, for

years first. And so I had, you know, for a long time, nobody paid me any, never mind. So I had lots and lots of time to

mind. So I had lots and lots of time to build up all these ecosystems and applications and relationships and ecosystems and I connected all this stuff together in all these different

fields of industry. I had 25 years to do it. In the case of Huawei with 5G they

it. In the case of Huawei with 5G they were >> we were they were completely through policy completely isolated people thought in China. So they had a billion

phone users all but to themselves. It

gave them the opportunity to grow scale.

They exported the technology to all of the countries that >> belt and road and now there's AI belt and road and so they'll definitely per diffuse the Chinese technology as

quickly as possible because they understand that the sooner you get there the sooner you build the ecosystem on top the sooner you become a sticky you become sticky you become essential part

a dependent part of that ecosystem >> tell me about the Chinese ecosystem they're trying to create obviously it is it's deep and it's robust and that it

has a physical as well as a technological and economic dimension.

How do you look at that? Take a step back again. Remember I think it's like

back again. Remember I think it's like nine out of the 10 top science and technology schools in the world are now in China.

They lead in science and technology in many different fields. This has

completely flipped in the last half to a decade.

We used to lead most of them. Now they

lead most of them. They have a large population of highly qualified students.

>> Number one. Number two, 50% of the world's AI researchers are Chinese.

>> Third, 70% of last year's AI patents are published by China.

The ecosystem of AI in China is vibrant, rich, incredibly innovative.

>> Yeah. Yeah.

>> They work incredibly hard. This is a country with an enormous might.

>> So that is the ecosystem of software developers.

>> Yeah.

>> Now that layer as I just mentioned, the model and the application layer. All of

these scientists, they're sitting at the model and the application layer. And now

they're going to take that capability because United States is no longer participating in China. We've left

China. We're evacuated that market.

We've conceded that market. And so now they they've got to go build their own.

So using these AI researchers, all of this incredible computer scientists that they have, their richness of software capability, and they're going to go build their own complete stack.

>> Once they build that entire complete stack, they'll export it.

>> Yeah.

>> As quickly as you could imagine. And

this is the the world. What we will find someday if we don't activate >> will be buyers, not sellers.

>> That's right.

>> Let me ask you ask you now. I you're in Washington DC. I know you don't look

Washington DC. I know you don't look forward to those opportunities, but um we're um >> it's my only opportunity to wear a suit

>> and a tie. Um but but let me ask because um you know, we're um we're in we're involved in something I've not seen

before in in my 45 years here. We we've

delved into industrial policy. I always

thought industrial policy was something that we shouldn't be doing in this country. Now, the Biden administration decided that they would

define what they would allow you to sell and they have this thing that they called diffusion that they were trying to manage. Now you get the Trump

to manage. Now you get the Trump administration. They don't have that.

administration. They don't have that.

but they want a golden chair and they want a percent of the cut, you know, on how you're doing business. Tell me about how you look at this this industrial

policy that we have in Washington.

>> I do agree that that um industrial policy uh should should intervene

when a dramatic action needs to be taken.

Um, I also would say that President Trump walked into a circum into a situation where dramatic actions needed

to be taken. The first dramatic action that needed to be taken is to reverse the mistakes that have been made in energy

growth over the course of the last decade.

We are we have we have done our country a great disservice.

There there are no new industries you can grow without energy.

>> Yeah.

>> Electricity.

>> That's right. We need electricity because otherwise sure we could all be in the services industry and as you know the service industry only needs calories

but manufacturing industry needs electricities and so uh we need energy number one. Number two we do need to if

number one. Number two we do need to if we want to if we want to fix our social issues domestic social issues we have to create prosperity not just for people

with PhDs and college degrees. We have

to create prosperity for every segment of the economy.

>> And so the largest segment of the economy is manufacturing. And we've

offshored that too for too long for 20 years. We got to bring that back and we

years. We got to bring that back and we have the ability to do so. And this AI industrial revolution, this flash point is precisely when we should do it

because it allows us, it it created a company called Nvidia, made it possible for us to have such a large ecosystem of suppliers. We can encourage them to

suppliers. We can encourage them to partner with us. We can encourage Taiwan to partner with us to help us reindustrialize the United States. And

they've done so with great support.

Taiwan really needs to have some acknowledgement for the incredible effort that they're putting in place to help us re-industrialize the United States. If not for the work that they're

States. If not for the work that they're doing, the work that the work that Nvidia has done in Arizona wouldn't have made the progress it has.

>> I recently gave a congratulation speech at TSMC in Arizona. And when I looked out into the audience, it was twothirds Taiwanese and one-third American.

Arizona is practically well the quality of Taiwanese food in Arizona, let me just put it that way.

The quality of Taiwanese food in Arizona has increased tremendously. Okay, you

want to get a bowl of get a bowl of beef noodle soup, you're going to do just fine. But but but all these young all

fine. But but but all these young all these young uh families from Taiwan came to help us stand up our our factories.

>> And so we should acknowledge that. Um

and South Korea helping us stand up our memory manufacturing. We should

memory manufacturing. We should acknowledge that. Uh the companies uh

acknowledge that. Uh the companies uh Foxcon Wis Wistron Amcor Spill helping us set up systems manufacturing.

They came from Taiwan. Really important.

And so so one if not for the fact the second industrial policy is to reindustrialize the United States. That I think is a

fantastic fantastic initiative. And I'm

all behind that. I was probably the first CEO to jump behind that and take advantage of Nvidia's capabilities and this flash point of AI industrial revolution to help bring all of that

supply chain. I committed to my

supply chain. I committed to my customers, my partners that we're going to build in this administration within within President Trump's term half a trillion dollars of AI supercomputers.

And so that's the second part, energy growth, re-industrializing United States. The third part that I I think I

States. The third part that I I think I think um uh required a fair amount of discussion uh to help

policymakers understand that technology leadership, American technology leadership and American national security goes hand in hand.

Our nation's extraordinary technology industry is part of our national security. The fact that we have our

security. The fact that we have our technology all over the world that the world relies on to build their industries, their ecosystem, their

economies is an advantage for the United States. It's a strength of the United

States. It's a strength of the United States. It helps keep United States safe

States. It helps keep United States safe when everybody works with us.

>> Let me let me build on that. Um you know I think I think national security there are two two dimensions of national security >> and I differentiate small case and large

case small case national security small N small s u I think that's you know aircraft carriers and bombers and

divisions and training programs capital national security NS is the uh dynamism

of your economy Okay. The the

productivity of your industry, the creativity of your ideas industry, u the sense of fairness in your judicial

system. Uh you are here, you you benefit

system. Uh you are here, you you benefit from that larger case, but you're building that larger national security industry. tell us how you think about

industry. tell us how you think about your role uh on national security.

>> Uh number one, Nvidia was birthed in the United States.

We are a proud American company.

We're inventive. We're vibrant. We're at

the center of the single most important industrial revolution in human history.

This is an industrial revolution in every single way as important as electricity. We are going to impact

electricity. We are going to impact every single industry. Every single

company, every country will build it.

Every company will use it.

We export American technology wherever the United States would like us to export the American technology.

This is an extraordinary opportunity for us.

to make a substantial contribution to our national security. We also know that national security and economic security and economic prosperity go hand in hand,

the wealthier our nation, the more we can fund the mightiest military on the planet.

And I do believe that it is the case we are because of this new industrial revolution that we've started, we are creating new factories in

America. We're creating new jobs in

America. We're creating new jobs in America. And somebody recently told me

America. And somebody recently told me that we contributed more to economic growth singularly than just about any company in the world today to the American economy. And I believe that

American economy. And I believe that that's probably true. And the reason for that is Nvidia is a multiundred billion dollar company supporting multiundred

billion dollar companies going after trillion trillion dollars of of industry.

>> And so the economic prosperity the technology leadership unquestionable the technology the economic prosperity that

we can contribute to unquestionable.

Now this the question then becomes how do we think through the diffusion of the export of the proliferation of American technologies

and standards.

We should of course number one safeguard our national security the little little N and little S to ensure that adversaries don't have access to

sensitive technology or advanced technology that we don't need them to have access to >> right >> we should number two ensure that American companies American technology

companies through partnership with us have the benefit of the best and first but then after that after number one and number two, we

should also proliferate American technology standards, compete around the world, fuel this flywheel

of funding >> our R&D so that we can continue to be to be the mightiest technology industry in the world so that we can fund the tech

the mightiest military in the world and all of that I think goes hand in several times. Uh, you know, Chairman

several times. Uh, you know, Chairman Dang, you've talked about energy as being a pacing problem here. We, uh, you

know, when we invented LED lighting, we just, uh, lost the demand signal and half of our uh, of our electricity uh,

grid is merchant supplier and so they don't buy ahead of need. And so we're now really way behind. And you pointed out that China

>> has built out twice the capacity of electricity than has the United States.

How big a constraint do you see that as being for our buildout for this revolution that you're trying to create?

Deeply serious.

I think at this point we have to use every form of energy we can. I believe

we can't rely on the power grid. We got

to build behind the meter. We obviously

need power generation systems. There's no question we should try to encourage and try to accelerate nuclear.

We need to have energy growth very, very shortly.

In the meantime, we're advancing our technology so quickly. No company our scale has ever

quickly. No company our scale has ever introduced new generations every year.

And when I say we just ship a new chip every year, people, you know, when people because there's so many gamers in the world and they've known me for so long and when they think about what

Nvidia builds, they think it's a a a module that looks like a gaming graphics card, our GeForce graphics card, and

they plug it into their PC. Well, a GPU for AI centers, AI AI data centers. That

GPU weighs two tons.

It has one and a half million parts.

It consumes 200,000 watts.

>> It costs $3 million.

>> Every so often, somebody says, you know, these GPUs are being smuggled. I really

would love to see it. Yeah.

>> Not to mention, you have to smuggle enough of them to fill a football field >> full of these things so that you could

run it as an AI data center. And so

anyhow, the technology that we make each year allows us to increase the performance at about the same power by

many times. And let me just pick a

many times. And let me just pick a number. Say five times or 10 times each

number. Say five times or 10 times each year. As a result, our energy efficiency

year. As a result, our energy efficiency improves by five times or 10 times each year.

>> But the problem is this. We're at the beginning of this technology buildout.

I'm improving the performance by a factor of 10 times each year, but demand is going up by a factor of 10,000 a million times each year.

>> No.

>> AI is getting more computensive. The

adoption is going way up. I've got all these exponentials and so we're going to keep chasing this. Uh we're going to be completely dedicated to advancing the technology as fast as we can. But the

bottom line is we need energy.

>> Yeah. And I I you know, forgive me for interjecting myself. I do think we have

interjecting myself. I do think we have to overcome the Nimi constraints. You

know, we're going to have to find some structure of federal preeemption so we can overcome the the barriers. That's my

comment. That's not your comment. I

don't want you to get in trouble for for my saying that. Let me ask you, I mean, last year, >> thank you for that.

>> Last year, um, the world installed two million robots.

Half of them were in China, which is really astounding when you think about it. Tell me how robots fit in with AI.

it. Tell me how robots fit in with AI.

Um, you know, let me just give you one example of why it's around the corner.

You know, these days you could describe, you could describe in text and you give it to um a video AI

and it generates a video. You guys know this, right? It actually from words you

this, right? It actually from words you can generate a video. Okay? And let's

say the video is uh Jensen reaches over, picks up a cup.

So I take a picture of this screenshot, give it to the AI. That's the starting starting condition. And I say, "Now

starting condition. And I say, "Now cause Jensen to reach over and pick up the cup."

the cup." The AI creates pixel by pixel, token by token, my arm picking up the cup. And

that everybody knows is possible today.

You guys have seen it. Well, the AI can't tell the difference between it man manipulating pixels versus it's manipulating a bunch of motors.

So, the idea that I can tell the robot pick up the cup is clearly just around the corner. We just have to take that AI

the corner. We just have to take that AI which currently sits in the cloud and we have to put it into otherwise called embody it into a physical

>> mechanical system which is called robotics. So the AI is around the

robotics. So the AI is around the corner. We can see early evidence that

corner. We can see early evidence that the technology must be possible. Now

China is going to be very very good at this for several reasons. They have

great demand. They have a natural indigenous demand for more workers.

Manufacturing is core part of what they do. We, by the way, because we're now

do. We, by the way, because we're now re-industrializing reshoring manufacturing, we now again also have significant demand

for factory automation. And there's no question we have a shortage of labor. We

have right we all know that our industries would be would be larger more profitable more vibrant if we just had more workers and so they have the same challenge they have worker shortage

coming up very severe worker shortage coming up so they have a a a national strategic imperative to make sure that robotics happens number one number two they have the AI technology and number

three this is where they have a big advantage they're really very good at electronics and mechanical intersections

otherwise known as megatronics. This

entire area is they have the harmony of demand and supply side capability.

>> Now many other countries Japan has surely demand side. They have

the megatronics but Japan needs to have much better AI technology. Germany great

demand extraordinary mechatronics they need to have great AI technology United States we have if we reshort industrial indust re-industrialize our

nation we will have great demand we have great sa software technology but we really at the moment need to improve our mechanical electronics

>> yeah I mean you know using AI to find a better you know vegan recipe for foy gr. You know, maybe something my wife will look up, but we need to make this.

>> That would be a miracle indeed.

>> It would be good. But we we need to turn this into productive machinery and the way in which it's going to change the the landscape. Let me ask you, we're

the landscape. Let me ask you, we're because we're running out of time. Um,

you know, I was talking to a friend of mine who's a dean of a of a major research institute, and I asked him, I said, "How is your faculty dealing with

uh with AI?" And he said, "Well, you know, the engineering faculty is excited. They really think this is

excited. They really think this is fabulous." You said the science faculty

fabulous." You said the science faculty is really curious and they think it potentially opens up real opportunity and the humanities faculty thinks it's

the end of the world.

>> Um so it is a shorthand for the anxiety that people feel about the dark side

>> of AI. How do you how do you talk to us about that?

Um let me start from the from the end.

There's no question that everyone's jobs profession will be affected by AI

because the tasks within our jobs are going to be dramatically enhanced by AI.

>> Yeah.

>> Some jobs will become obsolete.

New jobs are going to be created >> and every job will be changed.

>> So that let me just I used two words just now and it's really important we think about these two words very differently. One is task the other one

differently. One is task the other one is job. Now it turns out

is job. Now it turns out I think it was something like seven, eight years ago a very important AI scientist maybe the

most important AI scientist declared the first application for AI will be radiology because computer vision was the first

breakthrough and that in fact entire radiology industry in within five years will be completely transformed by AI.

die and that in a in five years time radiologists will all lose their job and he advises that no one should be a radiologist.

That was his advice and it was taken very seriously.

Now some five, six, seven, eight years later every single radiology platform has been

completely transformed by AI 100%.

every single radiology platform the number of radiologists has increased.

The question is why?

And the reason for that is because as it turns out studying the scans, studying the images is the task of a radiologist.

The goal or the job of a radiologist is to diagnose disease.

This is true for many many people.

People say, "I don't need software engineers because apparently coding is going to be automated." I've given AIS to every one of my software engineers and hardware engineers and engineers

period.

>> 100% of Nvidia has AI assistants, AI coders, and they're busier than ever.

And so the question is, what is the task versus what is the job? no different

than a financial analyst. The task is mess around with spreadsheets, but the job is to make a financial advice. The

job is to help a customer. The job is to analyze a market, make a prediction about market. And so there's still the

about market. And so there's still the human factor is still quite significant.

>> And I would just tell everyone before you decide that the the the that AI uh is something that you're you're you're worried about or scared about, go engage

it. Go use it. And even in the

it. Go use it. And even in the humanities, the fact of the matter is without, you know, with AI today, my writing has improved.

I don't think the quality is it still writes in my my taste and my my ways but my speed of writing has dramatically improved

>> and so I'm more productive today I'm still writing the original pieces I still have to write the original voice I still have to we I still have to create the original thought still has but every

so often as you know when we derive uh other speeches out of other previous speeches the concepts are very similar But the content, the delivery, the

context is so different. We we now can use AI to help us regenerate the first draft, you know. So, so for me, u for the humanities, I would just say

original thought, original writing, your taste made with human hands are still always going to be valuable.

>> I went in for an MRI recently. My wife

said, "Make sure you take a picture. I

don't think there's a brain up there, but I'd like to see it prove there's something." Um,

something." Um, >> and what what did you find out?

>> There was there was nothing. I mean, she was right and I was wrong.

>> Uh, we're we're coming to the end and and um you're in Washington. you don't this isn't always a joyful experience to come

to Washington but um share with us what your you know you know your thoughts on how we should think about this remarkable uh revolution that's

appearing in your world. You're leading

it. We're going to experience it. We're

probably going to try to regulate it. We

don't know how to do that. But uh tell us just a little bit how you think we should be anticipating this and thinking about our future.

>> Um there are many of course that we we spoke about many different things that that uh Washington has been uh extraordinarily helpful in already shaping the outcome for our nation. Uh

we spoke about industrial policies and and how in fact a heavyhanded approach was necessary and it was just in time. Uh it is the case that

in time. Uh it is the case that Washington DC is foreign to me and and um I I've had the benefit of coming here

now since the first time I saw you uh our first our first night and um it's unnatural to me uh however however what

I I can tell you is uh we all want the same thing. We want America to win. We

same thing. We want America to win. We

want America to be the greatest nation in the world. We have extraordinary capabilities.