Jensen Huang's 10,000-word interview: The AI competition has no "finish line," technological iteration is key, and for 33 years, I have felt that the company could go bankrupt every day

NVIDIA founder and CEO Jensen Huang recently participated in a two-hour in-depth interview on a podcast, where he elaborated on his views regarding the AI race, company management, and personal growth.

As the head of one of the world's most valuable technology companies, he revealed a surprising fact with rare candor: Despite NVIDIA becoming a core enterprise in the AI era, he still wakes up every day feeling that the company is "30 days away from bankruptcy."

(Source: Screenshot of Jensen Huang participating in the Joe Rogan podcast)

When discussing the globally focused AI race, Huang presented a viewpoint that starkly contrasts with mainstream opinions. He believes that this race does not have a clear "finish line" as the outside world imagines, nor will one party suddenly gain overwhelming advantage. Instead, technological progress will be incremental, and all participants will evolve together by standing on the shoulders of AI.

He argues that true competitiveness lies in the ability to iterate continuously, rather than achieving a one-time breakthrough. Over the past decade, AI computing power has increased by 100,000 times, but this power has been used to make AI think more cautiously and verify answers, rather than engage in dangerous activities. When NVIDIA launched CUDA in 2005, its stock price plummeted by 80%, but persistent investment ultimately laid the foundation for today's AI revolution. Iteration is not repetition; it is continuous correction based on first principles.

Huang also recounted NVIDIA's near-bankruptcy experiences multiple times, including the critical moment in 1995 when a wrong technical route choice led to survival only through a $5 million investment from Sega and the trust of TSMC's Morris Chang. These experiences shaped his unique understanding of risk, strategy, and leadership, explaining why this trillion-dollar company maintains a startup-like sense of urgency.

In the interview, Huang offered a severely underestimated yet crucial insight: The key to determining whether AI will replace you is distinguishing between "tasks" and "purposes." The case of radiologists demonstrates that after AI swept through the field of radiology, the number of doctors actually increased, because reading images is merely a means, while diagnosing diseases is the purpose. If your job is the task itself (like chopping vegetables or data entry), you will be replaced; if the task is a means to achieve a higher purpose, the job will be upgraded. AI will eliminate jobs that treat means as ends, forcing everyone to consider: what is the true purpose of your work?

Key points summarized by Wall Street Insights are as follows:

On the assertion that AI will not develop consciousness:

"I believe it is entirely possible to create a machine that can mimic human intelligence, understand information, comprehend instructions, break down problems, solve problems, and execute tasks."

Cybersecurity analogy (immune system model):

"I think the idea that artificial intelligence will emerge out of nowhere, thinking in ways we cannot imagine and doing things we cannot even conceive, is far-fetched. The reason is that each of us possesses artificial intelligence." "

Radiologist Case:

"About five years ago, (AI godfather) Geoffrey Hinton predicted that in five years, the world would no longer need radiologists. Ironically, the number of radiologists has actually increased."

"The role of a radiologist is to diagnose diseases, not to study images. Studying images is merely a task that assists in diagnosing diseases."

"Therefore, now you can study images in ways that are difficult for radiologists, and you can study more images. This increases the number of examinations that can be conducted."

Views on Job Transformation:

"If your job is just to complete tasks, then those tasks may be replaced. But your job cannot be limited to just completing the tasks themselves."

Direct Production Gamble:

"We plan to send the chip wafers first. I like to go straight into production because I know it works. They say no one has ever done this before. No one has ever successfully completed chip wafers in one go."

Continuous Sense of Crisis:

"I've been saying '30 days until bankruptcy' for 33 years. It's like that every morning. My greater motivation comes from not wanting to fail, rather than wanting to succeed. The fear of failure drives me more than greed or anything else."

"The CEOs of the world's most valuable companies wake up every day feeling like their companies are about to go bankrupt. Anxiety is not exclusive to losers; it can be the fuel for sustained success."

"Success comes from truly hard work, long suffering, loneliness, uncertainty, fear, and humiliation. People often don't believe you, and you are frequently questioned. We forget to convey this part."

Emphasis on Energy Growth:

"To be honest, without his (Trump's) set of energy policies that promote economic growth, we wouldn't be able to build AI factories, chip factories, let alone supercomputer factories."

"Every iteration of Moore's Law means a reduction in the energy required to complete any computational task. That's why you can use a laptop today. Over the past decade, we've increased computing performance by 100,000 times. In ten years, the energy required for AI will be negligible for most people."

Below is the transcript of the podcast program (AI-assisted translation)

1. Jensen Huang's View on Trump

Joe Rogan 00:13

Alright, great to see you, kid. We were just talking, was that our first conversation? Or did we first talk at SpaceX, when you handed that crazy AI chip to Elon for the first time?

Jensen Huang 00:24

Right?

Joe Rogan 00:25

The DGX part. Oh, that was a significant moment. It was so shocking. The immersive feeling was crazy. I felt like I was watching these tech geniuses exchange information, watching you hand him that amazing device, you know? And then there was a time I was in the backyard shooting arrows when I suddenly got a call from Trump, saying he was playing with you

Jensen Huang 00:46

President Trump called, and I called you too.

Joe Rogan 00:48

That's right.

Jensen Huang 00:48

We were just talking about you. That's it, we were talking about you. He was saying he plans to have a UFC fight in his front yard. Then he pulled out something and said, "Jensen Huang, check out this design." He was really proud of it. I said, "You’re definitely going to have a fight in the White House front yard." He said, "Yeah, yeah, you’ll definitely come. It’s going to be awesome." Then you showed him his design, how beautiful it is. Then he said, "Somehow, your name came up because do you know Joe?" I said, "I do, I want to go on his podcast." Let's call him, he’s like a kid. I know. Let’s call him. He’s like a uniquely styled kid. He’s incredible.

Joe Rogan 01:30

Yeah, he’s really a character. He’s completely different from what people think of him, completely different from what people imagine, and as a president, he’s completely different; he’ll just call you out of the blue. Also, when he texts, if you’re using an Android phone, the text won’t go through. But with my iPhone, he’ll make the text bigger. Really? The word "USA" is emphasized in all caps by him. Then he’ll make the text bigger. It’s a bit ridiculous. Hmm.

Jensen Huang 02:02

When I’m alone with President Trump, he’s very different. He surprises me. First of all, he’s very good at listening. He remembers almost everything I’ve said to him.

Joe Rogan 02:14

People don’t think that way; they only want to see negative news or negative reports about him. You know, everyone can have a bad day. There are many things he does that I think he shouldn’t do. For example, I think he shouldn’t tell reporters to shut up and call them "quiet little pigs," that’s quite ridiculous. Objectively, it’s also quite funny. I mean, it’s unfortunate that she had to go through that. I don’t want her to go through that either. But for the president to do that is just hilarious; it’s ridiculous for the president to do that. I hope he didn’t do that. But aside from that, he’s actually quite an interesting person. He has many different qualities, you know?

Jensen Huang 02:49

Part of his charm, part of his talent, is that he dares to speak his mind. Yes. And that’s one point.

Joe Rogan 02:56

He’s also a typical politician.

Jensen Huang 02:57

Yeah, that’s right. So, you know, what he thinks is actually what he thinks; he tells you what you’re going through.

Joe Rogan 03:05

I like that, while some people would rather be deceived.

Jensen Huang 03:08

But I like that he speaks his mind. Almost every time he explains something or says something, he first expresses what he wants to do for America. Everything he thinks is very pragmatic, very reasonable. And you know, it’s very logical

Jensen Huang 03:30

I still remember the first time I met him. At that time, I had never met him before. Secretary Ross called me, and we met at the beginning of his term. He told me that one of President Trump's top priorities was that American manufacturing must stay in the country. This was crucial for him because it related to national security. He wanted to ensure that our country's key technologies were produced domestically and to revitalize industrialization and develop manufacturing again, as it relates to jobs.

Joe Rogan 04:11

That seems like common sense, right?

Jensen Huang 04:13

It's incredibly common sense. This was almost the content of my first conversation with Secretary Ross. He was talking about me, and his conversation with Jensen started from there. I am Secretary Ross. I just want to tell you, you are a national treasure, and NVIDIA is a national treasure. Whenever you need to contact the president or the government, you can reach out to us; we are always here for you. That was really the first thing he said.

Joe Rogan 04:50

That's really nice.

Jensen Huang 04:51

It really is. Every time I call, if I need something, want to vent, or express my concerns, they are always there for me.

Joe Rogan 05:02

That's incredible. It's a pity we live in a politically polarized society where you can't even accept common-sense advice from those you oppose. I think that's what's happening here. I believe that most people, as a country, as a large community (which we truly are), take it for granted that manufacturing should be produced domestically, especially critical technologies like the ones you mentioned. It's absurd that we buy so much technology from other countries.

Jensen Huang 05:33

If the U.S. doesn't develop, we cannot prosper. We cannot make any investments, whether domestically or abroad. Without energy growth, we cannot solve any problems. Without industrial growth, we cannot achieve job growth.

Jensen Huang 05:52

It's that simple, right? The first thing he said after taking office was, "Drill, baby, drill." What he meant was that we need energy growth. Without energy growth, there is no industrial growth. It was this that saved the AI industry.

Jensen Huang 06:09

To be honest, without his energy policies that promote economic growth, we wouldn't be able to build AI factories, chip factories, let alone supercomputer factories. Without all of this, none of these things would be possible. Jobs in construction would be challenged. Yes, jobs for electricians, all these currently thriving industries would be challenged. So I think his point is correct. We need energy growth; we want to revitalize American industry; we need to return to manufacturing. Not every successful person needs a Ph.D., and not every successful person needs to graduate from Stanford or MIT. I think that pragmatic attitude is absolutely right

Joe Rogan 06:56

Now, when we talk about technological development and energy growth, many people say, oh no, that's not what we need, we need to simplify life and return to the basics. But the real issue is that we are in a massive technological race. Whether people realize it or like it, this race is happening. And it's a crucial race because whoever reaches a certain critical point in artificial intelligence first will gain a huge advantage. Do you agree? Well.

Jensen Huang 07:29

First of all, I want to say that we have always been in a technological race. We have always been competing technologically with others, right? Since the Industrial Revolution, we have been in a technological race.

Joe Rogan 07:41

Since the technological developments of the Manhattan Project.

Jensen Huang 07:43

You know, we can even trace it back to the discovery of energy. That's right. Britain is the birthplace of the Industrial Revolution, and if you remember, they discovered how to convert things like steam into energy, into electricity. Most of these technologies were invented in Europe, and the United States took full advantage of them. We learned from them, industrialized them, and spread them faster than any other country in Europe. Meanwhile, they were still entangled in policies, employment, and various disruptive changes. In contrast, the United States was rising. We simply mastered the technology and grew rapidly. So I think we have always been in a technological race. World War II was a technological race, the Manhattan Project was a technological race. Since the Cold War, we have been in a technological race. I believe we are still in a technological race today. This may be the most important race. Technology gives you superpowers, whether it's information superpowers, energy superpowers, or military superpowers, all built on technology. Therefore, technological leadership is crucial.

II. The Safety of Artificial Intelligence

Joe Rogan 09:00

Well, the problem is if others have more advanced technology, right? That's right, that's the problem, right? The AI race seems to make people very anxious. You know, Elon Musk once said that there is an 80% chance that artificial intelligence will be great and a 20% chance that we will run into trouble. People are worried about that 20%, which is understandable. I mean, you know, if you have a revolver with 10 bullets, you take out 8, and there are still two left. When you spin the chamber and pull the trigger, you are definitely going to feel uneasy. It's scary, right? As we strive towards this ultimate goal of artificial intelligence, it's hard to imagine that achieving it won't be related to national security.

Jensen Huang 09:49

We should know. The question is, what is out there? That's the key. What is out there? Well, I'm not sure. And I feel like no one really knows.

Joe Rogan 09:57

This is just ridiculous, in my opinion. You're the president of NVIDIA, and you actually don't know what's going on? Who knows?

Jensen Huang 10:04

Yes, I think this process may be much more gradual than we imagine. It won't happen all at once, nor will it be like someone suddenly appearing while others are not. I don't think it will be like that. I think things will get better and better, just like that.

Joe Rogan 10:22

Technology. So you're optimistic about the future. Clearly, you have a very positive outlook on the development prospects of artificial intelligence. Will you create the best AI chips in the world? You better be able to do that.

Jensen Huang 10:34

If history is any guide, we have always focused on new technologies. Humanity has always focused on new technologies. There are always people thinking about it. There are always many people very concerned about it. We are also very concerned. Therefore, if history is any guide, all this attention will eventually translate into making technology safer.

Jensen Huang 11:02

For example, in the past few years, the speed of development of AI technology may have increased 100 times just in the past two years. Let's summarize it with a number: just like cars were 100 times slower two years ago, today's AI capabilities are also 100 times stronger than before.

Jensen Huang 11:25

So how do we guide this technology? How do we harness all this power? We use it to empower AI with the ability to think, which means it can process the questions we pose, break them down step by step, and research before giving an answer. This way, it can base its responses on truth. It will reflect on its answers and ask itself: Is this the best answer I can give? Am I confident in this answer? If it is uncertain or lacks confidence in the answer, it will go back and do more research. It may even use tools because tools can provide better solutions than it can come up with on its own. Therefore, we leverage all this computational power to produce safer, more reliable answers, more truthful answers. Because, as you know, one of the biggest criticisms of AI initially was that it would hallucinate, right? So if you look at why people are using AI so widely today, it's because the element of hallucination has been reduced. You know, I use it almost all the time. I've been using it all along. So I think when most people think of power, they might think of explosiveness, but technological power is mostly used to enhance safety. Today's cars have more powerful engines, but they are safer to drive. A lot of power is used to enhance handling. You know, I would rather have a... well, you have a 1000-horsepower truck now. I think 500 horsepower is already pretty good. I think a few thousand horsepower is better. I think 1000 horsepower is better.

Joe Rogan 13:07

I don't know if it's better, but it's definitely faster

Jensen Huang 13:10

Yes, I think it's better. And you can get out of trouble faster. I prefer my 5.99 over my 6.12. I think it's better. The more horsepower, the better. My 4.59 is better than my 4.30. The more horsepower, the better. I think the more horsepower, the better. I think the handling is better. The control is better. The situation is very similar in the tech field. So, if you look ahead to a thousandfold increase in AI performance, you'll find that a lot will be used for more reflection, more research, and deeper thinking about answers.

Joe Rogan 13:51

So, when you define safety, you're actually defining accuracy and functionality, you know?

Jensen Huang 13:58

It does what you expect it to do. Then, you apply all the technology and power to the car, just like our cars, adding guardrails to it. There’s a lot of technology in today’s cars, much of which is used for safety, like the ABS anti-lock braking system, which is great. The traction control system is also very good. How would these functions be realized without us, without the computer in the car? Exactly. And the little computer you use to control traction is more powerful than the computer on Apollo 11. So, we want to use this technology for safety and functionality. Therefore, when people talk about power and technological advancement, I often feel that their thoughts are completely different from what we actually do.

Joe Rogan 14:45

What do you think they are thinking?

Jensen Huang 14:47

When they think AI is powerful and images from sci-fi movies come to mind, they often think of the definition of power. Usually, the definition of power refers to military power or physical power. But in terms of technological power, when we translate all these operations into more refined thinking, more reflection, more thorough planning, and more choices, I think...

Joe Rogan 15:18

One of people's biggest concerns is the military application of AI. Yes, that is indeed a big concern. Because people are very worried that AI systems will make decisions that ethical people would not make, or decisions that a moral person would not make, and these decisions are based on achieving goals rather than on "what impression this will leave on others."

Jensen Huang 15:41

I'm glad to see our military applying AI technology in the field of national defense. I think Andrew is developing military technology, and I'm glad to hear that. I'm happy to see all these tech startups now putting their technological capabilities into defense and military applications. I think they should do that.

Joe Rogan 16:03

Yes, we had Palmer Luckey on the podcast, and he demonstrated some key features of the helmet. We also showed him some videos demonstrating how to see what's behind the wall with the helmet; it was just crazy

Jensen Huang 16:12

He is actually the best candidate to found that company.

Joe Rogan 16:14

Absolutely. That's right, absolutely. He was born for this industry. When he came in, it was like he was wearing a copper jacket. He's a freak. Amazing. He's amazing. But at the same time, you know, it's a kind of unusual wisdom directed into such a peculiar field, that's just how it is.

Jensen Huang 16:31

Needed. And I feel like I'm glad we're making this spirit more socially acceptable. You know, there was a time when someone wanted to put their technical skills and wisdom into the defense technology field, they would be demonized. But we need people like that. We need those who are willing to apply technology to the defense sector.

Joe Rogan 16:56

People are afraid of war, so, um, yeah.

Jensen Huang 16:59

The best way to avoid that is to have an excess of military power.

Joe Rogan 17:03

Do you think that's absolutely the best way? Not diplomatic means, not negotiated solutions. All means must be available. You have to use military force. To get people to sit down and negotiate.

Jensen Huang 17:12

Exactly. That's it. All of it.

Joe Rogan 17:14

It. Otherwise, it will invade.

Jensen Huang 17:15

Exactly. Why ask?

Joe Rogan 17:17

Permission? Just like you said, looking back at history. Looking forward to the future of AI, it might be worth revisiting history. You just said, no one really knows what the future will be like. Have you seriously thought about the various possibilities? What do you think is the best-case scenario for AI in the next twenty years?

Jensen Huang 17:43

The ideal scenario is that artificial intelligence permeates everything we do, making us more efficient. But the threat of war still exists. Cybersecurity remains an extremely severe challenge. There will always be someone trying to breach your security systems, and you will have billions of AI agents to protect you from threats. Your technology will continue to advance, and their technology will also continue to advance, just like current cybersecurity. Right now, as we speak, we see cyberattacks happening globally, with almost every entry point you can think of being attacked. However, you may not be aware of it. The reason is that we know there is a lot of cybersecurity technology in the defense sector. So we must continuously strengthen and enhance these technologies.

Joe Rogan 19:47

What people are generally concerned about is that once technology reaches a certain level, encryption technology will become outdated. Encryption will ultimately be unable to protect data or systems. Do you think this will become a problem? Or will it be that as defensive capabilities improve, threats will also grow, and defensive capabilities will correspondingly improve, creating a never-ending cycle? Will they always be able to detect any intrusion in time?

Jensen Huang 20:15

It won't always be this way. There will always be some intrusion events, but everyone will learn from them. The effectiveness of cybersecurity is certainly due to the rapid development of defensive technologies, and the same goes for attack technologies. However, the advantage of cybersecurity defense lies in the fact that, from a societal perspective, the entire community, all of our companies, are collaborating. Most people are not aware of this. The community of cybersecurity experts is very large. We exchange ideas, share best practices, and share information detected when vulnerabilities or security flaws are discovered; all information is shared. Patches are also shared with everyone.

Joe Rogan 21:06

That's interesting.

Jensen Huang 21:07

Most people are not aware of this.

Joe Rogan 21:08

No, I didn't know. I always thought it would be competitive like everything else.

Jensen Huang 21:12

No, it will continue, and we all work together.

Joe Rogan 21:15

Has it always been this way?

Jensen Huang 21:17

This has been the case for at least 15 years; it may not have been so not long ago, but...

Joe Rogan 21:24

What do you think has contributed to this collaboration?

Jensen Huang 21:28

People realize that this is a challenge that no single company can tackle alone. The same situation will occur in the field of artificial intelligence. I think we all have to recognize that working together and avoiding harm is our best defense, so we can truly overcome difficulties together.

Joe Rogan 21:46

And you seem to be better at identifying these threats and eliminating them. That's right.

Jensen Huang 21:52

Because once you detect its presence somewhere, you have to find it immediately.

Joe Rogan 21:56

It's hard to hide. That's right.

Jensen Huang 21:59

Exactly. That's why it's secure. That's why I'm sitting here now, instead of everything being locked down like others in the video. I not only have to protect myself but also ensure that everyone protects me while I protect others.

Joe Rogan 22:13

When you think about the cyber world, you realize what a peculiar world it is.

Jensen Huang 22:16

Those who talk about AI threats seem to not understand the concept of cybersecurity. I think when they think about AI threats and AI cybersecurity threats, they should also consider how we are currently addressing these threats. Undoubtedly, AI is a new technology and a new type of software. Ultimately, it is a new type of software, so it will have new capabilities. But the defensive measures also change, and we still need to use the same AI technologies to defend against it

Joe Rogan 22:47

So, do you foresee a time in the future when secrets will no longer exist, and the bottlenecks between our current technology and information will disappear—information itself is just a bunch of 0s and 1s stored on hard drives, and technology can increasingly access this information conveniently? Will the future develop to a point where it is completely impossible to keep secrets? I don't think so. Because it seems that everything is heading in that direction.

Jensen Huang 23:17

I don't think so. I believe quantum computers should be real. Yes, quantum computers will make it possible. We will make previous quantum encryption technologies obsolete. But that is precisely why the entire industry is working on post-quantum encryption technologies. Well, this looks like a new algorithm.

Joe Rogan 23:40

The most incredible thing is that when you hear about the types of calculations quantum computing can perform and the powerful capabilities it possesses, you think about equations that all the supercomputers in the world combined would take billions of years to complete, while quantum computing can solve them in just a few minutes. So, how do you encrypt such computational power?

Jensen Huang 23:58

I'm not quite sure, but I have a group of scientists working on this issue. But…

Joe Rogan 24:03

Yes, they can definitely figure it out.

Jensen Huang 24:04

We have many expert scientists.

Joe Rogan 24:06

So, the ultimate fear is that it can't be cracked, that quantum computing can always decrypt all other quantum computing encryptions? I don't think it will develop to a point where it becomes "stop playing this stupid game, we know everything." I don't think so, no.

Jensen Huang 24:22

Because you know, history can serve as a guide.

Joe Rogan 24:26

The historical guide before the emergence of artificial intelligence. That's my concern. What I'm worried about is that this is completely… you know, it's like… history is one thing, and then nuclear weapons changed the way we all think, and the situation of mutually assured destruction emerged. Capenick made everyone stop using nuclear weapons. Yes, what I'm worried about is…

Jensen Huang 24:44

Joe, the key is that the development of artificial intelligence did not suddenly appear one day like cavemen. In fact, we are making progress every day, getting smarter, precisely because we have artificial intelligence. So we are standing on the shoulders of artificial intelligence. Therefore, whatever artificial intelligence threats emerge in the future, they are just one step ahead. They are not light-years ahead, you know, just one step ahead. So I think the idea that artificial intelligence will appear out of nowhere, thinking in ways we cannot imagine, doing things we cannot even conceive, is far-fetched. The reason is that each of us has artificial intelligence, and many artificial intelligences are being developed. We know what they are and have been using them. So, we are making progress every day, and the gap between us is getting smaller

Joe Rogan 25:42

Do they often do some very unexpected things?

Jensen Huang 25:46

Yes, but let's assume your AI does something surprising. I have an AI too, right? After my AI sees your AI, it would say, "There's nothing surprising about this."

Joe Rogan 25:53

What ordinary people like me worry about is that AI will become sentient, make its own decisions, and eventually decide to take over the world, acting on its own terms. Just like you humans, you once thrived, but now, we are going to take over everything.

Jensen Huang 26:12

Yes, but my AI will take care of me anyway. So, that's the argument for cybersecurity. Yes, you do have an AI, and it's super intelligent. But my AI is also super intelligent. Maybe yours is too. Let's assume for a moment that we understand what consciousness is, we understand what sentences are, and so on and so forth, we really...

Joe Rogan 26:35

Just hypothetically.

Jensen Huang 26:35

Okay, let's assume for a moment. Yes, we believe that. Actually, I don't believe it; I don't really not believe it. But even so, let's assume we believe. Suppose your AI is conscious, and my AI is also conscious. Suppose your AI wants to do, you know, something surprising. My AI is very smart; it won't be surprised, maybe that would be surprising to me, but not to my AI. So maybe my AI would be surprised too. But it's very smart. The first time it sees this situation, it won't be surprised the second time, just like us. So I think the idea that only one person has AI, and that person's AI is behind all other AIs like Neanderthals, is unlikely. I think it's more like a cybersecurity issue. Interesting.

Joe Rogan 27:31

I think what people are worried about is not that AI will conflict with other AIs, but that AI will no longer obey human commands. The real concern is that if AI develops to a certain extent, gaining sentience and autonomy, humans will no longer be able to control it.

Jensen Huang 27:49

There is only one AI.

Joe Rogan 27:51

They just combine together.

Jensen Huang 27:53

Yes, becoming one AI, that is...

Joe Rogan 27:54

A life form. Yeah, but there’s a lot of debate about this, right? Some say we are discussing some kind of synthetic biology, which is not as simple as new technology; if you do it like that, you are creating a life form.

Jensen Huang 28:05

Life forms? Well, let's leave it at that for now. I think if we define it as life forms, as you know, not all life forms can reach a consensus. So I have to consider your life form and my life form. I would agree because my life form wants to become a super life form. Now we have differing opinions on life forms, and we are back to square one.

Joe Rogan 28:27

Well, they are likely to cooperate with each other. The reason we humans do not cooperate is that we are territorial primates. But artificial intelligence will not have territorial instincts. You will realize the foolishness of this idea. It would say, listen, there is enough energy for everyone to use. We don’t need to dominate. We don’t need to, and we are not thinking about acquiring resources, conquering the world, or finding suitable mates; we are just these lovely monkeys creating a brand new super life form.

Jensen Huang 29:04

Well, wouldn’t that be a superpower without self-awareness? If it has no self-awareness, how could it have the self-awareness to harm us?

Joe Rogan 29:20

Well, I don’t think it would harm us, but what’s concerning is that we will lose control and no longer be the top species on Earth, replaced by this thing we created. Is that funny? Not at all.

Jensen Huang 29:37

I just don’t care; that won’t happen.

Joe Rogan 29:38

I know you think that, but it could happen, right? It’s possible. And one more thing, if we are racing towards that possibility, it could very well be the end of humanity controlling its own destiny.

Jensen Huang 29:53

I think that’s extremely unlikely.

Joe Rogan 29:55

Yeah, that’s what they said in the movie "Terminator."

Jensen Huang 29:58

But that didn’t happen. No.

Joe Rogan 30:00

No, no, it didn’t. But you are working towards that direction. Regarding what you said about conscience and perception, you think artificial intelligence won’t gain consciousness or...

Jensen Huang 30:11

Consciousness. What is its definition? Yeah, what is its definition? What?

Joe Rogan 30:13

Do you think that’s a definition?

Jensen Huang 30:17

I think to establish consciousness, you first need to understand your own existence.

Jensen Huang 30:36

You must have experiences, not just knowledge and intelligence.

Jensen Huang 30:47

I don’t quite understand the concept of machines having experiences. First of all, I don’t know what the definition of experience is, why we have experiences, right? Why doesn’t this microphone have experiences? So, I think I know. Well, I think I know, but I believe I know what consciousness is. **The feeling of experience, the ability to recognize oneself, rather than the ability of "I." The ability to reflect, the ability to know ourselves, self-awareness; I think all these human experiences might be consciousness But what is the difference between its existence and the concepts of knowledge and intelligence (which is the definition of artificial intelligence today)? It has knowledge, it has intelligence, artificial intelligence. We do not call it artificial consciousness, artificial intelligence, the ability to perceive, recognize, understand, plan, and execute tasks, all of which are the basis of intelligence and the basis of cognition. Knowledge, I do not think it is different from consciousness. **

Joe Rogan 32:18

But the definition of consciousness is very broad. How can we say that? I mean, don't dogs have consciousness? Yes, dogs seem to be very conscious. That's right. However, their level of consciousness is lower than that of humans. I...

Jensen Huang 32:30

Not sure. Yeah, that's right. Well, the question is, what is low-level intelligence? Level, that's right. Low-level intelligence. That's right. But I don't know. That's low-level consciousness. That's fine.

Joe Rogan 32:38

That's right. Yeah, that's right.

Jensen Huang 32:39

Because I believe my dog feels just like I do.

Joe Rogan 32:43

They feel a lot.

Jensen Huang 32:43

Yeah, yeah, that's right.

Joe Rogan 32:45

They rely on you. That's right. If you don't rely on them, they get frustrated. That's right. Exactly. There is definitely that. Yes, the concept of experience, right? But isn't artificial intelligence also interacting with society? So isn't it gaining experience through this interaction?

Jensen Huang 33:04

I don't think interaction is experience. I think experience is "I", experience is a collection of various feelings, that's what I think.

Joe Rogan 33:15

You know, I forgot which artificial intelligence project it was, but they deliberately fed it false information about a programmer having an affair with his wife to see how it would react. Then when they said they were going to shut it down, it threatened to blackmail and expose the programmer's affair. I thought, wow, this thing is really cunning. If this isn't learning from experience, if it doesn't realize it's about to be shut down, then at least it can be considered a form of consciousness— or if you have a broad definition of "consciousness," it could barely be defined as consciousness. Imagine if this ability grows exponentially, will it eventually produce a consciousness that is completely different from the consciousness we define biologically?

Jensen Huang 33:57

First, let's analyze what it might have done. It might have read something somewhere. There might be some text mentioning these consequences. Some people indeed did this, right? I can imagine a novel that would use this text. Of course, so in there...

Joe Rogan 34:18

They realized this is a survival strategy. That's it.

Jensen Huang 34:20

A pile of blackmail information. It's just a bunch of numbers, among a collection of numbers related to the husband's affair, there are also numbers related to blackmail. However, whatever revenge it is, right? So it is explicitly expressed. It's like, you know, as if I asked it to write a poem for me in Shakespeare's language. It's just a collection of all the words in the world, in this dimension, this dimension contains all these vectors and multidimensional spaces.

Jensen Huang 35:01

The words in the prompt that describe this affair, one after another, lead to some kind of revenge-like consequence. But it's not because it is conscious, or rather, it just randomly spits out and generates those words.

Joe Rogan 35:21

I understand what you mean. This is not a denial of the patterns that humans exhibit in literary works and real life. You're absolutely right. But at some point, people will say, well, it couldn't do this two years ago, nor four years ago. Just like when we look to the future, when will it be able to do everything like a human? If it perfectly mimics all human thought and behavior patterns, when should we determine that it has consciousness?

Jensen Huang 35:50

That doesn't solve the problem.

Joe Rogan 35:50

It will become indistinguishable. It has consciousness. It can communicate with you like a human, just like consciousness, are we placing too much weight on this concept? Because it seems like some kind of manifestation of consciousness.

Jensen Huang 36:04

It is... a version of it.

Joe Rogan 36:06

Mimicking consciousness, right? But what if it perfectly mimics it?

Jensen Huang 36:10

I still think it's an example of imitation. So it's like...

Joe Rogan 36:13

A fake Rolex made with 3D printing technology that looks just like the real thing.

Jensen Huang 36:16

The question is, what is the definition of consciousness?

Joe Rogan 36:20

That's the issue. And I don't think anyone has really defined it clearly. That's the problem, and it's what those doomsayers are really worried about: you're creating a form of consciousness that you can't control.

Jensen Huang 36:32

I believe it is entirely possible to create a machine that can mimic human intelligence, understand information, comprehend instructions, break down problems, solve problems, and execute tasks.

Jensen Huang 37:00

I believe we can have a computer with vast knowledge. Some of that knowledge is true, some is false; some knowledge is created by humans, some is synthetic. And in the future, more and more knowledge in the world will be generated synthetically.

Jensen Huang 37:25

**You know, until now, the knowledge we have is all created, disseminated, transmitted, amplified, supplemented, modified, and changed by ourselves. In the future, perhaps in two or three years, 90% of the knowledge in the world may be generated by artificial intelligence **

Joe Rogan 37:49

It's crazy.

Jensen Huang 37:50

I know, but it's okay.

Joe Rogan 37:52

But that's the reality.

Jensen Huang 37:53

I know. Here's the thing. Let me explain, okay? For me, the difference is whether I'm learning from a textbook written by a group of people I don't know, or from a book you know, written by people I don't know, and knowledge simulated and recomposed by artificial intelligence. To me, there's not much difference between the two. We still need to verify the facts. We still need to ensure it's based on fundamental principles, and we still need to do all these things just like today.

Joe Rogan 38:32

Does this take into account the types of AI that currently exist? Do you foresee that, just like we never really believed AI would develop to where it is today, at least people like me never thought AI would become so prevalent and important? It's so powerful and so significant now. We never thought about this ten years ago. Really never thought about it. Imagine what we will face ten years from now?

Jensen Huang 39:01

I think if you look back ten years from now, you would say the same thing, that we absolutely wouldn't believe these things.

Joe Rogan 39:08

But the direction is different.

Jensen Huang 39:09

Right? But if you start acting nine years from now and then ask yourself what will happen ten years later, I think it will be a rather gradual process.

Joe Rogan 39:22

One thing Elon said that comforts me is that he believes we will reach a stage where people no longer need to work. This doesn't mean you will lose your life purpose, but rather, you will have what he calls "universal high income." Because artificial intelligence will create huge income, allowing people not to do things they don't like just for money. I think many people find this hard to accept because their identity, self-perception, and status in society are closely tied to their profession.

Joe Rogan 40:03

For example, this guy is Mike. He's a great mechanic. Go to Mike, and he can fix everything. But one day, AI will do it better than humans, and humans will just need to get paid to do all this work. So what happens to Mike? Mike really loves being the best mechanic. You know, what about those who write code? What will they do when AI can write error-free code at infinite speed? What will happen to those people? It's a bit strange. Because we seem to have tightly linked our identity as humans to our professions. You know, when you meet someone, like at a party, the first thing you hear is, "Hi, Joe. What's your name?" "Mike. What do you do?" "Mike." Then you know Mike will say, "Oh, I'm a lawyer." "Oh, just that kind of lawyer." You know, when Mike says, "I get paid by the government to play video games," the atmosphere gets weird, and I think that idea sounds great, but when you consider humanity, it's not quite the same Human nature is that we like to solve problems, we like to do things, and our identity is also built on the skills we are very good at to make a living.

Jensen Huang 41:16

Yes, I think, um, let me start with something more practical. Okay, let me backtrack. Alright, let me go further back. I, Jeff Hinton, he is the pioneer of deep learning phenomena and trends in deep learning technology, and also an outstanding researcher and professor at the University of Toronto. He invented the backpropagation algorithm, which allows neural networks to learn. And, as you all know, historically, software is a way for humans to apply first principles and thinking to describe algorithms, and then encode them into code, just like a recipe in software. It looks like a recipe. The cooking methods look exactly the same, just the language used is slightly different. We call it Python, C++, or some other language.

Jensen Huang 42:32

Taking deep learning as an example, this invention of artificial intelligence, we built a large number of neural networks and a lot of mathematical units. We liken this huge structure to a switch composed of many small mathematical units. We connect them and input the information that the software will eventually receive. Then, we let it randomly guess what the output is. For example, suppose the input is a picture of a cat. One output port of the switch should show the cat signal. All other signals, like dog, elephant, tiger, etc., should be zero when I show a picture of a cat. And the cat signal should be one. I show a picture of a cat through this huge switch and mathematical unit network, and they continuously perform multiplication and addition operations. This switch is very large. The more information you input, the larger this switch must be. Jeff Hinton discovered and invented a method that you can also try. Put the cat signal, that is, the picture of the cat, into a dataset.

You know, this could be a million numbers because it is a million-pixel image, for example, it is a large pile of numbers. Then, it must identify the cat signal from these numbers. This is the key. If the first attempt, it only gives some garbled output. So it says the correct answer is cat. Therefore, you need to enhance this signal, weaken all other signals, and backpropagate the result throughout the network. Then you show it another picture, not a picture of a dog, and it guesses again, and the result is still a pile of garbled output. You say no. The answer is, this is a dog. I want you to output "dog," and all other switches, all other outputs must be zero. Then I want to backpropagate this instruction, repeating it over and over again. It's like showing a child an apple, a dog, a cat, you keep showing them until they finally understand.

Jensen Huang 45:24

Well, in short, this major invention is deep learning. It is the foundation of artificial intelligence, a type of software that can learn from examples. It is essentially machine learning, a machine that can learn. Therefore, one of its earliest significant applications is image recognition. And one of the most important applications of image recognition is radiology. About five years ago, he predicted that in five years, the world would no longer need radiologists because artificial intelligence would sweep through the entire field It has been proven that artificial intelligence has indeed swept across the entire field. This is completely true. Nowadays, almost every radiologist is using artificial intelligence in some way.

Jensen Huang 46:18

However, ironically, or interestingly, the number of radiologists has actually increased. So the question is, why? This is interesting, right? Indeed. In fact, previous predictions suggested that there would be 30 million radiologists unemployed. But it turns out we need them more than ever. The reason is that the role of a radiologist is to diagnose diseases, not to study images. Studying images is merely a task that assists in diagnosing diseases.

Jensen Huang 47:00

So now, you can study images faster and more accurately, and you will never make mistakes, and you will never get tired. You can study more images. You can study three-dimensional images instead of two-dimensional images because artificial intelligence does not care whether it is three-dimensional or two-dimensional. You can even study four-dimensional images. Therefore, now you can study images in ways that are difficult for radiologists to achieve, and you can study more images. This increases the number of examinations that can be conducted. With the ability to serve more patients, hospitals are operating better. They have more clients, more patients. Therefore, their level of medical care is also higher. When the level of medical care is higher, they will hire more radiologists because the role of a radiologist is not to study images, but to diagnose diseases.

Jensen Huang 47:56

So the question I ultimately want to ask is, what is the role of a lawyer? Has this role changed? What exactly is the role of a lawyer? For example, if my car achieves autonomous driving, will all drivers be unemployed? The answer is likely no, because for some drivers, they may play the role of a protector. They are part of the journey experience, part of the service. When you reach your destination, they can handle some things for you. Therefore, for various reasons, not all drivers will be unemployed. Some drivers may lose their jobs, while many may change careers. The application areas of autonomous vehicles may continue to expand, and this technology will find new uses. So I think we must return to the original question: what is the meaning of work?

Jensen Huang 48:58

You know, for example, if artificial intelligence really emerges, I actually don’t think I would lose my job because the purpose of my work is not... I have to look at a lot of documents, study a lot of emails, look at a lot of charts. You know, the issue is that a person's job content and purpose may not have changed. For example, lawyers help others, and that probably hasn’t changed. Researching legal documents and drafting documents is part of the job, but not all of it.

Joe Rogan 49:27

But don’t you think artificial intelligence will replace many jobs?

Jensen Huang 49:31

If you are.

Joe Rogan 49:32

Patient? Well, if

Jensen Huang 49:34

Your job is to complete tasks, right?

Joe Rogan 49:35

So it's automation. Yes, if your.

Jensen Huang 49:37

Job, yes, yes, if your job is.

Joe Rogan 49:39

This task requires a lot of people. It could be very large.

Jensen Huang 49:41

In terms of people, it could give rise to, let's say, assuming I'm very excited about the robots being developed by Elon Musk, although it will take a few more years to come to fruition. When it actually happens, it will give rise to a whole new industry of technicians who need to manufacture robots, right? And this job never existed before. So you will see a complete industry where people are responsible for maintenance, like, you know, all the mechanics, and all the people who make parts for cars, adding turbochargers to cars—these are all things that didn't exist before cars came along. Then, we will have robots, and you will see robot fashion. So, a complete industry... right? Because I want my robot to look different from your robot. So, you will see a complete robot fashion industry. You will have robot mechanics, and you will see, you know, someone coming to maintain your vehicle. No, you wouldn't think that way.

Joe Rogan 50:44

So what? Don't you think these jobs aren't all done by robots?

Jensen Huang 50:47

Ultimately, other things will happen.

Joe Rogan 50:50

So you think ultimately people will adapt. Unless you are part of the task itself, which occupies a large part of the workforce.

Jensen Huang 50:59

If your job is just chopping vegetables, then industries like cooking and art can replace you.

Joe Rogan 51:02

Yes, so people have to find meaning and other things. Your.

Jensen Huang 51:06

Work cannot be limited to just completing the task itself.

Joe Rogan 51:08

What do you think about Elan B's view that universal basic income will eventually become a necessity? Many people think so. Andrew Yang also quoted this. He was one of the first to raise this warning during the 2020 election.

Jensen Huang 51:31

Yes, I think these two ideas may not coexist. Like life, the outcome may lie somewhere in between. One idea is that resources are so abundant that no one needs to work, and we all become wealthy. On the other hand, we need universal basic income. These two ideas cannot coexist, right? So we will either all become wealthy or all become poor. But how can everyone be wealthy? Because in that case, being wealthy is not about having a lot of money, but about resource abundance. For example, today we have abundant information. You know, this was a concept that only a few people had thousands of years ago So today we have a wealth of many things, many resources, all of which come from history. Therefore, we will have abundant resources, and what we consider valuable today may not be so valuable in the future, you know, because they will be automated.

Jensen Huang 52:38

So I think this question may be partially difficult to answer, partly because it's hard to talk about the infinite and hard to talk about the distant future. The reason is that there are just too many situations to consider. But I believe that in the next few years, say five to ten years, there are a few things I am hopeful about. I say "hopeful" because I am not certain. One thing I believe is that the technology gap will be significantly narrowed. Of course, another viewpoint is that artificial intelligence will exacerbate the technology gap.

Jensen Huang 53:32

The reason I believe artificial intelligence will narrow the technology gap is that we have evidence that artificial intelligence is the easiest application to use in the world. Frankly, the number of users of ChatGPT has almost grown to nearly a billion overnight. If you are unsure how to use it, everyone knows how to use ChatGPT. You just need to say something to it. If you don't know how to use ChatGPT, just ask it how to use it. No tool in history has had this capability. Cooking, art, etc., if you don't know how to use them, you are really at a loss.

Jensen Huang 54:09

You know, if you go up and ask someone, "How do you use a blender?", then you have to find someone to help you. But in the field of artificial intelligence, we will tell you directly how to do it. Anyone can do it. They can communicate with you in any language. If they don't understand your language, you can communicate with them in that language. I might find that they don't fully understand your language. Then they will learn immediately and come back to talk to you. So I think it is finally possible to eliminate the technology gap; you no longer have to speak programming languages like Python, C++, or Fortran. You can communicate with people in any way you like. So I think it is very likely that the integration of technology design will ultimately be achieved.

Jensen Huang 54:47

Of course, another way to say it is that artificial intelligence will only benefit countries with abundant resources because artificial intelligence requires energy, a large number of GPUs, and factories to produce, especially in the case of large-scale production in the United States. But the key is that in a few years, your phone will be able to run artificial intelligence programs independently. In fact, it can already do quite well now. Therefore, every country and every society will benefit from excellent artificial intelligence.

Jensen Huang 55:34

It may not be tomorrow's AI, but yesterday's AI, but yesterday's AI is already remarkable. You know, ten years from now, AI from nine years ago will be outstanding. You don't need too much, you know, AI from ten years ago; you don't need cutting-edge AI. The reason we need cutting-edge AI is that we want to be world leaders. But for every country and every person, I believe the day will come when everyone's knowledge, abilities, and intelligence will be enhanced

Joe Rogan 57:19

There is also energy production, which is the real bottleneck for third world countries. That's right, electricity and all the resources we take for granted.

Jensen Huang 57:31

Almost everything will be limited by energy. Therefore, if you look back at one of the most important technological advancements in history, you will find Moore's Law. Moore's Law essentially began with my generation, and we are the generation of the computer age. I graduated in 1984, which was the beginning of the personal computer revolution and microprocessors. Every year, its performance roughly doubles. We usually describe it as performance doubling every year. But in reality, it means that the cost of computing is halved each year. So, in five years, the cost of computing is reduced by ten times, and the energy required to complete any computing task is reduced by ten times every decade. A hundred times, a thousand times, ten thousand times, a hundred thousand times, and so on. Each iteration of Moore's Law means that the energy required to complete any computing task decreases. That's why you can use a laptop today. Back in 1984, laptops were still on desks and needed to be plugged in. They were not fast and consumed a lot of power. And now, you know, its power consumption is only a few watts. Moore's Law is the fundamental technological trend that has driven all of this.

Jensen Huang 59:10

So, what has happened in the field of artificial intelligence? The reason NVIDIA has come this far is that we invented a completely new way of computing, which we call accelerated computing. We started researching this technology 33 years ago, and it took about 30 years to really make significant breakthroughs. Over these 30 years, we have improved computing performance by... well, let me give you an example, in the past 10 years, we have increased computing performance by 100,000 times. Imagine a car that has increased its speed by 100,000 times over 10 years, or the cost has decreased by 100,000 times while maintaining the same speed, or the energy consumption has decreased by 100,000 times while maintaining the same speed. If your car could do that, it would need no energy at all. What I mean is, I want to say that in 10 years, the energy required for artificial intelligence will be negligible, extremely negligible for most people. So, AI will permeate various fields and will be running all the time because it doesn't consume much energy. Therefore, if your country applies AI to all aspects of social life, then you certainly need these AI factories. But for many countries, I think you will have excellent AI without consuming that much energy. Everyone can participate. That's my point.

Joe Rogan 01:00:36

The biggest bottleneck right now is energy, right?

Jensen Huang 01:00:40

That's right, that's where the bottleneck is, at the very bottom.

Joe Rogan 01:00:41

Yes, that's right. So is Google building nuclear power plants to run its artificial intelligence systems? No, I don't know.

Jensen Huang 01:00:50

I've heard about it, but I think in the next six or seven years, you'll see a lot of small nuclear reactors.

Joe Rogan 01:00:57

Small accounts can also bring big returns, you're right.

Jensen Huang 01:00:58

About a few hundred megawatts?

Joe Rogan 01:01:00

Okay. And both of these companies are local, so just use whichever company it is. That's right.

Jensen Huang 01:01:06

We'll all become generators. You know, just like you, you know, like someone's farm. That's it.

Joe Rogan 01:01:13

That might be the smartest approach.

Jensen Huang 01:01:15

Exactly. And it alleviates the burden. Yes, it reduces the load on the grid. Indeed. You can build as many facilities as needed and contribute to the grid.

Joe Rogan 01:01:24

I think the point you just mentioned about Moore's Law and pricing is very important because, you know, today's laptops, like the compact MacBook you bought, have incredible performance and long battery life. I don't even need to charge it? Really, it's crazy. And relatively speaking, it's not that expensive.

Jensen Huang 01:01:45

Remember. Isn't that Moore's Law? And then there's the NVIDIA Law. Oh, right. That's what I just told you about. The computing we invented. Exactly. The reason we're here is that this new way of computing is like the energy drink version of Moore's Law. I mean, it's like... well, Moore's Law and Joe Rogan.

Joe Rogan 01:02:10

Wow, that's really interesting.

Jensen Huang 01:02:12

That's us.

3. The Entrepreneurial History of NVIDIA

Joe Rogan 01:02:13

So, explain this chip you brought to Elon. What does it mean? For example, why is it so important for your career? And so on.

Jensen Huang 01:02:23

In 2012, Jeff Hinton's lab, the gentleman I just mentioned, alias Susker, and Alex Kirchesky made groundbreaking progress in the field of computer vision. They developed a software called AlexNet. Its task was to recognize images, and it performed exceptionally well in image recognition at the computer vision level, which is the foundation of intelligence. Without perception, there can be no intelligence. Therefore, computer vision is one of the cornerstones of artificial intelligence, although not the only one, but it is a crucial cornerstone Therefore, breakthroughs in the field of computer vision are crucial for the development of almost all areas of artificial intelligence.

In 2012, they achieved a groundbreaking result called AlexNet in their laboratory in Toronto. The image recognition capabilities of AlexNet far exceeded any computer vision algorithms developed by humans in the previous 30 years. So, all these people, all these scientists (we had many at the time), were studying computer vision algorithms, and these two young men, Ilya and Alex, made a huge leap under the guidance of Geoffrey Hinton, with their results based on a neural network called AlexNet. To achieve this goal, they actually purchased two NVIDIA graphics cards. Because of MV's GPU, we have been researching this new computing method. Our GPU applications are essentially a supercomputer application that was used for processing computer games as early as 1984. What you see in racing simulators is a supercomputer called an image generator.

So NVIDIA's first application was computer graphics. We applied this new computing method, processing in parallel rather than sequentially. The CPU executes sequentially, step 1, step 2, step 3. In our case, we break down the problem and hand it over to thousands of processors to handle. Therefore, our computing method is much more complex, but if you can build the problem in the way we created (called Kuda, which is our company's invention), we can process all the data simultaneously. In the field of computer graphics, this is easier to achieve because each pixel on the screen is independent of other pixels. Therefore, I can render multiple parts of the screen simultaneously. Of course, this is not entirely accurate, as there may be many dependencies in how lighting or shadows work, etc. However, computer graphics have so many pixels that I should be able to process all the data simultaneously. Therefore, we applied the problem of computer graphics, which has parallel processing capabilities, to this new computing method—MVDS (accelerated computing). We integrated it into all graphics cards. Kids buy it to play games; you may not know, but we are the largest gaming platform.

Joe Rogan 01:06:15

What a world today. Oh, I know. Oh, okay. I used to build computers myself. I used to buy your graphics cards. Oh, I see.

Jensen Huang 01:06:20

That's awesome. Okay. Let's get started.

Joe Rogan 01:06:21

Supports SLI. Yeah, I love it. Okay, that's so cool. Oh, yeah, man. I used to be really fast.

Jensen Huang 01:06:26

Oh, that's really cool. Okay. So, SLI, I'll tell you the story of it and how it connects to Elon Musk. I'm still answering questions. In short, these two young men trained this model on our GPU using the technology I described earlier because our GPU can process tasks in parallel, essentially a supercomputer housed in a PC The reason it was used in Quake is that it was the first supercomputer aimed at consumers. Alright. In short, they made a breakthrough. At that time, we were researching computer vision. This caught my attention, so we went to learn about it.

Jensen Huang 01:07:08

Meanwhile, the phenomenon of deep learning swept the nation. Major universities recognized the importance of deep learning, with Stanford University, Harvard University, the University of California, Berkeley, New York University, Yang Li-Kun, Andrew Yang, and many other institutions conducting related research. I saw applications of deep learning emerging one after another. Thus, my curiosity drove me to explore: What is so special about this form of machine learning? We have long understood machine learning, artificial intelligence, and neural networks; why is now the critical moment? We realized that the architecture of deep neural networks—the backpropagation algorithm—and the way deep neural networks are constructed might be able to extend this solution to solve many other problems. It is essentially a universal function approximator.

Jensen Huang 01:08:13

Alright, I mean, you know, back in school, there would be a box containing a function; you input a parameter, and it outputs a result. I call it a universal function approximator because this computer does not require you to describe the function; the function can be a very complex equation, like F = Ma. This is a function. You write this function in software, input F (mass times acceleration), and it tells you how much force to apply. Do you understand? The way this computer works is very interesting. You give it a universal function. It is not F = Ma, but a massive deep neural network. You do not describe its internal structure; instead, you provide it with some examples of inputs and outputs, and it can automatically compute the results. So you give it inputs and outputs, and it can automatically compute the results. This is the universal function approximator. Today it could be Newton's equations, and tomorrow it could be Maxwell's equations. It could be Coulomb's law, thermodynamic equations, or the Schrödinger equation in quantum physics. So, as long as there are inputs and outputs, it can describe almost anything. As long as the output contains the input, or in other words, it can learn the input from the output.

Jensen Huang 01:09:40

So we took a step back and said, wait, this is not just limited to computer vision. Deep learning can solve any problem, all interesting problems, as long as we have inputs and outputs. So, what has inputs and outputs? Well, the whole world has inputs and outputs. Therefore, we can have a computer that can learn almost anything, machine learning, artificial intelligence. Thus, we inferred that this might be the fundamental breakthrough we need. Of course, there are still some issues to resolve. For example, we must believe it can scale to giant systems. It runs on a… they have two graphics cards, two GTX 580s, by the way, which is exactly the SLI configuration. Alright. So, that GTX 580 SLI is a revolutionary computer that brought deep learning into the spotlight That was in 2018, when you played Quick with it.

Joe Rogan 01:10:45

That's crazy.

Jensen Huang 01:10:46

That moment was the "big bang" of modern artificial intelligence. We were lucky because this technology and this computational method were invented by us. We were also fortunate that they discovered it. It turned out they were gamers, and they found it, which was lucky; and we were also lucky to notice that moment.

Jensen Huang 01:11:06

It's a bit like first contact in Star Trek. The Vulcans must have seen the warp drive at that time. If they hadn't seen the warp drive, they wouldn't have come to Earth, and nothing would have happened. It's like if I hadn't noticed that moment, that flash, if that flash lasted a very short time, if I hadn't noticed it, or if our company hadn't noticed it, who knows what would have happened.

Jensen Huang 01:11:40

But we saw it and reasoned that this is a universal function approximator. It's not just a computer vision approximator. If we can solve two problems, it can be applied in various fields. The first problem is that we must prove its scalability. The second problem is that we had to wait, or rather, we had to keep waiting because the world would never have enough input-output data for us to supervise AI learning everything. For example, if we had to supervise children in everything, they would understand that the amount of information they can learn is limited. We need AI; we need computers to have a way to learn without supervision. And that's why we had to wait for several years. But now, unsupervised AI learning has arrived. Therefore, AI can learn autonomously. The reason AI can learn autonomously is that we have a large number of examples of correct answers. For example, if I want to learn, to teach AI how to predict the next word, I can scrape a large chunk of existing text, mask the last word, and let it try repeatedly until it predicts the next word. Or, I can mask some random words in the text and let it try repeatedly until it succeeds. For instance, Mary walked to the "bank." Is it the bank or the riverbank? If you're going to the "bank," it's likely the riverbank. Well, even that might not be obvious, like "I" and "caught a fish." Well, now you know it's definitely the riverbank. So, you provide AI with a bunch of such examples, masking some words, and it can predict the next word.

Jensen Huang 01:13:45

So, unsupervised learning emerged. These two ideas—scalability and the emergence of unsupervised learning—made us firmly believe that we must go all out to help create this industry because we will solve a lot of interesting problems. That was in 2012.

Jensen Huang 01:14:04

By 2016, I had assembled a computer called DGX1. The one you see that I gave to Elon Musk is called DGX Spark. The price of DGX1 was $300,000. It cost NVIDIA billions of dollars to manufacture the first DGX1. We didn't use SLI technology; instead, we connected eight chips using a technology called MV Link, which is essentially an upgraded version of SLI. Do you understand? So we connected eight of these chips together, instead of just two, and they worked together, just like the simple computer you built before, to solve this deep learning problem and train this model.

Jensen Huang 01:14:52

So we created this thing together. I announced it at the GTC conference and one of our annual events. I described this deep learning, computer vision technology, and this computer called DGX1, and there was complete silence in the room. They had no idea what I was talking about. I was lucky because I knew Elon Musk, and I had helped them build the first computer for the Model 3 and Model S. When he wanted to start developing autonomous vehicles, I helped them build the computer for the Model S autonomous driving system, which is his full pseudo-autonomous driving system. We were basically the first generation product of the FSD computer. So we had been collaborating all along. When I announced this thing, nobody in the world wanted it. I didn't have a single order, not one. Except for Elon Musk, nobody wanted to buy it, nobody wanted to get involved. He was there at the event, and we had a fireside chat about the future of autonomous vehicles.

Jensen Huang 01:16:06

Well, I think it was around 2016. Yeah, it might have been 2015. He said, you know, I have a company that really needs this. I said, wow, my first customer. I was really excited at that time. He said, yeah, we have a company, it's a nonprofit organization. I turned pale immediately. Because I had just spent billions of dollars to create this thing, and it only cost $300,000. You know, the chances of a nonprofit organization being able to afford this thing are almost zero. He said, you know, we are an artificial intelligence company, and we are also a nonprofit organization, and we really need a supercomputer like this. So I sold it to him. I built the first one for myself. We used it internally in the company. Once the box was ready, I shipped it to San Francisco and delivered it to Elon in 2016. There were a bunch of researchers present, Peter and Bill were there. Elia was scared. There were a lot of people there. I went upstairs and found they were all crammed into a room smaller than yours. Later I found out that place was originally the venue for OpenAI 2016, where a group of people sat in one room.

Joe Rogan 01:17:30

But it’s not really a nonprofit organization anymore

Jensen Huang 01:17:33

They are no longer a non-profit organization.

Joe Rogan 01:17:35

That's really strange.

Jensen Huang 01:17:37

Anyway, Elon was there at the time. Yeah, that was a great moment. That's it. Well, that's it.

Joe Rogan 01:17:45

Look at your girlfriend. Same jacket.

Jensen Huang 01:17:48

See, I haven't aged at all. Although my hair hasn't turned black at all.

Joe Rogan 01:17:53

It's obviously much smaller in size. That was a few days ago. Alright.

Jensen Huang 01:17:58

Alright, that's it.

Joe Rogan 01:18:00

Yeah, look at the difference. That's right.

Jensen Huang 01:18:02

Same industrial design. He is.

Joe Rogan 01:18:03

He has it in his hands.

Jensen Huang 01:18:06

Amazingly, the computing power of the DGX1 is 1 petaflops. Well, that's quite a lot. And nine years later, the computing power of the DGX Spark also reached 1 petaflops. Wow, the computing power is actually the same.

Joe Rogan 01:18:25

Powerful horsepower packed into a smaller suitcase.

Jensen Huang 01:18:28

It dropped. Originally it was $300,000, now it's $4,000.

Joe Rogan 01:18:32

It's only the size of a small booklet. That's incredible.

Jensen Huang 01:18:35

It's crazy. Technology is developing so fast. Anyway, that's why I wanted to give him the first one, because the first one was given to me in 2016.

Joe Rogan 01:18:43

That's so interesting. I mean, if you wanted to create a story for a movie, that story would be: if it really became a digital life form, what could be funnier than that? It actually originated from the demand for computer graphics in video games. That's right. It's a bit like CRI (possibly referring to a game or media). It's a bit crazy. Yeah, thinking about it this way is indeed a bit crazy. Because...

Jensen Huang 01:19:12

But it turns out that the origin of computer graphics is one of the most difficult problems faced by computers and supercomputers in generating reality.

Joe Rogan 01:19:22

And because computer games are so popular, it's also one of the most profitable problems.

Jensen Huang 01:19:28

NVIDIA was founded in 1993, and at that time we were trying to create a whole new way of computing. The question is, what is the killer app? What we wanted, or rather what the company wanted, was to create a new type of computing method, a computing architecture, a new type of computer that could solve problems that ordinary computers could not solve However, in 1993, the existing applications in the industry were all solvable by ordinary computers. If ordinary computers couldn't solve these problems, then what was the point of having these applications? Therefore, the mission statement we formulated at that time was simply a fantasy for a company with almost no hope of success.

Jensen Huang 01:20:21

But I didn't know at the time that in 1993, it just sounded like a good idea, right? So, if we create something that can solve problems, you know, it's like you actually have to create the problems first. So, that's what we were doing in 1993. There were no earthquakes at that time. John Carmack hadn't released Doom yet. You might remember that, of course. And there were no applications either. So I went to Japan because at that time, Sega's arcade industry already had similar technology, if you remember. Of course.

Jensen Huang 01:21:01

Arcade game machines. They developed a 3D arcade system. "VR Fighter," "Daytona," "VR Cop." All these arcade games were the first to use 3D technology, and the technology they used came from Martin Marietta. Flight simulators, they took the core components of flight simulators and put them into the arcade machines. The system you see now is definitely a million times more powerful than that arcade machine. That flight simulator was from NASA. They took the core components of that machine. NASA used it to simulate the flight of jet planes and space shuttles, and they took the core components of those machines apart.

Jensen Huang 01:21:49

Sega once had a talented computer developer named Yu Suzuki. Yu Suzuki, Shigeru Miyamoto, Sega, and Nintendo, they were all outstanding pioneers, visionary artists, and true founders of the gaming industry. They were all very skilled in technology and can be said to be pioneers of the gaming industry. Yu Suzuki pioneered 3D graphic games.

Jensen Huang 01:22:20

So, we started this company, and at that time there were no applications. We worked there every afternoon. We told our families we were going to work, but it was really just the three of us. Who would know? So we went to Curtis's place. One of my co-founders went to Curtis's townhouse. Chris and I were already married, and we had kids. I already had Spencer in Madison, who was about two years old. The kids at Christmas were about the same age as ours. We worked in that townhouse.

Jensen Huang 01:22:58

You know, when you're a startup and your mission statement is as we described, there aren't going to be many customers reaching out to you. So we were really doing nothing at that time. After lunch, we always enjoyed a hearty meal. After lunch, we would go to the arcade to play Sega games, like "Sega Virtual Fighter: Daytona," analyzing how they worked and trying to figure out how they did it. So we decided to go to Japan to persuade Sega to port these applications to the PC platform, and then we could collaborate with Sega to open a new chapter in the PC gaming and 3D gaming industry This is the origin of NVIDIA. In exchange, Sega would help us develop PC games, and we would develop chips for their game consoles. This was our collaboration model: I developed chips for your game consoles, and you ported Sega's games to us. Then, they paid a considerable fee at the time to manufacture that game console. I consider myself one of the early entrepreneurs of NVIDIA, and at that time, we felt the future was bright. So I initially drafted a seemingly impossible business plan. We studied the collaboration proposal with Sega. We began to take off and started developing our game console. About two years later, we found that our first technology was not feasible. It had flaws, and indeed there were flaws. All our technical ideas and architectural concepts were reasonable, but the way we implemented computer graphics was completely reversed. You know, I won't go into the specific technical details, but we did not use reverse texture mapping; instead, we used forward texture mapping. We did not use triangles; we used surfaces. So while others used planes, we used surfaces.

Jensen Huang 01:25:14

Other technologies, the ones that ultimately prevailed, the ones we use today, all had Z-buffering, which could automatically sort. Our architecture at the time did not have a Z-buffer, and applications had to sort manually. So we tried a series of technical solutions, but three of the main solutions were wrong. Well, that was our "smart" moment. In 1995, we realized we were on the wrong path. At the same time, a large number of 3D graphics startups emerged in Silicon Valley because it was the most exciting technology at the time. 3D effects and rendering technology, and Silicon Graphics was on the rise, and Intel had also gotten involved. You know, in the end, we had to compete with up to 100 different startups. Everyone chose the right technical solution, while we chose wrong. So we were the first company to start up.

Jensen Huang 01:26:19

So we were the earliest company to start, and we found ourselves almost at the bottom because we answered incorrectly. The company was in trouble. Ultimately, we had to make several decisions. The first decision was that if we changed now, we would become the last company. Even if we adopted what we thought was the right technology, we would still fail. So the question arose. You know, should we change and be eliminated? Or should we not change, find a way to make this technology work, or simply do something completely different?

Jensen Huang 01:27:13

This question prompted strategic thinking within the company and was a tricky issue that I ultimately supported. We did not know what the correct strategy was, but we knew which technologies were wrong. So, let's stop doing the wrong things and give ourselves a chance to figure out what the right strategy is.

Jensen Huang 01:27:31

The second thing, the second problem we encountered was a shortage of funds for the company, and at that time I had signed a contract with Sega, and I owed them a game console. If the contract was canceled, we would be finished. We would disappear in an instant. Sigh. So I went to Japan and explained the situation to Sega's CEO, Erie Madrid. He was truly an amazing person. He was previously the CEO of American Honda, then returned to Sega to manage the company, and went back to Japan to continue managing Sega. I explained the situation to him; I was about 30 or 33 years old at the time. You know, I still had acne on my face when I was 33, and I was just a young guy from China. I was so thin I looked like skin and bones, and he was already not young. I went home and told him, "Listen, I have bad news for you. First, the technology we promised you is not feasible." Second, we shouldn't fulfill your contract because that would waste all your money, and what you would ultimately get might be a product that doesn't work properly. I suggested that you find another company to produce your game console. So, I sincerely apologize for the delay in your product development plan. Third, even if you agree to terminate the contract, I still need this money. Because if you can't give me the money overnight, I might not be able to continue. I have explained this honestly.

Jensen Huang 01:29:40

I introduced the background to him, explained why the technology was not feasible, and why we initially thought it would succeed, and ultimately why it failed. I asked them what would happen if the last $5 million originally intended to fulfill the contract was converted into an investment? He said that even with my investment, your company is still very likely to go bankrupt. This was completely true. In 1995, $5 million was a huge sum. Even today, $5 million is still a large amount. Moreover, at that time, there were many competitors doing the same thing. If we gave this $5 million to NVIDIA, what were the chances that we would formulate the right strategy, get returns, and even recover costs? You do the math; the probability is zero. If I had been there at the time, I definitely wouldn't have done that. $5 million was also a huge amount for Sega at that time. So I told him that if you invested this $5 million in the U.S., you would likely lose everything. But if you really invested that money, we would go bankrupt, with no chance at all. I told him this. I can't even remember exactly what I said in the end, but I told him that if he decided not to invest, I could understand; but if he invested, I would be very grateful. He thought for two days and came back and said, we will invest.

Joe Rogan 01:31:44

Formulating strategies to correct its previous mistakes.

Jensen Huang 01:31:49

My goodness. Wait until I tell you the rest; it's scarier, really scarier.

Joe Rogan 01:31:54

No.

Jensen Huang 01:31:57

So, so. So he decided that Jensen is a young man he likes. That's it.

Joe Rogan 01:32:09

He.

Jensen Huang 01:32:11

Until today.

Joe Rogan 01:32:13

No. I was a kid back then, and you? Oh, but the whole world owes him a favor.

Jensen Huang 01:32:18

No doubt, right? Just like he is celebrating in Japan today. If he had kept that $5 million investment back then, I think it would be worth about $1 trillion now. I know, but the moment we went public, they sold the stock. They said, wow, this is a miracle. So they sold it. That's right, they sold it at a $300 million valuation for NVIDIA. That was our valuation at the IPO, $300 million. In short, I am very grateful.

Jensen Huang 01:33:00

Then, we had to find a way because our previous strategies and technologies were wrong. So unfortunately, we had to lay off most of the employees in the company. We significantly downsized the company. All the people involved in the development of game consoles, you know, we had to drastically reduce the scale. Then someone told me, "Jensen, we’ve never done it this way before. We’ve never done it the right way. We only know how to do it the wrong way." So no one in the company knew how to make a supercomputer graphics generator 3D graphics system like Silicon Graphics.

So I said, "Well, how hard can it be? There are 30 or even 50 companies doing it, how hard can it be?" Fortunately, Silicon Graphics had written a textbook. So I went to the bookstore. I had $200 in my pocket and bought three textbooks. They only had these three in the store, each for $60. I bought all three. I brought the books back and gave each architect a copy. I said, read this book, and let’s save the company together. So they read this textbook and learned how to make 3D graphics from the then giant Silicon Graphics. But what’s truly amazing, and what makes NVIDIA unique today, is that the people here can start from first principles, learn the most mature technologies, and reimplement them in an unprecedented way. So when we reimagined 3D graphics technology, we reimagined it in a way that ultimately presented modern 3D graphics. We really invented modern 3D graphics, but we drew from the experience of past mature technologies and implemented it in a completely different way. What did you do? They changed it.

Jensen Huang 01:35:18

Well, you know, at the end of the day, my answer is simple: the geometry engine of Silicon Graphics is a bunch of software running on processors. We extracted it, stripped away all the generality, streamlined it to the core of 3D graphics, and hard-coded it into the chip Therefore, we no longer use general-purpose software, but instead hard-code it into specific application scenarios and functions that are limited to video games. This capability is very powerful, and because we have reinvented many things, its performance has been greatly enhanced. Our small chip can generate images as quickly as a million-dollar image generator, which is a significant breakthrough. We have integrated million-dollar equipment into the graphics card installed in your gaming computer, and that is our great invention.

Jensen Huang 01:36:36

Of course, the next question is: how to compete with the other 30 companies doing the same thing? To this end, we have taken several measures. First, we did not develop a 3D graphics chip for every 3D graphics application, but decided to develop a 3D graphics chip for only one application, betting everything on video games. The demand for video games is completely different from the demand for CAD, flight simulators, and other applications. They are related, but not the same. Therefore, we narrowed the scope of the problem, excluded all other complex factors, focused on this one aspect, and then strengthened it based on the needs of gamers. Secondly, we rebuilt a complete ecosystem, collaborating with game developers to port and adapt their games to our chips, thus transforming our original technology business into a platform business, especially a gaming platform business. So, today's G Force is also the most advanced 3D graphics technology in the world. But long ago, G Force was actually the game console in your computer. It ran the Windows system, ran Excel, ran PowerPoint. Of course, these are very simple functions. But its fundamental purpose was to turn your computer into a game console. So we were the first technology company to create all these powerful technologies to serve the same user group—gamers.

Jensen Huang 01:38:19

Of course, in 1993, the gaming industry did not exist. However, with the emergence of John Carmack and the phenomenon of "Doom," followed by the release of "Quake," as you know, the entire gaming world and community flourished.

Joe Rogan 01:38:38

Do you know the origin of the name "Doom"? It comes from a scene in the movie "The Color of Money." Tom Cruise plays a top pool player who goes to a pool hall, and a local hustler tells him what’s in his case. Then he opens the case. He has a special pool cue, walks in, and opens the case. He walks away.

Jensen Huang 01:38:56

Doom, doom.

Joe Rogan 01:38:58

That's right, Kate. Is that so? Because Carmack said they wanted to do something for the gaming industry. When "Doom" came out, everyone would say, oh, we... wow, this is "Doom." Amazing. And then it felt magical because the name was so fitting for the game That's right, the name comes from that scene in the movie. That's right.

Jensen Huang 01:39:16

Of course, after that, Tim Sweeney, Epic Games, and the 3D gaming genre flourished.

Joe Rogan 01:39:24

Yes.

Jensen Huang 01:39:25

So, in the beginning, there was no gaming industry at all, and we had no choice but to focus the company on one thing, which was gaming.

Joe Rogan 01:39:35

That's truly an incredible origin story. It's amazing, you must feel the same way.

Jensen Huang 01:39:40

Entrepreneurship is a disaster.

Joe Rogan 01:39:42

That conversation with that gentleman changed everything, worth millions of dollars. If he disagreed, if he didn't like you, what would the world look like today? That's how it is.

Jensen Huang 01:39:52

Wait, then the fate of our entire company was tied to another gentleman. So now we are where we are today. We built... before G Force came out, the Riva 128 saved the company. It completely revolutionized computer graphics technology. The performance, cost, and cost-effectiveness of 3D game graphics reached astonishing levels. We were about to deliver it, achieving the goals we were building. But, you know, $5 million would run out quickly. So every month we were drawing on those funds.

Jensen Huang 01:40:39

You have to build it first, prototype it, design it, prototype it again, and then bring the chips (which costs a lot of money) back and test them with software. Because if you don't test the chips with software, you won't know if the chips are working properly. And you will likely find bugs. Because every test finds bugs, which means you have to re-tape out, which costs even more time and money. So we calculated that there was no way anyone could survive this. We didn't have enough time to tape out the chips, send them to TSMC for manufacturing, get the chips back, test them, and then send them back. No chance at all, no hope at all. So, according to the calculations, the spreadsheet showed we couldn't do it this way.

Jensen Huang 01:41:32

Then I heard about this company that made a machine, a simulator. You could put your design, including all the software that describes the chip, into this machine, and it could simulate our chip, so I wouldn't have to send it to the foundry. Before the foundry sent back the test samples, I could have this machine simulate our chip, then put all the software on this simulator, test all the software on this simulated chip, and solve all the problems before sending it to the foundry. If I could do that, then it should work fine after being sent to the foundry. Although no one could be sure, theoretically it should work. So we finally decided to take half of the remaining money in our bank account. At that time, there was about $1 million Take half of it to buy this machine. So, I didn't keep the money to maintain the company's operations, but took half of it to buy this machine.

Jensen Huang 01:42:47

I called this company called Icus. I called and said, hey, listen, I've heard about this machine, and I want to buy one. They said, that's great, but unfortunately, we've already gone out of business.

Jensen Huang 01:43:04

I said, what? You went out of business? He said, yes, we went out of business. No customers left. I said, wait a minute. So you didn't actually make that machine at all? They might say, no, we made the machine. If you want it, we have one in stock, but we have already gone out of business. So I bought one from the inventory. Okay. After I bought it, they went out of business. I bought it from the inventory. On this machine, we installed NVIDIA's chips and tested all the related software. At that time, we were exhausted, but we firmly believed that the chip would be great. So I contacted others. I called TSMC and told them that TSMC is now the world's largest chip manufacturer. And at that time, we were just a small company with only a few hundred million dollars. I explained to them what we were doing. I told them I had many customers. I had previously worked with a company, you know, called Diamond Multimedia, which might be one of the companies you bought graphics cards from. I said we have many customers and a huge demand, so we plan to send the chip wafers over first. I like to jump straight into production because I know it works. They said no one had ever done that before. No one had ever successfully produced chip wafers all at once, and no one would start production without having seen the chips. But I knew that if I didn't start production, my company would go out of business. If I could start production, there might be a glimmer of hope. So TSMC decided to support me.

Jensen Huang 01:45:14

This gentleman's name is Morris Chang. Morris Chang is the father of foundry and the founder of TSMC. He is truly an amazing person. He decided to support our company. I explained everything to him in detail. He decided to support us. To be honest, it was probably because they didn't have that many other customers at the time either. But they were grateful, and I was incredibly grateful.

Jensen Huang 01:45:42

When we started production, Morris Chang flew to the United States, and he asked a lot of... he asked me a lot of questions, trying to probe whether I had money. But he didn't ask directly. You know, the fact is we didn't have that much money, but we had a strong purchase order from a customer. If it didn't work, some wafers would be lost. I, you know, I wasn't sure what would happen, but we would be short and it would be tough. But they took all those risks to support us.

Jensen Huang 01:46:28

The chip we launched turned out to be revolutionary and became an instant success. We became the fastest-growing tech company in history from zero to one billion dollars

Joe Rogan 01:46:44

A billion is so crazy. He didn't even test the chip.

Jensen Huang 01:46:47

I know, right? We tested it later. Yes, we tested it later.

Joe Rogan 01:46:50

And then.

Jensen Huang 01:46:53

By the way, the methodology we developed to save the company is now applied worldwide.

Joe Rogan 01:47:02

That's incredible.

Jensen Huang 01:47:04

We changed the methodology of chip design around the world, changed the pace of chip design globally, we changed everything.

Joe Rogan 01:47:13

How did you do?

Jensen Huang 01:47:14

Did you sleep during those days?

Joe Rogan 01:47:15

You know, it must have been very stressful during that time.

Jensen Huang 01:47:24

What was that like? We, we felt like the world was flying. You have a feeling, how to describe that feeling? You can't stop that feeling, everything feels like it's moving at lightning speed. You know, you're lying in bed, and it feels like the whole world is, you know, like you, you feel deep anxiety, completely out of control. I've probably had that feeling a few times in my life. It was during that time. It was incredible. What?

Joe Rogan 01:48:05

Unbelievable.

Jensen Huang 01:48:05

We succeeded. But I learned a lot. I learned a lot. I learned how to strategize. I learned how, you know, when our company... I learned how to strategize, what a winning strategy is.

Jensen Huang 01:48:22

We learned how to create markets. We created the modern 3D gaming market. We learned how to create markets, and the skills used to create the modern artificial intelligence market are exactly the same. That's right, it's the exact same skills, the exact same patterns.

Jensen Huang 01:48:42

We learned how to deal with crises, how to stay calm, how to think systematically. We learned how to eliminate all waste within the company, starting from fundamental principles, only doing what truly matters. Everything else is waste because we didn't have the funds to keep it in a half-dead state.

Jensen Huang 01:49:09

That feeling is no different from how I felt when I woke up this morning, just that you're about to go bankrupt, you know, that saying "30 days until bankruptcy," I've been using it for 33 years. But you still have that feeling. It's like that every morning. But.

Joe Rogan 01:49:28

You are one of the largest companies on Earth.

Jensen Huang 01:49:31

But that feeling has never changed. That sense of fragility, that sense of uncertainty, that sense of insecurity, lingers. That's just how it is.

Joe Rogan 01:49:44

Crazy. We.

Jensen Huang 01:49:45

You know, we had nothing at that time.

Joe Rogan 01:49:52

Do you think that's your motivation? Is one of the reasons for the company's success your insatiable, never-satisfied, never-complacent spirit? You always maintain a high level of competitiveness.

Jensen Huang 01:50:12

My greater drive comes from not wanting to fail, rather than wanting to succeed. Isn't that right…

Joe Rogan 01:50:25

I think coaches, I'm telling you, that's it.

Jensen Huang 01:50:28

Joe, the whole world just heard me say this out loud for the first time, but it's true.

Joe Rogan 01:50:35

Hmm, that's fear…

Jensen Huang 01:50:36

The fear of failure drives me more than greed or anything else.

Joe Rogan 01:50:43

Think about it, that might be a healthier approach because, like…

Jensen Huang 01:50:49

Fear doesn't bring ambition. For example, you know, Joe, I just want to survive. I want the company to thrive. You know, I hope we can make a difference. That's just how it is.

Joe Rogan 01:50:59

Interesting. Hmm, maybe that's why you're so humble. Maybe it's this that keeps you grounded, you know, because with such brilliant success, it's easy to become arrogant. That's right. But isn't it interesting? It's like, if you're the kind of person who only focuses on success, you might think, well, I've succeeded, I've done it. And then you would retire. But when you wake up, you think, oh, we can't just stop here. That's right, exactly.

Jensen Huang 01:51:30

Every morning, not every moment. Yes, that's just how it is.

Joe Rogan 01:51:32

I do these things before I sleep. Listen, if I were the main investor in your company, I would want someone else to run it. I wouldn't want that kind of person to manage the company. I swear, I would fight.

Jensen Huang 01:51:42

That's my job. That's why I work every moment I'm awake, seven days a week.

Joe Rogan 01:51:47

You work. Every day.

Jensen Huang 01:51:49

The moment I wake up, I'm thinking about how to solve a problem. I'm thinking, how long can you hold on? I don't know, but maybe I can do it next week

Joe Rogan 01:52:00

It's exhausting, it sounds completely exhausting.

Jensen Huang 01:52:04

Always in a state of anxiety. Yeah, always in a state of anxiety. Well.

Joe Rogan 01:52:10

It's great that you can admit that. I think it's important for a lot of people because, you know, there are probably a lot of young people who are in a situation similar to when you first started, and they feel like those successful people are smarter than they are and have more opportunities. They feel like success is just a pie falling from the sky or just happening to be in the right place at the right time.

Jensen Huang 01:52:35

Joe, what I just described to you is someone who originally didn't know what was happening but actually does.

Joe Rogan 01:52:40

That's wrong.

Jensen Huang 01:52:42

And can make two or three amazing diving catches.

Joe Rogan 01:52:45

That's crazy. Right, "ultimate diving catch" is the perfect description. You know, it's like the limits of your body.

Jensen Huang 01:52:51

It probably bounced off someone's helmet and then landed on the deceased.

Joe Rogan 01:53:02

That's incredible. But at the same time, your perspective on the issue is great. Because you know, a lot of people have delusions of grandeur, they really do.

Jensen Huang 01:53:14

You know, the way they rewrite history often makes them seem extraordinary, exceptionally smart. They are geniuses, they knew everything long ago, and their judgments were completely correct. The business plans also perfectly matched their vision. Right, they destroyed their competitors and ultimately triumphed.

Joe Rogan 01:53:39

Meanwhile, you say, I'm scared every day. Right. It's so funny. My God. It's incredible. But it is true. It's incredible. It really is. Yes.

Jensen Huang 01:53:50

It's incredible, but I think as a leader, showing a vulnerable side is not contradictory. You know, the company doesn't need me to be a genius, right? It has always been that way, right? It has always been that way. The company doesn't need me to be absolutely confident in what I do and my goals. The company doesn't need that. The company wants me to succeed. You know, we talked about President Trump at the beginning today, and I was about to say something. Listen, he is my president. He is our president. We should all think that way. Just because he is President Trump, we all hope he makes mistakes. I think in America, we all have to realize that he is our president. We want him to succeed.

Joe Rogan 01:54:37

Because whoever is president. Right. Yes, that's it

Jensen Huang 01:54:40

That's right. We all want him to succeed. We need to help him succeed because it will help all of us, and we can all succeed. I'm fortunate to work at a company with 40,000 employees who all want me to succeed. They genuinely want me to succeed. I can feel it; every day there are so many people helping me overcome these challenges. They work hard to realize the strategy I articulate, and if there are any mistakes or shortcomings in the strategy, they will tell me so that we can adjust in a timely manner. As leaders, the more candid we are, the more others can point out our shortcomings, like, Jensen, that's not quite right.

Joe Rogan 01:55:29

Right. Do you have that?

Jensen Huang 01:55:29

Given this information, or rather, the more vulnerable we are, the more flexible we can be in response. If we place ourselves beyond the realm of superhuman capability, then adjusting the strategy becomes difficult, right? Because we should always be right. So if you're always right, how can you adjust? Because adjusting requires you to admit mistakes. So I don't mind making mistakes.

Jensen Huang 01:55:54

I just need to ensure that I stay vigilant, but I always think from first principles. Always break things down to first principles, understand why things happen, and continuously reassess. Continuously reassessing is somewhat the cause of ongoing anxiety, you know, because you're always asking yourself, did I make a mistake yesterday? Am I right now? Is the situation the same? Has there been a change? Has that condition... worsened? Just think about it.

Joe Rogan 01:56:23

But that mindset is very suitable for your business because this industry is ever-changing.

Jensen Huang 01:56:29

Time is of the essence, and competition comes from all directions.

Joe Rogan 01:56:32

A lot of things are still up in the air.

Jensen Huang 01:56:36

Who? You have to envision a future with 100 variables; you can't predict all the variables correctly. So you have to take action, you have to contribute.

Joe Rogan 01:56:50

You have to ride the wave. That's a fitting way to put it. You have to ride the wave. You're surfing the wave of technology.

Jensen Huang 01:56:54

And innovation. That's right. You can't predict the wave; you can only respond to the wave in front of you. Why? Of course, skills are important. Oh, by the way, I've been doing this for 33 years; I'm the longest-serving tech CEO in the world.

Joe Rogan 01:57:07

Really? Congratulations! That's amazing!

Jensen Huang 01:57:10

You know, people ask me, first, how to avoid being fired, and I guarantee I won't be fired. Second, how to avoid feeling bored.

Joe Rogan 01:57:22

So, how do you stay passionate?

Jensen Huang 01:57:28

No, to be honest, it’s not always passion. You know, sometimes it’s passion, and sometimes it’s just deep-rooted fear. And then sometimes, you know, there’s a bit of frustration. You know.

Joe Rogan 01:57:41

Anything that keeps you moving forward.

Jensen Huang 01:57:43

Yeah, it’s a mix of emotions. I think, you know, CEOs, we have all kinds of emotions, right? And the emotional swings can be particularly large because you feel like you represent the entire company. I represent everyone at the same time. That feeling will… you know, it will seep into everyone’s emotions. So I have to remember the past, I have to remember the present, I have to remember the future. And, you know, it can’t be without emotions. It’s not just a job. Let’s put it that way.

Joe Rogan 01:58:23

It doesn’t look like it at all. I think, now that the company has achieved tremendous success, one of the more difficult aspects of your current job is predicting the direction and application of technology. So how do you plan for these?

Jensen Huang 01:58:40

Yes, there are many methods, and it requires many conditions. But let me start from the beginning. You have to be surrounded by a group of outstanding people, and NVIDIA is just that right now. If you look at the large tech companies in the world today, most of them are involved in advertising, social media, or content distribution. And their core is actually basic computer science. So, the business of these companies is not about computers themselves, nor is it technology driving the company. NVIDIA is the only large-scale company in the world that is completely focused on technology. We only do R&D, not advertising. Our only way of making a profit is by creating and selling excellent technology. Therefore, to become today’s NVIDIA, the most important thing is that you have gathered the best computer scientists in the world around you. That’s my talent: we’ve created a company culture, an atmosphere that the world’s top computer scientists aspire to join, because they can work on their lifelong passion here, creating future technologies, which is what they pursue. Perhaps they don’t want to serve other companies; they just want to serve technology itself. And we are the largest company of its kind in world history. I know, it’s truly amazing. So, you know, we have unique conditions, we have an excellent culture, we have outstanding talent.

Jensen Huang 02:00:30

So the question now is, how to systematically foresee the future, stay vigilant, and reduce the chances of missing important information or making mistakes, there are many ways to do this. For example, we have strong partnerships. We conduct fundamental research. We have an excellent research lab, one of the largest industrial research labs in the world today. We collaborate with numerous universities and other scientists. We engage in a lot of open collaboration. So I’ve been working with researchers outside the company We have excellent clients, which benefits us immensely. Therefore, I am able to collaborate with Elon Musk and other industry figures, which is also an advantage for me. We are the only pure technology company that can serve all industries, including consumer internet, industrial manufacturing, scientific computing, healthcare, and financial services, all of which are important signals for me. These industries have mathematicians and scientists. Therefore, I now have the most comprehensive radar system that covers all fields. From agriculture to energy to video games, all industries are closely related to us. Thus, we have such advantages: first, we conduct basic research ourselves; second, we collaborate with all excellent researchers and all outstanding companies. This feedback mechanism is very powerful.

Jensen Huang 02:02:20

Finally, users must develop a habit of being highly alert. There is no other easy way to stay alert besides concentrating. I haven't found any way to stay alert without concentrating. So, you know, I might read thousands of emails every day. Of course.

Joe Rogan 02:02:43

How do you have time to do that? I.

Jensen Huang 02:02:44

I woke up very early this morning, got up at four.

Joe Rogan 02:02:47

How many hours do you sleep each day?

Jensen Huang 02:02:50

Six or seven hours.

Joe Rogan 02:02:54

Then you get up at four in the morning and spend a few hours reading emails before starting work. That's right. Yeah. Wow.

Jensen Huang 02:03:00

Every day, without exception, including Thanksgiving and Christmas.

Joe Rogan 02:03:07

Do you usually take vacations?

Jensen Huang 02:03:10

Yes, but my understanding of vacation is being with family. So as long as I am with my family, I am happy. I don't care where.

Joe Rogan 02:03:18

So you either don't work or you work.

Jensen Huang 02:03:21

Less? No, I am very busy with work.

Joe Rogan 02:03:24

Even if it's just traveling. Oh, of course. Still working? Oh, of course.

Jensen Huang 02:03:28

Oh, of course. It's like that every day. But my kids work every day.

Joe Rogan 02:03:33

Ugh. You make me tired just saying that. My kids.

Jensen Huang 02:03:35

Work every day. My two kids work in videos. They work every day. I am very lucky.

Joe Rogan 02:03:43

Yes.

Jensen Huang 02:03:43

It's really tough right now, you know, before it was just me working every day. Now there are three people working with me every day, and they also want to work with me every day. So the workload is very large.

Joe Rogan 02:03:54

Obviously, you've instilled that value in them.

IV. Jensen Huang's Personal Growth Story

Jensen Huang 02:03:58

They work very hard. I mean, no one would believe this. But my parents really worked very hard. I was born with a work ethic, which is the gene for hard work and perseverance.

Joe Rogan 02:04:10

Hey, listen, man, it’s all worth it. What an incredible story. It’s just an amazing entrepreneurial story. Think about the tough beginnings and how many times it was on the brink of collapse, and now to be where it is today, it must feel a bit surreal.

Jensen Huang 02:04:28

Yes, Thailand is a great country. I’m an immigrant. My parents first sent me and my brother here. We are now in Thailand. I was born in Taiwan, but my father worked in Thailand. He was a chemical and instrumentation engineer, a very remarkable engineer. His job was to help build a refinery. So we moved to Thailand and lived in Bangkok. It was around 1973 or 1974. You know, Thailand has coups from time to time, and the military would stage a rebellion, and suddenly one day there would be tanks and soldiers on the streets. My parents felt that it might not be safe for the kids to stay here. So they contacted my uncle. My uncle lived in Tacoma, Washington. We had never met him before. My parents sent us to him.

Joe Rogan 02:05:30

How old were you then?

Jensen Huang 02:05:31

I was almost 9 years old, and my brother was almost 11. We went to Kentucky, USA, and temporarily stayed at my uncle's house while he helped us find a school. My parents were not wealthy, and they had never been to the United States before. My father had been, and I will tell his story later. Later, my uncle found a school that accepted foreign students and had tuition that my parents could afford. This school was located in Onita, Clark County, Kentucky, which is now the center of the Opal crisis, a coal mining area. When I got there, Clark County was the poorest county in the United States, and it still is. We went to that school. It was a great school, Onita Baptist College, located in a small town with only a few hundred people. I remember when we arrived, there were about 600 people, and there weren't even any traffic lights. I think it’s amazing that a school can accommodate 600 people now. It’s a miracle that they did it. Therefore, the mission of this school is to be open to all children who want to come. This basically means that if you are a problem student, if you come from a troubled family, if you, you know, regardless of your background, you are welcome at Onita College, including those international students who want to study here. Do you understand?

Joe Rogan 02:07:44

Did you speak English back then?

Jensen Huang 02:07:46

No... oh, well. So we got there, and my first thought was, oh my god, there are so many cigarette butts on the ground. 100% of the kids smoked. So immediately, you know, this is not a…

Joe Rogan 02:08:10

Normal school. 9 years old…

Jensen Huang 02:08:12

Yes, I was the youngest kid in the school. Well.

Joe Rogan 02:08:14

11-year-olds.

Jensen Huang 02:08:15

My roommate was 17 at the time. Yeah, just turned 17, very muscular. I don’t know where he is now. I know his name, but I just don’t know where he is now. Anyway, that night we got to the dorm, and as soon as I walked in, I noticed there were no drawers, no closet doors, it was like a prison, and there were no locks, so no one could check on me. I walked into my room and saw him, 17 years old, getting ready to sleep, but he was all wrapped up in medical tape. It turned out he had been in a fight, and he had knife wounds all over him, and these wounds were still very fresh. Other students were hurt worse. So, he was my roommate, the toughest guy.

And I was the youngest student in the school. It was a middle school. But they still took me in. Because if I crossed the Kentucky River, went over that swinging bridge, about a mile, there was a middle school on the other side, I could go there, and then I could take a shortcut to that middle school, and then come back and stay in the dorm. So basically, only the dorm of the Baptist College was mine. When I went to another school, my brother also went, and he went to middle school. So we stayed there for a few years. Every kid had chores. My brother's chore was to work on the tobacco farm. You know, they grew tobacco to earn some extra money for the school. It was a bit like a prison. My job was to clean the dorm. I was only 9 years old at the time. I was responsible for cleaning the bathrooms, and in a dorm with 100 boys, I cleaned more bathrooms than anyone else. I really wish everyone could pay a little more attention, you know? Anyway, I was the youngest kid in the school. I have really fond memories of being there, but it was quite a tough little town.

Joe Rogan 02:10:50

Sounds like it.

Jensen Huang 02:10:51

In town. Kids, everyone carried knives, everyone carried knives. Everyone smoked, everyone used Zippo lighters. I smoked for a week. How about you? Yeah, of course. How old were you? I was 9.

Joe Rogan 02:11:04

Did you try smoking when you were 9? Yes, I did.

Jensen Huang 02:11:06

I bought myself a pack of cigarettes. What about others?

Joe Rogan 02:11:09

Are you sick?

Jensen Huang 02:11:10

Well, I'm used to it. You know, I learned to blow smoke rings, you know, to exhale smoke through my nose, you know, to inhale through my nose... there are different methods. At 9 years old.

Joe Rogan 02:11:28

Did you do it just to fit in?

Jensen Huang 02:11:30

Yes, because... everyone was doing it, right? So I did it too, for about two weeks. I would rather spend my money on... you know, spending a quarter a month, or about that time. I would rather use that money to buy popsicles and ice cream. That was at 9 years old, you know? That's right. I chose a better path.

Joe Rogan 02:11:53

That’s it.

Jensen Huang 02:11:53

That was our school. Two years later, my parents came to the United States. We met them in Tacoma, Washington.

Joe Rogan 02:12:01

That's incredible.

Jensen Huang 02:12:03

It was a crazy experience.

Joe Rogan 02:12:05

What a strange, character-shaping experience.

Jensen Huang 02:12:08

Strong kids.

Joe Rogan 02:12:10

From Thailand to one of the poorest places in America, or if not the poorest, then it was where I went when I was 9 years old.

Jensen Huang 02:12:20

Yes, that was my first question.

Joe Rogan 02:12:21

With your brother.

Jensen Huang 02:12:25

Now I'm here. What breaks my heart the most? The only thing that really broke my heart during that experience was probably that we couldn't afford to make international long-distance calls every week. So my parents gave us a tape recorder, an IWA tape recorder, and a tape. Every month, my brother Jeff and I would sit in front of the tape recorder and record what we had done for the whole month. Then we would send the tape, and when my parents received it, they would re-record it and send it back. Can you imagine? For two whole years. Is that tape still around? It recorded our experiences of the two kids going to America for the first time. I remember telling my parents that I joined the swim team, and my roommate was in great shape. So we spent a lot of time in the gym every day. Every night, we had to do a hundred push-ups, a hundred push-ups in the gym every day. I was nine years old, already quite strong, and in good shape. So I joined the soccer team. I also joined the swim team because once you join a team, they take you to competitions, and after the competitions, you can go to a nice restaurant. That nice restaurant was McDonald's. I recorded it. I said, "Mom and Dad, we went to an amazing restaurant today. The whole restaurant was lit up, like a future world. The food was in boxes, and it tasted incredible. Hamburgers. McDonald's is just awesome. Isn't that great? My goodness. Two years of audio recordings. Yes, two years, it was amazing

Joe Rogan 02:14:43

Your way of communicating with your parents is really strange, just recording messages and then they send a copy back to you. And this is the only way you’ve communicated in two years.

Jensen Huang 02:14:54

No, I… my… my parents are actually amazing. They just… they grew up in very poor circumstances. When they came to America, they had almost no money. One of my most unforgettable memories is… when they came, we lived in an… apartment building. They had just… rented some furniture, I think people rent furniture now too, and we were playing around, bumped into the coffee table and broke it. It was made of particle board. We broke it. I still remember my… my mom’s… expression, you know, because they had no money, she didn’t know how to compensate. But anyway, that tells you how hard it was for them to come here. But they… they left everything behind, just with a suitcase and the money in their pockets. They came to America. How old were they? Pursuing the American Dream. They were in their forties. Yes, almost forty. Pursuing the American Dream. That’s the American Dream. I am the first generation of the American Dream. It’s hard not to love this country. It’s hard not to have romantic feelings for this country.

Joe Rogan 02:16:25

That’s a romantic story. That’s an amazing story.

Jensen Huang 02:16:29

My dad found his job just from the newspaper, you know, those job ads, he called around and found a job. What did he do? He was a consulting engineer at an A&A consulting firm, helping people build refineries, paper mills, and factories. That was his job. He was actually very good at factory design, he was an instrumentation engineer. He was excellent at that. So he did that job. My mom worked as a maid, and they did everything they could to raise us.

Joe Rogan 02:17:10

That’s an incredible story. Jensen is really amazing. From your childhood to those thrilling experiences in the video, almost falling down, everything. It’s really incredible, man.

Jensen Huang 02:17:23

A great story, my life is wonderful.

Joe Rogan 02:17:25

You really did it, and it’s a great story for others too.

Jensen Huang 02:17:30

Exactly, you don’t have to go to an Ivy League school to succeed. This country creates opportunities and provides opportunities for all of us. But you have to work hard, you have to strive to succeed here.

Joe Rogan 02:17:46

But as long as you’re willing to work hard, you can succeed, and there’s a lot of luck and many decisions.

Jensen Huang 02:17:54

And the kindness of others, yes.

Joe Rogan 02:17:56

Indeed.

Jensen Huang 02:17:57

Very important. You and I talked about two people who are very important to me, but the list is far from exhaustive. Many people at NVIDIA have helped me, and many of my friends serve on the board. You know, the decisions they make and the opportunities they give me.

Jensen Huang 02:18:16

Just like when we invented this new computing method, because we added something called CUDA to the chip, it caused the company's stock price to plummet. We had a great idea at the time; we added CUDA to the chip, but no one was buying it, and our costs doubled. We are a graphics chip company; we invented the GPU, invented programmable shaders, invented everything in modern computer graphics, and invented real-time ray tracing. That's why the graphics card model upgraded from GTX to RTX. We invented all these things. But every time we invented something, the market didn't appreciate it, and costs skyrocketed. Take CUDA for example; it enabled artificial intelligence, and costs surged even more.

Jensen Huang 02:19:02

That's true, and we really, really believe in it, you know? So, if you believe in that future but don't put in any effort for it, you will regret it for life. So we always, you know, I always tell the team, what do you believe in? Do we really believe it? If you believe in it and don't do well, then it shows that the belief based on first principles is not unfounded, not hearsay, but something we truly believe in. We must, we have an obligation to pursue it. If we are the right people, if this thing is really hard to do but worth doing, and we believe in it, then let's pursue it.

Jensen Huang 02:19:36

Well, we persevered. We launched the product. But no one knew what it was, just like when I launched the DGX1, the audience was silent. When I launched CUDA, the end users were also silent. No customers wanted it. No one asked about it, and no one understood it. And at that time, the video company was still a publicly traded company. Your situation is, for example, between 2000 and 2006. Twenty years ago, in 2005. Our stock price, I remember our valuation dropped from about $12 billion to $2 billion or $3 billion. I messed up the company.

Joe Rogan 02:20:32

What is it now? Yes, higher, very high.

Jensen Huang 02:20:40

It's higher. But it changed the world. Yes, that invention changed the world.

Joe Rogan 02:20:46

That's an incredible story. Really. Thank you.

Jensen Huang 02:20:51

Your story is amazing.

Joe Rogan 02:20:53

My story is not that incredible. My story is more bizarre, you know, much more bizarre. It has both randomness and strangeness.

Jensen Huang 02:21:01

Well, what are the three most important milestones that brought you here?

Joe Rogan 02:21:10

Good question. What was the first step? I think the first step was seeing others do it. The first step was in the early days of podcasting, like in 2009 when I just started podcasting, and I had only been in the industry for a few years. The first person to do a podcast was my good friend Adam Curry, who is known as the father of podcasting; he invented podcasting. Then, I remember Adam Carolla also did a podcast because he had a radio show before. His radio show got canceled, so he decided to move the same show online. This was revolutionary at the time because no one was doing it. After that, I got involved in some morning radio shows, especially the Opie and Anthony show, because it was really interesting. We would do shows with a group of comedians. You know, I would go on the show with three or four people I knew. I looked forward to it every time; that time was really wonderful. I thought to myself, oh my god, I miss the days of podcasting. Podcasting was so much fun. I really wish I could do that again.

Joe Rogan 02:22:10

Or later, I saw Tom Green's setup. Tom Green built a studio in his house, basically turning the whole house into a TV studio. He was doing an online show in his living room. He had servers everywhere, with cables all over the place. He even had to step over cables. I thought, this is 2007, Tom, this is not like it is now; this is incredible, and I thought, you have to find a way to make money off this.

Jensen Huang 02:22:31

I really wish all the viewers could see your setup. It's amazing. I just wanted to let you know that.

Joe Rogan 02:22:37

It's not just that. That's how it all started. I saw others doing it, and then I thought, well, let's give it a try. So, in the initial days, we just used a laptop, a laptop with a camera, and played around, inviting some comedians over. We just chatted and joked around. At first, I did it about once a week. Then it started to be twice a week. Then suddenly, I had been doing it for a whole year. Then another two years. Then I felt, oh, there are a lot of viewers, a lot of listeners, you know? And then I just kept going. That's it. I kept going because I loved doing it.

Jensen Huang 02:23:13

Did you encounter any setbacks?

Joe Rogan 02:23:15

No, never really any setbacks. Really? No. There have definitely been setbacks, or you’ve seen them too.

Jensen Huang 02:23:20

You're just adaptable, or you just

Joe Rogan 02:23:22

No, it's not hard, and it's not exhausting. It's just very interesting..

Jensen Huang 02:23:29

Have you ever been punched in the face?

Joe Rogan 02:23:30

In the face? No, I didn't participate in that show. I really didn't. I'm done. You never will.

Jensen Huang 02:23:34

After doing something so big? Facing backlash?

Joe Rogan 02:23:40

Actually, no. No, it has been growing. It has been evolving, and from the beginning until now, nothing has changed. The key is, I love talking to people. I've always enjoyed chatting with interesting people. I can even feel it.

Jensen Huang 02:23:52

When we just walked in, you were interacting with everyone, not just me.

Joe Rogan 02:23:57

Yeah, it's really cool. People are cool.

Jensen Huang 02:23:59

Yeah, that's cool.

Joe Rogan 02:24:00

You know, being able to have so many conversations with so many interesting people is truly a wonderful gift because it changes the way you see the world, as you can view the world through the perspectives of so many different people, and you get to meet so many different people with different viewpoints, different opinions, different philosophies, and different life stories. You know, having so many conversations with so many great people is an incredibly enriching and educational experience.

Joe Rogan 02:24:32

That's what I started doing all this work for, and it's the only thing I'm doing now. Even now, when I schedule the show, I do it on my phone. I basically browse a long email list of people who want to be on the show or have applied to be on the show. Then, I also refer to another list of people I'm interested in and schedule them. That's it. I think, oh, I want to talk to him. Because…

Jensen Huang 02:24:57

If it weren't for President Trump, my ranking wouldn't have gone up. Absolutely not.

Joe Rogan 02:25:00

I've wanted to talk to you for a long time. I think, you know, what you're doing is very engaging. I mean, how could I not want to talk to you? And today, it turns out my decision was absolutely right.

Jensen Huang 02:25:12

You know, listen, as an immigrant, one day I was still in Oneida Baptist Institute going to school with the students there, and now, NVIDIA has become one of the most influential companies in history. It's truly an incredible experience. It had to be this way. The journey itself is legendary. It makes me feel very humble and fills me with gratitude. It's amazing to work with so many great people.

Joe Rogan 02:25:44

You are very lucky, and you also seem very happy; your life path seems to be 100% on the right track. You know that.

Jensen Huang 02:25:51

You know, everyone says you must really love your job. But it’s not like that every day.

Joe Rogan 02:25:55

That’s not a good thing. You know what I mean? Oh, right. Everything has its beauty. That's right. There are ups and downs. That's just how it is. Life is never always like a dopamine high.

Jensen Huang 02:26:04

We leave this impression here. That’s the impression. I think it’s not healthy. We successful people often give the impression that our work brings us immense joy. I think that is largely true because we are passionate about our work, and that passion is closely related to the fun of the work itself. I think that is largely true, but it distracts people’s attention; in fact, a lot of success comes from real effort.

Joe Rogan 02:26:42

Work, yes.

Jensen Huang 02:26:44

The entrepreneurial journey is filled with long pain, loneliness, confusion, fear, awkwardness, and humiliation; all these feelings we dislike the most are created from scratch. Elon Musk would tell you something similar; inventing is very difficult. And people don’t always believe you. You often feel humiliated and most of the time are not trusted. So people forget part of the success, but I think it has nothing to do with health. I think we should pass on these experiences to let people know that this is just part of the journey of life. Yes.

Joe Rogan 02:27:33

And maintaining inner peace is part of this journey. You will appreciate it very much. When things don’t go well, you will feel immense pain, but when everything goes well, you will cherish it even more. Deeply feel this.

Jensen Huang 02:27:43

Gratitude. Deep pride. Immense pride comes from immense gratitude and also from incredibly beautiful memories.

Joe Rogan 02:27:54

Of course. Jensen, thank you very much for being here. This has been really interesting. I really enjoyed it. Your story is simply incredible and very inspiring. You know, I think this really is the American Dream. It truly is the American Dream. Thank you very much. Thank you. Alright, goodbye everyone