FINK Good morning everyone. It's really nice to be back here in the Congress Hall. Hopefully everybody had a good day yesterday and are enjoying it today. It is my real pleasure to introduce Jensen Huang, who is somebody I admire, He has been a teacher to me on the journey of learning about  technology and AI. It is amazing watching how he led Nvidia. And I don't  often measure myself on  comparisons, but I like this one comparison. So since the Nvidia has been public, which was in 1999, same year as BlackRock - Nvidia's total return for its shareholders has been a compounded 30 37%. Just think about that. What what would that mean to every pension fund if they invested in Nvidia as an IPO? The eamount of successes we have with everybody's retirement. At the same time, uh BlackRock's annualized total return has been 21%. not so bad for a a financial services company but  it certainly pales and  so that  is just a really great indication of Jensen's leadership the positioning of Nvidia and also it is a great statement about what the ai world believes is the future with Nvidia. So, Jensen, congratulations on that journey and I know we have many more years of that journey ahead of us. 

Jensen Thank you. I appreciate that. My only regret was at the IPO,, I wanted to buy my parents something nice and so I sold Nvidia stock at a valuation of $300 million.  I bought them a Mercedes S-Class. It It is the most expensive car in the world!!. They regret it. Do you still have it? Oh, sure. Yeah, they still have it.  

Fink Let me go into the subject matter. But I just want to say  you know the debate on AI is about how it's going to change the world and the global economy. Today I want to talk about how AI can add to the world to the world economy and how AI can increasingly become a foundational technology that everyone in this room can be utilizing, enhancing our lives, enhancing the lives of everyone in the world.And we need to talk about how it's going to reshape productivity, labor, infrastructure across virtually every other sector, but importantly, how it's going to reshape  the world and how can more segments of the world benefit from AI and how can we ensure that we have a broadening of the global economy, not a narrowing of the global economy. And I can't think of another person who has a clearer view on not just what AI is, but the infrastructure around it. The infrastructure that is necessary to build around it. And because so many of the major hyperscalers are utilizers of what Nvidia creates and the whole engagement around the infrastructure around AI, the potential of AI, I think we have a great voice to listen to this afternoon or this morning. So Jensen, once again, thank you. This is his first time here at the World Economic Forum in Davos and I know uh you have a really busy schedule. So it's uh thank you for taking that time.

Jensen-  I appreciate that. 

Fink So let me go right into it. Why do you believe that AI has the potential to be that significant engine of growth and what makes this moment this technology different than past technology cycles?

Jensen  first of all when when you think about AI and you're interacting with AI in all these different ways. Chad gPT of course, using Gemini of course, using anthropic claude of course, --the magical things that  it can do: it's helpful to reason back to the first principles of fundamentally what is happening to the computing stack.

 this is a platform shift. A platform is something where applications are built on top of. And this is a platform shift like the platform shift of PCs.; New applications were developed to run on a new type of computer. A platform shift to the internet. A new type of computing platform hosted all kinds of new applications. A platform shift to mobile cloud. In each and every one of these platform shifts,In each platform shift - computing stack was reinvented and new applications were created. 

So now AI  (deep data mapping) is a new platform shift in the sense that today  when you're using Chat Gpt.  it's important to understand that itself is an application but very importantly new applications will be built on top of chat GPT.  . And so so it's a it's a platform shift in that way BUT is really easy to understand if you realize what it can do that you could never do before. Software in the past was effectively pre-recorded..Humans would type and describe the algorithm or the recipe for the computer to execute. uh it was able to process structured information, meaning you've got to put the name, the address, you know, their account number, uh their age, where they live. You create these structured tables that software would then go and retrieve information from. We call it SEQUEL Queries SQL is the single most important database engine the world had ' ever known. Almost everything ran on SQL before now. Now we have a a computer that can understand unstructured information, meaning it could look at an image and understand it. It could look at text and understand it. It's completely unstructured. .. it could listen to sound and understand it,, understand the meaning of it, understand the structure of it and reason about what to do about it. And so for the first time we now have a computer that is not pre-recorded but it's processed in real time meaning that it's able to take the context of the circumstance whatever the environmental information the contextual information and whatever information you give it. It could reason about what is the meaning of that information and reason about  your intent which could be described in a really unstructured way. Uh, 

 you describe it however you want to describe it. We call this "prompts".  but you can describe it however you like  and to the extent that it can understand your intention, it can perform a task for you. 

5 LAYER AI STACK  Now the other mportant thing about this is that because we're reinventing that entire computing stack the question is what is AI? When you think about AI Models it's really important to understand industrially AI is  essentially a five layer cake. At the bottom is energy. AI because it's processed in real time and it generates intelligence in real time. It needs energy to do so. Energy is the first layer. The second layer is the layer that I live in. It's chips. Chips and computing infrastructure. The next layer above it is the cloud software infrastructure and sovereign investment data cloud services. The layer above that is the AI models. This is where most people think AI is. But don't forget that in order for those models to happen, you have to have all of the layers underneath it. But the most important layer, and this is the layer that's happening right now, the reason why last year was an incredible year, frankly, for AI is that the AI models made so much progress that the layer above it, which is ultimately the layer that we all need to succeed, the application layer above ai. And so this application layer could be in financial services, it could be in healthcare, it could be in manufacturing. This layer on top ultimately is where economic benefit will happen. But the important thing though because this computing platform requires all of the layers underneath it. It has just started  SO everybody's seeing it right now so what's started is the largest infrastructure buildout in human history. We're only a few hundred billion dollars into it.  Larry and I, we get the opportunity to work on many projects together. There are trillions of dollars of infrastructure that needs to be built out. And it's sensible. It's sensible because all of these contexts have to be processed so that the AI so that the models can generate the intelligence necessary to power the applications that ultimately sit on top. And so when you go back and when you reason about it layer by layer by layer and you you realize that the energy sector is now seeing extraordinary growth. the chip sector. TSMC just announced they're going to  build 20 new chip plants. Foxcon working with us and  Wistron and Quanta building 30 new computer plants which then go into these AI factories. So we have chip factories, computer factories and AI factories all being built around the world and memory. And memory right exactly those chip labs. uh Micron has started investing $200 billion in the United States. SKH Highix is doing incredibly. Samsung is doing incredibly. You could see that entire chip layer growing incredibly today. 

And now, of course, we pay a lot of attention to the model layer, but it's really exciting that the layer above them is really doing fantastically. And now, one indicator is where are the VC funding going into? Last year 2025 was one of the largest years in VC funding ever and last year most of the funding went to what is called AI native companies. These are companies in healthcare, the company in robotics and company manufacturing, financial services, all of the large industries in the world. You're seeing huge investments going in to those AI natives because for the first time the models are good enough to build on top of. 

Fink So let's just dive a little further. Obviously everybody I'm sure uses their own chat bot and getting information. So but  you're talking about the dispersion of AI is going to be the key. Let's talk about  more upside ideas related to the dispersion of it in the physical world. You mentioned obviously healthcare is a great example of that but where do you see the transformational opportunities in areas like transportation or science?

Jensen Well,  last year I would say three major things happened in AI in the AI technology  model layer. The first one is that the the models themselves started out  being curious and interesting, but they hallucinated a great deal. And last year  we can all reasonably accept that these models are better grounded. They could do research.:they can reason about circumstances that maybe they weren't trained on. break it down into step-by-step reasoning steps and come up with a plan to and to answer your question to do your research or perform the task. So last year we saw the evolution of language models becoming AI systems that we call agentic ; systems - agentic AI. The second major breakthrough is the breakthrough of open models it was just a year ago Deep Seek changed everything. Ir came out and a lot of people were quite concerned about it. Frankly, Deep Seek was a huge event for most of the industries, most of the companies around the world because it's the world's first open reasoning model since then a whole bunch of open reasoning models have emerged and open models have enabled companies and industries, researchers,, educators,  universities, startups to be able to use these open models to start something and create something that's domain specific or specialized for their needs. The third area that had enormous progress last year was the concept of physical intelligence of physical AI. AI that understands not just language but AI that understands nature and it could be AI that understands the physical world here.  that understand proteins, chemicals,, naturae of physics, for example, fluid dynamics, particle physics, quantum physics, AIs that are now  learning all these different structures and different,  languages, if you will, proteins is essentially a language. And so all of these AIs are now making such enormous progress that these industries ..industrial companies  whether it's you know manufacturing or drug discovery are really making great progress and one of the great indicators is a partnership that we had with Eli Lily hat they realize now that AI has made such extraordinary progress in understanding the structure of proteins and the structure of chemicals.  essentially be able to interact and talk to the proteins like we talked to Chat GBT we're going to see some really great big breakthroughs 

Fink So all these breakthroughs raises concerns about the human element. You and I have had many conversations on this but we need to tell the whole audience there is a huge concern that AI is going to displace jobs. Um and you've been arguing the opposite. Obviously the buildout of AI as you've talked about the biggest infrastructure buildout in history is going to occur which energy is creating jobs industries creating jobs the infrastructure layers creating jobs land power and shell jobs I mean right it's incredible so let's get into that a little more detail so you actually believe we're going to face labor shortages and so how do you see that AI and robotics changing the nature of work rather than eliminating it now there's several different ways that we could think through it. 

Jensen First of all, uh this is the largest infrastructure buildout in human history. That's going to that's going to create a lot of jobs. And it's it's wonderful that that um the jobs are related to uh trade craft. and  we're going to have uh plumbers and electricians and construction and steel workers and network network  uh technicians and uh people who who  install ah the equipment and  all of these jobs we're going to in the United States we're seeing quite a significant boom in this area. salaries have gone up nearly doubled. And so we're talking about six figure salaries for for people who are building uh chip factories or computer factories or AI factories. And we have a great shortage in that and and I'm really delighted to see so so many people in so many countries really recognizing this important area. You know, everybody should be able to make a great living. You don't need to have a PhD in computer science to do so. And so I'm delighted to see that. the second thing to realize and so we theorize about  the automation of tasks and things like that and what is the implication to jobs. I'll just offer some anecdotes. These are real world anecdotes of what has actually happened. 

Remember 10 years ago one of the first first professions that everybody thought was going to get wiped out was radiology. And the reason for that was the first AI that became superhuman in capability was computer vision. And the one of the largest applications of computer v vision is studying scans by radiologists.Well, 10 years later, it is true that AI has now completely permeated and diffused into every aspect of radiology. And it is true that radiologists um use uh AI to study scans. Now it the impact is 100% and the impact is completely real. However, not surprisingly I say not surprisingly if you reason from first principles not surprisingly the number of radiologists have gone up. Is that because a lack of trust oor is that because the human interaction with the with the results of AI exactly is a better outcome? 

Exactly. The reason for that is because a radiologist their job their purpose of their job is to diagnose disease to help patients . That's the purpose of their job. The task of the job includes studying scans. The fact that they're able to study scans now infinitely fast allows them to spend more time with patients diagnosing their disease, interacting with the patients, interacting with other clinicians. Well, surprisingly, also not surprisingly,actually, as a result of that, the number of patients that the hospital can see has gone up because, you know, there a lot of people waiting a long time to get to get their scans done. And so now because the the number of patients have gone up, the revenues of the hospital has gone up, they hire more radiologists. This is the same thing is happening to nurses. We're 5 million nurses short in the United States a result of using AI to do the charting and the transcription of  the patientpatient visits. uh nurses spend half of their time charting and now they could use AI technology in one particular company a bridge their a partner of ours doing incredible work as a result of that the nurses could spend more time visiting patients touch that's right and because you could now see more patients and we're no longer bottlenecked by the number of nurses more patients could get into the hospital sooner as a result hospitals do better they hire more nurses 

And so surprisingly AI is increasing their not surprisingly AI is increasing their productivity. As a result the hospitals are doing better. They want to hire more people. You have too many people waiting too long to get into hospitals. And so these are two perfect examples. Now the easiest way to think about whether what is the impact of AI on a particular job is to understand job what is the purpose of the job and what is the task of the job.

if you if you just put a camera on the two of us and just watched us, you  would probably think the two of us (Huang & Fink) are typists because I spend all of my time typing and so if AI could automate so many so much word prediction and help us type. then we would be out of jobs but obviously that's not our purpose and so the question is what is the purpose of your job in the case of radiologists and nurses is to care for people and that t purpose is enhance hands that made more productive because the task has been ma has automated and so to the extent that you can reason about each one of the people's purpose versus the task I think it's a helpful framework

27:45 fink let's let's move this beyond the developed economies; helping understand how AI is it abroad the world and help the world I read a I an anthropic piece this past weekend that basically said the utilizization of AI most recently is very dominant by the educated society and they're even seeing the educated component of each society being heavily more utilized and they're obviously they're they're using it against their own model caught so it maybe it may have its own biases um so how do we ensure that AI is a transformational technology maybe like what Wi-Fi and 5G was for the emerging world and when you intersect that what does it mean for the emerging world and John how do we broaden the global economy and two you know getting back to the whole job situation with robotics and AI there is going to be some substitution there and there's substitution in the United States already going on we may be creating more plumbers and electricians but we probably need less analysts at financial institutions, lawyers need less anal and you know because they're able to accumulate the data faster. So let's just pivot on to the emerging world for a second in the developing world. How do you see that play out? 

Jensen Well, first of all, um AI is infrastructure and there's not one country in the world I can't imagine that you need to have AI as part of your infrastructure because every country has its electricity, you have your roads, you should have AI  as part of your infrastructure. .you could always import AI um but AI is not so incredibly hard to train these days and because there are so many open models these open models with with uh your your local expertise you should be able to create models uh that are helpful to your own own country and so I I really believe that that every country should get involved to build AI infrastructure build your own AI take advantage of your fundamental natural resources which is your language and culture, develop your AI, continue to refine it, and have your national intelligence be part of your  ecosystem. And so I I think that's number one. And number two, remember AI is super easy to use. It is the is the easiest software to use in history. And that's the reason why it's the fastest growing and fast most rapidly adopted. I mean in just a couple of two three years it's coming up to almost a billion people. Um I think first of all claude is incredible. They've anthropic has made a huge progress huge leap in developing claude.  we use it all over our company ,the coding capability of claude  its reasoning capability it's you know it its ability is just really incredible and and anybody software company really ought to get involved and and use it. on the other hand uh chat GPT is probably the most successful consumer AI in history and its ease of use and its approachability I think everybody should get involved and whether whether it's um somebody in a developing country or you know somebody a student it is very clear that it is essential to learn how to use AI how to direct an AI how to prompt an AI how to manage an AI how to guard rail the AI evaluate the AI. These skills are no different than leading people, managing people, things that you and I do all the time. So, in  the future, instead of biological, you know, carbon based AIS, in the future, we're also going to have um digital versions of AIS, silicon versions of AIS, and and we'll have to manage them. They're just part of our  digital workforce, if you will. And so I I would I would advocate that for the developing countries .. build your infrastructure, get engaged in AI and and and recognize that AI is likely to close the technology divide, right? Because it is so easy to use and so abundant and so accessible. And so, you know, I I'm I'm actually fairly optimistic about the potential of AI to lift  the countries that are that are um uh that are emerging. And fpr many people who haven't had computer science degree, uh all of you can be programmers now, you know, and so in the past we had to learn how to program a computer. Now, you program a computer by saying to the computer, how do I program you? you know, and if I if you don't know how to use an AI, just go up to the AI and say, "I don't know how to use an AI. How do I use an AI?" And it would explain it to you. And you know, you you say, "I like to I'd like to write a program to create my own website. How do I do that?" And it says it would ask you a whole bunch of questions about what kind of website you would like to build and then write you the code. And so it is that easy to use. And that's of course the the incredible, you know, power of AI, which which is exciting. 

Fink Two quick questions, then we're going to run out of time. We're sitting here in Europe. When we were talking about a lot of companies, we mentioned a lot of US companies and Asian companies. Um, talk to us about how AI uh and the success of Europe and the future Europe can intersect and what and how do you see Nvidia play that role here in Europe? 

Jensen Well, I get I have the benefit Nvidia has the benefit of working with every AI company in the world and uh because we're  in the infrastructure layer and we power AI across the board and we power AI that are languages the you know their biology their physics their  world models and related to manufacturing and robotics and and the the thing that's really  exciting for Europe is remember your industrial base is so strong. The  industrial manufacturing base in Europe is incredibly strong. This is your opportunity to now leap past the era of software. United States really led the era of software. AI is software that doesn't need to write software. You don't write AI, you teach AI. And so get get in early now so that you can now fuse your industrial capability, your manufacturing capability with artificial intelligence and that brings you into the world of physical AI or robotics. You know robotics is is a once in a generation opportunity for the for the European nations and whether whether it's you know uh well all of the countries that I visit here uh industrial base is really really strong. Um the other thing to realize is that that so much of of uh the deep sciences are still very very strong here in Europe, right? And the deep sciences now have the benefit of applying artificial intelligence to accelerate your discovery. And so I I um I think that that it's fairly certain that you have to get serious about increasing your energy supply so that you could invest in the infrastructure layer so that you could have a rich ecosystem of artificial intelligence here in Europe. 

Fink So what so what I'm hearing is we're far from an AI bubble. The question is are we investing enough? let's turn the turn it around because there's so many people talking about a bubble but the question is what I'm hearing from you is you know are we investing enough to do what we need to do to broaden the global economy 

Jensen  one good test on the AI bubble is to recognize that Nvidia has now has now millions of NVIDIA GPUs in the cloud  we're in every cloud um you know we're used everywhere and if you try to rent an Nvidia GPU these days it's so incredibly hard And the spot price of GPU rentals is going up. Not just the latest generation, but two generation old GPUs. The spot price of rentals are going up. And the reason for that is because the number of AI companies that are being created, the number of companies shifting their R&D budget. 

Lily is a great example. three years ago, most of their R&D budget, all of their R&D budget was probably wet labs.  notice the big AI supercomputer that they've invested in the big AI lab. Increasingly that R&D budget is going to shift towards AI and so the AI bubble comes about because the investments are large and  because we have to build the infrastructure necessary for all of the layers of AI above it. And so I I think the opportunity is really quite extraordinary and everybody ought to get involved. Everybody ought to get engaged. Uh we need more energy. I think that we all recognize that we need more land power and shell. Um uh we need more uh trade skill workers and in fact that population of workforce is so strong here in Europe. Yes. In a lot of ways, the United States lost that um in the last, you know,  but it's still incredibly strong here in Europe. It's it's an extraordinary opportunity you got to take advantage of. And so I I would, you know, in I know that where where Larry and I work, uh we uh we see the the investment  opportunities um and the investment uh scale is going up. , number of startups as I mentioned earlier that L2025 the largest investment year in VC history over a hundred billion dollars around the world -most of it was AI natives and so these AI companies are building basically the application layer above they're going to um you know and go build this future and I actually believe it's going to be a great investment for pension funds around the world to to be a part that to grow with this AI world. And this is one of my messages as so many political leaders. We need to make sure that the average pensioner, the average saver is is a part of that growth. If they're just watching it from the sidelines, you know, they're they're going to feel left out. And we want to invest in infrastructure, right? In infrastructure is a great investment option. This is the single largest infrastructure buildout in human history. Get involved.

FINK  We're out of time. Hopefully everybody in the audience and everybody on the web streaming seeing the the power of Jensen Wong as a leader not just a leader in technology and AI but a leader uh in business and also a leader in in heart and soul which is really important today having that leadership from the heart and the soul. So thank you everyone.