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please welcome Nvidia founder and CEO Jensen [Music] [Applause] hang hello [Applause] mumai wow it's so great to be here I just realized I forgot something I actually did it's on where is it where is it what uh this is what happens when you don't rehearse up don't go anywhere uh hello anybody back here I bet this has when you have it could you bring it out to me I bet this has never happened before oh thank you ladies and gentlemen [Applause] McKenzie Mumbai so much happening so much happening this is as you know India very

very dear to the world's computer industry Central to the IT industry at the center at the core of the it of just about every single company in the world my industry your industry that we've built over the last several decades is going through fundamental change seismic change tectonic shifts let's talk about that today but before we start let me thank all of our partners there are so many of you working with yeah please thank you our incredible partners that we're working with here in India to transform the IT industry together and so I'm delighted that

all of you have joined us today there are two fundamental shifts that are happening at the same time this hasn't happened since 1964 the year after my birth it wasn't because of my birth but in 1964 the IBM system 360 introduced the the world to the concept of it the IT industry as we know it introduced the idea of general purpose Computing they described a central processing unit a CPU IO subsystems multitasking the separation of hardware and application software through a layer called the operating system IBM described family compatibility for application so that you could

benefit by the install base of your Hardware to run your software over a long period of time they described architectural benefit across Generations so that the investment that you make in software the Investments you make in using the software is not squandered every single time you buy new hardware they recognized the 19 1964 the importance of install base the importance of software investment the importance of building computers that run the software architecture discipline all described in 1964 I've just described today's computer industry the same industry that the India IT industry was built from general purpose

Computing as we know it has existed for 60 years until now for the last 30 years we've had the benefit of Mo's law an incredible phenomenon without changing the software the hardware can continue to improve in an architecturally compatible way and the benefits of that software doubles every year as a result of doubling in performance every year depending on what your applications you're reducing your cost by a factor of two every single year the most incredible depreciating force of any technology the world's ever known by depreciation cost reduction it made it possible for society to

use more and more of it as we continue to consume it as we continue to process more data more law made it possible for us to continue to drive down cost democratizing Computing as we know it today those two events the invention of the system 360 Moors law with Windows PC drove what unquestionably one of the most important industries in the world every single industry has subsequently been built on top of it it but we know now that the scaling of CPUs has reached its limit we can't continue to ride that curve that that Free

Ride The Free Ride of Moors law has ended we have to now do something different or depreciation will end and we now will not enjoy depreciation but experience inflation Computing inflation and that's exactly what's happening around the world we no longer can afford to do nothing in software and exper and expect that our Computing experience will continue to improve that cost will continue to decrease and continue to spread the benefits of it and to benefit from solving greater and greater challenges we started our company to accelerate software our vision was there are applications that would

benefit from acceleration if we augmented general purpose Computing we take the workload that is very computer intensive and we offload it and we accelerate it using a model we call Cuda a programming model that we invented called cuda that made it possible for us to accelerate applications tremendously that acceleration benefit has the same qualities as Moors law for applications that were impossible or impractical to perform using general purpose Computing we have the benefits of accelerated computing to realize that capability for example computer Graphics realtime computer graphics processor we call gpus the GPU was really the

first accelerated Computing architecture running Cuda running computer Graphics a perfect example we democratized computer Graphics as we know it 3D Graphics is now literally everywhere it could be used as a medium for almost any application but we felt that long term accelerated Computing could be far far more impactful and so over the last 30 years we've been on a journey to accelerate one domain of application after another the reason why this has taken so long is simply because of this there is no such magical processor that can accelerate everything in the world because if you

could do that you would just call it a CPU you need to reinvent the Computing stack from the algorithms to the architecture underneath and connected to applications on top in one domain after another domain computer Graphics is a beginning but we've taken this architecture Cuda architecture from one industry after another industry after another industry today we accelerate so many important industries ktho is fundamental to semiconductor semiconductor manufacturing comput computational lithography simulation computer Aid and Engineering even 5G radios that we've recently announced Partnerships with that we can accelerate the 5G software stack Quantum Computing so that

we can invent the future of computing with classical Quantum hybrid Computing parabricks our Gene sequencing software stack CVS one of the most important things every single company's working on is going from databases to to knowledge bases so that we can create AI databases UVS we can create and vectorize all of your data qdf data frames data frames is essentially another word for structured data SQL acceleration is possible with qdf in each one of these different libraries we're able to accelerate the application 20 30 50 times of course it takes a rewrite of software which is

the reason why it's taken so long in each one of these domains we've had to work with the industry work with our ecosystem software developers and customers in order to accelerate those applications for their domains kopt one of my favorites combinatorial combinatorial Computing application a a very a very uh compute intensive application for example the travel salesperson problem every supply chain every driver Rider combination those applications could be accelerated with Coop incredible speedup modulus teaching and AI the laws of physics not just to be able to predict the next next word but to be able

to predict the next moment in time of fluid dynamics and particle physics and so on so forth and of course one of the most fa famous application libraries we've ever created called CNN made it possible to democratize artificial intelligence as we know it these acceleration libraries Now cover so many different domains that it appears that accelerated Computing is used everywhere but that's simply because we've applied this architecture one domain after another domain that we've covered just about every single industry now accelerated Computing or Cuda has reached the Tipping Point several years ago about a decade

ago something very important happened and most of you have seen the same thing alexnet made a gigantic leap in the performance of computer vision computer vision is a very important field of artificial intelligence alexnet surprised the world with how much of a leap that it was able to produce we had the benefit of taking a step back and asking yourselves what are we witnessing why is alexnet so effective how far can it scale what else can we do with this approach called Deep learning and if we were to find ways to apply deep learning to

other problems how does it affect the computer industry and if we wanted to do that if we believe in that future and we're excited about what deep learning can do how would we change every single layer the Computing stack so that we could reinvent Computing all together 12 years ago we decided to dedicate our entire company to go pursue this Vision it is now 12 years later you every single time I've come to India I've had the benefit of talking to you about deep learning have benefited talking to you about machine learning and I think

it's very very clear now the world has completely changed now let's think about what happened the first thing that happened of course Is How We Do software our industry is underpinned by the method by which software is done the way that software was done call It software 1.0 programmers would code algorithms we call functions into to run on a computer and we would apply it to input information to predict an output this is basically software 1.0 no somebody would write python or C or Fortran or Pascal or C++ code algorithms that run on a computer

you apply input to it and output is produced very classically the computer model that we understood quite well and it of course created one of the largest Industries in the world right here in India the production of software coding programing in became a whole industry this all happened within our generation however that approach of developing software has been disrupted it is now not coding but machine learning using a computer using a computer to study the patterns and relationships of massive amounts of observed data to essentially learn from it the function that predicts it and so

we are essentially designing a universal function approximator using machines to learn the expected output that would produce such a function a function that would produce such an expected output and so going back and forth looking this is software 1.0 with human coding to now software 2.0 using machine learning notice notice who is writing the software the software is now written by the computer and after you're done training the model you inference the model you then apply that function now as the input that function that large language model that deep learning model that computer vision model

speech understanding model is now an input neural network that goes into to the GPU that can now make a prediction given new input unobserved input this way of doing software notice is based on fundamentally machine learning and we have gone from coding to machine learning from developing software to creating artificial intelligence and from software that prefers to run on CPUs to now neural networks that runs best on gpus this at its core is what happened to our industry in the last 10 years we have now seen the complete reinvention of the Computing stack the whole

technology stack has been reinvented the hardware the way that software is able is is developed and what software can do is now fundamentally different we dedicated ourselves to advance this field and so this this is what we now build what all of you have initially when I first met India we were building gpus that fit into a PCI Express card that goes into your PC this is what a GPU looks like today this is Blackwell incredible system that is designed to study data at an enormous scale yeah thank you a massive system designed to study

data at an enormous scale so that we could discover patterns and relationships and learn the meaning of the data this is the Greek breakthrough in the last several years we have now learned the representation or the meaning of words and numbers and images and pixels and videos chemicals proteins amino acids fluid patterns particle physics we have now learned the meaning of so many different types of data we have learned to represent how to represent information in so many different modalities not only have we learned the meaning of it we can translate it to another modality

so one great example of course is translating English to Hindi translating English large body of text into other English summarization from pixels to image image recognition from words to pixels image generation from images videos to words captioning from words to proteins used for drug Discovery from words to chemicals discovering new compounds from amino acids to proteins understanding the structure of proteins these fundamental ideas essentially a universal translator of information from any modality to another modality has led to a Cambrian explosion of the number of startups in the world they're applying the basic method that I

just described if I could do this and that what else can I do if I can do that and this what else can I do the number of applications has clearly exploded in the last couple two three years the number of generative AI companies around the world tens of thousands tens of billions of dollars have been invested in this field all because of this one instrument that made it possible for us to study data at enormous scales well I just want to say that that and so this is basically Blackwell now this is one of

the things that's really incredible about the system let me show it to you nothing's easy this morning this is MV link and it goes across the entire back spine of a rack of gpus and these gpus are all connected from the top to the bottom using MV link driving these incredible CIS the world's longest driving CES for copper and it connects uh all of these gpus together 72 dual GPU packages of black WS 144 gpus connected together so it's one giant GPU if I were to spread out all of the chips to show you what

this connects together it's essentially a GPU so large it be like this big but it's obviously impossible to build gpus that large so we break it up into the LGE the smallest chunks we could which is retical limits and the most Advanced Technologies and we connect it together using MV link and so this is mvlink backs spine you're looking at all of the gpus being connected that's the quantum switch that connects all of these gpus together on top Spectrum X if you would like to have ethernet and uh uh in what connect next this together

this is like 50 lb this I'm just demonstrating how strong I am this is connected to this switch and this is one of the most advanced switches the world's ever built now all of this together represents Blackwell and then it runs the software uh that's on top the Cuda software CNN software uh Megatron for the large language models tensor RT for doing the inference tensor RT llm for doing uh distributed multi-gpu inference for large language models and then on top of that we have two software Stacks one is NVIDIA ai ai Enterprise that I'll talk

about in a second and then the other uh is Omniverse I'll talk about both of those in a second this job is surprisingly rigorous so this is the Blackwell system this is what Nvidia builds today and uh for for uh those of you who have known us for a very long time uh it's it's really quite surprising how the company has transformed um but literally we reason from first principles we reason from first principles how Computing was going to be done in the future and and this is this is Blackwell now the Blackwell system the

Blackwell system is extraordinary of course the computation is incredible each rack is 3,000 lb 120 kilow 120,000 watts in each rack the density of computing the highest the world's ever known and what we're trying to do is to learn larger and smarter models it's called a scaling law the scaling law comes from the fact that the observation that the empirical observation and measurements that suggests the more data you have to train a large language model with and therefore the correspondingly large model size you know the more information you want to learn from the larger the

model has to be or the larger model you would like to train the more data you need to have and each one each year we're increasing the amount of data and amount of the model size each by about a factor of two which means that every single year the computation which is the product of those two has to increase by a factor of four now remember there was a time when the world Moors law was two times every year and a half or 10 times every five years 100 times every 10 years we are now

moving technology at a rate of four times every year four times every year over the course of 10 years incredible scaling and we continue to find that AI continues to get smarter as we scale up uh scale up the uh uh the training size the second thing that we've discovered recently and this is a very big deal after you're done training the model of course course uh all of you have used chat GPT when you use chat GPT is a oneshot you ask you give it a prompt instead of writing a program to Compu communicate

with a computer today you write a prompt you just talk to the talk to the computer the way you talk to a person you describe the context you describe what it is you're you're querying about uh you could ask it to write a program for you you could you know ask it to write a recipe for you whatever question you would like to have and the AI process through a very large neural network and produces a sequence of answers producing one one uh one word after another word in the future and starting with strawberry we

realize that of course intelligence is not just one shot but intelligence requires thinking and thinking is reasoning and maybe you're doing path planning and maybe you're doing some simulations in your mind you're reflecting on your own answers and so as a result thinking results in higher quality answers and we've now discovered a second scaling law and this is a SCA scaling law at a time of inference the longer you think the higher quality answer you can produce this is not illogical this is very very intuitive to all of us there are some problems for example

you know uh what's what's my favorite if you were to ask me what's my favorite Indian food I would tell you chicken briani okay and I don't have to think about that very much and I don't have to reason about that I just know it and there are many things that you can ask it like for example what's Nvidia good at it was we Nvidia is good at building AI supercomputers nvidia's great at building gpus and those are things that you know that it's encoded into your knowledge however there are many things that requires reasoning

you know for example if I had to travel from uh Mumbai to California and uh I I want to do it in the in a way that allows me to enjoy four other cities along the way you know today I got here at 3:00 a.m. this morning and um I got here through Denmark I I and right before Denmark I was in Orlando Florida and before Orlando Florida I was in California okay and so uh that was two days ago and I'm still trying to figure out what day we're in right now but anyways I'm

happy to be here uh if I were to to tell it uh uh uh I would like to go from California uh to Mumbai and uh uh I would like to do it within uh 3 days uh and I give it all kinds of constraints about what time I'm willing to leave and able to leave what hotels I like to stay at so on so forth uh the people I have to meet the number of permutations of that of course uh quite high and so the planning of that process planning and coming up with an

optimal plan is very very complicated and so that's where thinking reasoning planning comes in and the more you compute the higher quality answer uh you could provide and so we now have two fundamental scaling laws that is driving our technology development first for training and now for inference and so uh we're going to we're going to deliver black Wells by the Q4 time frame of this year and shipping out to to customers and it's the demand for black Wells is incredible and the reason for that is this the number of foundation model makers factors has

led to the demand for black wellbe incredibly High let's talk about now how we're going to use this technology this is this is um the headline I thought was really good Nvidia is AI in India now aside from the letter V you could use Nvidia to create the rest of that sentence which I thought was really cool now you you thank you you don't know this story but in 1993 we had to come up with a name for our company and the reason why we chose Nvidia I'll do the extreme short version the reason why

I chose Nvidia in the end was because I really love Nvidia being sounds like a mystical place and so if yes India [Applause] Nidia and sounded like a great place and so if it turns out that computer graphics and accelerated Computing didn't work out for us we could do almost anything and so I'm just happy it worked out okay so so Nvidia in in uh Nvidia in in India uh we have we have a really rich ecosystem here uh the first thing that you have to realize is that in order to build an AI ecosystem

in any industry or in any country you have to start first with the ecosystem of the infrastructure and we announced that Yoda that ET T Communications and our other partners uh are joining us to build fundamental Computing infrastructure here in India and in just one year's time by the end of this year we will have nearly 20 times more compute here in India than just a little over a year ago that that's the amount of infrastructure we're y so the first part of building an AI ecosystem is the AI infrastructure just as the first part

of uh infrastructure for for uh uh the internet ecosystem was building the infrastructure of of networking of course uh the infrastructure of networking internet in consists of the personal computer cloud and and internet itself um in the case of AI it starts with the AI Computing infrastructure the next part the operating system of AI is large language models and we've worked with Partners here in India to build the Hindi large language model and Hindi large language model as you know there's 25 different um uh formal languages here in in India with apparently um a new

a dialect every you know 1,500 kilometers and so so you don't have to go very far before you need to train another model and so here here in India if if anybody this is this is the this is the hardest language model region in the world and if anybody could do it you can do it and and once India figures out how to create the Hindi large language model you could you could figure it out for every other country so you know and so the next the next layer is um the application layer above that

and uh working with us to bring uh AI to uh the ecosystem of India of course uh AI native companies that are creating new applications that are started that made possible only with AI and then our uh our Service Partners uh from from wiipro to Infosys to to TCS working with us to take uh uh the AI models and the AI infrastructure out to the world's Enterprises now that's Nvidia in India I'm going to have uh Vel our country leader come join me on stage because I would love for him to talk to you about

some of the companies that we're working with here in India velle Melle tupar okay so I'm going to introduce a couple of other ideas and so earlier I told you earlier I told you that we have Blackwell we have all of the libraries acceleration libraries that we were talking about before but on top there are two very important platforms are working on one of them is called Nvidia AI Enterprise and the other is called Nvidia Omniverse and I'll explain each one of them very Qui quickly first Nvidia AI Enterprise this is a time now where

the large language models and the fundamental AI capabilities have reached a level of capabilities we're able to now create what is called agents large language model models that understand understand the data that of course is being presented it could be it could be streaming data could video data language model data it could be data of all kinds um and the first stage is perception the second is reasoning about given its observations uh what is the mission and what is the task it has to perform in order to perform that task the agent would break down

that task into steps of other tasks and and uh it would reason about what it would take and it would connect with other AI models some of them are uh good at prod for example understanding PDF maybe it's a model that understands how to generate images maybe it's a model that uh uh is able to retrieve information AI information AI semantic data from a uh proprietary database so each one of these uh large language models are connected to the central reasoning large language model we call agent and so these agents are able to perform all

kinds of tasks uh some of them are maybe uh marketing agents some of them are customer service agents some of them are chip design agents Nvidia has Chip design agents all over our company helping us design chips maybe there software engineering uh agents uh maybe uh uh maybe they're able to do uh marketing campaigns uh Supply Chain management and so we're going to have agents that are helping our employees become super employees the these agents these agents or agentic AI models uh augment all of our employees to supercharge them make them more productive now when

you think about these agents it's really the way you would bring these agents into your company it's not unlike the way you would onboard uh someone uh who's a new employee you have to give them training curriculum you have to uh fine-tune them teach them how to use uh how to perform the skills and the understand the vocabulary of your of your company uh you evaluate them and so they're evaluation systems and you might guard rail them uh if you're accounting agent uh don't do marketing if you're a marketing agent you know don't report earnings

at the end of the quarter so on so forth and so each one of these agents are guard railed um that entire process we put into essentially an agent life cycle Suite of libraries and we call that Nemo our partners are working with us to integrate these libraries into their platforms so that they could enable agents to be created onboarded deployed improved into a life cycle of agents and so this is what we call Nvidia Nemo we have um on the one hand the libraries on the other hand what comes out at the output of

it is a API inference microservice we call Nims and so essentially this is a factory that builds AIS and Nemo is a suite of libraries that onboard and help you operate the AIS and ultimately your goal is to create a whole bunch of Agents uh we have Partners here that we're working with in India and velle if you could tell everybody about our ecosystem here absolutely Jensen you know the word that stuck me as I was standing behind was a word called Mystique this is the Mystique of India Jensen was here exactly 12 months back

and he asked me a pretty profound question that the rich tapestry of India how are you going to encode it and it All Began from the infrastructure as mentioned in just 12 months today we have Computing from Yota which has built the state of the art infrastructure tatas are going live E2 e2e has been in existence giving us exceled Computing infrastructure for a long long period of time all this Computing helped us to leave frog to solve one of India's largest problem that is about communication like Jensen said we speak in so many languages he

did say 1,500 km but all of you know every 50 kilom we change our dialect we don't only speak English we speak English and if you are from South there'll be a little bit of malali also added into it so how do we make this really work is the work of some of our partners seram is a classical example servum basically started their efforts to basically help India talk they decided we're going to do voice to voice and while doing voice to voice they had to understand how does this language work which is multimodal how

do we make sure that it performs and they came into existence pretty quickly because there was infrastructure that was available to us similarly we saw projects coming from bat GPT again a work that has been done predominantly in Academia the Academia in India has been rich with ideas and every time they wanted an idea here to be translated into reality they need infrastructure today the work that we are doing in iits the work that we are doing at different organization is all a result of coming together solving the critical issue that India Has Not only

was the language getting solved we also realized very quickly that there are many mega challenges that India has and one of the it's almost lunchtime yes but take take your time okay just one more thing okay yeah just just one more thing health no one loves India more than Michelle a Wells spoken Indian and a healthy Indian always make a difference and that's why we have companies who've been working on health as many of us know it's been challenging how do we look after our health but Diagnostics coming from s Tuple cure. is really helping

us solve many of these challenges so with that promise Jensen that's awesome healthy yep and well spoken healthy and well spoken and the the important thing here that the uh it takes an entire ecosystem of Partners to be able to help the world apply AI to help their employees be more productive and this is where whereas India was focused on it the back office operations of software the delivery of software the delivery of software producing software the next generation of it is going to be about producing and delivery of AI and as you know the

delivery of software coding and the delivery of AI is fundamentally different but drama atically more impactful insanely more exciting and the ability for this industry for India to help every single company around the world to enjoy the benefit of agents to enjoy the benefits of AIS across all of their different functionalities and to be to be able to deploy it at scale I don't know anybody else who could do it this is just an extraordinary opportun our job our job is to help you build Ai and deploy AI to build Ai and deploy AI your

job is to take these libraries and the capabilities that we have combine it with your incredible it capabilities software capabilities so that we can create agents and help every single company benefit from it and so this is the first part the second part is this what happens after agents now remember every single company has employees but most companies the goal is to build something to produce something to make something and that those things that people make could be factories it could be warehouses it could be cars and planes and trains and uh ships and so

on and so forth all kinds of things computers and servers the servers that Nvidia builds it could be phones most companies in the largest of Industries ultimately produces something it's sometimes produ production of service which is the IT industry but many of your customers are about producing something those that next generation of AI needs to understand the physical world we call it physical AI in order to create physical AI we need three computers and we created three computers to do so the dgx computer which this AI super Blackwell for example is is a reference design

an architecture for to create things like dgx computers for training the model that model needs a place to be refined it needs a place to learn and needs the place to apply its physical capability its robotics capability we call that Omniverse a virtual world that obeys the laws of physics where robots can learn to be robots and then when you're done with the training of it that AI model could then run in the actual robotic system that robotic system could be a car it could be a robot it could be AV it could be a

autonomous moving robot it could be a a picking arm uh it could be an entire Factory or an entire Warehouse that's robotic that computer we call agx Jetson agx dgx for training and then Omniverse for doing the digital twin now here here in India we've got a really great ecosystem who is working with us to take this infrastructure take this ecosystem of capabilities to help the world build physical AI systems and you know what I've really loved is adverb is one of the largest robotics company they build Robotics and more importantly they put it in

add twin where optimization takes place they teach the robo all the inputs that comes out of the physical world not only is that work taking place our system integrators asenta TCS Tech Mahindra are taking that knowledge not only into India but also outside India so do it in India for India and do from India for globe start locally grow globally right right that's fantastic okay thank you thank you thank you very much Michelle thank you thank you we made a short video to help you put everything together that I just said run it please for

60 years software 1.0 code written by programmers ran on general purpose CPUs then software 2.0 arrived machine learning neural networks running on gpus this led to the Big Bang of generative AI models that learn and generate anything today generative AI is revolutionizing 100 trillion dollar in Industries knowledge Enterprises use agentic AI to automate digital work hello I'm James a digital human Industrial Enterprises use capable of monitoring and adjusting its operations or speaking to us Nvidia builds three computers to enable developers to create physical AI the models are first trained on dgx then the AI is

fine-tuned and tested using reinforcement learning physics feedback in Omniverse and the trained AI runs on Nvidia Jetson agx robotics computers Nvidia Omniverse is a physics-based operating system for physical AI simulation robots learn and fine-tune their skills in Isaac lab a robot gym built on Omniverse this is just one robot future factories will orchestrate teams of robots and monitor entire operations through thousands of sensors for factory digital twins they use an Omniverse blueprint called Mega with mega the factory digital twin is populated with virtual robots and their AI models the robots brains the robots execute a

task by perceiving their environment reasoning planning their next motion and finally converting it to actions these actions are simulated in the environment by the world simulator in Omniverse and the results are perceived by the robot brains through Omniverse sensor simulation based on the sensor simulations the robot brains decide the next action and the loop continues while Mega precisely tracks the state and position of everything in the factory digital twin this software in the loop testing brings software defined processes to physical spaces and embodiments letting Industrial Enterprises simulate and validate changes in an Omniverse digital twin

before deploying to the physical world saving massive risk and cost the era of physical AI is here transforming the world's heavy Industries and Robotics [Applause] before I wrap up uh I I want to introduce you to somebody I met today and uh there's a superstar in the audience and and I I think I think all of you would love uh to know who's also interested in technology and artificial intelligence aay Kumar [Applause] AE and I have many things in common for example both of us have been doing our jobs for over three decades uh one

of us is a marshal artist and one of us has 80 million followers hello everyone thank you very unbelievable I especially told you not to call me this word I especially told you I know he did he did he did but I think there was super I know who was my father-in-law Mr rajes he he he absolutely insisted I do not say that he is so humble but can we all agree he's a superstar so so you and I we started our careers around the same time yeah we started now you've achieved you've achieved a

level of artistry that that um I'm still trying to You're So the two of us I started I started when I was 29 years old Nvidia I don't mean you and I have something in common we both started from Thailand Thailand that's right we both grew up in Thailand in Bangkok and we were just speaking Tai he he went to Thailand he went to Thailand to learn how to be a martial artist I went to Thailand just to grow up but well I had no other choice I mean said that was one place which was

cheap enough to for me to go there and my parents couldn't afford it so that was the place I went there I wanted to learn and it's so happened that uh that today martial art has helped me where I am I call myself a stunt man first and an actor later so so tell tell me uh both of us we've been doing really the same job for about 30 years all right and and constantly same job literally exactly the same job okay and and constantly striving uh to to uh heighten Elevate our Artistry Elevate our

craft uh constantly uh striving to be better and so so when you look back on your career what are some of the things that that you would say are really fundamental to you being here today and really helped you achieve what you've achieved what has been there to what I have achieved in life and what are the fundamental things that you w yeah how what are the what are your characteristics what are you think some of the core values or um you know your nature that has I think the one of the biggest thing has

been self-discipline MH and that's always been there which has helped me throughout it's been like 34 years now in this industry this industry has given me a lot and it's um one thing is important for me is self-discipline which uh which has got me where I am today so that's the main part which is this and and I always believe and I always say to people that uh guys make your children get into martial lot discipline them up it is the one of the best thing and a very very very important thing your children are

also in that's right both of my children are second degree black belts here we go yeah that's perfect it's the most important thing that that's that's what it has been there it gives it gives them uh it gives them something to be good at yep something they could be proud of uh when you're good at anything when you're good at anything uh it gives you confidence to do everything else and of course martial arts uh it teaches you discipline but the other thing that that you have an abundance of is humility you're just incredibly humble

and uh martial arts also teaches you that it it teaches you it teaches you a lot of that it teaches you gives you a good confidence and um it uh I would I would like to know something from you um you're probably wondering you're probably wondering how I stay so disciplined I'm just saying you are have you noticed have you noticed we're both martial artists you are you you have done a great job of yourself you're 61 [Laughter] that's what that's that's what the record shows then what is the that is what the AI shows

that's what the record shows I'm I I think I'm crawling up on 62 but yeah okay so I think you have maintained your you're what 42 uh no [Applause] 37 okay and the two of us been doing the job for 30 years each that's true he started when he was seven I started when I was 29 well you know um ah my Hindi film industry has never made a film on AI and like we have Robo [Laughter] Bindi all all I know is actually actually says you you Jensen you have to watch my last movie

it's about super cops I no it's going to release now yeah oh yeah it's going to release now it's I can't tell you about it it's a secret he told me about it it's about super cops okay I I must say I must admit that you keep the secret very well well um what I want to know is what is one thing which um AI can't copy from humans which I would like to know that what kind of a thing would it be that um humans can do but AI can't yeah and actually it's an

excellent question and in fact this is this is probably the single most vital question for now right which is what what are all the things that AI can do what can it do it turns out that as we speak AI has no possibility of doing all of what we do however depending on the jobs that we do sometimes it could do 20% of our jobs 20% of our work a thousand times better for some people it might be able to do 50% of their job a thousand times better but in no job can they do

all of it and so this is the this is the great observation because of that every one of us should apply AI to automate to become an assistant to help us with that either 20% 40% or 50% people ask me you know Jensen is AI going to take your job and I tell them absolutely not the person who uses AI to automate that 20% or 50% is going to take your job and so the that's right that's right and so the most important thing the most important thing for us right now is the build e

e a eyes to watch each other make sure that that it's used properly of course there will always be people who will try to use this technology in nefarious ways but it is up to all of us to advance the technology so that we have access to this incredible capability to keep Society safe so there can be people who can use it in the wrong side also sure like all things they can yeah but the good news is there are more people who are good than there are people who are not good and we have

to have access to the technology so that we can keep the rest of keep an eye on keep the world safe completely y there one more last question I just want to ask you how many hours do you sleep last night I arrived at 3:00 I was up at I guess 6:30 and so that was only today three for 3 and a half hours but I'm 100% you know this is it 100% 100% on it yeah yeah this is fine so do you do kind of some kind of yoga or something no or is it

because on the weekend I catch up on the other 100% perfect thank you thank a aumar thank you unbelievable thank you thank you thank you so so what is it that we've we've spoken about let me talk let me let me close very quickly about about artificial intelligence now remember I just said on first principles we've reinvented the whole Computing stack from coding to machine learning from running code on CPUs to running neural networks on gpus from developing software to now developing artificial intelligence we also imagined the two most General versions of artificial intelligence one

is Agents essentially assistant for ourselves agents for all kinds of different parts of our job assistants that help us be more productive do superhuman things and the other robots essentially physical versions of Agents these two general purpose agents or robots are going to be are being built right now as we speak and the Technologies are available nvidia's job is to create the technology to help you build AIS and agents and help you deploy it now what happens when we do that at scale remember India used to be a country that produced software you exported software

in the future India is going to export AI when you export AI That's Right In order to in order to create Ai and produce AI you need a Machinery these AI infrastructures we've been talking about these machines would take energy and transform them to what is called tokens these tokens are floating Point numbers and these numbers reconstitute depending on its modality into artificial intelligence artificial intelligence digital intelligence one of the most valuable Commodities we know and so the future is going to have a new industry and this new industry is the production of intelligence this

is production of intelligence at enormous scale that's the reason why I say there's a new Industrial Revolution a singular Factory singular concept of a factory running all these different process all these different types of data creating these models generating and producing intelligence and tokens at scale for all kinds of different Industries this is what we're seeing happening in front of our in front of us as we speak and so I hope to partner with all of you to enable India to be at the center of this new Industrial Revolution now to talk to you about

some more of this and how it applies to India I have another special guest and you will surely know him as well an industry Pioneer an industry Pioneer someone someone we can genuinely said digit help digitalize India and yeah please and help build the fabric of the modern internet India that we know ladies and gentlemen mesh Amani my friend mesh how are you so good to very nice to see you very very nice to see you please sit down well you know we've been this morning we've been talking about AI MH and the last time

you and I spent time together we were talking about Ai and the time before that we were talking about Ai and uh I now you could see we don't really have much to talk about aside from Ai and and um no one no one has contributed more Mukesh to help India become a high tech and a deep Tech India now you're at the beginning of that Journey you have great aspirations I know you have deep aspirations to help India become a deep tech industry and and uh what gives you that conviction and why is artificial

intelligence that moment for India so Jensen first let me welcome you to our city of Mumbai a city with a large heart e e if we think about Vidya Vidya is Saraswati and Saraswati is our godess of knowledge so when you actually devote yourself sincerly to the goddess of knowledge and you acquire knowledge then in our tradition the goddess of prosperity which is Lakshmi follows so what you are doing 32 years ago I knew this so and now the story of Nvidia has been revealed to all of you so our first principles right are what

you are driving thank you is the knowledge Revolution converting into the international into what I call the intelligence Revolution and that drives Prosperity across the world for all all the 8 billion people and I think that what we are at the doorsteps of is the new intelligence age and on behalf of everybody I very proud to have you as my friend and welcome to India and thank you for actually contributing to the world to bring the intelligence Age In Our Lifetime and hopefully together with everybody this can drive to more prosperity for all the 8

billion people in the world and particularly the 1 and a half billion people in India [Applause] mesha it is it is such an honor and such a great privilege and and incredible joy to be able to contribute in this way and and um as as you know uh the IT industry of India is world world renowned for its very large scale and not just in size but in deep expertise of computer science very few countries in the world has this natural resource this amazing natural resource called it and computer science expertise in the last couple

of years we've been working together to upskill and we've now upskilled about 200,000 it professionals into the world of AI you know what what do we have to do together and how can we work together to help transform India at the speed of light really because everything is moving so fast past to to to to transform India into a center not of just it but a center of AI so from my point of view uh Jensen let me tell you my own uh experience uh in India first right as our prime minister has said that

this is a new aspirational India what we have today is we are among the only country in the world where the average age of 1.4 billion Indians is below 35 so what is driving our economy is not only new technologies like AI but also aspirations and I believe that uh you know the Prime Minister and I believe that his leadership in terms of converting India to a premier Digital Society has been vital and continues to drive activity at the ground level so it's demography it's activity at the ground level so it's demography e e that

today A Part from the US and China right India has the best digital connectivity infrastructure 4G 5G and Broadband in the world yeah when people talk about Gio and you know we said we Gio took India from number 158 in the world to number one in the world in 8 years we as a single company didn't know anything about this domain right but today we are the largest data company in the world mhm right yeah our volumes are equivalent to at NT mobile and Verizon combined yeah so I I would I would say I would

say uh uh size of local market is quite an advantage but let me tell you like the most satisfying piece and well having one and a half billion customers do it Part the best part still coming that's pretty satisfying so the most satisfying piece is that as Gio we delivered about 16 exabytes of data this year or we will deliver this year and the average in the US you pay $5 a GB in the world average for data is about $35 a GB in India Geo delivers data at 15 cents a GP and what and

what that means is you don't do you encourage your customers to use their phones we do and what really that means Jensen is a Perpetual value yeah right that technology has delivered customer value yeah of between 5700 billion a year year on year every year to Indians and this is the gift of technology to the people of India and this is what right what you described as intelligence we can do to actually bring prosperity to all the people and bring equality to the world and that is the opportunity why I describe this and this is

the reason that India will be one of the biggest intelligence markets and it it's not only our aspirations but I think it is just the raw gene pool and the raw Gene power that exists in India the youth power that exists in India that is actually going to and drive intelligence and hopefully once we drive intelligence for our domestic market right yeah we will use intelligent Services Beyond software to integrate with the rest of the world and Indians now will not only export CEOs to the world's largest companies but hundreds of millions of Indians it's

it's true it's true all of my all of my colleagues all of my friends back home they're all Indians all all of my CEOs and and hundreds of Millions will deliver to the world AI services to help a better world and uh that is why your being here thank you right is important your commitment to this country is important and working together right this cannot be done by any one company any one individual but we all have to work together to bring this intelligence age safely to the world so that we can create a more

equal World a prosperous world and allow the global South to catch up with the rest of the world yeah this way [Applause] terrific and you know one one of the things that that that uh you you've highlighted is just the immense amount of Digital Data that's available um surely at Gio and in India and this is leads to leads to one of the things that I want to announce uh with you uh as you as you know in order to lead in artificial intelligence you need to have uh AI model technology that uh India has

you need to have data massive quantities of data and using a uh the last thing you need is uh AI infrastructure and uh uh we're we're announcing that that Reliance and Nvidia are partnering uh to build AI infrastructure here in India absolutely know and then and then the the thing that I will say is that in order ultimately to create that into a flywheel is one of the great advantages that India has which is a very large population of users and and so now you you have the fundamental ingredients uh AI data and AI infrastructure

uh and you have a large population of users that ultimately creates your AI flywheel the thing that that I really love and um when I met modii the first time he asked me to meet his cabinet uh was to this this has got to be about six years ago he asked me to address this cabinet about artificial intelligence and I was so surprised that was the literally the first time any government leader uh any national leaders asked me to address uh his cabinet on um uh this particular topic it was long before anybody was talking

about artificial intelligence and my last visit with him he said he said this and it was really quite profound he said I I was explaining to him uh the concept of uh AI infrastructure and why it's essential for every nation to have their own AI infrastructure like their own communication their internet infrastructure their roads uh energy of course and of course intelligence should be part of your infrastructure and the manufacturing of intelligence should be part of your infrastructure and and he said this he said he said it makes completely complete sense that India should manufacture

its own AI manufacture your own AI you should not Outsource you should not export data to import intelligence that India should not export data to import intell intelligence and he said absolutely and and mo Modi said it's like India should not just export flour to import bread we should add value to the data ourselves and and uh and the partnership uh that we have is to start that journey to build the underlying infrastructure so that India could have your own infrastructure you surely have your own computer science expert and you also have your data you

have a giant population of users uh to to drive that flywheel and then one one more comment uh this is the thing that that that he was he was most inspired by uh six years ago he said he said that artificial intelligence has the ability to elevate um the entire population of India and the reason for that I was talking earlier to him about the fact that there are so few people in the world who knows how to program a computer programming is not easy uh here in India it's the largest population of any pro

of programmers in the world however still programming is not easy most people don't know how to program python or C++ or you know Pascal or Fortran but or Java but everyone knows how to program an intelligence and so the ability to program computers is available to a small population but the ability to program AI is something that everyone can do and if if AI could be put into the hands of every citizen it would Elevate and put into the hands of everyone this incredible capability you and I get the benefit from called computers and this

computer could now benefit everybody in society and and that he he explained that back to me absolutely and I think that that is why I started by saying that we are very for forunate to have a Visionary leader who believes not only in Vision but in execution yeah and where [Applause] I and you know Jensen where I see our partnership and uh is really in a sense I was waiting for your gb2 200s to mature because like you from first principles I don't like uh doing anything but the best technology and now your gb200 right

is undoubtedly the best technology I'm looking forward all of my technology is the best [Laughter] technology India India including the next one India will start with what is the absolute best that you have and I'm happy to like what we are doing at jamnagar is we are now ready for big scaleup so we are building infrastructure right and we think big so we're building infrastructure for 1 gwatt which can be expandable to multiple gws at one location we already have the green power so that we are not dependent on anybody else for Power we are

building this so that we can scale this and as your multiple order of magnitude Technologies come we will build our infrastructure and uh we will one important piece that I believe is important is that for India and Indians right we have to repeat a Geo for intelligence to be really affordable available to the Common People yeah and towards that it is important that we design and build infrastructure so that to use AI our customers don't have to change a phone don't have to change their computers but they can still get good quality Ai and we

take the burden of putting that infrastructure together yeah and I think that is what uh we are counting on you and us to do on top of that I have again great respect for my friend Mark zukerberg because by bringing open source to the world of intelligence he has given you know everybody the opportunity to participate in this Evolution yeah llama 3 has activated every single company every single industry around the world it's incredible and what you have done with llama 3 also right is and all of us we can build on top of that

and to my mind this move of Mark will be written in the history right when we look at it 100 years from now that open source all the big things in the world have have helped on open source like Linux was open source and I think that uh at least from an India point of view we can use Lama as a base model it allows all of us to develop on top of a state ofth art uh model and surely then we can finetune train retrain do everything else and I am sure that there is

somebody in this audience who is very bright and very young and we will have right into the future an Indian model right as you very rightly said which might be 10x of Lama and that will happen from India and I hope and pray that our young people will do that but to start off with open source is great that's right on top of that right all your tools so The Foundry tools that we have we are looking forward to a Development Center where we take core of your tools and train hundreds of thousands of developers

in India to use all the Enterprise tools to use the Omniverse tools so that we can really apply intelligence in a practical way and to me this is just the starting of this intelligence age it's a multi- decadal journey cash is talking like an engineer you guys listen listen him go he's starting to sound like a 28-year-old engineer what do you guys think I like it I like it and that's why that's what we're going to do together and uh true I can like assure you that like like we did in data in a few

years from now right we will surprise the world with what India and Indians can achieve in the intelligence Market thank you [Applause] mesh it it will it will um uh certainly certainly we would agree that this is an extraordinary time for the world and this is an extraordinary opportunity for India um to have precisely the conditions that have such a large population and large industry of computer scientists at a time when this industry the Computing industry is going to become the intelligence industry leveraging on everything that you have leveraging on everything that you know and

your indigenous Advantage enormous amounts of data a large population of consumers to drive that flywheel of intelligence to data data to intelligence intelligence to data and have to National will to go do something about it this is such an extraordinary time and I am honored and privileged to be partnered with you to do this and let's let's uh let's make it a promise today that we will work together so that India could take advantage of the intelligence Revolution that's ahead of us okay thank you very much thank you thank you thank you thank you so

very much thank you ladies and gentlemen mes Amani thank you thank you thank you and Jensen my friend right you are here only a few days uh before Diwali Diwali is our new year it is where we worship the goddess of prosperity so on behalf of uh all of us we wish you thank you a very very prosperous New Year and to all of you a happy Diwali and a happy happy Diwali everyone thank you thank you my friend that was good e e for