block . i still like it boeing, happy thanks giving everyone. >> i'm thankful for my family that tolerates me . thankful for all of you. i like that bob is picking up steam. >> thank you for watching fast money. i'm thankful for you have a great thanks giving. mad money with jim cramer starts now . >> my mission is simple, to make you money. i'm here to level the playing field for all investors. there's always a bull market somewhere and i promise to help you find it. mad money starts now. hey i'm jim cramer and welcome to this special nvidia focused edition of mad money.

for many of you know i've been pounding the table of nvidia for years. i watched the stock row 350% over the last five years. artificial intelligence and its accoutrements have been going rampant on wall street. it's not a fleeting finite detail it's one of the greatest stories we've ever told. when i was at the dream force conference, the salesforce ceo sat down with one ceo of nvidia making a cooperation agreement regarding salesforce's new agent force rollout. it's a field he packed it he created practically created. take a look. >> it's the best. nobody should miss the next decade, would you agree with that? he won't want to miss this movie. you want to see the next 10 years. you want to see the breakers and technologies, diagnosing disease, the breakthroughs in science. it will be so much in the scientific assistance. >> moments like these remind

me that nvidia is misunderstood, they make chips that could do unimaginable things. they will perform many miracles. i'm skeptical of many of what we have now. they tend to be all the things that would've been done anyway, things that would have been rebranded but one thing that we know for sure is that it will be at the forefront of whatever ai does in the world. that's why when the ceo talks i listen and it's also why tonight we are taking you to my exclusive one-on-one conversation with the man i called the da vinci of ai himself, the developers conference in march, we talked about chip demand, the company stock split, the growing list of partners? take a look. >> we are at what some people

are calling the woodstock of ai and is in it more than that? isn't this a change than the when it comes to digital and creating were thinking? you are changing that. isn't this what we are doing out here? >> yes, it's an incredible conference. this is nvidia's developer conference. everything that we do begins with software . it's and surf service of all the software developers in solving the difficult algorithms. we are represented by 120 and dollars of industry here. healthcare is here, financial services are here, manufacturing, industrial, automotive, climate, tech. you know, holy cow, communications is here. consumers are here. >> people always think of you though as hardware but you are talking about the different platforms and a system that

frankly be unassailable from competitors because when the companies get involved they are going to stick with nvidia. >> it's a specialized way of doing accelerated computing. this is the observation we made a long time ago, 30 years ago we observed it's good at many things but there are some things that surprisingly i'm good at. parallel things. a large number of processors, we added nvidia to a cpu and connected it to offload to work the cpu is not good at and we run the work insanely fast. surprisingly this represents 95% of the time that is spent in computing. we offload that and run this 100 times faster. >> but you're talking about a do over of technology . our country is building new plants using old technology if that's

the case. >> it's wrong, well, we should build amazing semiconductor plants here and we would be more than happy to build all kinds of chips here but it's clear, in the future, the general purpose computing is like a general-purpose amongst anything. an instrument of any kind, it isn't very efficient. there's many types of things we'd want to do efficiently, computation of mathematics, we want to do that efficiently. as a result of doing a sufficiently you would drive the cost down and use less energy. one of our computers, the latest generation, this is the chip that goes into this, the largest chip the world has ever seen and beyond the limits of physics as we have two new use new in technology. 208 billion transistors in this

tiny part in the middle. >> how much did this cost? >> this will cost $30,000- $40,000 per >> how much did you spend to develop it? >> the first one, the budget of this generation is probably something like $10 billion. >> you deserve the right to recoup that and you are doing this. >> we will do our best job. this computer here , this is called the blackwell computer. it's a really terrific mathematician. it will replace thousands of general-purpose computers. this is the part that is incredible. what's amazing, the cables of connecting last veneration general-purpose commuters computers costs more than the price of one of these computers. the amount of energy we've saved, it is incredible. megawatts and megawatts.

because of this we've made it possible for the computer to write software by itself and it's so insanely fast, now the software could write, the computer could write its own software and we call this artificial intelligence. >> if that's the case why do we still need us? >> willie while we still have to guide the software, we create algorithms such that it could write software. that algorithm is called deep learning. it's quite a remarkable thing that happened. >> if we ask deep questions , inference, this speaks our language? >> if you ask this a question, first of all it not only recognizes words but understand your meaning . it understands the meaning. >> nuance? >> sure. you could say first of all i will let you read this book then i will ask you a bunch of questions about this. first it goes and reads it.

>> doesn't understand why ishmael is completely driven by moby ? >> absolutely, it read the end of the story . not only that, it's read a bunch of other stories. so, it understands the context of this conversation, it also has included within it a lot of things that it's read from society. >> but you are describing something different from ernie's first share. you are describing wonderment. you are describing this creating something that could create the replacement of trillions of dollars of what we don't need anymore doing this more productively. cleaner. everything has to be replaced. >> there's a lot of waste in the world. oftentimes we can't chase it down but of course there's a lot of wasted energy used in doing computing and now with computing we could make this more efficient. there's a lot of waste in just

about every single industry. the challenge, we've never been able to use a computer in order to understand the information of these industries at one of the things that is exciting, we have been able to sequence chains but have never been able to understand what it means. >> we didn't understand what the pro chains do? we could begin to understand what protein does. >> we could do drug trials in 60 days instead of six years so companies would tackle these tough illnesses that the can't afford to tackle. >> that's exactly right and that the minimum you got to go through trial and trials on people and things like that but we could reduce the time it would take to go through the entire search space of drugs and proteins and targets and that search space is gigantic. it is impossible for humans to do this. computers with artificial

intelligence could understand the language and biology to sort through this more quickly. >> what about the last frontier ? >> the last frontier, we have to teach it to understand physical things. it has to understand when you drop something it falls to the ground but it doesn't go through the ground and you've got to understand that the mechanical hinges work in a particular way. the mechanical hinges that work in a particular way, this is no different from word sequences or the sequences of sentences turning into paragraphs, it could understand and learn to understand physics and understand mechanical things. once a dunce that we could once it does that we could understand how these computers work. >> if you order fries you should also recommend some dietary options. >> does it bother you in the

end we are trying to figure out whether it's $1 trillion for nvidia, are these questions to pedestrian versus the years you have worked to get here? >> first of all, we do different things , nvidia is an accelerated computing company. we built the chips, the systems, the networking. the entire data center practically in the software that goes into this and sell it in parts. that's what confuses people. they think we are a chip company because we sell things in parts but the reason we do this is so that our customers could integrate the technology into their data centers to help every day alike. everyone's data centers are different and systems are different so when we build up the whole thing we make it work and we sell it in part so that it fits into the nooks and crannies. >> if you've got the software why would there be any semiconductor companies? >> there's lots, the world of

semiconductors is gigantic. we serve one niche called the accelerated computing and artificial intelligence. this is the foundation of computing as we know going forward but it's a data center scale company were full stack software company designs the system. we sell this in parts so that everyone could enjoy nvidia. >> why isn't nvidia a $2 trillion company? >> that's a tough question. first of all, there are several things that i appreciate about the work we do. one, the foundation, computing. we have computers that could understand information of all different kinds and the impact to the industries that are enormous. $100 trillion of industry that's here in the impact of the work we do for all of these

industries is incredible. >> you could take your 2% of the $100 trillion? >> as we spoke, they've casually tracked another trillion dollars in market. they've received trillions of dollars of market impact. we are hearing all about the secret to their success next. >> don't miss a second of mad money. follow at cramer on ex. sent him an email to mad money cnbc.com or give us a call one 807 43 cnbc. miss something? go to mad money.cnbc.com. i've seen it. trust me, after 15 walks, it gets a little old. ugh. stop waiting. start investing. e*trade ® from morgan stanley. (♪♪)

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are looking at going on here our viewers want to thank you for being able to retire on your stock. putting their kids through school, to change their lives and i think that it's good manners to say thank you. >> i want to say thank you to all of our shareholders with their shared support as we were able to do our work and realize our hopes and dreams to make a real contribution to the industry and the world so i'd like to thank you. >> well you are welcome because we have to start that way and what you've created here, it's something that is remarkable. it's being reported by the stock market. $2 trillion valuation work so i ask you, what has nvidia done to deserve such evaluation and maybe it's still an expensive? >> there's probably never been a technology company that's made a greater technology contribution to one of the most important industries in the

world and that such a large scale. we reinvented the computer as we know it. it's been the same since 1964 since the year after i was born. we have reinvented it with this idea called accelerated computing. now you could have a computer that's 100 times faster or 20 times more energy efficient and cost 20 times less and to be able to do or solve problems at a scale that no one has imagined such that we helped to solve all our official intelligence and are on our way to making enormous progress in the automation of intelligence and as you know, intelligence is foundation to the industry is why they are all here. >> this is a factory of intelligence. >> in the future, exactly. can you see this? these servers are the most dense computers in the world which replaces the entire data centers in the past and shrinks them into this tiny data center

here. this will probably be more powerful than all of the computers in the world. >> will this be slow? >> every couple of years we will come up with something more incredible and in the last eight years we approved a performance per chip for one of these chips, approving the performance for one of these chips by 1000 times in the last eight years. >> this means it could talk about a movie, what does this mean that this is so fast? >> it's probably read those things and read about the movies . so if you wanted to ask a question about those movies or a book you'd say, read this book. now let me talk you to you about the book and you could talk to it about just about anything. >> couldn't make it so that a product like the vision pro

becomes a commercial product where it would be great to be able to step into a car and find out what it feels like and what it sees and maybe that would be the sales elements for a car company? >> first of all i've enjoyed the vision pro and i could tell you, it's really fantastic and i really enjoy it. they've done a great job with it . the tracking, the tracking with the world, the registration of all of the objects in the world. you feel like you are really in it and the thing that is great, when we connect vision pro with the world we call the on the verse and it's running on these computers, we essentially created digital world that is overlaid with the physical world and apple calls this spatial computing and you feel like you're practically there. it's amazing. >> it costs a fortune to do a

trial and because it costs a fortune to do a trial they don't do trials or they try to solve the easy illnesses. i talked to kimberly powell and it was clear beginning with blackwell we will not do trials the way we had done. we will go after parkinson's, schizophrenia, the things that no one could conquer these are now within this, they are now possible. >> we use artificial intelligence to understand a novel and we can use a similar technology to understand the meaning of proteins and the meaning of life. once we could understand the meaning of life and be able to operate and use this in a computer we could use that computer to simulate life such that we don't have to do as much of the screening in a lab. we could do a lot of that screening in a computer and that computer does this so

fast, we could explore the chemical space that is so much larger and explore the target protein space that so much larger and much more quickly whatever we decide, ultimately to take to trials, it will have higher possibilities for actually passing the trial. >> i think one of the things with your keynote, to urge people to watch, the soaring rockets at the end and how gorgeous they are but people don't realize in the end you are a supplier to other companies so if i wanted to do this, i wouldn't call jensen, i would be working with the company that's figuring out how to be able to use you to develop the trial. you are not the nameplate and that's one of the reasons i think people cannot understand you're a $2 trillion company because they are on to the nvidia phone. >> there's never been a company

built like ours. we created a new way to do computing. everyone we work with here, researchers and scientists of $100 trillion of industry in healthcare and financial services and such, so when we are done building these computers we break them up into parts. we integrate them into microsoft azure, hp intel, ibm . then they take it to market. the application software has been offered by cadence, synopsis, a really amazing company that we also work with. audit desk, adobe, and others.

our technology is integrated into their is and our technology is integrated into these computer makers. the world connects it together and that's the reason why it is everywhere. >> nvidia is everywhere as jensen said. it's becoming the everything and everywhere company that's why his stock has the valuation it does and it's why i say own it and don't trade it and i'm a believer in jensen and his vision. we have more with nvidia's ceo after the break.

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nvidia centric addition of mad money. the market for nvidia has soared as the company is different from the stocks a few years ago. it isn't you and me but the other companies that we buy from, partners like amazon, hp, or meta-. it relies on their innovation to power their own innovation. i asked jensen about the concept when companies realize they need nvidia, what i call getting it right with jensen. >> the technology is integrated with the computer makers. the world connects together which is why nvidia is everywhere. >> we hear all the time but you know amazon is out with a competitor product and all i hear from you is good. we want to help everyone to develop what is necessary. you're not at war with customers. >> know. we did something very different first of all.

our architecture, on the one hand could do artificial intelligence, it could do computer graphics, physics simulation, data processing, sql data processing which consumes a lot of energy and a lot of cost for many customers and we reduce this by 95%, 20 times reduction in cost of energy used. so much so that it's been delegated accelerated by it. they will accelerate their data process, a large-scale scout processing company. it's all something you could do with architecture. another thing you could do is everywhere, if your developer and you develop on nvidia you could run this on aws, gcp, hp, dell, ibm. anywhere. >> but everything is allocation and you do that then no one has enough nvidia products, correct? does mark zuckerberg have

enough with 350,000 chips? >> well we are in the beginning of the ai computing ramp. we are in the beginning of the accelerated computing ramp and it's going to last a few years. >> we know that you are tech power. i can't get enough tech power so how do i get right with jensen? >> everyone is right with me, they are fine so the most important thing is to work together to plan for the delivery of the chip. teacher data center ready, get all the engineers working on these data centers together and we will make sure that we support this. >> you can't just switch. if it were just chips you could be a commodity but you're not

commoditizing you go the other way. >> it's a computing platform so the applications that are developed for hardware runs on the hardware. trent will have to take a break and when we return we will find out more about this man who is sitting opposite me . this is amazing. >> from brainstorming on a napkin to owning and managing a $3 million company, jensen huang is a legend in the industry. we have more with nvidia's ceo, jensen huang coming up.

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>> welcome back to mad money with the nvidia ceo jensen huang.

>> jensen, 8 billion people did not get a degree in computer science. what are you doing to democratize this world? >> we will make computers smarter so that they don't have to learn computer science o program a computer. the computer should understand what we want and what we intend . >> you say these help you build a factory that could make he best cars. >> it surely will help a lot. the reason for this is because you give this a plan, you tell it the type of parts you'd like to put into it, eventually the factory will be a robot that is orchestrating a bunch of manufacturing robots that are building cars that will be robotic. >> why do robots look like people? >> robots look like people because of a couple of reasons. the first reason, the most important, we built the ruled for ourselves so the workstations of a factory and a manufacturing line of a factory were created for people so that's the most important reason in the second most important reason, we have to teach the robot how to be a

productive robot. you need data for that so we are in a world where in order to write the software for computers, we use data or give it examples in the computer learns from these xamples. we have the examples of human moving around of just of any other form of data. >> you thought of this , were you at denny's sitting around with some people saying, you know, we could do this, it might take 20 years or 30 years but we will do this. when did you think of this? >> we started the company in 1993 and our big idea was acceleration, accelerating the work that the cpus aren't good at. if we take the work that the cpu is not good at and offloaded to something that's incredibly good at it we could make the computer more efficient. that was the big idea. game was the first application.

>> you're a gamer. >> we are so good at making the chip for games that people thought we were a gaming company. >> intel thought you were a game company. >> we were happy that anyone thought of this at all. we were so good at it and in fact nvidia is the world's best game technology chip company today. i'm so proud of the work we do there and as you know, game is the simulation of the virtual world. >> somehow you are still the underdog . you are hungry and it makes a lot of business in only 30 days. >> you know, it's probably something just related to upbringing. you know, we grew up working

hard. my parents worked hard. >> you are with them before. >> my older brother brought me to the united states. he was 10 so we had a 10-year- old bringing a nine-year-old to the united states so we had quite a great life but we had to work for it and we were immigrants and took nothing for granted. my parents worked incredibly hard at work incredibly hard today. it's part of my dna. >> where they were working hard? >> they worked credibly hard. i have two kids and they both work at nvidia. they wanted to do their own thing. one wanted to be a world-class chef and one wanted to be in marketing and an artist.

now both of them are here. one is in marketing and one is an engineer and it's terrific. spencer is in robotics and medicine is an omnivorous and they do amazing work. >> are these the most expensive things on earth? this chip is the heart of the blackwell system and it's the largest chip the world is ever made. it's an anatomy process. it's so large that we have to take two of the largest chips in the world and connect them together into one giant ship. that chip goes into the blackwell computer and this computer, it's about $10 billion. what goes into this is supported by a whole bunch of unbelievable networking and high-speed i/o and mountains of software and it goes into the

data center and the data center becomes an artificial intelligence factory introduces artificial intelligence. >> can we safely say if we wanted to have, let's say 1000 incredibly smart people at our company, they wouldn't be collectively even as smart as that? >> it depends on the type of smartness . you know, artificial intelligence is good at emulating us. so the simulated how we read and this emulates, in order to emulate how we read and finish sentences and summarize paragraphs, we have to understand what it read so in order to emulate it it had to understand words. >> so i visited you six years ago or five years ago, it's obvious to me when you showed me the dog picking up the jell- o then you reward the dog and i was seeing something special. it was so obvious but it took

chat gpt for everyone to know? >> well chat gpt is quite the amazing breakthrough. the engineers and scientists . i'm very proud that nvidia's computers made it possible for jet chat gpt to do this but the researchers do unbelievable work. >> there you have it from jensen himself, nvidia's computers made chat gpt possible. that's why say own it don't trade it. it looked like it was done. their creativity and computing power and innovation, more with jensen huang after this break .

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welcome back to mad money. more with the nvidia ceo jensen huang now. one of the things that does concern me is we aren't perfect yet, i went to microsoft's copilot and asked who your best partner is and it said your best partner is intel. i don't think that's true. >> intel is a great partner. intel is a great partner. >> who isn't a great partner? >> we work with just about everybody, you know? here is the thing, nvidia is a market maker not share taker. we create markets. everything we do did not exist before. >> well then why are some people so scared of ai? there's this public fear that

this will make it so they don't have a job at this will create jobs. >> it's going to create jobs and make companies more productive when the companies are more productive their earnings improve or the revenues go up and when this happens they hire more people. >> that's called an industrial revolution, that's what the steam engine was. >> they make companies more productive and create more jobs and make the economy larger. >> is there a cpu that should withstand it or would you want everything? i know we don't have this yet but don't we want this ourselves? in a consumer fashion. >> absolutely. every device will run artificial intelligence software. the question is, is it small software or large software or gigantic artificial intelligence? >> will there be an arms race? we are friendly with every country in the world so won't other countries say, you know what, we have to create our own

blackwell and compete because we should necessarily share what we have is a country? >> the most important thing countries have to do is to create their own intelligence . >> sovereign ai. >> they have to do their own sovereign ai. >> they've got a lot of data that longs to their country. it's a natural resource. other people, of their language, culture. china's going to do their own anyway. every single country should harvest and process the data of their culture and turn this into intelligence that their own society could use. sweden is doing this and india is working on doing this. japan is working on doing this. every country should do their own and make sure that they own their own intelligence. >> most importantly this is because the dado the data belongs to the people.

this could be combined and shared with everyone else. we are happy to provide the hardware which helps everyone do this but this is important that all these countries create their own sovereign ai. >> i want to talk about the things that seem superfluous or frivolous but work. entertainment. the way we sing, the language we use. people don't realize the music that this could read. how does this have so much creativity? >> it understands music the way it understands language . you know, today when you asked chat gpt a question it will answer your question based on the context of the conversation. you could have a context of music. the computer doesn't know the difference between letters, words, or sentences. it doesn't know this any more than it knows the sounds and bars so this could create music

in the same way it creates language. >> the same way it creates a better operation or better machine operation. >> better chemicals for drugs. drug double chemicals, better proteins for enzymes or antibiotics. >> let's bring this back to wall street, wall street is trying to pigeonhole it and the truth is your earnings have always exceeded, even going to 2016, how do we try to value what you talk about? i myself, i think i'm a $representative. it was supposed to be funny like your speech. >> i was laughing inside. >> okay. okay that's good. >> on the outside i was just listening. >> i don't know if it's $10

trillion. maybe it should be a $10 trillion company because you are describing everything. everything that moves and everything that is digitized could be better. if that is something you could do with software or hardware, that's not a $2 trillion product. >> the opportunity for our company and the impact of our company has everything to do with the size of the industries we serve. there has never been a computing company that has directly impacted so many large industries before. artificial intelligence isn't -- it's related to a particular domain. artificial of intelligence of information is one come up for transportation is another, for manufacturing, industrial, for each one of these industries the technology that is associated with making the

impact for the industry is different so our opportunity is very large. >> so you can't beat demand by any means. so i think there's this interest between the transitions. it seems like all nonsense to me. it's a continuum and people who never seen the h 100. it's not outvoted, it works. it could create a giant liquefied natural gas boat. >> the demand is so high that every customer wants to have their hopper right now and they are more than happy. >> you think he'd be happy? >> he be delighted. >> they want to build their business and run their business today. they don't want to wait nine months from now to run their business they want it today so

our chips are not a consumer product that you could wait next week for or a year from now to purchase. it's an operational part of the company and you want o run your company today. so hoppers will be in great demand there will be great supply coming as well as great demand. >> i thought that one of the amazing things there were many companies that had nothing to do with technology. john deere, they made tractors and they need you? >> i love the fact that john deere is here , they made farming more efficient so that the farmers could be more prosperous. all of this, you've got retail, consumers, it's incredible, industrials. >> if you're a retailer . rockwell automation is here. one of the things was the demo i couldn't do because we ran out of time but microsoft, awk well rockwell automation, hexagon did a digital factory

completely in simulation. it was fantastic, the industrial digital twin, a fantastic demonstration and i hope we put it online. they did a great job. >> this is what makes nvidia so different from the rest of the pack. the demand is unique. it's not you and me asking for a new iphone or new car it's amazon, meta-, pfizer, tesla asking for jensen's latest innovations right now. more jensen huang after the u break.

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jensen huang cofounded nvidia in 1993 he's been the president and ceo ever since but the jensen before nvidia is just as interesting as the jensen after. we talked to him about his personal life and how his upbringing brought him to where he is today.

>> now, i want to go back to your upbringing. i know that you went to a special school in , you were the little guy with the glasses, you got beat up a lot but i also know everyone in the end seemed to like you and became friends and he put a school out there. who are you? >> i went to a school in the mission of the school is to welcome anyone who needs to come. there were some kids there who needed to go for behavioral reasons and some because they had broken homes and in our case because we were immigrants and it was a school that was willing to take us. the accessibility of the school was great for us. it was a tough school with a bunch of tough kids because us because some of these kids had

to be there. >> you won them over. >> yeah they are all good friends now. >> the last thing i want to ask you, there are two kinds of stack and talk about this stack and it's worth billions. then there's the stack you used to serve at denny's which of course is the full stack. >> my first company. >> right. which is more fun? >> it depends on the time of day. you know, first of all, i love my job at denny's. you and i were both in the restaurant business. i washed a lot of dishes. it was a tough job, you know. then i was a busboy and the waiters and the customers took great care of me. >> you like that too. >> i left it. >> you've got a lot of joy in her life. >> i do. i do. i cannot imagine a more perfect life. >> what world you'd want to save the most earth to perhaps?

>> artificial intelligence has its two greatest opportunities i'd say, the most greatest opportunity, one is to learn the language of life and that is healthcare. if we could solve that in this generation and the impact it would be, it's enormous. the other is to understand physics and science, multi- physics, large-scale physics all the way down to small-scale physics so that we could predict the climate. the ability for us to understand these two things are so profound to society and we are excited about it and this is the reason why nvidia has healthcare so that we could help contribute to the industry and all of the other scientists working on this from our perspective understanding how the computers work. our perspective and the scale of computing to be able to make a contribution in these areas. >> well i would like to thank you for the contributions he made for so many people who

watch our show and believe in you and are correct to do so. >> well i am grateful for all of their support. thank you. >> that was jensen huang, cofounder, president and ceo of nvidia. i like to say there's always a bull market somewhere. i will find it right here for you on mad money. i am jim cramer. i will see you next time. they'll invest their own money or fight each other for a deal. this is "shark tank." ♪♪ i'm jorrae. and i'm kelly. and we're sisters from philadelphia, pennsylvania. you know why it's gonna be really good? 'cause you made it. because i made it. i'll tell you the truth. we've cooked all our lives. we love to cook. my mom was the best cook ever. we would go to church on sundays, come home, and she would tear the kitchen up. so it's very important that we continue the tradition.