Nvidia's CEO Reveals SHOCKING AI Future

please welcome to the stage Nvidia founder and CEO Jensen Wang Jensen hang recently did an incredible presentation at nvidia's keynote event he talked about the latest developments at Nvidia and what he talks about is really eye openening a lot of people are failing to grasp what it is that they've created when Jensen talks about an AI Factory the scale of what he's talking about is staggering take a listen Chad gbt came along and um and something is very important in this slide here let me show you something this slide okay and this Slide the fundamental difference is this until chat GPT revealed it to the world AI was all about perception natural language understanding computer vision speech recognition it's all about perception and detection this was the first time the world saw a generative AI It produced tokens one token at a time and those tokens were words some of the tokens of course could now be images or charts or tables songs words speech videos those tokens could be anything they anything that that you can learn the meaning of it could be tokens of chemicals tokens of proteins genes you saw earlier in Earth 2 we were generating tokens of the weather we can we can learn physics if you can learn physics you could teach an AI model physics the AI model could learn the meaning of physics and it can generate physics we were scaling down to 1 kilometer not by using filtering it was generating and so we can use this method to generate tokens for almost anything almost anything of value we can generate steering wheel control for a car we can generate articulation for a robotic arm everything that we can learn we can now generate we have now arrived not at the AI era but a generative AI era but what's really important is this this computer that started out as a supercomputer has now evolved into a Data Center and it produces one thing it produces tokens it's an AI Factory this AI Factory is generating creating producing something of Great Value a new commodity in the late 1890s Nicola Tesla invented an AC generator we invented an AI generator the AC generator generated electrons nvidia's AI generator generates tokens both of these things have have large Market opportunities it's completely fungible in almost every industry and that's why it's a new Industrial Revolution we have now a new Factory producing a new commodity for every industry that is of extraordinary value and the methodology for doing this is quite scalable and the methodology of doing this is quite repeatable notice how quickly so many different AI models generative AI models are being invented literally daily every single industry is now piling on for the very first time the IT industry which is $3 trillion $3 trillion IT industry is about to create something that can directly serve $100 trillion of Industry no longer just an instrument for information storage or data processing but a factory for generating intelligence for every industry a lot of the clips you're going to see here look like animation they look like something that in the past we would think of as a cartoon something that somebody drew or animated on a computer but that's not quite true what is generative AI what is its impact on our industry and on every industry a blueprint for how we will go forward and engage this incredible opportunity and what's coming next generative Ai and its impact our blueprint and what comes next these are really really exciting times a restart of our computer industry an industry that you have forged an industry that you have created and now you're prepared for the next major Journey but before we start Nvidia lives at the intersection of computer graphics simulations and artificial intelligence this is our soul everything that I show you today is simulation it's math it's science it's computer science it's amazing computer architecture none of it's animated and it's all homemade this is Invidia soul and we put it all into this virtual world we called Omniverse next Jensen talks about NS and I think this is a bigger deal than we realize the same way that Microsoft changed the computer industry with prepackaged software Nims are going to change what we think of AI and AI agents now the name might change but understand the concept of what he's talking about language models and argumented by Ai and so these one these boxes that you see are basically Nims some of the NIMS are reasoning agents given a task figure out what the mission is break it down into a plan some of the NIMS reach retrieve information some of the NIMS might uh uh uh go and do search some of the NIMS uh might use a tool like kuop that I was talking about earlier it could use a tool that uh could be running on sap and so it has to learn a particular uh language called abap maybe some Nims have to uh uh do SQL queries and so all of these Nims are experts that are now assembled as a team so what what's happening the application layer has been changed what used to be applications written with instructions are now applications that are assembling teams assembling teams of AIS very few people know how to write programs almost everybody knows how to break down a problem and assemble teams very every company I believe in the future will have a large collection of Nims and you would bring down the experts that you want you connect them into a team and you you don't even have to figure out exactly how to connect them you just give the mission to an agent to a Nim to figure out who to break the tasks down and who to give it to and they that a that Central the leader of the of the application if you will the leader of the team would break down the task and give it to the various team members the team members would do their perform their task bring it back to the team leader the team leader would reason about that and present an information back to you just like humans this is in our near future this is the way applications are going to look now of course we could interact with these large these AI services with text prompts and speech prompts however there are many applications where we would like to interact with what what is otherwise a humanlike form we call them digital humans Nvidia has been working on digital human technology for some time let me show it to you and well before I do that hang on a second before I do that okay digital humans has the potential of being a great interact interactive agent with you they make much more engaging that could be much more more empathetic and of course um we have to uh uh cross this incredible Chasm this uncanny Chasm of realism so that the digital humans would appear much more natural some people including some pretty smart scientists believe that it's possible that our world our reality is a simulation this question becomes even more fascinating now that we're getting closer to potentially being able to simulate our own reality if we're able to create simulated realities with simulated beings in them who's to say that perhaps there's not another reality above us the base Reality by reducing the cost of computing incredibly the market developers scientists inventors will continue to discover new algorithms that consume more and more and more Computing so that one day something happens that a phase shift happens that the marginal cost of computing is so low that a new way of using computers emerge in fact that's what we're seeing now over the years we have driven down the marginal cost of computing in the last 10 years in one particular algorithm by a million times well as a result it is now very logical and very common sense to train large language models with all of the data on the internet nobody thinks twice this idea that you could create a computer that could process so much data to write its own software the emergence of artificial intelligence was made possible because of this complete belief that if we made Computing cheaper and cheaper and cheaper somebody's going to find a great use well today Cuda has achieved the virtual cycle install base is growing Computing cost is coming down which causes more developers to come up with more ideas which drives more demand and now we're on in the beginning of something very very important but before I show you that I want to show you what is not possible if not for the fact that we create a Cuda that we created the modern version of General the modern Big Bang of AI gen generative AI what I'm about to show you would not be possible this is Earth 2 the idea that we would create a digital twin of the earth that we would go and simulate the Earth so that we could predict the future of our planet to better avert disasters or better understand the impact of climate change so that we can adapt better so that we could change our habits now this digital twin of Earth is probably one of the most ambitious projects that the world's ever undertaken and we're taking step large steps every single year and I'll show you results every single year but this year we made some great breakthroughs let's take a look more and more people working on AI find themselves talking about things like synthetic data and self-play this idea that AI can improve itself can create data to train itself we're beginning to see the emergence of self-improving AI we enabled Transformers to be able to train on enormously large data data sets well what happened was in the beginning the data was human supervised it required human labeling to train AI unfortunately there's only so much you can human label Transformers made it possible for unsupervised learning to happen now Transformers just look at an enormous amount of data or look at enormous amount of video or look at enormous amount of uh images and it can learn from studying an enormous amount of data find the patterns and relationships itself while the next generation of AI needs to be physically based most of the AIS today uh don't understand the laws of physics it's not grounded in the physical world in order for us to generate uh uh images and videos and 3D graphics and many physics phenomenons we need AIS that are physically based and understand the laws of physics well the way that you could do that is of course learning from video is One Source another way is synthetic data simulation data and another way is using computers to learn with each other this is really no different than using alphago having alphao play itself selfplay and between the two capabilities same capabilities playing each other for a very long period of time they emerge even smarter and so you're going to start to see this type of AI emerging well if the AI data is synthetically generated and using reinforcement learning it stands to reason that the rate of data generation will continue to advance and every single time data generation grows the amount of computation that we have to offer needs to grow with it Nvidia AI senior research scientist Dr Jim fan once said that everything that moves will be automated and it will be driven by an AI system and as you'll see here they're not kidding around about that the next wave of AI is physical ai ai that understands the laws of physics AI that can work among us and so they have to understand the world model so that they understand how to interpret the world how to perceive the World they have to of course have excellent cognitive capabilities so they can understand us understand what we asked and perform to tasks in the future robotics is a much more per pervasive idea of course when I say robotics there's a humanoid robotics that's usually the representation of that but that's not at all true everything is going to be robotic all of the factories will be robotic the factories will orchestrate robots and those robots will be building products that are robotic robots interacting with robots building products that are robotic and that was it for today's video see you again in the next video

Channel: AI Upload

Views: 19,496

Keywords: AI Upload, Artificial Intelligence, AI, Nvidia, Nvidia AI

Id: 3eta3TvTZqs

Length: 16min 18sec (978 seconds)

Published: Tue Jun 11 2024