Every part Introduced at Nvidia’s CES Occasion in 12 Minutes
At CES 2025, Nvidia CEO Jensen Huang kicks off CES, the world’s largest shopper electronics present, with a brand new RTX gaming chip, updates on its AI chip Grace Blackwell and its future plans to dig deeper into robotics and autonomous vehicles.
Right here it’s. Our model new GForce RTX 50 collection, Blackwell structure, the GPU is only a beast, 92 billion transistors, 4000 tops, 4 petaflops of AI, 3 occasions increased than the final technology Ada, and we’d like all of it to generate these pixels that I confirmed you. 380 ray tracing teraflops in order that we may for the pixels that now we have to compute, compute probably the most stunning picture you presumably can and naturally 125 shader teraflops. There’s really a concurrent shader teraflops in addition to an integer unit of equal efficiency. So two twin shaders, one is for floating 0.1 is for integer. G7 reminiscence from micron 1.8 terabytes per second, twice the efficiency of our final technology, and we now have the flexibility to intermix AI workloads with laptop graphics workloads. And one of many wonderful issues about this technology is the programmable shader can be in a position to now course of neural networks. So the shader is ready to carry these neural networks and consequently, we invented. Neuro texture compression and neural materials shading with the Blackwell household RTX 5070, 4090 efficiency at 5:49. Inconceivable with out synthetic intelligence, not possible with out the 4 tops, 4 tear ops of AI tensor cores. Inconceivable with out the G7 recollections. OK, so 5070, 4090 efficiency, $549 and this is the entire household ranging from 5070 all the way in which as much as $5090 5090 {dollars}, twice the efficiency of a 4090. Beginning After all we’re producing a really massive scale availability beginning January. Nicely, it’s unimaginable, however we managed to place these gigantic efficiency GPUs right into a laptop computer. This can be a 5070 laptop computer for 1299. This 5070 laptop computer has a 4090 efficiency. And so the 5090, the 5090. Will match right into a laptop computer, a skinny laptop computer. That final laptop computer was 14, 4.9 millimeters. You bought a 5080, 5070 TI and 5070. However what we mainly have right here is 72 Blackwell GPUs or 144 dies. This one chip right here is 1.4 exaflops. The world’s largest supercomputer, quickest supercomputer, solely not too long ago. This whole room supercomputer solely not too long ago achieved an exaflop plus. That is 1.4 exaflops of AI floating level efficiency. It has 14 terabytes of reminiscence, however this is the wonderful factor the reminiscence bandwidth is 1.2 petabytes per second. That is mainly, mainly the complete. Web site visitors that is occurring proper now. All the world’s web site visitors is being processed throughout these chips, OK? And now we have, um, 10 130 trillion transistors in complete, 2,592 CPU cores. Complete bunch of networking and so these I want I may do that. I do not suppose I’ll so these are the blackwells. These are our ConnectX. Networking chips, these are the MV hyperlink and we’re making an attempt to faux in regards to the the the MV hyperlink backbone, however that is not attainable, OK. And these are the entire HBM recollections, 1214 terabytes of HBM reminiscence. That is what we’re making an attempt to do and that is the miracle, that is the miracle of the black wall system so we nice tune them utilizing our experience and our capabilities and we flip them into the Llama Nemotron suite of open fashions. There are small ones that work together in uh very very quick response time extraordinarily small uh they’re uh what we name tremendous llama Nemotron supers they’re mainly your mainstream variations of your fashions or your extremely mannequin, the extremely mannequin could possibly be used uh to be a instructor mannequin for a complete bunch of different fashions. It could possibly be a reward mannequin evaluator. Uh, a choose for different fashions to create solutions and resolve whether or not it is a good reply or not, mainly give suggestions to different fashions. It could possibly be distilled in a whole lot of other ways, mainly a instructor mannequin, a information distillation, uh, uh, mannequin, very massive, very succesful, and so all of that is now obtainable on-line and By way of Cosmos, the world’s first. World basis mannequin. It’s educated on 20 million hours of video. The 20 million hours of video focuses on bodily dynamic issues, so dynamic nature, nature themes themes, uh, people, uh, strolling, uh, arms shifting, uh, manipulating issues, uh, you already know, issues which can be, uh, quick digital camera actions. It is actually about educating the AI, not about producing inventive content material, however educating the AI to grasp the bodily world and from this with this bodily AI. There are lots of downstream issues that we may uh do consequently we may do artificial information technology to coach uh fashions. We may distill it and switch it into successfully to see the beginnings of a robotics mannequin. You possibly can have it generate a number of bodily primarily based, bodily believable, uh, eventualities of the longer term, mainly do a Physician Unusual. Um, you could possibly, uh, as a result of, as a result of this mannequin understands the bodily world, after all you noticed a complete bunch of photos generated this mannequin understanding the bodily world, it additionally, uh, may do after all captioning and so it may take movies, caption it extremely nicely, and that captioning and the video could possibly be used to coach. Massive language fashions. Multimodality massive language fashions and uh so you could possibly use this expertise to uh use this basis mannequin to coach robotics robots in addition to massive language fashions and so that is the Nvidia cosmos. The platform has an auto regressive mannequin for real-time functions as diffusion mannequin for a really top quality picture technology. It is unimaginable tokenizer mainly studying the vocabulary of uh actual world and an information pipeline in order that if you want to take all of this after which prepare it by yourself information, this information pipeline as a result of there’s a lot information concerned we have accelerated every thing finish to finish for you and so that is the world’s first information processing pipeline that is may accelerated in addition to AI accelerated all of that is a part of the Cosmos platform and right now we’re saying. That Cosmos is open licensed. It is open obtainable on GitHub. Nicely, right now we’re saying that our subsequent technology processor for the automotive, our subsequent technology laptop for the automotive known as Thor. I’ve one proper right here. Grasp on a second. OK, that is Thor. That is Thor That is This can be a robotics laptop. This can be a robotics laptop takes sensors and only a insanity quantity of sensor data, course of it, you already know. Umpteen cameras, excessive decision radars, LIDARs, they’re all coming into this chip, and this chip has to course of all that sensor, flip them into tokens, put them right into a transformer, and predict the subsequent path. And this AV laptop is now in full manufacturing. Thor is 20 occasions. The processing functionality of our final technology Orin, which is de facto the usual of autonomous automobiles right now. And so that is simply actually fairly, fairly unimaginable. Thor is in full manufacturing. This robotics processor, by the way in which, additionally goes right into a full robotic and so it could possibly be an AMR, it could possibly be a a a human or robotic, uh, it could possibly be the mind, it could possibly be the, uh, manipulator, uh, this this processor mainly is a common robotics laptop. The chat GPT second. For normal robotics is simply across the nook. And actually, the entire enabling applied sciences that I have been speaking about is. Going to make it attainable for us within the subsequent a number of years to see very fast breakthroughs, shocking breakthroughs in generally robotics. Now the explanation why normal robotics is so essential is whereas robots with tracks and wheels require particular environments to accommodate them. There are 3 robots. 3 robots on this planet that we will make that require no inexperienced fields. Brown discipline adaptation is ideal. If we, if we may presumably construct these wonderful robots, we may deploy them in precisely the world that we have constructed for ourselves. These 3 robots are one agentic robots and agentic AI as a result of you already know they’re data employees as long as they may accommodate uh the computer systems that now we have in our workplaces, it is gonna be nice. Quantity 2, self-driving vehicles, and the explanation for that’s we spent 100+ years constructing roads and cities. After which quantity 3, human or robots. If now we have the expertise to resolve these 3. This would be the largest expertise trade the world’s ever seen. That is Nvidia’s newest AI supercomputer. And, and it is lastly known as Undertaking Digits proper now and if in case you have a superb title for it, uh, attain out to us. Um, uh, this this is the wonderful factor, that is an AI supercomputer. It runs the complete Nvidia AI stack. All of Nvidia software program runs on this. DGX cloud runs on this. This sits Nicely, someplace and it is wi-fi or you already know related to your laptop, it is even a workstation for those who prefer it to be and you could possibly entry it you could possibly you could possibly attain it like a like a cloud supercomputer and Nvidia’s AI works on it and um it is primarily based on a an excellent secret chip that we have been engaged on known as GB 110, the smallest Grace Blackwell that we make, and that is the chip that is inside. It’s it’s in manufacturing. This prime secret chip, uh, we did in collaboration with the CPU, the grey CPU was a, uh, is constructed for Nvidia in collaboration with MediaTech. Uh, they’re the world’s main SOC firm, and so they labored with us to construct this CPU, the CPU SOC, and related with chip to chip and the hyperlink to the Blackwell GPU, and, uh, this little, this little factor right here is in full manufacturing. Uh, we’re anticipating this laptop to uh be obtainable uh round Could time-frame.
