Nvidia's Generative AI Collaboration with ServiceNow

Nvidia's collaboration with ServiceNow revolutionizes AI platforms, accelerating computing and digital intelligence manufacturing.

### Jensen Huang's Vision for ServiceNow: Revolutionizing AI with Nvidia
* 🤝 Jensen Huang and ServiceNow have formed a fantastic collaboration, with ServiceNow using Nvidia for **building, training, and inferring models**.
* 🚀 Nvidia is pivoting towards **accelerated computing and generative AI**, transforming **every layer of computing infrastructure**.
* 🏗 ServiceNow has reinvented its platform across the entire stack, becoming the first enterprise software company to work on a **full-stack generative AI platform**.
* 💡 Huang emphasizes the **rapid pace of AI technology**, moving a **million times faster every 10 years**, and encourages everyone to **get on the AI train**.
* 🔮 The shift from **instruction-driven computing** to **intention-driven computing** will drive the adoption of AI across various industries.
* 🎨 Nvidia showcases a live demo of a customer service example using voice-to-text capabilities, highlighting the **future of interacting with AI through various modalities**.
* 🤖 Huang envisions the future of AI as **multi-modal, multi-shot, reasoning-based systems** that act as **employees in companies**, working with other AI and humans.

[Music] [Applause] I want service now thank you. I want I want service now they agree with me thank you thank. We want our service now yes thank you so Jensen last year you were here and it was still in the early Innings uh early stages of AI revolution. First thing is that we are delighted to be partnering with your teams there are as jod. We shared multiple meetings every week and we have collaborated. We are using you for building our models training our models and then inferences. We are a100 and h100s fantastic collaboration between djx super Parts. H100 is six times F faster than a100 little expensive but six times faster and then that's another way of saying six times cheaper. Yeah it's okay you yeah so for you pretty awesome pretty awesome collaboration and I know that's intelligent workflows uh you have a high bar for your employees you say you have to do extraordinary things to be extraordinary. How has service now roll out gone in the last one year at Nvidia

yeah, first of all, I'm delighted to be here. Uh, ServiceNow is the first enterprise software company that started working on a full-stack generative AI platform. Uh, you know, we're going through a major platform shift accelerated Computing and generative AI. Uh, every layer of computing is being transformed from the Computing infrastructure, the processors, to the acceleration libraries, to pre-train models. Uh, Nvidia has been pivoting in this direction for some time, and it was incredible that you saw the same vision that we saw, the same vision, and work together to do that. Uh, from pre-training the models, uh, to aligning them, guard railing them, optimizing them for the performance and the latency and the cost and the throughput, uh, to the packaging of these things into microservices that we call nim, so that you can run it, uh, in every cloud, including on-prem, uh, to Building Services. Now, ServiceNow is only infrastructure, own infrastructure, so that you could deploy these, uh, have a Sandbox for your engineers, and our

Engineers to collaborate in as well as providing the service to your customers. I mean across the entire stack you got you have really reinvented service now. It's really quite amazing to see that's pretty awesome and and just so you so everybody know uh we also are built on service now. It's correct. Thank you thank you thank you every morning I I wake up and the first thing I say is I want my service now and CJ just jumps right to it. Yeah thank you Jensen you know we have seen big shifts personal Computing to cloud computing to mobile but the AI shift seems really really accelerated yeah and very fast how should our customers think about where to use AI not just in general you know you have healthcare companies financial services company manufacturing companies uh life sciences how should they think about Ai and what will be possible with AI in next two to four years yeah one of the things that's really happening CJ is is um if you look at classically Moors law advancing 10 times every five years 100 times every

10 years. Over the last 10 years, AI has scaled a million times. First of all, you got to take a step back and ask yourself, if something is moving a million times faster every 10 years, what should you do, right? And we're talking about the, for the very first time, the production, the manufacturing of digital intelligence. We used to manufacture electricity, um, the last Industrial Revolution was the manufacturing of software, something that nobody understood that you could manufacture at scale, and we manufacture software at scale, and now we're manufacturing digital intelligence at scale, yeah. Now, the rate at which this technology is moving is so, so fast. The first thing you should do is, instead of looking at the train, you know, from the side and trying to figure out why the train is moving faster and faster, get on the train, because on the train, it's not moving that fast. When you're on the train, it doesn't move fast. Now, of course, one of the things that, uh, you've already shown in, in, uh, in the work that you guys

are doing from un one of the reasons why the technology is is being adopted so quickly is because we've transitioned from instruction-driven Computing, which is coding. Instruction-driven Computing where very few people can do to intention-driven Computing, which is intelligence interacting with somebody through intention. And so, even if you can't express, I mean it's very often that when I'm trying to get help, I'm not able to explain exactly what the problem is and how to express the help, yeah. And so now with service now being able to have the intelligent assistant, you don't have to be exact and ex and how you precisely describe the problem service now understands what the problem is. And so, I think that that's really really something to consider that every aspect of computing is going to go from in instruction-driven to intention-driven, yeah. And you guys are in some amazing work. We want to show you a very quick demo as you know that Nvidia is really really good really really good at graphics and for a certain class of users they would like voice to text.

rather than text so Amy quickly. We can show the demo. Okay, let's do it. Let's do it. So this is a customer service example, and we know that our customers want to deliver seamless customer support, especially in the moments that matter. So imagine you're at home and your Wi-Fi is moving incredibly slowly. It's down to a crawl, and you're the presenter in a critical meeting. You need service immediately. I need to contact customer support right now to see if I can upgrade. Now, normally I'd do this on my mobile phone. This is a live demo, so I'm going to be talking to customer support through this headset right here. Hi, Amy. I'm your ServiceNow assistant. How can I help you? I'm having a hard time downloading files, and my internet is sluggish. Can you help? I can see that your Wi-Fi service is working correctly. However, you have the 150 megabits per second package, the slowest connection speed we offer. Would you like to upgrade? Yes, give me the fastest connection you have. I can upgrade you to our highest

speed of 800 megabits per second, which costs $60 per month. For one year, you can save $60 a year, one month for free if you choose this service for the next 2 years. Sounds good. I'll take that 2-year package. I have a credit card on file and can process the upgrade right away. Is it okay if I use the credit card ending in 6304? Yes, I have upgraded your service immediately. Enjoy the fastest Wi-Fi we have. Thanks for choosing me to help you today. Have a good day. Thank you. Thank you much. That was a live demo between service Now language models and in Ras digital avatars. Jensen tells me the teams are working really hard for a certain class of users. For customer surveys, voice to text or text back to voice will be a real thing. Yeah, yeah. I think obviously there's a lot of different ways to get and engage a digital uh intelligence. And of course Tex is one way. Um, in the future, you'll be able to interact in a whole bunch of other ways and and one of

the one of the really interesting ways is digital humans and so you're going to see a lot of different applications of this in time. Thank you Jensen. Can you inspire us in with AI five 10 years out? Understood the instructions how faster things are moving the cost is becoming cheaper. What would be possible with AI in whether how work gets done or some of the big inventions that we thought are still not impossible? Well, there's a whole bunch of things that the industry is working on that we're working on together. First of course, you mentioned already multi-modality, the ability to associate information that is embedded inside different modalities coming together so that you could find greater insight across the modalities. This is no different than cars that are using cameras and radars and LiDARs at the same time trying to better perceive, better understand the environment through multimodality. That's one. Another is today most of the AIS are one shot you prompt it with something and it

generates instantly. And uh, the recommendation uh, in the future, uh, AI will be multi-shot. It will be reasoning-based systems just as we plan through various complicated, uh, scenarios. Uh, it will do some planning itself. And so, you're going to have fast-thinking AIS like we currently have. You're going to have multi-step reasoning AIS, uh, that will be coming along. Uh, these types of AIS will become increasingly agentic. Uh, you and you demonstrated some early examples of this as well. AIS that takes, uh, that uses tools. AIS that works with other AIS. AIS that access information they have privilege and access to. Um, Access Control to. And so, in the future, AIS are going to be like employees in our companies. In the sense that our employees work with your employees. And so, our AIS will work with other AIS. Um, and, uh, we'll have Consulting AIS. We'll have specialist AIS. We'll have generous generalist AIS. But one of the things that's for sure service now is in such a great position because this is where our

employees is the platform of our employees. This is the operating system of our company, and I've always hoped that Nvidia would become an AI. I now realize that what I need to do is make you an AI, and we'll use ServiceNow. That's very awesome. So Jensen, this AI Revolution would have not happened if it was not for you and the teams at Nvidia, the greatest innovator. Thank you for being here, sharing your vision with our customers. Please thank Jensen Wang for being here today and inspiring all of us. Thank you so much. Thank you. I want ServiceNow. I want ServiceNow. I want ServiceNow. Thank you.

Jensen Huang at the ServiceNow Knowledge24 Keynote

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling industrial digitalization across markets. NVIDIA is now a full-stack computing infrastructure company with data-center-scale offerings that are reshaping industry.

NVIDIA

The Partnership between Nvidia and ServiceNow

Nvidia and ServiceNow have formed a fantastic collaboration for building and training AI models, with Nvidia's H100 being six times faster than A100.

ServiceNow has been rolling out a full-stack generative AI platform, aligning with Nvidia's vision of transformation in computing infrastructure and microservices.

The partnership involves pre-training models, optimizing performance, and providing infrastructure for deployment in every cloud.

AI technology is advancing at an unprecedented rate, outpacing the progress of previous technological shifts like personal computing and cloud computing.

The rapid scaling of AI raises the question of how businesses should approach its use across various industries in the next two to four years.

The manufacturing of digital intelligence at scale is now a key focus, with the advice to not just observe the speed of development, but to actively get on board with the advancing technology.

The Transition from Instruction-Driven to Intention-Driven Computing

Technology adoption is rapidly increasing due to the shift from instruction-driven computing to intention-driven computing, allowing for more natural and intuitive interactions.

This transition is exemplified by ServiceNow's intelligent assistant, which understands and responds to user needs without the need for precise expression.

The demo also showcases the use of voice interaction for seamless customer support, highlighting the growing importance of intention-driven computing in improving user experiences.

AI is advancing rapidly, with the potential to offer faster and cheaper services in the near future.

Multi-modality is a key focus, aiming to integrate information from different sources for greater insights.

The development of digital humans is an emerging trend, offering new ways for users to interact with AI.

The Future of AI and Its Impact on Businesses

AI is projected to evolve into multi-shot and reasoning-based systems, capable of complex planning and acting increasingly agentic.

These AI systems will resemble employees, collaborating with each other and providing specialized and generalist services, ultimately impacting the operations of businesses.

Nvidia is acknowledged for driving the AI revolution and is praised for its innovation in shaping this future.