【0602直播】COMPUTEX 2026 Arm CEO Rene Haas /畫面由COMPUTEX TAIPEI 2026提供

The silence. Right before the world changes. It's that split-second of realization. The moment when you know that life as you've lived it is about to become something entirely new.

For more than 35 years, we've learned to recognize that moment. From Cambridge to the US to Taiwan to the world. We partnered with our ecosystem, solving problems together. We've been here from the start of AI, preparing the world for what's next. Powering intelligence everywhere. In how we live, work, play, and move. Together. This is our moment. Because when you know you have the power to change everything, you step forward.

Now I'm inviting Arm CEO Rene Haas. Please welcome Arm's Chief Executive Officer Rene Haas.

That's a pretty cool video of Rene. Superstar. Not just a superstar, he's an action hero.

Look at his stock price. I announce a product, look at his stock price. Every product I announce his stock price goes up. Nothing happens to mine.

Yeah, yeah. Well, I needed the cash. So what were we talking about? RTX Spark?

Well, we wanted to reinvent the computer. You know, the PC has been here for 40 years and the operating system code written by hand is now going to be replaced with applications that are agentic. Now, these agentic systems, agentic AIs will use the PC, will use the tools in the PC. And so when we imagine this future, we thought let's see how would we change the architecture and how would we change the operating system and reinvent the computer and you know, that's kind of where we are. And so one of the things that we realized is that an agentic system really wants to have excellent CPUs, which is the reason why we used Arm and it has a 20 core CPU. It has to have excellent single threaded performance. The parameters, the memory has to hold a lot of parameters and so we created a new numerical format called NVFP4 so that we can compress the large language models as much as possible and fit a very smart AI into the system memory. We also wanted to unite CUDA that is for accelerated computing and CUDA tiles are tensor core processing into one processor. And the reason for that is because when you're operating these agents and they're thinking and they're using the tools, the agents are fast. And when the agents are fast, they expect the tools to respond quickly. And so that's why we're accelerating all of the tools. We're accelerating Adobe. Adobe announced they're going to re-architect Adobe Photoshop and Premiere so that it's CUDA accelerated and agentically accessible. And so we're accelerating applications. We accelerated Blender with RTX. We accelerated, you know, we're going to accelerate everything. We accelerated Adobe, Autodesk, Dassault, Siemens. We're going to accelerate every tool. And once these tools are accelerated, then they can respond to the agents very quickly. And so now, in order to build this computer, this SOC, unless you have the ability to integrate with the CPU and adapt the CPU to exactly the shape of the computer, it's really quite impossible, which is the reason why Arm is perfect. Thank you.

Well, you know, ultimately these personal computers are going to be becoming agents that are running all the time. They're autonomously running all the time. I could imagine today, if I left my laptop at home where I left my laptop in the hotel, I won't use it again until I get there. But in the future, you just pick up your phone and you chat with your agent. You're chatting with your PC in the future. And maybe there's something that you needed to have done and sent to you. Maybe there's a speech I need to have quickly written. And so, you know, I'll be working with my agent, working with my assistant, and that is now the Arm personal computer. Right. And so the PC is working in the back while you're not there, it's working. Yeah. And so if I want to do something that requires a cloud API, of course, I'll call it into the cloud API. But whatever I can do locally, we're going to continue to do on the PC, which is kind of the nature of PC. The nature of a personal computing device is that whatever you can do on the device you do. You don't have to worry about metering, you don't have to worry about the time spent. But whatever you need to do in the cloud, you will.

Our PC has got 128 GB of memory. If it was completely compressed into NVFP4, then you can have a 100 billion parameter model working on your PC all the time. And a 100 billion parameter open model, say Nemotron 3 Super, say, that's a really, really good model. And so it could do a lot of the basic work. And whatever deep thinking and frontier model that you need to use, it's just connected to the cloud anyhow.

These agents are going to be, you have agents and sub-agents and teams of agents. They're going to be working in the cloud, they're going to be working on devices. And so it's just like today, mobile cloud is not cloud only, not mobile only, it's mobile and cloud. And so it allows you to have a really great personal computing experience, your own experience. But whatever you need to connect to the cloud, you will.

Well, the operating system is going to be just as important as ever before, if not more important. And the reason for that, and this is the controversial part. The people say AI comes along, software is dead. You know, nothing is further from the truth. And now people are starting to realize that. When agents are here, they're going to use tools. And so those tools are more important than ever. And so they're going to use Adobe Photoshop, they're going to use Adobe Premiere, they're going to use Canva, they're going to use Dassault's tools, Siemens' tools, they're going to use tools, whatever they have on the device. This is the incredible part. Today, most of us probably know 10, 15, 20% of the features of a tool. If you know how to use Photoshop, use Lightroom, unless you're an expert like my son, it's kind of hard for you to know all of the features. But now, with your agent, you tell the agent what you're looking for, and the agents know exactly how to use the tools because it's read a skills file. It's essentially read the manual of that tool. And so now it goes and uses the MCP or the CLI connected to that tool, and it does everything you need it to do. Yeah, so it's going to unlock all these tools. These tools are going to be more useful and more valuable than ever. And these tools run on the operating system. So we're going to need Windows, we're going to need all these APIs and all these tools for a long time.

Well, it's probably going to be everywhere. This is at this point if you look at our evolution, first Hopper was designed for training. Then Grace Blackwell was of course great at training, but we also specialized NVLink 72 for inference. And at first people thought, you know, inference was easy and we explained to people that MOEs, large language models, and to be able to inference very quickly and generate these tokens as efficiently as possible, you're going to need a very complicated computer. And so Grace Blackwell NVLink 72 is the most efficient and we produce the lowest cost tokens in the world. Okay? And so that was a big breakthrough and now people understand that. That token that you want very advanced systems to generate tokens at very low cost. Vera Rubin took of course all of that and we extended it to run agents. At first when I said that 2 years ago, most people had a hard time understanding what that meant, but now they realize that an agent is orchestrating thinking, is using tools, it's accessing long-term memory, it's dealing with short-term memory, working memory, and it's doing memory compaction to remember to think about what should I remember for the future. How do I index SQL memory? How do I index structured memory? How do I index unstructured memory? And so how do I deal with all of that? That agentic system is what Vera Rubin is and it's a large system. And so people are now starting to understand that when we were thinking about agentic systems, what we're really thinking about is a new computing application pattern and that it really requires a new architecture. Well, now the big breakthrough, of course, these agents now are producing useful AI. And that's the reason why all of our growth, right? Your growth, my growth, it's just so incredible because when AI becomes useful, then the tokens that are being generated are profitable. And when token generation is profitable, everybody wants to generate a trillion times more tokens. The other part is that the agent compute pattern is a thousand times, maybe a hundred thousand times, and depending on the work, it's a million times more than chatting. And so you could see that the agents are working, they're working for minutes, hours, sometimes days, sometimes weeks. And so instead of a chatbot, which responds from one click, now the AI is thinking, using tools, reading, thinking some more, planning, trying. And so the amount of tokens that we have to generate has increased tremendously. The profitability of the tokens obviously is driving demand. So the compound effect of need more compute with more demand, that compound effect is what you and I are experiencing. And so we're seeing constraints almost everywhere. In our case, we were fortunate that we planned. You know, one of the best things about Arm is that they don't have to worry about the supply chain. You know, the supply chain of IP is electrons, and you can use as many electrons as you need, okay? And so I love his business model. I mean, as you know, I tried to become Arm, you know?

I know. I was trying to become Arm. Rene and I used to work together, and then we tried to work together again but anyways that was okay. I'm not sad still, I'm a little sad but this is a happy meeting. So my point is in our case we saw agents coming and we saw Vera Rubin coming so we did a good job planning our supply chain and so our supply chain can support our very robust growth. We grew almost 100% year-over-year this year, we're going to grow very aggressively next year and so our supply chain can support our growth but the fact of the matter is demand is even higher than that.

Take a step back, what's happening? Take a step back and think what's happening. What's happening is the computer industry was limited by the number of people using the computers. And now we have agents that are autonomously using computers and so we're going to have instead of 1 billion humans using computers we will have tens of billions, maybe more than that, of agents and robots and self-driving cars using computers. And so the question is how large can the computer industry be? And so, you know, my sense is that at this point it's a foregone conclusion that what is a trillion-dollar, multi-trillion-dollar industry is likely 10 times larger and so we're on our way to... And that's why Nvidia is the largest market cap company in the world and if you combine the two companies we'd be the largest in the world still.

Well, congratulations on everything you guys are doing.

How come when we were younger... I have to tell you, I think I aged better.

Come here. You're my guest. You aged better. It's to you.

Hey, this is Andrew Brown from Exam Pro, and cloud computing has now become one of the essential skills that you need to learn in order to make it in the web development industry. And AWS, Amazon Web Services, is the most popular cloud computing service used by startups. So, this whole course is about getting AWS certified for the certified cloud practitioner, which is the entry-level certification, and the idea here is that by getting the certification, you are going to be able to prove that you can work with cloud computing, prove that you can work with AWS, and you're going to have a lot more job opportunities available to you. So, you know, let's get to this and start learning about AWS.

Hey, this is Andrew Brown from Exam Pro, and I'm going to try to answer all the questions you might have about the CCP, which is known as the Certified Cloud Practitioner, to determine whether it's the right certification for you. Okay? So, the CCP is all about AWS foundational knowledge. So, what that means is that it can show that you know how to poke around, and you can use AWS console, and you know the general offerings from AWS. It's like a light version of the Solutions Architect Associate, okay? But, the CCP has some very unique offerings, which no other certification on AWS has, which is they have a strong focus on billing and business-centric concepts, okay? And that's why it's going to make a lot of sense why a lot of people who try to obtain the CCP are in sales and management, because it's going to give them that knowledge to help them inform VPs or CEOs the reasons why to use AWS, okay? All right. So, the next thing you're probably going to ask me is what value does the CCP hold? Well, it's not a gilded title. It can help superficially increase your AWS certification count, if that's something that some companies care about, but it's not recognized as an important certification for developers on resume. So, if you think by getting the CCP, it's going to help you get a job, it probably won't help too much. If you were a boot camp grad, then it could be a good indicator that you're a little bit familiar with AWS, so...