Wherever you are in the world, your technology, your devices contain multiple microchips. And more often than not, those chips at their core have been designed by just one company. So that's your phones, your headphones, your watches, your cars: 350 billion devices, all designed at core by ARM Holdings, not a company from Silicon Valley. They're based in Europe, in the United Kingdom, in Cambridge. And I was invited by their boss, Rene Haas, to discuss the future of AI, of self-learning humanoid robots, of possibly curing cancer, and of what jobs will be left for mankind.
ARM is an intellectual property company, so it's the heart of what we do. So, this is a snapshot into our world of all the inventions of ARM engineers.
And then just tell us in terms of the application of AI scientifically, you know, where could we go? What problems that are currently unsolvable could be solved?
Yeah, I've always thought that the killer app for AI is health. You know, drugs can take 20 years to be developed. 95% of those R&D efforts fail.
AI is going to not only shorten the amount of time that those drugs can be invented, it's going to shorten the amount of time that you test them. You'll start to replace some human trials with AI, but more importantly, you'll find a cure for cancer that today, you and I, other humans—not in our lifetimes. I believe in our lifetime, AI will help cure cancer.
So, this is your company that built on science, but it will transform science as well.
Good. Well, have you got any patents?
Rene Haas, thank you very much for joining BBC News. I want to start pretty big, right? What does the world look like in 10 years' time because of AI, and what's the thing the public hasn't understood that you can tell us about what's yet to come?
I think in 10 years artificial intelligence will be ubiquitous into every market that we know, every vertical we can think of, whether it's health, whether it's education. It will be pervasive everywhere. It will have some pretty dramatic effects, I think, on how we live, play, and work. Some jobs will go away, some jobs will be created that we don't know about, but at the heart of it will be AI.
You have experience not just, if you like, in supply—the core supply chain of the chips that drive the AI—but also in the applications. Talk to us about the key growth area. You're in every corner of smartphones or automotive or whatever. Robotics, for example, is something that you've been pushing hard.
Yeah, maybe I'll link back to your first question with robotics. ARM is the heart of the semiconductor industry and the electronics industry to that end. We are the CPU or the brain that sits inside every electronics device. And the brain is so important, as you can imagine, for every electronics device because that's what essentially runs the chip or the program or the end device. We're in data centers, we're in automobiles, we're in PCs, we're in smartphones, we're in earbuds. But we are the brain that makes those things go.
Robotics, to your first question, I think in 10 years will be a huge change function. We are the brain in today's robotics. One of the leaders today in robotics is Nvidia; their Jetson series, all of the things that they do there, the heart of that uses an Nvidia GPU and an ARM CPU. The work that Qualcomm does in robotics, they use ARM CPUs. So we are the brain of all these modern robots. And I do think in 10 years we will see physical AI robotics in a very large way, whether it's around manufacturing, cleaning services, security infrastructure, building bridges, doing repairs. We will see—
So actual—I mean, people talk about robots and they're not—you're the sci-fi future of actual—
Absolutely, 100%. Robots prior to AI were built for a certain purpose. You see them in factories today: they install a tire in a factory, or inside a distribution area, they're the forklifts that move up and down. With artificial intelligence, these robots can see, learn, and essentially be reprogrammed for new tasks.
So, in the service industry, the robot that was programmed to make a bed can now make a bed, but can also learn how to arrange the towels in a room or clean the dustbins or whatever you want to go off and do. This is only enabled by AI. AI allows these robots to learn, these humanoids. So what will happen is you'll have these general-purpose systems that, because of AI, will be able to learn and deliver new types of workflows. That is going to happen 100%. We need to get the costs down. We need to be able to get them to be lighter, faster, but that's just an engineering cost issue that we're going to get our hands around.
Well, massive consequences for that. We'll come back to that. But I wanted to just take you back to your origins. For those that don't know, I mean, obviously you're ubiquitous in the tech industry, but you're not a brand that a consumer would buy at this point. Just describe what is at the core of what you have done, and where you've come from, and just how many of these devices you're in.
We build a CPU, as I mentioned earlier, which is the brain. It's the essential element. But what we do is we design that brain and we license it to a company building chips. So, it's the blueprint. If you're building homes, we're providing the blueprint to how you build that house.
And then it's a very wide business model that essentially Apple, Nvidia, Qualcomm, Samsung, Tesla, Amazon, Google, Microsoft—it would be very hard to name a company that doesn't use us as opposed to who does use us. So, we are in every major device you can think of. Over 350 billion chips have been shipped since the company was—
An astonishing number. Dozens for every human.
Yeah. And it's probably low. I think we have figured out that not only have we shipped enough chips for every person on Earth, we've shipped more chips than every person who's ever lived on Earth. Add them all up and we're still larger than that. So it's the most ubiquitous compute platform ever invented.
And yet where we are now is the potential start of an exponential curve up in the usage of these sorts of chips.
We are at the start of a growth phase unlike anything we've ever experienced, certainly I've ever experienced. And it's really around what drives artificial intelligence, which is—when you think about the logic of it, it makes sense, because artificial intelligence, number one, requires a lot of chips.
It requires a lot of compute. That's what we do. And artificial intelligence can touch everything, every human, every industry, every workflow.
So I'm struck that some of the main deployments, the most advanced deployments of AI, is happening in the AI industry, in the tech industry. Tell me, how have you used AI within your company almost to make the AI? It becomes a little bit circular, but is it replacing jobs? Is it augmenting? What's the balance?
I think it's definitely augmenting. I wouldn't be able to tell you today that proudly my headcount is reduced by 25% because we have AI bots doing all the work, but we have a lot of engineers using the work just to make their work be easier and to go faster.
One of the things that's a big part of when you design a product or a chip, it's not the design, it's verifying that design and going through all the bugs and testing the bugs, identifying the bugs. AI is wonderful at solving bugs, addressing bugs, making it easier to find out what was the cause of the bugs. And we have engineers literally—I've had many of them tell me they'll run a report on a weekend and come in on a Monday. In the past, they would have to do all the Pareto analysis of exactly what they saw. When they come back, two-thirds of it might have been done and fixed. That just allows them to go faster. So I think probably we have 90% of engineering use it on a daily basis. I use it all the time myself personally. So yeah, we use it very heavily inside ARM.
And what about in your home life? How would you advise people use it with their children? Some concerns as well as some opportunities there.
Yeah. For people who say, "Gosh, you know, AI is going to replace humans and it's going to replace jobs and knowledge work," AI is going to be there, period. We know that, and that's for all the things we have talked about. So I would tell anyone who's talking to their kids, or in my case grandkids: learn it, embrace it, and become comfortable with it, because ultimately AI is a utility that's going to allow us to be more productive and effective. So don't be afraid of it.
Well, you say don't be afraid, but it's quite difficult not to hear from the AI leaders that keep on saying how doomsayery the future might be and how we all need to protect against it and governments need to be quite hard. You're actually running the core technology that provides the capacity for this exponential power to replace human labor, to do some mildly scary things, we're told by the AI companies. Do you think about that responsibility? Is that your job or are you just going to provide as much compute power as possible?
A little bit. But I would say at the same time, the estimates of jobs going away and being completely replaced by machines is a bit overstated. I was reading an article this morning—I can't even tell you why I was reading it, but it was about the economy in 1776 when the United States became an independent nation. 96% of the revenue and labor was farming, right?
Now in the US, it's about 4%. But were people worried about, "Oh, the farming jobs are going away, and as a result, because the farmers have no jobs, there are no jobs"? Almost kind of nonsensical, right?
I view AI as a similar type of thing. Will it change how we work and live and play? Of course it will. But at the same time, it's going to create opportunities that we can't imagine today in terms of what that means. So I tend to be an optimist by heart. I would say embrace it, learn it. And in ARM's role, I feel very lucky to be leading a company that's at the heart of it, because I think we can make the planet a better place.
Just to go back to origin for a second, this all begins where we are right now, in Cambridge in the 1980s. A team behind the BBC Micro, the Acorn computer, some engineers with not a great deal of money, I understand, in a barn designing chips that were so frugal that they even worked when the circuit board wasn't plugged in. Just describe that and how central Cambridge in the UK is to your story.
Oh, gosh. Yes, we're in a beautiful facility right now, so I can assure you that this is not where it all started. It started in a barn not far from here. It was a joint venture between a number of companies, but the real driver was VLSI Technology, Apple. It was a spin-out of Acorn. And what the company was looking to do was to design a new microprocessor, a new CPU, for use—in fact, the first use case was the first PDA, something called the Apple Newton.
And there were two big requirements for that first PDA. This is the 1990s now, a long, long time ago. It had to be low power because you're running off a battery, and it also had to be rather inexpensive because it had to go inside a plastic package. Back then they were in very heavy ceramic packages. So we needed it so it didn't generate a lot of heat. So that was the design requirement: make it inexpensive and don't draw a lot of power. And to your comment, yes, the engineers overachieved because what they found out was the very first microprocessor—the way these test boards are built is you have a test board that has a bunch of other components and you plug it into the wall and the processor runs. But what they found out overnight on the very first run was when they unplugged it, so no power is on the board anymore—so technically the CPU should not work—the CPU was still working.
And it was still working because there's tiny little bits of leakage currents that exist on the board. That sipping amount of power was still enough to make the CPU go. So they thought, "Oh my gosh, we're really onto something. We've got something that's incredibly power efficient," which is kind of the heart and DNA of the company.
And the critical point that you still retain to this day is the combination of compute power and power efficiency in terms of energy use.
That's right. The company then grew quite a bit, and the first designs were the GSM phones and then smartphones, and now, as I said, we're really everywhere. Power efficiency is the key to it, but I think one of the most important things that happens with any company when it's conceived are the habits you learn relative to designing products. We were fortunate—I'm super fortunate now as the CEO of the company—that that DNA was forged around low power and being very power efficient. And that really found itself into every single product that we build.
Which is why now even in data centers, when people think about, "Oh my gosh, ARM, aren't you known for smartphone chips? How are you possibly being used in these data centers?" Well, these data centers use hundreds of megawatts of gigawatts. Anything you can do to be more power efficient is incredibly critical, and ARM is twice as power efficient as the next leading CPU.
So famously, you designed the chips, you did the blueprints for them, and others manufactured them. A big moment this year when you start essentially manufacturing chips for a specific purpose.
We're having someone else build it for us. Manufacturing chips is a big lift. But what we were faced with a couple years ago was many customers were starting to come to us and say, "Hey, look, you're licensing this blueprint to me, and increasingly you're expanding the blueprint." So we worked very closely with Meta a couple years ago, and Meta came to us and said, "We would like to have you actually have the chip manufactured and you be the supplier to us of that product." That product is the ARM AGI CPU. We announced it in March. Meta was the lead partner, but since then we've announced many other customers—Cloudflare, SK Telecom, Oracle, multiple customers—and the takeoff has just been amazing.
