There's a company nearly every chipmaker relies on that doesn't actually make anything tangible. Yet, its Blockbuster IPO in September valued it above $54 billion.
It's the largest public offering in over two years.
The valuation of the company has tripled.
If you have a smartphone in your pocket or in front of you, you have an ARM circuit somewhere inside of it. We are the CPU, the heart of everything.
They're the winner of the CPU side. The foundation models, the software, it's moving far faster than the hardware. So, what we're seeing is people investing faster and faster into new hardware, which ends up being a good thing for us. Ladies and gentlemen, please welcome ARM CEO Renee Hos.
How are you?
Welcome. Welcome.
David. Hey, good to see you. Hi.
Hello.
Renee, what are you banging these days? Three milligrams of AL pouches or you're up to nine? I know you're competing with Nvidia, so you probably want to go with the nine, right?
I will go with the nine. With Jensen, you have to go big.
You have to go big with Jensen. What's that like to compete against Nvidia?
Well, I will say Nvidia is a customer of ours. So, I'm not going to say Jensen is my competitor today, but you know, I worked for Nvidia for many, many years as you know. And he's fantastic, and I learned so much working there, working for him, working with him. And then Nvidia almost acquired ARM in 2020, so I almost had a chance to work with him again.
What did you learn from Jensen?
You know, one of the things about Jensen that is amazing, I think it's also true for people like Michael Dell, Masa. You have these entrepreneurs who started their companies 30 years ago, 40 years ago, and they're still running it. So, you have this amazing set of characteristics of vision, speed, fearlessness, taking risk, and an ability to pivot very, very fast. And I saw that a lot at Nvidia. You know, when I was there, we were only about $4 billion in sales. And at that time, we were looking at lots of different ways to grow business models and such. And I just remember being, you know, one story: we were at a strategic offsite and it was supposed to be a review of roadmaps where we were looking at each one of the general managers going through what they projected in their business. And what was intended to be a roadmap review turned into: we're changing the strategy. We're abolishing this product line. We're going to move 2,000 engineers off of project X onto project Y. And by the way, we were only about 6,000 people at the time.
What was project X? What was project Y?
So we were involved at that time in trying to do mobile chipsets connecting to an Intel processor, right? And back in the day, for those who remember PC architecture, doing these chipsets competing with Intel was really hard business and Intel was making it very, very hard to compete relative to the integration that they did. And in fact, that was the genesis of starting to pivot to ARM in a very big way inside Nvidia because at that time Jensen looked at what was going on with SoCs and ARM-based architecture and moved everybody onto the program.
Let's maybe take a step back and level set for the audience. So just to give some background, Masayoshi Son and SoftBank took ARM private.
Took it private. Yeah. For $32 billion.
$32 billion and then tried to sell it famously.
Hung on to it. Took it public. It's now a $150 billion market cap company.
And you were telling us backstage he famously refuses to sell a share.
So it's like a slow kind of process of just building the shareholder base, but you've done phenomenally well as a business.
Just set the landscape for people that want to understand Nvidia, the most valuable company in the world, but it's a window to understanding AI.
Why does what do they make that's so powerful? And why aren't there other competitive solutions at that level of scale yet? And how do you think that changes over the next 5, 10 years?
Oh boy. A lot there to describe. So the way to think about Nvidia, and to some extent I don't, even though I'm the CEO of ARM, I don't want to tie it necessarily back to ARM, but in our world what really drives demand is compute workloads. At the end of the day, it's compute workloads. And when a new workload is essentially either identified or invented, then it comes down to what is the best architecture processor-wise to address that workload. So let's look at AI. The lightning bolt moment of AlexNet and the work actually that the Demis team were working on. AI, particularly training, is a very, very complex parallel problem that is well suited for a GPU. And in fact, the very first work done by the engineers on AlexNet was not with Blackwell. It was not with an AI processor, but it was with a gaming GPU, a gaming card. So Nvidia was in a very, very good place to seize that moment relative to the DeepMind moment, AlexNet, slash the transformer, and fast forward: training these complex AI models as Demis was just talking about, this is a huge, huge amount of work. Now, what role does ARM play there? Every one of these workloads requires a CPU to not only run the computer but help the accelerator run. And that's where Nvidia is a customer today. Their most advanced chip called Grace Blackwell is 72 ARM CPUs with a Blackwell architecture. And that's where Nvidia plays today. So, back to where does Nvidia fit? There is competition. Demis talked about prior with Google, they do their own chip called TPUs. Obviously Nvidia is the leader with general purpose, but right now we're in this interesting world where people are looking at: is it a general purpose chip, is it a custom chip, etc. It's a fascinating time to be in this industry for sure.
Where do you think companies like Tesla, you know, Tesla recently merged two pads and now they're working on AI5 and AI6? And some of the more emerging companies like Cerebras and there's a whole slew of companies now, Grock and others that have raised enormous amounts of money. Do you believe that the role of ARM should be to be, for lack of a better phrase, the arms dealer to all of those folks that need that capability, or at some point do you think that you know you see enough of it or you're like gosh I could just do this better?
Maybe a little bit of both. I mean today the role we play is we are now increasingly that microprocessor that connects to these accelerators, whether it's something that's done by Cerebras or it's something that's done by Nvidia, something done by Google. They're connected. Could we do something ourselves custom? It's possible. Could we also supply the intellectual property to somebody building a custom chip? We're doing that today. So to some extent we're in a very unique place that not only can we provide the solution whether it's standard or custom, but as AI moves from gigawatt data centers to running in these headsets or running in a wearable or running in something that needs to be energy efficient, you still need to run the compute workload but now you need to run the AI workload and that is a place that I think only ARM is uniquely positioned to address.
