Decoder with Nilay Patel
Arm CEO Rene Haas on the AI chip race, Intel, and what Trump means for tech
Mon, 16 Dec 2024
Alex Heath, Deputy Editor at The Verge, guest hosts this episode of Decoder featuring a live interview with Arm CEO Rene Haas about the future of AI and the semiconductor industry. The two discuss his thoughts on the struggles of Intel, the rumors Arm is developing its own AI chips to rival Nvidia’s, and his thoughts on the incoming Trump administration. Links: What Arm’s CEO makes of the Intel debacle | Command Line How Arm conquered the chip market without making a single chip | Decoder Arm could be the unexpected winner of the AI investment boom | FT Arm to reportedly launch AI chips by 2025 to capture explosive demand | CNBC Intel’s CEO is out after only three years | The Verge What happened to Intel? | The Verge Nvidia plans ARM-based PC platform to rival Intel, AMD | DigiTimes Qualcomm x Arm beef escalates | The Verge Transcript: https://www.theverge.com/e/24084728 Credits: Decoder is a production of The Verge and part of the Vox Media Podcast Network. Our producers are Kate Cox and Nick Statt. Our editor is Callie Wright. Our supervising producer is Liam James. The Decoder music is by Breakmaster Cylinder. Learn more about your ad choices. Visit podcastchoices.com/adchoices
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Hello and welcome to Decoder. I'm Alex Heath, Deputy Editor at The Verge, filling in for Nilay while we finish out the year here on the show. On another recent episode, I teased an interview with the CEO of chip design company Arm, and today we have that interview for you. I sat down live in Silicon Valley earlier this month with Arm's CEO, Rene Haas, at an event hosted by Alex Partners.
It was a really fun conversation, and I think you're going to like it. Rene is a fascinating character in the tech industry. He's worked at two of the most important chip companies in the world, first NVIDIA and now ARM. That means he's had a front row seat to how the industry has changed in the shift from desktop to mobile and how AI is now changing everything all over again.
Arm has been central to these shifts as the company that doesn't build but rather designs some of the most important computer chips in the world. Arm's architectures are behind Apple's custom iPhone and Mac chips, they're in electric cars, and they're powering AWS servers that host huge chunks of the internet.
When he was last on Decoder a couple of years ago, Rene called Arm the Switzerland of the electronics industry, thanks to how prevalent its designs are. But his business is getting more complex in the age of AI, as you'll hear us discuss. There have been rumors that Arm is planning to not only design but build its own AI chips, which would put it into competition with some of its key customers.
I pressed Rene on these rumors quite a bit, and I think it's safe to say he's planning something. When Rene was last on Decoder, he was about six months into the CEO job after Nvidia failed to buy Arm for $40 billion. After regulatory pressure killed that deal, Rene led Arm through an IPO, which has been tremendously successful for Arm and its majority investor, the Japanese tech giant SoftBank.
I asked Rene about that SoftBank relationship and what it's like working with its eccentric CEO, Masayoshi-san. I also made sure to ask Rene about the problems over at Intel. There have been reports that Rene looked at buying part of Intel recently, so I wanted to know what he thinks should happen to the struggling chipmaker.
Of course, I also asked about the incoming Trump administration, the U.S. versus China debate, the threat of tariffs, and all that. Rene is a public company CEO now, so he has to be more careful when answering questions like these. But I think you'll find a lot of his answers quite illuminating. I know I did. Okay, Arm CEO Rene Haas, here we go. Rene Haas, you are the CEO of Arm.
Welcome to Decoder. Thank you. This is actually your second time on the show, believe it or not. You were, I think, last on in 2022. You hadn't been the CEO for that long. The company had not yet gone public. So a lot has changed. We're going to get into all of that. You're also a podcaster now, so the pressure's on me to do this well.
Rene has a show where he interviewed Jensen pretty recently that you all should check out. The theme of this convo, we'll touch on several things. A lot has changed in the world of AI in the last couple of years, policy. We're going to get into all that and then the classic kind of decoder questions about how you're running ARM.
But first, I wanted to talk about a thing that I bet a lot of people in this room have been talking about this week, which is Intel. We're going to start with something easy. Great. What do you think should happen to Intel?
Oh, my gosh. I guess at the highest level, as someone who's been in the industry my whole career, it is a little sad to see what's happening from the perspective of Intel as an icon. The amount of innovation that Intel has provided, whether it's around computer architecture or fabrication technology, PC platforms, servers. Intel is an innovation powerhouse.
So to see the troubles they're going through is a little sad. But at the same time, you have to innovate in our industry. There are lots of tombstones of great tech companies that don't reinvent themselves. And I think Intel's biggest dilemma is just how to disassociate being either a vertical company or a fabulous company, to oversimplify.
And I think that is the fork in the road that they've faced for the last probably decade, to be honest with you. And Pat had a strategy that was very clear that vertical was the way to win. I will say that in my opinion, that when he took that strategy on in 2021, that was not a three-year strategy. That's a five to 10-year strategy.
So now that that's been, at least he's gone and there's a new CEO to be brought in, that's the decision that has to be made. My personal bias says that Vertical integration is a pretty powerful thing. And if they could get that right, I think they would be in an amazing position. But the cost associated with it is so high that it may be too big of a hill to climb.
We're going to talk about vertical integration as it relates to ARM later, but I wanted to reference something you told Ben Thompson earlier this year. You said, I think there's a lot of potential benefit down the road between Intel and ARM working together. And then there were reports more recently that you all actually approached Intel about potentially buying their product division.
Do you want to work closer with Intel now, what's gone on in the last couple of weeks?
Well, a couple of things with Intel. I'm not going to comment on the rumors that we're going to buy them. But I think, again, if you're a vertically integrated company and the power of your strategy is the fact that you have a product and you have fabs, inherently, you have a potential huge advantage in terms of cost. versus the competition.
And when Pat was the CEO, I did tell him more than once, you ought to license ARM, because if you've got your own fabs, fabs are all about volume, and we can provide volume. I wasn't successful in convincing him to do that, but I do think that would not be a bad move for Intel.
On the flip side, I think in terms of ARM working with Intel, we work really closely with TSMC, we work really closely with Samsung, and IFS is a very, very large effort for Intel in terms of external customers. So we work very closely with them to enable them to ensure that they have access to the latest technology. We have access to their design kits.
So we want external partners who want to build at Intel to be able to use the latest and greatest ARM technology. So on that context, we work closely with them.
Turning to policy, a few things I want to get into, but do you have any reaction to David Sachs being Trump's AI czar? I don't know if you know him.
I do know him a little bit. Kudos to him. I think that's a pretty good thing. I think it's quite fascinating that if you go back eight years to Trump 1.0 in terms of where we were in December as he was starting to fill out,
His cabinet choices and appointees it was a bit chaotic and also at the same time There wasn't a lot of representation from the tech world and I think this time around whether it's Elon whether it's David Whether it's Vivek. I know Larry Ellison has been very involved in terms of discussions with the administration. I think it's a good thing, to be honest with you.
Having a seat at the table and having access to policy, I think is really good.
I would say few companies face as many geopolitical policy questions as you guys, just given all of your customers. How have you or would you advise the incoming administration on your business?
I would say, not just for our business, but let's talk about China for a moment. The economies of the two countries are so inextricably tied together that a separation of supply chain, a separation of technology is a really difficult thing to architect.
So I would just say that as this administration or any administration comes into play and looks at policy around export control and such, be mindful that a hard break isn't as easy as it might look on paper. And there's just a lot of levers to consider back and forth. We are one attribute in the supply chain. But if you think about what it takes to build a semiconductor chip... There's EDA tools.
There's the IP from ARM. There's the fabrication. There's the companies like NVIDIA, Mediatek that build chips. But then there's raw materials that go into building the wafers and the ingots and the substrates, and they come from everywhere. So it's just such a complex problem that's so inextricably linked together that I don't believe there's a one-size-fits-all policy.
And I think administration's being open to understanding that There just needs to be a lot of balance in terms of any solution that's put forward.
What's your China strategy right now? I was reading that you're maybe working kind of to directly offer your IP licenses in China. You have a subsidiary there as well. Has your strategy in China shifted at all this year?
No. I mean, the only thing that's probably changed for us in China, and I would say that's probably for a lot of the world, is that China used to be a very rich market for startup companies. And venture capital flew around very freely. There was a lot of innovation and things of that nature. That has absolutely slowed down, whether that is the exit
for these companies isn't as clear, whether from a stock market standpoint, whether it's getting access to key technology isn't as well understood. We've seen that definitely slow down. On the flip side, we've seen incredible growth in segments such as automotive. If you look at companies like BYD or even Xiaomi,
building EVs, the technology in those vehicles is just unbelievable in terms of its capability. And selfishly for us, they all run on ARM. And the reason for that is, and China is very pragmatic in terms of how they build their systems and products. They rely very heavily on the open source global ecosystem for software. And
All of the software libraries have been tuned for ARM, whether it's ADAS or in the powertrain or IVI, that's all ARM based. So we have our automotive business in China is really strong.
Does President-elect Trump's rhetoric on China and tariffs specifically worry you at all as it relates to ARM?
Not really. I think my personal view on this is that the threats of tariffs are a bit of a tool to get to the negotiating table. I think President-elect Trump has proven over time that he is a businessman, and tariffs, I think, are one lever to start a negotiation. We'll see where it goes, but in my belief, I'm not too worried about that.
What do you think about the efforts by the Biden administration with the CHIPS Act to bring more domestic production here? And do you think we need a Manhattan project for AI like OpenAI has been pitching?
I don't think we need a government OpenAI Manhattan-type project. I think the work that's being done by OpenAI or Anthropic or even the work in the open source that's being driven by Meta with Llama, we're seeing fantastic innovation on that. I think if you look and say... Is the U.S. a leader in terms of foundation models and frontier models? Absolutely, yes.
And that's being done without a government intervention. So on the AI theme, I don't think it's necessary, personally. On the area of fabs, going back to the question that you started me on with on Intel, spending $30 to $40 billion a year in CapEx for these leading-edge nodes, that is a hard... pill to swallow for any company.
And that's why Chips Act, I think, was a good and necessary thing because building semiconductors is fundamental to our economic engine. We learned that during COVID when it took 52 weeks to get a key fob replaced in terms of everything going on with supply chain. So I think having supply chain resiliency is super important. I think it's super important on a global level.
It's definitely important on a national level. So I was and am in favor of the CHIPS Act.
So even if we have the capital potentially to invest more in domestic production, do we have the talent? That's a question that I think about. And I've heard you talk about, you know, you spend a lot of time trying to find talent and it's scarce. If we even spend all this money, do we have the people that we need in this country to actually win and make progress?
I think one of the things that's happening is a real raise of visibility on this talent issue. And I think putting more and more money into university programs around semiconductors, semiconductor research is helping. I think that for a number of years, semiconductors and particularly manufacturing was not seen as the most attractive of degrees to go off and get.
A lot of people were looking at software as a service and things in other areas. So I think we need to get back to that on the university level. Now, one could argue if AI bots and agents can come in and do meaningful work, maybe that helps. But
I think in the area of building chips and semiconductor process, that is very much an art as well as a science, and particularly around improving manufacturing yields. So I don't know if we have enough talent, but I know there's a lot of effort now going to try to bolster that.
We have to take a quick break. We'll be right back.
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Turning to Arm's business, you have a lot of customers, all of the big tech companies. So you're exposed to AI in a lot of ways. You don't really break out as far as I know exactly how AI contributes to the business. But can you give us a sense of where the growth is that you're seeing in AI and for Arm?
Yeah, I think one of the things we were talking about earlier was we are now a public company. We were not a public company in 2022. So one of the things I've learned as a public company is break out as little as you can possibly can. So nobody can ask you questions in terms of where things are going.
Well, I'm asking now.
Yeah, I know you are. So I would say this, no, we don't break any of that stuff out. But what we are observing is that, and I think this is only going to accelerate, is whether you're talking about an AI data center or you're talking about an AirPod or a wearable in your ear, there's an AI workload that's now running and that's very clear.
This doesn't necessarily need to be chat GPT-5 running six months of training to figure out the next level of sophistication. But this could be just now you want to run a small level of inference that is helping the AI model run wherever it's at. So we are seeing AI workloads, as I said, running absolutely everywhere. So what does that mean for ARM?
So our core business is around CPUs, but we also do GPUs. We also do NPUs, neural processing engines. And what we are seeing is the need to add more and more compute capability to accelerate these AI workloads. We're seeing that kind of as table stakes. Either put a neural engine inside the GPU that can run acceleration or make the CPU more capable to run extensions that can accelerate your AI.
We are seeing that everywhere. And I think that I wouldn't even say that's going to accelerate. That now is going to be the default. So what you're going to have is from the tiniest of devices at the edge to the most sophisticated data centers, an AI workload is going to be running on top of everything else that you had to do, right?
So if you look at a mobile phone or a PC that has to run graphics, it has to run a game, it has to run the operating system, it has to run the apps. And oh, by the way, it now needs to run some level of co-pilot or it needs to run an agent. It's good for us because what that means is I need more and more compute capability inside a system that's already kind of constrained on cost.
It's kind of constrained on size. It's kind of constrained on area. But it's great for us because it gives us a bunch of hard problems to go off and solve. But that's clearly what we're seeing. So I would say AI is everywhere.
There was a lot of chatter going into Apple's latest iPhone release about this AI super cycle with Apple Intelligence and this idea that Apple Intelligence would reinvigorate iPhone sales and the mobile phone market in general is plateaued. When do you think AI, on-device AI, really does begin to reignite the growth in mobile phones? Because right now it doesn't feel like it's happening.
And I think there's two reasons for that. One is the... models and the capabilities are advancing very fast. And the capability of the model is advancing how you manage the balance between what runs locally, what runs in the cloud, things around latency and security. It's moving at an incredible pace.
I think OpenAI, and I was in a discussion with the OpenAI guys last week, they're doing the 12 days of Christmas. 12 days of shipments. 12 days of shipments, yeah. And they're doing something every day. It takes two or three years to develop a chip, right? So think about the chips that are in that new iPhone when they were conceived.
and when they were designed and when the features that were thought about that had to go inside that phone. ChatGPT didn't even exist at that time. So I think this is going to be something that is the classic, it's going to be gradually and then it's suddenly. You're just going to see sort of a knee in the curve moment where the hardware is now sophisticated enough and then the apps rush in.
What is that shift? Is it a new product? Is it a hardware breakthrough? A combination of both?
Well, I think, as I said, one of the things that we're seeing is that whether it's a wearable or a PC or a phone or a car, the chips that are being designed are just being stuffed with as much compute capability to take advantage of what might be there. So it's a bit of chicken and egg relative to you load up the hardware with as much capability, hoping that the software lands on it.
And the software is innovating at a very, very rapid pace. But that intersection will come where suddenly, oh my gosh, I've shrunk the large language model down to a certain size. The chip that's going in this tiny wearable now has enough memory to take advantage of that model. And as a result, the magic takes over. And that will happen. It will be gradual and then sudden.
Are you bullish on all these AI wearables that people are working on? I know Arm is in the MetaRay bands, for example, which I'm actually a big fan of. I think that form factor is interesting. AR glasses, headsets, do you think that is a big market that's coming? I do.
Yeah, I do. It's interesting because many of the markets that we have been involved in, whether it's mainframes to PCs to mobile and then wearables or watches... Some new form factor drives some new level of innovation. It's hard to say what that new next form factor looks like.
So I think it's going to be more of a hybrid situation, whether it's around the glasses or around devices in your home that are more of a push device than a pull device instead of... asking Alexa or asking Google Assistant what to do, you may have that information pushed to you. You may not want it pushed to you, but it could get pushed to you in such a way that's looking around corners for you.
And I think the form factor that that comes in, I think will be somewhat similar to what we're seeing today, but you may see some of these devices get just much more intelligent in terms of, as I said, in the push level.
That makes me remember there's been reports that Masa, your boss at SoftBank, has been working with Johnny Ive and OpenAI or a combination of the three to do hardware. And I've heard rumors that there could be something for the home. Is there anything there that you're working with that you can talk about here? Yeah, I read those same rumors. Yeah, okay, good.
Amazon just announced that it's working on the largest data center for AI with Anthropic. And Arm is really getting into the data center business. What are you seeing there with the hyperscalers and their investments in AI?
Well, the amount of investment that's going on is through the roof. You just have to look at the numbers of some of the folks who are in this industry. And I think it's a very interesting time because right now we're still seeing an insatiable investment in training. Training is hugely compute intensive. It's hugely power intensive. And that's driving a lot of the growth.
But the level of compute that will be required for inference is actually going to be much larger. I think it'll be Better than half, maybe 80% over time would be inference. But the amount of inference cases that we'll need to run are far larger than what we have today.
So I think that's why you're seeing companies like CoreWeave and Oracle and people who are not traditionally in this space who are now running AI cloud. Well, why is that? Because... capacity. The traditional large hyperscalers, the Amazons, the Metas, the Googles, the Microsofts, there's just not enough capacity.
So what I think we'll continue to see is a changing of the landscape, maybe not a changing so much, but certainly opportunities for other players in terms of enabling and accessing this growth. And for ARM, it's very, very good because we've seen a very, very large increase in growth in market share for us in the data center, AWS at reInvent,
this week who build their general purpose devices, Graviton, based on Arm. They say that 50% of all new deployments are Graviton. So 50% of anything new at AWS is Arm. And that's not going to decrease. That number is just going to go up. And I think one of the things we're seeing, whether it's devices like Grace Blackwell from NVIDIA.
Grace, which is the CPU, and that's ARM, using an NVIDIA GPU, that's a big benefit for us because what happens is the AI cloud is now running a host node based on ARM. And if the data center now has an AI cluster where the general purpose compute is ARM, They naturally want to have as much of the general purpose compute that's not AI running on ARM.
So what we're seeing is just an acceleration for us in the data center, whether it's AI or inference or general purpose compute.
Are you worried at all about a bubble with the level of spending that's going into hyperscaling to the models themselves? It's an incredible amount of capital. ROI is not quite there yet. You could argue it is in some places. But do you ascribe to the bubble fear?
On one hand, it would be crazy to say that growth continues unabated, right? We've seen, obviously, that that is never really the case. I think what will get very interesting in this particular growth phase is to what level does real benefit come from AI that can augment and or replace certain levels of jobs? You know, some of the AI models and chatbots today are decent, but not great.
They supplement work, but they don't necessarily replace work. But if you start to get into agents that can do real level of work that can replace what people might need to do in terms of thinking and reasoning, then that gets fairly interesting. And then you say, well, how's that going to happen? Well, We're not there yet, so we need to train more models.
The models need to get more sophisticated, et cetera, et cetera. So I think the training thing continues for a bit, but I can see as we get to some level of AI agent that reasons close to the way a human does, then I think it asymptotes on some level.
I don't think training can be unabated because at some point in time, you get more now into specialized training models as opposed to general purpose models, and that requires less resources.
I was just at a conference where Sam Altman spoke and he was really lowering the bar on what AGI will be pretty intentionally. Has talked about declaring it next year. I cynically read into that as them trying to rearrange their profit sharing agreement with Microsoft. But putting that aside, what do you think about AGI when we will have it? What it will mean?
Is it going to be an all at once big bang moment? Or is it going to be as Altman now is talking about more like a whimper?
I know he has his own definitions for AGI and he has reasons for those definitions. I don't subscribe so much to what is AGI versus ASI, artificial superintelligence, but I think more around when these AI agents start to think and reason and invent. And to me, that is a bit of a cross the Rubicon moment, right? For example, Chat GPT can do a decent job of passing the bar exam.
But to some extent, you'd say load enough logic and load enough information into the model, and the answers are there somewhere. And to what level is the AI model a stochastic parrot and just repeats everything that it has found over the internet? Because at the end of the day, you're only as good as the model that you've trained on is only as good as the data.
But when the model gets to a point where it can think and reason and invent, create new concepts, new products, new ideas, to me, that's kind of AGI when you get to that level. And I think, I don't know if we're a year away, but I would say we are a lot closer. If you would ask me this question a year ago, I would have said it's quite a ways away.
You ask me that question now, I say it's much closer. What is much closer, two years, three years? Probably. And I'm probably going to be wrong on that front. You know, every time I interact with some of the partners who are working on their models, whether it's at Google or OpenAI, and they show us the demos, it's breathtaking in terms of the kind of advancements that they're making.
So, yeah, I think to getting to a model that can think and reason and invent, we're not that far away.
We're going to take another quick break. We'll be right back.
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We're back with Arm's CEO, Rene Haas, discussing the future of AI. Before the break, I asked Rene about his thoughts on the AGI debate. But there's one really crucial question I've wanted to ask him this whole time. Is Arm going to build its own AI chips? When you were last on Decoder, you said ARM is known as the Switzerland of the electronics industry.
But now there's been a lot of reports this year that you were looking at really going up the stack and designing your own chips. And I've heard you not answer this question many times, and I'm expecting a similar non-answer, but I'm going to try. Why would Arm want to do that? Why would Arm want to go up the value chain?
Yeah, this is going to sound like one of those if I did it answers, right? So I got to be thinking about why would Arm consider doing something other than what it currently does? I'll go back to the first discussion we were having relative to AI workloads. What we are seeing consistently is that AI workloads are being intertwined with everything that is taking place from a software standpoint.
So we are, at our core, we are a computer architecture. That's what we do. We have great products, our CPUs are wonderful, our GPUs are wonderful, but our products are nothing without software. The software is what makes our engine go. If you are defining a computer architecture and you're building the future of computing,
One of the things you need to be very mindful of is that link between hardware and software. And that link in terms of really understanding where the tradeoffs are being made, where the optimizations are being made, what are the ultimate benefits to consumers from a chip that has that type of integration, that is easier to do if you're building something than if you're licensing IP.
just from the standpoint that if you're building something, you're much closer to that interlock and you have a much better perspective in terms of the design trade-offs to make. So if we were to do something, that would be one of the reasons we might.
Are you worried at all about competing with your customers, though?
Well, I mean, my customers are Apple. I don't plan on building a phone. My customer is Tesla. I'm not going to build a car. My customer is Amazon. I'm not going to build a data center.
What about NVIDIA? You used to work for Jensen.
Well, he builds boxes, right? He builds DGX boxes, and he builds all kinds of stuff.
Speaking of Jensen, we were talking about this before we came on. When you were at NVIDIA, CUDA was really coming into fruition. And you were just talking about the software link. How do you think about software as it relates to ARM and as you're thinking about going up the stack like this? Is it lock-in? What does it mean to have something like the CUDA?
Yeah, lock-in is a... It's either one can look at it as an offensive maneuver that you take and I'm going to do these things so I can lock people in and or you provide an environment in such that it's just so easy to use your hardware that by default you then quote locked in. Let's go back to the AI workload commentary.
So today, if you're doing general purpose compute, you're writing your algorithms in C or JAX or something of that nature. And now you're, let's say, wanting to write something in TensorFlow or Python. In an ideal world, what does the software developer want?
Software developer wants to be able to write their application at a very high level, whether that is a general purpose workload or an AI workload, and just have it work on the underlying hardware with not really having to know what the attributes are of the underlying hardware. I don't know if there's any software people in the room. Software people are wonderful.
They are inherently lazy and they want to be able to just have their application run and have it work. So as a computer architecture platform, it's incumbent upon us to make that easy. So when we think about providing a heterogeneous platform and homogeneous across the software, that is a very big initiative for us. And we're doing it today.
We have a technology called Clyde and these are Clyde libraries for AI. And they do that for the CPU. All the goodness that we put inside our CPU products that allows for acceleration by using the libraries, and we make those available open. There's no charge. Developers, it just works.
So going forward, since vast majority of the platforms today are ARM-based and the vast majority are going to run AI workloads, we just want to make that really easy for folks.
I'm going to ask you about one more thing you can't really talk about before we get into the fund decoder questions. I know you've got this trial with Qualcomm coming up. You can't really talk about it. At the same time, I'm sure you feel the concern from investors and partners about what will happen. Address that concern.
You don't have to talk about the trial itself, but address the concern that investors and partners have about this fight that you have.
Yeah, so the current update is that it plans to go to trial on December 16, which isn't very far away. And I can appreciate, because we talk to investors and partners, that what do they hate the most is uncertainty. So that I can appreciate. But on the flip side, I would say the principles as to why we filed the claim are unchanged. And that's about all I can say.
All right, more to come there. So decoder questions. Last time you were on the podcast arm had not yet gone public. I'm curious to know now that you're a couple years into being a public company. What surprised you about being a public company?
I think what surprised me on a personal level is the amount of bandwidth that it takes away from my day that I end up having to think about things that we weren't thinking about before. But at a highest level, it's actually not a big, big change. From the perspective of Arm, Arm was public before. When SoftBank bought us, we still consolidated up through SoftBank.
So the muscles in terms of being able to report quarterly earnings and have them reconciled with a timeframe, all of that, we had good muscle memory on that. So I think operationally for the company, we have great teams. I have a great finance team that's really good at doing that.
I think for me personally, it was just maybe the appreciation that there's now a chunk of my week that's dedicated to activities that I wasn't really working on before.
Has the structure of Arm organizationally changed at all since you went public?
No, I am a big believer of not doing a lot of organizational changes. To me, organizational design follows your strategy, and strategy follows your vision. And if you think about the way you've heard me talk about Arm publicly for the last couple of years, that's pretty unchanged. So as a result, we haven't done much in terms of changing the organization.
I think organization changes are horrendously disruptive. We're an 8,000-person company, so we're not gigantic. But if you do a gigantic organization change, it better have followed a big strategy change. Otherwise, you've got off-sites and team meetings and Zoom calls about talking about my new leaders. And if it's not in support of a change of strategy, it's a big waste of time.
So I really try hard not to do much of that.
Well, what we talked about earlier with potentially looking at going more vertical or the value there, that seems like a big change that could affect the structure.
If we were to do that.
If you were to do that, yeah. Is there a trade-off that you've had to make this year in your decision-making that was particularly hard and something you can talk about, something that you had to wrestle with, and how did you weigh those trade-offs?
I don't know if there was one specific trade-off. I think in this job, a CEO, which I've been now, gosh, it'll be three years in February, you're constantly doing the mental trade-off of what needs to happen in the day-to-day versus what needs to happen five years from now. My proclivity just tends to be to think five years ahead as opposed to thinking one quarter ahead.
So I don't know if there's any major trade-off that I would say that I make, but what I'm constantly wrestling with is that balance between what is necessary in the day-to-day versus what needs to happen in the next five years. Because I've got great teams. I've got the engineering team is fantastic. The finance team is fantastic. Sales and marketing, they're great.
So in the day-to-day, there isn't a lot I can do to impact what those jobs are, but the jobs that I can impact is the next five years. So where I try to do is spend areas of time for me personally, of work only I can do. And if there's work that the team can do that I'm not going to add much to it, I try to stay away from it.
But that's the biggest trade-off I wrestle with is the day-to-day versus the future. How different does Arm look in five years? I think we don't know that we look very different as a company, but hopefully we are continuing to be an extremely impactful company in the industry. I have big ambitions for where we can be.
I'd love to know what it's like to work with Masa. He's your largest shareholder. He's your board chair. I'm sure you talk all the time. Is he as entertaining in the boardroom as he is in public settings?
Yes. Yeah, he is. He's a fascinating guy. One of the things I admire a lot about Masa, and I don't think he gets enough credit for this, is that he's the CEO and founder of a 40-year-old company. And he's reinvented himself a lot of times. I mean, SoftBank started out as a distributor of software. And he's reinvented himself from being an operator, whether it's SoftBank Mobile, to an investor.
He's a joy to work with, to be honest with you. I learn a lot from him. He is very ambitious, obviously, loves to take risks. But at the same time, he has a good handle on the things that matter. So he's, yeah, I think everything you see about him is accurate. He's a very entertaining guy.
How involved is he in setting Arm's long-term future with you?
Well, he's the chairman of the company, right? He's the chairman of the board. So from that perspective, if you think about the board's job is to evaluate the long-term strategy of the company and my proclivity towards thinking, you know, also in the long-term, he and I talk all the time about those kinds of things.
You've worked with two very influential tech leaders, Masa and Jensen at NVIDIA. What are the unique traits of both of them?
That's a wonderful question. I think Jensen, Masa, Larry Ellison, Jeff Bezos, I'm sure I'm leaving out names, people who built a company and are running it 20, 30 years later and drive it with the same level of passion and innovation, carry a lot of the same traits.
And those traits are obviously very intelligent, obviously brilliant, looking around corners, work incredibly hard, but have an incredible amount of courage. And I think that is all, those ingredients are necessary for people who stay at the top that long. I'm a big basketball fan and I've always drawn analogies between, if you think about basketball
a Michael Jordan or a Kobe Bryant when people talk about what made them great. Obviously, their talent was off the roof and they had great athleticism, but it was something in their character and their drive that cut them in a different level. And I think Jensen, Massa, Larry Ellison, the other names I mentioned, they all fall in the same group. Elon Musk, obviously.
All right. Well, we're going to leave it there for the podcast. Thank you so much. I'd like to thank Renee for taking the time to speak with me, and thank you for tuning in. I hope you enjoyed it. If you'd like to let us know what you thought about this show or what else you'd like us to cover, drop us a line. You can email us at decoderattheverge. We really do read every email.
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Our producers are Kate Cox and Nick Statt. This episode was edited by Travis Larchuk and Callie Wright. Our supervising producer is Liam James. The Decoder music is by Breakmaster Cylinder. See you next time.
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