Broadcom Inc. (AVGO) Earnings Call Transcript & Summary

All right. Good afternoon. We have a standing room-only session. Good afternoon. Welcome. I'm Vivek Arya. I lead the BofA semiconductor semi-cap equipment research team. And I'm really delighted and honored to have our keynote speaker Hock Tan, President and CEO of Broadcom. Under Hock's leadership, Broadcom has become the most profitable semiconductor company on the planet, 50% plus free cash flow margins. very diversified portfolio across wireless, across wired, AI, networking, storage, infrastructure software. So I'm really delighted to get the opportunity to chat with you, Hock. Thank you for [ joining ] our conference.

Happy to be here.

Thank you. So maybe Hock, just let's start with the state of the union. A lot of mixed messages from the macro environment consumer, a bit softer, but some of the investments in data center is somewhat stronger. So how do you see things right now versus what you thought at the start of the year?

Well, our thinking since the start of the year hasn't changed. Now first and foremost, we are largely in enterprises infrastructure. We do very little consumer with the exception of our wireless business. Other than that, it's all and infrastructure for data -- for hyperscale, telcos and enterprises, very much. So -- and what we figured is '21, '22 were very strong growth years. We all see that. And it was one of those up cycles in the semiconductor industry is one way to look at it. But largely, to some extent, triggered by COVID, but it was extraordinary -- they were extraordinarily strong. And we displayed a big part of that, too. We always thought '23 would be when things level off. And frankly, later in the beginning of fiscal year, which was November last year, if you ask me, my thought would be '23 could be the point, the tipping point when our industry, the IT industry, especially for infrastructures that rolling over. And we enter, what I call, a recession in the industry. We haven't seen it yet. And we have seen fiscal '23 kind of moderated a lot, slow down. And when we reported our results, Q2 was -- Q2 was still moving quite okay in the semiconductor space, high single digits, close to 10%. But Q3 and probably Q4 would definitely slow down year-on-year growth. But as I said, it's a slowdown in the growth rate. It's not a rollover. And we get -- I get a sense that we won't see that roll over in '23 in terms of demand, in terms of what we will see out there because we are shipping, as I've said before, constantly, even 2 years back, to today. We're only shipping to what as much as we can determine our end customers will consume. And I guess the bottom line to what this is indicating to me is consumption, deployment of our technology is still at the high level. It may not be growing as fast as '22 or '21, but it's holding up.

Good. Hock, what do you think has helped Broadcom to grow this year or is helping Broadcom to grow this year versus a decline in the broader semiconductor industry, including many of your peers, right, who are exposed to the enterprise environment?

I think the simplest answers, if you look at that whole thing is -- and you can extend it to the broader perspective of our entire semiconductor industry where it's known as a cyclical industry. And maybe I'm trying to prove to the world, it really should not be a cyclical industry because when you think about it, underlying fundamental demand as measured by -- to the extent you can measure conceptually consumption of the customers, and I'm talking particularly infrastructure, obviously, no position on consumer. Our exposure is limited, is that it's always growing for years to a -- with certain exceptions towards the [indiscernible] maybe not as fast as the market as the industry matures, still growing. But then where does the cycles come from. We used to believe use -- I used to believe that's because supply comes in discrete large chunks. So when a tipping point happens where demand exceeds supply in a particularly extreme way. It's -- you start to get a trigger cycle. And what happens is when there's a shortage of supply, customers' behavior. They behave in a manner that says, I'm rushing for whatever products I can lay my hands on. So they place excessive demand out there, excessive purchase orders. And if you ship to your customer -- those panic customers are doing, it's great. But then when the cycle is over, when supply catches up, guess what, you will have all that inventory, you have shipped out to digest and then you go plunging down. But if you never ship to one -- Day 1 rather ship to what day you think they should actually consume. Then I guess you will actually trace that steady growth rate. And I believe that's what we're seeing in '23. And we like to believe in '21, '22, we were shipping very closely to consumption, and we're doing the same in '23.

How do you put those checks in place? Because I mean, you have some of the largest hardware customer -- some of the largest customers. So if they come and say, I need 20 of this widget versus 10. How do you say, no, we should really be giving you 10? How do you make that judgment?

I guess, there's no hard and fast rule. It's really about being very closely engaged with the customer in a more architectural manner in a more strategic deeper manner than basically shipping just to what procurement tells you they want supply. So in a sense, it's about relationships, but it's also about the kind of products you are shipping. If you're shipping to a core product, it's probably easier to get that level of engagement, then be shipping, building block products. Then you tend to be kind of in the periphery.

Got it. So let's -- we will dig deeper into your AI portfolio, but...

You know it was coming.

But before we get to the specific aspects of the portfolio, when you look at the overall spending environment, Hock, that doesn't seem to be growing to the same extent that AI is growing. So do you see that push and pull that customers are just putting so much more emphasis there, so something else has to suffer disproportionately also?

I don't know the answer to that because obviously, I -- it's not clear in this early stage of the AI, generative AI, especially surge that's going on that we're seeing clear trade-offs. That could be, you're right. But it's not clear to us. If there is -- if they are pushing up what you call traditional IT spending, just so that they can invest in AI, and I'm referring in particular to basically the hyperscale. Enterprises, not sure at all. I don't think enterprises are really jumping in and investing in AI in a big -- in the way the hyperscalers are doing.

Got it. So Hock, you've been in the industry for such a long time, you have seen many of these hit or hype cycles come and go. What's your gut? Do you think generative AI is a long-term successful investment? Or do you think it's too early to make that call today?

I don't know. It's too early. How -- what you are saying, how sustainable it is?

That's right.

Well, AI is something that's been going on for a long time, right? Businesses, companies have been steadily investing in -- we used to call it, what, analytics, then became AI, then machine learning, Now generative AI. It's all putting a label on what is essentially the ability to try to do a better job of figuring out what's going on in our businesses and in the world around us. And so generative AI seems to have kicked things up a notch because it's literally trying to scale out, trying to scale out in a massive manner. Large databases to get us to experience that's totally different one used to be. But it's been more, I call it, it's an evolution. So this evolution will continue. And when you ask, is this sustained? My rather straightforward this and generous answer is, yes, of course, it will, and you'll keep growing more and more. But will it go up at the scale we're seeing today? Can't tell, I don't know.

Got it. So what was the genesis of your Broadcom's involvement in the AI? So you have had, right, very strong expertise in compute offload ASICs for a while. So did that investment start because a customer came and engaged with you? Or did you have that vision or foresight that look, AI is going to be a big thing? How did your involvement start in AI?

There wasn't any vision here, I show you, no. The vision is very simple. We have a vision. We're not totally blind, guys. But the simple vision of our business is, we have 22 different product divisions. 17 of them, be very false. I'm just putting in context in semiconductors. And you know our business model. We only -- each of this business division are doing products in a specific vertical in technology, in the semiconductor industry, very narrow vertical in some situation where we have -- where we've been added for many, many years and where we are -- we have a leadership position. If we're not in a leadership position, technology markets we don't play in that game. And we are 17 of it where we are. And within that 17, I assure you, compute is not any computing, whether it's an ARM, CPU, x86 or GPU, which I consider is computing, we're not in that game. There are other players there who have been doing it for much longer. And that ties into our business model. We do want -- we are very good at doing and where we foresee by investing and continually driving it hard to be continuing in the lead on a road map in any particular areas we are in, and you know the areas we are in, in particular, networking, switching, routing, among other areas and other which you know about. So this is not an area we're in. But one of the areas in the 22 division that we are -- we feel very good about is basically creating Intel IP cores in silicon, Intellectual IP cores for connectivity, for networking. I'd like to use the word connectivity of all types at very leading-edge stages of the technology. And we use silicon, and we're very good at implementing leading-edge silicon. And as part of it, we are very good at converting and designing highest performance type analog components into digital, which is then used across the rest of the company whether it's in broadband, RF, networking, storage, the highest technology. So this division that does ASICs was approached many years ago by one hyperscaler to get -- to try to develop an AI engine, a very dedicated AI engine focus on the models of that particular hyperscale, very dedicated, very team optimized [indiscernible] where we are, took a lot of work, took some level of investment, but it's -- our IP really relates to our ability to manifest in silicon, what is a very complicated AI training chip and inference chip. And that's how we got into it. It's true being able to having the technology and the skills to create silicon, not an architectural definition play that says -- or vision that says, hey, AI is the place to be in. We don't do computing typically. We're not -- and it's not an area not to say we can't do it. It's not an area where we want to come in and compete against players who have been focused on doing it much longer and will probably out invest us in those space.

Got it. How broad -- Hock, so we know that you have 1 large customer, right, in that compute offload business. What are your plans to diversify that business, right, with other hyperscalers? Do you see other hyperscalers also having the same intention to have that kind of large internal solution to compete with the GPU alternative, as an example?

Hyperscalers, big companies always have this after a while gets into this aspirational intention to consider, hey, I could do a chip better focus on my model than what's out there in merchant. That typically happens until they get into it and the water is freezing and boiling. It's not that easy because you do not only do 1 chip, 1 generation that you feel the need to do it. Once you're in it, you got to do the next generation and the next, and the next. It never stop because if you stop, then what are you going to do and keep using the older generation there's merchant silicon out there who is probably -- who is continuing to progress. And so your competitors will be using the better product than you are, so careful about going in. It doesn't stop a lot of large hyperscalers from doing it. Having said that, and you all have seen it. We have new -- there's always a news. In truth, it's a much, much less phenomenon than we all think it is because many of these guys know it needs a lot of investment. It needs a lot of focus, and that's not their business model. At the end of the day, and you want to compete against a semiconductor, focused semiconductor business with lots of investment and who is doing it for the entire industry, that's hard. Now having said that, many of the hyperscale have a lot of resources, very smart people, a lot of need. So they will always like to try. It doesn't mean they will succeed.

Got it. So when they come to you and say, we want to engage with you, how do you put some sense into that relationship? So what is it that once you have a 1- or 2-year visibility, then you're like, okay, whatever you want to do.

We go by financial return, right? My model is all financial, if they're willing to pay for my engineering. I might consider it. But at the end of the day, that's not -- I'm not never going to out-guess, out-argue to a customer that his model is not a smart model. If it's willing to pay, I'm happy to do it.

Makes sense. So when you look at the long-term kind of mix between general purpose versus an ASIC solution, do you think it stays where it is? Or do you think that the trend is a lot more towards general purpose over time?

I don't know about AI. What I may tell you, historically, on the products we have done, Broadcom. As you noticed, I have 17 semiconductor divisions. Effectively, only 1 is in ASICs, got some silicon, that's 16 others. And they're all merchant silicon. Where do you think I'm going to likely come out in my experience. Merchant silicon tends to prevail long term. Now long term, might take a while because some of my customers are very rich, and they are very ambitious and they're willing to do it. So I'm happy to oblige because I have a division, they focus on doing the best they can for their customers, and it's still consistent with the model we have.

Got it. The complementary part of those accelerators is networking. And I think you mentioned the goal to kind of almost quadruple your switching sales tied to generative AI to almost $800 million this year. What's helping that because that's a very significant growth rate, right? It's in fact, a higher growth rate than we even seen the accelerated businesses for some of the other players.

Well, yes, because what is happening is, I mean -- for the last several years, as more and more enterprises and that includes cloud guys, put in more resources and then many -- some of the cloud guys have been running AI networks, clusters of AI that need to be networked together. We have been supplying products, networking switches, fabric that enables clusters of AI engines to work together and larger and larger scale as the models for basically -- models for predicting for analytics skips growing bigger and bigger. We have been broadening it up. And -- but for years, high-performance computing, which is another way of calling AI, by the way, used to be called HPC high-perform computing, and we all call it AI, then we call it something -- machine learning, and now it's back to AI, generative AI, whatever it is, the scale is growing. And one is particularly clear is AI networks, AI workloads are different, High-performance computing workloads and which is it's what they call elephant workloads. It means unlike traditional IT infrastructure, when [ HID6 ] run in your data centers in your company. The number of workloads is much simpler, much less. AI workloads tend to be large, good reason they're called elephant workloads, huge workloads. And when you want to then run AI models through clusters of AI compute engines because each of those engines is now no longer big enough high performance enough to run those large database to create those -- to get any good outcomes from those large models. You need to network them. And then you find -- you need a different kind of network because you need those workloads to run faster, they are larger workloads and to get full output in terms of performance from your GPU or TPU. You really want the network to be able to match the performance of the GPU that keeps improving. And you don't have to, but only means you run your GPU slower and you're happy with a lot smaller models. Then last year, generative AI showed up with Open AI and ChatGPT, where they talk about taking huge database, large language models, LLM, as we call it now, and load it all into this massive computer -- computing machine to be able to literally create analytics out of a huge database, especially in training. And you need to do it with lots -- you hear about lots and lots of AI engines, which have to work in a synchronized manner. You have to network them, and then we suddenly see a demand starting last year, in particular, of different -- actually almost for us seeing almost for the first time, we know about existing in some hyperscalers. We now see it for the first time that we need to create a different kind of product to optimize these kind of workloads. And since then, if nothing else, this has gone even more extreme when we hear about trying to inter network from -- used to be 4,000 nodes, which is GPU to 8,000, 16,000. And now we're talking about 32,000 by next end of this year, early next year. To do that, you need a whole new scale, you need a whole new, not just switching, you need a fabric. And that's what's pushing us now to step up to create almost to innovate on more advanced technologies to handle that. The unfortunate thing is we have all the -- most of all the building blocks of that technology in our -- within the company. A lot of it of what we do and what we're seeing here because when I think by AI, the theories behind AI has been around for a long time. And by the way, an ability to land work and run jobs completion in a training chip or in a cluster of training chips simultaneously and exchange parameters. It changes very efficiently so that by the time when you finish the exchange, you just finish the next job completion. That's a law to that and sort of a law of physics that makes this happen. That calls for a different kind of network that is one step higher performance than traditional data center networking. And we have the technology. So we're out there engaging with all the hyperscalers in helping them create in a much better way, this -- the AI networks to essentially optimize or utilize GPU engines or TPU engines, much more efficiently, effectively than what they have been able to do, just using regular networking. So that's a whole new step up, and it's been a great driver as we announced, and as you pointed out, to that business that relates to AI.

Right. Over time, what is the right way to think about growth in switching in that. So before I get to that question, how do you differentiate, Hock, between a switch that is a regular switch versus a switch that's for generative AI? Is it a certain port speed? Is it a certain SKU? How do you make that distinction?

Until we come up with the new products. Now last year, we came out quickly with a product in partnership with Arista Networks called the 7850 Arista. And that's Arista markets as an AI switch. That's clear because it's not a Tomahawk sitting in there. It's a Jericho, Why? Because the Jericho, which is used for routing in telco networks for the last 10 years, older generation, has a lot of the technology and architecture that is perfect for AI networks today. Just need to amp up the speed. But you have that. So it's like recycle the technology and take it in here quickly, and bingo, we got it for a Arista Network's only 7850. That's great. Now go that was 8,000, 4,000, 8,000 nodes. Now to go to 16,000, 32,000. So we have to come up with a new generation of Jericho AI switch, and we launched a Jericho3 AI, just to kick up the PR on it. It's really meant for AI switching the successor to the 7850 for use to some of the hyperscalers who wants to use Ethernet to drive their AI networks. And that's almost one question. When you go up to scale up so big, 16,000, 32,000, 64,000 is so much easier to use Ethernet. If you can make Ethernet meet certain criteria of loss less and high latency. Something Ethernet has not been good at doing, but InfiniBand has been very good at doing. InfiniBand's problem is scaling out that much is tricky. It's meant to scale out to the size and scale up. It's possible to be done. You just have to stage the architecture that makes it harder. Ethernet on the other side is just known to be just all out there. But it loses packets, and latency is not so good. So what we do is we put in the technology that makes it lossless and make the -- improve the latency to the level is acceptable. And one, it's meant by acceptable is that you can run 16,000 GPUs simultaneously exchange the data and keep running it, that's it. And that's a whole new scheme. So to answer your question, beginning to get clearer and clearer what is AI network switch, what is AI fabric versus non-AI fabric? But from that now it is. Before that, not so clear. You just -- we just have to engage with our customers who work with us and then you get a sense what they use for versus what they don't. Now fortunate thing is there are not that many customers out there.

Got it. Do you think customers are still investing in non-AI switches of Broadcom this year?

Of course. You got to run workloads. And it's a cycle. I mean many of the cloud guys, unless they want to swap their equipment and even then there's a limit in which they can swap their existing equipment you need to upgrade, you need to refresh, you need to expand to run a bigger thing because don't forget your AI networks are meant for very high-performance workloads. You don't necessarily want to use that network to run your traditional enterprise workloads, makes some sense.

What proportion, Hock, do you think roughly your workloads are AI-related at hyperscale today?

I have no clues.

Is it -- do you think it's like less than -- like if I were to take the proportion of your switch sales, right, versus overall sites, is that a reasonable way to look at that metric?

No, because I have an installed base by the billions that's still running traditional workloads. This new middle stuff is barely up and running. So this is not that huge compared to what's running on now. This -- the traditional workloads is still rail, solid. And if you look at my numbers for networking, strip out AI, I'm still growing in networking. Strip out my offload, strip up the $800 million this year, I still am growing. So it still is a need. Enterprise is still buying the thing. Even hyperscaler is still buying. They needed to run workloads.

Got it. Now traditionally, we have seen decisions on computing and networking kind of done a little bit separately, best-of-breed in each. In AI, do you think that just given the tight connection, right, and the low latency requirements, that does it give an edge to your GPU competitor because they have InfiniBand switches because they have a new Ethernet switch. Do you think just by the virtue of the fact that they have a larger share in accelerators, does it give them a chance to gain switching share versus Broadcom?

Best way to answer it because we're talking about a new phenomenon. But if we go back in history, I mean how many companies, semiconductor companies, in particular, have come out historically than many of you invest in semiconductors over the years have seen it. When -- just because they do a core chip, before you know it, they want to sell the whole platform. And I'm going to almost say it's not natural. And if you have seen over the years, platforms disappear because customers want flexibility and choices. Just why I say merchant gets to win at the end of the day, they want choices. They want a disaggregated and distributed model in data centers. And now in AI and generative AI, in particular, today, guess who are the customers? There are the bunch of the largest, smartest guys around the hyperscale. And guys want small enterprise, maybe they buy a black box and be done with it. Hyperscalers, no. They don't. They look at it, they assess it, and they want flexibility. And so -- which is why we engaged with them on AI networks.

And one last kind of technology topic that's also gaining some industry attention is the consideration of co-packaged optics, right, or whether the industry will stay with the current format, which is to use these pluggables with their separate DSPs, right? Where does Broadcom fall on that spectrum, right? Do you think it's going to be co-packaged optics in a big way? Or do you think those are niches where they make sense versus its pluggables for the most part?

Well, it's back to customers at the end of the day. I mean my whole business model is about addressing in technology and engineering what the customer wants. And by the way, I may not ship what they want, but I give them the technology they want. And it's basically this, it could exist both ways. Just like -- because some customers who prefer even as you offer co-packaged silicon like a fabric or switch and double the speed and yet a 10% reduction in power, double the speed. So you think for AI networks that will run at high performance, lots of power coming out. That power is becoming the constraint to building AI data centers in scale. You think they want co-packaging. The drawback with silicon photonics, which is called packaging, is effectively what it is, is the active components of fiberoptic modules that connects a switch to the server or to other switches is integrated into my switch, one big thing, cool, right, a lot of content, lower power, much better proximity performance better, all that nice stuff, yes . But guess what, pluggable optics gives more flexibility if you are building a data center, right? You may not want to populate the entire switch in day 1 is just on to populate maybe half. Well, you can, if you buy my co-package switch, I give you the whole thing. And so it's -- I can see that there are many situations where they don't want to co-package. In other situations, particular power constraints that they may use a co-package. And I've seen the cloud guys, they pick and choose to optimize their very heterogeneous data centers.

Now, Hock, the other way Broadcom has kind of been unique is through your investments in infrastructure software, right, whether it's for CA, whether it was Symantec or Brocade. How would you grade those investments, if you take a look back, like -- so if you go back to what was your original strategy about investing right and diversifying outside of semiconductor, right, versus the results that you have seen, how would you kind of grade those investments?

Software is a great financial business for us. It has been. I mean, we make great margin, great cash flow and bloody pay your dividends, guys. It is. I don't have to touch the semiconductor guys at almost pay your dividends every year. That's pretty good and it's borrowing, which is great. I'm not kidding. And you look at me, I have gone nuts. It's -- see, it's [indiscernible] we buy the assets. And then we manage it. We buy them we focus on large footprints of customers today. And we still invest, but we give these customers the best literally support and feature request requirements they need. That's it. And we have a limited number of customers, 600, 700 among our software group. So you can mention, we can spend to give them that experience, and we can focus the center experience. And that's great. So that's been a great model.

Got it. Has it driven synergies, like have you seen synergies between the semiconductor side and the infrastructure software side? And if there aren't, is that a good or back thing? Like how do you look at driving synergies between the 2 groups?

We never look to drive synergies. I mean my 17 product divisions, semiconductors, they don't try to create -- help each other. They don't try to. We -- each is run by General Manager, each has a management team and each are told to be totally selfish. Don't take one for the other guy, come on. If the other guy cannot stand on its own, he doesn't deserve to exist. So that's why we need to be in an environment where they learn how to survive and prosper on a stand-alone basis. And that's -- that's the key jump requirement of the general manager and the team. You survive on your own. If you have to depend on somebody else to prop you up, that's bad. We don't do that. So very limited synergies. The only synergies is, when we go to leading-edge silicon technology or packaging technology. Yes, we develop it centrally, and we share the know-how and IP. But other than that and some core intellectual property like SerDes, A to D converters, stuff like that, high speeds. Other than that, no, they are each on their own, you think software and handwrite even less.

Got it. Is there a certain mix like if you look at Broadcom, say, 5 or 10 years from now. Is there a certain mix between semiconductor and software that you're looking for? Or you think whatever develops naturally based on the strength of each segment?

From my last answer, you probably got -- you already hit it. No, it does -- we don't -- we don't -- I don't have any vision in my mind that I should be 50% hardware, 50% software. We are really a technology company. And we look at areas in technology, to invest in to buy first, invest in, develop, even grow where we can be very successful. And we look at VMware the same way except in VMware case, unlike the software companies I have today, this business, we actually see to grow. That's why we're investing in it. We actually believe it can grow, and we will invest big time.

Got it. When you make R&D decisions, Hock, right? So Broadcom's R&D intensity is among the lowest, right, in this industry. But obviously, you're still growing it, right, because the overall business is growing. How do you make that trade-off? Like if you were to invest an extra dollar and you were able to drive 100 basis points faster growth, how do you make those kinds of decisions? Like is it to maintain the profitability at out levels? Or is it to grow faster? How do you make that trade-off?

We never manage any of those divisions in semiconductor as an example by numbers. We don't -- and you notice each of them, 17 have different levels of profitability, I'd be honest, I won't tell you what each one is, but it ranges. It ranges from -- nevermind, it ranges. It ranges very much...

It's okay if you tell us.

But it's not okay for my customers.

Yes.

But more than that, it's more natural what each business is like. How -- what you need to invest. Don't forget the management team and general manager, believe it or not, which makes my job and Charlie's job easier, they are empowered to invest as much as they need. Seriously, you think we're kidding, no. They can invest as much as they need in the business to sustain and grow in some cases, their business to sustain the business as far as the provided they just focus on make that basic vertical they are in. They're not allowed to go beyond guardrails. That's a requirement. And if you don't go beyond guardrails then just focus on investing as much as they need, we leave you alone. They invest as much as the need. And I'm telling you, we don't tell them how much to invest, how little to invest. What they invest is what they show, and we pull it together, we show you the numbers. And people say, are you underinvesting? No, we're not. They are each allowed to invest. It's kind of telling what's happening out there that if you focus on being the best and just focus in this narrow area, you can do -- you don't have to spend all that money that's out there. And just investing more to R&D dollars doesn't get you any way either because it's not just about spending dollars, it's about getting the best people. And we believe in semiconductors, especially we probably have the best teams in the specific areas we're in, in the world, [indiscernible].

Got it. And then just the last thing, Hock, when you look at just the broader semiconductor industry. There is a contention that the industry can grow faster than it has in the past because pricing is a lot more resilient, right, versus it has been in the past. But at the same time, some end markets such as consumer are not growing as quickly. So let's say, if in the past, we thought semis would grow 5%, 6%. Do you think they grow -- if you look at the next 5 to 7 years, they grow roughly at that pace? Or you think that it is a new industry, and we can actually grow at much higher rates than we have managed to grow?

I don't know how to answer to that, Vivek. That's a very good, thoughtful question. And not sure because you can see that at some point when supply exceeds demand, there will be a lot of price pressure because customers are doing that. Now I have customers change their behavior is what you're saying?

Right.

To some extent, we see that, but it's still early. After 2 years of customers, literal customers, biggest customers, almost having existential issues over supply. They're kind of like, okay, they are more well behaved. But let's see how long that lasts. I'd like to tell customers, hey, make a long-term agreement with me. We have a partnership. I give you engineering. I show you supply you work with me closely on your road map, not current, by future. Yes, we have some of this that exists. And I like customers to believe that is a route to grow in an industry that has matured and is consolidating. I'd like to believe that we see some of that. But I think it's still too early to come to any conclusion that, that will translate into a growth kicker for the entire industry.

Got it. And then finally, Hock, Broadcom as right, some of the most premium margins in the industry. How do you look at the progression of those margins over time? Do you still think there is more leverage still the ability to expand profit margins further? Or do you think that those premium margins can attract more competition over time?

No. Nothing to do with that. There will be. And it's nothing to do with competition or anything else if you are the best of the best in the narrow -- in the specific verticals you are in to doing it. What we have always articulated out there is the nice thing about in technology especially semiconductors is simply this. It doesn't stay still, your customers, they are end users, always one a better product, better features, lower power, higher speeds, more ports, whatever. So you have a chance to always come out with the next generation. Now in industrial, that next-generation or automotive may take 5 years. In consumer like smartphones, it comes out almost every 12, 18 months. And networking, 2 years, 2.5 years, faster and faster. Storage, 4, 5 years, but it does. And each time we time with new generation, you literally save the -- you create more value to your customer, literally, more value. Think about Tomahawk5 versus Tomahawk4. The bandwidth doubles. So you think I'll go to a customer and say, can I have 2 extra prizes, I'm doing it because they save topology 4x. No, but we raised the price, something like 40%. So every generation gives you a chance to extract more value. So if the average accounts of broad portfolio like we have across different end markets, and know that every year, we have a new -- further in the new generation of products, depending on different areas. We have what we've seen empirically over the last 10 years in Broadcom. Our gross margin -- product margin indication of value of our products to our customers on average grow 100 basis points of gross margin. You take that on an OpEx that will grow roughly even the level of sales, if not lower, you have an operating margin that translates into an constant expansion. So -- and we have seen that happen over 10 years. And I expect to continue to see that happening over the next 10 years, given that industry, semiconductor technology continues to evolve.

Terrific. Thank you so much, Hock. Really appreciate your time.

Thank you.

Thank you for great insights. Thanks, everyone.