Johny Srouji

An Office Hours question asked by Fred S., May 1, 2026

Q: Ever since Johny Srouji started talking about Apple Silicon and the power consumption for the performance and the unified memory, and now we've seen the Mac mini surge, I just wonder about high-end computing. The whole area of where that Mac architecture may go beyond its success as an individual consumer computing product. From all the high-end workloads that might be coming their way.

The story of Apple is one of personal computing. It's not a story of servers, it's not a story of clouds, it's not a story of centralized computing. They've tried once or twice to make a server product, and they abandoned it. They've even abandoned the high-end Pro product, and created the almost-as-fast Studio product.

Now, that does not mean they're shying away from high-power computing. They're just saying, we're going to put that high-power computing in a desktop, or in the laptop, or even in the phone. Everyone who's grown up throughout the personal computer era can remember Moore's Law, and how exponential growth has driven computation to levels that seemed impossible just a few years earlier. We've hit some slowdowns, but fundamentally, the potential exists.

And by the way, it's not even a classic computational CPU problem. We're dealing with AI. We're mostly dealing with high bandwidth, large data, and we're dealing with simple calculations on it in parallel, which means the architecture is much more around large matrix computations. This is why Nvidia came from graphics. Graphics was the same problem — a graphics accelerator is a matrix problem. And so is machine learning. So different variations of these have come in as a sort of a parallel to the CPU, the general computation problem.

The idea Apple has is that they're going to catch up with whatever is done on the server, they're going to do it on the device. You can call it Edge, you can call it personal — the old term was personal computing.

I may be naive, but I think we'll get very powerful desktop computers that can do what is essentially AI, but for the individual. The other aspect here is that Apple is a consumer company, not a B2B company — it's a B2C. They want to bring that power to as many people as possible. And they're certainly delivering hundreds of millions of computers a year. Nvidia's making tens of millions of computers a year. Apple is capable of doing orders of magnitude more.

So I think they're going to affect the disruption in AI. It's not going to be that there's no profit in AI, it'll be that it'll be done with Edge more, especially as it doesn't have to be a world model — it can be a personal model. If you want to look up something globally, you can use the cloud, but if you want to deal with tasks in your world, you're going to work with Apple computers.

It may take years to get there. But in the meantime, I don't think a centralized service — these OpenAI, or Anthropic, or Microsoft, who are trying to make us a singular superintelligence — is necessary for everyone. It'll be a good reference, but it's not how you want to handle your personal information. So I think that's what the future is, and I think Apple's very much planning for it.

It sounds cliche, but when Apple started, it was IBM that dominated computing. And IBM was about centralized computing, and their thesis was everything we now call "the cloud" — but it was all in one big computer that served the entire organization, whether that organization is a government or a big company. And then we went to mini computers, then we went to desktop computers, then we went to portable computers.

Then, fast forward 25 years and we had Google. Well, now central computing is the internet. In the internet, everything needs to be indexed to be able to be found. So they created an index in the cloud. And then a lot of companies moved that computing they used to have locally into the cloud, as a shared resource from Amazon, AWS, and others, and that became cloud compute. Even now, those are the drivers for growth for Microsoft and Amazon and Google.

The AI part of that is tiny — there's revenue from AI, but there's a lot of revenue from cloud. That still is valuable. But that's not a job for consumers. You do some things in the cloud — you store things, you search, you communicate in messages and so on. But most of the data that matters to you will get also indexed locally, so you can pull up your photos, pull up these things, and it'll be a blend of the two.

So that's where Apple lives, and I don't see anything fundamentally changing about this, because computation tends to commoditize. Software tends to be replicated. Algorithms tend to be replicated. In fact, even the AIs we have today were all because people publish papers, and one company invents it, another implements it, as was the case with the transformer. As far as I understand, it was Google who actually wrote the paper on it.

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Editor's Note: This was one of the questions asked by the participants in Asymco's May 2026 Office Hours live Q&A sessions, open to Asymco One subscribers.

You've probably heard of Jony at Apple but probably don't know about Johny.

Jony is a celebrity executive known as the face of Apple Design. Johny is the executive in charge of custom silicon and hardware technologies across Apple’s entire product line.

Under Johny's leadership, Apple has shipped 1.7 billion processors in more than 20 models and 11 generations. Currently Apple ships more microprocessors than Intel. ((Trailing 12 months’ PC shipments 265 million. Equivalent iOS devices 281 million. Not included are Apple processors in Apple TV.))

The Apple A11 Bionic processor has 4.3 billion transistors, six cores and an Apple custom GPU using a 10nm FinFET technology. Its performance appears to be almost double that of competitors and in some benchmarks exceeds the performance of current laptop PCs.

A decade after making the commitment to control its critical subsystems in its (mobile) products, Apple has come to the point where is dominates the processor space. But they have not stopped at processors. The effort now spans all manners of silicon including controllers for displays, storage, sensors and batteries. The S series in the Apple Watch the haptic T series in the MacBook, the wireless W series in AirPods are ongoing efforts. The GPU was conquered in the past year. Litigation with Qualcomm suggests the communications stack is next.

This across-the-board approach to silicon is not easy or fast or cheap. This multi-year, multi-billion dollar commitment is rooted in the Jobsian observation that the existing supplier network is not good enough for what you're driving at. Tiny EarPods, Smart Watches, Augmented Reality, Adaptive Acoustics require wrapping your arms around all parts of the problem. The integration and control it demands are in contrast to the modular approach of assembling off-the-shelf components into a good-enough configuration.

There are times and places where modules are adequate and times and places where they aren't. The decision depends on whether you are creating new experiences or new "measures of performance" vs. optimizing for cost within existing experiences or measures of performance.

The very notion of a microprocessor is a rejection of the discrete component designs that preceded it. Earlier computers had central processors made up of many discrete components. VLSI stands for Very Large Scale Integration with emphasis on Integration. As computing has progressed toward ambience and ubiquity the idea of using discrete components became normative again but that was not considered sufficient by Apple.

So while the "Silicon" in Silicon Valley has come to be seen as an anachronism, silicon development today means competitive advantage. The only problem is that it takes years, decades even to establish competence. The same duration that it took for the building of Apple as a design-centric business fronted by Jony Ive.

Apple also now needs to be understood along the dimension of silicon-centric engineering as led by Johny Srouji.