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Will Apple Silicon Tackle Memory?

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Why won’t Apple become a cloud company?

Asked by Ian Hobson

Q: Will Apple evolve to make their own memory chips, or manufacture compute chips instead of just designing them? Will they go much more vertical?

It's a possibility — capability is not willingness to do it. They're capable of doing it. They can become vertically integrated on all manners of silicon. I think the decision is a very careful one, because you have to commit years in advance. They did so, as I said, with Qualcomm. They needed to push that dependency out. I think memory may come next. And they need to figure out what they're going to do about TSMC as well, by the way, if you have a single supplier there.

But this is an ongoing thing. They're always re-evaluating it. And I'm not concerned, because nobody does this better. You see other companies' jealousy. You see other companies wanting to do what Apple did eight years ago with the A series. The fact that you can hire a team and become a chip designer — we hear about Tesla, Google, Amazon. I don't know — probably Microsoft's got a team, and probably Meta's got a team. So I just see these out of the corner of my eye and say, well, obviously, yeah, you can now hire a semiconductor team.

And one of the things about Srouji, by the way, that was making a lot of news, is that he got elevated to this position. Very likely he is getting a lot of inbounds, saying, hey, if you come and head this up for us, we'll give you half a trillion dollars. And the amount of money people are willing to throw at this is extraordinary. But again, he wasn't the first, he's not the last. There is an importance in good teams, but it is also important to have a deep bench.

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.

See also: May 2026 Office Hours


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1 comment

  1. FredHS ·

    Apple uses memory more efficiently, key attributes of their control of chip architecture and the OSes.

    With AI workloads, this advantage matters even more for basic consumer AI users, and high end prosumer and professional users.

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