Apple Is the King of AI and Nobody Knows It →

The endgame of AI is not four companies renting you intelligence by the token from a datacenter in Virginia. The endgame is intelligence as a commodity — models good enough for 95% of everything, free to download, running on hardware you own, answering to nobody. Every historical technology wave ends the same way: the mainframe becomes the PC, the timeshare becomes the laptop, the cloud becomes the edge. The only people who ever argue otherwise are the people selling mainframes.

The models went free, and they’re getting better every three weeks. The only consumer hardware civilization that can hold them is Apple’s — cheaper per byte of model memory by multiples, cheaper to feed by an order of magnitude, clusterable with a $69 cable, private by architecture, and about to get a lot bigger on memory if the CXMT play lands. The hyperscale build-out that justifies NVIDIA’s $5 trillion assumes none of this matters. It matters. It’s the whole game.

I am convinced that inference and in particular local inference will become more important than training, but I think there's three assertions I would question:

1. The cloud has been an extremely profitable business for the hyperscalers, even before the AI boom, while some companies have retained their data on-prem. It's not clear there's not a profitable market for both AI hosting models.
2. That competitors don't already know this and can't leverage their own ecosystems, partners, and strategic strengths to capture some or most of this market. As discussed in the article, NVIDIA is already working on similar hardware architectures. OpenAI and Anthropic are both hiring chip designers. Google and Microsoft already build consumer-focused hardware.

And the biggest assertion:

3. That people will find AI-based projects that return non-zero ROI. To quote, "An MIT study found 95% of enterprise AI pilots produce zero ROI." The assertion is that these projects work but are too expensive. I'm not sure that's the problem.