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Comment by sghiassy

8 hours ago

Imagine spending a trillion dollars on data centers and then reading this article. Nightmare fuel for OpenAI

For 99.99% of people, spending 15 grand on a Mac Studio just to run Qwen 3.8 locally is a non starter.

  • It's not the M5 Ultra itself, but the M7s or M9s that will do the damage.

    99% of people will use whatever AI is free. The sophisticated, heavy users that are willing and able to pay a lot of money the ones that will be interested in controlling their inference bills.

    Today, the sweet spot where an M5 Ultra makes sense is tiny. But we might expect that to grow a lot.

    • Anthropic is reporting 100 Billion ARR.

      Even if you could get a frontier model, you would not be able to run it on any Mac. So speculating on what M7 or M9 will achieve in 5 years (if we even still exist) seems pointless.

      3 replies →

And nightmare fuel is just what they'll be selling at the UN this week, for this very reason.

Sam's address will probably be more riveting, imaginative, and terrifying than the last couple of Terminator screenplays. Legislators will lobby him to write the laws for them, and the ghost of Harlan Ellison will threaten to sue him.

I don't see how that math works? This is a $15k rig under benchmark and per the results it competes very acceptably against... one consumer GPU.

I really don't see who buys this, except people who want the Studio for some other reason. But nothing in the story says you want to fill racks with these instead of Blackwell or TPU parts; it's not even close.

  • Your math is correct, but it’s math based on today’s economics.

    Think of a company like Apple moving onto your turf. They’re not going to cede AI to the cloud. They want their part of the pie.

    So in 7 years, how much AI will be handled locally on your iPhone. And will you have repaid all the debt on your balance sheet before Apple eats your lunch

    • I think most important thing is that Nvidia doesnt want to give 100% of market to frontier AI labs either.

      It's way too easy for 1T+ frontier labs to ditch Nvidia. So Nvidia will also put effort to make sure there are open weights models and local hardware available.

      And Apple will benefit from this too.

    • There is zero chance that an LLM approximating a modern frontier model is going to be running on a phone in the next decade. Even if you grant that you could stack enough DRAM dies on top of each other in the package, that would be a three order of magnitude improvement in power efficiency just for the compute.