People buy Apple products for social status as much as because they are (like me) in their moat. Datacenters have the moat problem with Nvidia, but there is no social status — or very little. And I think that in the long run, the moat will not be as deep. Just like with mainframes, which are still around in the world and still drive most of the revenue and all of the profits at IBM. Nvidia is IBM, not Apple.

Apple had a first mover advantage as well and quickly lost market share as in unit and later revenue share but to this day Apple has 75% of the profit share in the smartphone market.

There will be alternatives to Nvidia but to say that Nvidia’s margin will fall because of this depends on how Nvidia will position themselves. Apple’s margin come from their iOS platform. Nvidia goes that same direction with their DGX platform. DGX will always have competition and alternatives but with DGX Nvidia will try to perform the best performing solution and earn the highest margins. With DGX Nvidia controls most of the value chain of a data center since Nvidia doesn’t need a system builder, a networking partner, not even a data center planner and so on. It’s like HPE/Cray would start developing CPUs+GPUs+networking and offer it in their data centers. That is Nvidia DGX in a nutshell.

With data centers usually many vendors are involved and want their share of the margins. It’s like in the smartphone market. Apple can keep high margins because the own the whole platform. Apple earns on HW, earns on their services and apps and earns on apps from 3rd party sold on their platform as well as on accessories. With Android it’s different, Samsung for example earns on HW, Google earns on SW+app purchases and accessories are margin for many different 3rd parties.

->things can change rapidly, in a way nobody would have ever thought of.

As a person who has spent a few decades predicting the future, I will concede that it is hard to tell. And fall back on my own line, despite an enthusiasm for HPC simulation: The only way to accurate predict the future is to live it. We shall see, and it won’t be boring.

While I don’t doubt your fundamental assertion that ultimately, competition will erode the monopoly NVIDIA has today, I too doubt that 2025 is “peak”. The issue is not that there will be alternative architectures that dilute demand for AI CPU’s – it is that Fabs are taking 3-4 years to build. Between NVIDIA and Apple, TSMC is running to the max. Intel does not expect to see a ROI from its foundry efforts until 2027 at the earliest. They are right now counting on superior packaging capability. This puts Wafer making in the hands of TSMC, and its new Arizona fabs will not come on-line until 2026, leaving NVIDIA in the monopoly drivers seat pushing the CUDA platform for another 2-3 years. Oh, and with Spectrum-X, I expect a high level of integration between switching fabric and Data Center parts. So does Intel, who is scared at how fast IB and a fabric Enet are reshaping Data Center connectivity and priorities. All of these parts live in the high margin space of the market with NVIDIA constrained by their production partner for a solid 2 years.

I agree. It’s not as if the competitors don’t have a blueprint for how to compete.
Nvidia didn’t invent a brand new technology, they just made a matrix math engine that’s really fast. Everyone else knows how to make a matrix math engine, and now just need to keep making them faster. The barrier to entry is the high cost of using newest generation fab tech at tsmc, but even a 5% AI market share will make that worthwhile.

Like I said. Nvidia will make money for a long, long time. It is the new mainframe. But that did not stop RISC/Unix and Windows/Linux on X86. Alternatives that are cheaper will emerge, and even Yann LeCun is warning that LLMs are not the models of the future….

Yes, I have. Since its beginning.

PyTorch and Llama 3 or 4 will be good enough for most enterprises. I see another stack rising, and someone will try to make a commercialized version of it.

Have you ever looked into Nvidia Enterprise AI which Nvidia released in 2022 and it’s impact on everything at enterprise level?

I see here a lot of assumption based on HW and CUDA level but enterprises who seek solutions aren’t DIY, especially outside of IT industry. To many it seems that CSPs buy lots of AI infrastructure for themselves which wouldn’t make sense since they could just focus more on their accelerators. But CSPs have another business going on and that is renting infrastructure.

But to whom do they rent and what do those customers do with Nvidia platform?

I suggest you take a deeper look at Nvidia’s business model and how it’s connected to DGX cloud and Enterprise AI SW solutions. A hint, 1 year ago AWS claimed that they skip DGX in favor for AMD. Today, AWS is another DGX cloud partner and seems to have complete interest in AMD. I’m pretty sure that AWS customer demand had a significant role in that change.

>all of the hyperscalers and cloud builders will be using their own accelerators for a large portion of the workloadsCompetition will happen from other fronts. Price performance will continue and companies will learn to make do with smaller models on smaller machines.The peak can be a plateau. But somewhere north of $100 billion a year — whatever level Nvidia does attain in fiscal 2025 — is it.People will find other ways to solve this problem because it is far too expensive right now.<

Thanks for the reply, appreciate for your thoughts.