It puts nvidia on both the vendor and customer side of the relationship, which seems odd
That alone means many users will want to use Nvidia hardware even at a decent price premium when the alternative is an extra few months of engineering time in a very fast moving market.
[0] https://docs.pytorch.org/xla/release/r2.7/learn/xla-overview...
Nvidia has the most desirable chips in the world, and their insane prices reflect that. Every hyperscaler is already massively incentivized to build their own chips, find some way to take Nvidia down a peg in the value chain.
Everyone in the world who can is already coming for Nvidia’s turf. No reason they can’t repay the favor.
And beyond just margin-taking, Nvidia’s true moat is the CUDA ecosystem. Given that, it’s hugely beneficial to them to make it as easy as possible for every developer in the world to build stuff on top of Nvidia chips — so they never even think about looking elsewhere.
It almost sounds like you're cheering on Nvidia, framing it as "everyone else trying to reduce the value of Nvidia", meanwhile they have a long, long history of closed-source drivers, proprietary & patented cost-inflated technology that would be identical if not inferior to alternatives - if it weren't for their market share and vendor lock-in strategies.
"Well, what are they gonna do about it?" When dealing with a bully, you go find friends. They're going to fund other chip manufacturers and push for diversity, fund better drivers and compatibility. That's the best possible future anyone could hope for.
1. "Identical if not for market share" is a complete contradiction when what we're talking about is the network effect of CUDA
2. What vendor lock in? What are you talking about? They have a software and compiler stack that works with their chips. How is that lock in, that's literally just their product offering. In fact the truth is you can compile CUDA for AMD (using hipify) and guess what - the result sucks because AMD isn't a comparable alternative!
You can compile x64 to ARM and performance tanks. Does this means ARM isn't a comparable alternative to x64?
It just means their software works badly with said architecture. Could be that AMD acceleration is horrible (but then the FSR would be worse) or it could be that it's just different, or the translation layer is bad.
With the Nvidia solution you have at least another option. Vendor agnostic, but Nvidia lock in.
If most ML startups, one hyper scaler and at best also AMD, would go with one common backend, then it might get enough traction to become *the* standard.
Closed source?? Who cares? It's their own products. Vendor lock in? It's their own chips man. You wouldn't expect Nvidia to develop software for AMD chips would you? That would be insane. I would not do that.
Their tech is superior to everybody else's and Jensen keeps pulling rabbits out of a hat. I hope they keep going strong for the next decade.
Because they are an amoral mass that seeks to make profit and has turned GPU market into a cluster fuck?
> Their tech is superior to everybody
Their only saving grace is CUDA, and DLSS, their hardware has been overvalued for quite some time.
They have a nice software stack but the hardware is overvalued
it is true, but also not. nvidia is certainly producing a chip that nobody else can replicate (unless they're the likes of google, and even they are not interested in doing so).
The CUDA moat is the same type of moat as intel's x86 instruction set. Plenty of existing programs/software stack have been written against it, and the cost to migrate away is high. These LLM pipelines are similar, and even more costly to migrate away.
But because LLM is still immature right now (it's only been approx. 3 yrs!), there's still room to move the instruction set. And middleware libraries can help (pytorch, for example, has more than just the CUDA backend, even if they're a bit less mature).
The real moat that nvidia has is their hardware capability, and CUDA is the disguised moat.
AMD, Intel?
Nobody can touch it. Then that's just the hardware. The software is so much better on Nvidia. The width and breadth of their offering is great and nobody is even close.
>Ultra Accelerator Link (UALink) is an open specification for a die-to-die interconnect and serial bus between AI accelerators. It is co-developed by Alibaba, AMD, Apple, Astera Labs,[1] AWS, Cisco, Google, Hewlett Packard Enterprise, Intel, Meta, Microsoft and Synopsys.[2]
I suppose this can change.
Just took a random server: https://instances.vantage.sh/aws/ec2/m5d.8xlarge?duration=mo... - to get a decent price on it you need to commit to three years at $570 per month(no storage or bandwidth included). Over the course of 3 years that's $20520 for a server that's ~10K to buy outright, and even with colo costs over the same time frame you'll spend a lot less, so not exactly crushing those margins to dust.
Getting more developers creating more models that can then be run on those services will likely expand business for all of those vendors.
Having been a partner for Microsoft research I've also had them try and patent the stuff we were providing them.
In short with megacorps the only winning move is to fuck them faster than they can fuck you.
No cloud provider is gonna see further price gouging from the company with the largest market share and think "Yeah, let's disconnect from the only remaining competitor, make sure every nail is in our coffin".
It's probably the opposite. I bet this move will lead to AMD's increased funding towards compatability and TPU development, in the hopes that they'll become a serious competitor to Nvidia.
no investor is going to bet on the second-place horse. Because they would've done the betting _before_ nvidia became the winning powerhouse that it has become!
The fact is, AMD's hardware capability is just insufficient to compete, and they're not getting there fast enough - unlike the games industry, there's not a lot of low budget buyers here.
[1] https://www.reuters.com/business/aerospace-defense/nvidia-ce...
So now NVIDIA has a whole bunch of cloud infrastructure hosted by the usual suspects that they can use for the same type of business the usual suspects do.
well played tbh
Bostonian•3d ago
snihalani•3h ago