21–30 of 128 posts
Earlier quoted context omitted.
Gaming GPUs is a side business for them at this point. It’s all about AI.
Gosh, I have a coworker who acts like gaming GPUs are the only hardware that matters. I've tried explaining that one or two AI data center clients for Nvidia dwarfs the entire gaming GPU market, but he just doesn't get it.
That's not a trend yet. We're about to enter an era where most media is generated. Demand is only going to go up, and margins may not matter if volume goes up.
> The open question is long-term (>6yrs) durability1. Hyperscalers (Google, Microsoft, Amazon, and Meta) are aggressively consolidating AI demand to become the dominant consumers of AI accelerators; while developing competitive, highly-credible chip efforts.
Hyperscalers aren't the only players building large GPU farms. There are large foundation model companies doing it too, and there are also new clouds that offer compute outside of the hyperscaler offerings (CoreWeave, Lambda, and dozens of others). Granted, these may be a drop in the bucket and hyperscalers may still win this trend.
Interesting, Marvell is actually down over 50% this year. I just don't understand the bear case at all. I'm a nobody and I'm still willing to buy a $1500 gpu, and that GPU still can't do what the cloud does. The next $1500 gpu probably can't either. It feels like we're over thinking this. The hardware roll-out is all there is imho. Jensen has mentioned he sees Nvidia being a 10 trillion-dollar company, and I'm willin…
> I wonder what's stopping Nvida from releasing an AI phone B2C is a hellish headache that has marginal returns if you are not B2C first, and the amount of investment needed to be B2C competent just isn't worth it when there are alternative options to invest in > A LLM competitor service (Hey, how about you guys make your own chips Already exists. AI Foundary > They are already releasing an AI PC It's just an OEM reh…
I'm curious to know more about this if you (or anyone else) can elaborate on it.
What constitutes a tech vendor? Are you talking about Walmart buying PCs from Dell, from buying/renting a SaaS from someone, from IT-consulting coming in to do a one-time service for them (even if that service takes years)?
You're not talking about stuff like "Apple wants to sell iPhones to Walmart customers", I assume - yes?
Services! Services services services! This is what will help protect Nvidia now that DC and cluster spend is cooling. They own the ecosystem thanks to CUDA, Infiniband, NGC, NVLink, and other key tools. Now they should add additional applications (the AI Foundry is a good way to do that), or forays into adjacent spaces like white-labeled cluster management. Working on building custom designs and consulting on custom…
> They own the ecosystem thanks to CUDA, Infiniband, NGC, NVLink, No they do not. The article explains that Google, Amazon, Microsoft, and Meta are developing their own hardware and software for AI/HPC. Google Gemini was not trained using CUDA or Nvidia hardware.
Chinese CSPs are the only ones can develop their own hardware / software for AI / HPC.
Earlier quoted context omitted.
> They own the ecosystem thanks to CUDA, Infiniband, NGC, NVLink, No they do not. The article explains that Google, Amazon, Microsoft, and Meta are developing their own hardware and software for AI/HPC. Google Gemini was not trained using CUDA or Nvidia hardware.
Only one of the 4 companies you mention is successful at this. And it will remain that way. Chinese CSPs are the only ones can develop their own hardware / software for AI / HPC.
Interesting, Marvell is actually down over 50% this year. I just don't understand the bear case at all. I'm a nobody and I'm still willing to buy a $1500 gpu, and that GPU still can't do what the cloud does. The next $1500 gpu probably can't either. It feels like we're over thinking this. The hardware roll-out is all there is imho. Jensen has mentioned he sees Nvidia being a 10 trillion-dollar company, and I'm willin…
WRT your edit: The answer to all of this is that it's very hard and requires a huge amount of investment to produce good vertical solutions in each of these spaces. You cannot build a good AI phone without first building a good phone. You cannot build a self-driving car without starting with a good car, etc. For robots, I'll point you to someone using Nvidia chips: the Matic is a complete ground-up rethink of how robot vacuums should work. It's taken them 7 years to get to early adopter phase.
At some point one of these Nvidia doomers will be right but there is a long line of them who failed miserably.
Seems like another article based on the assumption that Nvidia just sits there doing nothing while everyone who has so far proven unable to compete suddenly figures it out and steals their lunch. At some point one of these Nvidia doomers will be right but there is a long line of them who failed miserably.
The article explains that Nvidia's biggest customers (50% of datacenter revenue) are switching to their own hardware.
Earlier quoted context omitted.
Gaming GPUs is a side business for them at this point. It’s all about AI.
Gosh, I have a coworker who acts like gaming GPUs are the only hardware that matters. I've tried explaining that one or two AI data center clients for Nvidia dwarfs the entire gaming GPU market, but he just doesn't get it.
> I've tried explaining that one or two AI data center clients for Nvidia dwarfs the entire gaming GPU market, but he just doesn't get it.
I have a feeling that the different judgements come from the fact that the coworker thinks that the AI bubble will soon burst - thus, in his judgement, the AI data center sector of Nvidia is insanely overvalued, and will collapse. What will "save" Nvidia then will be the gaming GPUs. Thus, in his opinion, this is the sector that matters most for Nvidia, since it will become Nvidia's lifeline when (not "if"! - in your coworker's judgement) things will go wrong in AI.
You, on the other hand believe AI data centers are here to stay (which is a bold assumption: it could happen that AI will move more to the edge), and no big competition will arise for NVidia for "big AI ASICs" (another bold assumption). Your judgment is based on these two strong assumptions about the future, while your coworker's is based on different (possibly similarly bold) assumptions.
Earlier quoted context omitted.
Only one of the 4 companies you mention is successful at this. And it will remain that way. Chinese CSPs are the only ones can develop their own hardware / software for AI / HPC.
Wrong. It's all explained in the article. https://www.reuters.com/technology/artificial-intelligence/m... https://azure.microsoft.com/en-us/blog/azure-maia-for-the-er... https://aws.amazon.com/ai/machine-learning/trainium/
Meta will not be able to produce a chip that can run GenAI workload in the next 2 years.
Microsoft is doing a side-quest, and they haven't even proved themselves with their FPGA adventure and ARM server adventure.
Amazon is legit, they have done well on ARM server, but trainium is TBD, and how much they will pull back in a recession given Jassy is a number guy will be a question mark.
No need to discuss, we can just see this in 2 years, everything will be crystal clear.