The Future of Compute: Nvidia's Crown Is Slipping
NVIDIA faces challenges in the AI hardware market as hyperscalers like Google and Amazon develop custom silicon, shrinking its revenue and threatening its market position amid declining margins and profitability.
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NVIDIA's dominance in the AI hardware market is facing significant challenges due to demand consolidation among hyperscalers like Google, Microsoft, Amazon, and Meta, who are increasingly developing their own custom silicon. This shift is driven by the need for cost efficiency and the limitations of current compute infrastructure. As hyperscalers consolidate their AI workloads, NVIDIA's revenue base is shrinking, with approximately 50% of its datacenter demand coming from these large customers. The trend towards distributed and vertically-integrated systems poses a risk to NVIDIA's traditional GPU sales, as smaller independent cloud providers struggle to compete and face declining margins. Price cuts have further eroded profitability, with GPU rental costs dropping significantly. Meanwhile, hyperscalers are ramping up their own chip development, with companies like Google and Amazon successfully replacing NVIDIA GPUs with their custom solutions, such as TPUs and Trainium chips. This trend is expected to continue, as these companies leverage their scale and engineering talent to create competitive alternatives to NVIDIA's offerings. As a result, NVIDIA's long-term position in the market appears increasingly precarious, with its reliance on a few large customers and the growing capabilities of its competitors.
- NVIDIA's market dominance is threatened by hyperscalers developing custom silicon.
- Demand consolidation among major cloud providers is shrinking NVIDIA's revenue base.
- Independent cloud providers are struggling with declining margins and profitability.
- Price cuts in GPU rentals are impacting the economics of cloud services.
- Hyperscalers are successfully replacing NVIDIA GPUs with their own custom chips.
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- Some commenters believe NVIDIA's strategic position and ecosystem development will sustain its market dominance despite competition.
- Others express skepticism about the long-term viability of NVIDIA's current business model as hyperscalers develop custom chips.
- There is a sentiment that NVIDIA's services and ecosystem, including tools like CUDA, will help mitigate revenue declines.
- Several users highlight the ongoing demand for AI hardware, suggesting that NVIDIA may continue to thrive despite increased competition.
- Some commenters question the quality of NVIDIA's GPU drivers, indicating potential concerns about product reliability.
12 commentsAt some point one of these Nvidia doomers will be right but there is a long line of them who failed miserably.
Edit:
- I wonder what's stopping Nvida from releasing an AI phone
- A LLM competitor service (Hey, how about you guys make your own chips?)
- They are already releasing an AI PC
- Their own self driving cars
- Their own robots
If you mess with them, why won't they just compete with you?
Just wanted to say one more thing, that Warren Buffet famously said he regretted not investing in both Google and Apple. I think something like this is happening again, especially as there are lulls that the mainstream public perceives, but enthusiasts don't. To maintain the hyperbole, if you are not a full believer as a developer, then you are simply out of your mind.
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 GPU projects would be helpful as well by helping monetize their existing design practice during slower markets.
Of course, Nvidia is starting to do both, with Nvidia AI Foundry for the former and is working on the latter by starting a GPU architecture and design consulting as announced at GTC and under McKinney
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.
Not ideal for them but hardly a death blow
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