NVIDIA vs Cloud Providers - AWS, Azure, GCP

#nvidia #aws #ai #gpu #tpu #ai #generativeai
The ‘big three’ public cloud services - Microsoft Azure, Google Cloud Platform (GCP), and market leader Amazon Web Services (AWS) are facing crisis with the rise of generative AI and the hardware needed to power large language models (LLMs) and other workloads.
With its hold on the AI hardware segment, Nvidia is moving quickly to shore up its leverage by deepening partnerships with smaller cloud providers. This could work to shake up a public cloud market which we had assumed was set. Nvidia has big ambitions in AI. It wants to move beyond only selling semiconductors to providing a complete AI solution to end-customers. This includes providing extensive software tools and even its own cloud service.
Nvidia is using its popular H100 chips as leverage by prioritizing smaller players such as Coreweave, Equinix, and Lambda to receive the first available shipments of the in-demand H100s. By doing so, it is folding cloud providers into its cloud ambitions. Nvidia is assuming the role of gatekeeper for the ‘big three’ cloud service providers in this AI age. The firm uses its software - CUDA - and hardware - H100 and GH200 - to retain partnerships and pressure holdouts.
The question we are addressing this video is will Nvidia's AI dominance shake up the public cloud ‘big three’?
Why will NVIDIA dominate AI? Why do Nvidia’s chips dominate the AI market?
Nvidia surpasses Microsoft to become the largest public company in the world
Nvidia, Wall Street’s artificial intelligence poster child, is now the most valuable company in the world, taking the crown from Microsoft. Nvidia’s market capitalization closed at roughly $3.34 trillion on Tuesday, edging past Microsoft’s $3.32 trillion value. Apple is the third most valuable company in the US with a $3.27 trillion market cap.

[@cosmic_sky_mountain]

its the wild west of ai .. who knows who will win, might be a new start up or nvidia in long term.. whoever is able to make a breakthrough in super efficient chipsets and software implementation and training speeds .. one day , perhape , everyone will be assigned an ai at birth to direct one's life..

[@SustainHub]

super informative thanks..now i know why there are only NVidia V100s in Asia with the hyperscalers

[@AI_Data_Demystified]

Thanks @SustainHub for viewing and your comment. Yes apac region has smaller share of GPUs. India's Yotta did get a lot of GPUs from Nvidia. Similarly is other countries the smaller cloud providers have a good supply.

[@AdvantestInc]

Curious about the long-term impacts of these strategic shifts on AI's accessibility and innovation.

[@AI_Data_Demystified]

Thanks @AdvantestInc for viewing and your comment. My view is that Nvidia’s approach will give opportunities to smaller cloud providers to enter the market and innovate. Nvidia will dominate the AI market for the near future and possibly long term if their reference architectures get an adoption like CUDA by the developer community. This might have a significant impact on the cloud provider’s dominance and they will have to come up with better propositions for the enterprise customers for AI. Microsoft is better placed at the moment. Let’s see what AWS and Google come up with.