Intriguing facts about Kubernetes and GPU infrastructure for AI workloads


Innovators Weekly

Hello Reader,

I hope you're doing well! Cloud-native technologies such as Kubernetes and serverless have been revolutionizing modern application design and deployment in recent years. Now, with Artificial Intelligence's rising importance, Kubernetes and GPUs are becoming the backbone of some major AI research companies. For instance, OpenAI is leveraging them to train its complex multimodal AI model scaling to 7,500 worker nodes.

How is NVIDIA so good in Accelerated Computing

On May 30, 2023, NVIDIA became a member of the trillion-dollar club with a $1.02 trillion market value. In less than a year, NVIDIA’s net worth doubled and reached an incredible 2 trillion dollars in February 2024.

Did you know there’s a secret weapon behind NVIDIA’s success in powering the AI boom? NVIDIA’s AI chips play a pivotal role in training Large Language Models (LLMs) for advanced generative AI applications

video preview​

How DID NVIDIA BUILD $100B AI MONOPLY

Remember when NVIDIA acquired Run.ai? That wasn’t random. Run.ai built a GPU orchestration layer on top of Kubernetes. Their work allows teams to dynamically allocate GPUs, schedule jobs, share resources, and squeeze maximum performance out of their compute.

Fast forward to 2025, NVIDIA reached a 5 trillion market cap and isn’t just selling GPUs anymore!

You see, in 2025 alone, NVIDIA poured money into more than 50 AI startups including $100 millions in OpenAI. In plain English, NVIDIA brings the GPUs, OpenAI brings the AI models.

But the real genius? They brought a bunch of other companies, such as Microsoft, Oracle to this AI money-making machine. Morgan Stanley even calls it “circular financing.” Money flows in a loop, with NVIDIA at its center.

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Mélony Qin (aka. CloudMelon) - Founder @iMelonArt

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