On-Premises AI Deployment
2 bite-size cards · 60 seconds each
Why GPU Memory is the Real Bottleneck in AI Infrastructure
The conversation around AI infrastructure focuses on FLOPS and GPU count, but in practice memory is what determines what models you can run. A 70B parameter model needs at least 140GB of GPU memory in FP16, far exceeding what a single GPU offers — and this constraint shapes nearly every infrastructure decision.
What is AI Infrastructure?
AI infrastructure is the hardware, software, and networking layer that lets AI models train and run at scale. It includes GPU clusters, specialized chips, distributed storage, and the orchestration systems that coordinate them. Without solid infrastructure, even the best AI models can't reach real users.
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