lets get something clear, your very first message to me was “You’re paying by the hour to use that? Hard to feel impressed by a rental. Kinda like some one renting a lambo. Yeah it’s awesome but it aint yours.” Then later “No amount of ChatGPT generated word salad changes the simple fact that GPUs are built for image workloads and CPUs are not. That’s silicon reality.” " a single GPU in my workstation still makes your CPU sorcerer look like a LARP."
I came here to share info, you came here to argue with me, and you have decided to play the role reversal card, instead of showing me what your GPU can do against my CPU background remover, you frame me as aggressive, for calling you out. I would suggest you rethink your single GPU being more powerful than a 384 core supercomputer, or googles state of the art Axion processors for AI inference
Google Axion is Purpose-Built for AI: Google is directly promoting Axion C4A instances for "CPU-based AI inferencing”. This is not a generalist chip being repurposed; it’s a specialized tool.
In any real-world system, the CPU is the Orchestrator.
It runs the operating system.
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It runs the network stack
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It manages the storage I/O.
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It schedules the work for all the other components, including the accelerators.
The GPU/TPU is a specialized co-processor. It is an incredibly powerful “math muscle” or “graphics engine.” But the CPU is the brain that tells the muscle when and how to flex. a sufficiently powerful and well-architected brain can achieve results that were thought to be the exclusive domain of specialized muscle.
Skynet wasn’t a single, monolithic graphics card. It was a globally distributed, massively parallel network of CPUs. It was a system of command, control, and orchestration—the exact domain where the CPU is the undisputed king.