Lucas and Luna unpack the latest cloud cost surprise: GPU idle charges. As AI workloads surge, providers like AWS, Azure, and GCP are introducing fees for reserved but unused GPU capacity. The hosts trace this to NVIDIA's dominance, elastic training jobs, and a subtle shift in how hyperscalers price scarcity. They walk through a real scenario: a startup spinning up a p4d instance for fine-tuning, forgetting to tear it down, and getting a $12,000 surprise. The episode also covers strategies to avoid idle charges — spot instances, preemptible VMs, and aggressive autoscaling. A must-hear for anyone running AI inference or training on the big three clouds.

#CloudComputing #GPUIdleCharge #AIWorkloads #AWS #Azure #GCP #NVIDIA #CloudCosts #FinOps #MachineLearning #SpotInstances #PreemptibleVMs #Autoscaling #Technology #FexingoBusiness #BusinessPodcast #CloudInfrastructure #CostOptimization

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