Flexibility in chip usage is crucial for managing costs in AI model deployment. When demand for inference is unpredictable, the ability to switch chips between training and inference can significantly enhance utilization rates. The conversation highlights the disconnect between model costs and the underlying infrastructure, emphasizing the importance of adapting to fluctuating customer needs.
