In the past, AI demand has primarily focused on training workloads, particularly for frontier models. While leading tech companies continue pouring resources into building ever-larger AI models, they are also reallocating more investment toward inference. Inference is the stage where trained AI models process new data to generate insights, make predictions or support decision-making. While training a model is essentially a one-time expense, prompting a model (inference) produces tokens, each of which carrie ...