There are three key components needed for machine learning inference: a data source, a machine learning system to process the data, and a data destination. GPUs play an important role in the development of today's machine learning applications. When choosing a GPU for machine learning applications, there are several manufacturers to choose from.  CUDA cores are better for general purpose parallel computing tasks, while Tensor cores are better for deep learning and AI workloads that involve large matrix operations.
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