accelerator chip

A category of specialized hardware components designed to perform key computations needed for deep learning algorithms. Accelerator chips (or just accelerators, for short) can significantly increase the speed and efficiency of training and inference tasks compared to a general-purpose CPU. They are ideal for training neural networks and similar computationally intensive tasks. Examples of accelerator chips include: - Google's Tensor Processing Units (TPUs) with dedicated hardware for deep learning. - NVIDIA's GPUs which, though initially designed for graphics processing, are designed to enable parallel processing, which can significantly increase processing speed.

Practitioners refer to accelerator chip when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.