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One of the problems of creating a machine learning project is training the model on large datasets. This relies on a lot of computing power to chew through the data, but improvements here can help speed up training, and potentially improve the models.
A new project from PHD student Tristan Bilot, Francesco Farina, and the MLX team, mlx-graphs is a library intended to help Graph Neural Networks (GNNs) to run more efficiently on Apple Silicon. GNNs are used to make predictions of nodes, edges, and in performing graph-based tasks, with a particular usefulness in computer vision.
Go Here to Read this Fast! Apple Silicon gets massive AI training speed boost with this new project
Originally appeared here:
Apple Silicon gets massive AI training speed boost with this new project
