Modularity Libraries

2 Components & Libraries

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Modularity Libraries

Collective Mind (CM) is a collection of portable and extensible automation recipes with a unified and human-friendly interface and minimal dependencies to make it easier to compose, benchmark and optimize AI, ML and other applications and systems across diverse and continuously changing models, data sets, software and hardware (cloud/edge)

For example, you should be able to run the MLPerf inference benchmark on Linux, Windows and MacOS using a few CM commands: You can also run the same commands using a unified CM Python API:

apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly. See the documentation page: https://apricot-select.readthedocs.io/en/latest/index.html

apricot implements submodular optimization for the purpose of summarizing massive data sets into minimally redundant subsets that are still representative of the original data. These subsets are usef…