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Collective Knowledge (CK) is a community initiative focused on understanding how to run AI, ML, and other emerging workloads efficiently and cost-effectively in real-world scenarios, across diverse models, datasets, software, and hardware, leveraging state-of-the-art R&D and public hackathons.

This educational project was created by Grigori Fursin and is being developed in collaboration with ACM, MLCommons, MLPerf, FlexAI, cTuning, dedicated volunteers and contributors, and participants in open challenges.

You can learn more about this open-source project through the ACM TechTalk'21, the Journal of Royal Society'20 article, the ACM REP'23 keynote, and our white paper'24.

Please explore our past prototypes here (please note that a new version is currently under development).