Better Machine Learning
MLPerf Results Highlight Growing Importance of Generative AI and Storage
Latest benchmarks include LLM in inference and the first results for storage benchmark
Chakra: Advancing Benchmarking and Co-design for Future AI Systems
Announcing Chakra, execution traces and benchmarks working group
MLCommons at ICML 2023
Join our a data-centric ML research workshop, LLM panel, and the MLCommons Data Underground Social
Accelerating Machine Learning Innovation
MLCommons is a collaborative engineering organization focused on developing the AI ecosystem through benchmarks, public datasets, and research. Together with our members, which include startups, leading companies, academics, and non-profits from around the world, we are working to make Machine Learning better for everyone.
Benchmarks provide consistent measurements of accuracy, speed, and efficiency. Consistent measurements enable engineers to design reliable products and services and empower researchers to compare innovations and choose the best ideas to drive the solutions of tomorrow.
Datasets are the raw materials for all of machine learning. Models are only as good as the data on which they are trained. Academics and entrepreneurs in particular depend on public datasets to create new technologies and new companies.
Ways to Get Involved
MLCommons is a community-driven and community-funded effort. We welcome all corporations, academic researchers, nonprofits, government organizations, and individuals on a non-discriminatory basis. Join us!Get Involved