About
Collective Knowledge (cKnowledge) is a research, engineering and consulting company
supporting open-source projects, investing into startups and sponsoring non-profits
that help researchers and engineers automate their tedious and repetitive tasks,
improve productivity, unleash creativity, accelerate innovation,
reduce all R&D costs and make AI accessible to everyone.
It was established by Grigori Fursin
in 2019 in Paris based on his long and tedious experience
pioneering the use of AI, federated learning and collective tuning (cTuning) to automate development of
high-performance and cost-effective computer systems, and helping the community
reproduce the state-of-the-art research projects and validate them in the real world.
We usually prototype new ideas and projects with the community using our Collective Knowledge Playground
powered by the Collective Mind automation framework that we donated to MLCommons in 2023 to benefit everyone
(see our keynote at the 1st ACM conference on reproducibility and replicability,
joint Nature'23 article,
and invited talk at MLPerf-Bench @ HPCA'24 for more details).
Ongoing projects
2024
-
supporting a stealth startup to make AI accessible to everyone -
please get in touch or stay tuned for more details.
-
collaborating with MLCommons to enhance open-source Collective Mind automation recipes for AI systems (CM)
to support, simplify and accelerate various MLCommons projects - we have successfully validated it with the cTuning foundation
in the MLPerf inference benchmark v4.0 while repeating a mass-scale submission of ~8K results (>90% of all submissions)
and finding for the 1st time top performance, power and cost-effective AI configurations across commodity hardware and software:
see our report
and CM GUI for MLPerf.
-
supporting a new project to "Automatically Compose High-Performance and Cost-effective AI Systems with MLCommons' CM and MLPerf":
see invited presentation at MLPerf-Bench @ HPCA'24.
-
supporting the upcoming Student Cluster Competition at SuperComputing'24
making it easier to run and reproduce MLPerf benchmarks
across different hardware and software from the international student teams.
Accomplishments
2023
-
donated open-source Collective Mind framework (CM) to MLCommons to benefit everyone: GitHub;
-
established the MLCommons Task Force on Automation and Reproducibility
to continue improving the CM automation framework
and help modularize, automate and unify MLPerf benchmarks as a collaborative engineering effort;
-
was invited to give a keynote about CM at the 1st ACM conference on reproducibility and replicability:
program,
slides.
-
sponsored the 1st community submission to MLPerf inference v3.1 with the help of CM
that became the 1st mass-scale MLPerf benchmark submission with >12000 results
(>90% of all results from 20+ other submitters):
report.
-
sponsored artifact evaluation and helped automate experiments using CM at
ACM/IEEE MICRO'23.
-
supported Student Cluster Competition at SuperComputing'23
making it easier to run and reproduce MLPerf Bert benchmark using CM
across different hardware and software.
2021-2022
-
developed a prototype of the Collective Mind framework (CM) with OctoML to modularize AI systems and automated their benchmarking
and optimization across different models, data sets, software and hardware from different vendors.
-
was invited to give an ACM TechTalk about our experience helping the community reproduce 150+ research papers and validate them in the real world:
YouTube,
slides.
2020
2019