My latest news:
2024 January: my cKnowledge Ltd is now working for MLCommons
to enhance reusable Collective Mind automation recipes for MLOPs and DevOps
to make it easier for the community to build, benchmark and optimize AI systems across rapidly evolving models, software and hardare.
It is a community project based on feedback from many great colleagues
from Google, AMD, Neural Magic, Nvidia, Qualcomm, Dell, Nutanix, OctoML, HPE, Red Hat, Intel, TTA, One Stop Systems and other organizations.
Our current goal is to provide a single common interface to
run and reproduce MLPerf inference benchmarks v3.1 and v4.0
on any software and hardware stack from Intel, Nvidia, Qualcomm, AMD
and other vendors in a unified way either natively or inside automatically-generated containers - please join Discord server
to participate in this project and get free help with your MLPerf inference v4.0 submissions.
2023 September: the cTuning foundation and cKnowledge Ltd are
proud to deliver the new version of the MLCommons CM workflow automation language,
CK playground and modular inference library (MIL)
that became the 1st open-source technology enabling mass submission of 12K+ performance
results in a single MLPerf inference submission round with more than 1900 power results across more
than 120 different system configurations from different vendors
(different implementations, all reference models and support for DeepSparse Zoo,
Hugging Face Hub
and BERT pruners from the NeurIPS paper, main frameworks and diverse software/hardware stacks)
in both open and closed divisions - see related HPC Wire article
for more details about our CK and CM technology.
You can learn more about my recent community initiatives, automation tools, platforms and industrial projects
with MLCommons, IBM, Intel, General Motors, Arm, Google, Amazon, OctoML, HiPEAC, ACM, IEEE
and other great collaborators from my
keynote at ACM REP'23,
overview in Philosophical Transactions of the Royal Society'21
and my reproducibility initiatives at ML and Systems conferences since 2014.
Feel free to reach me via our Discord server
and connect at LinkedIn.
I am a computer scientist, software engineer, business executive, angel investor,
educator, lifelong learner, and adventurer with more than 15 years
of professional experience leading innovative projects
to make AI fast, efficient and accessible to everyone in collaboration
with MLCommons, IBM, Intel, General Motors, Arm, Amazon, Google, HiPEAC, ACM, IEEE, and
My passion is to work with the community to solve real-world problems,
It turned out that I was among the first researchers
to use AI to automate
the development of efficient software and hardware while
open-sourcing all my code, data, models, automation workflows,
experimental results, tech. reports and other artifacts in 2008 when it was still a taboo.
Even though it was a very painful experience to go against the current and try to change
the Status Quo in ML and Systems research back then, I did that because I strongly believed
in the power of open science, open source, collaboration, and knowledge sharing to
accelerate innovation and solve the most challenging problems.
I am very glad that this effort was not wasted and eventually helped establish
reproducibility initiatives and artifact evaluation at practically all ML
and Systems conferences.
It also allowed me to esablish cTuning.org
and continue collaborating with the community and many companies,
startups, and non-profits including MLCommons, IBM, Intel, General Motors,
Arm, Amazon, Google, INRIA, HiPEAC, IEEE and ACM to develop open-source
automation tools and platforms including Collective Knowledge (CK)
and Collective Mind (CM)
that I donated to MLCommons in 2022
to benefit everyone.
I continue leading these community projects to solve the growing
complexity of software projects and AI systems; make it easier
to prototype, validate and reproduce research ideas across rapidly
evolving models, data, software, and hardware; automate the development
of fast and efficient computer systems using AI; accelerate innovation and
technology transfer; and make AI accessible to everyone
in an open and fair way.
At this moment, I focus on the development of the open-source Collective Mind workflow automation language
and Collective Knowledge Playground
with the community and MLCommons (125+ AI organizations)
to bridge the growing gap between AI research and production, facilitate reproducible research, and accelerate AI innovation.
Our goal is to help everyone benchmark and optimize numerous AI/ML models across continuously changing data, software and hardware,
and validate them in the real world
across diverse and rapidly evolving AI/ML models, data, software and hardware from the cloud to the edge.
In my spare time, I continue helping ML and Systems conferences organize
and automate reproducibility initiatives
I also use my experience to help investors and startups avoid numerous pitfalls
and reduce risks and costs when bringing complex ML/AI systems
to production via my cKnowledge Ltd
Finally, I have a few stealth projects that should go live around mid 2024.
When I have time and resources, I am glad to give invited talks and lectures, and help new projects and initiatives
related to automating and simplifying development and deployment of efficient AI systems,
supporting reproducible research, enabling open-science, and making AI fast, efficient and accessible to everyone - you can reach me
via Discord server
I am very grateful to my fantastic colleagues and collaborators
who helped develop Collective Knowledge framework (2014-2022)
and Collective Mind technology (2022-cur.)!
You can find more details about my R&D timeline, professional career and projects in the extended version of this page