Open engineering consortium for machine learning formed from MLPerf.
The organization will take on some engineering activities and has a founding board of directors that includes representatives from Alibaba, Facebook, Google, Intel, Nvidia and Professor Vijay Janapa Reddi of Harvard University.
The founding membership includes 15 startups and small companies that focus on semiconductors, systems, and software from across the globe, as well as researchers from University of California Berkeley, University Stanford, and the University of Toronto.
“MLCommons has a clear mission – accelerate Machine Learning innovation to ‘raise all boats’ and increase positive impact on society,” said Peter Mattson, President of MLCommons, in a statement. “We are excited to build on MLPerf and extend its scope and already impressive impact, by bringing together our global partners across industry and academia to develop technologies that benefit everyone.”
MLCommons will take on such tasks as developing and providing access to AI and Machine Learning datasets and models, best practices, benchmarks and metrics. An intent is to enable access to machine learning solutions such as computer vision, natural language processing, and speech recognition by as many people, as fast as possible.
MLCommons has some similarities to Linaro, which develops open-source software for the ARM ecosystem. MLCommons will provide pre-competitive infrastructure to help propel the adoption of machine learning and artificial intelligence for the benefit of all ML-oriented companies.
Next: Young field
“Machine Learning is a young field that needs industry-wide shared infrastructure and understanding,” said David Kanter, executive director of MLCommons, in the same statement. “With our members, MLCommons is the first organization that focuses on collective engineering to build that infrastructure. We are thrilled to launch the organization today to establish measurements, datasets, and development practices that will be essential for fairness and transparency across the community.”
Initially MLCommons will focus on benchmarks and metrics under the name of MLPerf while adding: People’s Speech, the world’s largest public speech-to-text dataset; and MLCube, a set of conventions that enables sharing of ML models.
For People’s Speech MLCommons has collected more than 80,000 hours of speech with the goal of democratizing speech technology. This will create opportunities to extend the reach of advanced speech technologies to many more languages and help to offer the benefits of speech assistance to the entire world population rather than confining it to speakers of the most common languages.
The MLCommons founding members are from leading companies, including Advanced Micro Devices, Inc., Alibaba Co. Ltd., Arm Ltd., Baidu Inc., Cerebras Systems, Centaur Technology Inc., Cisco Systems Inc., Ctuning Foundation, Dell Technologies, d-Matrix Corp., Facebook AI, Fujitsu Ltd., FuriosaAI Inc., Gigabyte Technology Co. Ltd., Google LLC, Grai Matter Labs, Graphcore Ltd., Groq Inc., Hewlett Packard Enterprise, Horizon Robotics Inc., Inspur, Intel Corp., Kalray, Landing AI, LSDTech, MediaTek, Microsoft, Myrtle.ai, Neuchips Corp., Nettrix Information Industry Co. Ltd., Nvidia Corp., Qualcomm Technologies Inc., Red Hat Inc., SambaNova Systems, Samsung Electronics Co. Ltd., Shanghai Enflame Technology Co. Ltd., Syntiant Corp., Tenstorrent Inc., VerifAI Inc., VMind Technologies Inc., Xilinx, Gungdong Oppo Mobile Telecommunications Corp. Ltd (Zeku Technology (Shanghai) Corp. Ltd.) and researchers from the following institutions: Harvard University, Indiana University, Stanford University, University of California, Berkeley, University of Toronto, and University of York.
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