About MLCommons
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11-50 employees
View all MLCommons employees
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Computer Software
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San Francisco, US
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MLCommons is an open engineering consortium with a mission to benefit society by accelerating innovation in machine learning. The foundation for MLCommons began with the MLPerf benchmark in 2018, which rapidly scaled as a set of industry metrics to measure machine learning performance and promote transparency of machine learning techniques. In collaboration with its 50+ founding partners - global technology providers, academics and researchers, MLCommons is focused on collaborative engineering work that builds tools for the entire machine learning industry through benchmarks and metrics, public datasets and best practices.
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MLCommons Alternatives
Frequently Asked Questions about MLCommons
The decision makers in MLCommons are Gregory Diamos, David Kanter, Kelly Berschauer, etc. Click to Find MLCommons decision makers emails.
You can reach out to MLCommons through their official website's contact form or by emailing them directly at [email protected]. They welcome questions about their benchmarks, datasets, and initiatives aimed at advancing machine learning.
Yes, MLCommons provides a staff directory on their website. This directory includes key personnel involved in various projects and initiatives, allowing you to identify and contact specific team members for collaboration or inquiries.
MLCommons supports a wide range of industries, including technology, healthcare, automotive, and finance. Their benchmarks are designed to help organizations improve their machine learning systems and drive innovation across these sectors.
MLCommons offers solutions such as standardized benchmarks, datasets, and performance metrics that help organizations evaluate and optimize their machine learning models. These resources are essential for driving innovation and ensuring competitive performance.
To stay informed about MLCommons' latest initiatives, you can subscribe to their newsletter on their website. Additionally, following them on social media platforms will provide updates on new benchmarks, datasets, and industry collaborations.
Yes, MLCommons encourages collaboration on machine learning projects. Interested parties can reach out via their contact form or email to discuss potential partnerships or contributions to ongoing initiatives and benchmarks.
MLCommons Staff Directory
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