MLCOMMONS

Classe 35 — Comércio e serviços

Association services, namely, promoting innovation in the field of machine learning; association services, namely, promoting public awareness of machine learning training accuracy, speed, performance, and efficiency; association services, namely, promoting public awareness of machine learning inference accuracy, speed, performance, and efficiency; association services, namely, promoting public awareness of mobile device and embedded device machine learning accuracy, speed, performance, and efficiency; business services, namely, formulation of best practices for machine learning and machine learning interoperability and functionality to accelerate progress in the field of machine learning; providing information, data sets, and best practices pertaining to machine learning and machine learning interoperability and functionality; collection, analysis, and display of data for business purposes in the fields of machine learning and machine learning interoperability and functionality; collection, analysis, and display of device and test data pertaining to machine learning, namely, compiling and analyzing statistics, device test data, and server test data regarding the machine learning interoperability and functionality of such devices and servers for business purposes; organizing, arranging, and conducting presentations on the topic of machine learning; organizing, arranging, and conducting business networking events in the field of machine learning.;

Classe 42 — Software e TI

Design and development of technical specifications in the field of machine learning requirements, interoperability, and functionality; design and development of technical specifications for devices and servers pertaining to machine learning requirements, interoperability, and functionality; design and development of technical specifications for devices and servers pertaining to machine learning training and inference accuracy, speed, performance, and efficiency; design and development of technical specifications for mobile device and embedded device machine learning accuracy, speed, performance, and efficiency; design and development of software in the field of the machine learning; design and development of software for testing devices and servers; design and development of software for testing devices and servers for compliance with machine learning requirements and to measure machine learning interoperability and functionality; providing benchmarking information and best practices in the field of machine learning for use to measure accuracy, speed, performance, efficiency, and interoperability.;