World's Largest Wi-Fi 6 Training Set Used in First Ever AI-derived Landscape
Unified's OPAL (Objective PAtent Landscape) report was designed to address asymmetries in the licensing of standard essential patents and to create a more fair and transparent patent licensing process around core patents supporting next waves of consumer technology growth.
According to OPEN, Unified Patents’ IEEE standards submissions database, over 7,182 technical contributions have been submitted. These top 10 contributors account for 27% of all technical contributions.
The Wi-Fi 6 “OPAL” tool objectively scores the statistical essentiality of patent publications to Wi-Fi 6 functionality. It was created using a machine learning algorithm trained on a large set of expert reviewed Wi-Fi 6 patents. A short summary of OPAL’s methodology follows:
Universe of Patents Subject to Analysis - 3.6M+ applications and granted patents potentially relevant to Wi-Fi 6
Patents Evaluated Manually by Experts - 3,000+ unique families evaluated manually by technical experts at Scintillation Research
AI Training - Patents were vectorized using FastText, and a binary classification algorithm was trained to predict essentiality to the universe of patents
ML Performance - Training complied with accepted machine learning practices and the results achieved a high F-1 score of 0.99
Read more about Wi-Fi 6 OPAL’s report and methodology HERE. If you have any questions, please contact info@unifiedpatents.com.