{"id":118431,"date":"2020-02-01T12:15:38","date_gmt":"2020-02-01T17:15:38","guid":{"rendered":"https:\/\/ipwatchdog.com\/?p=118431"},"modified":"2020-01-31T18:26:39","modified_gmt":"2020-01-31T23:26:39","slug":"winning-ai-race","status":"publish","type":"post","link":"https:\/\/ipwatchdog.com\/2020\/02\/01\/winning-ai-race\/id=118431\/","title":{"rendered":"Who is Winning the AI Race?"},"content":{"rendered":"

\u201cThe U.S. Patent and Trademark Office in 2019 granted 14,838 patents that mentioned AI or ML, of which 1,275 specifically mentioned AI or ML in their titles or abstracts. That is roughly double the issuance in 2018.\u201d<\/p>\n<\/div>\n

\"https:\/\/depositphotos.com\/33795973\/stock-photo-runner-winning-race-against-blue.html\"<\/a>Much has been written about how artificial intelligence<\/a> (AI) and machine learning<\/a> (ML) are about to transform the global productivity, working patterns and lifestyles and create enormous wealth. Gartner projects that by 2021, AI augmentation will create $2.9 trillion of business value<\/a> and $6.2 billion hours of worker productivity globally. McKinsey forecasts AI potentially could deliver additional economic output<\/a> of around $13 trillion by 2030, boosting global GDP by about 1.2 percent a year. Companies around the globe are all racing to adopt and innovate AI and ML technologies. Indeed, by any account, much progress has been made and the adoption and innovation rates are quickening. But who is winning or leading in the race? A quick review of U.S. patent data may provide a glimpse into the state of the race.<\/p>\n

Digging Into the Data<\/strong><\/h2>\n

The U.S. Patent and Trademark Office (USPTO) in 2019 granted 14,838 patents that mentioned AI or ML, of which 1,275 specifically mentioned AI or ML in their titles or abstracts. That is roughly double the issuance in 2018, where 8,227 granted patents mentioned AI or ML, and 515 specifically mentioned AI or ML in their titles or abstracts.<\/p>\n

The U.S. AI\/ML patents granted in 2019 cover a wide range of areas, from adoption and application of AI\/ML technologies to life science, engineering, computing, e-commerce, to business\/finance to innovation in machine training and neural network technologies themselves. Not surprisingly, classification 706, data processing: artificial intelligence, has the highest number of patents granted that specifically mentioned AI\/ML in either the title or abstract, at 151. Examples of class 706 patents are U.S. Patent No. 10198399<\/a>, Cryptographically Secure Machine Learning, and U.S. Patent No. 10198698<\/a>, Machine Learning Auto Completion of Field. Other classes with more than 50 patents granted that specifically mentioned AI\/ML in either the title or abstract are:<\/p>\n