Who is Winning the AI Race?

By Al AuYeung
February 1, 2020

“The 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.”

https://depositphotos.com/33795973/stock-photo-runner-winning-race-against-blue.htmlMuch has been written about how artificial intelligence (AI) and machine learning (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 and $6.2 billion hours of worker productivity globally. McKinsey forecasts AI potentially could deliver additional economic output 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.

Digging Into the Data

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.

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, Cryptographically Secure Machine Learning, and U.S. Patent No. 10198698, 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:

  • Class 713 Electrical Computer and Digital Data Processing and System Support: 107
  • Class 209 Classifying, Separating and Assorting Solids: 93
  • Class 455 Telecommunications: 85
  • Class 701 Data Processing: Vehicles, Navigation and Relative Location: 84
  • Class 705 Data Processing: Financial, Business Practice or Cost/Price Determination: 64
  • Class 340 Communications, Electrical: 58

The Art Units designed to handle these applications are:

  • Art Unit 2129 for Class 706
  • Art Unit 2131 for Class 713
  • Art Units 3642 and 2649 for Class 455
  • Art Unit 3655 for Class 701
  • Art Units 3685, 3689 and 3693 for Class 705
  • Art Units 2481, 2684 and 2686 for Class 340

The average time it took from filing to issuance was 850 days. The patent that took the longest time to issue was U.S. Patent No. 10410308, System, method, and device for personal medical care, intelligent analysis, and diagnosis. It took 4,530 days. The fastest issuance was U.S. Patent No. 10470510, Systems and Methods for Full Body Measurements Extraction Using Multiple Deep Learning Networks for Body Feature Measurements. It took only 94 days.

[[Advertisement]]

Who’s Leading the Pack?

Not surprisingly, Big Techs are the top recipients of these patents, with IBM leading the pack; the company received 81 of these patents. Following IBM are Microsoft with 56, Amazon with 51, Cisco and Facebook each with 30, and Google with 26. Apple came in at a distant sixth place, having received only 10 of these patents. Perhaps that explains in part Apple’s recent purchase of Seattle’s Xnor.ai for $200 million, following its high-profile purchase of another Seattle startup, Turi, in 2016.

But Big Tech companies are not the only major recipients of these patents. Among the non-Big Tech firms, Capital One received 50, Fanuc Corp received 36, Accenture received 21, and Bank of America received 15 AI/ML patents. Many of these are adoption patents, like Capital One’s “Utilizing machine learning with self-support actions to determine support queue positions for support calls” U.S. Patent No. 10263862. Others are technology centric patents, like “Systems and methods for accelerating model training in machine learning” U.S. Patent No. 10332035, and Systems and methods for providing automated natural language dialogue with customers U.S. Patent No. 10322505.

For non-U.S. companies, European giant Siemen leads the pack, receiving 18 such patents, followed by Korean’s LG with 11 and Samsung with 9. Among Japanese companies, NEC was the leader, receiving 6 AI/ML patents, followed by Sony with 7 and Toyota with 2.

Eye on China

A lot has been written about China’s focus on AI and how the AI/ML filings in China by Chinese companies have significantly increased. Perhaps because of the time it takes from filing to issuance, we are yet to see the Chinese push in issued U.S. patents. Of the Chinese Big Tech names, Baidu leads the pack, receiving 19 of these patents. Huawei received only 2, and Tencent received only 1. However, one wonders if the picture might be significantly different in 2020 and beyond.

The author obtained the data in this article via an independent search of USPTO databases.

Image Source: Deposit Photos
Image ID: 33795973
Copyright: londondeposit 

The Author

Al AuYeung

Al AuYeung is an intellectual property attorney at Schwabe, Williamson & Wyatt.. He works with hardware, software, Internet and e-commerce businesses from Fortune 100 multinationals to emerging companies, both domestic and overseas. Clients count on him for seasoned advice on patent prosecution as well as global innovation protection and cross-border technology transactions. In more than 25 years of legal practice, Al has counseled clients on overall IP strategy, portfolio development, freedom to operate, design around options, infringement exposure, validity of third party IP, licensing and enforcement.

For more information or to contact Al please visit his Firm Profile Page.

Warning & Disclaimer: The pages, articles and comments on IPWatchdog.com do not constitute legal advice, nor do they create any attorney-client relationship. The articles published express the personal opinion and views of the author and should not be attributed to the author’s employer, clients or the sponsors of IPWatchdog.com. Read more.

Discuss this

There are currently 3 Comments comments.

  1. angry dude February 1, 2020 4:18 pm

    China is winning of course

    The AI of the future will be written in Chinese and speak Chinese

    https://spectrum.ieee.org/tech-talk/computing/software/classical-chinese

    non-chinese speaking american lemmings will be subservient to it

  2. Anon February 1, 2020 5:12 pm

    With a bit of tongue in cheek, I can tell you who is not winning:

    AI itself.

    😉

  3. Albert Du February 24, 2020 2:42 pm

    I wonder how many AI patents are directed toward the actual training vs application
    of AI and/or training and application of AI.

    Also, what the differences between the 3600 business methods groups vs other groups is with regard to claim language and/or allowance rates.