Recently at Gartner we have been researching issues surrounding the ownership and legal protection of a company’s information assets and analytic models. Since information can be legally protected only via copyrights (in rare cases) or specific usage contracts, I was curious to see if patent applications for algorithms have ticked up over the years.
Fortunately, one of Gartner’s recent Cool Vendors, AULIVE, (see: Cool Vendors for Information Innovation and Governance, 2016) tracks, analyses and provides all kinds of interesting query, charting and reporting on patents and patent applications worldwide. Here’s what I discovered:
Nearly 17,000 patents applications in 2015 mention “algorithm” in the title or description, versus 570 in 2000. They jumped from 2400 applications in 2011 to 8000 in 2012, and to 12,000 in 2013 (A post-recession bump?). Including those mentioning algorithm anywhere in the document, there were over 100,000 patent applications last year versus 28,000 five years ago.
At this post-recession pace, plus considering the increasing interest in protecting algorithmic intellectual property (IP), by 2020 there could be nearly half a billion patent applications mentioning “algorithm” and over 25,000 patent applications specifically for algorithms.
You may wonder whether the term “algorithm” simply is growing in popularity as a synonym for “process” or “routine” or “formula”. Google trend data shows this is not the case.
Granting/Rejecting and Backlog
Patent applications for algorithms have about a 60/40 granted-to-rejected ratio. By comparison, applications for devices or products end up granted 66% of the time.
Looking at the algorithm patents granted, peaking at 7000 in 2013 then dropping to 4700 and 2400 the past two years, it seems there’s an incredible backlog of applications. How can patent offices and examiners hope to keep up? Perhaps an algorithm for patent examination? Seriously. By the time your algorithm patent application gets reviewed it’s likely outdated anyway. Still, “patent pending” offers some value and limited protection.
Over the past fifteen years IBM has led with 2100 algorithmic patent applications, followed by Microsoft (1500), Samsung (1400), Huawei (1300), Qualcomm (1300), State Grid Corp of China (1200), and Philips Electronics (1100) submitted the most patent applications mentioning “algorithm”.
Over the past five years, the top 40 applicants are Chinese companies and universities except for: #5 IBM, #10 Qualcomm, #17 Microsoft, #21 Intel, #25 Samsung, #33 Google, and #36 Apple. Last year (2015), the top nine applicants were Chinese companies and universities. IBM was in the 10-spot.
The past year, the top classifications (patent CPC codes) mentioning “algorithm” were for the following:
Learning machines (68 applications) Segmentation or edge detection Computer-assisted medical diagnosis or treatment Biomedical image inspection Network communication and protocols These are followed by algorithms for image sequencing (esp. stereoscopic images), querying/filtering with personalization, and internet querying.
Application Key Words
Particularly conspicuous is that most Chinese patent applications mentioning “algorithm” the past year have titles including the words like detection, sensing or controlling. While those from IBM, Microsoft and Apple predominantly mention: information processing, computing, memory, storage, documents, data, cloud, power, filtering, visualization, and customer experience related topics. Intel’s of course are more related to microprocessor-related stuff. If I were to draw conclusions from this, it seems the Chinese are making a concerted effort to 1) corner the market on internet-of-things (IoT) related IP, 2) mollify their reputation (right or wrong) for IP larceny by flooding patent offices with their own IP, and/or 3) plotting to litigate the US into IP oblivion.
Regardless, as the focus of innovation in 21st century shifts from products to processes, it seems American, European, Indian, Japanese, Korean, Israeli and Latin American companies and universities known for innovation are being pummeled by the Giant Panda.
What do you think? I’m always interested in other ideas on these topics, and look forward to your comments.
Follow me on Twitter @Doug_Laney #infonomics #GartnerEIM #GartnerBI
(About the author: Doug Laney is a a vice president and distinguished analyst, chief data officer research and advisory, at Gartner. This post originally appeared on his Gartner blog, which can be viewed here)
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