Our 8th deep learning patent is a first.
On Octobert 9, 2018, Intraspexion’s patent family achieved a first: Our 8th patent is the first U.S. patent to use the terms “deep learning” and blockchain in the legally relevant field of patent Claim(s). For more detail, see the Blockchain group, below.
Our 1st patent is the parent to the others.
On July 1, 2016, with assistance from co-founders Dan Cotman and Obi Iloputaife of CotmanIP Law Group PLC (Pasadena, CA), founder Nick Brestoff filed the provisional application for our first patent.
On September 27, 2016, the formal application was filed for “Using Classified Text and Deep Learning Algorithms to Identify Risk and Provide Early Warning.”
On December 12, 2016, as a first Office Action, we received a Notice of Allowance.
On January 24, 2017, our first patent issued as U.S. Pat. No. 9,552,548.
Based on this 1st patent, we conceived additional inventions and began writing continuations-in-part. Currently, seven (7) “continuations” have been approved.
On March 27, 2019, an application for a 9th patent was filed. It relates to a post-litigation e-discovery stage known as Early Case Assessment.
Each of Intraspexion’s issued patents relate back to our first patent, with the following characteristics:
Priority Date: July 1, 2016.
Expiration Date: September 27, 2036.
Our patents-first strategy.
Our first instinct was to build the software system to implement our first patent. We did.
However, because Intraspexion’s leadership believed that “deep learning” — a form of Artificial Intelligence (AI) — was hot and getting hotter, we also adopted a unique AI “patents-first” strategy.
Who’s Got Deep Learning Patents?
Let’s put our 8 patents in context. We’ve been keeping a list and, with a request via the Contact Us page, will provide an Excel spreadsheet to you free of charge.
Year over Year results (boldface indicates the # of patents): 2013 (3), 2014 (4), 2015 (4), 2016 (36), 2017 (81), 2018 (162), and 2019 (through the current date of June 18, 2019) (143).
The deep learning patent “land rush” began in 2016, when the level jumped from 4 to 36. then it more than doubled in 2017, and then doubled again in 2018. With 131 new patents in 5 months, we can expect that roughly 300 patents will be issued in 2019.
As of the current date, the Leaderboard Top 10 standings are as follows:
1. IBM (41)
2. Google (29)
3. Microsoft (22)
4. Siemens Healthcare (20)
5. NEC (12)
6. Amazon.com, Amazon Technologies and A9.com (subsidiary) (9)
6. Samsung (9)
8. Adobe Systems Incorporated (8)
8. INTRASPEXION (8)
10. Facebook, Inc. (7)
11. Ford Global Technologies (6)
11. General Electric Company (6)
11. Intel Corporation (6)
11. Nuance Communications (6)
The Intraspexion patent family.
On January 24, 2017, Patent No. 9,552,548 was issued and assigned to Intraspexion. The title is “Using Classified Text and Deep Learning Algorithms to Identify Risk and Provide Early Warning.”
On September 12, 2017, No. 9,760,850 was issued. This patent goes by the same title but has different claims.
On September 5, 2017, the USPTO issued patents related to identifying risks in connection with a Product Defect (No. 9,754,205), Contract Invalidity (No. 9,754,206), Entertainment and Publishing projects (No. 9,754,219), and Medical Diagnoses (No. 9,754,220).
On September 5, 2017, the USPTO also issued a patent for “Using Classified Text and Deep Learning Algorithms to Identify Support for Financial Advantage and Provide Notice” (No. 9,754,218).
Note: This patent is for identifying a financial advantage to obtain rather than a risk to avoid.
On October 9, 2018, the USPTO issued Patent No. 10,095,992 for "Using Classified Text, Blockchain and Deep Learning to Identify Low-Frequency Adverse Situations, and Provide Early Warning."
This patent is the first U.S. patent to use the terms blockchain and “deep learning” in any set of U.S. patent Claim(s); and, as a fundamental matter, is the first U.S. patent to enable the creation of deep learning models where the number of training examples is small, e.g., in instances of potential violations of the Foreign Corrupt Practices Act, Product Liability litigation, and losses due to the theft of trade secrets.