U.S. Patent 10095992 was awarded to Intraspexion, Inc. on October 09, 2018 and is entitled “Using classified text, deep learning algorithms and blockchain to identify risk in low-frequency, high value situations, and provide early warning.” The first named inventor is Nelson E. Brestoff of Sequim, WA. The abstract contains an overview of the patent disclosure:

Deep learning is used to identify specific, potential risks to an enterprise while such risks are still internal electronic communications. The combination of Deep Learning and blockchain technologies is a system for overcoming the problem of “small training sets” for highly adverse situations. Each enterprise’s data is secure; is not revealed to any other enterprise and yet is being aggregated using blockchain technology into a training set that is provably viable for building a Deep Learning model which is specific to a given adverse situation. When deployed, the Deep Learning model may provide an early warning alert to an enterprise’s corporate counsel (or leaders) of a potential adverse situation the enterprise would like to know about in time to conduct an internal investigation in order to prevent or avoid the risk. Link to Full Patent

This blockchain patent was originally filed on January 08, 2018  as U.S. Patent Application 15/864785 at the United Stated Patent and Trademark Office. The application was them awarded a patent grant and published as U.S. Patent 10095992. The primary examiner was Michael B Holmes.

Intraspexion, Inc., who is the original assignee of this patent, has at least 8 total granted patents in the United States as of the date of this article. This blockchain patent has been cited 4 times by other U.S. patents according to our law firm research, and can be considered an innovative patent in the field of cryptocurrency and blockchain.

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