Patents by Inventor Aaron POFFENBERGER
Aaron POFFENBERGER has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Patent number: 11818155Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.Type: GrantFiled: January 4, 2022Date of Patent: November 14, 2023Assignee: Intellective Ai, Inc.Inventors: Wesley Kenneth Cobb, Ming-Jung Seow, Curtis Edward Cole, Jr., Cody Shay Falcon, Benjamin A. Konosky, Charles Richard Morgan, Aaron Poffenberger, Thong Toan Nguyen
-
Publication number: 20220150267Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.Type: ApplicationFiled: January 4, 2022Publication date: May 12, 2022Applicant: Intellective Ai, Inc.Inventors: Wesley Kenneth COBB, Ming-Jung SEOW, Curtis Edward COLE, JR., Cody Shay FALCON, Benjamin A. KONOSKY, Charles Richard MORGAN, Aaron POFFENBERGER, Thong Toan NGUYEN
-
Publication number: 20220006825Abstract: Embodiments presented herein describe techniques for generating a linguistic model of input data obtained from a data source (e.g., a video camera). According to one embodiment of the present disclosure, a sequence of symbols is generated based on an ordered stream of normalized vectors generated from the input data. A dictionary of words is generated from combinations of the ordered sequence of symbols based on a frequency at which combinations of symbols appear in the ordered sequence of symbols. A plurality of phrases is generated based an ordered sequence of words from the dictionary observed in the ordered sequence of symbols based on a frequency by which combinations of words in ordered sequence of words appear relative to one another.Type: ApplicationFiled: July 6, 2021Publication date: January 6, 2022Applicant: Intellective Ai, Inc.Inventors: Ming-Jung SEOW, Wesley Kenneth COBB, Gang XU, Tao YANG, Aaron POFFENBERGER, Lon W. RISINGER, Kishor Adinath SAITWAL, Michael S. YANTOSCA, David M. SOLUM, Alex David HEMSATH, Dennis G. URECH, Duy Trong NGUYEN, Charles Richard MORGAN
-
Publication number: 20210014258Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.Type: ApplicationFiled: July 31, 2020Publication date: January 14, 2021Applicant: Intellective Ai, Inc.Inventors: Wesley Kenneth COBB, Ming-Jung SEOW, Curtis Edward COLE, JR., Cody Shay FALCON, Benjamin A. KONOSKY, Charles Richard MORGAN, Aaron POFFENBERGER, Thong Toan NGUYEN
-
Patent number: 10735446Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.Type: GrantFiled: May 13, 2018Date of Patent: August 4, 2020Assignee: Intellective Ai, Inc.Inventors: Wesley Kenneth Cobb, Ming-Jung Seow, Curtis Edward Cole, Cody Shay Falcon, Benjamin A. Konosky, Charles Richard Morgan, Aaron Poffenberger, Thong Toan Nguyen
-
Publication number: 20190230108Abstract: Embodiments presented herein describe techniques for generating a linguistic model of input data obtained from a data source (e.g., a video camera). According to one embodiment of the present disclosure, a sequence of symbols is generated based on an ordered stream of normalized vectors generated from the input data. A dictionary of words is generated from combinations of the ordered sequence of symbols based on a frequency at which combinations of symbols appear in the ordered sequence of symbols. A plurality of phrases is generated based an ordered sequence of words from the dictionary observed in the ordered sequence of symbols based on a frequency by which combinations of words in ordered sequence of words appear relative to one another.Type: ApplicationFiled: December 11, 2018Publication date: July 25, 2019Applicant: Omni AI, Inc.Inventors: Ming-Jung SEOW, Wesley Kenneth COBB, Gang XU, Tao YANG, Aaron POFFENBERGER, Lon W. RISINGER, Kishor Adinath SAITWAL, Michael S. YANTOSCA, David M. SOLUM, Alex David HEMSATH, Dennis G. URECH, Duy Trong NGUYEN, Charles Richard MORGAN
-
Publication number: 20190124101Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.Type: ApplicationFiled: May 13, 2018Publication date: April 25, 2019Inventors: Wesley Kenneth COBB, Ming-Jung SEOW, Curtis Edward COLE, Cody Shay FALCON, Benjamin A. KONOSKY, Charles Richard MORGAN, Aaron POFFENBERGER, Thong Toan NGUYEN
-
Patent number: 10187415Abstract: Embodiments presented herein describe techniques for generating a linguistic model of input data obtained from a data source (e.g., a video camera). According to one embodiment of the present disclosure, a sequence of symbols is generated based on an ordered stream of normalized vectors generated from the input data. A dictionary of words is generated from combinations of the ordered sequence of symbols based on a frequency at which combinations of symbols appear in the ordered sequence of symbols. A plurality of phrases is generated based an ordered sequence of words from the dictionary observed in the ordered sequence of symbols based on a frequency by which combinations of words in ordered sequence of words appear relative to one another.Type: GrantFiled: March 26, 2017Date of Patent: January 22, 2019Assignee: Omni AI, Inc.Inventors: Ming-Jung Seow, Wesley Kenneth Cobb, Gang Xu, Tao Yang, Aaron Poffenberger, Lon W. Risinger, Kishor Adinath Saitwal, Michael S. Yantosca, David M. Solum, Alex David Hemsath, Dennis G. Urech, Duy Trong Nguyen, Charles Richard Morgan
-
Patent number: 9973523Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.Type: GrantFiled: November 29, 2016Date of Patent: May 15, 2018Assignee: Omni AI, Inc.Inventors: Wesley Kenneth Cobb, Ming-Jung Seow, Curtis Edward Cole, Jr., Cody Shay Falcon, Benjamin A. Konosky, Charles Richard Morgan, Aaron Poffenberger, Thong Toan Nguyen
-
Publication number: 20180046613Abstract: Embodiments presented herein describe techniques for generating a linguistic model of input data obtained from a data source (e.g., a video camera). According to one embodiment of the present disclosure, a sequence of symbols is generated based on an ordered stream of normalized vectors generated from the input data. A dictionary of words is generated from combinations of the ordered sequence of symbols based on a frequency at which combinations of symbols appear in the ordered sequence of symbols. A plurality of phrases is generated based an ordered sequence of words from the dictionary observed in the ordered sequence of symbols based on a frequency by which combinations of words in ordered sequence of words appear relative to one another.Type: ApplicationFiled: March 26, 2017Publication date: February 15, 2018Applicant: Omni AI, Inc.Inventors: Ming-Jung SEOW, Wesley Kenneth COBB, Gang XU, Tao YANG, Aaron POFFENBERGER, Lon W. RISINGER, Kishor Adinath SAITWAL, Michael S. YANTOSCA, David M. SOLUM, Alex David HEMSATH, Dennis G. URECH, Duy Trong NGUYEN, Charles Richard MORGAN
-
Publication number: 20170163672Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.Type: ApplicationFiled: November 29, 2016Publication date: June 8, 2017Inventors: Wesley Kenneth COBB, Ming-Jung SEOW, Curtis Edward COLE, JR., Cody Shay FALCON, Benjamin A. KONOSKY, Charles Richard MORGAN, Aaron POFFENBERGER, Thong Toan NGUYEN
-
Patent number: 9639521Abstract: Embodiments presented herein describe techniques for generating a linguistic model of input data obtained from a data source (e.g., a video camera). According to one embodiment of the present disclosure, a sequence of symbols is generated based on an ordered stream of normalized vectors generated from the input data. A dictionary of words is generated from combinations of the ordered sequence of symbols based on a frequency at which combinations of symbols appear in the ordered sequence of symbols. A plurality of phrases is generated based an ordered sequence of words from the dictionary observed in the ordered sequence of symbols based on a frequency by which combinations of words in ordered sequence of words appear relative to one another.Type: GrantFiled: August 11, 2014Date of Patent: May 2, 2017Assignee: Omni AI, Inc.Inventors: Ming-Jung Seow, Wesley Kenneth Cobb, Gang Xu, Tao Yang, Aaron Poffenberger, Lon W. Risinger, Kishor Adinath Saitwal, Michael S. Yantosca, David M. Solum, Alex David Hemsath, Dennis G. Urech, Duy Trong Nguyen, Charles Richard Morgan
-
Patent number: 9507768Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.Type: GrantFiled: August 11, 2014Date of Patent: November 29, 2016Assignee: Behavioral Recognition Systems, Inc.Inventors: Wesley Kenneth Cobb, Ming-Jung Seow, Curtis Edward Cole, Jr., Cody Shay Falcon, Benjamin A. Konosky, Charles Richard Morgan, Aaron Poffenberger, Thong Toan Nguyen
-
Publication number: 20150047040Abstract: Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.Type: ApplicationFiled: August 11, 2014Publication date: February 12, 2015Inventors: Wesley Kenneth COBB, Ming-Jung SEOW, Curtis Edward COLE, JR., Cody Shay FALCON, Benjamin A. KONOSKY, Charles Richard MORGAN, Aaron POFFENBERGER, Thong Toan NGUYEN
-
Publication number: 20150046155Abstract: Embodiments presented herein describe techniques for generating a linguistic model of input data obtained from a data source (e.g., a video camera). According to one embodiment of the present disclosure, a sequence of symbols is generated based on an ordered stream of normalized vectors generated from the input data. A dictionary of words is generated from combinations of the ordered sequence of symbols based on a frequency at which combinations of symbols appear in the ordered sequence of symbols. A plurality of phrases is generated based an ordered sequence of words from the dictionary observed in the ordered sequence of symbols based on a frequency by which combinations of words in ordered sequence of words appear relative to one another.Type: ApplicationFiled: August 11, 2014Publication date: February 12, 2015Inventors: Ming-Jung SEOW, Wesley Kenneth COBB, Gang XU, Tao YANG, Aaron POFFENBERGER, Lon W. RISINGER, Kishor Adinath SAITWAL, Michael S. YANTOSCA, David M. SOLUM, Alex David HEMSATH, Dennis G. URECH, Duy Trong NGUYEN, Charles Richard MORGAN