IP Library Granted Patent US 11,620,549
Granted Patent B2
US 11,620,549 · App. 16/939,471 · Granted Apr 4, 2023

Cognitive learning system having a cognitive graph and a cognitive platform

Inventors: Matthew Sanchez (Austin, TX); Manoj Saxena (Austin, TX)
Assignee: Tecnotree Technologies, Inc.
G06N5/04
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Quick Facts
Patent No.
US 11,620,549
App. No.
16/939,471
Granted
Apr 4, 2023
Kind
B2
Abstract

A cognitive information processing system environment comprising a plurality of data sources; a cognitive inference and learning system coupled to receive data from the plurality of data sources, the cognitive inference and learning system processing the data from the plurality of data sources to perform a cognitive learning operation, the cognitive learning operation applying a cognitive learning technique to generate a cognitive learning result; and, a destination, the destination being updated based upon the learning result.

Claims (25)

1. A cognitive information processing system environment comprising:

a plurality of data sources;

a cognitive inference and learning system coupled to receive data from the plurality of data sources, the cognitive inference and learning system processing the data from the plurality of data sources to perform a cognitive learning operation, the cognitive learning operation applying a cognitive learning technique to generate a cognitive learning result, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising:

a cognitive graph, the cognitive graph being derived from the plurality of data sources, the cognitive graph enabling the cognitive inference and learning system to generate the cognitive learning result, the cognitive graph comprising a plurality of nodes, some of the plurality of nodes being linked with other of the plurality of nodes;

a cognitive engine, the cognitive engine comprising a dataset engine, a graph query engine and an insight/learning engine, the dataset engine being implemented to establish and maintain a dynamic data ingestion and enrichment pipeline, the graph query engine being implemented to receive and process queries such that the queries are bridged into the cognitive graph, bridging the queries into the cognitive graph comprising interpreting the queries within a predetermined user context and then mapping the queries to predetermined nodes of the plurality of nodes within the cognitive graph, the insight/learning engine being implemented to generate a cognitive insight from the cognitive graph, the dataset engine, the graph query engine and the insight/learning engine operating collaboratively to generate the cognitive learning result; and,

a destination, the destination being updated based upon the learning result, the destination comprising a knowledge model, the knowledge model being implemented as the cognitive graph.

2. The cognitive information processing system environment of claim 1 , wherein:

the knowledge model is updated by the cognitive platform using the cognitive learning result.

3. The cognitive information processing system environment of claim 1 , wherein:

the plurality of data sources comprise repositories of multi-structured data, the repositories of multi-structured data comprising at least one of public data repositories, private data repositories, social data repositories and device data repositories.

4. The cognitive information processing system environment of claim 1 , wherein:

the multi-structured data comprises at least one of unstructured data, semi-structured data and structured data.

5. The cognitive information processing system environment of claim 1 , wherein:

the cognitive inference and learning system iteratively performs the cognitive learning operation to iteratively improve the cognitive learning result over time.

6. The cognitive information processing system environment of claim 1 , wherein:

the cognitive inference and learning system comprises a universal knowledge repository; and,

the destination comprises the universal knowledge repository.

7. The cognitive information processing system environment of claim 6 , wherein:

the universal knowledge repository comprises at least one of cognitive agents, a cognitive knowledge model, a fault-tolerant data compute architecture, and a data sovereignty, security, lineage and traceability system.

8. The cognitive information processing system environment of claim 1 , wherein:

the cognitive inference and learning system comprises a shared analytics services component.

9. The cognitive information processing system environment of claim 8 , wherein:

the shared analytics services component comprises at least one of a Natural Language processing (NLP) services component, a development services component, a models as a service component, a management services component, a profile services component and an ecosystem services component.

10. The cognitive information processing system environment of claim 1 , wherein:

the cognitive inference and learning system comprises deep cognition engine.

Assignments (4)
SECURITY INTEREST Recorded Dec 22, 2022
From: TECNOTREE TECHNOLOGIES INC.
To: TRIPLEPOINT CAPITAL LLC
Reel/Frame 062213/0388 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 14, 2022
From: COGNITIVE SCALE, INC.; COGNITIVESCALE SOFTWARE INDIA PVT. LTD.; COGNITIVE SCALE UK LTD.; COGNITIVE SCALE (CANADA) INC.
To: TECNOTREE TECHNOLOGIES, INC.
Reel/Frame 062125/0051 →
SECURITY INTEREST Recorded Oct 25, 2022
From: COGNITIVE SCALE INC.
To: TRIPLEPOINT CAPITAL LLC
Reel/Frame 061771/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 27, 2020
From: SANCHEZ, MATTHEW; SAXENA, MANOJ
To: COGNITIVE SCALE, INC.
Reel/Frame 053317/0384 →
Continuity (2)
Continuation 14869169 · Sep 29, 2015
Related Publication 20200356880A1 · Nov 12, 2020
Cited By (1)
US 12,190,247