Abstract

Approaches, techniques, and mechanisms are disclosed for accessing AI services from one region to another region. An artificial intelligence (AI) service director is configured with mappings from domain names of AI cloud engines to IP addresses of edge nodes of an AI delivery edge network. The AI cloud engines are located in an AI source region. The AI delivery edge network is deployed in a non-AI-source region. An AI application, which accesses AI services using a domain name of an AI cloud engine in the AI cloud engines located in the AI source region, is redirected to an edge node in the edge nodes of the AI delivery edge network located in the non-AI-source region. The AI application is hosted in the non-AI-source region. The AI services is then provided, by way of the edge node located in the non-AI-source region, to the AI application.

IPC Classes  ?

• G06N 5/043 - Distributed expert systemsBlackboards
• G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
• H04L 67/59 - Providing operational support to end devices by off-loading in the network or by emulation, e.g. when they are unavailable
• H04L 67/567 - Integrating service provisioning from a plurality of service providers
• G06F 18/20 - Analysing
• G06N 20/00 - Machine learning
• H04M 3/42 - Systems providing special services or facilities to subscribers

Abstract

Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons. Any ML algorithm can use, or operate in conjunction with, a neural knowledge artifactory comprising the knowledge neurons to enhance or improve baseline accuracy, for example during a cold start period, for augmented decision making and/or for labeling data points or establishing ground truth to perform supervised learning.

IPC Classes  ?

• G06N 3/08 - Learning methods
• G06N 3/042 - Knowledge-based neural networksLogical representations of neural networks
• G06N 3/044 - Recurrent networks, e.g. Hopfield networks

Abstract

Approaches, techniques, and mechanisms are disclosed for accessing AI services from one region to another region. An artificial intelligence (AI) service director is configured with mappings from domain names of AI cloud engines to IP addresses of edge nodes of an AI delivery edge network. The AI cloud engines are located in an AI source region. The AI delivery edge network is deployed in a non-AI-source region. An AI application, which accesses AI services using a domain name of an AI cloud engine in the AI cloud engines located in the AI source region, is redirected to an edge node in the edge nodes of the AI delivery edge network located in the non-AI-source region. The AI application is hosted in the non-AI-source region. The AI services is then provided, by way of the edge node located in the non-AI-source region, to the AI application.

IPC Classes  ?

• G06N 20/00 - Machine learning
• G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
• H04M 3/42 - Systems providing special services or facilities to subscribers
• H04L 67/59 - Providing operational support to end devices by off-loading in the network or by emulation, e.g. when they are unavailable
• H04L 67/567 - Integrating service provisioning from a plurality of service providers
• G06N 5/043 - Distributed expert systemsBlackboards
• G06F 18/20 - Analysing

Abstract

Approaches, techniques, and mechanisms are disclosed for accessing AI services from one region to another region. An artificial intelligence (AI) service director is configured with mappings from domain names of AI cloud engines to IP addresses of edge nodes of an AI delivery edge network. The AI cloud engines are located in an AI source region. The AI delivery edge network is deployed in a non-AI-source region. An AI application, which accesses AI services using a domain name of an AI cloud engine in the AI cloud engines located in the AI source region, is redirected to an edge node in the edge nodes of the AI delivery edge network located in the non-AI-source region. The AI application is hosted in the non-AI-source region. The AI services is then provided, by way of the edge node located in the non-AI-source region, to the AI application.

IPC Classes  ?

• G06N 5/04 - Inference or reasoning models
• G06K 9/62 - Methods or arrangements for recognition using electronic means
• H04L 67/567 - Integrating service provisioning from a plurality of service providers
• H04L 67/59 - Providing operational support to end devices by off-loading in the network or by emulation, e.g. when they are unavailable
• G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
• H04M 3/42 - Systems providing special services or facilities to subscribers

Abstract

Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons. Any ML algorithm can use, or operate in conjunction with, a neural knowledge artifactory comprising the knowledge neurons to enhance or improve baseline accuracy, for example during a cold start period, for augmented decision making and/or for labeling data points or establishing ground truth to perform supervised learning.

IPC Classes  ?

• G06N 3/08 - Learning methods
• G06N 3/04 - Architecture, e.g. interconnection topology

Abstract

Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons. Any ML algorithm can use, or operate in conjunction with, a neural knowledge artifactory comprising the knowledge neurons to enhance or improve baseline accuracy, for example during a cold start period, for augmented decision making and/or for labeling data points or establishing ground truth to perform supervised learning.

IPC Classes  ?

• G06F 15/18 - in which a program is changed according to experience gained by the computer itself during a complete run; Learning machines (adaptive control systems G05B 13/00;artificial intelligence G06N)
• G06N 3/08 - Learning methods
• G06N 3/04 - Architecture, e.g. interconnection topology
• G06F 16/951 - IndexingWeb crawling techniques
• G06F 16/2457 - Query processing with adaptation to user needs

Abstract

Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons. Any ML algorithm can use, or operate in conjunction with, a neural knowledge artifactory comprising the knowledge neurons to enhance or improve baseline accuracy, for example during a cold start period, for augmented decision making and/or for labeling data points or establishing ground truth to perform supervised learning.

IPC Classes  ?

• G06F 17/30 - Information retrieval; Database structures therefor
• G06F 16/2455 - Query execution
• G06N 3/08 - Learning methods
• G06N 3/04 - Architecture, e.g. interconnection topology
• G06F 16/21 - Design, administration or maintenance of databases