Knowledge acquisition for distributed learning models

A non-transitory computer readable medium comprising computer readable program code, which when executed by a computer processor enables the computer processor to perform a method for creating discriminative artificial intelligence (AI) models, the method comprising:

• receiving, at a distributed learning knowledge acquirer, data from a local small foundation system, a distributed endpoint management system, and a centralized large foundation system, wherein:
• the distributed learning knowledge acquirer is connected to the distributed endpoint management system and the local small foundation system which are located on a distributed edge site of a plurality of distributed edge sites,
• the plurality of distributed edge sites are connected to a centralized system to form an artificial intelligence (AI) hybrid distributed inference system, and
• the centralized large foundation system is located on the centralized system with an external information repository;
• making a determination that the data to determine reaches a threshold to perform a drift evaluation;
• based on the determination, evaluating the data to determine the data causes a conceptual drift and can be used as local training data;
• transmitting the local training data to a centralized training dataset repository of the external information repository and a local federated model trainer;
• training a local discriminative model using the local training data;
• evaluating the local discriminative model using a model evaluation module to determine local discriminative model is ready to be used at the distributed endpoint management system;
• and
• transmitting the local discriminative model to a discriminative AI model repository of the external information repository and the distributed endpoint management system, wherein the local discriminative model includes elements trained on data produced locally on the distributed edge site by classifications from the local small foundation system and data produced centrally at the centralized system by classifications of the centralized large foundation system.

A distributed learning knowledge acquirer, comprising:

• a processor;
• storage comprising instructions, which when executed by the processor perform a method, the method comprising:
• receiving, at the distributed learning knowledge acquirer, data from a local small foundation system, a distributed endpoint management system, and a centralized large foundation system, wherein:
• the distributed learning knowledge acquirer is connected to the distributed endpoint management system and the local small foundation system which are located on a distributed edge site of a plurality of distributed edge sites,
• the plurality of distributed edge sites are connected to a centralized system to form an artificial intelligence (AI) hybrid distributed inference system, and
• the centralized large foundation system is located on the centralized system with an external information repository;
• making a determination that the data to determine reaches a threshold to perform a drift evaluation;
• based on the determination, evaluating the data to determine the data causes a conceptual drift and can be used as local training data;
• transmitting the local training data to a centralized training dataset repository of the external information repository and a local federated model trainer;
• training a local discriminative model using the local training data;
• evaluating the local discriminative model using a model evaluation module to determine local discriminative model is ready to be used at the distributed endpoint management system;
• and
• transmitting the local discriminative model to a discriminative AI model repository of the external information repository and the distributed endpoint management system, wherein the local discriminative model includes elements trained on data produced locally on the distributed edge site by classifications from the local small foundation system and data produced centrally at the centralized system by classifications of the centralized large foundation system.