Patent ID: 11948083
Assignee: UMNAI LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. The method of claim 1, wherein the explainable model, first model, and second model are implemented on at least one of a digital electronic circuit, analog circuit, a digital-analog hybrid, integrated circuit, application specific integrated circuit (ASIC), field programmable gate array (FPGA), neuromorphic circuit, optical circuit, optical-electronic hybrid, spiking neurons, spintronics, memristors, a distributed architecture, and quantum computing hardware;
wherein the one or more explainable models are implemented as one or more distributed explainable models arranged to be processed in parallel; and wherein each distributed explainable model is configured to split a dataset into multiple subsets of data for training the multiple explainable models,
wherein the one or more explainable models comprise hybrid models comprising one or more of: an explainable artificial intelligence model, an explainable neural network, an explainable transducer transformer, an explainable reinforcement learning model, an explainable spiking neural network, explainable memory network, and/or an interpretable neural network, wherein one data part is configured to implement one model, while another data part is configured to implement another model; and wherein the one model and another model are combined to form an aggregate model.