EXPANDABLE AND REAL-TIME RECOFIGURABLE HARDWARE FOR NEURAL NETWORKS AND LOGIC REASONING

摘要

This invention presents a scalable field-reconfigurable learning network and machine intelligence system that is reconfigured to match the architecture or processing flow of a selected deep learning neural network and well suited for combining neural network learning and logic reasoning. It partitions the N layers, clusters or stages of the selected learning network into multiple parts with inter-parts connections to a plural of field-reconfigurable processing modules. The inter-parts connections are configured into a field-reconfigurable processing and interconnection module. Multiple field-reconfigurable learning networks can be interconnected to produce a larger scale field-reconfigurable learning network, and can be connected to the Internet to provide a field-reconfigurable learning network cloud service.