Verizon Patent and Licensing Inc.

Balint Magyar

Andras Horvath

Anna E Csorgo

Mark Szabo

Techniques described herein provide for the use of a heterogeneous artificial intelligence/machine learning ('AI/ML') architecture, in which relatively complex AI/ML, techniques may be used in conjunction with more lightweight AI/ML techniques in order to leverage the accuracy of relatively complex AI/ML techniques with the reduced processing power and/or time requirements of more lightweight AI/ML techniques. A teacher model system may utilize processing resource and/or time-intensive AI/ML techniques and/or models in order to determine classifications associated with source data, and may provide such classifications to a student model system that may utilize the classifications in accordance with less processing resource and/or time-intensive AI/ML techniques in order to accurately classify sensor data in real time or near-real time.

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Budapest, Hungary

Balint Magyar