A method for generating an event includes monitoring a first neural network with a second neural network. The method also includes generating an event based at least in part on the monitoring. The event is generated at the second neural network.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for generating an event, comprising monitoring a first neural network with a second neural network; and generating the event, at the second neural network, based at least in part on the monitoring. 2. The method of claim 1, in which operation of the first neural network is independent from operation of the second neural network. 3. The method of claim 1, in which the first neural network has same neuron types as the second neural network. 4. The method of claim 1, in which the first neural network has a same topology as the second neural network. 5. The method of claim 1, in which the event is an exception. 6. The method of claim 5, in which the exception is a breakpoint for debugging. 7. The method of claim 1, in which the event triggers a message. 8. The method of claim 7, in which the message affects operation for a network, system, and/or hardware associated with the first neural network, the network, the system, and the hardware being different from the first neural network. 9. The method of claim 1, further comprising reconfiguring the second neural network based at least in part on the event. 10. The method of claim 9, in which reconfiguring comprises one or more of adjusting a size of the second neural network, reconfiguring parameters, and/or adjusting thresholds. 11. The method of claim 1, in which the second neural network is configured to generate the event based at least in part on a subset of states of the first neural network. 12. The method of claim 11, in which a second state of the second neural network tracks a first state of the first neural network. 13. The method of claim 12, in which: a first neuron of the first neural network operates based at least in part on the first state, the first neuron having a first threshold, and a second neuron of the second neural network operates at least in part based on the second state, the second neuron having a second threshold. 14. The method of claim 1, in which the second network is trainable based at least in part on one or more of a user input, monitoring performed by the second network, or a combination thereof. 15. An apparatus for generating an event, the apparatus comprising: a memory unit; and at least one process coupled to the memory unit; the at least one processor being configured: to monitor a first neural network with a second neural network; and to generate the event, at the second neural network, based at least in part on the monitoring. 16. The apparatus of claim 15, in which operation of the first neural network is independent from operation of the second neural network. 17. The apparatus of claim 15, in which the first neural network has same neuron types as the second neural network. 18. The apparatus of claim 15, in which the first neural network has a same topology as the second neural network. 19. The apparatus of claim 15, in which the event is an exception. 20. The apparatus of claim 19, in which the exception is a breakpoint for debugging. 21. The apparatus of claim 15, in which the event triggers a message. 22. The apparatus of claim 21, in which the message affects operation for a network, system, and/or hardware associated with the first neural network, the network, the system, and the hardware being different from the first neural network. 23. The apparatus of claim 15, in which the at least one processor is further configured to reconfigure the second neural network based at least in part on the event. 24. The apparatus of claim 23, in which the at least one processor is further configured to perform one or more of adjusting a size of the second neural network, reconfiguring parameters, adjusting thresholds, or a combination therefore based at least in part on the event. 25. The apparatus of claim 15, in which the second neural network is configured to generate the event based at least in part on a subset of states of the first neural network. 26. The apparatus of claim 25, in which a second state of the second neural network tracks a first state of the first neural network. 27. The apparatus of claim 26, in which: a first neuron of the first neural network operates based at least in part on the first state, the first neuron having a first threshold, and a second neuron of the second neural network operates at least in part based on the second state, the second neuron having a second threshold. 28. The apparatus of claim 15, in which the second neural network is trainable based at least in part on one or more of a user input, monitoring performed by the second network, or a combination thereof. 29. An apparatus for generating an event, the apparatus comprising: means for monitoring a first neural network with a second neural network; and means for generating the event, at the second neural network, based at least in part on the monitoring. 30. A computer program product for generating an event, the computer program product comprising: a non-transitory computer-readable medium having program code recorded thereon, the program code comprising: program code to monitor a first neural network with a second neural network; and program code to generate the event, at the second neural network, based at least in part on the monitoring.