An information processing system, which includes a control system and an artificial neural network, is disclosed. The artificial neural network includes a group of neurons and a group of synapses, which includes a first portion and a second portion. The control system selects one of a group of operating modes. The group of neurons processes information. The group of synapses provide connectivity to each of the group of neurons. During a first operating mode of the group of operating modes, the first portion of the group of synapses is enabled and the second portion of the group of synapses is enabled. During a second operating mode of the group of operating modes, the first portion of the group of synapses is enabled and the second portion of the group of synapses is disabled.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An information processing system comprising: a control system configured to select one of a plurality of operating modes comprising a first operating mode and a second operating mode; and an artificial neural network comprising: a plurality of neurons configured to process information; and a plurality of synapses comprising a first portion and a second portion, and configured to provide connectivity to each of the plurality of neurons, wherein: during the first operating mode, the first portion of the plurality of synapses is configured to be enabled and the second portion of the plurality of synapses is configured to be enabled; and during the second operating mode, the first portion of the plurality of synapses is configured to be enabled and the second portion of the plurality of synapses is configured to be disabled. 2. The information processing system of claim 1 wherein during the first operating mode, the artificial neural network has a first power consumption, and during the second operating mode, the artificial neural network has a second power consumption, which is less than the first power consumption. 3. The information processing system of claim 1 wherein the first operating mode is a learning operating mode and the second operating mode is an inference operating mode. 4. The information processing system of claim 1 wherein: the first operating mode is a learning operating mode; and each of the plurality of synapses is associated with a corresponding one of a plurality of weights. 5. The information processing system of claim 1 wherein: the first operating mode is a learning operating mode; each of the plurality of synapses is associated with a corresponding one of a plurality of weights; and during the first operating mode, the artificial neural network is configured to train the artificial neural network to determine each of the plurality of weights. 6. The information processing system of claim 1 wherein: the first operating mode is a learning operating mode; each of the plurality of synapses is associated with a corresponding one of a plurality of weights; and a highest precision of each of the plurality of weights is 32-bits. 7. The information processing system of claim 1 wherein: the first operating mode is a learning operating mode; each of the plurality of synapses is associated with a corresponding one of a plurality of weights; and each of the second portion of the plurality of synapses is associated with a corresponding one of a second portion of the plurality of weights; the second portion of the plurality of weights is configured to be represented by a plurality of binary numbers; and a copy of the plurality of binary numbers is configured to be stored external to the information processing system. 8. The information processing system of claim 1 wherein: the first operating mode is a learning operating mode; each of the plurality of synapses is associated with a corresponding one of a plurality of weights; each of the second portion of the plurality of synapses is associated with a corresponding one of a second portion of the plurality of weights; the second portion of the plurality of synapses comprises clock-gated memory configured to store the second portion of the plurality of weights; during the first operating mode, a clock signal to the clock-gated memory is configured to be enabled, thereby allowing access to the second portion of the plurality of weights; and during the second operating mode, the clock signal to the clock-gated memory is configured to be disabled, thereby preventing access to the second portion of the plurality of weights and reducing power consumption. 9. The information processing system of claim 1 wherein: the first operating mode is a learning operating mode; each of the plurality of synapses is associated with a corresponding one of a plurality of weights; each of the second portion of the plurality of synapses is associated with a corresponding one of a second portion of the plurality of weights; the second portion of the plurality of synapses comprises power-gated memory configured to store the second portion of the plurality of weights; during the first operating mode, the power-gated memory is configured to be enabled, thereby allowing access to the second portion of the plurality of weights; and during the second operating mode, the power-gated memory is configured to be disabled, thereby preventing access to the second portion of the plurality of weights and reducing power consumption. 10. The information processing system of claim 1 wherein: the second operating mode is an inference operating mode; each of the first portion of the plurality of synapses is associated with a corresponding one of a first portion of a plurality of weights; each of the second portion of the plurality of synapses is associated with a corresponding one of a second portion of the plurality of weights; the first portion of the plurality of weights is representative of at least a most significant bit (MSB) of the plurality of weights; and the second portion of the plurality of weights is representative of a plurality of least significant bits (LSBs) of the plurality of weights. 11. The information processing system of claim 10 wherein during the second operating mode, the artificial neural network is configured to monitor the artificial neural network, such that if a triggering event is detected, the control system is further configured to select a third operating mode of the plurality of operating modes. 12. The information processing system of claim 10 wherein during the second operating mode, the artificial neural network is configured to monitor the artificial neural network, such that if a triggering event is detected, the control system is further configured to select a third operating mode of the plurality of operating modes, such that during the third operating mode of the plurality of operating modes, the second portion of the plurality of synapses is configured to be enabled. 13. The information processing system of claim 10 wherein: the plurality of synapses further comprises a third portion; each of the third portion of the plurality of synapses is associated with a corresponding one of a third portion of the plurality of weights; the third portion of the plurality of weights is representative of a plurality of middle significant bits of the plurality of weights; and during the second operating mode, the artificial neural network is configured to monitor the artificial neural network, such that if a triggering event is detected, the control system is further configured to select a third operating mode of the plurality of operating modes, such that during the third operating mode of the plurality of operating modes, the third portion of the plurality of synapses is configured to be enabled. 14. The information processing system of claim 10 wherein during the second operating mode, the artificial neural network is configured to monitor the artificial neural network, such that a triggering event is detected when the MSB of the plurality of weights is a logic 1. 15. The information processing system of claim 10 wherein during the second operating mode, the artificial neural network is configured to monitor the artificial neural network, such that a triggering event is detected when the MSB of the plurality of weights is a logic 0. 16. The information processing system of claim 10 wherein: the first portion of the plurality of weights is representative of a plurality of MSBs of the plurality of weights; and during the second operating mode, the artificial neural network is configured to monitor the artificial neural network, such that a triggering event is detected when the plurality of MSBs of the plurality of weights is above a threshold. 17. The information processing system of claim 10 wherein: the first portion of the plurality of weights is representative of a plurality of MSBs of the plurality of weights; and during the second operating mode, the artificial neural network is configured to monitor the artificial neural network, such that a triggering event is detected when the plurality of MSBs of the plurality of weights is below a threshold. 18. The information processing system of claim 10 wherein: the first portion of the plurality of weights is representative of a plurality of MSBs of the plurality of weights; and during the second operating mode, the artificial neural network is configured to monitor the artificial neural network, such that a triggering event is detected when the plurality of MSBs of the plurality of weights is above a first threshold and below a second threshold. 19. The information processing system of claim 1 further comprising additional circuitry, wherein the artificial neural network further comprises an additional interface, which is coupled between the second portion of the plurality of synapses and the additional circuitry. 20. The information processing system of claim 19 wherein during the second operating mode, the additional circuitry is configured to access the second portion of the plurality of synapses via the additional interface.