Abstract:
An embodiment method for continuous configuration of learning devices includes operations for storing, by a learning device within a decentralized system of a plurality of learning devices, events obtained while in a monitoring mode, activating a triggered mode for a reflex when at least one of the stored events corresponds to a trigger pattern, determining whether the reflex has a trigger weight exceeding a trigger weight threshold, conducting the predetermined action associated with the reflex when the trigger weight exceeds the trigger weight threshold, obtaining at least one additional event while in the triggered mode, adjusting the trigger weight of the reflex when the at least one additional event corresponds to a correction pattern or a reward pattern occurring in response to conducting the predetermined action, and creating a second reflex when the at least one additional event does not correspond to a known pattern.
Abstract:
Various embodiments for conducting proxy teaching for learning devices within a decentralized system, including an embodiment method with operations for obtaining, by a teacher signaling device, objectives data related to activities of one or more of the learning devices, generating, by the teacher signaling device, teaching routines based on the obtained objectives data, and broadcasting, by the teacher signaling device, teaching signals configured to teach one or more of the learning devices based on the generated teaching routines. Other embodiments may obtain objectives data by requesting reflex information from the learning devices or intercepting event report messages transmitted by the learning devices. Other embodiments may include broadcasting discovery signals to identify nearby learning devices and modifying teaching routines when objectives of the generated teaching routines cannot be achieved. Other embodiments may include transmitting an authorization request to a user device to determine whether to broadcast teaching signals.
Abstract:
Methods, systems and devices for implementing different modes or persona of a wireless communication device that allow the wireless communication device to function as multiple devices corresponding to conditions and circumstances that may be defined by an enterprise. Operating modes or persona may be defined by a set of operating characteristics that may include user permissions, device functionality, capabilities enabled, and user restrictions that may be selected by the enterprise. Automatic switching between modes/persona may be controlled through triggers based on any of location, proximity, time, and context of the wireless communication device. Automatic switching of mode control capabilities may also controlled through such triggers, enabling an enterprise to limit the ability of users to override the automatic mode/persona implemented in response to an enterprise-defined trigger.
Abstract:
A method of generating executable code for a target platform in a neural network includes receiving a spiking neural network description. The method also includes receiving platform-specific instructions for one or more target platforms. Further, the method includes, generating executable code for the target platform(s) based on the platform-specific instructions and the network description.
Abstract:
Methods and apparatus are provided for using a breakpoint determination unit to examine an artificial nervous system. One example method generally includes operating at least a portion of the artificial nervous system; using the breakpoint determination unit to detect that a condition exists based at least in part on monitoring one or more components in the artificial nervous system; and at least one of suspending, examining, modifying, or flagging the operation of the at least the portion of the artificial nervous system, based at least in part on the detection.
Abstract:
Various embodiments for modifying learning capabilities within a decentralized system of learning devices, a method including receiving, at a learning device, a signal from a nearby device, determining whether the received signal is a learning modifier signal based on data within the received signal, and modifying one or more of the learning capabilities in response to determining that the received signal is the learning modifier signal. The method may further include determining whether subsequent learning modifier signals are received, and resetting the modified one or more of the learning capabilities in response to determining that the subsequent learning modifier signals are not received. Modifying learning capabilities may include enabling or disabling a learning mode of the learning device and/or adjusting values of variables used to calculate trigger weights of reflexes. When subsequent learning modifier signals are not received, the learning device may reset modified learning capabilities.