Abstract: A method, computer program product, and computing system for enabling a user to select a plurality of functional modules from a library of functional modules; and enabling the user to visually arrange the plurality of functional modules to form a conversational application; wherein the conversational application includes a contingency platform configured to enable an administrator of the conversational application to activate a contingency plan at some point-in-time after the deployment of the conversational application.

Abstract: Various technologies pertaining to allocating computing resources of a neuromorphic computing system are described herein. Subgraphs of a neural algorithm graph to be executed by the neuromorphic computing system are identified. The subgraphs are each executed by a group of neuron circuits serially. Output data generated by execution of the subgraphs are provided to the same or a second group of neuron circuits at a same time or with associated timing data indicative of a time at which the output data was generated. The same or second group of neuron circuits performs one or more processing operations based upon the output data.

Abstract: A data stream processing unit (DPU) and methods for its use and programming are disclosed. A DPU includes a number of processing elements (PEs) arranged in a physical sequence. Each datum in the data stream visits each PE in sequence. Each PE has a memory circuit, data and metadata input and output channels, and a computing circuit. The metadata input represents a partial computational state that is associated with each datum as it passes through the DPU. Each computing circuit implements a finite state machine that operates on the data and metadata inputs as a function of its position in the sequence and a data context, producing an altered partial computational state that accompanies the datum. When the data context changes, the current state of the finite state machine is stored, and a new state is loaded. The processing elements may be collectively programmed to perform any desired computation.

Abstract: A data stream processing unit (DPU) and methods for its use and programming are disclosed. A DPU includes a number of processing elements (PEs) arranged in a physical sequence. Each datum in the data stream visits each PE in sequence. Each PE has a memory circuit, data and metadata input and output channels, and a computing circuit. The metadata input represents a partial computational state that is associated with each datum as it passes through the DPU. Each computing circuit implements a finite state machine that operates on the data and metadata inputs as a function of its position in the sequence and a data context, producing an altered partial computational state that accompanies the datum. When the data context changes, the current state of the finite state machine is stored, and a new state is loaded. The processing elements may be collectively programmed to perform any desired computation.

Abstract: A data stream processing unit (DPU) and method for use are provided. A DPU includes a number of processing elements arranged in a sequence, and each datum in the data stream visits each processing element in sequence. Each processing element has a memory circuit, data and metadata input and output channels, and a computing circuit. The metadata input represents a partial computational state that is associated with each datum as it passes through the DPU. The computing circuit for each processing element operates on the data and metadata inputs as a function of its position in the sequence, producing an altered partial computational state that accompanies the datum. Each computing circuit may be modeled, for example, as a finite state machine, and the collection of processing elements cooperate to perform the computation. The computing circuits may be collectively programmed to perform any desired computation.

Abstract: A data stream processing unit (DPU) and method for use are provided. A DPU includes a number of processing elements arranged in a sequence, and each datum in the data stream visits each processing element in sequence. Each processing element has a memory circuit, data and metadata input and output channels, and a computing circuit. The metadata input represents a partial computational state that is associated with each datum as it passes through the DPU. The computing circuit for each processing element operates on the data and metadata inputs as a function of its position in the sequence, producing an altered partial computational state that accompanies the datum. Each computing circuit may be modeled, for example, as a finite state machine, and the collection of processing elements cooperate to perform the computation. The computing circuits may be collectively programmed to perform any desired computation.