Abstract: Techniques for de-centralized execution of workflows are disclosed. A system executes a sequence of jobs in a workflow. Each job includes application code to perform a defined set of functions. Each job includes wrapper code at one or both ends of the application code. The system executes the sequence of jobs by iteratively spinning up a virtual machine, loading workflow data to be used by application code, executing the application code, and storing modified workflow data. The virtual machine executing one job triggers the next virtual machine to execute the next job in the workflow, without scheduling the next job by a centralized job scheduler. Upon spinning up the next virtual machine, a virtual machine executing a preceding job shuts itself down.

Abstract: Implementations described here provide a chatbot system that is configurable to meet the needs of the user. In one implementation, a chatbot system is configured to utilize and vary decision trees, decision tree complexity, and decision tree selection adaptive to the needs of the end user. Further, implements may utilize decision trees that are configured as static or dynamic using independent leaves and skillsets to allow for variations in the level of sophistication needed for a chatbot conversation. In other implementations, a chatbot system may be configured to assess the chatbot scenario and requirements in order to adapt processing requirements in order to increase or decrease processing threads to vary processing efficiency relative to the needs of the user. In some scenarios, the chatbot system described herein is introspective thereby using feedback and data to be adaptive to chatbot session errors and self-healing.

Abstract: Implementations described here provide a chatbot system that is configurable to meet the needs of the user. In one implementation, a chatbot system is configured to utilize and vary decision trees, decision tree complexity, and decision tree selection adaptive to the needs of the end user. Further, implements may utilize decision trees that are configured as static or dynamic using independent leaves and skillsets to allow for variations in the level of sophistication needed for a chatbot conversation. In other implementations, a chatbot system may be configured to assess the chatbot scenario and requirements in order to adapt processing requirements in order to increase or decrease processing threads to vary processing efficiency relative to the needs of the user. In some scenarios, the chatbot system described herein is introspective thereby using feedback and data to be adaptive to chatbot session errors and self-healing.

Abstract: Implementations described here provide a chatbot system that is configurable to meet the needs of the user. In one implementation, a chatbot system is configured to utilize and vary decision trees, decision tree complexity, and decision tree selection adaptive to the needs of the end user. Further, implements may utilize decision trees that are configured as static or dynamic using independent leaves and skillsets to allow for variations in the level of sophistication needed for a chatbot conversation. In other implementations, a chatbot system may be configured to assess the chatbot scenario and requirements in order to adapt processing requirements in order to increase or decrease processing threads to vary processing efficiency relative to the needs of the user. In some scenarios, the chatbot system described herein is introspective thereby using feedback and data to be adaptive to chatbot session errors and self-healing.

Abstract: Implementations described here provide a chatbot system that is configurable to meet the needs of the user. In one implementation, a chatbot system is configured to utilize and vary decision trees, decision tree complexity, and decision tree selection adaptive to the needs of the end user. Further, implements may utilize decision trees that are configured as static or dynamic using independent leaves and skillsets to allow for variations in the level of sophistication needed for a chatbot conversation. In other implementations, a chatbot system may be configured to assess the chatbot scenario and requirements in order to adapt processing requirements in order to increase or decrease processing threads to vary processing efficiency relative to the needs of the user. In some scenarios, the chatbot system described herein is introspective thereby using feedback and data to be adaptive to chatbot session errors and self-healing.