Abstract: Systems and processes for application integration with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving a natural-language user input; identifying, with the one or more processors, an intent object of a set of intent objects and a parameter associated with the intent, where the intent object and the parameter are derived from the natural-language user input. The method further includes identifying a software application associated with the intent object of the set of intent objects; and providing the intent object and the parameter to the software application.

Abstract: A method for artificial intelligence-based automated parser creation includes obtaining a first event log of one or more first event logs of first telemetry data. The first event log includes one or more event log key-value pairs. The method includes generating, using a first artificial intelligence (AI) model, a portion of parser code to map a first event log key of an event log key-value pair of the one or more event log key-value pairs to a predefined field. The method includes generating an event log parser that includes the portion of the parser code. The method includes causing the event log parser to be executed on a second event log of one or more second event logs of second telemetry log data.

Abstract: A system may include one or more operations, which may include obtaining a first structured event log. The first structured event log may include one or more event log key-value pairs. The operations may further include identifying, among one or more predefined fields, a predefined field for an event log key of a first event log key-value pair of the one or more event log key-value pairs. The operations may include generating a portion of parser code to map the event log key of the first event log key-value pair to the identified predefined field. The operations may further include generating an event log parser that includes the portion of the parser code. The operations may further include causing the event log parser to be executed on a second structured event.

Abstract: Systems and processes for application integration with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving a natural-language user input; identifying, with the one or more processors, an intent object of a set of intent objects and a parameter associated with the intent, where the intent object and the parameter are derived from the natural-language user input. The method further includes identifying a software application associated with the intent object of the set of intent objects; and providing the intent object and the parameter to the software application.

Abstract: Systems and methods include a memory and processing devices configured to perform operations. The operations include obtaining telemetry log data comprising an event log that includes one or more values; parsing, using an event log parser extension, a first portion of the one or more values to insert one or more first key-value pairs into a data object, wherein at least a portion of the one or more first key-value pairs includes a value from the first portion of the one or more values and a key assigned to the value; and performing one or more data analysis operations on the data object.

Abstract: Systems and methods include identifying fields associated with a log event of telemetry data and, for each field, selecting a key from multiple keys and generating a field-key mapping that includes a mapping from the fields to the selected key. The systems and methods generate an event log parser extension that includes the field-key mappings and validate the parser extension by testing its performance on sample log events. The systems and methods then execute a base parser and the validated event log parser extension on event logs to convert the event logs into a standardized format and perform data analytics on the standardized event logs to identify trends in the event logs and identify possible threats.

Abstract: Techniques are disclosed relating to component-based risk evaluation using flow signature values. In various embodiments, the disclosed techniques include a server system providing a service usable to provide various computing operations for requesting users, where the server system includes various components with associated component identifier values. In various embodiments, different sequences of the components are usable to perform different ones of the various computing operations. In response to a request from a client device, the server system may perform a requested computing operation via a processing flow that utilizes a particular sequence of components. In various embodiments, the server system generates a particular flow signature value for that particular processing flow, including by generating a flow identifier value by combining component identifier values for the particular sequence of components.

Abstract: Systems and processes for application integration with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving a natural-language user input; identifying, with the one or more processors, an intent object of a set of intent objects and a parameter associated with the intent, where the intent object and the parameter are derived from the natural-language user input. The method further includes identifying a software application associated with the intent object of the set of intent objects; and providing the intent object and the parameter to the software application.

Abstract: Systems and processes for application integration with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving a natural-language user input; identifying, with the one or more processors, an intent object of a set of intent objects and a parameter associated with the intent, where the intent object and the parameter are derived from the natural-language user input. The method further includes identifying a software application associated with the intent object of the set of intent objects; and providing the intent object and the parameter to the software application.

Abstract: In one embodiment, a system includes an automatic speech recognition (ASR) module, a natural-language understanding (NLU) module, a dialog manager, one or more agents, an arbitrator, a delivery system, one or more processors, and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to receive a user input, process the user input using the ASR module, the NLU module, the dialog manager, one or more of the agents, the arbitrator, and the delivery system, and provide a response to the user input.

Abstract: Embodiments of the present disclosure disclose methods and systems for generating operational alarms for a plurality of clients, the operational alarms being generated by a business performance system, each client being associated with a plurality of Key Performance Indicators (KPIs). An aggregate rank for each client based on ranks of each KPI is generated. For each client: the aggregate rank of the client over one or more time periods is monitored. If the aggregate rank deteriorates over the one or more time periods, a severity indicator is determined based on change of value of each KPI and change of rank of each KPI for the client over the one or more time periods. An operational alarm based on value of the severity indicator is determined. The operational alarm is displayed on a user interface, wherein the operational alarm displays one or more KPIs with highest severity values.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. In accordance with one example, a method includes, at an electronic device with one or more processors and memory, obtaining a first set of data corresponding to one or more interactions between a user and the digital assistant on the electronic device; obtaining a second set of data corresponding to one or more interactions between the user and an application on the electronic device; and storing the first set of data and the second set of data. The method further includes receiving a set of executable instructions; processing, based on the received set of executable instructions, the first set of data and the second set of data to obtain a third set of data; and transmitting the third set of data to a remote electronic device.

Abstract: Systems and processes for application integration with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving a natural-language user input; identifying, with the one or more processors, an intent object of a set of intent objects and a parameter associated with the intent, where the intent object and the parameter are derived from the natural-language user input. The method further includes identifying a software application associated with the intent object of the set of intent objects; and providing the intent object and the parameter to the software application.

Abstract: Systems and processes for application integration with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving a natural-language user input; identifying, with the one or more processors, an intent object of a set of intent objects and a parameter associated with the intent, where the intent object and the parameter are derived from the natural-language user input. The method further includes identifying a software application associated with the intent object of the set of intent objects; and providing the intent object and the parameter to the software application.

Abstract: An expandable drawing surface is described. In various embodiments, a drawing surface manager is configured to cause a size of a drawing surface to expand dynamically to provide a user with a truly infinite drawing surface such that the user is not limited for space in any direction. To do so, the drawing surface manager creates and displays new pages for the drawing surface as the user scrolls in any direction. The new pages are displayed proximate existing pages such that the user is presented with a continuous drawing surface on which the user can work seamlessly. In one or more embodiments, a memory manager is configured to provide efficient memory techniques such that, at any point of time, only data associated with visible pages of the drawing surface is loaded onto a memory.

Abstract: Speech recognition is performed on a received utterance to determine a plurality of candidate text representations of the utterance, including a primary text representation and one or more alternative text representations. Natural language processing is performed on the primary text representation to determine a plurality of candidate actionable intents, including a primary actionable intent and one or more alternative actionable intents. A result is determined based on the primary actionable intent. The result is provided to the user. A recognition correction trigger is detected. In response to detecting the recognition correction trigger, a set of alternative intent affordances and a set of alternative text affordances are concurrently displayed.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. An example process receives natural language input and determines a first and a second parsing result for the natural language input. The first and the second parsing results include respective mappings of one or more properties of a domain corresponding to the natural language input to one or more words of the natural language input. The process determines whether the second parsing result corresponds to a data item in a knowledge base, and in accordance with determining that the second parsing result corresponds to the data item in the knowledge base, the process ranks the second parsing result higher than the first parsing result. Based on the ranking, the process generates a task flow using the second parsing result and executes the task flow to provide an output based on the data item.

Abstract: Systems and processes for application integration with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving a natural-language user input; identifying, with the one or more processors, an intent object of a set of intent objects and a parameter associated with the intent, where the intent object and the parameter are derived from the natural-language user input. The method further includes identifying a software application associated with the intent object of the set of intent objects; and providing the intent object and the parameter to the software application.

Abstract: Systems and processes for application integration with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving a natural-language user input; identifying, with the one or more processors, an intent object of a set of intent objects and a parameter associated with the intent, where the intent object and the parameter are derived from the natural-language user input. The method further includes identifying a software application associated with the intent object of the set of intent objects; and providing the intent object and the parameter to the software application.

Abstract: Speech recognition is performed on a received utterance to determine a plurality of candidate text representations of the utterance, including a primary text representation and one or more alternative text representations. Natural language processing is performed on the primary text representation to determine a plurality of candidate actionable intents, including a primary actionable intent and one or more alternative actionable intents. A result is determined based on the primary actionable intent. The result is provided to the user. A recognition correction trigger is detected. In response to detecting the recognition correction trigger, a set of alternative intent affordances and a set of alternative text affordances are concurrently displayed.