Abstract: Techniques for machine learning inferencing endpoint discovery in a distributed computing system are discloses herein. In one example, a method includes searching a database containing machine learning endpoint records having data representing values of execution latency or prediction accuracy corresponding inferencing endpoints deployed in the distributed computing system. The method also includes generating a list of inferencing endpoints matching the individual target values and determining whether a count of the inferencing endpoints in the generated list exceeds a preset threshold. In response to determining that the identified count does not exceed the preset threshold, the method includes instantiating one or more additional inferencing endpoints in the distributed computing system based on the individual target values in the received query.

Abstract: A method of generating a unified graph is described. First graph data is received from a first data source, nodes within the first graph data including first, second, and third fields. Second graph data is received from a second data source, nodes within the second graph data including first, second, and fourth fields. The unified graph is generated from the first and second graph data using aggregated fields of the first field and the third field as a unique identifier of a unified schema for nodes within the unified graph having a first type and aggregated fields of the first field and the fourth field as a unique identifier of the unified schema for nodes within the unified graph having a second type, wherein nodes of the unified graph represent entities and edges of the unified graph represent relationships among the entities.

Abstract: When sharing events between users, the sharing users and the recipient users often have different relationships with details of the events. An event structurer enables sharing users to share events via a single user interface with recipients and tailor what aspects of the events are shared, thus ensuring the relevant portions of the events are properly presented to new recipients based on their new relationship with the event's details.

Abstract: Techniques for machine learning inferencing endpoint discovery in a distributed computing system are discloses herein. In one example, a method includes searching a database containing machine learning endpoint records having data representing values of execution latency or prediction accuracy corresponding inferencing endpoints deployed in the distributed computing system. The method also includes generating a list of inferencing endpoints matching the individual target values and determining whether a count of the inferencing endpoints in the generated list exceeds a preset threshold. In response to determining that the identified count does not exceed the preset threshold, the method includes instantiating one or more additional inferencing endpoints in the distributed computing system based on the individual target values in the received query.

Abstract: Techniques for machine learning inferencing endpoint discovery in a distributed computing system are discloses herein. In one example, a method includes searching a database containing machine learning endpoint records having data representing values of execution latency or prediction accuracy corresponding inferencing endpoints deployed in the distributed computing system. The method also includes generating a list of inferencing endpoints matching the individual target values and determining whether a count of the inferencing endpoints in the generated list exceeds a preset threshold. In response to determining that the identified count does not exceed the preset threshold, the method includes instantiating one or more additional inferencing endpoints in the distributed computing system based on the individual target values in the received query.

Abstract: Techniques for machine learning inferencing endpoint discovery in a distributed computing system are discloses herein. In one example, a method includes searching a database containing machine learning endpoint records having data representing values of execution latency or prediction accuracy corresponding inferencing endpoints deployed in the distributed computing system. The method also includes generating a list of inferencing endpoints matching the individual target values and determining whether a count of the inferencing endpoints in the generated list exceeds a preset threshold. In response to determining that the identified count does not exceed the preset threshold, the method includes instantiating one or more additional inferencing endpoints in the distributed computing system based on the individual target values in the received query.

Abstract: When sharing events between users, the sharing users and the recipient users often have different relationships with details of the events. An event structurer enables sharing users to share events via a single user interface with recipients and tailor what aspects of the events are shared, thus ensuring the relevant portions of the events are properly presented to new recipients based on their new relationship with the event's details.

Abstract: When sharing events between users, the sharing users and the recipient users often have different relationships with details of the events. An event structurer enables sharing users to share events via a single user interface with recipients and tailor what aspects of the events are shared, thus ensuring the relevant portions of the events are properly presented to new recipients based on their new relationship with the event's details.

Abstract: When sharing events between users, the sharing users and the recipient users often have different relationships with details of the events. An event structurer enables sharing users to share events via a single user interface with recipients and tailor what aspects of the events are shared, thus ensuring the relevant portions of the events are properly presented to new recipients based on their new relationship with the event's details.

Abstract: Variety of approaches to automatically update a calendar event are described. A productivity service initiates operations to automatically update a calendar event by analyzing the calendar event to identify a contextual information associated with the calendar event. A service provider associated with the contextual information is queried for an update signal associated with the calendar event. Upon receiving the update signal from the service provider, the calendar event is updated based on the update signal.

Abstract: Variety of approaches to automatically update a calendar event are described. A productivity service initiates operations to automatically update a calendar event by processing a content of a received email. Event information is identified within the content of the email. The event information relates to the calendar event. Next, an update to the calendar event is detected within the event information. The update is applied to the calendar event.

Abstract: Embodiments are directed to registering a device to receive notifications. In one scenario, a computer system receives a notification registration request from a computing device. The computer system generates a registration secret which includes identification information that uniquely identifies the computing device, and sends the generated registration secret including the information that uniquely identifies the computing device to a notification service. The computer system receives a hash value from the computing device, where the hash value is generated based on the identification information of the generated registration secret.

Abstract: Embodiments are directed to registering a device to receive notifications. In one scenario, a computer system receives a notification registration request from a computing device. The computer system generates a registration secret which includes identification information that uniquely identifies the computing device, and sends the generated registration secret including the information that uniquely identifies the computing device to a notification service. The computer system receives a hash value from the computing device, where the hash value is generated based on the identification information of the generated registration secret.

Abstract: Process for purification of vegetable oils upon withdrawal of solids by centrifugation in the miscella stage consists of the industrial extraction of vegetable oils, including the soybean oil by using a solvent, usually a mixture of hydrocarbons, in which the main constituent is hexane. The percolation extractors that operate continuously and in countercurrent provide an optimized extraction and a good performance. The replacement of the traditional miscella purification processes by a process of Centrifugation in the mixture of oil and solvent (miscella) within the process with the removal of solids contained therein, returning it to the extractor results in final products as oil and lecithin of a better quality, also providing a better functioning of the process by avoiding fouling in heat exchangers and distillation of solvent, reducing downtime and lower fuel consumption resulting in lower production costs.

Abstract: Process for purification of vegetable oils upon withdrawal of solids by centrifugation in the miscella stage consists of the industrial extraction of vegetable oils, including the soybean oil by using a solvent, usually a mixture of hydrocarbons, in which the main constituent is hexane. The percolation extractors that operate continuously and in countercurrent provide an optimized extraction and a good performance. The replacement of the traditional miscella purification processes by a process of Centrifugation in the mixture of oil and solvent (miscella) within the process with the removal of solids contained therein, returning it to the extractor results in final products as oil and lecithin of a better quality, also providing a better functioning of the process by avoiding fouling in heat exchangers and distillation of solvent, reducing downtime and lower fuel consumption resulting in lower production costs.

Abstract: Data is maintained that identifies the available domain controllers for performing management actions with respect to a distributed directory service database. When a request is received to perform a management action on a directory service database object, the particular domain controller that is to perform the management action, called the master domain controller, is selected deterministically. Once the master domain controller has been identified, a request to perform the management action is transmitted to the master domain controller. The failure of a master domain controller will cause the identification of that domain controller to be removed from the data that identifies the available domain controllers and a deterministic failover to be performed to another master domain controller.