Microsoft Technology Licensing, LLC

Juan Diego Ferre

Juan Vicente Esteve Balducci

Roshin Lal Ramesan

Hao Huang

Vipindeep Vangala

Elio Damaggio

Devi Jalakandapuram Viswanathan

Ashish Pinninti

Nishchay Kumar

Vinod Shanbhag

Long Qiu

Zhenghua Yang

Amit Anand Amleshwaram

Sangita N Pitre

Rafael Barcelos

Sebastian Bengochea

Julien J T Pierre

Giselli Panontini De Souza

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.

Unified graph generation

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.

Inferencing endpoint discovery in computing systems

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.

Sharing events with structured metadata

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Seattle, WA, United States of America

Juan Diego Ferre