Microsoft Technology Licensing, LLC

Netapp, Inc.

Kausik Ghatak

Neeraj Ramkrishna Singh

Priyanka Goel

Ganessh Kumar R P

Suyash Kumar Tiwari

Swathi Karri

Shabaz Ahmed

Christopher Chinwen Yu

Amit Kumar Singh

Ashutosh Tripathi

Arvind Kumar Singh

Janani Varadharajan

Swapnil M Potey

Eatesh Kandpal

Hitesh Kumar Jhamb

Swathy Thoppay Mothilal

Ravi Krishnan

Vikram Gupta

Pranavasthitha Tandra

Aman Rastogi

Sarang Deshpande

Moinak Chatterjee

Anubhuti Arun

Manish Kataria

Davis John

Sandeep Vasanth Kamath

Manoj

A head-mounted display device, including a display, one or more input devices including one or more image sensors, one or more communication devices, and a processor. The processor may output for display a mixed reality experience including one or more virtual objects. The processor may transmit imaging data to a server computing device. The processor may receive, from the server computing device, an identification of a virtual content item display opportunity, which may include a determination that the mixed reality experience and one or more physical features identified from the imaging data satisfy one or more spatial and/or temporal constraints. The processor may transmit a request for one or more virtual content items to the server computing device based on the identification. The processor may receive the one or more virtual content items from the server computing device and may output the one or more virtual content items for display.

Virtual content display opportunity in mixed reality

Methods, computer systems, and computer-storage media, and graphical user interfaces are provided for facilitating efficient meeting management, according to embodiments of the present technology. In one embodiment, engagement data associated with an attendee of an online meeting is obtained. Thereafter, an engagement metric is generated using the engagement data, the engagement metric indicating an extent of engagement of the attendee to the online meeting. Based on the engagement metric indicating that the extent of engagement of the attendee to the online meeting falls below an engagement threshold, a request is provided to disconnect or throttle an audio and/or video stream of the online meeting to and/or from an attendee device associated with the attendee of the online meeting. Efficient meeting management may also be performed by clustering related messages.

Facilitating efficient meeting management

Servers configured to perform automatic summarization of content in electronic messages are discloses herein. In one embodiment, upon receiving an email, an server determines whether the incoming email is a templated message. In response to determining that the incoming email is not a templated message, the server classifies one or more sentences in the email as a statement of decision, judgement, inference, or fact, cluster the classified statements into clusters, and select one or more of the clusters to automatically generate summaries of the incoming email. The server can then insert data representing the generated summaries into the email before transmitting the email to a destination via a computer network.

Automatic summarization of content in electronic messages

Methods and systems for networked systems are provided. A reinforcement learning (RL) agent is deployed during runtime of a networked system having at least a first component and a second component. The RL agent detects a first degradation signal in response to an error associated with the first component and a second degradation signal from the second component, the second degradation signal generated in response to the error. The RL agent identifies from a learned data structure an action for fixing degradation, at both the first component and the second component; and continues to update the learned data structure, upon successful and unsuccessful attempts to fix degradation associated with the first component and the second component.

Methods and systems for self-healing in connected computing environments

A computer-implemented technique is described herein for receiving activity signals from plural logic components running on one or more computing devices. Each activity signal includes an activity information item (AII) that describes an activity performed by a subject (e.g., a user), or to be performed by the subject, as recorded by a logic component. The technique stores AIIs extracted from the activity signals in a graph data structure. The technique then: determines, by interrogating the graph data structure, one or more activity clusters within a span of time, each activity cluster pertaining to a group of AIIs associated with a same encompassing project; generates one or more summary documents based on the identified activity cluster(s); and sends the summary documents to an output device.

Automatically generating activity summaries based on signals obtained from plural devices and logic components

A computer-implemented technique is described herein for scheduling events. The technique involves recommending one or more candidate spaces (e.g., candidate meeting rooms) based on a selected visit profile for each attendee to the event. More specifically, the technique selects a visit profile for each attendee from a group including a live visit profile, a short-term visit profile, and a long-term visit profile. Each such visit profile describes one or more visits made by the attendee within a prescribed timespan. The technique captures visit data for each such visit based on movement-related signals provided by one or more movement-determining mechanisms. A mobile computing device provides at least one movement-determining mechanism. In a preliminary phase, the technique can identify the geographical position of each candidate meeting space using a crowdsourcing operation.

Recommending meeting spaces using automatically-generated visit data, with geo-tagging of the meeting spaces

Email servers configured to perform automatic summarization of content in electronic messages are discloses herein. In one embodiment, upon receiving an email, an email server determines whether the incoming email is a templated message. In response to determining that the incoming email is not a templated message, the email server classifies one or more sentences in the email as a statement of decision, judgement, inference, or fact, cluster the classified statements into clusters, and select one or more of the clusters to automatically generate summaries of the incoming email. The email server can then insert data representing the generated summaries into the email before transmitting the email to a destination via a computer network.

A computer-implemented technique is described herein for detecting work-related visits. The technique includes receiving movement data from one or more movement-sensing mechanisms associated with a local computing device carried by a user. The technique further includes: determining, using a state machine, and based on the movement data, that a user has commenced a candidate visit, the candidate visit being described by visit data; determining, using the state machine, and based on the movement data, that the user has completed the candidate visit; and determining, using a context-determining component, and based on the visit data, whether the candidate visit corresponds to a work-related visit for which work has been completed. The technique further includes mechanisms that allow the user to add a content item to the visit data of an ongoing visit, prevent private data from leaving the local computing device, and efficiently consume power of the local computing device.

Computer-implemented detection of a work-related visit based on data from movement-sensing mechanism(s)

Methods and systems for a networked storage system are provided. One method includes utilizing a training dataset for prioritizing a plurality of events associated with a networked storage system using a plurality of resources. Each event is associated with a plurality of parameters, each parameter associated with a severity level determination for each event; and each event is provided an initial priority score based on a time when each event is selected for resolution. The plurality of parameters may include an event source. The method further includes using the training dataset to identify a weight of each parameter by executing an iterative prediction algorithm; determining a priority score of a new event based on the weight of each parameter; updating the training dataset with the priority score of the new event; and adjusting a resource impacted by the new event, based on the priority score of the new event.

Methods and systems for prioritizing events associated with resources of a networked storage system

Examples are disclosed herein that relate to mixed reality objects. One example provides a computing device comprising a logic machine and a storage machine holding instructions executable by the logic machine to execute a mixed reality application, the mixed reality application defining a third-party object slot, present a mixed reality environment, and upon detecting a condition associated with the third-p arty object slot, send to a remote computing system a request to fill the third-party object slot, the request based on sensing of a real-world portion of the mixed reality environment with a sensor of the computing device. The instructions are further executable to receive a third-party object from the remote computing system selected by the remote computing system based on the request, and display the third-party object in the third-party object slot such that the third-party object is constrained by a real-world portion of the mixed reality environment.

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Bengaluru, India

Kausik Ghatak