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公开(公告)号：US20240378396A1
公开(公告)日：2024-11-14
申请号：US18313857
申请日：2023-05-08
Applicant: Microsoft Technology Licensing, LLC
Inventor： Dhirendra Kumar BHUPATI , Mrinal Kumar SHARMA
Abstract: Technology is disclosed herein for the integration of large language model (LLM) services for content analysis in productivity applications. In an implementation, an application identifies content associated with the application executing on the computing apparatus. The application identifies a context relating to the content, wherein the context comprises contextual information by which to evaluate the content. The application generates a prompt for an LLM service which includes the content and the context. The prompt requests an evaluation of the content to recommend supplemental content and submits the prompt to the LLM service. The application receives a response to the prompt from the LLM service which includes a suggestion for supplemental content based on the evaluation and displays, in a user interface of the application, a recommendation based on the suggestion from the LLM service.
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公开(公告)号：US20200081698A1
公开(公告)日：2020-03-12
申请号：US16129354
申请日：2018-09-12
Applicant: Microsoft Technology Licensing, LLC
Abstract: A set of devices is inventoried to identify components on the device. Usage information is also identified, indicating a level of usage of the different components. The set of devices is dynamically divided into different collections and deployment control signals are generated to control deployment of an item, onto the devices, based upon the identified collections.
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公开(公告)号：US20240338193A1
公开(公告)日：2024-10-10
申请号：US18131323
申请日：2023-04-05
Applicant: Microsoft Technology Licensing, LLC
Inventor： Dhirendra Kumar BHUPATI , Johnny Sterling CAMPBELL
IPC: G06F8/65
CPC classification number: G06F8/65
Abstract: Described herein is a software update distribution service that leverages reinforcement learning—a specific type machine learning algorithm—to discover or learn optimal times (e.g., a schedule) to download software updates and to install software updates for software applications installed on a group of client computing devices of a specific enterprise, in order to achieve one of several predefined goals or objectives selected for the specific enterprise, or for the specific group of client computing devices. Using reinforcement learning, a software-based agent learns to perform activities relating to software updates at specific times that minimize a penalty, wherein the penalty is derived based on a weighted combination of metrics, some of which relate to the impact of software update timing on network traffic and power consumption.
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公开(公告)号：US20230352056A1
公开(公告)日：2023-11-02
申请号：US18328240
申请日：2023-06-02
Applicant: Microsoft Technology Licensing, LLC
Inventor： Dhirendra Kumar BHUPATI
IPC: H04L9/40 , G11B27/34 , H04L65/60 , G11B27/036 , G11B27/00 , H04L65/403
CPC classification number: G11B27/036 , G11B27/002 , G11B27/34 , H04L63/0428 , H04L65/403 , H04L65/60
Abstract: Systems and methods for recording a meeting using a retroactive record feature. The present technology provides for improved systems and methods for providing a recording of a virtual meeting, where a selection to initiate the recording from the beginning or an earlier time in the meeting from a current time may be received after the virtual meeting has started. The system may process received meeting content streams to generate a plurality of data segments that may collectively form a meeting recording. Each data segment, for example, may include meeting content associated with a particular user/attendee and associated with a timestamp and/or time duration. In some examples, the plurality of data segments may be stored on a blockchain, which may provide an immutable meeting record that may be concatenated together and made available for playback based on a selection to record the meeting and consent given by the users/attendees.
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