Microsoft Technology Licensing, LLC

Vivek Gupta

Randall Edward Aull

Firdosh Kersy Bhesania

Andrea A Keating

Robert E Harris, Jr

Philip Albert Froese

Robbie Harris

Ehimwenma Nosakhare

Anthony Yuting Chen

Eliyas Yakub

Rahul Ramadas

Wee Hyong Tok

Martin Richard Borve

Jayson L Kastens

Cong Yang

Mawulolo Koku Ameko

Jyh-Han Lin

Qingwei Lin

Vu Minh Le

Fang Liu

Chetan Bansal

Si Qin

Avrilia Floratou

George Evangelos Roussos

Arvind R Aiyar

Inigo Goiri Presa

Jenna Hong

Eli Cortez Custodio Vilarinho

Irene Rogan Shaffer

Jordan Joseph Henkel

Jue Zhang

Joyce Yu Cahoon

Abhishek Uday Kumar Shah

Mark A Kromer

Benjamin Allen Pullen

Mahmoud Sayed

Felipe Vieira Frujeri

Pankaj Bharti Gupta

Yandan Wang

Jason Wang

Sean Gormley T Kelley

Kiran Kudli Anantha Shastry

Shaily Jignesh Fozdar

Yanjie He

Andrea Treviño Gavito

Robert Edward Minneker

Alexander David Fischer

Preston Tapley Stephenson

Soumya Ram

Sidhanth M Panjwani

Camille Jean Couturier

Randell E Aull

Fangkai Yang

Deng Zhong

Bowen Pang

Yan Qiu

Ashish Neupane

Kabir Walia

Abhishek Narain

Gust Verbruggen

Noelle Yanhui Li

David Joseph Donahue

Daniel Muñoz Huerta

Richard Anarfi

Robert Harris

A method for recommending a computer hardware configuration, including: receiving, by a processor, a machine-readable specification of a computing task; extracting, by the processor, a plurality of features from the machine-readable specification of the computing task; supplying, by the processor, the plurality of features to a reinforcement learning model to generate a proposed computer hardware configuration to execute the computing task; and providing, by the processor, the proposed computer hardware configuration to a user.

Automatic selection of computer hardware configuration for data processing pipelines

A method for dynamically adjusting a number of virtual machines for a workload, includes: receiving a probability indicator for each of a plurality of N sequential stages, where N is a natural number greater than 1, of a likelihood that a virtual machine assigned to a workload will be evicted during the N sequential stages; predicting a target number of virtual machines to configure in a current stage for a subsequent stage from among the plurality of N sequential stages based on the probability indicator, a target capacity for the workload, and a current price for maintaining a virtual machine; and configuring a number of virtual machines for the workload during the current stage based on the target number to be loaded for the workload for the subsequent stage.

System and method of dynamically adjusting virtual machines for a workload

A computer-implemented method for proactively detecting and remediating anomalous devices includes accessing, via a network, device attributes corresponding to enterprise devices within an enterprise network, providing the device attributes to a supervised machine learning model, and predicting, via the supervised machine learning model, whether each enterprise device is healthy or anomalous, where the enterprise device is predicted to be healthy unless the supervised machine learning model determines that the probability of the enterprise device being anomalous exceeds a specified confidence threshold. The method includes, for each enterprise device that is predicted to be anomalous, perturbing a portion of the corresponding device attributes via an automated counterfactual generator to generate synthetic data representative of counterfactual healthy devices. The method includes generating recommended remedial action(s) that will cause each enterprise device to approximate each counterfactual healthy device and causing surfacing, via a user interface, of the recommended remedial action(s).

Proactively detecting and remediating anomalous devices using supervised machine learning model and automated counterfactual generator

A computer-implemented method for performing natural language-based data integration includes causing execution of a data integration application on a remote device via a network and causing surfacing of a GUI corresponding to the data integration application on a display of the remote device. The method includes receiving, via the GUI, a natural language input representing a data integration task, generating, via an LLM, a set of ordered activities corresponding to the data integration task represented by the natural language input, and selecting, via the LLM, one or more APIs for performing each activity within the set of ordered activities. The method also includes generating a data pipeline based on the set of ordered activities and the API(s) for performing each activity, as well as back-translating the data pipeline to a desired data format for execution by the data integration application.

Natural language-based data integration

Embodiments described herein are directed to mechanisms that enable roles (e.g., host vs. function, power provider vs. power consumer, master vs. slave, server vs. client, source vs. sink, upstream vs. downstream) to be dynamically assigned between two interconnected dual-role devices in an intelligent and deterministic manner based on the available context on each device.

Intelligent role selection for dual-role devices

Described are examples for synchronizing multiple timing sources in a computing device. At least a first clock associated with a first timing source and a second clock associated with a second timing source can be maintained at the computing device. A request for an indication of a difference in values between the first clock and the second clock can be received from the application. A first elapsed time of the first clock and a second elapsed time of the second clock from a previous instance of an event can be determined by the computing device at an instance of a reoccurring event in a domain of one of the first timing source or the second timing source. An indication related to the first elapsed time and the second elapsed time can be provided to the application.

Synchronizing timing sources in computing devices

A universal serial bus stack may use an emulation layer to grant a non-universal serial bus device access to universal serial bus drivers and applications. The universal serial bus stack may exchange a device communication at an emulation layer. The universal serial bus stack may translate between a universal serial bus communication and the device communication at the emulation layer, and then may exchange the universal serial bus communication at a universal serial bus client interface.

Universal serial bus emulation layer

Systems and methods for specifying extended descriptor information in a device accessed using a communication interface are disclosed. One method includes transmitting a request to a device from a host computing system, and receiving an extended capability descriptor identifying to the host computing system at least one extended descriptor set stored on the device. The extended capability descriptor identifies a minimum operating system version able to support a corresponding extended descriptor set.

Extraction of operating system-specific characteristics via a communication interface

In one example, a host device may identify a serial device connected to the host device to determine a host action. The host device may receive a serial device signal with a child serial device identifier from a serial device bridge. The host device may identify a child serial device based on the child serial device identifier. The host device may execute a host action based on the child serial device.

Child serial device discovery protocol

Various embodiments provide a two-way interface between a URC driver (URCD) and various Protocol Adaption Layer (PAL) drivers. The two-way interface can enable bandwidth to be shared and managed among multiple different PALs. The two-way interface can also be used to implement common radio functionality such as beaconing, channel selection, and address conflict resolution. In at least some embodiments, the two-way interface can be utilized for power management to place PALs in lower power states to conserve power and to support remote wake-up functionality. Further, at least some embodiments can enable vendor-specific PALs to interact with vendor-specific hardware.

Ultra-wideband radio controller driver (URCD)-PAL interface

Growing community of inventors

Bothell, WA, United States of America

Vivek Gupta