Abstract: A latency processing system detects traffic at a cloud service end point and analyzes packets in the detected traffic to identify a network configuration of a client that is accessing the cloud service. Latency components corresponding to different parts of the network configuration are identified and quantified. A recommendation engine is controlled to generate and surface an output indicative of recommendations for reducing network latency.

Abstract: Based on replay of a thread, one implementation observes an influx of a value of a memory cell comprising an interaction between the thread and the value of the memory cell at an execution time point in the replaying, and determines whether the value of the memory cell observed from the influx is inconsistent with a prior value of the memory cell as known by the thread at the execution time point. If so, this implementation initiates an indication of a data inconsistency. Based on replay of a plurality of threads, another implementation identifies a memory cell that was accessed by a first thread while a thread synchronization mechanism was active on the first thread. Then, if there was another access to the memory cell by a second thread without use of the thread synchronization mechanism, this implementation initiates an indication of a potential data contention.

Abstract: Technologies for unseen notification handling are described. Embodiments select an initial set of notifications, provide the selected initial set of notifications to a client device, store seen notifications in a first data store, maintain sent but unseen notifications in a second data store that is an in-memory online data store, retrieve a set of the sent but unseen notifications from the second data store, create a list of unseen notifications by combining the retrieved set of sent but unseen notifications with a set of unsent and unseen notifications, generate a set of relevance scores for the list of unseen notifications, create a new version of the list of unseen notifications based on the new set of relevance scores, and provide the new version of the list of the unseen notifications to the client device.

Abstract: Machine learning is utilized to learn an optimized quantization configuration for an artificial neural network (ANN). For example, an ANN can be utilized to learn an optimal bit width for quantizing weights for layers of the ANN. The ANN can also be utilized to learn an optimal bit width for quantizing activation values for the layers of the ANN. Once the bit widths have been learned, they can be utilized at inference time to improve the performance of the ANN by quantizing the weights and activation values of the layers of the ANN.

Abstract: In an example embodiment, a framework to infer a user's value for a particular attribute based upon a multi-task machine learning process with uncertainty weighting that incorporates signals from multiple contexts is provided. In an example embodiment, the framework aims to measure a level of a user attribute under a certain context. Rather than attempting to devise a universal, one-size-fits-all value for the attribute, the framework acknowledges that the user's value for that attribute can vary depending on context and factors in the context under which the user's attribute levels are measured. Multiple contexts are defined depending on different situations where users and entities such as companies and organizations need to evaluate user attribute levels. Signals for attribute levels are then collected for each context. Machine learning models are utilized to estimate attribute values for different contexts. Multi-task deep learning is used to level attributes from different contexts.

Abstract: Neural processing elements are configured with a hardware AND gate configured to perform a logical AND operation between a sign extend signal and a most significant bit (“MSB”) of an operand. The state of the sign extend signal can be based upon a type of a layer of a deep neural network (“DNN”) that generate the operand. If the sign extend signal is logical FALSE, no sign extension is performed. If the sign extend signal is logical TRUE, a concatenator concatenates the output of the hardware AND gate and the operand, thereby extending the operand from an N-bit unsigned binary value to an N+1 bit signed binary value. The neural processing element can also include another hardware AND gate and another concatenator for processing another operand similarly. The outputs of the concatenators for both operands are provided to a hardware binary multiplier.

Abstract: Techniques of keyless authentication of computing services in distributed computing systems are disclosed herein. One example technique includes upon receiving a command to instantiate a computing service, transmitting a request to an authentication service for an identity assertion token corresponding to an application execution of which instantiates the computing service. The example technique can also include upon receiving the requested identity assertion token, storing the received identity assertion token in the container and modifying an entry of a configuration file in the container that allows the instantiated computing service to access the stored identity assertion token and authenticate to the authentication service using the identity assertion token.

Abstract: A liquid-submersible thermal management system includes a cylindrical outer shell and an inner shell positioned in an interior volume of the outer shell. The cylindrical outer shell has a longitudinal axis oriented vertically relative to a direction of gravity, and the inner shell defines an immersion chamber. The liquid-submersible thermal management system a spine positioned inside the immersion chamber and oriented at least partially in a direction of the longitudinal axis with a heat-generating component located in the immersion chamber. A working fluid is positioned in the immersion chamber and at least partially surrounding the heat-generating component. The working fluid receives heat from the heat-generating component.

Abstract: A display with a curved portion is provided. The display includes a capacitive sensor mesh layer including a plurality of cells, wherein at least a cell of the plurality of cells includes at least one cell face that has a discontinuity in the cell face based at least in part on a position of the cell on the curved portion.

Abstract: Computerized systems are provided for detecting or receiving a sharing gesture in a communication group and responsively instantiating or updating one or more computer objects that include rich contextual data associated with the sharing gesture. These computer objects can be instantiated or updated based on one or more rules or policies. These computer objects or associated indications can be surfaced back to a user to give the user context regarding the shared resource. It can be determined whether a user has access to (or permission to access) such a computer object and/or an associated computer resource for presentation to the user.

Abstract: Examples of the present disclosure describe systems and methods for probabilistic neural network architecture generation. In an example, an underlying distribution over neural network architectures based on various parameters is sampled using probabilistic modeling. Training data is evaluated in order to iteratively update the underlying distribution, thereby generating a probability distribution over the neural network architectures. The distribution is iteratively trained until the parameters associated with the neural network architecture converge. Once it is determined that the parameters have converged, the resulting probability distribution may be used to generate a resulting neural network architecture. As a result, intermediate architectures need not be fully trained, which dramatically reduces memory usage and/or processing time.

Abstract: Embodiments of the disclosure extract annotations from web pages. The annotations are combined with search results and/or advertisements to allow the user to better understand the content of the search result or advertisement landing web page. A visual snapshot of the web page is taken. Visual processing extracts information from the visual representation. The HTML, for the web page is also analyzed and various pieces of information extracted. The information from the visual processing is combined with the information extracted from the HTML. The combined information is evaluated and information for the annotations are selected. The annotations are then combined with the search results and/or advertisements.

Abstract: Techniques for generating a high resolution full color output image from lower resolution sparse color input images are disclosed. A camera generates images. The camera's sensor has a sparse Bayer pattern. While the camera is generating the images, IMU data for each image is acquired. The IMU data indicates a corresponding pose the camera was in while the camera generated each image. The images and IMU data are fed into a motion model, which performs temporal filtering on the images and uses the IMU data to generate a red-only image, a green-only image, a blue-only image, and a monochrome image. The color images are up-sampled to match the resolution of the monochrome image. A high resolution output color image is generated by combining the up-sampled images and the monochrome image.

Abstract: A computing device is provided, including a plurality of memory devices, a plurality of direct memory access (DMA) controllers, and an on-chip interconnect. The on-chip interconnect may be configured to implement control logic to convey a read request from a primary DMA controller of the plurality of DMA controllers to a source memory device of the plurality of memory devices. The on-chip interconnect may be further configured to implement the control logic to convey a read response from the source memory device to the primary DMA controller and one or more secondary DMA controllers of the plurality of DMA controllers.

Abstract: A method for estimating human body temperature includes receiving, via a thermal camera, a thermal image captured of a real-world environment, the thermal image including thermal intensity values for each of a plurality of pixels of the thermal image. A position of a human face is identified within the thermal image, the human face corresponding to a human subject. An indication of a distance between the human subject and the thermal camera is received. Based on the distance, a distance correction factor is applied to one or more thermal intensity values of one or more pixels corresponding to the human face to give one or more distance-corrected thermal intensity values. Based on the one or more distance-corrected thermal intensity values an indication of a body temperature of the human subject is reported.

Abstract: Disclosed in some examples are methods, systems, and machine readable mediums for efficient asynchronous replication of hierarchical records across data storage locations. Methods and systems are also described for efficiently updating replicated records. Disclosed also in some examples are improved storage, replication, and distribution of data related to network-based meetings (e.g., media) in hierarchical records. Data for one or more components of the meeting (e.g., media) may be stored in a child record (called a component record). The network-based meeting may be described by a parent record with links to, and in some examples descriptions of, the meeting component records (the child records).

Abstract: The description relates to modeling acoustic effects in scenes with dynamic portals. One implementation includes obtaining a representation of a scene having a plurality of portals and simulating sound travel in the scene using a plurality of probes deployed in the scene. The implementation also includes determining acoustic parameters for initial sound traveling between respective probes based at least on the simulating. The implementation also includes identifying one or more intercepted portals in the scene that are intercepted by a particular initial sound path from a particular source location to a particular listener location, using particular acoustic parameters for the particular source location and the particular listener location.

Abstract: An automated program repair system uses a neural transformer model with attention to predict a bug-free version of a method having a source code bug identified in an associated stack trace. The neural transformer model is pre-trained with English language text and the source code of a target programming language. The pre-trained neural transformer model is trained to create synthetic bugs in bug-free methods. The bug-free methods with the synthetic bugs are executed with a test case to obtain a stack trace of the source code bug. The method with the synthetic bug, without the bug, and its stack trace are used to train the neural transformer model to predict repairs for buggy methods.

Abstract: Examples are disclosed that relate to computing devices, head-mounted display devices, and methods for displaying holographic objects using slicing planes or volumes. In one example a computing device causes a display system to display a holographic object associated with a holographic volume, the holographic object occluding an occluded holographic object that is not displayed. Location data of at least a portion of a hand is received from a sensor. The location data of the hand is used to locate a slicing plane or a slicing volume within the holographic volume. Based on the location of the slicing plane or the slicing volume, at least a portion of the occluded holographic object is displayed via the display system.

Abstract: Examples are disclosed relating to performing signal processing on time-of-flight sensor data using pixelwise temporal metrics. One example provides a computing system comprising a logic machine, and a storage machine holding instructions executable by the logic machine to obtain temporal phase data for a plurality of pixels as acquired by a time-of-flight image sensor, the temporal phase data comprising phase data for a plurality of light modulation frequencies, determine temporal active brightness data for the pixel, and, for each pixel of the plurality of pixels, determine a statistical metric for the temporal active brightness data. The instructions are further executable to perform phase unwrapping on the temporal phase data for the plurality of pixels to obtain a depth image, based on the statistical metric for the temporal active brightness data, perform a denoising operation on at least some pixels of the depth image, and output the depth image.