Abstract: Systems and methods for information retrieval are described. Embodiments generate a dense embedding for each of a plurality of media objects to be searched, generate a sparse embedding for each of the media objects using an encoder that takes the dense embedding as an input, wherein the sparse embedding satisfies a sparsity constraint that is applied to at least one layer of the encoder during training, and perform a search on the plurality of media objects based at least in part on the sparse embedding.

Abstract: A system can provide a visual representation of an inventory of data entities for a distributed computing system. Inventory data including cost and operational data for data entities such as data centers, servers, and virtual machines, can be converted into a format file. The format file can be used to create a tree of nodes and node summaries corresponding to the data entities. A user interface can display hierarchical and isolated views of the tree revealing parent child relationships between data entities within a computing system infrastructure. Node summaries including cost and utilization data can be displayed to reveal how specific sub-costs such as labor and licensing, are driven by data entities in one level of the infrastructure and pushed to respective parent or child data entities in other levels. Views of the tree can be used to determine areas of inefficiency or reduced value within the computing system.

Abstract: The disclosure describes embodiments for vehicle-to-everything (V2X) data transfer for automated vehicles. In some embodiments, a method includes providing or attempting to provide, by a communication unit of an ego vehicle, digital data to a communication device based on a mode of the communication unit, where the digital data is relayed by the communication device to be received by a server. The method includes determining, by a processor of the ego vehicle, feedback that describes a bandwidth constraint of the communication unit. The method includes modifying, by the processor, the mode based on the feedback so that the mode is consistent with the bandwidth constraint and the digital data is successfully received by the server.

Abstract: Embodiments are directed to methods and systems for automatically determining a resource layout. An example embodiment begins by obtaining data indicating a position and a task performed by each resource of a plurality of resources. Then, for each resource of the plurality, a respective zone on a plane of interest occupied by the resource is automatically determined using the obtained data indicating the position and the task performed by the resource. In turn, determined zones of two or more resources of the plurality of resources are automatically combined into a combined zone based upon criteria and a file, e.g., a CAD/CAM file, indicating a layout of the plurality of resources on the plane of interest is automatically created based upon the determined zones and the combined zone.

Abstract: Embodiments are disclosed for pixel-based techniques for combining vector graphics shapes. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving a selection of a plurality of vector graphics shapes to be combined based on an operation type, identifying a dominant shape based on the operation type, applying stroke and fill properties associated with the dominant shape to each of the plurality of vector graphics shapes, initializing a buffer at least as large as a bounding box associated with the plurality of vector graphics shapes, the buffer storing pixels inside the bounding box, and populating each pixel of the buffer with values representing pixel types determined from the plurality of vector graphics shapes based on the operation type.

Abstract: A server-side administrative interface for a social media platform allows for restriction of defined geographical areas. Social media items originating from such restricted areas are automatically filtered or age-restricted for availability via a map-based graphical user interface of the social media platform.

Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces.

Abstract: The disclosed technology generally relates to ferroelectric materials and semiconductor devices, and more particularly to semiconductor memory devices incorporating doped polar materials. In one aspect, a semiconductor device comprises a capacitor which in turn comprises a polar layer comprising a base polar material doped with a dopant. The base polar material includes one or more metal elements and one or both of oxygen or nitrogen. The dopant comprises a metal element that is different from the one or more metal elements and is present at a concentration such that a ferroelectric switching voltage of the capacitor is different from that of the capacitor having the base polar material without being doped with the dopant by more than about 100 mV. The capacitor stack additionally comprises first and second crystalline conductive oxide electrodes on opposing sides of the polar layer.

Abstract: Autoscaling comprises: accessing operational data associated with a pool of servers; determining an expected load associated with a service provided by the pool of servers based at least in part on the operational data; determining an estimated capacity associated with the service provided by the pool of servers; determining that an autoscale operation is to be performed based at least in part on the expected load and the estimated capacity, wherein the autoscale operation automatically scales out one or more additional servers or automatically scales in one or more servers in the pool of servers; and performing the autoscale operation.

Abstract: The present disclosure provides an application development platform and associated software development kits (“SDKs”) that provide comprehensive services for generation, deployment, and management of machine-learned models used by computer applications such as, for example, mobile applications executed by a mobile computing device. In particular, the application development platform and SDKs can provide or otherwise leverage a unified, cross-platform application programming interface (“API”) that enables access to all of the different machine learning services needed for full machine learning functionality within the application. In such fashion, developers can have access to a single SDK for all machine learning services.

Abstract: In one embodiment for generating passthrough, a computing system may access images of an environment captured by cameras of a device worn by a user. The system may generate, based on the images, depth measurements of objects in the environment. The system may generate a mesh covering a field of view of the user and then update the mesh based on the depth measurements to represent a contour of the objects in the environment. The system may determine a first viewpoint of a first eye of the user and render a first output image based on the first viewpoint and the updated mesh. The system may then display the first output image on a first display of the device, the first display being configured to be viewed by the first eye of the user.

Abstract: Aspects of the present disclosure relate to threat detection of executable files. A plurality of static data points may be extracted from an executable file without decrypting or unpacking the executable file. The executable file may then be analyzed without decrypting or unpacking the executable file. Analysis of the executable file may comprise applying a classifier to the plurality of extracted static data points. The classifier may be trained from data comprising known malicious executable files, known benign executable files and known unwanted executable files. Based upon analysis of the executable file, a determination can be made as to whether the executable file is harmful.

Abstract: Aspects of the disclosure relate to detecting random and/or algorithmically-generated character sequences in domain names. A computing platform may train a machine learning model based on a set of semantically-meaningful words. Subsequently, the computing platform may receive a seed string and a set of domains to be analyzed in connection with the seed string. Based on the machine learning model, the computing platform may apply a classification algorithm to the seed string and the set of domains, where applying the classification algorithm to the seed string and the set of domains produces a classification result. Thereafter, the computing platform may store the classification result.

Abstract: The present technology discloses methods, systems, and non-transitory computer-readable media for defining, for a network primitive in a network domain, whether the network primitive can receive data carrying an assigned context associated from one or more source nodes through a software-defined wide area network (SDWAN) fabric overlay; advertising a capability of the network primitive, the capability stating whether the network primitive can receive the data carrying the assigned context; and controlling selective transmission of the data carrying the assigned context from the one or more source nodes to the network primitive through the SDWAN fabric overlay based on the capability of the network primitive to receive the data carrying the assigned context.

Abstract: The present disclosure is directed to a system and method for viewing jobs managed by heterogeneous job schedulers on heterogeneous computing systems. Organizations often rely on workflow schedulers or job schedulers to execute and manage their workflow pipelines. However, different departments within a large organization may rely on different job scheduling applications for managing their workflows. Without the capability to monitor and manage all or a subset of jobs running on heterogeneous job scheduling applications across the organization at the same time, organizations lack the insight they need to make their workflow pipeline more efficient. The disclosed system and method allows users to monitor jobs or computer applications, including details regarding job execution and service level agreements, running on heterogeneous job schedulers across the organization.

Abstract: This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collect one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to perform an excavation routine by excavating earth from a hole using an excavation tool positioned at a single location within the site. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, navigating the excavation vehicle over a distance while continuously excavating earth from a below surface depth, and preparing a digital terrain model of the site as part of a process for creating the excavation routine.

Abstract: Techniques for suggesting a candidate layout based on historical characteristics are disclosed. A system trains a machine learning model to suggest layouts for three-dimensional spaces. The system obtains sets of historical characteristic data, including spatial characteristics of a particular three-dimensional space and layout characteristics including information indicating items present in the particular three-dimensional space and positioning information indicating a position of each item within the particular three-dimensional space. The system trains the machine learning model based on the sets of historical characteristic data. The system receives a first request for a layout suggestion from a first user, including at least a first set of spatial characteristics for a first three-dimensional space.

Abstract: Methods of doping a semiconductor material are disclosed. Some embodiments provide for conformal doping of three dimensional structures. Some embodiments provide for doping with high concentrations of boron for p-type doping.

Abstract: An excavation vehicle capable of autonomously actuating an excavation tool or navigating an excavation vehicle to perform an excavation routine within an excavation site is described herein. Sensors mounted to the excavation vehicle and the excavation tool produce signals representative of a position and orientation of the corresponding joint relative on the excavation vehicle relative to the excavation site, a position and orientation of the excavation vehicle relative to the excavation site, and one or more features of the excavation site based on the position of the excavation vehicle within the excavation site. A set of solenoids are configured to couple to corresponding hydraulic valves of the excavation tool to actuate the valve. A controller produces actuating signals to control the joints of the excavation tool to autonomously perform the excavation routine based on the signals produced by the sensors.