Abstract: Technologies directed to a hybrid-feed network of a parallel feed network and series-fed sub-arrays are described. The hybrid-feed network includes a parallel feed network and multiple groups of series-fed tiles, each tile including a beamforming integrated circuit (IC) and a set of antenna elements.

Abstract: A schema and cell value aware Named Entity Recognition (NER) model is used to perform natural language queries. Natural language queries may be received via an interface of a natural language query processing system. A fuzzy search may be performed that allows non-exact matches for column names or cell values of data sets potentially used to answer the natural language query. An NER model that adds a type embedding for an exact match of a column name or cell found in the fuzzy search that corresponds to a span of one or more words may be applied as part of generating the entity prediction for the natural language query. One or more queries to at least one of the data sets may be performed to return a result to the natural language query using the entity prediction generated by the NER machine learning model.

Abstract: Systems and methods are disclosed for containers having mechanical secured door indicators. In one embodiment, an example container may include a first container wall, a second container wall, a third container wall, and a fourth container wall configured to move from an open position to a closed positon. The fourth container wall may include a first portion coupled to the second container wall, and a second portion coupled to the third container wall, where the first portion and the second portion are coplanar when the fourth container wall is in the closed position. The foldable container may include a bottom container platform having a machine-readable code, and a pivotable arm configured to cover the machine-readable code when the fourth container wall is in the closed position, and to uncover the machine-readable code when the fourth container wall is not in the closed position.

Abstract: Generated instruction sequences captured from software interactions may be executed as part of formal verification of a design under test. Software-instructed commands to be performed to configure a design under test formatted according to an interface implemented by the design under test can be obtained. A sequence to perform the software-instructed commands may be generated to configure the design under test in a hardware design and verification language. The sequence may then be executed to perform the software-instructed commands to configure the design under test and then perform formal verification on the configured design under test.

Abstract: Media content may be mastered at a higher quality than is supported on various remote workstations to perform tasks with respect to that content, using transmission channels that do not support data transfer rates for large, high quality media content. A compressed version of this content may be transmitted over a first channel for use with various tasks on a remote workstation. For tasks such as color grading that benefit from this higher quality content, a separate but parallel communication channel is used to transmit a higher-quality version of this content. An uncompressed video stream can be encoded using a lossless codec to retain higher quality data. A high quality video stream can be transmitted over a separate transmission channel, and received to a decoder that can decode this stream to provide a high quality video signal for presentation via a grading monitor or other such high quality presentation device.

Abstract: Systems and methods for processing a DNS query to identify and implement pre-processing information by a DNS server component in anticipation of a corresponding content request from a client computing device are provided. The pre-processing information can correspond to identification of content to be preloaded or other actions to be implemented by one or more computing devices in association with an anticipated client content request. Based on identification of the content or future actions, a DNS server component can provide the pre-processing information to one or more computing devices, such as computing devices of a CDN service provider and/or an original content provider, in advance of a corresponding request for content from the client computing device in order to improve performance associated with responding to the client request.

Abstract: Maintaining the security of biometric data is an utmost priority. Biometric data is secured using one or more techniques. With one technique, biometric input such as images of a user's palm is used to generate first primary data (PD). The original biometric input is deleted from temporary secure storage while the first PD is securely stored. The first PD may then be processed later to determine a second PD. The first PD may then be deleted, and the second PD subsequently used. With another technique, biometric input or a PD may be processed by a first model to determine first secondary data (SD) that is representative of features of a particular user within a first embedding space. Later the PD may be processed by a second model to determine a second SD in a second embedding space. The first SD is deleted, and the second SD subsequently used.

Abstract: A device includes a housing, a camera at least partially disposed within the housing, one or more microphones at least partially disposed within the housing, and a printed circuit board (PCB) including a switch. The switch has a lever that is transitionable between a displaced position and a non-displaced position. A privacy cover couple to the housing and includes a rib disposed on an interior surface of the privacy cover. The privacy cover is transitionable between a first position in which the camera is obstructed and the rib is engaged with the lever to transition the lever to the displaced position, and a second position in which the camera is unobstructed and the rib is disengaged with the lever such that the lever is permitted to transition to the non-displaced position.

Abstract: A fault tolerant quantum computer is implemented using hybrid acoustic-electric qubits or electromagnetic qubits, as a few examples. A control circuit includes symmetrically arranged asymmetrically threaded superconducting quantum interference devices (ATSs) that excite phonons in a resonator by driving a storage mode of the resonator and dissipate phonons from the resonator via an open transmission line coupled to the control circuit, wherein the open transmission line is configured to absorb photons from a dump mode of the control circuit. The symmetric ATSs are arranged such that undesirable terms in respective Hamiltonians for the ATSs individually, cancel each other out when combined in the symmetric configuration.

Abstract: Real-time audio enhancement for a target speaker may be performed. An embedding of a sample of speaker audio is created using a trained neural network that performs voice identification. The embedding is then concatenated with the input features of a trained machine learning model for audio enhancement. The audio enhancement model can recognize and enhance a target speaker's speech in a real-time implementation, as the embedding is in the same feature space of the audio enhancement model.

Abstract: A storage object and an associated permissions record is stored at a storage server. The permissions record indicates that some storage consumers are not permitted to perform a type of I/O operation on the storage object. In response to detecting that an event of a deletion triggering type with respect to the records, a modified version of the permissions record is stored at the server, indicating that the storage consumers remain prohibited from performing the I/O operations. In response to receiving a command to perform a particular I/O at the server after the modified version has been stored, the modified version is used to process the command.

Abstract: During text-to-speech processing, a speech model creates output audio data, including speech, that corresponds to input text data that includes a representation of the speech. A spectrogram estimator estimates a frequency spectrogram of the speech; the corresponding frequency-spectrogram data is used to condition the speech model. A plurality of acoustic features corresponding to different segments of the input text data, such as phonemes, syllable-level features, and/or word-level features, may be separately encoded into context vectors; the spectrogram estimator uses these separate context vectors to create the frequency spectrogram.

Abstract: Systems and techniques for validation and generation of localized content for audio and video are described herein. The systems and techniques provide for training of twin neural networks to evaluate performance characteristics, sometimes referred to as content-auxiliary characteristics, of a localized performance. The localized performance may be validated or improved by identifying misalignment in the performance characteristics to ensure that localized content preserves content as well as creative intent and performance ability in the final product. The machine learning models trained using the techniques described herein may be used in connection with auto-localization processes to automatically generate high quality localized audio and video content.

Abstract: A system configured to improve audio processing by performing dereverberation and noise reduction during a communication session. In some examples, the system may include a deep neural network (DNN) configured to perform speech enhancement, which is located after an Acoustic Echo Cancellation (AEC) component. For example, the DNN may process isolated audio data output by the AEC component to jointly mitigate additive noise and reverberation. In other examples, the system may include a DNN configured to perform acoustic interference cancellation, which may jointly mitigate additive noise, reverberation, and residual echo, removing the need to perform residual echo suppression processing. The DNN is configured to process complex-valued spectrograms corresponding to the isolated audio data and/or estimated echo data generated by the AEC component.

Abstract: An object data store may generate metadata responsive to a request that causes a scan of a data object for subsequent use in performing queries to the data object. A request may be received that causes a scan operation of the data object. As part of performing the scan one or multiple types of metadata describing the data object may be generated. The generated metadata may be applied to access the data object and perform a subsequently received query to the data object at the object data store.

Abstract: Enhanced graphical user interfaces for transcription of audio and video messages is disclosed. Audio data may be transcribed, and the transcription may include emphasized words and/or punctuation corresponding to emphasis of user speech. Additionally, the transcription may be translated into a second language. A message spoken by a user depicted in one or more images of video data may also be transcribed and provided to one or more devices.

Abstract: This disclosure describes a system for fulfilling items at a materials handling facility. In some instances, a predicted items list that identifies items that are likely to be picked by a user are determined and, when the user arrives at the materials handling facility, those predicted items are presented to the user for selection. For example, predicted items may be determined and an inventory holder that holds one or more of those predicted items may be retrieved by a mobile drive unit (such as a Kiva mobile drive unit) and presented to the user at a retrieval area. The user may pick the items they desire from the presented inventory holder.

Abstract: Techniques are disclosed to implement an adaptive testing service (ATS) capable of automatically generating test cases for a network service to adapt test coverage to observed behaviors of the network service. In embodiments, the ATS uses telemetry data from a production version of the network service to identify classes of testable behaviors. Test cases are generated for the behaviors and assigned weights based on frequency or recency metrics of the behaviors. The test cases are stored in a test case repository, and may be used to monitor the production version of the network service or verify code changes to a development version of the network service. The test case weights may be used to select which test cases to run or determine whether code changes should be accepted or rejected. The test cases are evolved over time to adapt to behavior changes in the network service.

Abstract: Systems, devices, and methods are described herein for improving object detection frameworks. Proposed regions can be used to identify similar images from a novel image set. Once identified, a weighted average of the feature representations of the similar images and/or a probability distribution of the classification labels for those images can be generated. The weighted average of the feature representations and/or the probability distribution can be used to steer the predicted classification confidence and/or predicted bounding box coordinates of the object detection framework. The disclosed techniques can be easily integrated with the object detect framework to improve the accuracy of its predictions without adding additional trainable parameters so as to refrain from adding complexity to the learning process.

Abstract: Techniques for guiding camera focusing using barcode images are described herein. In an example, a computer system receives an image of a calibration target having a center that is aligned with an optical axis of a camera that generated the image. The calibration target includes steps that are located at different depths with respect to a lens of the camera. The calibration target includes barcode sets. Individual barcodes of a barcode set have a barcode attribute. The computer system decodes the barcode sets in the image and determines a set of decoded barcodes of the barcode sets. The computer system determines, for individual steps, a sharpness metric based on the barcode attribute of individual barcodes of the set of decoded barcodes and determines an adjustment of a focal plane of the lens based on the sharpness metric for the individual steps.