Abstract: Systems and methods for image-based item identification are disclosed. Image data corresponding to one or more images depicting an item may be sent to one or more remote systems for image-based item identification. The identification indications and/or identification confidence scores received from the remote systems may be aggregated and weighted based at least in part on one or more factors related to the remote systems, the results, domains, image capture timing, image capture angles, and/or events to more accurately identify an item depicted in the images.

Abstract: Techniques for communications in a multi-zone space are described. In an example, a system stores data indicating devices in zones of a space and data indicating zones that are associated with a communications session. A display in a zone presents graphical user interface indicating the zones associated with the communications session. Incoming audio data can be mixed with audio data detected from another participating zone and a speaker in the zone can output this audio data. Audio data detected from the participating zone can also be mixed and sent to a remote device that is an endpoint of the communications session.

Abstract: Techniques for predicting a pair of an enzyme primary sequence and a substrate, and interaction probability for the pair are described. An exemplary method includes receiving a request to predict a pair of an enzyme primary sequence and a substrate, and interaction probability for the pair; combining an enzyme vector, a substrate vector, and an interaction indication for the enzyme and substrate to form a machine learning model input; applying a machine learning model to the machine learning model input to predict the pair of an enzyme primary sequence and a substrate, and interaction probability for the pair; and outputting a result of the application of the machine learning model including the predicted pair of an enzyme primary sequence and a substrate, and interaction probability for the pair.

Abstract: A request is received associated with a review. Within first content, a first field of interest and a second field of interest are identified and within second content, a third field of interest and a fourth field of interest are identified. A review is generated that includes a first indication of the first field of interest and a second indication of the second field of interest within the first content, as well as a third indication of the third field of interest and a fourth indication of the fourth field of interest within the second content. The review is transmitted to a device of a reviewer for reviewing the content.

Abstract: A domain registry (DR) service executing within a service provider network protects data, such as account data, that is associated with different accounts for testing and/or performing other operations/actions by registering an account with one or more domains. The DR service may register an account in one or more domains based on a request by a user. The operations performed that uses/changes data associated with accounts may be restricted based on the domains for which an account is registered. For example, an account that is registered in a “testing” domain may have different workflows/operations performed using the account data associated with the account registered in the testing domain as compared to an account that is not part of the testing domain.

Abstract: An IoT service of a provider network may be used to optimize downlink scheduling for edge devices that use a radio communication protocol (e.g., LoRaWAN). A processing instance receives DL packets from a client application that are to be sent to an edge device. The processing instance adds metadata entries (device ID, message ID) to a metadata queue and stores the DL packets into a data store. A scheduling instance obtains a metadata entry and the associated DL packet, formats the DL packet based on edge device information, and publishes the packet to a gateway topic. A separate connection instance receives the formatted DL packet and sends it to a gateway of the client network.

Abstract: Devices and techniques are generally described for detection of network anomalies. In various examples, first data describing network communication between a plurality of source entities and a plurality of destination entities may be received. In some examples, respective feature data representing network communication between a respective source entity and one or more of the plurality of destination entities may be generated. In some examples, an unsupervised machine learning model may be used to determine a first number of clusters of the feature data. In various cases, a first source entity that is an outlier with respect to the first number of clusters may be determined based at least in part on the first number of clusters. The first source entity may be classified as an anomalous entity.

Abstract: Techniques are described for enabling model-driven server migration workflows in a cloud provider network. Cloud provider networks often provide various types of tools and services that enable users to migrate computing resources (e.g., servers, databases, applications, etc.) from users' on-premises computing environments to a cloud provider network. A model-driven server migration service as described herein comprises a plurality of modular migration components including, e.g., a snapshot validation component, a snapshot conversion component, an injection component, etc. The model-driven server migration service enables users to customize server migration workflows using server migration templates containing descriptive configurations for some or all of the provided migration components.

Abstract: Techniques for performing centralized unsuperivised learning in a multi-domain system are described. A user may request labeled data for an ML task, where the request includes a prompt for obtaining relevant explicit user feedback. The system may use the prompt to collect explicit user feedback for relevant runtime user inputs. After a duration of time (in the user's request for labeled data) has elapsed, the system determines whether collected user feedback indicates processing of the user input was defective and, if so, determines a cause of the defective processing. The system then uses one or more label generators to generate labeled data using the collected user feedback, whether the processing was defective, and the determined defect cause.

Abstract: Time and value ordering may be applied for items stored in data backups. A change log that persists changes to a data set may be updated with changes and used to update an in-memory table for the data set, which describes changes to items up to a current time. An event may be detected to seal the in-memory table from subsequent updates and a persistent data object that orders the items in the in-memory according to both keys of the respective items and the respective time values of the items, as stored in the change log, may be generated and stored as part of a backup for the data set.

Abstract: A system that implements a data storage service may store data for a database table in multiple replicated partitions on respective storage nodes. In response to a request to back up a table, the service may back up individual partitions of the table to a remote storage system independently and (in some cases) in parallel, and may update (or create) and store metadata about the table and its partitions on storage nodes of the data storage service and/or in the remote storage system. Backing up each partition may include exporting it from the database in which the table is stored, packaging and compressing the exported partition for upload, and uploading the exported, packaged, and compressed partition to the remote storage system. The remote storage system may be a key-value durable storage system in which each backed-up partition is accessible using its partition identifier as the key.

Abstract: Techniques are disclosed for detecting an uncovered portion of a body of a person in a frame of video content. In an example, a first machine learning model of a computing system may output a first score for the frame based on a map that identifies a region of the frame associated with an uncovered body part type. Depending on a value of the first score, a second machine learning model that includes a neural network architecture may further analyze the frame to output a second score. The first score and second score may be merged to produce a third score for the frame. A plurality of scores may be determined, respectively, for frames of the video content, and a maximum score may be selected. The video content may be selected for presentation on a display for further evaluation based on the maximum score.

Abstract: Techniques are described for providing an access control list (ACL) assisted process for filtering the analysis and display of dependency relationships among software application components (e.g., packages, files, classes, etc.), e.g., as part of modernization processes aimed at decomposing monolithic applications, identifying anti-patterns, or otherwise analyzing such applications. A software modernization service of a cloud provider network provides discovery agents and other tools that are capable of creating an inventory of users' software applications and collecting application artifacts (e.g., source code or bytecode files) associated with the software applications in users' computing environments. Various techniques are described for using ACLs containing entries enabling or disabling the analysis or display of various application components to customize various modernization processes and results displays.

Abstract: Modular storage systems include load sensors disposed beneath or in association with platforms. The load sensors are pulse-sampled for signals corresponding to loads at time intervals, rather than continuously, in order to conserve electrical power. An item associated with a transaction is identified based on a change in the loads, as determined from the pulse-sampled signals. The platforms are aligned at horizontal or non-horizontal angles, and photovoltaic power sources with banks of photovoltaic cells are mounted to front edges of the platforms. When a user reaches over one of the photovoltaic cells to access an item on a platform, a level of power or voltage generated by the photovoltaic cell is diminished. The item closest to the photovoltaic cell having the diminished power or voltage, or a customer that accessed the item, may be identified accordingly.

Abstract: A hardware security module (HSM) client processes a request to store data in a set of HSMs. The HSM client determines a property of the data indicative of a sensitivity classification of the data. As a result of determining the data lacks a classification as sensitive, the HSM client transmits the data to a data store outside the set of HSMs and updates a database used by the HSM client to associate an identifier of the data with a reference to a location in the data store.

Abstract: An assembly includes a frame and a conveyor mat configured to transition between a retracted state in which the conveyor mat is disposed within a footprint of the frame, and a deployed state in which the conveyor mat is disposed at least partially disposed outside the footprint of the frame. The conveyor mat has a plurality of linkages, a plurality of rollers, a plurality of supports, and a plurality of axles. Individual axles couple to individual linkages of the plurality of linkages, individual rollers of the plurality of rollers, and individual supports of the plurality of supports together. A tensioning system is configured to control the conveyor mat transitioning between the retracted state and the deployed state.

Abstract: Data clean rooms provided for subscribers to advertising analysis services include data regarding advertising impressions, selections, view or conversion events, and memberships of audience segments, and computing functions or capacities for processing the data in an anonymized fashion. When advertisements are presented to customers, and interactions by customers (e.g., impressions, views, clicks, conversions or others) with goods or services are detected, data regarding the interactions may be aggregated and stored. When queries on behalf of an advertiser are identified, data associated with the queries may be retrieved and stored in a data clean room for processing or analysis. Anonymized responses to the query may be returned to the customer or serve as basis for one or more advertising events.

Abstract: A speech recognition platform configured to receive an audio signal that includes speech from a user and perform automatic speech recognition (ASR) on the audio signal to identify ASR results. The platform may identify: (i) a domain of a voice command within the speech based on the ASR results and based on context information associated with the speech or the user, and (ii) an intent of the voice command. In response to identifying the intent, the platform may perform a corresponding action, such as streaming audio to the device, setting a reminder for the user, purchasing an item on behalf of the user, making a reservation for the user or launching an application for the user. In some instances, the speech recognition platform engages in a back-and-forth dialog with the user in order to properly fulfill the user's request.

Abstract: Disclosed are systems, methods, and apparatus of an automated and self-service kiosk that allows customers to select inventory items available from the kiosk and walk or move away with selected inventory item(s) without having to process payment, identify the inventory item(s), or provide any other form of checkout. After a customer has picked one or more items and departed the kiosk, the picked items are determined and the customer charged for the items. For example, one or more of detected weight changes measured at the kiosk and/or images generated at the kiosk may be used to identify items picked by the customer from the kiosk.

Abstract: Techniques for monitoring devices to use ultrasonic signals to detect and track the locations of moving objects in an environment. To determine distance information, the monitoring devices emit a frequency-modulated continuous wave (FMCW) signal at an ultrasound frequency range. Reflections of the FMCW ultrasonic signal are used to generate time-of-arrival (TOA) profiles that indicate distances between the monitoring device and objects in the environment. The reflections can be processed to suppress undesirable interferences, such as reflections off non-mobile objects in the environment (e.g., walls, furniture, etc.), vibrations off the floorings or the ceilings, etc. After processing the reflections, a heatmap can be used to plot the intensity of the reflections for the different TOAs of the reflections, and depict the movement of the user over time. Finally, a Kalman filter is used to smooth the peaks in the intensity values on the plot, and determine the trajectory of the human.