Abstract: Respective statistical distributions of a target variable within a proposed training data set and a proposed test data set for a machine learning model are obtained. A metric indicative of the difference between the two statistical distributions is computed. The difference metric is used to determine whether the proposed test data set is acceptable to evaluate the machine learning model.

Abstract: Techniques are generally described for performing outfit recommendation using a recurrent neural network. In various examples, a computing device may receive a first state vector representing an outfit comprising at least one fashion item. First image data depicting a second fashion item of a first item category may be received. A machine learning mode may generate a first output feature vector based on the first state vector, the first image data, a first attribute vector, and the first item category. The first output feature vector may be compared to other feature vectors representing other fashion items in the first category to determine distances between the first output feature vector and the other feature vectors. A set of fashion items may be recommended based on the distances between the first output feature vector and the other feature vectors.

Abstract: Techniques for implementing a local neural network and global decoding scheme for quantum error correction of circuit-level noise within quantum surface codes such that the decoding schemes have fast decoding throughout and low latency times for quantum algorithms are disclosed. A local neural network decoder may be pre-trained via a supervised learning technique such that the local neural network decoder may be applied for error correction in the presence of circuit-level noise in arbitrarily sized surface codes in a local decoding stage. Prior to a global decoding stage, an intermediate stage may be used to remove vertical pairs of highlighted vertices within the matching graph, which may reduce a syndrome density within the matching graph to allow for faster decoding at the global decoding stage. Such an intermediate stage may include application of a syndrome collapse or vertical cleanup technique.

Abstract: A data storage system having an intermediary server including an input interface, a memory and an output interface. The input interface configured to establish, via one or more programmatic interfaces, a connection with a client device to receive data for upload to a storage server and measure an input rate of the data received from the client device. The memory configured to store the data in a buffer as the data is received. The output interface configured to establish a connection with the storage server, determine an output rate for sending the data from the buffer to the storage server based at least in part on the input rate and a timeout value for the storage server, and send the data from the buffer to the storage server at the output rate.

Abstract: A system, method and processor that mitigates security vulnerabilities using context-dependent address space hiding. In some embodiments, a hardware mechanism allows a more-privileged software component managing multiple less-privileged software components to blind itself against “out-of-context” less-privileged software components. The hardware mechanism can allow the more-privileged software component to dynamically hide a portion of the more-privileged address space related to the “out-of-context” less-privileged software components, based on knowledge of the “in-context” less-privileged software component. A context register is set with a value from which an address range, within the address space of the more-privileged software component, can be determined, where the address range is associated with a first less-privileged software component can be determined.

Abstract: At an artificial intelligence system, training iterations of a first machine learning model are implemented. In a particular iteration, a group of data items are selected from an item collection using active learning, and respective labels selected from a set of tags are obtained for at least some of the items of the group. Using feature processing elements of a different machine learning model, a respective feature set corresponding to individual labeled items is generated in the iteration, and the feature sets are included in a training set used to train the first machine learning model. A trained version of the first machine learning model is stored after a training completion criterion is met.

Abstract: The following description is directed to a logic repository service. In one example, a method of a logic repository service can include receiving a first request to generate configuration data for configurable hardware using a specification for application logic of the configurable hardware. The method can include generating the configuration data for the configurable hardware. The configuration data can include data for implementing the application logic. The method can include encrypting the configuration data to generate encrypted configuration data. The method can include signing the encrypted configuration data using a private key. The method can include transmitting the signed encrypted configuration data in response to the request.

Abstract: A candidate attribute combination of a first data set is identified, such that the candidate attribute combination meets a data type similarity criterion with respect to a collection of data types of sensitive information for which the first data set is to be analyzed. A collection of input features is generated for a machine learning model from the candidate attribute combination, including at least one feature indicative of a statistical relationship between the values of the candidate attribute combination and a second data set. An indication of a predicted probability of a presence of sensitive information in the first data set is obtained using the machine learning model.

Abstract: Systems and methods for device control using near real time learning are disclosed. For example, an automatic action is performed by a target device in response to a predefined condition being met. Thereafter, context data is gathered and utilized to determine whether a negative user reaction has been provided in response to performance of the automatic action. When a negative user reaction is determined, mitigating actions may be taken close in time to when the context data is received to prevent further negative user reactions.

Abstract: At a first resource to be used to perform a computing operation, a pair of execution environments is configured. I/O permissions of programs running in the different environments are based on respective sets of constraints. A program performs the operation in one of the environments, with input data being provided to the program from the second environment. A result of the operation is provided to a destination from the second environment.

Abstract: Techniques are described for facilitating use of software components by software applications in a configurable manner. In some situations, the software components are fee-based components that are made available by providers of the components for use by others in exchange for fees defined by the components providers, and in at least some situations, the software components may have various associated restrictions or other non-price conditions related to their use. The described techniques facilitate use of such software components by software applications in a configured manner. Furthermore, in at least some situation, the execution of such software applications is managed by an application deployment system that controls and tracks the execution of the software application on one or more computing nodes, including to manage the execution of any software components that are part of the software application.

Abstract: This disclosure describes, in part, techniques for retrieving images based on detecting events. For instance, system(s) may detect an event, such as an event associated with a collection of images for an item. Based on detecting the event, the system(s) may determine an area within a facility, such as an inventory location, for retrieving image data. The system(s) may then determine one or more imaging devices that have field(s) of view of the area. Additionally, the system(s) may score the imaging device(s) based on visibility data associated with the imaging device(s). The system(s) may also determine occlusion data for image data generated by the imaging device(s). Using the scores and the occlusion data, the system(s) may then select image data that represents the area. The system(s) may then store the image data in one or more data stores, such as with the collection of images.

Abstract: An edge data pipeline service may build and deploy an edge data pipeline application to an edge device, based on specification provided by a user. The service may receive, from the client, indications for any number of data sources (e.g., cameras, sensors), data sinks (e.g., video files, databases), and application modules (e.g., motiondetect, anomalydetect) to be used by an edge data pipeline application at an edge device. The client may indicate a mapping that maps data sources to data sinks and one or more criteria that, when satisfied, cause an application module to send data from one or more data sources to one or more data sinks according to the mapping. The service builds a package and deploys the package to the edge device, which implements the data pipeline application to route data from sources to sinks.

Abstract: A system includes a location controller for a building, a container arranged to store items, and a device attached to the container. The device includes a first radio and a light emitting diode. The first radio emits a signal. The location controller determines a first location of the device in the building based on the signal and communicates, based on the first location of the device in the building, a first instruction to the device indicating that the device should be moved to a second location. The light emitting diode emits light of a first color in response to the first instruction.

Abstract: Systems and methods are described for implementing a multi-tenant caching service. The multi-tenant caching service provides a scalable infrastructure with dedicated per-tenant cache widths for tenants of a hosted computing environment, and allows tenants to implement a caching layer between cloud-based services that would otherwise need to scale up in response to load. Tenants may also use the service as a public facing endpoint that caches content provided by backend servers. Content provided by the tenants may be distributed and cached across a cell-based architecture, each cell of which may include a set of storage volumes that are partitioned into caches for individual tenants and configured to store a portion of the content provided by that tenant. Eviction policies may be implemented based on tenant cache usage across multiple cells, and geolocation policies may be implemented to ensure that cached content remains within a particular geographic region.

Abstract: Systems, devices, and methods are provided for training and/or inferencing using a list ordering model. A list ordering model, such as a Markov chain, may be trained using a plurality of lists with location metadata in common, wherein a first list of the plurality comprises items and corresponding competition timestamps. A list ordering model may accept, as an input, a plurality of items, and determine, as an output, an order for the plurality of items. Recommendations may be generated based on the determined order.

Abstract: Systems and methods for integration of speech processing functionality with organization systems are disclosed. For example, a voice interface application may be created to enable a voice interface functionality for devices associated with an organization. Space identifiers of spaces of the organization may be created and associated with the voice interface application. Devices associated with the space identifiers may be enabled for utilizing the voice interface application and may be set up utilizing wireless network identifiers associated with the spaces and/or the organization.