Abstract: Customized navigation maps of an area are generated for autonomous vehicles based on a baseline map of the area, transportation systems within the area, and attributes of the autonomous vehicles. The customized navigation maps include a plurality of paths, and two or more of the paths may form an optimal route for performing a task by an autonomous vehicle. Customized navigation maps may be generated for outdoor spaces or indoor spaces, and include specific infrastructure or features on which a specific autonomous vehicle may be configured for travel. Routes may be determined based on access points at destinations such as buildings, and the access points may be manually selected by a user or automatically selected on any basis. The autonomous vehicles may be guided by GPS systems when traveling outdoors, and by imaging devices or other systems when traveling indoors.

Abstract: A system and method performs multilingual wakeword detection by determining a language corresponding to the wakeword. A first wakeword-detection component, which may execute using a digital-signal processor, determines that audio data includes a representation of the wakeword and determines a language corresponding to the wakeword. A second, more accurate wakeword-detection component may then process the audio data using the language to confirm that it includes the representation of the wakeword. The audio data may then be sent to a remote system for further processing.

Abstract: Autonomous mobile robots (AMRs) having adaptive safety systems may operate individually or as part of a convoy. During individual operations, an AMR may determine a safety zone and stop responsive to detecting an object within the safety zone. During convoy operations, an AMR may selectively mute a portion of the safety zone and allow a forward AMR of a convoy within the portion of the safety zone. In this manner, the adaptive safety systems may enable convoy operations of multiple AMRs with relatively greater density and greater speed, thereby improving speed and efficiency of AMR operations without negatively impacting safety.

Abstract: Intermodal vehicles may be loaded with items and an aerial vehicle, and directed to travel to areas where demand for the items is known or anticipated. The intermodal vehicles may be coupled to locomotives, container ships, road tractors or other vehicles, and equipped with systems for loading one or more items onto the aerial vehicle, and for launching or retrieving the aerial vehicle while the intermodal vehicles are in motion. The areas where the demand is known or anticipated may be identified on any basis, including but not limited to past histories of purchases or deliveries to such areas, or events that are scheduled to occur in such areas. Additionally, intermodal vehicles may be loaded with replacement parts and/or inspection equipment, and configured to conduct repairs, servicing operations or inspections on aerial vehicles within the intermodal vehicles, while the intermodal vehicles are in motion.

Abstract: Techniques for generating a visual response to a user input are described. A system may receive a natural language input and use a machine learning model to determine a first component is to determine a response to the natural language input while a second component is to determine supplemental content related to the natural language input. The system may receive, from the first component, first image data corresponding to the response. The system may also receive, from the second component, second image data corresponding to the supplemental content. The system may send, to a display, a command to present the first image data and the second image data.

Abstract: A post-task-completion retention period for which a computing resource is to be retained, without de-activating the resource, on behalf of a set of requesters of machine learning tasks is determined at a machine learning service. A first task, identified at the service prior to expiration of the retention period at a first computing resource at which a second task has completed, is initiated at the first computing resource. In response to obtaining an indication of a third task and determining that a threshold criterion associated with the retention period satisfies a criterion, the third task is initiated at an additional computing resource. The additional computing resource is de-activated after the third task completes, without waiting for the retention period to expire.

Abstract: This disclosure describes techniques implemented partly by a communications service for identifying and altering undesirable portions of communication data, such as audio data and video data, from a communication session between computing devices. For example, the communications service may monitor the communications session to alter or remove undesirable audio data, such as a dog barking, a doorbell ringing, etc., and/or video data, such as rude gestures, inappropriate facial expressions, etc. The communications service may stream the communication data for the communication session partly through managed servers and analyze the communication data to detect undesirable portions. The communications service may alter or remove the portions of communication data received from a first user device, such as by filtering, refraining from transmitting, or modifying the undesirable portions.

Abstract: Methods, systems, and computer-readable media for query language interoperability in a graph database are disclosed. Data elements are inserted into a graph database using one or more of a plurality of graph database query languages. The graph database query languages comprise a first graph database query language associated with a first data model and a second graph database query language associated with a second data model. The data elements are stored in the graph database using an internal data model that differs from the first and second data models. One or more of the data elements are retrieved from the graph database based at least in part on a query. The query is expressed using a different graph database query language than the graph database query language used to insert the one or more retrieved data elements.

Abstract: Clusters of users of networked services are defined based on tasks performed by such users during such networked services. Activities of the users during sessions of the networked services are tracked, and representations of such users or such activities are used to train a model to predict activities of users in the future, including but not limited to services utilized by such users, or pages visited by such users. Subsequently, when a user accesses a networked service during a session, activities of the user may be determined, and a representation of the session is provided as an input to the model, along with contextual information such as an identifier of the persona of the user. A next action, e.g., a service or a page utilized by the user, may be predicted based on outputs received from the model.

Abstract: Communication in an asymmetric multiengine system is handled using engine routing tables defining subsets of engines to control engine-to-engine connection mapping. Local devices perform an engine selection process that includes selecting an engine routing table based on a number of remote engines in a remote device and selecting an engine set from the selected table based on an identifier of the remote device. A connection to the remote device is created using the engines identified in the selected engine set.

Abstract: Systems and processes are described for a message service with distributed key caching for server-side encryption. Message requests are received by message handlers of the message service that cache data encryption keys used to encrypt and decrypt messages that are stored to message containers in back end storage. A metadata service obtains the data encryption keys from a key management service, caches the keys locally, and sends the keys to the message handlers upon request, where the keys are cached, again. The key management service may generate the data encryption keys based on a master key (e.g., a client's master key). The message handlers may send both message data encrypted using the data encryption key and an encrypted copy of the data encryption key to be stored together in the data store.

Abstract: An electric vehicle supply equipment (EVSE) holster including a locking mechanism and an image capture device is described herein. The image capture device is configured to capture image data relating to a connector face of the charging connector when the charging connector is inserted into the holster. The image data is then analyzed to determine if a physical abnormality is present on the charging connector (for example, damage to the charging connector or debris lodged in the charging connector. If a physical abnormality is detected, the locking mechanism is actuated to lock the charging connector to the holster until maintenance is performed on the charging connector.

Abstract: A satellite antenna ground station service includes a plurality of ground stations and associated data centers, wherein the data centers are part of a provider network. Clients may reserve satellite antenna access time-slots via a user interface of the satellite antenna ground station service and store data directly to a data center of the provider network or to the client's premises via a direct connection between the client and the provider network. In some embodiments, the provider network may offer a plurality of network-based services, such as a compute service, a data storage service, a machine learning service, or a data analytics service, and a client may utilize one or more of these services to analyze and process downlinked data received from a satellite of the client via a satellite antenna ground station of the satellite antenna ground station service of the provider network.

Abstract: Method and apparatus for compressing raw event logs into smaller readable formats are described. An example includes receiving an uncompressed log file including traces of events executed on a computing system. In the uncompressed log file, a number of consecutive events are identified referencing an action performed with different parameters, and the uncompressed log file is modified by replacing the identified consecutive events with a record indicating that an event has been repeated the number of times. In the modified log file, repeated sequences of events are identified, a compressed log file is generated by replacing, in the modified log file, repeated sequences of events with a record referencing an initial repetition of events and a difference between parameters included in the initial repetition of events and a respective repeated sequence, and the generated compressed log file is output.

Abstract: Systems and methods for contextual awareness in dynamic device groups are disclosed. For example, a dynamic device group may be generated while output of content is occurring. When a user provides user input to alter the output of the content, contextual data indicating the devices in the dynamic device group when the user input is received may be generated and utilized by an application to determine which devices are to receive a command to perform an action responsive to the user input.

Abstract: A system and method for associating motion data with utterance audio data for use with a speech processing system. A device, such as a wearable device, may be capable of capturing utterance audio data and sending it to a remote server for speech processing, for example for execution of a command represented in the utterance. The device may also capture motion data using motion sensors of the device. The motion data may correspond to gestures, such as head gestures, that may be interpreted by the speech processing system to determine and execute commands. The device may associate the motion data with the audio data so the remote server knows what motion data corresponds to what portion of audio data for purposes of interpreting and executing commands. Metadata sent with the audio data and/or motion data may include association data such as timestamps, session identifiers, message identifiers, etc.

Abstract: Various embodiments of apparatuses and methods for an automated machine learning pipeline service and an automated machine learning pipeline generator are described. In some embodiments, the service receives a request from a user to generate a machine learning solution, as well as a dataset that comprises values with different user variable types, and mapping of the user variable types to pre-defined types. The generator can validate the dataset, enrich the values of the dataset using external data sources, transform values of the dataset based on the pre-defined types, train a machine learning model using the enriched and transformed values, and compose an executable package, comprising enrichment recipes, transformation recipes, and the trained machine learning model, that generates scores for other data when executed. The service can further test the executable package using testing data, and provide results of the test to the user.

Abstract: Techniques for recommending a skill experience to a user after a user-system dialog session has ended are described. Upon a dialog session ending, the system uses a first machine learning model to determine potential intents to recommend to a user. The system then uses a second machine learning model to determine a particular skill and intent to recommend. The system then prompts the user to accept the recommended skill and intent. If the user accepts, the system calls the recommended skill to execute. As part of calling the skill, the system sends to the skill at least one entity provided in a natural language user input of the ended dialog session. This enables the skill to skip welcome prompts, and initiate processing to output a response based on the intent and the at least one entity of the ended dialog session.

Abstract: Techniques for an ontology-based approach for modeling service dependencies in a provider network. The approach is flexible and extensible to different provider network SOA systems and not limited to a particular provider network or a particular SOA system. The approach can be used to model an entire SOA system or selected portion thereof and from different perspectives. In some examples, the approach uses an ontology represented using a Web Ontology Language (OWL). In some examples, the ontology is used to identify service dependencies and relationships in a knowledge base that is populated based on operational data collected in the provider network environment.

Abstract: Methods, systems, and computer-readable media for a scalable architecture for a distributed time-series database are disclosed. Using a fleet of ingestion routers, time-series data generated by a plurality of client devices is stored into a plurality of durable partitions. The time-series data comprises a plurality of time series, and an amount of the ingestion routers is determined based at least in part on an ingestion rate of the time-series data. Using a fleet of stream processors, the time-series data from the durable partitions is stored into a plurality of storage tiers including a first storage tier and a second storage tier. A retention period for the first storage tier differs from a retention period for the second storage tier. An amount of the stream processors is determined based at least in part on the time-series data in the durable partitions.