Abstract: Systems and methods for training and performing query answering for programming related query answering are disclosed. During a training phase, queries and answers of a training dataset may be encoded as vectors into the Euclidean space. Loss values for query-answer pairs, duplicate queries, and augmented queries may be determined using loss functions and may be used to adjust the model of the encoder. During the operation phase, a query may be received and encoded into the Euclidean space. The encoded answer most proximate to the encoded query may be decoded and provided as the most relevant answer.

Abstract: Systems and methods are described for use of reserved storage capacity at a cloud provider network extension, sometimes referred to as a provider substrate extension (“PSE”) or “outpost”, as a data cache, thereby improving performance of the PSE. The reserved storage capacity may be reserved for a primary purpose, such as data replication in the event of failure of an in-use portion of the PSE's storage capacity. During non-failover operation, the reserved storage capacity may be otherwise unused. Embodiments of the present disclosure enable the reserved storage capacity, when not used for its primary purpose, to be used as a data cache to store information potentially used at the PSE.

Abstract: Features related to systems and methods for reinforcement learning are described. The environment includes one or more agents for automating the training of reinforcement learning (RL) models. The environment may include a simulator or real-world observations. The features described identify key training parameters, resource configurations, virtual network configurations, and simulators based on historical training data.

Abstract: This disclosure describes a test prediction service for predicting needed resources and associated costs for testing projects related to testing of new programs, services, etc., within a service provider network. The test prediction service uses a first machine learning model for predicting “hard costs” using data from a first data source that includes end-to-end test details such as associated resource and infrastructure use (costs) of the service provider network during previous end-to-end testing projects. A second machine learning model is used for predicting “soft costs” using data from a second data source that includes data, e.g., engineering headcount/hours spent developing the end-to-end testing and/or during previous end-to-end testing. The data is used to train the machine learning models. The test prediction service uses the trained machine learning models to generate estimated testing costs of new testing projects when a user enters project attributes for a new testing project.

Abstract: An item retrieval system can include a support defining a continuous pathway having an upper level, a lower level, and an end portion connecting the upper and lower portions. An advancement mechanism can move a carrier having a container advanced along the continuous pathway between the upper and lower levels.

Abstract: Systems, devices, and methods are provided for authorizing access to operating system resources using security policies managed by a service external to the operating system. An operating system may be provisioned with a kernel-mode component that intercepts system calls from applications, determines a request context for the system call, and sends a request to an external policy management service. The policy management service may be used to perform a policy evaluation to determine whether to grant access to operating system resources. In some cases, policies are cached by the operating system. In various examples, the operating system and policy management service are both hosted on resources managed by a computing resource service provider on behalf of a customer to run mainframe workloads.

Abstract: Techniques are disclosed for generating a representation of a motion of an object through a physical topography. In one example, a system receives from a camera a sequence of images that shows the motion of the object within a first field of view of the camera that shows a portion of the physical topography, the portion being mapped to a three-dimensional coordinate space. The object is detected using a computer vision model, and a motion profile of the object is determined that maps the motion of the object to the three-dimensional space. The motion profile is provided to a computing service for being combined with audiovisual data (e.g., including a three-dimensional model of the physical topography), and whereby the combined data is then provided to a user device for subsequent presentation.

Abstract: In response to a programmatic request, configuration information representing a multi-network-segment gateway established on behalf of a customer is stored at a networking service. In response to another programmatic request, a communication session is established between a route signaling node of the gateway and a routing information source located at a customer premise. In response to additional programmatic input, the networking service stores an indication that the gateway is to be used to transfer packets between a cloud-side virtual network and a customer-side virtual network. The routing information exchanged in the session pertains to the cloud-side and customer-side virtual network, and is used to transfer data packets between the two virtual networks.

Abstract: An automatic technique is disclosed to enrich presented answers by highlighting relevant shopping recommendations. The shopping recommendations can either be highlighted within the answer itself, or as an auxiliary list of suggestions. A model is described for selecting phrases from the answer text (sequences of consecutive terms called noun phrases) that refer to potential products that likely represent relevant shopping recommendation in context of the question-answer pair. The noun phrases are then ranked in order of importance. The top-ranked noun phrases are used to search products to be displayed in association with the noun phrases. Clicking or tapping on a highlighted noun phrase launches a shopping-related flow, such as presenting a widget with product recommendations or running a search in a search engine.

Abstract: Techniques for solving quantum circuit mapping problems using reinforcement learning techniques are disclosed. Quantum circuit mapping often requires the use of SWAP gates in order to configure logical quantum computations to be executed using fixed quantum hardware device layouts. A reinforcement learning model takes inputs such as a logical quantum circuit, a physical qubit connectivity graph corresponding to a quantum hardware device, and an initial qubit allocation scheme, and uses such information to schedule quantum gates of the logical quantum circuit for execution using respective physical qubits of the quantum hardware device. A reinforcement learning model that is configured to solve such quantum circuit mapping problems may comprise a neural network that is assisted by a Monte Carlo Tree Search (MCTS) algorithm, wherein the MCTS algorithm guides the neural network towards quantum circuit routing pathways which are more efficient (e.g., require fewer SWAP gates to be scheduled).

Abstract: Synchronous replication for a distributed database system may be performed using an erasure coding scheme. A request that causes a write to a database hosted in a distributed database system is received. A replication message for a synchronous replication technique is generated, then divided and encoded into a number of chunks according to an erasure encoding scheme that allows the replication message to be reassembled with less than the number of chunks. The chunks are sent to another instance of the database which receives and reassembles the replication message from the chunks and responds to acknowledge that the write is committed.

Abstract: Systems and methods for performing medical audio summarizing for medical conversations are disclosed. An audio file and meta data for a medical conversation are provided to a medical audio summarization system. A transcription machine learning model is used by the medical audio summarization system to generate a transcript and a natural language processing service of the medical audio summarization system is used to generate a summary of the transcript. The natural language processing service may include at least four machine learning models that identify medical entities in the transcript, identify speaker roles in the transcript, determine sections of the transcript corresponding to the summary, and extract or abstract phrases for the summary. The identified medical entities and speaker roles, determined sections, and extracted or abstracted phrases may then be used to generate the summary.

Abstract: Based on analysis of a workload associated with a throttling key of a client request directed to a first service, a scale-out requirement of the throttling key is obtained at respective resource managers of a plurality of other services which are utilized by the first service to respond to client requests. The resource managers initiate, asynchronously with respect to one another, resource provisioning tasks at each of the other services to fulfill the scale-out requirement. A throttling limit associated with the throttling key is updated to a second throttling key after the resource provisioning tasks are completed by the resource managers, and the updated limit is used to determine whether to accept another client request associated with the throttling key.

Abstract: Systems and methods of determining and providing optimized deployment plans for deploying software to vehicles are disclosed. In some embodiments, a vehicle software deployment system evaluates one or more cost functions to determine relative costs of different deployment configuration options for deploying software to a vehicle, such as resource costs (e.g., bandwidth, compute, memory, etc.), isolation costs (e.g., limited access to input information, limited connectivity to other ECUs, etc.), performance costs, etc. Based on the evaluation of the one or more cost functions, the vehicle software deployment system determines an optimized deployment plan. Also, the vehicle software deployment system receives telemetry data from the vehicle and automatically determines updated optimized deployment plans in response to changes in configuration of the vehicle indicated in the telemetry data.

Abstract: A vehicle signal relay system enables a relay agent in a first zone of a vehicle to send sensor signals having a first link-layer communication protocol to a software application deployed on a compute unit in another zone of the vehicle that is connected using another link-layer communication protocol. The vehicle signal relay system allows the software application to identify target relay agents with access to needed sensor signals. The vehicle signal relay system may further enable one way or mutual attestation. The vehicle signal relay system may also allow filters to be applied to the subscribed vehicle sensor signals, and may allow the software application to determine a communication protocol to be used between the software application and the relay agent.

Abstract: Techniques for encoding quantum circuit mapping problems as SAT solver optimization problems are disclosed. Quantum circuit mapping often requires the use of SWAP gates in order to configure logical quantum computations to be executed using fixed quantum hardware device layouts. A quantum compilation service takes a logical quantum circuit, a physical qubit connectivity graph, and a requested number of SWAP gates to solve the mapping using and encodes the information into a Conjunctive Normal Form (CNF) equation using a layout-transition-based encoding scheme. The CNF equation is then provided to a SAT solver which attempts to determine an assignment for the mapping using the set number of SWAP gates requested. Multiple CNF equations corresponding to different requested numbers of SWAP gates may be solved for in parallel using multiple SAT solving instances.

Abstract: Systems and methods for providing vehicle software deployment plans that include one or more fallback deployment plans are disclosed. In some embodiments, a vehicle software deployment system determines a deployment plan for deploying one or more software applications one or more electronic control units (ECUs) of a vehicle. Additionally, for one or more failure scenarios, the vehicle software deployment system determines one or more respective fallback deployment plans, such as a deployment plan that assumes one of the ECUs of the vehicle has failed. A deployment plan bundle is provided to the vehicle, comprising a primary deployment plan as well as the one or more fallback deployment plans. In the event that one of the failure scenarios takes place with respect to the vehicle, a deployment agent of the vehicle automatically deploys one of the fallback deployment plans that was provided with the deployment bundle.

Abstract: Techniques are described for executing satisfiability modulo theories (SMT) solvers in a “shadow” system configuration where input queries are provided to a primary SMT solver system and additionally to one or more secondary SMT solver systems. SMT solver systems can be used by cloud providers and in other computing environments to analyze the implications of configured user account policies defining permissions with respect to users' computing resources and associated actions within a computing environment, to help ensure the security of computing resources and user data, etc. The results generated by a primary SMT solver system can be provided to one or more secondary SMT solver systems, where each of the secondary SMT systems can comprise different system components or different versions of system components, to assess the correctness of the primary SMT solver system, to compare performance metrics, among other possible types of analyses.

Abstract: Systems and method for implementing quantum circuit compilation as-a-service are disclosed. In some embodiments, a quantum circuit compilation service is configured to compile quantum circuits for a plurality of third-party customers, wherein the compilation service supports compiling quantum circuits to be executed on a plurality of different quantum processing units that utilize various different quantum computing technologies. In some embodiments, the quantum computing service generates a customized compilation job plan for each quantum circuit to be compiled. The compilation job plan may reference modular compilation passes stored in a repository of the quantum circuit compilation service. The modular passes may be mixed and matched as needed to allow for compilation of a wide-variety of quantum circuits to be executed using various different quantum computing technologies.

Abstract: A vehicle software test environment management system provides a virtual vehicle environment that includes virtual electronic control units (vECUs) having a virtual bus connectivity configuration used to simulate respective ones of electronic control units (ECUs) of a real-world vehicle. The vehicle software test environment management system determines respective instance types of one or more virtual compute instances to be used to implement the vECUs based on respective configuration of respective ones of the ECUs and further determines respective machine images to emulate respective software environments of the respective ones of the ECUs. The vehicle software test environment management system may also deploy a vehicle software application to be certified on one or more of the vECUs and test the deployed vehicle software application using recorded signals of one or more ECUs of the real-world vehicle.