Techniques for determining one or more responses associated with one or more components that are responsive to a user input are described. The system receives a user input and causes one or more components to generate one or more responses associated with the user input. The system determines one or more of the responses are responsive to the user input, causes one or more actions associated with the responses to be performed, and outputs a natural language summary of the one or more responses. If the system determines that none of the responses are responsive to the user input and/or an ambiguity exists with respect to the user input, the system can generate a request for additional information usable to resolve the ambiguity, which may be sent to another component of the system and/or output to the user that provided the user input.
Techniques for performing speech processing using multi-modal widget information are described. A system may receive input data corresponding to a user input. The system may also receive widget context data corresponding to one or more multi-modal widgets active at a device. The system may use the widget context data to perform natural language understanding (NLU) processing with respect to the user input, and for selecting a skill component for responding to the user input. The system may send a widget identifier to the skill component when invoking the skill to respond to the user input.
Disclosed are various embodiments relating to remotely connecting to customer premises networks to access cloud-executed edge applications. In one embodiment, a layer-3 virtual private network is established between a cloud provider network and a customer premises network of a customer. A layer-2 virtual interface is established for an edge application executed on the cloud provider network using a tunnel to encapsulate layer-2 traffic over the layer-3 virtual private network. A client device outside of the cloud provider network is connected to the customer premises network via the layer-3 virtual private network.
Techniques for tracking and maintaining queues used for executing pending quantum objects using respective quantum processing units (QPUs) are disclosed. An amount of time to execute a given quantum object depends on many factors, and a non-deterministic nature of quantum computing resources is such that, while knowing an expected wait time in a queue for access to a given QPU is useful, it is difficult to reliably determine. A quantum computing service that manages submission and execution of quantum objects to respective QPUs may apply QPU-specific machine learning models in order to predict expected wait times and provide that information to customers. By generating labeled datasets using ground truth wait times pertaining to already-executed quantum objects, respective machine learning models may be trained using a supervised learning technique, which may be a self-contained and re-occurring process.
Techniques for generating tasks to be completed in order to perform an action responsive to a user input and, for a given task, shortlisting available components to those that are relevant for the task are described. The system processes a user input to determine tasks to be completed in order to perform an action responsive to the user input. The system determines a priority of the tasks and selects a top-ranked task. The system determines descriptions of processing performable by components that are semantically similar to the current task, and requests a description of the function the corresponding components would perform for the current task. Based on the received descriptions, the system selects one or more components to perform the task. Thereafter, the system causes the action to be performed and outputs a response to the user input.
Apparatus and methods are disclosed herein for remote, direct memory access (RDMA) technology that enables direct memory access from one host computer memory to another host computer memory over a physical or virtual computer network according to a number of different RDMA protocols. In one example, a method includes receiving remote direct memory access (RDMA) packets via a network adapter, deriving a protocol index identifying an RDMA protocol used to encode data for an RDMA transaction associated with the RDMA packets, applying the protocol index to a generate RDMA commands from header information in at least one of the received RDMA packets, and performing an RDMA operation using the RDMA commands.
Disclosed are various embodiments that enhance customer premises device functionality through the use of cloud-based micro-large language models. In one embodiment, a layer-3 virtual private network is established between a cloud provider network and a customer premises network of a customer. A layer-2 virtual interface is established for a cloud-based artificial intelligence (AI) engine executed on the cloud provider network using a tunnel to encapsulate layer-2 traffic over the layer-3 virtual private network. The cloud-based AI engine is used to provide a functionality for an edge device on the customer premises network.
G10L 15/183 - Speech classification or search using natural language modelling using context dependencies, e.g. language models
H04L 41/00 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
H04L 41/08 - Configuration management of networks or network elements
H04L 41/40 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using virtualisation of network functions or resources, e.g. SDN or NFV entities
8.
EXPOSING INTERFACES ON CUSTOMER PREMISES NETWORKS FOR USE BY CLOUD-EXECUTED EDGE APPLICATIONS
Disclosed are various embodiments that expose interfaces on customer premises networks for use by cloud-executed edge applications. In one embodiment, a layer-3 virtual private network is established between a cloud provider network and a customer premises network of a customer. A layer-2 virtual interface is established for an edge application executed on the cloud provider network using a tunnel to encapsulate layer-2 traffic over the layer-3 virtual private network. An interface on an edge device of the customer premises network is mapped so that the interface is accessible by the edge application via the tunnel.
Disclosed are various embodiments that extend customer premises networks onto a cloud provider network. In one embodiment, a layer-3 virtual private network is established between a tunneling agent and a virtual private network server on a cloud provider network. The tunneling agent is executed on an edge customer premises equipment (CPE) device on a customer premises network. A layer-2 virtual interface is established for an edge application on the cloud provider network using a tunnel to encapsulate layer-2 traffic between the customer premises network and the edge application over the layer-3 virtual private network.
Disclosed are various embodiments that extend customer premises networks onto a cloud provider network. In one embodiment, a layer-3 virtual private network is established between a tunneling agent and a virtual private network server on a cloud provider network. The tunneling agent is executed on an edge customer premises equipment (CPE) device on a customer premises network. A layer-2 virtual interface is established for an edge application on the cloud provider network using a tunnel to encapsulate layer-2 traffic between the customer premises network and the edge application over the layer-3 virtual private network.
A system and method for providing a fault tolerant quantum computer that is implemented using erasure qubits is disclosed. Erasure qubits provide flexibility in terms of mapping of different energy states such that computational basis states of a qubit may be mapped to two energy states of the system and such that detection of amplitude damping decay events may be heralded. By additionally implementing periodic erasure qubit checks and conditional and/or unconditional erasure qubit resets during an overall process of performing a quantum circuit using such a quantum computer, erasure errors can be detected and corrected mid-performance, therefore ensuring that a decoding process that is completed post-performance results in higher gate fidelity.
Techniques for replacing input values being loaded into a computational circuit are described. Small input values such as denormal numbers can be replaced with alternative values such as zeros to reduce switching activity in the computational circuit, and thus reduce power consumption. In applications such as most neural networks, the impact on the prediction results when replacing small numbers with zeros can be negligible. In applications where high precision computations may be desirable, the input values can be loaded into the computation circuit without modification.
G06F 7/544 - Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state deviceMethods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using unspecified devices for evaluating functions by calculation
Methods for modeling performance of tiered storage of a data processing service given a decrease in the storage capacity of a warm storage tier of the tiered storage are disclosed. Metadata of the warm storage tier is used to track hits due to incoming queries on data blocks that are stored in the warm storage tier. The metadata prioritizes data block identifiers that correspond to the data blocks stored in the warm storage tier by frequency of hits due to the incoming queries, or various other prioritization schemes. One or more partitions of the metadata may be set that correspond to respective downsized storage capacity scenarios of the warm storage tier. When an incoming query targets a data block within a given partition of the metadata, a hit counter is incremented to track the hit rate that would be made on the downsized warm storage tier corresponding to that partition.
Biological sample processing system assemblies include a swab chamber assembly configured to enhance transfer of a biological sample on a swab head to a resulting biological sample solution for subsequent processing. A swab chamber assembly includes a fluid channel and an elongated swab chamber having a proximal portion and a distal portion. The swab chamber is configured to accommodate insertion of a swab head of a swab into the swab chamber. The distal portion of the swab chamber slopes downwardly from a distal end of the proximal portion of the swab chamber so that lysis buffer solution transferred into the swab chamber accumulates within the distal portion of the swab chamber.
A satellite constellation provides communication resources, such as optical intersatellite links (ISL), to third-party (3P) satellites. An application programming interface (API) provided by a management system associated with the constellation allows a 3P requestor to determine availability of, and schedule, communication resources. Details about the scheduled communications are returned to the 3P requestor. Once scheduled, the management system operates associated satellites to provide the scheduled communication resources. The requestor may then use the details to operate the 3P satellite to use the scheduled communication resources. At the scheduled time(s), the ISL may be used to transfer data between the 3P satellite and ground or another 3P satellite.
H04B 10/00 - Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
H04B 10/118 - Arrangements specific to free-space transmission, i.e. transmission through air or vacuum specially adapted for satellite communication
An apparatus for moving racks and like devices, referred to herein as a rack moving apparatus, is described that is able to move racks quickly and without disassembly. The rack moving apparatus may include a multitude of wheeled carriages such that the rack moving apparatus can be rolled or otherwise positioned below a rack or other device for relocation. When positioned below a rack or similar storage device, a lever can be manipulated, which causes a multitude of lifting arms of the carriages to raise from a top surface of the apparatus, causing the rack or other storage device to become raised from the floor surface. A frame of the rack moving apparatus is sufficient to receive and retain a frame of a rack such that the rack can be transported without flexing, bending, or toppling of the rack.
B65G 1/10 - Storage devices mechanical with relatively-movable racks to facilitate insertion or removal of articles
B62B 3/00 - Hand carts having more than one axis carrying transport wheelsSteering devices thereforEquipment therefor
B62B 3/06 - Hand carts having more than one axis carrying transport wheelsSteering devices thereforEquipment therefor involving means for grappling or securing in place objects to be carriedLoad handling equipment for simply clearing the load from the ground, e.g. low-lift trucks
Implementations for providing event processing services test and deploy machine learning models described. Events associated with an application may be stored and replayed to a machine learning model. Operational metrics associated with the replaying of the events may be measured and stored for analysis and display. The machine learning model may be deployed after determining the operational metrics.
A collection of data is maintained by at least first and second nodes of a distributed database. The first node maintains a first subset of the collection of data in a first random-access memory, and the second node maintains a second subset of the collection of data in a second random access memory. The first node sends an HTTP-based request to obtain updates to the first subset of the collection of data. The request comprises a unique sortable identifier. The first node receives data from the second node, and updates the first subset of the collection of data based on the receive data.
A robotic delivery vehicle may be capable of providing sufficient insulation for perishable items without sacrificing the delivery robotic delivery vehicles' travel range by using passive cooling configurations. Passive cooling configurations may include improving the insulation performance of the robotic delivery vehicle as well as incorporating cooling elements. The robotic delivery vehicle may include a cargo bay liner and a vehicle lid that covers and encloses a cargo bay from the external environment. The cargo bay liner may include an insulated bottom and at least one insulated wall extending from the insulated bottom, wherein the at least one insulated wall and the insulated bottom define a cargo volume. The lid may define a lid volume and is configured to selectively enclose the cargo volume.
Replication of a client-managed table may be configured across shards of system-managed tables in a database system for improved query performance. A client-managed table may be identified to replicate as a complete copy of the table respectively collocated with two or more shards of one or more other system-managed tables. The complete copy may be stored in respective storage volumes of the two or more shards of the one or more other system-managed tables. Metadata for performing access requests at a database system may be updated to identify the client-managed table as collocated with the two or more shards of the one or more other system-managed tables.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
Techniques for a service of a cloud computing system to generate and present users with visualizations of computing resources and their network relationships in private networks of the users. The cloud system obtains resource and network connection data from private networks of users and determines overall network architectures for the computing resources and their network connections. The cloud system generates visualizations that represent the overall network architectures for private networks. The visualizations may comprise single pane-of-glass views for users to quickly understand the architectures and networking inside of their private networks. The visualizations may be interactive in that users can interact with visual depictions of resources and be dynamically presented with networking connections and details for the particular resources.
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
22.
Network improvements using adaptive timing compensation techniques
This disclosure describes techniques for managing clock drift compensation in a network of node devices. In some embodiments, such techniques may comprise determining a current status of a network that includes a set of node devices operating in a first mode, determining, based on the current status of the network, a quantity of the set of node devices to be switched to a second mode, determining, based on one or more characteristics of individual node devices in the set of node devices, a subset of the set of node devices including a selection of the quantity of node devices from the set of node devices, and providing, to individual node devices in the subset of the set of node devices, instructions to cause the individual node devices to switch from the first mode to the second mode.
A wearable device detects ambient ultraviolet light and provides output related to lengths of time for safe exposure and health benefits. Orientations of the device, determined by an orientation sensor, intensity of ambient light determined by ultraviolet and visible light sensors, or both are used to determine a current position of the sun or other source of ultraviolet light. Data from the sensors and position of the sun are used to select a gain level for the ultraviolet light sensor or a corrective factor to be applied to signals from the ultraviolet light sensor. At a subsequent time, detected intensity of ambient ultraviolet light may be used in combination with external data relating to the location of the device to determine an output, such as recommended times for exposure. Other sensors may determine physiological characteristics of the user, which may also be used to determine personalized recommended exposure times.
G01J 1/42 - Photometry, e.g. photographic exposure meter using electric radiation detectors
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
G01L 19/00 - Details of, or accessories for, apparatus for measuring steady or quasi-steady pressure of a fluent medium insofar as such details or accessories are not special to particular types of pressure gauges
Composite shipping labels for multi-location deliveries are described herein. In an example, a computer system receives a request for a delivery of an item to a delivery location associated with an intermediate location. The item is to be delivered to the intermediate location prior to being delivered to the delivery location. The computer system causes a printing of a label for the item. The label includes a first label part indicating the delivery location. The first label part is configured to be coupled to the item. The label also includes a second label part indicating the intermediate location. The second label part is configured to be positioned at least partially covering the first label part and at least partially detachable from the first label part. The computer system instructs an operation of attaching the label to the item.
Cloud services, such as a storage service, are able to communicate through a virtual PCI request over a non-PCI bus by using a modified device driver that communicates with a network interface. One or more cloud services can execute on a same board or within a same Integrated Circuit (IC) as the network interface. The network interface adapts communications from the one or more services by allowing the services to use a PCI protocol despite that the services are not communicating with the network interface over a PCI bus.
An inventory holder assembly can include a fabric sleeve and a drawer bin assembly. The fabric sleeve can be installed on a frame. The fabric sleeve can include multiple compartments, where each compartment includes a set of mounts couplable with interchangeable bin structures. The drawer bin assembly can coupled to a subset of mounts of a compartment of the fabric sleeve. The drawer bin assembly can include a drawer bin biased, via a biaser, to extend more than halfway (or fully) out from the compartment of the fabric sleeve to achieve an open state. Also, the drawer bin can be pushed against the biaser to stow away and lock in place within the compartment.
Adaptive bitrate techniques are used to select bitrates of segments to download when streaming video content. Different bitrate paths may be evaluated to optimize an objection function. Filtering bitrate paths that are unlikely to be optimal increases the computational speed, facilitating deployment.
H04N 21/462 - Content or additional data management e.g. creating a master electronic program guide from data received from the Internet and a Head-end or controlling the complexity of a video stream by scaling the resolution or bit-rate based on the client capabilities
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
H04N 21/4402 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving reformatting operations of video signals for household redistribution, storage or real-time display
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
28.
APPLICATION GATEWAYS IN AN ON-DEMAND NETWORK CODE EXECUTION SYSTEM
Systems and methods are described for providing an application-level gateway to an on-demand network code execution system. An on-demand network code execution system may allow users to submit code to be executed in a serverless environment, and may provide an interface for executing the user-submitted code on demand. The interface may require that users authenticate, provide input in a particular format, or meet other criteria when sending a request to execute the code. An application-level gateway may thus provide an interface that implements these functions, thereby allowing computing devices to interact with the code as though it were running on a server (e.g., by using HTTP). The application-level gateway may also use on-demand code execution to provide load balancing for servers that are running the user-submitted code, and seamlessly provide access to code that runs on both server-based and serverless environments.
Language models may be dynamically updated for trending entities based on tuning data for particular users. A user may provide specific tuning data associated with trending entities within a class to generate a weight map for a language model. A class based model may be trained using the weight map specific for the user for the trending entities. Additionally, weights may be further boosted using a boosting language model to emphasize the trending entities.
A codec system dynamically selects a codec from multiple available codecs with a highest level of encoding quality at a computing device based at least in part on the available computing resources at a particular computing device. The codec system can continuously monitor encoding performance and if encoding with the selected codec uses too many computing resources, then the codec system can switch to a codec that uses fewer computing resources.
H04N 21/2343 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
31.
PERFORMANCE OF READOUT AND RESET OF FLUXONIUM QUBITS
Techniques for performing readout and reset of fluxonium qubits are disclosed. When fluxonium hardware components are coupled to a quantum metamaterial through a readout resonator, said components may be dispersively coupled such that a quantum state of the corresponding fluxonium qubit is read out through the quantum metamaterial, and then the state of the fluxonium qubit is subsequently reset in order to proceed with a quantum computation to be performed. Alternatively, when fluxonium hardware components are coupled directly to a quantum metamaterial, a quantum state of a fluxonium qubit is read out using resonance fluorescence, and then may be subsequently reset back to its ground state, also using resonance fluorescence. A width of a passband of the quantum metamaterial, along with frequencies of the control sequences used, may be tuned such that either readout or reset is selectively activated.
Technologies directed to smart farming are described. A multimodal soil sensor device includes an elongated housing having first and second portions. An antenna is located in or above the first portion and coupled to a wireless communications component. The wireless communications component causes the antenna to radiate or receive electromagnetic energy to communicate with a second device. The multimodal soil sensor device includes one or more multimodal soil sensors to measure one or more first measurements of a first sensing modality and one or more second measurements of a second sensing modality different than the first sensing modality. The wireless communications component wirelessly sends measurement data, including the first measurements and the second measurements, to the second device via the antenna.
An event notification may be received, by a game feature integration service, from a first video game feature component. The game feature integration service may integrate a plurality of video game feature components that each have a respective set of one or more events for which event notifications are sent by a corresponding video game feature component to the game feature integration service and a respective set of one or more actions that are called on the corresponding video game feature component by the game feature integration service. A pre-configured or custom rule flow may trigger the game feature integration service to call an action on the second video game feature component based on the event notification. The game feature integration service, based at least in part on the rule flow, may call the action on the second video game feature component in response to the event notification.
A63F 13/77 - Game security or game management aspects involving data related to game devices or game servers, e.g. configuration data, software version or amount of memory
A63F 13/60 - Generating or modifying game content before or while executing the game program, e.g. authoring tools specially adapted for game development or game-integrated level editor
A pendulum queue system for inventory management can include a first queue with a first delivery portion and a first storage portion separated by a first operating space. A second queue can be positioned laterally from the first queue and can include a second delivery portion and a second storage portion separated by a second operating space. Each of the storage portions can include its own storage work cell through which inventory holders can be cyclable, and each delivery portions can include one or more carriers. A transfer apparatus can be configured to move back and forth between the queues and to move within the operating space of each queue to transfer an item between an inventory holder and a carrier within one of the queues during a time interval in which the other queue can undergo cycling of the inventory holders.
Systems and methods are disclosed for automated force feedback detection for autonomous robots transporting containers. In one embodiment, an example mobile robot is configured to transport a container. The mobile robot can include a first sensor, a second sensor, a motor, and a controller. The controller may be configured to determine that the container is loaded, determine, using at least one of the first sensor and the second sensor, that a first change in load distribution along a first axis satisfies a threshold, determine that the first change in load distribution has persisted for a first length of time, and cause the motor to be disabled.
B66F 9/06 - Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes movable, with their loads, on wheels or the like, e.g. fork-lift trucks
B66F 9/065 - Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes movable, with their loads, on wheels or the like, e.g. fork-lift trucks non-masted
36.
Systems and methods to test perception and safety responses of autonomous mobile robots
Systems and methods to test autonomous mobile robots (AMRs) may include a dynamometer, a robotic system carrying an object, and a control system. An AMR under test may be positioned on the dynamometer and instructed to perform navigation maneuvers, which may be detected by the dynamometer. The control system may receive the detected movements and determine corresponding movements for the robotic system using inverse kinematics. Then, the control system may instruct movement of the object via the robotic system based on the corresponding movements. Using such test systems and methods, perception systems and responses by safety, navigation, and/or drive systems of AMRs may be tested in a controlled, robust, and repeatable manner.
Autonomous ground vehicles that are outfitted with radar sensors and inertial measurement units accurately determine states of the autonomous ground vehicles, e.g., estimates of the vehicles' positions, orientations, or velocities or accelerations along or about one or more axes, based on data captured by the radar sensors and the inertial measurement units. Where objects are detected in radar scans, the objects are determined to be static (or fixed), or dynamic (or moving), and landmarks representing static objects are identified. Constraints on estimates of states may be calculated based on doppler effects, inertial measurement unit effects, or locations of landmarks, and the states may be determined as solutions to optimization problems based on the data and the calculated constraints. Odometry messages representing the determined states may be generated and stored or utilized for any purpose.
This disclosure describes architectures and techniques to provide information to a user about items with which the user interacts. In some instances, a user may utilize a wearable device that is configured to interact with one or more components of an information discovery system to obtain information about items in the user's environment.
G06F 3/00 - Input arrangements for transferring data to be processed into a form capable of being handled by the computerOutput arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
G06V 20/20 - ScenesScene-specific elements in augmented reality scenes
G06V 20/52 - Surveillance or monitoring of activities, e.g. for recognising suspicious objects
G06V 40/20 - Movements or behaviour, e.g. gesture recognition
G06V 40/18 - Eye characteristics, e.g. of the iris
39.
Rapid GPU scrubbing in a cloud provider network using same-slot auxiliary domains
Techniques for instance termination cleanup via auxiliary domains are described. A termination workflow is executed for a compute instance having graphics processing unit (GPU) access hosted in a cloud provider network. The termination workflow includes terminating the compute instance of the user, launching an auxiliary compute instance in the same slot, and executing a cleanup workflow by the auxiliary compute instance for the GPU. Upon the conclusion of the cleanup workflow, the state of the compute instance is updated to terminated, allowing for it to be relaunched.
The present disclosure relate to systems and methods for providing input data analysis configuration for a plurality of network-based services. A configuration service may obtain operator-defined inputs that define the value or variable of each attribute of the configuration service. The configuration service can generate one or more input data analysis configurations based on the operator-defined value or variable for each of the attributes. The configuration service can validate each of the one or more input data analysis configurations by compiling the configuration. For example, the configuration service can perform a conflict check to determine any conflicted values between attributes. The configuration service can also perform a completeness check to determine any undefined attributes.
Commit time logging is performed as part of implementing time-based Multi-Version Concurrency Control (MVCC). A query engine may determine a commit time for a database transaction is committed to a database by applying MVCC to select different versions of data in the database according to transaction commit times. The query engine may store the commit time for the database transaction in a log structure stored in a non-volatile data store. A segment describing the log structure maintained in a volatile memory maintained in a volatile memory may be updated to include the commit time for the database transaction.
A method includes accessing user trajectory information associated with a user account, wherein the user trajectory information corresponds to a first session, the first session including user interactions with a cloud computing provider, generating, by a large language model, a plurality of questions based on the user trajectory information, generating, for at least a subset of the plurality of questions, a plurality of answers corresponding to the at least the subset of the plurality of questions, wherein an answer of plurality of answers corresponds to a resource of the cloud computing provider, receiving, from a user device associated with the user account, an indication that the user account has started a second session, and responsive to receiving the indication, causing display of the at least the subset of the plurality of questions and corresponding answers on the user device.
A method for graph-based modeling to optimize geographic regions using a resource-constrained objective-maximal path may include a first geographic area as a first path between a first origin location and a first destination location; encoding a second geographic area as a second path between a second origin location and a second destination location; applying a set of constraints to the first geographic area and the second geographic area to cover the jurisdiction with geographic areas, and to map respective entities to a single respective geographic area; generating a first objective-maximal path between the first origin location and the first destination location; and generating a second objective-maximal path between the second origin location and the second destination location.
Techniques for mobile robots performing self-diagnostic fiducial classification are described herein. For example, a mobile robot can determine that an expected fiducial marker has not been detected as the mobile robot navigates via fiducial markers on a surface. In response, the mobile robot can generate an input to a machine learning model that can be executed on the mobile robot. The input can include images of the surface captured by the mobile robot. The machine learning model may be trained to generate an output comprising a classification of image data of the images based at least in part on the input. The mobile robot can determine an error event corresponding to the expected fiducial marker based at least in part on the classification of image data received from the machine learning model. The mobile robot can output a notification indicating the error event corresponding to the expected fiducial marker.
G06V 10/98 - Detection or correction of errors, e.g. by rescanning the pattern or by human interventionEvaluation of the quality of the acquired patterns
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
A system comprising one or more computing devices implements a vehicle analysis service, which generates logical instructions for deployment to a vehicle or a fleet of vehicles to implement in-vehicle data analysis in the vehicle or fleet of vehicles. Additionally, the vehicle analysis service and/or locally deployed analysis module provides updates based on newly learned trends in vehicle data or newly learned correlations for the vehicle or similarly situated vehicles. The vehicle analysis service and locally deployed analysis module enables analysis to be performed using detailed high-resolution vehicle data, without requiring large volumes of vehicle data to be streamed to a remote location for analysis. Also, the vehicle analysis service provides customized analysis modules that can perform local analysis using existing computing resources of the vehicle or the vehicles of the fleet.
G06Q 10/20 - Administration of product repair or maintenance
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G08G 1/00 - Traffic control systems for road vehicles
46.
Determination of meeting content for display by an enterprise system
Techniques for a service provider network to manage a meeting between individuals located in a conference room with one or more other individuals remote from the conference room are discussed herein. An Enterprise system can implement one or more machine learned models to generate tiles that represent different individuals associated with a meeting. A same or different machine learned model can automatically arrange a series of tiles for display that, when presented collectively, promotes inclusiveness and attention for both in-room and remote participants of the meeting. The meeting management techniques can include determining which content to include on a display device based on evaluating changes in behavior of the meeting participants over time.
Techniques are described for training and use of machine learning models to determine objective video quality scores. Video quality scores predict the quality of video content perceived by viewers. Quality scores have various uses, including the selection of encoding profiles and determination of encoding ladders. A core model and residual model may be used to determine quality scores.
A charging interface for a robot includes a housing comprising a plurality of recesses, one or more charge contact members, and one or more data contact members. The charge contact members can be at least partially disposed within on or more of the plurality of recesses. Each charge contact member can include an electrical charge pin extending through an opening of a surface of the charge contact member. The data contact members can be at least partially disposed within one or more of the plurality of recesses. Each data contact member can include an electrical data pin extending through an opening of a surface of the data contact member. The charge contact member and the data contact members can be moveably coupled to the housing.
A satellite provides communication between user terminals (UTs) and ground stations that connect to other networks, such as the Internet. The satellite uses a direction beam to transmit a beacon signal to particular areas on the Earth. To establish initial contact with a satellite, a UT searches for the beacon signal using a phased array or other steerable antenna with a directional receive pattern. While searching, a set of received beacon signal strength values are acquired while pointing the receive pattern in different sample directions specified by azimuth and elevation. The sample directions may be based on a predicted location of the satellite. The set of signal strength values and associated azimuth and elevation values are processed using a least-squares estimator to determine an estimated direction. The estimated direction may be used to point the antenna, allowing sufficient gain to perform an initial network entry and subsequent communication.
This disclosure describes, in part, techniques for identifying interactions between users and inventory locations. For instance, system(s) may receive image data generated by an imaging device located within a facility. The system(s) may then analyze the image data in order to determine one or more gaze points, where the gaze point(s) indicate location(s) on an inventory location for which a user was looking over a period of time. The system(s) may then generate gaze data indicating period(s) of time that the user was looking at the portion(s) of the inventory location. In some examples, the gaze data represents a heatmap. The system(s) may then use planogram data to determine identifier(s) of item(s) located at the portion(s) of the inventory location. Additionally, the system(s) may generate metrics data representing at least the identifier(s) of the item(s) and the period(s) of time that the user was looking at the item(s).
G06V 20/52 - Surveillance or monitoring of activities, e.g. for recognising suspicious objects
G06V 20/58 - Recognition of moving objects or obstacles, e.g. vehicles or pedestriansRecognition of traffic objects, e.g. traffic signs, traffic lights or roads
Systems, devices, and methods are provided for selective endpoint data monitoring. A system may determine, at an endpoint client running in a privileged mode of operation, a first request by a first application to access a first network destination. The system may further determine, at the endpoint client, that network traffic to the first network destination should be monitored. The system may further determine, at the endpoint client, that a data security extension has been provisioned on the first application. The system may provide, to the first application, information usable to access the first network destination. The system may obtain, from the data security extension, metadata associated with data that the first application provides to the first network destination.
Disclosed techniques provide enhanced advertising to facilitate sharing of user information with advertisers. An online service provider can store at least a portion of an advertisement on computer storage. Image data from a presentation of the advertisement can be obtained by the online service provider. The online service provider can verify that the image data corresponds to advertising image data stored on the computer storage. User information can be shared with an advertiser based at least on verifying the image data corresponds to the advertising image data stored on the computer storage.
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G06K 7/14 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
Techniques for evaluating speech processing components are described. A system may receive a task request including at least a plurality of entity names to be evaluated by at least one speech processing component. The system may determine synthetic user inputs corresponding to the plurality of entity names, and may cause performance of a speech processing task using the synthetic user inputs. The speech processing task may be an ASR processing task, an NLU processing task, or an ER processing task. The system may compare the results of the speech processing task with ground truth data to determine if an error occurred during processing.
Approaches provided herein can provide for adjustments to audio data. In particular, an audio resampling process can be performed wherein the correct audio frame size is determined. A “target” audio stream duration, as may be indicated by a time-to-sample atom (STTS) atom, can be used to apply one or more pitch-invariant, time-stretching audio filters to the audio data as that data is decoded during a media transcode process. A resulting output media metadata can specify accurate, constant audio frame durations, and the audio stream duration can match the corresponding video stream duration in a media file.
G10L 19/00 - Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocodersCoding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
H04N 21/233 - Processing of audio elementary streams
H04N 21/2343 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements
H04N 21/43 - Processing of content or additional data, e.g. demultiplexing additional data from a digital video streamElementary client operations, e.g. monitoring of home network or synchronizing decoder's clockClient middleware
An integrated circuit to synchronize a pulse signal from a first clock domain to a second clock domain includes a first flip-flop and a second flip-flop. The first flip-flop has a first stage input, a first clock input, and a first stage output. The first clock input is driven by a first clock signal of the first clock domain, and the first stage input is driven by a result of XOR-ing the input pulse signal and the first stage output. The second flip-flop has a second stage input, a second clock input, and a second stage output. The second clock input is driven by a second clock signal of the second clock domain, and the second stage input is driven by the first stage output. The synchronized output pulse signal is generated by XOR-ing the second stage output with the first stage output.
Techniques for processing of satellite sensor data by a mobile ground station are described. A satellite transmission from a tasked satellite is received by a mobile ground station, the satellite transmission including unprocessed downlink data. A software-defined radio (SDR) definition associated with a tasked satellite is selected from a plurality of SDR definitions stored by the mobile ground station. A sensor data processing (SDP) application associated with the tasked satellite is selected from a plurality of SDP applications stored by the mobile ground station. An SDR application is executed to extract the collected sensor data from the unprocessed downlink data, the SDR application is loaded with the selected SDR definition. The selected SDP application is executed to generate a product from the collected sensor data. The product is caused to be displayed on a display device.
H04B 1/00 - Details of transmission systems, not covered by a single one of groups Details of transmission systems not characterised by the medium used for transmission
58.
Privacy preserving protocol for serving user-specific supplemental content
Embodiments of a privacy preserving supplemental content server (PPSCS) implements a privacy preserving protocol with a content server that requests the PPSCS to serve supplemental content for users. In embodiments, a user-to-segment map (USM) containing user-private information is split into secret shares and stored separately at the PPSCS and the content server. When servicing a request, the USM data is used to identify a key segment of a user, which is in turn used to select a supplemental content for the user. Advantageously, the selection process is performed according to the privacy preserving protocol, which guarantees that (a) the content server does not learn any user-private information about the user in the USM, (b) the PPSCS learns at most one user segment of the user (e.g. the key segment), and (c) the PPSCS cannot track the user over time using any user-private information about the user learned during the execution.
This disclosure describes techniques for enabling dynamic adjustment of a wake interval frequency based on detection of a prioritization event. In embodiments, such techniques may comprise operating a STA device in a first mode in which wake intervals recur after a first amount of time and receiving, by the STA device from a AP device, information about a prioritization event. Based on receiving the information, the techniques may further involve operating the STA device in a second mode in which wake intervals recur after a second amount of time and, based on determining that the prioritization event has ended, operating the STA device in the first mode.
providing information to consumers on the sustainability features of products available for purchase; providing information to consumers on the sustainability certifications of products available for purchase; Providing information to consumers about a product’s sustainability impact areas; providing information to consumers on more sustainable packaging, shipping, and delivery choices; providing consumer product information relating to the sustainability features of products; providing consumer product information relating to the sustainability impact of products; provision of consumer information regarding the selection of products and items to be purchased and their sustainability features and impact; shopper's guide information, namely, provision of guides featuring commercial information to consumers in the choice of products with sustainability attributes; shopper's guide information, namely, provision of commercial information for consumers to evaluate and compare the sustainability features of products; shopper’s guide information, namely provision of information on more sustainable packaging, shipping, and delivery services choices; shopping facilitation services, namely, providing an online comparison-shopping search engine for obtaining purchasing information of products with sustainability features; shopping facilitation services, namely, providing an online comparison-shopping search engine for obtaining purchasing information to evaluate and compare sustainability features or attributes of products; promotion of more sustainable shopping choices; promoting public awareness of sustainability in the design, manufacture, packaging, and transport of consumer goods; providing an on-line commercial information directory for products with sustainability features and sustainability certifications on the internet; providing information to consumers on the sustainability attributes of products, namely indicating whether a product has sustainability certification; administration of a retail program which provides information regarding sustainability certifications and associated features; providing a database of products with sustainability certifications and associated sustainability attributes; providing an online commercial information directory on the internet of products with sustainability certifications and associated sustainability attributes; maintaining a registry of products with sustainability certifications and associated sustainability attributes; promoting public awareness of goods with sustainability attributes; promoting public awareness of sustainability certifications provided by others; providing a website that allows consumers to discover and shop for products with sustainability features; providing a website featuring data on sustainability certifications for the purpose of assisting consumers in making purchasing decisions; marketing and promotional services in the nature of promoting products with sustainability features; marketing and promotional services in the nature of promoting products with sustainability features and sustainability certifications; promoting public awareness of the benefits and availability of products with sustainability attributes; consulting services in the field of providing businesses with information and advice on the sale of products with sustainability features; business consulting in the field of retail, particularly in the sale of products with sustainability features
Providing information to consumers on the sustainability features of products available for purchase; providing information to consumers on the sustainability certifications of products available for purchase; providing information to consumers about a product’s sustainability impact areas; providing information to consumers on more sustainable packaging, shipping, and delivery choices; providing consumer product information relating to the sustainability features of products; providing consumer product information relating to the sustainability impact of products; provision of consumer information regarding the selection of products and items to be purchased and their sustainability features and impact; shopper's guide information, namely, provision of guides featuring commercial information to consumers in the choice of products with sustainability attributes; shopper's guide information, namely, provision of commercial information for consumers to evaluate and compare the sustainability features of products; shopper’s guide information, namely provision of information on more sustainable packaging, shipping, and delivery services choices; shopping facilitation services, namely, providing an online comparison-shopping search engine for obtaining purchasing information of products with sustainability features; shopping facilitation services, namely, providing an online comparison-shopping search engine for obtaining purchasing information to evaluate and compare sustainability features or attributes of products; promotion of more sustainable shopping choices; promoting public awareness of sustainability in the design, manufacture, packaging, and transport of consumer goods; providing an on-line commercial information directory for products with sustainability features and sustainability certifications on the internet; providing information to consumers on the sustainability attributes of products, namely indicating whether a product has sustainability certifications; administration of a retail program which provides information regarding sustainability certifications and associated features; providing a database of products with sustainability certifications and associated sustainability attributes; providing an online commercial information directory on the internet of products with sustainability certifications and associated sustainability attributes; maintaining a registry of products with sustainability certifications and associated sustainability attributes; promoting public awareness of goods with sustainability attributes; promoting public awareness of sustainability certifications provided by others; providing a website that allows consumers to discover and shop for products with sustainability features; providing a website featuring data on sustainability certifications for the purpose of assisting consumers in making purchasing decisions; marketing and promotional services in the nature of promoting products with sustainability features; marketing and promotional services in the nature of promoting products with sustainability features and sustainability certifications; promoting public awareness of the benefits and availability of products with sustainability attributes; consulting services in the field of providing businesses with information and advice on the sale of products with sustainability features; business consulting in the field of retail, particularly in the sale of products with sustainability features; retail store services featuring products with sustainability certifications and associated sustainability features and sustainability impact information.
(1) Providing information to consumers on the sustainability features of products available for purchase; providing information to consumers on the sustainability certifications of products available for purchase; providing information to consumers about a product's sustainability impact areas; providing information to consumers on more sustainable packaging, shipping, and delivery choices; providing consumer product information relating to the sustainability features of products; providing consumer product information relating to the sustainability impact of products; provision of consumer information regarding the selection of products and items to be purchased and their sustainability features and impact; shopper's guide information, namely, provision of guides featuring commercial information to consumers in the choice of products with sustainability attributes; shopper's guide information, namely, provision of commercial information for consumers to evaluate and compare the sustainability features of products; shopper's guide information, namely provision of information on more sustainable packaging, shipping, and delivery services choices; shopping facilitation services, namely, providing an online comparison-shopping search engine for obtaining purchasing information of products with sustainability features; shopping facilitation services, namely, providing an online comparison-shopping search engine for obtaining purchasing information to evaluate and compare sustainability features or attributes of products; promotion of more sustainable shopping choices; promoting public awareness of sustainability in the design, manufacture, packaging, and transport of consumer goods; providing an on-line commercial information directory for products with sustainability features and sustainability certifications on the internet; providing information to consumers on the sustainability attributes of products, namely indicating whether a product has sustainability certifications; administration of a retail program which provides information regarding sustainability certifications and associated features; providing a database of products with sustainability certifications and associated sustainability attributes; providing an online commercial information directory on the internet of products with sustainability certifications and associated sustainability attributes; maintaining a registry of products with sustainability certifications and associated sustainability attributes; promoting public awareness of goods with sustainability attributes; promoting public awareness of sustainability certifications provided by others; providing a website that allows consumers to discover and shop for products with sustainability features; providing a website featuring data on sustainability certifications for the purpose of assisting consumers in making purchasing decisions; marketing and promotional services in the nature of promoting products with sustainability features; marketing and promotional services in the nature of promoting products with sustainability features and sustainability certifications; promoting public awareness of the benefits and availability of products with sustainability attributes; consulting services in the field of providing businesses with information and advice on the sale of products with sustainability features; business consulting in the field of retail, particularly in the sale of products with sustainability features.
Technologies directed to smart farming are described. A multimodal soil sensor device includes an elongated housing having first and second portions. An antenna is located in or above the first portion and coupled to a wireless communications component. The wireless communications component causes the antenna to radiate or receive electromagnetic energy to communicate with a second device. The multimodal soil sensor device includes one or more multimodal soil sensors to measure one or more first measurements of a first sensing modality and one or more second measurements of a second sensing modality different than the first sensing modality. The wireless communications component wirelessly sends measurement data, including the first measurements and the second measurements, to the second device via the antenna.
G01J 1/42 - Photometry, e.g. photographic exposure meter using electric radiation detectors
G01K 1/024 - Means for indicating or recording specially adapted for thermometers for remote indication
G01N 21/25 - ColourSpectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
G01N 27/22 - Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating capacitance
Provided are systems, methods, and integrated circuits for neural network processing. In various implementations, an integrated circuit for neural network processing can include a plurality of memory banks storing weight values for a neural network. The memory banks can be on the same chip as an array of processing engines. Upon receiving input data, the circuit can be configured to use the set of weight values to perform a task defined for the neural network. Performing the task can include reading weight values from the memory banks, inputting the weight values into the array of processing engines, and computing a result using the array of processing engines, where the result corresponds to an outcome of performing the task.
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 13/28 - Handling requests for interconnection or transfer for access to input/output bus using burst mode transfer, e.g. direct memory access, cycle steal
G06F 15/80 - Architectures of general purpose stored program computers comprising an array of processing units with common control, e.g. single instruction multiple data processors
67.
DATA SET MANAGEMENT USING DATA SET LINEAGE METADATA
A data set management of a provider network may allow a user to create new data set instances. When a data set instance is created, data set lineage metadata is also generated to describe the new data set instance, including the transformation that was applied to data in order to create the data set instance. When modifications are made to source data (e.g., a data bucket), then the modifications are propagated via transformations to the parent data set instance and to any child data set instances according to the data set lineage metadata in order to update the data set instances. When modifications are made to a parent data set instance to create an updated parent data set instance, then the modifications are propagated via transformations to any child data set instances according to the data set lineage metadata. Transformations and transformation patterns may also be defined and scheduled.
A system and method for providing quantum entanglement-as-a-service and simultaneously producing verifiably random sequences of numbers are described. When distributing quantum entanglement between customers Alice and Bob, Alice and Bob may exchange information pertaining to a measurement basis that they respectively used when performing measurements using respective halves of entangled particles. When customer Alice, for example, determines that both Alice and Bob have performed a given measurement in a same measurement basis, said result may be used in a quantum key distribution (QKD) code. When customer Alice determines that they have not performed the given measurement in the same measurement basis, Alice may concatenate said portion of the results into a private and verifiable sequence of random numbers. Providing distributed quantum entanglement therefore results in both a QKD code between said customers and in respective private and verifiably random sequences of numbers.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable computer software using artificial intelligence (AI) for developing and running intelligent agents; Downloadable computer software using artificial intelligence (AI) for user interface (UI) automation, secure code execution and file management; Downloadable computer software using artificial intelligence (AI) for intelligent memory systems to enable agents to retain context across interactions and adjust behavior; Downloadable computer software using artificial intelligence (AI) for a secure, serverless runtime capability to deploy and scale intelligent agents and tools across various frameworks, protocols, and models; Downloadable computer software using artificial intelligence (AI) for building personalized intelligent agent experiences with fully-managed memory infrastructure and the ability to customize memory; Downloadable computer software using artificial intelligence (AI) to manage the digital identities of intelligent agents and control their access to resources; Downloadable computer software using artificial intelligence (AI) for developing and running intelligent agents using virtual machine (VM)-level isolation, identity controls, virtual private cloud (VPC) integration, and flexible network modes; Downloadable computer software using artificial intelligence (AI) for securely writing and executing code to perform complex calculations, validate reasoning, process data, and generate visualizations; Downloadable computer software using artificial intelligence (AI) to enable intelligent agents to navigate websites, complete multi-step forms, and perform complex web-based tasks within a fully managed, secure sandbox environment with low latency; Downloadable computer software using artificial intelligence (AI) to help developers trace, debug, and monitor intelligent agent performance in production environments. Providing on-line non-downloadable software using artificial intelligence (AI) for developing and running intelligent agents; Providing on-line non-downloadable software using artificial intelligence (AI) for user interface (UI) automation, secure code execution and file management; Providing on-line non-downloadable software using artificial intelligence (AI) for intelligent memory systems to enable agents to retain context across interactions and adjust behavior; Providing on-line non-downloadable software using artificial intelligence (AI) for a secure, serverless runtime capability to deploy and scale intelligent agents and tools across various frameworks, protocols, and models; Providing on-line non-downloadable software using artificial intelligence (AI) for building personalized intelligent agent experiences with fully-managed memory infrastructure and the ability to customize memory; Providing on-line non-downloadable software using artificial intelligence (AI) to manage the digital identities of intelligent agents and control their access to resources; Providing on-line non-downloadable software using artificial intelligence (AI) for developing and running intelligent agents using virtual machine (VM)-level isolation, identity controls, virtual private cloud (VPC) integration, and flexible network modes; Providing on-line non-downloadable software using artificial intelligence (AI) for securely writing and executing code to perform complex calculations, validate reasoning, process data, and generate visualizations; Providing on-line non-downloadable software using artificial intelligence (AI) to enable intelligent agents to navigate websites, complete multi-step forms, and perform complex web-based tasks within a fully managed, secure sandbox environment with low latency; Providing on-line non-downloadable software using artificial intelligence (AI) to help developers trace, debug, and monitor intelligent agent performance in production environments.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable computer software using artificial intelligence (AI) for developing and running intelligent agents; Downloadable computer software using artificial intelligence (AI) for user interface (UI) automation, secure code execution and file management; Downloadable computer software using artificial intelligence (AI) for intelligent memory systems to enable agents to retain context across interactions and adjust behavior; Downloadable computer software using artificial intelligence (AI) for a secure, serverless runtime capability to deploy and scale intelligent agents and tools across various frameworks, protocols, and models; Downloadable computer software using artificial intelligence (AI) for building personalized intelligent agent experiences with fully-managed memory infrastructure and the ability to customize memory; Downloadable computer software using artificial intelligence (AI) to manage the digital identities of intelligent agents and control their access to resources; Downloadable computer software using artificial intelligence (AI) for developing and running intelligent agents using virtual machine (VM)-level isolation, identity controls, virtual private cloud (VPC) integration, and flexible network modes; Downloadable computer software using artificial intelligence (AI) for securely writing and executing code to perform complex calculations, validate reasoning, process data, and generate visualizations; Downloadable computer software using artificial intelligence (AI) to enable intelligent agents to navigate websites, complete multi-step forms, and perform complex web-based tasks within a fully managed, secure sandbox environment with low latency; Downloadable computer software using artificial intelligence (AI) to help developers trace, debug, and monitor intelligent agent performance in production environments. Providing on-line non-downloadable software using artificial intelligence (AI) for developing and running intelligent agents; Providing on-line non-downloadable software using artificial intelligence (AI) for user interface (UI) automation, secure code execution and file management; Providing on-line non-downloadable software using artificial intelligence (AI) for intelligent memory systems to enable agents to retain context across interactions and adjust behavior; Providing on-line non-downloadable software using artificial intelligence (AI) for a secure, serverless runtime capability to deploy and scale intelligent agents and tools across various frameworks, protocols, and models; Providing on-line non-downloadable software using artificial intelligence (AI) for building personalized intelligent agent experiences with fully-managed memory infrastructure and the ability to customize memory; Providing on-line non-downloadable software using artificial intelligence (AI) to manage the digital identities of intelligent agents and control their access to resources; Providing on-line non-downloadable software using artificial intelligence (AI) for developing and running intelligent agents using virtual machine (VM)-level isolation, identity controls, virtual private cloud (VPC) integration, and flexible network modes; Providing on-line non-downloadable software using artificial intelligence (AI) for securely writing and executing code to perform complex calculations, validate reasoning, process data, and generate visualizations; Providing on-line non-downloadable software using artificial intelligence (AI) to enable intelligent agents to navigate websites, complete multi-step forms, and perform complex web-based tasks within a fully managed, secure sandbox environment with low latency; Providing on-line non-downloadable software using artificial intelligence (AI) to help developers trace, debug, and monitor intelligent agent performance in production environments.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Downloadable computer software using artificial intelligence (AI) for developing and running intelligent agents; downloadable computer software using artificial intelligence (AI) for user interface (UI) automation, secure code execution and file management; downloadable computer software using artificial intelligence (AI) for intelligent memory systems to enable agents to retain context across interactions and adjust behavior; downloadable computer software using artificial intelligence (AI) for a secure, serverless runtime capability to deploy and scale intelligent agents and tools across various frameworks, protocols, and models; downloadable computer software using artificial intelligence (AI) for building personalized intelligent agent experiences with fully-managed memory infrastructure and the ability to customize memory; downloadable computer software using artificial intelligence (AI) to manage the digital identities of intelligent agents and control their access to resources; downloadable computer software using artificial intelligence (AI) for developing and running intelligent agents using virtual machine (VM)-level isolation, identity controls, virtual private cloud (VPC) integration, and flexible network modes; downloadable computer software using artificial intelligence (AI) for securely writing and executing code to perform complex calculations, validate reasoning, process data, and generate visualizations; downloadable computer software using artificial intelligence (AI) to enable intelligent agents to navigate websites, complete multi-step forms, and perform complex web-based tasks within a fully managed, secure sandbox environment with low latency; downloadable computer software using artificial intelligence (AI) to help developers trace, debug, and monitor intelligent agent performance in production environments. (1) Providing on-line non-downloadable software using artificial intelligence (AI) for developing and running intelligent agents; providing on-line non-downloadable software using artificial intelligence (AI) for user interface (UI) automation, secure code execution and file management; providing on-line non-downloadable software using artificial intelligence (AI) for intelligent memory systems to enable agents to retain context across interactions and adjust behavior; providing on-line non-downloadable software using artificial intelligence (AI) for a secure, serverless runtime capability to deploy and scale intelligent agents and tools across various frameworks, protocols, and models; providing on-line non-downloadable software using artificial intelligence (AI) for building personalized intelligent agent experiences with fully-managed memory infrastructure and the ability to customize memory; providing on-line non-downloadable software using artificial intelligence (AI) to manage the digital identities of intelligent agents and control their access to resources; providing on-line non-downloadable software using artificial intelligence (AI) for developing and running intelligent agents using virtual machine (VM)-level isolation, identity controls, virtual private cloud (VPC) integration, and flexible network modes; providing on-line non-downloadable software using artificial intelligence (AI) for securely writing and executing code to perform complex calculations, validate reasoning, process data, and generate visualizations; providing on-line non-downloadable software using artificial intelligence (AI) to enable intelligent agents to navigate websites, complete multi-step forms, and perform complex web-based tasks within a fully managed, secure sandbox environment with low latency; providing on-line non-downloadable software using artificial intelligence (AI) to help developers trace, debug, and monitor intelligent agent performance in production environments.
Disclosed are systems, methods, and apparatus for unsupervised training of an activity classifier for movement measured at a target location of a user using a trained source activity classifier configured to determine an activity based on motion measured at a source location of a user. According to exemplary embodiments, the activity classifier for the target location can be trained using source embeddings generated by a trained classifier for the source location. For example, the source embeddings and the motion measured at the target location may then be provided as training inputs to the target activity classifier for the target location of a user, so that the target activity classifier can reconstruct the source embedding for the target motion without the use of any labeled training data and/or without having to learn the transfer function of the existing trained machine learning model.
Technologies directed to an energy efficient technique for Antennas as Sensors (A2S) systems used for detecting user input events are described. One electronic device includes a wireless communication component coupled to an antenna via a radio frequency (RF) path, and an RF switch selectively coupling the A2S system to the RF path. The radio sends RF signals to the antenna via the RF path in a first time window. The RF switch is controlled to selectively couple the A2S system to the RF path in the first time window. A processing device of the electronic device receives receiving an analog voltage signal representing impedance changes of the antenna in the first time window and determines, using the analog voltage signal, a user input event caused by a presence of an object in proximity to the antenna. The processing device performs an action in response to the user input event.
A client of a database service may request a migration of a remote source database to a target database provided by the database service, where the source database and target database are published by a database vendor. Responsive to the request, a migration tool published by the database vendor may be selected from among multiple migration tools. The migration tool may derive a schema from the source database and create the target database according to the derive schema. The migration tool may then extract data of the source database using native application programming interfaces (APIs) provided by the vendor. The extracted data may then be imported into the target database using one or more additional native APIs. The migration tool may then initiate replication of transactions performed at the source database to the target database.
This disclosure describes, in part, techniques for identifying user-specific content items and/or time-based content items, as well as techniques for providing the content items to the user. For instance, a remote system may receive first audio data from an electronic device, where the first audio data represents a request to identify content related to a topic. The remote system can then store the topic in a database and use the topic to identify the content. Later, the remote system can then receive second audio data from the electronic device, where the second audio data represents a request for the content. The remote system can then send third audio data to the electronic device that represents at least a portion of the content.
Techniques for a provider network user console with a natural language querying feature. The techniques include collecting a set of templatized query pairs. A pair includes a templatized natural language query (NLQ) and a templatized domain-specific index query language query. The set of templatized query pairs is expanded by substituting named variable tokens in the templatized query pairs with synthetic values to create a set of instantiated query pairs. A pre-trained neural machine translation model is retrained using the set of instantiated query pairs to yield a fine-tuned neural machine translation model. For a natural language query received, the fine-tuned neural machine translation model is used to translate the target natural language query to a corresponding domain-specific index query language query. The domain-specific index query language query is then executed against an index to yield an index result. The techniques reduce or eliminate the need for manual training data generation.
A machine learning model for extracting information from web pages is prepared. The preparation includes generating respective representations of a first set of web pages, including embeddings from screenshots and bounding boxes of the web pages for multi-phase training of the model. In a first phase of training of the model, multiple loss functions associated with respective prediction tasks are optimized jointly, including a markup language element prediction task and a prediction of overlap between bounding boxes and screenshot subdivisions. In a second phase of training, using output of a hidden layer of the model (whose parameters were learned in the first phase) as input, a loss function is optimized to achieve a target web information extraction objective. The trained version of the model is stored.
G06F 16/958 - Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
G06F 30/20 - Design optimisation, verification or simulation
G06F 30/27 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
Techniques for generating a natural language prompt to further a goal of a dialog, are described. During a dialog, the system receives one or more user inputs including a user question, a user response to the question, and a request to generate a further question following the response. The system determines ASR output data corresponding to the user inputs, and determines dialog history data of the dialog. Using the ASR output data and the dialog history data, the system determines a category and an explanation of relevance corresponding to the category. Using the ASR output data, the dialog history, the category, and the explanation, the system determines the further question to be output to the user.
Techniques for presence detection based on multi modal sensors are described. In an example, a computer system determines first data indicating a first prediction of presence detection within a space. The first data is generated based on first sensor data. The computer system determines second data indicating a second prediction of presence detection within the space. The second data is generated based on second sensor data. The second sensor data is of a different type than the first sensor data. The computer system generates third data indicating a third prediction of presence detection within the space based on the first data, the second data, and a fusion model. The fusion model is configured to generate the third data by at least using associations between presence detections, latent variables, and observed variables. The observed variables correspond to the first data and the second data. The latent variables include sensor-triggering events.
An autonomous mobile device (AMD) moves within in a physical space. The AMD may encounter features in the physical space, such as flooring transitions, or obstacles that may impede movement. Sensors such as an inertial measurement unit (IMU), wheel encoders, and motor torque sensors acquire sensor data. Based on the sensor data, measured motion values are determined. Based on physical parameters of the AMD and the sensor data, predicted motion values are determined. A residual or difference between the predicted and measured motion values is calculated. If the residual exceeds a threshold range, a collision may be deemed to have occurred. Characteristics of the residual may be used to determine which side of the AMD collided with an obstacle. Collisions are reliably detected while false detections due to features such as uneven floors or flooring transitions are reduced or eliminated.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G01C 21/16 - NavigationNavigational instruments not provided for in groups by using measurement of speed or acceleration executed aboard the object being navigatedDead reckoning by integrating acceleration or speed, i.e. inertial navigation
83.
Systems and methods for updating large language models
Techniques for updating a large language model (LLM) to correct generation of undesired responses, such as incorrect outputs, toxic outputs, etc. are described. Typical methods of retraining and fine-tuning are inefficient and computationally expensive for LLMs. Some embodiments of the present disclosure involve identifying a salient layer of the LLM that is responsible for the undesired response and editing only the salient layer. This layer is identified by computing a saliency value for the layer using a mean of gradient values for the layer, and the layer with the greatest saliency value is selected for editing. For editing, a small network is used to update the weights of the selected layer. The LLM is updated to include the edited layer, and the updated LLM is used for future processing.
Techniques implementable by a computer system are provided. The techniques include receiving a source speech waveform, the source speech waveform including one or more words spoken by a source speaker. The techniques also include generating source speaker characteristics associated with the source speaker based at least in part on the source speech waveform. The techniques also include receiving a target speaker selection, the target speaker selection associated with target speaker characteristics. The techniques also include generating a target speech waveform based at least in part on the target speaker characteristics, wherein the target speech waveform includes at least a portion of the one or more words.
A device capable of using image data for purposes of determining a location of a user and audio beam selection to isolate audio in the direction of the user. The beamforming/beam-steering may occur after determining the user's location in order to conserve computing resources that would otherwise have been spent determining beams for non-desired directions. The beamformed audio may be used for speech processing, a communication session involving the device, or other purposes.
G10L 17/20 - Pattern transformations or operations aimed at increasing system robustness, e.g. against channel noise or different working conditions
G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions
G10L 17/06 - Decision making techniquesPattern matching strategies
G10L 25/60 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for measuring the quality of voice signals
H04R 1/40 - Arrangements for obtaining desired frequency or directional characteristics for obtaining desired directional characteristic only by combining a number of identical transducers
A device determines estimated playback latency data that may then be used to synchronize audio presentation with other devices. Playback audio data is stored in a buffer by an application processor. A digital signal processor (DSP) retrieves frames of audio data from the buffer. The DSP may generate ultrasonic audio data and mix the playback audio data with the ultrasonic audio data. The mixed data is then sent to an audio output front end the presents the audio data that is audible to a user and the ultrasonic audio that is not. The estimated playback latency data is determined based on a buffer data quantity and a time since a last frame was consumed by the DSP. Given the estimated playback latency data, presentation of subsequent frames may be synchronized by advancing or delaying their write to the buffer, resulting in playback at a specified time.
Systems and methods are disclosed for floor-based antennas for wireless communication in robotic environments. In one embodiment, an example wireless communication system may include a first antenna embedded in a concrete floor structure, where the first antenna may be configured to transmit data to a number of mobile robots in a robotic environment. Individual mobile robots can be configured to transport container pods throughout the robotic environment, and individual container pods may be configured to support a number of inventory containers.
A device includes a first housing, a camera residing at least partially within the first housing, a switch residing at least partially within the first housing, and a second housing coupled to the first housing and at least partially residing within the first housing. The switch is configured to disable the camera. The second housing includes a receptacle configured to receive a battery, and an arm having a tab configured to engage and disengage a lever of the switch to disable the camera. One or more contacts at least partially reside within the first housing and are configured to electrically connect to an accessory coupled to the first housing.
A particular hyper-parameter combination (HPC) that was recommended for a first task is included in a collection of candidate HPCs evaluated for a second task. Hyper-parameter analysis iterations are conducted for the second task using the collection. In one of the iterations, the second task is executed using a first iteration-specific set of HPCs, including the particular HPC and one or more other members of the collection. One or more of the HPCs of the first iteration-specific set of HPCs are pruned to generate a second iteration-specific set of HPCs for a subsequent iteration. HPCs are selected for pruning based on a comparison of their results with the results obtained from the particular HPC that was recommended for the first task. A recommended HPC for the second task is identified based on results of the analysis iterations.
Systems and methods are provided for obtaining policy data associated with a private network implemented at least partly within a cloud provider network; establishing, based on the policy data, a first segment within the private network, wherein in a first geographic region of the cloud provider network, traffic associated with the first segment is isolated from traffic associated with a second segment of the private network, and wherein in a second geographic region of the cloud provider network, traffic associated with the first segment is isolated from traffic associated with a third segment of the private network; obtaining metadata indicating an isolated network of the cloud provider network is associated with the first segment; and enabling the isolated network to communicate, over the first segment, across the first geographic region and the second geographic region.
Described herein is a system for improving navigation by detecting glass surfaces. For example, the system may build an occupancy map representing objects present in an environment. The system performs additional processing to input scan data in order to detect glass surfaces and distinguish these glass surfaces from other obstacles. As glass is only detected within a narrow range of angles and the number of returns are small compared to non-glass surfaces, the system may determine whether an obstacle represented in the input scan data is glass by calculating a maximum range of angles and a number of overlapping returns for the obstacle. For example, the system may identify glass surfaces by identifying objects that are only detected within a narrow range of angles and that have a low number of overlapping returns.
Techniques for host fleet management in a cloud provider network are described. Forecast data including a forecasted demand for virtual machines in each capacity pool of a set of capacity pools is obtained. A mathematical optimizer application is executed to generate a first optimal fleet plan, the mathematical optimizer application having an objective function to minimize a number of new host computer systems to add to the set of host computer systems to satisfy the forecasted demand for each capacity pool, the first optimal fleet plan includes an identification of a set of hardware types and, for each hardware type in the set, a quantity of new host computer systems of the hardware type. A plurality of new host computer systems is deployed, based on the first optimal fleet plan, for a hardware type in the set of hardware types into the set of host computer systems.
Queries may be made against a non-relational database without impacting the capacities of the non-relational database by enabling performance of queries to a non-relational database via an external query management, backup management, and a non-relational database backup hosted in an external data storage. Query units may be provided to an external query engine to provide parallel units of work for accessing and performing queries on a backup of a database.
A system configured to perform source classification using a continuously active beamformer and a classifier to improve beamforming. A device processes audio data representing sounds from multiple sound sources to determine a source direction corresponding to each detected sound source. For each audio frame, the classifier receives a source direction for each unknown sound source and uses the source direction to determine first spectral characteristics that are unique to the individual sound source. By comparing the first spectral characteristics to spectral characteristics associated with labeled sound sources, the device identifies a match and associates the source directions with a corresponding labeled sound source. For each labeled sound source, the classifier determines attributes of a corresponding signal, and the device uses these attributes to select a single sound source. Using a desired look direction associated with the selected sound source, the beamformer generates audio data representing desired speech.
Optical add-drop multiplexers (OADMs) connect two or more network terminals in an optical network to perform wavelength division multiplexing. If a channel in an optical connection between an OADM and a terminal is interrupted for any reason such that the signal in the channel drops, transient effects such as spectral hole burning may occur which impacts neighboring channels. One approach to avoiding such transient effects in channel drop scenarios includes filling in the spectral hole so that neighboring channels are transmitted without any degradation. An OADM includes a broad spectral source, such as an amplified spontaneous emission (ASE) source, and an optical switch that replaces dropped channels with ASE. By providing an automatic mechanism for spectrum filling within the OADM itself in this way, high-capacity optical transmission networks are stable against transient effects even in the presence of channel drops or fiber cuts.
Disclosed are systems and methods that automatically generate access control policies based on access request log entries generated for an existing endpoint. For example, existing systems that utilize authorization control logic (or no authorization control logic) can continue processing access requests as normal and produce access request log entries for each access request. The disclosed implementations process those access request log entries, for example, using a large language model, and generate an access control policy set for the endpoint that includes one or more access control policies determined from the access request log entries.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
Disclosed are various embodiments for detecting potential quality issues in encoded video content. Frame level metrics included in metric data that is associated with an encoded video can be analyzed and one or more quality scores can be calculated using the frame level metric values. If the quality scores meet or exceed one or more threshold values, an alarm notification can be generated that identifies a video segment that has a quality issue along with the one or more quality scores. The alarm notification can be sent to an entity for further evaluation of the encoded video.
H04N 19/154 - Measured or subjectively estimated visual quality after decoding, e.g. measurement of distortion
H04N 19/172 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
H04N 19/177 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a group of pictures [GOP]
H04N 19/65 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using error resilience
H04N 19/85 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
99.
Managing location-aware wireless local area network (WLAN) profiles
Technologies directed to the management of location-aware WLAN profiles are described. A wireless device can store instructions and data with a first environment identifier (EID) unique to a first physical location and a second EID unique to a second physical location. A processing device of the wireless device can generate a third EID at the first physical location and determine that the third EID matches the first EID. The wireless device connects to a first wireless network at a first physical location using a first network name and a first password associated with the first EID.
