A first computing device can receive a fault instruction specifying a fault to inject into a virtual compute instance. The first computing device can then send a command to a second computing device that hosts the virtual compute instance to cause the second computing device to inject the fault into the virtual compute instance. Later, the first computing device can send a heartbeat message to the second computing device to indicate that the second computing device is to continue to introduce the fault. In turn, the second computing device can save a pre-fault state of the virtual compute instance and then introduce the fault into the virtual compute instance. Later, the second computing device can receive the heartbeat message from the first computing device and, in response to receipt of the heartbeat message from the first computing device, continue to introduce the fault into the virtual compute instance.
A surface treatment for use in fabrication of superconductor devices is disclosed. The surface treatment may include an isotropic chemical etch that removes native surface oxide layers and other contaminants, followed by a conformal deposition of a thin dielectric film. The surface treatment may be performed one or more times, at any of several stages in the fabrication of a superconductor device. Applying the surface treatment to a substrate prior to junction formation may provide improved within-wafer uniformity and wafer-to-wafer reproducibility of the resistance targeting. Applying the surface treatment on top of finished junctions and ground plane materials may provide reduced microwave losses, in addition to the increased within-wafer uniformity and wafer-to-wafer reproducibility of the junction resistance.
Techniques for updating a model are described. An example includes determining a proper subset of weights of a first trained machine learning (ML) model to change during an optimization procedure; updating only the proper subset of weights of a second ML model on a first source dataset to generate an optimized ML model; and storing the optimized ML model.
Systems and techniques are disclosed for determining discrepancies between conditions and parameters associated with an image. An image processing model may generate output indicating predicted values for an image using the image as input, while a text processing model may generate output indicating corresponding predicted values for an image using textual data associated with the image as input. A comparison of the output data may be performed to determine discrepancies between values. Discrepancies that are sufficiently significant and relevant may be reported for additional analysis.
A diffusion model is provided with a reference image and a text prompt, and generates output images having content specified in the prompt and style characteristics represented in the image. The reference image is encoded to generate multiple image embeddings. The prompt is encoded to generate a text embedding that is separate from the image embeddings. After each denoising step of the diffusion model, the text embedding is used to perform a first cross-attention operation on the denoising output, and the image embeddings are used to perform a second cross-attention operation. During earlier denoising steps, the second cross-attention operation is associated with a low weight parameter, causing the operation to have a smaller effect on the output image. During later denoising steps, a high weight parameter is used. In some cases, the input image for the model may be generated by performing a diffusion process using the reference image.
Structured interleaving of generations and external interactions for conversation-based generative artificial intelligence applications using extensible role sets and hidden markers
An automated conversation intermediary performs several operations during a conversation between end users and chatbots. Prior to adding natural language input from an end user to a chatbot prompt, the intermediary annotates the input to indicate a role of the end user, using hidden markers for the annotation that are not presented to the end user during the conversation. The intermediary receives output generated by the chatbot, which also includes hidden markers in addition to natural language to be presented to the end user, and removes the hidden markers before providing the natural language portion of the output to the end user.
A set of security rules for user plane traffic of a subset of user equipment (UE) devices of a radio-based application is received via programmatic interfaces at a service of a cloud provider network. A packet comprising user data associated with a UE device of the subset is received at a network function implementation server of the service. An action indicated in a security rule is implemented with respect to the packet at the server.
Systems and methods are provided to round the numbers produced by a systolic array. A rounder, including a plurality of random number generators, can receive a number from the systolic array. Each random number generator may be associated with a random number sequence and may generate a next random number in the random number sequence based on a state value representing a position within the random number sequence. Each random number generator can assume a state based on state value shared by the plurality of random number generators. Each random number generator can cycle through a number of positions within the random number sequence based on the relative position of the random number generator within the plurality of random number generators to generate a random number. The rounder can perform a rounding operation using the generated random number.
G06F 7/499 - Denomination or exception handling, e.g. rounding or overflow
G06F 7/58 - Random or pseudo-random number generators
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
9.
Machine learning image-based estimation of container fullness
Techniques are described herein for image-based determination of container fullness. An example method can include a computing system receiving, from an image-capturing device, a first two-dimensional image of a container including a first item. The computing system can determine, using a machine learning model, three dimensional information based at least in part on the two-dimensional image, the three dimensional information indicating a fullness of the container. The computing system can compare the fullness of the container to a target fullness of the container. The computing system can determine whether the fullness of the container exceeds the target fullness based at least in part on the comparison.
Described are systems and methods for detecting sleep-related breathing events during a sleep session of a user based on sensor data from a wearable device, such as a wrist-worn wearable device. For example, disclosed implementations detect biometric changes of the user that may be indicative of sleep-related breathing events and determine, based on features determined from those biometric changes, that a sleep-related breathing event has occurred. In addition, the disclosed implementations provide a presentation and explanation of the determined sleep-related breathing events.
Disclosed are various embodiments for a simulation framework that facilitates the integration and management of multiple services in a software-in-the-loop simulated environment. A simulation runtime engine can deploy multiple services which may have dependencies upon one another in a simulated environment. Network service calls sent from one simulated services to another service may be intercepted to ensure that the network service call is sent to the simulated instance of the service instead of the actual non-simulated instance of the service. In addition, system time calls are intercepted to ensure that the requested service is provided the simulation time.
Systems and methods are disclosed for shuttle height monitoring systems for shuttles powered by linear synchronous motors. An example system may include a track, a first sensor disposed adjacent to the track, a second sensor disposed adjacent to the track, a third sensor disposed adjacent to the second sensor, and a controller. The controller may be configured to determine, using the third sensor, that the first shuttle is adjacent to the first sensor, determine, using the first sensor, a first distance between a first lower portion of the first shuttle and the first sensor, determine, using the second sensor, that the second shuttle is adjacent to the first sensor, and determine, using the first sensor, a second distance between a second lower portion of the second shuttle and the first sensor.
Methods and systems configured to embed data representing content output by at least one device for downstream content recognition or other downstream processes. For example, a device operates one or more media data embedding components configured to embed information regarding the output media, such as audio or image content. The embedding component is trained to embed information for a subset of known downstream processes with some known processes deliberately held out from the training. Among other benefits, this approach can help reduce over customization of the embedding component and allow more information to preserved by the component for purposes of downstream operations that may yet be configured.
G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
Methods and systems of using an approximate duplicate event filter are disclosed. Event processing systems of a service provider network such as a security service may receive a large volume of events to analyze. Events that have previously occurred can be given a lower priority for analysis than new events. Events that are similar to previous events can likely also be given a lower priority for analysis. These non-exact match events can be detected by comparing token representations of new events to token representations of previous events. Events may be considered according to the context in which the events occur.
G06F 12/0864 - Addressing of a memory level in which the access to the desired data or data block requires associative addressing means, e.g. caches using pseudo-associative means, e.g. set-associative or hashing
G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
Systems and methods are described for using multiple threshold maps for color dithering. An example method may comprise determining a tertiary RGB color. The example method may comprise selecting, using data representing the tertiary RGB color, a dithering threshold map indicating a pattern of alternating threshold values. The example method may comprise selecting, based on the tertiary RGB color and the dithering threshold map, a tertiary color value set comprising a red value, a green value, and a blue value. The example method may comprise mapping, based on the dithering threshold map, the alternating threshold values to a pixel set of a portion of an RGB display. The pixel set may include one or more of a red pixel, green pixel, and/or blue pixel. The example method may comprise activating, based on the tertiary color value set and the dithering threshold map, at least in part, the pixel set.
G09G 3/20 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix
G02F 1/167 - Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulatingNon-linear optics for the control of the intensity, phase, polarisation or colour based on translational movement of particles in a fluid under the influence of an applied field characterised by the electro-optical or magneto-optical effect by electrophoresis
G02F 1/1677 - Structural association of cells with optical devices, e.g. reflectors or illuminating devices
G09G 3/34 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix by control of light from an independent source
17.
Mitigating denial of service attacks by leveraging geographical locations of network edges
A system analyzes network traffic at the network edge in a Point-of-Presence (POP) to prevent denial of service attacks, such a reflection attack, and filters such attack traffic. The POP can analyze a source identifier of the network traffic, such as a source prefix, and compare the source identifier to known source identifiers from the same geographic region as the POP. If the source identifier is outside of the POPs geographic region, then the network traffic is rate limited, such as by blocking the network traffic or reducing the network traffic to a desired threshold. To further ensure that the traffic is routed to the appropriate POP, the POP edge location announces anycast addresses for receiving the network traffic. The geographic region can be defined as a city, a country, sub-regions within a country, a portion of a continent (e.g., southeast region of Asia), a continent, etc.
A technique to compute statistics of data elements include serially inputting the data elements into a compute channel. The compute channel can generate a first running mean and a first running variance associated with data elements of the vector having odd sequence indices, and a second running mean and a second running variance associated with data elements of the vector having even sequence indices. Subsequent to serially inputting data elements into the compute channel, the first running mean and the second running mean are aggregated to generate a mean associated with the data elements of the vector, and the first running variance and the second running variance are aggregated to generate a variance associated with the data elements of the vector.
Testing recommendations for an updated software build can be generated. For example, a computer system can determine a classification of a modification of a component of a software build into a category based on a text file that indicates the modification of the component. The computer system can also determine a recognition of an entity type for the component of the software build based on the text file. The computer system can generate, based at least in part on the classification and the recognition, a recommendation indicating one or more tests for use in testing the modification to the software build.
Devices, systems, and methods for language model prompt engineering include a method of: providing, by at least one first processor, to a language model, a first prompt including a first task and instructing the language model to generate a set of task-specific reasoning modules; generating, by the language model, the set of task-specific reasoning modules based on the first prompt, the set of task-specific reasoning modules including a first reasoning module; providing, by at least one second processor, to the language model, a second prompt including the first task, a second task, and the first reasoning module, wherein the second prompt instructs the language model to generate an initial reasoning structure defining how to respond to the first task without providing a response; and generating, by the language model, the initial reasoning structure based on the second prompt.
Provided is a system for facilitating recovery of deleted computing resources in a cloud network environment. A centralized resource recovery service may communicate with a plurality of resource management services that are each configured to create, modify, or delete their respective computing resources such as storage volumes, databases, and compute instances. The resource recovery service may allow creation of immutable resource retention rules that are, under certain conditions, unable to be deleted or modified, even by an administrative user who created such retention rules. Such immutable retention rules may be used to thwart malicious attempts to permanently delete resources by deleting the retention rules that govern such resources. Since such attempts to delete such immutable retention rules would fail, the retention rules would continue to apply and allow deleted resources to be placed in a recoverable state according to the retention rules.
A large language model (LLM) may be used to generate an overall entity representation of an entity using an input that includes individual representations based on graph data, text data, and image data associated with the entity. Graph data that represents characteristics of the entity and types of relationships between the entity and other entities is used to generate a graph representation. Text associated with the entity is used to generate a text representation. Image data associated with the entity is used to generate an image representation. These representations are used to generate an input to the LLM, which is trained to generate an entity representation based on the input. The entity representation may be used by other models, such as to determine entities having similar or differing characteristics.
In various examples, systems and methods for stability prediction for 3D robotic bin packing are described. A set of contact points for a first item at a first candidate placement position may be determined. A first contact point having a minimum value along a first coordinate dimension and a second contact point having a maximum value along the first coordinate dimension may be determined. A third contact point that is a maximum distance between a line between the first contact point and the second contact point may be determined. A determination may be made whether a centroid of the first item is within a triangle defined by the first contact point, the second contact point, and the third contact point. A stability of the first item at the first candidate placement position may be determined based on the location of the centroid.
A control plane server of a network-accessible service of a cloud provider network obtains an indication from a client that security artifacts to be used for establishing connections among constituent services of an application are to be obtained automatically by the service. The control plane server transmits, to a first agent established at a first resource at which a first constituent service of the application runs, a set of security artifacts obtained from an artifact source and assigned to the first constituent service by the control plane server. The set of artifacts is used to establish a connection between the first agent and a second agent at a second execution resource at which a second constituent service of the application runs. Messages between the constituent services are sent using the connection.
H04L 15/16 - Apparatus or circuits at the transmitting end with keyboard co-operating with code discs
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
Techniques for implementing cross-domain identity trust using trusted token issuers are described. An identity provider is registered with an identity service of a cloud provider network in association with an organization or user. Thereafter, tokens generated by the identity provider can be provided to the identity service as part of token exchanges to obtain new tokens useful for accessing resources managed or provided by applications, such as services, within the cloud provider network. The token exchange process can include use of administrator-provided mapping information indicating how to associate user identity information from an identity provider token with user identity information in a directory utilized by the identity service, whereby the new tokens include identity information that is easily utilized by receiving applications for making access control determinations and performing logging for auditability.
A search language is provided for writing rules that allow semantic and syntactic checking of source code to find potential errors in a target code. The language allows for wildcards (also called placeholders), which provide a more expansive matching of search terms. A compiler is described that converts a search language query into a semantic graph representation. The target code being searched can also be converted to a target graph representation. A comparison can then be performed between the semantic graph representation and the target graph representation to determine if the semantic graph representation is contained within the target graph representation. If so, then a semantic match is found in the target source code. More specifically, semantic matching can be realized by checking homomorphism against the target graph representation. In one example, the semantic matching can include a comparison of nodes and edges connecting the nodes.
Systems and methods are provided for swift restoration of a network connection and communication session between computing systems. A network connection between two computing systems may be established. When the network connection is interrupted, one computing system may send a reestablishment connection to the other computing system, and the network connection may be reestablished based on the reestablishment communication without establishing a second network connection.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
H04L 41/0654 - Management of faults, events, alarms or notifications using network fault recovery
Computer-implemented techniques for autonomic control plane scaling in a container orchestration cluster. The techniques include a method that involves managing a container orchestration cluster's control plane. When a control plane instance is underutilized, it handles control plane requests and monitors its resource usage. If it becomes overutilized (hot state), it identifies another instance with spare resources (cold state) and redirects control plane traffic to it to maintain performance and availability.
A cart system for inventory management can include a cart frame including a base, a handle to control movement of the cart frame, a stationary shelf, and a movable shelf disposed above the stationary shelf. The movable shelf is movable in a path of travel vertically overhead of the stationary shelf to change a volume underneath the movable shelf to stack items over each other within the volume and supported by the stationary shelf. A height adjustor can be configured to lower or raise the movable shelf in a vertical direction to an ergonomic height for loading the items and a storage height to store the items while creating sufficient volume below the movable shelf loading the items on the stationary shelf. A cart controller can be configured to receive a height input, and control the height adjustor based on the height input.
B62B 3/02 - Hand carts having more than one axis carrying transport wheelsSteering devices thereforEquipment therefor involving parts being adjustable, collapsible, attachable, detachable, or convertible
B62B 3/04 - 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
B62B 5/00 - Accessories or details specially adapted for hand carts
A first-in-first-out (FIFO) device includes a plurality of FIFO stages coupled in series. Each FIFO stage includes a data register representing a FIFO entry, a valid register storing a data valid signal to provide a valid signal to indicate whether the FIFO entry is storing valid data, and an input multiplexer to provide data to a FIFO stage. Upon receiving a push signal to store input data into the FIFO device, a FIFO stage of the FIFO device determines whether to update the data register of the FIFO stage based on respective valid signals from the FIFO stage, and neighboring FIFO stages of the FIFO stage. Upon receiving a pop signal to provide output data from the FIFO device, the FIFO stage determines whether to provide data stored in the data register of the FIFO stage or the input data of the FIFO device to the preceding FIFO stage.
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
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
Aspects of the present disclosure relate to systems and methods for enforcing safe operational limits on the control signals used to operate a robotic system in a human-centric environment to protect against damage to the robotic components. According to an aspect of the present disclosure, the robotic system generates an intervention signal when control signals exceed safe operating limits. The intervention signal may be used to signal a warning to a user and/or may cause the system to change poses or activities to restore the robotic system to operating within the safe operating limits. Some aspects of the present disclosure relate to monitoring the power usage and/or temperature of components of the robotic system. One or more aspects of the present disclosure may be used in combination with each other and/or may be used with additional systems and processes for controlling a robotic system in a human-centric environment.
G05D 1/85 - Fail-safe operations, e.g. limp home mode
G05D 1/86 - Monitoring the performance of the system, e.g. alarm or diagnosis modules
G05D 101/15 - Details of software or hardware architectures used for the control of position using artificial intelligence [AI] techniques using machine learning, e.g. neural networks
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
33.
ORDERED TEMPORARY CREDENTIALS FOR ZERO-TRUST SYSTEMS
Techniques for implementing and utilizing ordered temporary credentials for a zero-trust system implemented in a multi-tenant cloud provider network are described. An Access Management (AM) service obtains ordering configuration indicating a sequence or pattern of requests that are allowed to be made in association with a credential or session. In authorizing requests made to services, the AM service can determine if the request, together with any other requests made via the credential or session, matches the constraints defined by the ordering configuration, and deny an access when the request would violate the ordering configuration.
A computing system supporting reliable network communications can include a virtual machine executing a user application, and a network adapter device coupled to the virtual machine via a plurality of virtual interfaces. The user application can communicate with the network adapter device using a virtual interface assigned to the user application. Queue pairs, each including a send queue and a receive queue, can be implemented to process transmit packets being sent from the virtual machine to the network and incoming packets being sent to the virtual machine from the network.
H04L 69/324 - Intralayer communication protocols among peer entities or protocol data unit [PDU] definitions in the data link layer [OSI layer 2], e.g. HDLC
H04L 69/326 - Intralayer communication protocols among peer entities or protocol data unit [PDU] definitions in the transport layer [OSI layer 4]
35.
ORDERED TEMPORARY CREDENTIALS FOR ZERO-TRUST SYSTEMS
Techniques for implementing and utilizing ordered temporary credentials for a zero-trust system implemented in a multi-tenant cloud provider network are described. An Access Management (AM) service obtains ordering configuration indicating a sequence or pattern of requests that are allowed to be made in association with a credential or session. In authorizing requests made to services, the AM service can determine if the request, together with any other requests made via the credential or session, matches the constraints defined by the ordering configuration, and deny an access when the request would violate the ordering configuration.
Facilities for accommodating ground vehicles include spaces or enclosures defined by frames, panels and doors mounted to such frames, and charging consoles provided within the spaces or enclosures. Doors may be operated to enable a ground vehicle to enter a space and receive electrical power from a charging console or transfer information or data to external computer systems. Doors may also be operated to enable workers to access the space to inspect the ground vehicle or deposit an item within the ground vehicle. Facilities may include multiple spaces or enclosures for accommodating ground vehicles and may be formed by joining frames to one another and mounting panels or doors to such frames.
Package storage space optimization systems and methods may utilize a combination of fixed racks for standardized packages, fixed racks for non-standardized packages, and reconfigurable racks that can be configured for either standardized packages or non-standardized packages based on an expected package mix. The reconfigurable racks may be manually, semi-automatically, or automatically configured between standardized or non-standardized package configurations. In addition, the reconfigurable racks may include controllers, visual and/or audio output devices, actuators, and/or sensors to facilitate at least partially automated conversion between standardized or non-standardized package configurations.
Selective frequency dissipation is implemented that enables cooling of energy gap protected qubits such that excited energy states resulting from heating or other undesired processes are returned to a lower excited energy state or a ground state manifold, thus reducing the probability of errors. Also, the selective frequency dissipation inhibits leakage from the energy gap protected qubits when in the ground state. Additionally or alternatively, Hamiltonian engineering by inducing parity rotations is implemented to decouple the wells of the energy gap protected qubit to further reduce errors when leakage does happen.
A signal to software interface management system generates a software code for implementing a signal to software interface to be deployed to a vehicle system component. The software interface management system may train a machine learning model using a plurality of types of vehicle signals and one or more vehicle specifications to generate the software code for implementing the signal to software interface. The signal to software interface may map a vehicle system component signal to a schema key associated with that vehicle system component, and may format the vehicle system component signal for use by a vehicle software according to a schema associated with the schema key.
A system may be configured to: receive, via user interaction with a user interface, content and a user request to generate a content summary of the content, wherein the user request specifies the content summary is to be generated according to a categorical description, generate, via a soft-prompt generator, a first soft prompt based on the request and one or more tokens, generate, via a summary generator, a categorical description output based on the first soft prompt and the content, generate, via the soft-prompt generator, a second soft prompt based on the categorical description output and the one or more tokens, transmit the second soft prompt to the summary generator; and generate, via the summary generator, the content summary based on the second soft prompt and the content.
Some embodiments provide an integrated circuit (IC). The IC includes a microprocessor circuit for loading configuration for a neural network and generating instructions for executing the neural network based on the configuration. The IC includes a neural network inference circuit for executing a neural network for input data according to instructions received from the central processing circuit. The IC includes an input processing circuit for receiving data and preparing input data for the neural network inference circuit. The IC includes a unified memory accessible by the microprocessor circuit, neural network inference circuit, and input processing circuit.
Techniques are described for maintaining contextual data to support content-related actions. In an example, a system stories second content at a source. The source is associated with first content. The system sends, to a device, an object that indicates the first content. From the device at a first time, the system receives first data indicating a first request for the second content and including source information that indicates the source. From the device at a second time, the system receives second data indicating a second request for the second content, the second data including the source information, the first data and the second data received at a frequency indicated by the object. The system determines that the requests are associated with the first content based on the source information included in the received data, and stores third data indicating a presentation of the first content by the device.
Computing resources for anomaly detection on time series data using a machine learning model may be dynamically provisioned. An expected workload of anomaly detection on time series data is determined in order to determine a number of computing resources. The number of computing resources are provisioned for anomaly detection and updated when the machine learning model is re-trained.
H04L 47/765 - Admission controlResource allocation using dynamic resource allocation, e.g. in-call renegotiation requested by the user or requested by the network in response to changing network conditions triggered by the end-points
Embodiments of secure session resumption protocol selection based on cost analysis are disclosed. Session resumption requests are received from clients (e.g., as packets). A cost (e.g., network latency time) associated with a client-round-trip-based resumption process that requires a round trip between the server and the client is determined. Another cost associated with a no-round-trip-to-client-based resumption process is determined (e.g., network latency to access a session state data store and/or session state data store processing time). The costs are analyzed in order to select which session resumption process is used to resume the requested session. The session is resumed using the selected session resumption process. In some embodiments, a particular secure session resumption protocol may be selected based on classification of the client into a category that estimates a roundtrip time between the client and the server.
A data anonymization service of an application development service is configure to protect sensitive data while providing data context in the reproduction of application events. Upon detection of an execution symptom within a production application, data required to reproduce the symptom is collected as input to an anonymizer to facilitate minimal-trust analysis of the symptom. The data may first be minimized to eliminate data elements not needed to reproduce the symptom, the data elements are identified that are essential to reproduce the symptom are determined to contain sensitive data according to client-provided rules. These identified elements are then transformed to anonymize the sensitive data while preserve reproducibility of the symptom. A modified data set including the transformed data elements may then be provided to an application development service for analysis.
Materialized views may be optimally selected for materialized view creation or refresh. Materialized views for creation or refresh may be identified. A subset of the materialized may be determined according to an optimization technique that selects the subset of the materialized views according to a maximized performance benefit for maintaining the subset of materialized views based on a workload of the database system caused by a set of previously received queries. Individual ones of the subset of materialized views to create or refresh may be selected and performed according to a performance benefit-based order of the subset of the materialized views.
Systems and methods are provided for natural language query processing and data visualization generation. The system can analyze the natural language query for semantic attributes and compare the semantic attributes against the semantic data of a set of data visualizations to generate context for the natural language query in the form of a personalized set of semantic data. Based on the semantic attributes and the semantic data, the system can select a set of exemplars that best match the natural language query and using the exemplars, and a library specification, generate library specification programming code for generating a structured query to resolve the natural language query. Based on the results of the structured query, the system can generate a data visualization as a response to the natural language query.
Some embodiments provide a method for training a first NLP network based on a previously-trained second NLP network. The method propagates text inputs through the first network to generate a first set of output vectors and the second network to generate a second set of output vectors. Each first-set vector generated based on a text input has a corresponding second-set vector generated based on the same text input and each vector of the first and second sets has a same number of vector components. The method computes a value for a loss function that emphasizes a maximum disparity between components of first-set vectors and corresponding components of second-set vectors. The method trains the first network using the computed loss function value to minimize the maximum disparity between the first-set vector components and corresponding second-set vector components so that the first network produces outputs similar to outputs of the second network.
A system may share updates to a machine learning model between a first device and a second device. The first device may determine one or more updatable layers of the model. The first device may train the first model to update parameters of the updatable layers in response to processing input data using the model. The first device may keep parameters of model layers other than the updatable layers constant during the training. The first device may send, to the second device, first model update data representing the updated parameters. The second device may aggregate model update data (e.g., from multiple devices), determine second model update data, and send the second model update data to the first device. The first device may update its model based on the second model update data.
A dialog driven system may implement context inclusive interruption detection. During an audio presentation of a dialog generated by a dialog driven system, a voice audio may be detected. A context inclusive encoding may be generated for the voice audio, such as an acoustic encoding of the voice audio. The context inclusive encoding may be used to apply a machine learning model to classify whether the detected voice audio is a true interruption or a false interruption. False interruptions may allow the audio presentation to continue. True interruptions may stop audio presentation to process the voice audio as a response to the dialog.
A system includes a housing and a light emission source positioned within the housing and including a first light emitter array characterized by a first polarization state and a second light emitter array characterized by a second polarization state. The light emitted by the light emission source is configured to propagate along an optical axis. The system also includes a lens positioned within the housing along the optical axis and a wavefront modification element positioned within the housing along the optical axis. The wavefront modification element comprises a polarization-sensitive diffractive structure.
H01S 5/183 - Surface-emitting [SE] lasers, e.g. having both horizontal and vertical cavities having only vertical cavities, e.g. vertical cavity surface-emitting lasers [VCSEL]
An access management policy and security information indicative of one or more security constraints may be received, by a service, from an entity, such as a customer. The access management policy and the security information may be received in association with a request for the service to perform a policy validation check for validating the policy. The service may perform a permissions comparison that compares a permissiveness of the access management policy to the one or more security constraints to generate a permissions comparison result. The service may generate, based on the permissions comparison result, a binary policy validation check result that may be indicative of either passing or failing the policy validation check. When the access management policy fails the policy validation check, the service may determine a given allow statement within the access management policy that caused the access management policy to fail the policy validation check.
Multiple streams of media are analyzed for defects by synchronizing the streams in time and generating hashes or other representations of images of the respective streams. Where the hashes or other representations of two or more streams are sufficiently similar to one another, the streams may be determined to be similar to one another, and a determination as to whether each of the streams is defective may be made by analyzing just one of the streams. Where the hashes or other representations of two or more streams are not sufficiently similar to one another, a determination as to whether each of the streams is defective may be only made by analyzing all of the streams independently.
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04N 21/2662 - Controlling the complexity of the video stream, e.g. by scaling the resolution or bitrate of the video stream based on the client capabilities
Techniques for generating an executable API call for an LLM-generated request, where the executable API call is usable to cause a component to generate a potential response to a user input, are described. In some embodiments, the system receives a user input and uses a language model to generate a request for a component to provide a potential response to the user input. The system uses the request, an API description corresponding to the component, and other information not available to the language model during processing to generate an executable API call corresponding to the request. The system can execute the executable API calls (in a system-determined order or concurrently) to cause the corresponding components to generate potential responses to the user input.
A method may include determining that a weighted volume of a first item in an inventory system. The weighted volume can be based on an actual volume and a weight associated with a volume category for the first item. The method may include comparing a weighted average volume based on weighted volumes for a second set of items in a container and a weighted volume of the first item with a volume threshold of the container. The method may include causing the item to be transferred to the container with respect to the comparison between the weighted average volume and the volume threshold. The method may include updating the volume threshold of the container based on a volume of a third set of items in the container after transferring the item to the container. The third set of items can include the first item and the second set of items.
An aerial vehicle or another system having moving components may be configured with a capacitive sensing system for detecting body parts of humans or other animals within proximity. The capacitive sensing system includes conductive components provided in association with surfaces of housings within which motors rotate propellers or other objects. The capacitors are coupled to circuits including transistors, resistors, capacitors or other features that are configured to determine levels of capacitance on the conductive components during operations of the aerial vehicle or other system. When a body part approaches a conductive component, and disrupts a level of capacitance on a capacitor coupled to the conductive component, a change in the level of capacitance on the capacitor is detected. Where the change exceeds a predetermined threshold, predetermined actions such as stopping or otherwise altering operations of the motors may be performed.
Generally described, the present application relates to providing a container orchestration service that can enable and manage execution of containerized applications on user-owned infrastructure and cloud-provided compute capacity. In some embodiments, a request to execute a task may indicate the type of compute capacity (e.g., internal/external, computing resource amount, etc.) to be used to execute the task. For example, if the task indicates that internal compute capacity is to be used, compute capacity hosted the cloud provider network can be identified and used to execute the task. Alternatively, if the task indicates that external compute capacity is to be used, instructions for executing the task can be generated and sent to the user-owned infrastructure, and the task can be executed using compute capacity provided within the user-owned infrastructure, which is external to the cloud provider network implementing the container orchestration service.
A group-based event analysis service may be implemented by a provider network to monitor service-to-service event streams to identify behavior that is abnormal for a particular group of event streams. Event streams may be classified into groups based on the computing resources or services that generate the events, the behavior patterns of the events in the event stream, and other information about the event streams. Deviations in behavior of individual members of a group relative to group behavior may be used to identify anomalous and/or potentially harmful behavior.
A system may receive a content request, and generate a set of tokens based on the content request. The system may transmit the set of tokens to a model deployer, and receive a mask in response. The system may then generate a second mask. The system may combine the model deployer mask and the second mask to generate a combined mask. The system may obtain a next token as part of a response, the next token selected based in part on an output of a machine learning model in response to the set of tokens and the combined mask being provided as input to the machine learning model. The system may add the next token to the set of tokens to generate an updated set of tokens; and transmit the updated set of tokens to satisfy the content request.
Techniques for training and testing machine learning models using biased samples are described. In some examples, a sampled test set is generated by estimating a propensity score for each annotation of the set of annotations, wherein a propensity score quantifies a likelihood of being human generated using the set of data, estimating a confidence score for each annotation of the set of annotations, wherein a confidence score quantifies a confidence in a correctness of the annotation, mapping each annotation of the set of annotations to a multi-dimensional space based at least in part on the propensity score, stratifying, based on the propensity score, the mapped annotations, and sampling each stratum according to a request to generate a sampled test set.
Techniques for modifying values included in an input to be provided to a LLM are described, where the values are likely to result in decrease accuracy of an LLM output. In some embodiments, the system receives a user input and may cause various components to determine data usable to generate a response to the user input. Prior to causing a language model(s) to process information, the system may identify that an input to the LLM includes a value that is to be modified. The system may generate a modified value and may provide input data including the modified value to the LLM. Thereafter, the system may revert the modified value to the original value so that another component may perform its configured processing with respect to the original value.
An electronic filter includes a ground plane and a top conductor overlying the ground plane. The top conductor includes an input and an output for receiving and outputting signals, respectively. The filter further includes a plurality of unit cells arranged in series along the top conductor. Each of the plurality of unit cells includes a planar structure disposed between the top conductor and the ground plane. Each of the plurality of unit cells further includes a pair of vias connecting the planar structure to the ground plane. The filter further includes at least one discrete reactive element connected to the top conductor and arranged in a series or a shunt configuration.
In a computer networking system, data is transmitted between network devices in packets. The disclosure provides mechanisms for preserving address data in a stateless manner by storing a unique identifier, corresponding to an address of an endpoint targeted by an original source device, in a header field of an encapsulated packet. The unique identifier may be persisted in an encapsulated return packet transmitted back to the original source device and used to recover the address of the endpoint for inclusion in a source header field of the return packet that is transmitted to the original source device.
Disclosed are various embodiments for self-service management of customer owned or controlled autonomous system numbers in a cloud provider network. In one embodiment, a request is received from a customer to utilize a first autonomous system number (ASN) of the customer in a cloud provider network. Control of the customer over the first ASN is authenticated based at least in part on data publicly associated with the first ASN. An account with the cloud provider network is authorized to utilize the first ASN based at least in part on an authorization request from the customer. Network traffic is routed according to routing information that associates a network address block of the account in the cloud provider network with the first ASN of the customer instead of a second ASN of the cloud provider network.
An analysis request for a data stream is received at a streaming data analytics service from a client associated with a customer account. A set of concurrency snapshot records of the customer account is retrieved from a data store and used to compute a request rate acceleration metric of the account. Based at least in part on the acceleration metric, the analysis request is accepted and analysis of the data stream is initiated.
Systems and methods for generating customized media content are provided (for example, trailers or recaps for a movie or television show). For example, the system may generate a trailer to a television show that is tailored to a specific user, such as a trailer that includes action-specific scenes for a user who often views content in an action-based genre. The system may receive as an input a text or voice-based query from the user (or the system may be automated and may receive user historical data as an input). Based on the input, one or more computing models may generate a text-based narrative to be used with the customized content. Once the narrative is generated, the one or more models may then identify specific video frames to include in the customized content. The video frames may then be stitched together and the customized content may be generated using the stitched video frames and the narrative.
Robotic manipulators that can independently or collaboratively perform tasks are described herein. For example, a robotic system can include a set of linear rails, a first robotic manipulator, and a second robotic manipulator. The first robotic manipulator can be mechanically coupled to a first linear rail of the set of linear rails. The first robotic manipulator can move, along the first linear rail, a first object between first locations. The second robotic manipulator can be mechanically coupled to a second linear rail of the set of linear rails. The second robotic manipulator can move, along the second linear rail, a second object between second locations. The second linear rail may be the same or different from the first linear rail. The first robotic manipulator and the second robotic manipulator may collaboratively move, along the first linear rail and the second linear rail, a third object between third locations.
Systems and methods for mechanical breakers with automatic resetting features and related systems. In one embodiment, an example breaker assembly includes a base portion having a backplate having a fixed position, a spring coupled to the backplate, and a first bracket configured to receive a securing member, where the securing member secures the spring to the first bracket. The breaker assembly may include a pivot portion configured to pivot with respect to the base portion, the pivot portion having a second bracket having a detent surface configured to engage the securing member when the breaker assembly is in a default position, and a member coupled to the pivot portion. The pivot portion pivots with respect to the base portion based at least in part on a force applied to the member, and the pivot portion returns to the default position automatically when the force is no longer applied.
B25J 19/00 - Accessories fitted to manipulators, e.g. for monitoring, for viewingSafety devices combined with or specially adapted for use in connection with manipulators
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
71.
Fiducial-based lidar malfunction detection for autonomous motile devices
An autonomous motile device (AMD) may include a light detection and ranging (LIDAR) subsystem that is usable for floor detection. The LIDAR subsystem may include a LIDAR component and a fiducial disposed in a path of light emitted by the LIDAR component. The LIDAR component provides distance data to a processor, the distance data comprising one or more distance values based at least in part on light emitted towards the fiducial. The processor determines a value based on the distance data, and determines whether the value is outside of a predetermined range of values. If the value is out of bounds, this may be indicative of the LIDAR component having malfunctioned, and the processor may cause the AMD to perform an action in response to the LIDAR malfunction.
A lens system includes an aperture stop, a first lens disposed on a first side of the aperture stop, a second lens disposed on the first side of the aperture stop, a third lens disposed on a second side of the aperture stop, and a fourth lens. The first lens is manufactured from glass. The second lens, the third lens, and the fourth lens are manufactured from thermoplastic. The fourth lens includes a first surface oriented towards the aperture stop and a second surface oriented away from the aperture stop. The first surface is refractive and diffractive to light passing through the lens system.
G02B 13/00 - Optical objectives specially designed for the purposes specified below
G03B 17/54 - Details of cameras or camera bodiesAccessories therefor adapted for combination with other photographic or optical apparatus with projector
G03B 21/00 - Projectors or projection-type viewersAccessories therefor
G03B 21/53 - Means for automatic focusing, e.g. to compensate thermal effects
73.
Balancing and improving holographic waveguide efficiency
Techniques for improving holographic waveguide efficiency are described. In an example, a waveguide includes a substrate having a first surface and a second surface. The waveguide includes a holographic layer configured to inject, into the substrate as first light, light received at the first surface, diffract a first portion of the first light such that the first portion propagates in a first propagation direction, and diffract a second portion of the first light such that the second portion propagates in a second propagation direction. The waveguide includes a reflective component configured to reflect a remaining portion of the first light as second light from the second surface toward the first surface. The holographic layer is further configured to diffract a first portion of the second light such that the first portion of the second light propagates within the substrate in the first propagation direction.
G03H 1/02 - Holographic processes or apparatus using light, infrared, or ultraviolet waves for obtaining holograms or for obtaining an image from themDetails peculiar thereto Details
A technique for matching the throughput between writing into and reading from a memory can include receiving, in parallel, computational results in a high precision format for storing into the memory at a first frequency, and storing the computational results in the memory. The technique may further include rounding the computational results using round-to-the-nearest-even or stochastic rounding to down-convert the computational results from the high precision format to a low precision format in parallel, and outputting the computational results in the low precision format in parallel from the memory at a second frequency.
G06F 7/499 - Denomination or exception handling, e.g. rounding or overflow
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
Systems and methods are provided to reduce the latency in accessing an input/output (I/O) hardware register by software executing on a central processing unit (CPU). The hardware register is located in a controller coupled to the CPU via an I/O bus. The CPU software can send a command to the controller for execution. The controller can execute the command and update the hardware register to indicate that the command has been executed. The controller can write contents of the hardware register to a specified address in a CPU memory that is assigned by the CPU software. The CPU software can read the specified address to determine that the command has been executed instead of reading the hardware register on the I/O bus.
G06F 13/16 - Handling requests for interconnection or transfer for access to memory bus
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
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 15/173 - Interprocessor communication using an interconnection network, e.g. matrix, shuffle, pyramid, star or snowflake
G06F 15/78 - Architectures of general purpose stored program computers comprising a single central processing unit
A data item identification service may use locality sensitive hashing to identify data items which are relevant to a search based on a hash of a search vector based on the search. Hashes of vectors based on data items may be stored using a set of bitmaps, where a given bitmap corresponds to a given bit position of a hash. Data items with matching or similar hashes may be related to each other. The data item identification service may perform searches by generating a hash for a search vector and comparing the hash to hashes for data items using one or more logical operations on the set of bitmaps to identify related data items.
Devices and techniques are generally described for application shortlisting for language models. An LLM may determine a first goal of first query data. The LLM may generate first code data representing the first query data. First encoded data including a first encoded representation of the first goal and the first query data may be generated. A first application may be determined based at least in part on analysis of the first encoded data with respect to second encoded data representing the first application. A second application may be determined based at least in part on analysis of the first encoded data with respect to third encoded data representing the second application. First prompt data including the first query data, first data identifying the first application, and second data identifying the second application may be generated. The LLM may generate output data based at least in part on the first prompt data.
Systems and methods are disclosed to implement, in a database service, applying operations to replicas of a global table based on homing rules and item attribute values. In embodiments, an instance of a database service may receive, from a client, a request to write an item to a global table. The instance may store the item at one or more replica tables at one or more different regions based a homing rule for the global table and one or more attribute values of the item.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
A natural language analysis system processes a data item and recommends similar data items. The natural language analysis system preprocesses the data items. The natural language analysis system encodes the text of the input data item using a machine learning model, such as a transformer model. The natural language analysis system recommends related data items based on the encodings of the data items. The natural language analysis system uses perturbations to provide explanations for the recommendations and/or improve the recommendations.
A nodal data structure based on a first data and a second data is generated. The nodal data structure can include a first node including the first data, a second node including the second data, the second node linked to the first node, and a reference to a data structure including the first data and the second data is associated with the second node. The reference to the data structure including the first data and the second data is located using the nodal data structure generated based on the first data and the second data.
A machine learning model may be trained to detect items depicted within images captured in a materials handling facility. Activations generated in response to inputs including images are provided to a masking component programmed with a support set including identifiers of items, such as items within a field of view of a camera that captured the images. The masking component converts activations corresponding to items not in the support set to significantly negative values, such as negative infinity, while leaving activations corresponding to items in the support set unchanged. Activations corresponding to items that are in the support set and not in the support set are then processed to generate probabilities that the images depict one of such items, with the significantly negative values of activations corresponding to items not in the support set resulting in probabilities of zero.
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 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
G06V 10/40 - Extraction of image or video features
G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 40/10 - Human or animal bodies, e.g. vehicle occupants or pedestriansBody parts, e.g. hands
82.
Dynamic insertion of intermediate network components
Systems and methods are provided for automatic generation of routing through a user-specified network appliance. A wide area network (WAN) may include isolated network nodes, such as, VPCs, VPNs, or client-on-premises devices. The WAN may also include network appliances, such as firewalls or load balancers. To manage traffic between isolated network nodes, a management component of the WAN may access instructions including specified network appliances for inclusion in routes between isolated network nodes. Based on these instructions, the management component may then generate segments with routing information relating to steering traffic through the specified network appliances. The routing information may relate to steering traffic across region and/or segment boundaries within the WAN.
Systems and methods are provided for allowing service providers to take actions based on identifying a function invoker executing a function via an on-demand code execution service. The service provider may receive an IP address or header information from the on-demand code execution service along with information regarding a function invoked by a function invoker. The service provider may determine the function invoker based on reviewing the IP address or header information. Once identifying the function invoker, the service provider may take actions based at least on information regarding the function invoked and the function invoker.
Techniques for a Predictive Connection Manager Service (PCMS) to predict when client applications will send service requests to backend services, and proactively establishes connections, caches data, or takes other actions, to reduce latencies between receipt of and response to these service requests. The PCMS analyzes historical usage data for the client applications to identify usage patterns, and uses those usage patterns to proactively scale resources to handle service requests. The PCMS can be implemented as a pass-through proxy for client applications to reduce frictions for managing how users interact with backend services. For instance, the PCMS can install client-side drivers such that updates or patches for the drivers need only be installed on the PCMS rather than on each client device. Further, the PCMS provides interfaces through which users can develop custom drivers for backend services, and also manages software drivers for different service provider networks, thus offering multi-provider connectors.
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
Medical services; healthcare services; telehealth services; telemedicine services; virtual healthcare services; remotely delivered medical and healthcare services; medical and healthcare services delivered via video conferencing; medical and healthcare counseling; medical testing services; medical diagnostic services; physician services; nursing services
88.
METHODS OF IDENTIFYING AND TREATING INDIVIDUALS WITH ELEVATED CANCER RISK
Disclosed herein are methods of treating an individual at risk for incidence or recurrence of cancer in need thereof. Methods can include the steps of identifying an individual at risk for incidence or recurrence of cancer based on a risk stratification parameter; analyzing a biological sample from using a multi-cancer detection (MCD) test to yield an MCD test result; and based on the MCD test result and optionally the risk stratification parameter, administering a neoantigen immunogenic composition to the individual in need thereof. Methods can include the steps of sequencing and analyzing of the biological sample from the individual or a new biological sample from the individual to identify neoantigens to be included in the neoantigen immunogenic composition; and analyzing a second biological sample from the individual at risk for incidence or recurrence of cancer using a second multi-cancer detection (MCD) test to determine efficacy of the neoantigen immunogenic composition.
C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
C12Q 1/6881 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for tissue or cell typing, e.g. human leukocyte antigen [HLA] probes
89.
Networking Device That Bridges Virtual and Physical Computer Networks
Techniques are described for providing logical networking functionality for managed computer networks, such as for virtual computer networks provided on behalf of users or other entities. In some situations, a user may configure or otherwise specify a network topology for a virtual computer network, such as a logical network topology that separates multiple computing nodes of the virtual computer network into multiple logical sub-networks and/or that specifies one or more logical networking devices for the virtual computer network. After a network topology is specified for a virtual computer network, logical networking functionality corresponding to the network topology may be provided in various manners, such as without physically implementing the network topology for the virtual computer network. In some situations, the computing nodes may include virtual machine nodes hosted on one or more physical computing machines or systems, such as by or on behalf of one or more users.
H04L 41/0806 - Configuration setting for initial configuration or provisioning, e.g. plug-and-play
H04L 41/0893 - Assignment of logical groups to network elements
H04L 41/0895 - Configuration of virtualised networks or elements, e.g. virtualised network function or OpenFlow elements
H04L 41/12 - Discovery or management of network topologies
H04L 41/122 - Discovery or management of network topologies of virtualised topologies e.g. software-defined networks [SDN] or network function virtualisation [NFV]
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
H04L 45/00 - Routing or path finding of packets in data switching networks
Some aspects of the present disclosure relate to systems and methods for performing automated tasks using a robotic system in a human-centric environment. According to a first aspect of the present disclosure, hierarchical object identification is used to generate a contextual model of the environment around the robotic system. According to a second aspect of the present disclosure, a semantic understanding of a task is determined in response to a user query. According to a third aspect of the present disclosure, a task-specific controller is used in combination with a general locomotion controller to execute task or sub-task specific processes in connection with completing a query. One or more aspects of the present disclosure may be used in combination with each other and/or may be used with additional systems and processes for performing automated tasks in a human-centric environment.
Some aspects of the present disclosure relate to systems and methods for performing automated tasks using a robotic system in a human-centric environment. According to a first aspect of the present disclosure, hierarchical object identification is used to generate a contextual model of the environment around the robotic system. According to a second aspect of the present disclosure, a semantic understanding of a task is determined in response to a user query. According to a third aspect of the present disclosure, a task-specific controller is used in combination with a general locomotion controller to execute task or sub-task specific processes in connection with completing a query. One or more aspects of the present disclosure may be used in combination with each other and/or may be used with additional systems and processes for performing automated tasks in a human-centric environment.
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06F 16/587 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
92.
METHOD FOR SEQUENTIAL TASK MANAGEMENT AND VISUOMOTOR POLICY INTEGRATION IN DYNAMIC ENVIRONMENTS
Some aspects of the present disclosure relate to systems and methods for performing automated tasks using a robotic system in a human-centric environment. According to a first aspect of the present disclosure, hierarchical object identification is used to generate a contextual model of the environment around the robotic system. According to a second aspect of the present disclosure, a semantic understanding of a task is determined in response to a user query. According to a third aspect of the present disclosure, a task-specific controller is used in combination with a general locomotion controller to execute task or sub-task specific processes in connection with completing a query. One or more aspects of the present disclosure may be used in combination with each other and/or may be used with additional systems and processes for performing automated tasks in a human-centric environment.
Systems and methods are described for configuring sensor circuits in electronic devices. An example sensor circuit may comprise a sensor comprising at least one of an electromagnetic resonance layer, a touch panel layer, a receiver, or a transmitter. The example may comprise a transmitter wire coupled to the sensor. The transmitter wire may be formed to include, at least in part, a first bent portion. The example may comprise a receiver wire coupled to the sensor. The receiver wire may be formed to include, at least in part, a second bent portion. The first bent portion and the second bent portion may be disposed, at least in part, in a bending area adjacent an edge of the sensor. The example may comprise a sensor tail formed to include, at least in part, the transmitter wire and the receiver wire. The sensor tail may be coupled to a control circuit.
A multi-component application test framework tests components of an application out of order and without all components being ready for test. Descriptions for each component of an application are received and stored. Definitions for waypoints (code or test data substitutes for actual components net yet submitted) are received and stored. An endpoint lookup directory is initialized with waypoint endpoints for each component. A particular component is submitted for test and the test deployed. The particular component dynamically looks up endpoints for input/output dependencies for the particular component with other components and activates inactive waypoints acting as substitutes for components not-yet-submitted. The test completes, and for a passing test, the endpoint directory is updated to point to the particular component for other component dependencies instead of waypoints, effectively merging the particular component with others dependent on it. A similar process is repeated until all components are merged.
A data conformance service determines, based at least on an information model of a machine at a remote site of a client, cloud test code to be executed by the data conformance service to perform at least a first type of conformance test for data provided by the machine and edge test code to be executed by an edge gateway at the remote site to perform at least a second type of conformance test for the data from the machine. The service deploys the edge test code to the edge gateway. The service receives data from the machine and executes the cloud test code using the data to generate cloud test results. The service receives edge test results and generates, based on the cloud and edge results, an indication of whether the data from the machine conforms to a specification.
An update to a data set is received at a distributed database system. The data set is stored with or cached for accessing different partitions of a database. A new version identifier of the data set is written to indicate the update to the data set using a corresponding log record written to respective update logs of the different partitions of the database. The new version identifier is then used as part of subsequent validation operations for access requests to the database.
Devices and techniques are generally described for event-triggered multimodal enrichment and question generation in search. First event data may be received from an event stream. A first prompt for a first language model may be generated. The first prompt may include the first event data and a first request to generate at least a first question associated with the first event data. The first language model may generate the first question and a first answer to the first question based at least in part on the first prompt. A first entry for a search index may be generated. The first entry may include the first question as a key value and the first entry may associate the first question with the first answer.
Systems and methods are described relating to performing various operations on third party data, including sensitive information, in a secure computing environment and enforcing privacy controls on the resulting data and metrics thereof prior to outputting that data. In some aspects, an isolated computing/execution environment may obtain execution logic from a client device for generating result data based on input data and input data. The execution logic may be executed in the isolated execution environment using the input data to generate result data and performance metrics data relating to the execution logic. A set of privacy constraints may be enforced on the result data and the performance metrics data prior to causing the result data and the performance metrics data to be accessible by the client device.
A system may receive a request to generate an item listing for an item. The system may retrieve a content seed comprising item information associated with the item, and generate the item listing based in part on providing the content seed as input to a machine learning model to generate an internally consistent item listing in a single pass, such that the item listing is formatted according to an object format associated with a content platform. The system may store the item listing in a database associated with a commerce platform.
Techniques are generally described for item inpainting in images using a small number of reference images without 3D models. In various examples, a first selection of a first item may be received. In some further examples, a first set of weights learned for a generative latent representation model fine-tuned using at least one image of the first item may be determined. In some cases, first user-input image data representing a target environment may be received. In various examples, the generative latent representation model may generate, using the first set of weights, first output image data representing a representation of the first item within the target environment.
