Results of applying a set of voting rules to a target corpus of documents are used to obtain a set of derived probabilistic labels indicating the probabilities of the presence of a particular attribute within the documents' constituent objects. A machine learning model is trained to identify a candidate portion of a document from which a value of the attribute is to be extracted. The training data for the model includes learned representations obtained from paths of constituent objects, and the corresponding derived labels. A proposed value for the attribute, obtained based on an assigned attribute value presence probability score for an individual constituent object from a selected candidate portion of a document, is provided.
The disclosure describes techniques for configuring wireless routers of a wireless mesh network with one or more secondary wireless access points (WAPs) such that client devices connected to the mesh network may remain online in the event that a primary WAP goes offline or otherwise becomes unavailable. For instance, a user of the wireless mesh network may specify a device, such as a mobile electronic device connected to a cellular network, to operate as a secondary WAP in the event that a primary WAP becomes unavailable. Thereafter, upon a wireless router of the mesh network detecting that the primary WAP is unavailable, the wireless router may perform a network scan to identify SSID(s) that are available within the environment. The wireless router may also instruct the other routers of the mesh network to perform a network scan.
A machine learning service implements programmatic interfaces for a variety of operations on several entity types, such as data sources, statistics, feature processing recipes, models, and aliases. A first request to perform an operation on an instance of a particular entity type is received, and a first job corresponding to the requested operation is inserted in a job queue. Prior to the completion of the first job, a second request to perform another operation is received, where the second operation depends on a result of the operation represented by the first job. A second job, indicating a dependency on the first job, is stored in the job queue. The second job is initiated when the first job completes.
Disclosed herein are methods for classifying a cell present in a sample. such as a tumor, of a subject. comprising: sequencing bulk DNA from first and second (e.g., tumor and healthy) a subject's tissue samples; classifying somatic variants as first or second sample alleles; sequencing RNA from the cell; aligning each RNA sequence with the bulk DNA; classifying each RNA sequence as a first, a second, or an unknown allele sequence, depending on whether it substantially aligns with the first, the second sample allele, or cannot be determined; and identifying the cell as a first, a second, or an unknown cell, based on the classifying of each of the plurality of RNA sequences. Methods can comprise validating identification by allelic frequency of germ-line variants in the RNA sequences. The methods provide improved characterization of heterogenous cell populations, such as cell populations contaminated with cells from different sources, or tumor populations.
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
A system configured to perform user orientation estimation to determine a direction a user is facing using a deep neural network (DNN). As a directionality of human speech increases with frequency, the DNN may estimate the user orientation by comparing high-frequency components detected by each of the multiple devices. For example, a group of devices may individually generate feature data, which represents audio features and spatial information, and send the feature data to the other devices. Thus, each device in the group receives feature data generated by the other devices and processes this feature data using a DNN to determine an estimate of user orientation. In some examples, the DNN may also generate sound source localization (SSL) data and/or a confidence score associated with the user orientation estimate. A post-processing step may process the individual user orientation estimates generated by the individual devices and determine a final user orientation estimate.
Systems, methods, and computer-readable media are disclosed for capacitive touch sensing using system-in-package components and batteries. In one embodiment, a device may include a flexible printed circuit, a button cell electrically coupled to the flexible printed circuit, and a system-in-package that is electrically coupled to the flexible printed circuit. The system-in-package may include an electromagnetic interference shield, and a capacitive touch sensor. The capacitive touch sensor may be configured to detect a change in capacitance via a change in electric field at the electromagnetic interference shield.
A system to manage database queries including storage devices to implement a data store to store database data and computing devices to implement a query engine. The query engine is configured to receive, from a client, a database query and initiate performance of the query at the data store. The query engine is configured to compare a performance time of the query with a performance time threshold. Based on the performance time exceeding the performance time threshold: send a query identifier for the query and a token indicating that the query has not been completed; and receive, from the client, an additional query comprising the token and the query identifier. Based on a determination that the performance time does not exceed the performance time threshold, send a response to the query to the client, the response comprising data requested by the query.
Described technologies generate a data structure corresponding to values sequenced based on a plurality of timestamps associated with the values. The data structure can include a first section identifying a first timestamp associated with the plurality of timestamps and a number representing how many timestamps are associated with the plurality of timestamps, and a second section including at least a value linked to the first timestamp, and an additional value representing an encoding type associated with the second section. The data structure can be stored in computer-implemented storage.
An audio/video (A/V) device includes a first housing and a second housing rotatably coupled to the first housing. The first housing includes a camera oriented in a first direction, one or more microphones oriented in the first direction, one or more first lighting elements oriented in the first direction, one or more second lighting elements oriented in a second direction, one or more third lighting elements oriented in a third direction, and one or more first contacts. The second housing includes a loudspeaker oriented in a fourth direction and one or more second contacts configured to engage with the one or one first contacts. An engagement between the one or more first contacts and the one or more second contacts communicatively couples the loudspeaker to computing components with the first housing.
G08B 13/196 - Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
G01J 5/00 - Radiation pyrometry, e.g. infrared or optical thermometry
H02J 7/00 - Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
H04N 23/74 - Circuitry for compensating brightness variation in the scene by influencing the scene brightness using illuminating means
Techniques for session-based device grouping are described. In an example, a computer system receives first data requesting an output, determines a function to provide content data based at least in part on the first data, determines a session identifier of a session associated with execution of the function, and determines session data associated with the session identifier. The session data includes a first device identifier of a first device, an indication that the first device is outputting the content data, and a second device identifier of a second device. The computer system also causes, based at least in part on the session data including the second device identifier, the second device to output the content data.
Systems, methods, and computer-readable media are disclosed for modular robotic manipulation systems. In one embodiment, an example modular robot assembly may include a housing having a base, and a robotic manipulator coupled to the base, where the housing is configured to provide the robotic manipulator access to a first side, a second side, and a third side of the modular robot assembly. The module robot assembly may include a first camera system, a controller, and an optional display coupled to the housing. The modular robot assembly may be configured to be coupled to other modular robot assemblies, and the housing may be configured to be secured, such that the modular robot assembly can be independently transported.
B25J 9/08 - Programme-controlled manipulators characterised by modular constructions
B25J 13/06 - Control stands, e.g. consoles, switchboards
B25J 21/00 - Chambers provided with manipulation devices
B65G 47/91 - Devices for picking-up and depositing articles or materials incorporating pneumatic, e.g. suction, grippers
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
13.
Application programming interface to generate data key pairs
A computer-implemented method for providing cryptographic services, including providing key pairs. A key management service receives a web service application programming interface or other such request to generate a key pair. To respond to the request, the key management service obtains a pregenerated key pair that is securely stored and provides the key pair in response to the request.
H04L 9/06 - Arrangements for secret or secure communications; Network security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
14.
System for managing profile data for users in a facility
Users in a facility may move about and their authentication status may change accordingly. For example, upon entering a facility, a user may present identification data. At that point, the user is considered an authenticated user with persistent profile data. However, the identification of a user may not be presented at entry or may be unreliable, which causes the user to be considered an unauthenticated user with temporary profile data. In other scenarios, the identification of authenticated users may become unreliable based on their location or their proximity to other users. In cases where users are crowded at a location, the profile data for such users may be aggregated and may be based on common settings of the set of possible users in the group. A user interface may be presented to a user based on their designated profile data.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06Q 10/087 - Inventory or stock management, e.g. order filling, procurement or balancing against orders
G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions
G06V 40/70 - Multimodal biometrics, e.g. combining information from different biometric modalities
15.
Automated virtualized storage snapshotting responsive to ransomware detection
Techniques are described for monitoring and analyzing input/output (I/O) messages for patterns indicative of ransomware attacks affecting computer systems of a cloud provider, and for performing various remediation actions to mitigate data loss once a potential ransomware attack is detected. The monitoring of I/O activity for such patterns is performed at least in part by I/O proxy devices coupled to computer systems of a cloud provider network, where an I/O proxy device is interposed in the I/O path between guest operating systems running on a computer system and storage devices to which I/O messages are destined. An I/O proxy device can analyze I/O messages for patterns indicative of potential ransomware attacks by monitoring for anomalous I/O patterns which may, e.g., be indicative of a malicious process attempting to encrypt or otherwise render in accessible a significant portion of one or more storage volumes as part of a ransomware attack.
Techniques for personalized batch and streaming speech-to-text transcription of audio reduce the error rate of automatic speech recognition (ASR) systems in transcribing rare and out-of-vocabulary words. The techniques achieve personalization of connectionist temporal classification (CT) models by using adaptive boosting to perform biasing at the level of sub-words. In addition to boosting, the techniques encompass a phone alignment network to bias sub-word predictions towards rare long-tail words and out-of-vocabulary words. A technical benefit of the techniques is that the accuracy of speech-to-text transcription of rare and out-of-vocabulary words in a custom vocabulary by automatic speech recognition (ASR) system can be improved without having to train the ASR system on the custom vocabulary. Instead, the techniques allow the same ASR system trained on a base vocabulary to realize the accuracy improvements for different custom vocabularies spanning different domains.
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 15/30 - Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
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
17.
On-circuit utilization monitoring for a systolic array
On-circuit utilization monitoring may be performed for a systolic array. A current utilization measurement may be determined for processing elements of a systolic array and compared with a prior utilization measurement. Based on the comparison, a throttling recommendation may be provided to a management component to determine whether to perform the throttling recommendation.
G06F 11/34 - Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation
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
Devices and techniques are generally described for voice-based content attribution for speech processing applications. In some examples, a request for voice-based content may be received from a first speech processing skill. First identifier data associated with the first speech processing skill may be received. A determination may be made that first content that is associated with the request. Voice-based output data describing the first content may be generated. A selection of the first content may be received. Attribution data may be determined based at least in part on the selection of the first content and the first identifier data. The attribution data may be sent to a remote computing device.
A quantum computing service may use multiple quantum computers to execute a same quantum computing algorithm to improve the quantum computational accuracy. The quantum computing service may instruct individual ones of the multiple quantum computers to execute the quantum computing algorithm repeatedly for a number of times. The quantum computing service may obtain a plurality of results from the multiple quantum computers. The quantum computing service may aggregate the plurality of results to generate an ensemble result, and provide the ensemble result to a customer as a final result of the quantum computing algorithm.
Systems and methods are provided for handling file operations from a hosted computing instance via a secure compute layer. The secure compute layer is presented to the instance as a virtualized service device that is locally addressable by the instance. Software within the instance can submit file operations to the virtualized service device, which the secure compute layer can translate into calls to a network-accessible storage service. Results from the calls can then be passed back to the instance through the virtualized service device. As a result, the instance can communicate with a variety of different network services, without itself implementing network communications for those services.
Systems and methods are provided for generating a flat garment pattern and/or 3D mesh representation of a garment from one or more images depicting the garment laid flat or hung up. A system may obtain both a front image depicting a front view of a garment and a back image depicting a back view of the garment. A front and back silhouette of the garment may then be generated, which may include segmenting the garment depiction from background image content. A parametric representation of the garment may then be generated based on the front and back silhouettes, which may be implemented by iteratively optimizing, using differentiable rendering techniques, a garment representation within a parametric garment space previously learned for the particular garment type. A 3D mesh garment representation may then be generated based on the parametric representation, from which a flat sewing pattern may subsequently be generated if desired.
Techniques for detecting regressions with respect to the accuracy of an anomaly detection compute service in detecting anomalies in users' time series data. The techniques include providing an instrumented time series instrumented with a set of one or more anomalies to the anomaly detection service. The anomaly detection service detects a set of one or more anomalies in the instrumented time series. The precision and recall of the detected anomalies with respect to the instrumented anomalies is computed. From the computed precision and recall, an anomaly detection accuracy is computed as an F-score or F-measure. It is then determined whether a regression in anomaly detection accuracy has occurred by comparing the computed accuracy score to a threshold. If a regression has occurred, an alert can be generated or a recent change to the anomaly detection service can be rolled back.
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
G06F 11/32 - Monitoring with visual indication of the functioning of the machine
G06F 11/34 - Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation
This disclosure describes, in part, devices and methods for deactivating tags. For instance, an electronic device may include antennas that transmit signals and/or fields for deactivating the tags. In some examples, the electronic device includes a first gate that includes a first portion of the antennas and a second gate that includes a second portion of the antennas. To deactivate the tags, the electronic device may detect locations of an object relative to the electronic device. The electronic device may then activate a respective tag and/or a respective group of tags based on the location of the object. For example, the electronic device may activate a first tag and/or a first group of tags when the object is at a first location, activate a second tag and/or a second group of tags when the object is at a second location, and/or so forth.
Provided herein are techniques for enabling communications between an access point (AP) and a number of stations (STAs) while maximizing transmission quality and/or minimizing power consumption. For example, an STA may be associated with a camera device used to capture video data and transmit the video data to the AP, and the AP may be configured to receive a registration request from the STA, register the STA, receive video data from the STA, and transmit the video data to a backend system such as a storage server. In some cases, the AP and STAs may communicate using a communication bandwidth that is sub-GHz but has a higher bandwidth relative to the low-bandwidth sub-GHz communication protocols discussed above. An example of such a high-bandwidth sub-GHz communication protocol is one that supports data transmission (e.g., video data transmission) using a bandwidth of 900 megahertz (MHz).
H04B 1/38 - Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving
H04L 69/18 - Multiprotocol handlers, e.g. single devices capable of handling multiple protocols
H04N 17/00 - Diagnosis, testing or measuring for television systems or their details
26.
Scoring media program participants for predicting policy compliance
When creators generate media content in accordance with media programs, the media content is evaluated to identify any number of violations of policies, and to generate scores representing a level of risk that the creators will violate one or more of the policies in the future. Subsequently, media content of the creators is transmitted to listeners in accordance with the scores. In addition to audio data of creators or transcripts of the audio data, scores may be generated based on images associated with the creators, titles or summaries of media programs, or reports received from listeners. Scores calculated for creators may increase or decrease over time, depending on numbers of violations of policies by such creators, or other factors, and be utilized with a goal of protecting listeners against exposure to harmful content.
Techniques and systems can obtain a first private key usable with a classical cryptography algorithm and a second private key usable with a post-quantum cryptography algorithm based on classical and post-quantum public keys hosted by a computer-implemented storage of an online service provider. A plurality of keys to perform a cryptography operation on data hosted by the computer-implemented storage can be generated, the plurality of keys generated based on at least the first and second private keys and a cryptography derivation function identified in the computer-implemented storage. The plurality of keys can be used to perform the cryptography operation on the data hosted by the computer-implemented storage.
H04L 9/06 - Arrangements for secret or secure communications; Network security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
This disclosure describes techniques for updating planogram data associated with a facility. The planogram may indicate, for different shelves and other inventory locations within the facility, which items are on which shelves. For example, the planogram data may indicate that a particular item is located on a particular shelf. Therefore, when a system identifies that a user has taken an item from that shelf, the system may update a virtual cart of that user to indicate addition of the particular item. In some instances, however, a new item may be stocked on the example shelf instead of a previous item. The techniques described herein may use sensor data generated in the facility to identify this change and update the planogram data to indicate an association between the shelf and the new item.
A device including a mount, a first arm coupled to the mount, and a second arm coupled to the mount. The first arm includes first teeth and the second arm includes second teeth. A first light assembly rotationally couples to the first arm, and includes a first coupler that engages with the first teeth. A second light assembly rotationally couples to the second arm, and includes a second coupler that engages with the second teeth. A camera assembly pivotably couples to the mount, and includes a camera, a first passive infrared (PIR) sensor, and a second PIR sensor.
Systems and methods are described for execution of multiple tasks associated with a set of code in an on-demand network code execution system. A user may provide a set of code that is associated with the multiple tasks. The system may generate a first virtual machine instance for execution of a first task. The system may determine that a second task is associated with the first task and may identify a location of the first virtual machine instance. The system may further identify a second virtual machine instance for execution of the second task based on the location of the first virtual machine instance. For example, the system may identify the first virtual machine instance from a plurality of pre-generated virtual machine instances and/or may generate the first virtual machine instance.
Methods, systems, and computer-readable media for interactive command generation for natural language input are disclosed. A natural language dialog system receives a natural language input for a dialog with a user. The system determines a state representation of the dialog based at least in part on the natural language input. The state representation indicates an operation offered by a service. The system generates a natural language output based at least in part on the natural language input. The natural language output solicits an additional natural language input for the dialog. The system determines an updated state representation of the dialog based at least in part on the additional natural language input and the state representation. The updated state representation indicates parameter value(s) for the operation. Based at least in part on the updated state representation, the system generates a command invoking the operation with the parameter value(s).
An input/output (I/O) device can initiate data migration of a virtual machine (VM) instance from a source device to a target device. The data migration of the VM instance may include migrating the data for the VM instance and tag data associated with the data. The data for the VM instance and the tag data may be stored together in a source memory. A first read request from the I/O device can enable a memory controller in the source device to read the data for the VM instance and the tag data together, store the tag data in a tag data buffer, and transmit the data for the VM instance to the target device. A second read request from the I/O device can read the stored tag data from the tag data buffer and transmit to the target device. The target device can write the data for the VM instance together with the tag data in the target memory.
Systems and methods to generate synthetic lip synchronization may generate source facial keypoints based on a source video, generate target facial keypoints based on a target audio, determine distances between the source facial keypoints and target facial keypoints, and transform or warp the source facial keypoints and associated surfaces to the target facial keypoints. In this manner, target video having synthetic lip synchronization that matches the target audio may be generated, and the target video may substantially preserve or maintain surface textures or features from the source video in the target video, thereby generating natural and believable synthetic lip synchronization corresponding to the target audio.
Hyperparameters for tuning a machine learning system may be optimized using Bayesian optimization with constraints. The hyperparameter optimization may be performed for a received training set and received constraints. Respective probabilistic models for the machine learning system and constraint functions may be initialized, then hyperparameter optimization may include iteratively identifying respective values for hyperparameters using analysis of the respective models performed using an acquisition function implementing entropy search on the respective models, training the machine learning system using the identified values to determine measures of accuracy and constraint metrics, and updating the respective models using the determined measures.
A host device may include an interconnect, a host memory, and a set of processor cores. A processor core may execute a VM assigned to a cryptographic key and may send a request to access a physical address in the host memory toward the interconnect. An enforcer device may receive the request and extract a key identifier from the request. The enforcer device may determine whether to allow the request to access the physical address via the interconnect based on the key identifier and a list of allowed keys stored on the enforcer device. If the enforcer device determines to not allow the request to access, the enforcer device may modify the physical address and/or the key identifier of the request.
G06F 9/455 - Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 21/72 - Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer to assure secure computing or processing of information in cryptographic circuits
A computer network organized in a logical grid having rows and columns can include network nodes coupled according to harmonics. Each network node can be coupled to network nodes of the same row using a set of horizontal strands according to a set of horizontal harmonics. Each of the horizontal harmonics specifies a node distance along the row between adjacent connection points on the corresponding horizontal strand. Each network node can also be coupled to network nodes of the same column using a set of vertical strands according to a set of vertical harmonics. Each of the vertical harmonics specifies a node distance along the column between adjacent connection points on the corresponding vertical strand.
A network device operating as a network node in a network fabric has a set of connection ports to provide a bandwidth capacity for the network device. The connection ports include fabric ports to connect with respective strands using multipoint optical connections. Each strand can connect network nodes of the network fabric according to a harmonic specifying a node distance between adjacent connection points on the strand. The connection ports also include server ports to connect with servers and/or external networks. The network device also includes processing logic to distribute traffic for a destination node to network nodes along corresponding strands of the fabric ports.
Voice customization is an application of voice synthesis that involves synthesizing speech having certain voice characteristics, and/or modifying the voice characteristics of human speech. Certain techniques for voice customization may be used in conjunction with compressing speech for storage and/or transmission. For example, speech may be received at a first device and transformed into a latent representation and/or compressed for storage and/or transmission to a second device. The system may use normalizing flows to transform the source audio to a latent representation having a desired variable distribution, and to transform the latent representation back into audio data. A flow model may be conditioned using first speech attributes when transforming the source audio, and an inverse flow model may use second speech attributes when transforming the latent representation back into audio data. The first and/or second speech attributes may be modified to alter voice characteristics of the transmitted speech.
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
40.
SOUND SOURCE LOCALIZATION USING ACOUSTIC WAVE DECOMPOSITION
Disclosed are techniques for an improved method for performing sound source localization (SSL) to determine a direction of arrival of an audible sound using a combination of timing information and amplitude information. For example, a device may decompose an observed sound field into directional components, then estimate a time-delay likelihood value and an energy-based likelihood value for each of the directional components. Using a combination of these likelihood values, the device can determine the direction of arrival corresponding to a maximum likelihood value. In some examples, the device may perform Acoustic Wave Decomposition processing to determine the directional components. In order to reduce a processing consumption associated with performing AWD processing, the device splits this process into two phases: a search phase that selects a subset of a device dictionary to reduce a complexity, and a decomposition phase that solves an optimization problem using the subset of the device dictionary.
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 virtual network verification service for provider networks that leverages a declarative logic programming language to allow clients to pose queries about their virtual networks as constraint problems; the queries may be resolved using a constraint solver engine. Semantics and logic for networking primitives of virtual networks in the provider network environment may be encoded as a set of rules according to the logic programming language; networking security standards and/or client-defined rules may also be encoded in the rules. A description of a virtual network may be obtained and encoded. A constraint problem expressed by a query may then be resolved for the encoded description according to the encoded rules using the constraint solver engine; the results may be provided to the client.
H04L 41/50 - Network service management, e.g. ensuring proper service fulfilment according to agreements
H04L 43/0811 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking connectivity
H04L 67/02 - Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
42.
CONVERTING NATURAL LANGUAGE QUERIES TO SQL QUERIES USING ONTOLOGICAL CODES AND PLACEHOLDERS
An NLQ-SQLQ tool or service of a provider network may receive a natural language query (NLQ) from a client and convert the NLQ to an SQL query using ontological codes and placeholders. For one or more portions of the NLQ, the tool/service determines that the portion is associated with one or more codes of an ontology. The tool/service then assigns, based on criteria, a particular code to the portion. The tool/service replaces portions of the NLQ with different argument placeholders to generate a modified NLQ. A trained model converts the modified NLQ into an initial SQL query that has argument placeholders and subquery placeholders. The tool/service generates a final SQL query based on the initial SQL query, predefined SQL subquery templates associated with the subquery placeholders, and codes associated with the argument placeholders. The tool/service executes the final SQL query and sends results to the client.
A system for storing data includes a rack, one or more data storage modules coupled to the rack, and one or more data control modules coupled to the rack. The data storage modules may include a chassis, two or more backplanes coupled to the chassis, and one or more mass storage devices (for example, hard disk drives) coupled to the backplanes. The data control modules may access the mass storage devices in the data storage modules.
A system for providing a geofence service is disclosed. The geofence service receives an encrypted geospatial index for a specified geofence based on application of a hash function to respective ones of a plurality of locations for the specified geofence in accordance with a secret key that is unknown to the geofence service. The geofence service stores the encrypted geospatial index to a data store according to a geofence identifier for the specified geofence. The geofence service receives an encrypted device location identifier generated based on application of the hash function to a representation of a current location of a user device in accordance with the secret key. The geofence service determines whether the user device is located in a location of the plurality of locations based on a query of the encrypted geospatial index according to the encrypted device location identifier.
H04W 4/021 - Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
H04W 12/037 - Protecting confidentiality, e.g. by encryption of the control plane, e.g. signalling traffic
H04W 12/0431 - Key distribution or pre-distribution; Key agreement
Techniques for graduated navigation displayed on an electronic device used in servicing items for users are described herein. For example, the electronic device can receive a first set of directions for moving towards a first geolocation associated with a service address using a first navigation method for presentation. The electronic device can transition from the first set of directions to a second set of directions in response to detecting a transition trigger associated with a second geolocation. The transition can involve ceasing providing the first set of directions for presentation. The transition can also involve providing the second set of directions for moving from the second geolocation towards the service address using a second navigation for presentation.
This disclosure describes a system for associating multiple totes with a single profile so that items placed into any of the multiple totes are identified on a profile item identifier list. For example, if two users located in a materials handling facility are picking items that are to be consolidated or otherwise treated together, each user may select a different tote and move separately through the materials handling facility. As either user picks items and places those items into a corresponding tote, a profile item identifier list is updated to include an item identifier for each picked item.
B65G 1/137 - Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
G05B 15/02 - Systems controlled by a computer electric
G06K 17/00 - Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups , e.g. automatic card files incorporating conveying and reading operations
G06Q 10/087 - Inventory or stock management, e.g. order filling, procurement or balancing against orders
A fiber optic connector can include a connector body with a connector channel extending therethrough. A ferrule can be positioned in a first end of the connector channel and a hollow core fiber can be positioned in a second end of the connector channel. A lens can be positioned in the connector channel between the ferrule and the hollow core fiber. The lens can direct light emitted from the hollow core fiber to an optical fiber within the ferrule.
Systems and methods are described relating to aggregating log anomalies. In some examples, a plurality of log anomaly instances may be obtained, from a log anomaly detector, where individual instances are associated with a first log anomaly type and a first anomalous log event. Log anomaly instances associated with the first log anomaly type and the first anomalous log event may be combined into a first log anomaly class. The first log anomaly class may be combined with a second log anomaly class, including log anomaly instances associated with the first anomalous log event and a second log anomaly type, into a log anomaly group, which may correlate the occurrences of the first and second anomaly types to the same first anomalous log event over a period of time. An indication of the log anomaly group may then be output.
Systems and methods are provided to improve system performance when multiple transaction retry events associated with transaction requests from requester nodes to completer nodes are detected. A retry monitor can monitor the transaction retry events associated with the transaction requests to provide retry information. An intervention level generator can receive information about the transaction retry events and determine an intervention level from a plurality of intervention levels based on the retry information and a retry configuration. Each requester node can be coupled to a regulator to regulate the transactions being requested by that requester node based on the intervention level and a regulator configuration, which can allow the corresponding completer nodes to complete the outstanding transactions and reduce the occurrence of retry events.
Automatic partitioning of a machine learning model may be performed for training across multiple processing devices. A training job for a machine learning model may specify a number of partitions for a machine learning model. An optimization parameter may be determined for the machine learning model. Different partitions of the machine learning model to be trained across multiple processing devices may be determined based on the specified number of partitions and the optimization parameter. A schedule for executing the training job may be generated according to the respective partitions of the machine learning model. The training job may be executed according to the schedule.
The present disclosure presents a generative model configured to receive input regarding an item in two different modalities, such as text data and non-text data (including, for example, image or audio data), in order to generate output regarding the item that is determined based on a combination of both modalities' input. Specific relative positional and token type embeddings may be employed in an encoder portion of an encoder-decoder arrangement. An associated decoder may be trained to generate new text corresponding to diverse tasks based on the encoded representation of the two inputs as generated within the encoder. For example, the decoder may be utilized to generate attributes regarding the input item, auto-complete or auto-correct a title or description of the item, among other uses.
Generally described, one or more aspects of the present application relate to prefetching container image layers for use in a cluster of compute instances. For example, the dependencies among the individual layers within the container images stored and/or executed on a cloud provider network may be analyzed. Then, the layers that are likely to be used by a user of the cloud provider network may be identified and prefetched into the caches of the compute instances provided by the cloud provider network, before execution of the container images including such layers is requested by the user. By doing so, the latency between the time a request to execute a set of container images is received and the time the execution of the set of container images is actually initiated can be reduced, thereby providing an improved and more efficient application execution experience to the user.
Systems and methods are disclosed to update ads on user devices that may connect to a network only intermittently by predicting and tracking various metrics associated with ads delivered to the user devices. An example method may include determining a first set of ads that were presented at a first semi-connected device while the first semi-connected device was disconnected from a network, determining a first device identifier associated with the first semi-connected device, and determining, based at least in part on the first device identifier, a first estimated number of ad impressions for a first ad. Example methods may include determining, based at least in part on the first estimated number of ad impressions, that the first semi-connected device is to be updated with the first ad, causing the first ad to be sent to the first semi-connected device, and causing at least one ad of the first set of ads to be removed from the first semi-connected device.
This disclosure is directed to, in part, a processing pipeline for detecting predefined activity using image data, identifying an item-of-interest and a location of the item-of-interest across frames of the image data, determining a trajectory of the item-of-interest, and determining an identifier of the item-of-interest and an action taken with respect to the item-of-interest. The processing pipeline may utilize one or more trained classifiers and, in some instances, additional data to identify items that are placed into or removed from a tote (e.g., basket, cart, or other receptacle) by users in material handling facilities as the users move around the material handling facilities.
Techniques and methods are disclosed for detecting long-form audio content in one or more audio files. A computing system receives first audio data corresponding to a first version of an audio file and second audio data corresponding to a second version of the audio file. The computing system generates a first transcript of the first audio data and a second transcript of the second audio data. The computing system compares the first audio data and the second audio data and the first transcript and the second transcript to identify advertisement portions and content portions of the audio data. Using a semantic model based on a machine learning (ML) transformer, the computing system can determine advertisement segments within the advertisement portions, the advertisement segments corresponding to separate advertisements. Information corresponding to the duration and location of the advertisement segments is stored in a data store of the computing system.
Systems and methods for preemptive wakeword detection are disclosed. For example, a first part of a wakeword is detected from audio data representing a user utterance. When this occurs, on-device speech processing is initiated prior to when the entire wakeword is detected. When the entire wakeword is detected, results from the on-device speech processing and/or the audio data is sent to a speech processing system to determine a responsive action to be performed by the device. When the entire wakeword is not detected, on-device processing is canceled and the device refrains from sending the audio data to the speech processing system.
Devices and techniques are generally described for nearest device arbitration. In various examples, a first device may receive first audio data representing a wakeword spoken by a first speaker at a first time. In some examples, a second device may receive second audio data representing the wakeword spoken by the first speaker at the first time. In some cases, the first device may generate first feature data representing the first audio data and the second device may generate second feature data representing the second audio data. In various examples, a machine learning model may use the first feature data and the second feature data to generate first prediction data representing a prediction that the first device is closer to the first speaker than the second device.
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 15/28 - Constructional details of speech recognition systems
G10L 25/21 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being power information
G10L 25/84 - Detection of presence or absence of voice signals for discriminating voice from noise
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 system configured to perform audio processing with adaptive multi-stage output gains. For example, an Audio Front End (AFE) component may generate a first output using a fixed gain value in order to improve device arbitration and a second output using an adaptive gain value in order to improve wakeword detection. A wakeword engine may process the second output to determine that a wakeword is present along with start/end times of the wakeword. The AFE component can use the start/end times to determine an amount of wakeword energy represented in the first output, which is sent to a remote device for device arbitration. The AFE component can also use the start/end times to determine an amount of wakeword energy represented in the second output, which can be used to determine the adaptive gain value that is unique to the device.
G10L 25/21 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being power information
Methods, systems, and computer-readable media for delivery of log records to stateless clients are disclosed. A record delivery system receives, from a client, a first request to read from a persistent log comprising an ordered sequence of records. The first request is associated with a receiver session. The system sends a first set of records to the client and stores a data structure indicating that the first set of records was sent to the client in the receiver session. The system receives, from the client, a second request to read from the persistent log in the receiver session. Based at least in part on the data structure, the system determines a second set of one or more records in the persistent log. The system sends the second set of records to the client.
A technology is described for device communication with computing regions. An example method may include receiving at a first computing region a request for a computing resource. In response to receiving the request, a device associated with the request may be authenticated using authentication credentials for the device. An identity token that indicates permission for the device to access the computing resource in a second computing region may be generated and the identity token and instructions to connect to the second computing region may be provided to the device. The device may present the identity token to the second computing region in order to access the computing resource in the second computing region.
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
G06F 21/34 - User authentication involving the use of external additional devices, e.g. dongles or smart cards
Systems and methods in provide approaches for channel fitting to determine a particular number of resources, such as cores, that may be used for one or more processing jobs for a particular input channel. A given channel may be evaluated to determine performance affecting parameters and those parameters may be evaluated against previously known hardware configurations or against a historical heuristic dataset. A configuration for the channel may be selected where particular cores of a set of resources are assigned to the channel to perform one or more operations, such as transcoding operations. As a result, empirically determined or historical data may be used to efficiently allocate resources for different transcoding operations to provide both predictable performance and high utilization.
H04N 19/40 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video transcoding, i.e. partial or full decoding of a coded input stream followed by re-encoding of the decoded output stream
H04N 21/218 - Source of audio or video content, e.g. local disk arrays
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating MPEG-4 scene graphs
A wearable audio output device (e.g., headphones) having an open design that allows ambient noise to pass to a listener without physically isolating the listener from a surrounding environment. The device may include an open earcup design that may partially or completely surround the listener's ear, and in some examples a portion of the listener's head may be uncovered by the open earcup. To improve comfort, the device includes a floating audio component configured to generate output audio in a direction of the listener's ear without contacting the listener's ear. To reduce an amount of ambient noise, the device may be configured to perform active noise cancellation (ANC) processing using feedforward and/or feedback microphones. The device may include an acoustic structure configured to direct the output audio in the direction of the listener's ear and/or position the feedback microphone(s) closer to the listener's ear.
G10K 11/178 - Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
Single use cartridges for testing biological samples are provided that include multiple processing channels. A single use cartridge includes an aliquot staging well, a first amplification well, a second amplification well, an actuation port, and a fluid channel control valve assembly. The fluid channel control valve assembly is reconfigurable between a first fluid channel configuration and a second fluid channel configuration.
Integrated cooling structures and methods may comprise a motor, a propeller, and a component having at least one structural feature configured to receive or channel airflow to generate a positive pressure region at a first end of the motor. During operation of the motor and propeller, a negative pressure region may be generated at a second end of the motor proximate the propeller. The positive and negative pressure regions may generate a pressure differential or gradient between ends of the motor, such that a cooling airflow may be generated that flows through an interior of the motor from the positive pressure region to the negative pressure region. The cooling airflow may increase cooling of internal components of the motor, and consequently improve various operational capabilities, performance, and reliability of the motor and associated vehicle, machine, or system.
Systems and methods are disclosed for seamless disengagement of shuttles powered by electromagnets. An example system may include a frame coupled to a track, a first conveyor disposed along the first side of the track, a second conveyor disposed along the second side of the track, and an actuator configured to drive the first conveyor and the second conveyor, where the first conveyor and the second conveyor are configured to engage a first bar disposed on a lower surface of the shuttle. The system may be configured to (i) move the shuttle from a first location along the track to a second location along the track, and (ii) pause movement of the shuttle between the first location and the second location.
An electronic device includes a first passive infrared (PIR) sensor and a second PIR sensor positive vertically below the first PIR sensor. One or more lenses are shaped and positioned to focus light received at the one or more lenses onto the first PIR sensor and the second PIR sensor. The first PIR sensor has a first field of view (FoV), and the second PIR sensor has a second FoV that is vertically and horizontally offset from the first FoV.
Systems and methods provide for submission, verification, and validation of one or more code packages associated with provisioning logic for third-party applications. A user may request verification as a publisher and submit a code package for use with a third-party application within a resource provider environment. The code package may be tested and, upon passing, be published to a public repository for discovery and use by other users. The code package may form part of an extension that is integrated into a template that enables automated provisioning of resources and applications.
Techniques for distributing data associated with the weight values of a neural network model are described. The techniques can include performing computations associated with the neural network model in a neural network accelerator to generate data associated with weights of the neural network model. A multicast request packet is then generated to distribute the data. The multicast request packet may contain the data associated with the weights, and an address in a multicast address range of a peripheral bus multicast switch. The multicast request packet is sent to a port of the peripheral bus multicast switch, and in response, the peripheral bus multicast switch generates multiple packets containing the data from the multicast request packet and forwards them to multiple peripheral bus ports corresponding to other processing nodes of the system.
A system responds to a request to enable a restoration capability for a first database instance of a first operating environment. The system stores, in the first operating environment, transaction data for the first database instance and data indicative of aspects of the configuration of the first operating environment on which the first database instance is dependent. The transaction data and configuration data are replicated to a second environment. In response to a request to restore the first database instance, a second operating environment is configured according to the replicated configuration data, and the data is restored to a second database instance, in the second operating environment, based on the replicated transaction data.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
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
Described herein is a computer-implemented method for extracting and identifying an audio song. An audio file can be accessed by a computing device. A set of audio categories and a set of probabilities associated with the set of audio categories can be determined for a first audio clip. A subset of the set of audio categories can be determined based on a subset of the set of probabilities. Each audio category of the subset of the set of audio categories can correspond to an audio class label. Whether the first audio clip is part of a song can be determined. The song can be defined by combining the first audio clip with other audio clips.
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
G10L 25/57 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for processing of video signals
Described herein are approaches for generating a new queue based on an existing queue. This may include receiving a request to transfer the existing queue from a first device to a second device. A set of move criteria may be evaluated using a playback context, a user profile, a configuration associated with the second device, and/or a level of access constraints. Depending on the results of the evaluation, the existing queue may be completely reformulated to define the new queue. The second device may then be instructed to play the new queue.
Systems and methods are disclosed for harvesting electrical energy from mechanical components of hard disk drives (HDDs) in a data storage system and propagating the electrical energy to devices outside of the HDDs. A power distribution board (PDB) may be coupled to a plurality of HDDs and used to detect a voltage drop on a connection between the PDB and the HDDs indicative of a power loss condition, and, in response, enable the flow of electrical energy from the HDDs to the PDB. The electrical energy from the HDDs may be converted for use by the PDB and/or distribution to other components of the data storage system.
A machine learning model analyzes text describing an item to determine portions of the text that correspond to multiple characteristics of the item. A first set of embeddings that represent the text describing the item is determined. A second set of embeddings that represent text indicating the characteristics is determined. The second set of embeddings includes a token for each characteristic that is used to indicate tokens that are associated with a particular characteristic. The first set of embeddings and portions of the second set of embeddings for a particular characteristic are used to determine a set of interaction embeddings for each characteristic by determining an element-wise product. These interaction embeddings are analyzed to determine label predictions indicating text that is associated with each characteristic. Text for multiple characteristics may therefore be identified using a single pass rather than multiple passes.
Techniques for filtering the output of supplemental content are described. When a supplemental output system (e.g., a supplemental content system or notification system) receives supplemental content for output, the supplemental output system sends a user identifier (of the recipient user) and the supplemental content to separately implemented filtering component. The filtering component uses a machine learning (ML) model to determine a topic of the supplemental content. The filtering component determines whether the supplemental content should not be output based on the ML model-determined topic, one or more guardrail policies of the supplemental output system, and user frustration data regarding previously output supplemental content. Use of the ML model to determine the topic prevents a content publisher from surreptitiously associating supplemental content with a specific topic in an effort to bypass topic-based output guardrails.
Session-specific edit recommendations may be made for editing a code file. After a code editing session is started, code file edits may be captured. A machine learning technique may be applied to learn the code edits and recommend alternative code portions for portions of the code file during the code editing session. The recommendations may be provided and accepted, or not, via an interface of a code editor application.
Enhanced training data representative of possible inputs is used to train a machine learning system. For example, a machine learning system to determine identity based on an image of a human palm may be trained using enhanced training data comprising images. The enhanced training data may comprise source images that have been modified to appear to depict synthetic artifacts that attempt to simulate human palms, augmented images of dirty hands, and so forth. A synthetic artifact image may be produced by selectively removing some data from a source image. An augmented image may be produced by selectively blending the source image with features extracted from sample images. These images may then be used as training data to train the machine learning system.
G06V 10/24 - Aligning, centring, orientation detection or correction of the image
G06V 10/77 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
G06V 10/774 - Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
A monitoring service analyzes client-based monitoring data in correlation with network-based monitoring data for paths between two endpoints in a network upon request from a client. The endpoint can be any valid private IP address or DNS name where traffic is to be sent. Clients may define parameters for the monitoring, including thresholds for identifying network issues based on the client-based monitoring data. Different levels of network-based monitoring may be performed responsive to results of the correlation and continued performance determinations relative to the thresholds. The client-based and network-based monitoring data may include reports of performance signals, such as packet loss and round-trip time or other measured latency, as well as events such as connection issues and timeouts. The monitoring data from the different sources can be compared to determine whether a network issue is present in the network or outside of the network/in the client.
H04L 43/0811 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking connectivity
Techniques for anomaly and causality detection are described. An example includes receiving time series data; performing anomaly detection on the received time series data to detect at least one anomaly using an anomaly detection model; detecting a causal relationship between measures, wherein a set of measures are related when a first of the set of measures has a causal influence on a second of the set of measures, wherein a single time series is a metric and a measure is a numerical or categorical quantity a metric describes; and outputting a result of the anomaly and causality relationship detections.
Systems and methods for activity-based device recommendations are disclosed. For example, historical usage data associated with a device may indicate that the device is likely to be associated with a given state at a given time. When the device is not in the anticipated state, a recommendation to transition the device state, for example, may be sent. Additionally, a determination of the activity state associated with the device, such as an active state, an asleep state, and/or an away state may be utilized to determine the recommendation to surface, to determine whether to send a recommendation, and when and/or how to send the recommendation.
G05B 19/42 - Recording and playback systems, i.e. in which the programme is recorded from a cycle of operations, e.g. the cycle of operations being manually controlled, after which this record is played back on the same machine
G05B 19/042 - Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
G06F 1/3296 - Power saving characterised by the action undertaken by lowering the supply or operating voltage
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
80.
Request cost index for throttling requests to execute operations in a multi-tenant provider network
Techniques for calculating and using a request cost index for throttling application programming interface (API) requests to execute operations in a provider network. The techniques encompass the step receiving a request to execute an operation at an API service in the provider network. Further steps include determining to execute the operation based on a request rate limiting algorithm, executing the operation to yield an operation result, and sending the operation result. Additional steps include calculating a request cost index that reflects an amount of computing resources utilized by executing the operation, determining an adjustment amount for a state variable of the request rate limiting algorithm based on the calculated request cost index, and adjusting (e.g., lowering) the state variable by the adjustment amount. Other (e.g., subsequent) requests to execute queries received at the API service that are metered by the state variable can be throttled by the API service.
Portions of text data generated from inverse text normalization may be redacted. Text data for redaction may be obtained. One or more inverse text normalization models may be applied to the text data to generate normalized text data. A machine learning model, trained to recognize text for redaction, may be applied to identify portions of the normalized text data for redaction. The identified portions may be redacted and the redacted normalized text provided to a destination.
A compiler-implemented technique for performing a storage allocation is described. Computer code to be converted into machine instructions for execution on an integrated circuit device is received. The integrated circuit device includes a memory having a set of memory locations. Based on the computer code, a set of values that are to be stored on the integrated circuit device are determined. An interference graph that includes the set of values and a set of interferences is constructed. While traversing the interference graph, a set of memory location assignments are generated by assigning the set of values to the set of memory locations in accordance with one or more color selection schemes.
Described are systems and methods for providing fault tolerant drivers for electric motors. Embodiments of the present disclosure may provide a single power electronics unit and/or ESC that is configured to drive more than one electric motor. According to exemplary embodiments, each power electronics unit and/or ESC may be connected to more than one electric motor (e.g., three electric motors, etc.) and each power electronics unit and/or ESC may be configured to drive and/or control a single phase of multiple electric motors. This can facilitate two-phase mode operation in the event of a faulty power electronics unit and/or ESC, thereby facilitating continued operation of the affected electric motors. Exemplary embodiments of the present disclosure can also provide alternate modes of operation for the electric motors that are operating in two-phase mode to mitigate thermal stresses that may be experienced by the power electronics and/or the electric motors during two-phase operation.
H02P 29/028 - Detecting a fault condition, e.g. short circuit, locked rotor, open circuit or loss of load the motor continuing operation despite the fault condition, e.g. eliminating, compensating for or remedying the fault
H02K 11/33 - Drive circuits, e.g. power electronics
84.
Decomposition of monoliths into multi-account provider network structures
Remapping mainframe functional components from a mainframe computing environment onto a network of distinct but communicating accounts of a provider network. The mainframe computer (or network of such computers) is analyzed hierarchically through one or more of physical separation between logical partitions (LPARs), LPARs within the mainframe computer(s), separation of batch and transactional workloads, separation of batch and transactional accounts, or security of the mainframe architecture. Mainframe application artifacts obtained through the analyzing are used to generate a graph model representing relationships among the mainframe application artifacts. The graph model includes nodes representing the mainframe application artifacts and edges connecting pairs of the mainframe application artifacts, where the edges represent use relationships between the pairs of mainframe application artifacts. The nodes are then clustered, where the clusters represent sets of mainframe artifacts having high density of use relationships, and the clusters correspond to the distinct accounts in the provider network.
It is determined that a workflow comprising inter-resource requests of a distributed application is to be initiated. In response to detecting, at a first resource during execution of the workflow, that a triggering condition for retrying a request is met, and that a workflow-level retry budget of the workflow indicates that a retry is permitted, the retry is attempted and the budget is modified to indicate that the retry has been attempted. In response to detecting, at another resource, that a triggering condition for retrying another request is met, and that the workflow-level retry budget of the workflow indicates that a retry is not permitted, an indication that the workflow has failed is generated.
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
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
Systems and techniques for power delivery to an electronic device using multiple power management integrated circuits (PMICs) are described herein. The systems and techniques provide for two signal connections between each of the PMICs to sync transition signals on a first line and provide faults to interrupt operations on a second line. The PMICs are connected to an electronic device that commands power transitions for voltage rails from the PMICs with the commands received over I2C communication from the electronic device.
A system, technique, or computer program product generates a simplified version of a geometry, based on a target number of points to be included in the output. A first plurality of points, representative of a geometry, is received. The simplified version of the geometry is generated by, at least, expanding a segment of a simplified version of the geometry. The segment is identified for expanding by determining that a point associated with the segment is at a distance from the segment that exceeds a tolerance value, and is includable in the simplified version of the geometry without causing the simplified version of the geometry to exceed the target size.
Different types of index structures are used for a replica group of a database. A leader node of a replica group performs receives updates to a copy of the database using a first type of index structure. A follower node performs updates received from the leader node as a log of updates to a copy of the database in an external storage system when a size of the received updates exceeds a threshold. The follower node performs requests to read data from the database using the copy in the external storage.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
G06F 16/22 - Indexing; Data structures therefor; Storage structures
A system configured to perform content identification using fingerprinting to recognize known media content. The system may generate a reference database including reference fingerprints for each media content item to include in the content identification. In addition, the system may generate a hash table that associates individual frames of the reference fingerprints with identification information for corresponding media content items. When a device is playing media content, the system may perform content identification by generating query fingerprints representing the media content and comparing the query fingerprints to the reference database. For example, the system may match a query fingerprint to a reference fingerprint by identifying which of the reference fingerprints shares the most frames with the query fingerprint using the hash table. In addition, the system may use additional decision criteria to confirm a match, such as fine-grain matching or tracking successive fingerprints over time.
A virtual machine controller service of a service provider network may provide a virtual machine controller environment where applications associated with machine controllers (e.g., programmable logic controllers (PLCs), programmable automation controllers (PACs), etc.) can execute and data can be provided as input to the executing applications. An example process may include receiving a request to create a virtual controller instance, and creating the virtual controller instance in a service provider network based at least in part on the request. The example process may further include executing, on the virtual controller instance, an application that is associated with a machine controller that is operable within a facility, and sending data as input to the application to elicit a response from the application. This example process can be used for training personnel and/or for validating machine controller applications prior to their deployment on a physical machine controller in a facility.
A computing system may detect that a service, which receives a plurality of task requests associated with clients or profiles, is under duress based on performance information associated with the service. The computing system, responsive to detecting that the service is under duress, may successively, until the service is detected to not be under duress, select a profile based on a respective volume of requests associated with the profile, apply a task request limit to the profile, and detect whether the service is still under duress.
A camera device may capture a high-resolution image of a frame and store the high-resolution image in memory. The camera device may down-sample the high-resolution image to a low-resolution image of the frame. The camera device may transmit, to an external compute node, the low-resolution image. The camera device may receive, from the external compute node, a request for a region of interest from the high-resolution image. The camera device may transmit, to the external compute node, the region of interest from the high-resolution image. The camera device may have a captured frame rate at which high-resolution images are captured. The camera device may also have an external frame rate based upon which all, or only some, of the high-resolution images may be down-sampled to low-resolution images that are transmitted to the external compute node. The external frame rate may be decoupled from the captured frame rate.
G06K 7/14 - Methods or arrangements for sensing record carriers by corpuscular radiation using light without selection of wavelength, e.g. sensing reflected white light
Machine learning models may be generated that are compatible with another machine learning model and satisfy a resource constraint. Techniques that ensure weight compatibility and architectural compatibility between a machine learning model being created to be compatible with another machine learning model are applied. The resource constraint is enforced so that the generated machine learning model also fits within the resource constraint.
To improve performance of a computational array, the architecture of the array can be modified to allow the processing engines of a column to operate in parallel and the clock frequency of the array to be increased. The processing engines of each column of the array can be grouped into a series of row groups. The processing engines of each row group can be loaded with input values, and computations on the input values can be carried out in parallel to generate the column output. One or more flip-flop stages can be inserted into the computational logic of each of the processing engines. The computational logic can then be distributed across the flip-flop stages to reduce the propagation delay between flip-flop stages of the processing engine, hence allowing the clock frequency of the array to be increased.
G06N 3/063 - Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
G06F 7/544 - Methods 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
G06F 9/30 - Arrangements for executing machine instructions, e.g. instruction decode
95.
Fine-grained sparsity computations in systolic array
A systolic array can implement an architecture tailored to perform matrix multiplications on sparse matrices. Each processing element in the systolic array may include a register configured to store a value, and a multiplexor configured to select an input element from multiple input data buses based on metadata associated with the value. Each processing element may also include a multiplier configured to multiply the selected input element with the value to generate a multiplication result, and an adder configured to add the multiplication result to a partial sum input to generate a partial sum output.
G06F 7/544 - Methods 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
G06F 9/38 - Concurrent instruction execution, e.g. pipeline, look ahead
G06N 3/063 - Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
96.
Interest based advertising inside a content delivery network
A system, method, and computer readable medium for distributing data objects that are dynamically customized for users in a content delivery network. The system obtains information based on content accessed by a user, the content being accessed by the user through a content delivery network device. The system associates the user with other users based on the obtained information, the other users having accessed another content through the content delivery network device. The system generates a cluster, the cluster comprising a plurality of nodes representative of the user and the associated other users. The system determines a set of tags for the cluster, the set of tags derived from a plurality of websites accessed by the user.
An optical communication system comprises a plurality of linked single-wavelength coherent optical transceivers configured to communicate via short-reach data-center links at a common reference wavelength, each transceiver including a single single-wavelength laser source that is used to produce a source beam at a source beam wavelength, the source beam being used to produce transmit beams sent by the transceiver and for mixing with one or more receive beams received by the transceiver; wherein each of the transceivers includes a thermo-electric cooler configured to control a temperature of the single-wavelength laser source around a temperature setpoint that locks the source beam wavelength to the common reference wavelength; wherein each transceiver includes a wavelength deviation detector configured to detect a wavelength deviation between the source beam wavelength and the wavelength or wavelengths of the one or more receive beams or between the source beam wavelength and the common reference wavelength, wherein the wavelength deviation detector is configured to detect a threshold amount of wavelength deviation that is indicative that the single-wavelength laser source is problematic or a single-wavelength laser source of a separate transceiver coupled to send the one or more receive beams is problematic, wherein each transceiver is configured to indicate the wavelength deviation or problematic characteristic in order to identify problematic laser sources and thereby prevent the linked network of transceivers from communicating at a linked network wavelength that is marginal or out-of-range in relation to the common reference wavelength.
This disclosure describes, in part, techniques for adapting bandwidth estimation algorithms to account for local network stalls (e.g., Wi-Fi stalls). For instance, an electronic device may use a pacer component and/or a network socket buffer to detect Wi-Fi stalls. The pacer component and/or the network socket buffer may both be configured to store packets. The pacer component may determine a number of bytes to send to the network socket buffer based on a current bandwidth (or bitrate) estimation value and may move packets from the pacer component to the network socket buffer. If the second queue reaches capacity at a first time and is no longer at capacity at a second subsequent time, a Wi-Fi stall may be detected, and the electronic device may transition from a first state to a second state causing the electronic device to determine whether to update a current bandwidth estimation value.
Techniques are described for performing actions (e.g., streaming video content, such as advertising content) based on visual markers detected within a live video feed being streamed to one or more computing devices. First video content is streamed to the one or more computing devices. A presence of a content item within the first video content is detected at a first point in time during streaming of the first video content. An action associated with the content item is performed at a second point in time in response to detection of the presence of the content item in the first video content.
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 MPEG-4 scene graphs
G06V 20/40 - Scenes; Scene-specific elements in video content
H04N 5/272 - Means for inserting a foreground image in a background image, i.e. inlay, outlay
Techniques for utilizing machine learning to generate and use publishing parameters for a content delivery system are described. According to some examples, a computer-implemented method includes receiving, by a content delivery service, a request from a content provider device to send a media file to a client device; determining, by a provider intention match machine learning model of the content delivery service, a first set of one or more potential publishing parameters for the media file based on the request; sending a proposal to the content provider device to send the media file to the client device according to the first set of one or more potential publishing parameters; receiving, by the content delivery service, an indication from the content provider device to modify the first set of one or more potential publishing parameters for the media file; determining, by a negotiation simulation machine learning model of the content delivery service, a second set of one or more potential publishing parameters for the media file based on the indication from the content provider device; and sending the media file to the client device based on the second set of one or more potential publishing parameters.
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
patents
