Abstract: A method in an electronic device includes detecting, with one or more processors, initiation of an image capture operation using an image capture device situated on a first surface of the electronic device and having a first field of view extending away from the first surface in a first direction. In response to detecting the initiation of the image capture operation, the method includes actuating a second image capture device situated on a second surface of the electronic device and having a second field of view extending away from the second surface in a second direction. The method then captures image content with the second image capture device and presenting the image content on a display situated on the first surface of the electronic device. Thereafter, the one or more processors capture at least one image with the first image capture device.

Abstract: Systems, computer program products, and methods are described herein for providing authentication across a distributed resource network. The method includes receiving an authentication request associated with a user. The authentication request includes one or more potential physical characteristics. The method also includes identifying a non-fungible token associated with the user. The non-fungible token associated with the user includes one or more stored physical characteristic of the user. The method further includes comparing the one or more potential physical characteristics of the authentication request with the one or more stored physical characteristics of the user. The method still further includes generating an access determination for the authentication request based on the comparison of the one or more potential physical characteristics of the authentication request with the one or more stored physical characteristics of the user.

Abstract: A system and method for creating a performance-optimized server image. The method includes receiving logs that include performance information of one or more servers of a first type. Current values for performance parameters of the one or more servers are determined based on the logs. Optimal value ranges for the performance parameters are determined. In response to determining that, for at least one performance parameter, a current value is outside a respective optimal value range, incremental changes are determined. The incremental changes are applied to a latest version of a server image of the first type to create a new version of the server image. New values for the performance parameters are determined. In response to determining that, for each performance parameter, a new value is within a respective optimal value range, the new version of the server image is validated as a performance-optimized version of the server image.

Abstract: Techniques for causing an LLM to generate semantically related phrase variations for an identified phrase are disclosed. An LLM that is generally pre-trained on an arbitrary corpus of language training data is accessed. Seed data is fed as input to the LLM. The seed data includes multiple phrases that are semantically related and that describe a command. When any one of the phrases is received as utterance input, the utterance input triggers execution of the command. The LLM generates multiple phrase variations based on the phrases, where each phrase variation is semantically related to the other phrases. When any one of the phrase variations is received as new utterance input, the new utterance input also triggers execution of the command. The phrases and phrase variations are then stored together in a data storage.

Abstract: Techniques for facilitating voice based dictation of programming code within a context of an IDE are disclosed. Programming code is fed to a text-to-speech (TTS) model. The TTS model generates an audio file associated with the code. The audio file is then fed to a speech-to-text (STT) model. The STT model generates a transcription file associated with the audio file. Each respective line of code included in the programming code is mapped to a corresponding line of code included in the transcription file, resulting in generation of a list of phrase pairings. These phrase pairings represent relationships between actual code and how that actual code sounds if read out loud. An LLM then ingests the list of phrase pairings. The LLM identifies correlations between programming vocabulary that has specific meaning within the context of the IDE and how that programming vocabulary sounds if read out loud.

Abstract: Techniques for performing contextualized intent and slot extraction using a large language model (LLM) are disclosed. The LLM is generally pre-trained on an arbitrary corpus of language training data. A prompt is provided to the LLM. This prompt includes a limited number of prompt phrases. The prompt phrases share a semantic relationship with one another. A spoken utterance is recorded and then converted to text, resulting in generation of a transcription. The transcription is provided to the LLM. The LLM extracts, from the transcription, an extracted intent and an extracted slot. The extracted intent is determined to be related to a prompt-described intent that was included in the prompt. The prompt is supplemented by adding the extracted intent and the extracted slot to the prompt, resulting in the extracted intent being identified as sharing the semantic relationship with the other prompt phrases in the prompt.

Abstract: A system and method for automating and improving data extraction from a variety of document types, including both unstructured, structured, and nested content, is disclosed. The system and method incorporate an intelligent machine learning model that is designed to intelligently identify chunks of text, map the fields in the document, and extract multi-record values. The system is designed to operate with little to no human intervention, while offering significant gains in accuracy, data visualization, and efficiency. The architecture applies customized techniques including density-based adaptive text clustering, tabular data extraction based on hierarchical intelligent keyword searches, and natural language processing-based field value selection.

Abstract: A level-shifting pulse latch is provided for a self-timed memory clock signal for a memory. The level-shifting pulse latch includes a system-power-domain-to-memory-power-domain level-shifter that inverts and level-shifts a system clock signal into an inverted version of the system clock signal. A pass transistor controls whether the inverted version of the system clock signal drives a memory-power-domain latch to produce the self-timed memory clock signal.

Abstract: Aspects of the present disclosure provide techniques and apparatus for safety monitoring of a vehicle control system. An example method of operating a vehicle includes detecting an error associated with a system-on-a-chip (SoC) having a main domain and a safety domain, wherein the main domain is coupled to a first bus for communicating with one or more electronic control units (ECUs) and wherein the safety domain is coupled to a second bus for communicating with the one or more ECUs; indicating the error to the one or more ECUs via at least one of the first bus, the second bus, or a power management integrated circuit (PMIC) in response to detecting the error, wherein the PMIC is configured to supply power to the main domain or the safety domain; and performing one or more actions in response to detecting the error.

Abstract: A refrigeration unit includes a cabinet and a first evaporator assembly. The first evaporator assembly is operable between an uninstalled condition and an installed condition. In the uninstalled condition, the first evaporator assembly is not assembled with the cabinet. In the installed condition, the first evaporator assembly is assembled with the cabinet. The first evaporator assembly includes a first evaporator, a first suction line connected to the first evaporator at a first suction line joint, and a first capillary tube connected to the first evaporator at a first capillary tube joint. The first suction line joint and the first capillary tube joint of the first evaporator assembly are leak testable in the uninstalled condition of the first evaporator assembly.

Abstract: Techniques for context-based display of content and alert based on distance on a multi-display system are described. For instance, the described techniques can be implemented to determine a device context based on one or more of a first instance of media content displayed on a first display device positioned at a first surface of a client device or an environment in which the client device is positioned. Based on the device context, the described techniques enable output of a second instance of media content via a second display device positioned at a second surface of the client device.

Abstract: Techniques for managing call sessions in multi-display systems are described. For instance, the described techniques can be implemented to manage media content in the context of a client device that includes two or more housings attached via a hinge region such that the housings are pivotable relative to one another. The described techniques, for example, enable dynamic configuration of output of call sessions based on changes in user position relative to a client device.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to improve webservers using dynamic load balancers. An example method includes identifying a first and second data object type associated with media and with first and second data objects of the media. The example method also includes enqueuing first and second event data associated with the first and second data object in a first and second queue in first circuitry in a die of programmable circuitry. The example method further includes dequeuing the first and second event data into a third and fourth queue associated with a first and second core of the programmable circuitry, the first circuitry separate from the first core and the second core. The example method additionally includes causing the first and second core to execute a first and second computing operation based on the first and second event data in the third and fourth queues.

Abstract: A computerized-method for gauging agent's self-assessment effectiveness, is provided herein. The computerized-method includes for each interaction (i) operating a Self-assessment Consolidation module to calculate a confidence-interval for each data-point of one or more preconfigured data-points, and (ii) operating a Self-assessment Divergence Determinant (SDD) module. The operating of the SDD includes: retrieving one or more data-points of the interaction; for each data-point retrieving the confidence interval; setting a divergence-indicator as zero, when the data point is within the confidence-interval; setting the divergence-indicator as a subtraction of the data point from the calculated lower-bound, when the data-point is lower than the lower-bound of the confidence-interval; and setting the divergence-indicator as a subtraction of the calculated upper-bound from the data-point, when the data-point is greater than the upper-bound of the confidence-interval.

Abstract: A device may receive historic temporal data identifying events associated with a system, and may perform block bootstrapping of the hierarchical time series data, based on a hyperparameters, to generate blocks of data points of the historic time series data. The device may process the blocks of data points, with a plurality of different machine learning models, to calculate predictions, and may apply weights to the predictions to generate weighted predictions. The device may aggregate the weighted predictions to generate aggregated predictions, and may apply final weights to the aggregated predictions to generate weighted aggregated predictions. The device may aggregate the weighted aggregated predictions to generate a final prediction, and may perform one or more actions based on the final prediction.

Abstract: Systems, computer program products, and methods are described herein for authentication and monitoring of an artificial intelligence (AI) engine. The present invention is configured to receive, from a first network device, a first set of binary data associated with an AI engine; calculate, based on the first set of binary data, an engine hash value; store the engine hash value; receive, from a second network device, an approval of the first set of binary data; update an approval status of the engine hash value; receive, from a network device associated with a final user, a second set of binary data; determine that a second hash value associated with the second set of binary data matches the engine hash value; and transmit a notification to the network device associated with the final user, wherein the notification instructs the network device to allow the final user to launch the AI engine.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations: training, using labeled training data and a list of substitutes for an item, a machine learning algorithm; determining, using the machine learning algorithm, as trained, a respective similarity score for each substitute of the list of substitutes; ranking each substitute of the list of substitutes based on its respective similarity score; and re-training the machine learning algorithm based on at least the labeled training data and a highest ranked substitute of the list of substitutes. Other embodiments are disclosed herein.

Abstract: Systems, computer program products, and methods are described herein for authentication and monitoring of an artificial intelligence (AI) engine. The present invention is configured to receive, from a first network device, a first set of binary data associated with an AI engine; calculate, based on the first set of binary data, an engine hash value; store the engine hash value; receive, from a second network device, an approval of the first set of binary data; update an approval status of the engine hash value; receive, from a network device associated with a final user, a second set of binary data; determine that a second hash value associated with the second set of binary data matches the engine hash value; and transmit a notification to the network device associated with the final user, wherein the notification instructs the network device to allow the final user to launch the AI engine.

Abstract: Systems, computer program products, and methods are described herein for monitoring an artificial intelligence (AI) engine. The present invention is configured to receive, from a first network device, a first set of decision parameters associated with an AI engine; encrypt the first set of decision parameters, generating an encrypted dataset; store the encrypted dataset on a transaction object; receive, from a second network device, an output associated with the AI engine; update the transaction object based on the output associated with the AI engine; and transmit a notification to the first network device, wherein the notification comprises a decrypted dataset.

Abstract: A multi-port memory is provided that supports collision between a read port and a write port to the same multi-port bitcell. A sense amplifier reads a data bit from a multi-port bitcell when a write port to the multi-port bitcell is addressed during a system clock signal. Should a read port to the multi-port bitcell be addressed during the same system clock signal, a multiplexer selects for an output bit from the sense amplifier.