Abstract: Embodiments provide artificial intelligence-based methods and systems for generating scalable task-agnostic embeddings for training task-specific models. Method performed by server system includes accessing historical transaction data from database. Historical transaction data includes entity-specific data, cardholder-specific data, and transaction-specific data. Method includes generating one or more pseudo-objective models for each of plurality of entities based on historical transaction data and one or more pseudo-objectives. Plurality of entities includes acquirer, merchant, and issuer. Method includes determining via one or more pseudo-objective models, entity-specific embeddings for each entity of plurality of entities based on entity-specific data. Entity-specific embeddings includes acquirer-specific embeddings, merchant-specific embeddings, and issuer-specific embeddings. Upon receiving request to induct new entity, method includes accessing new entity data associated with new entity from database.

Abstract: An intelligent Radio Access Network (RAN) optimization framework. For an E2 Node, optimization services are initiated for handling by a Near-Real Time RAN Intelligent Controller (RIC) (Near-RT RIC). The E2 Node compares the performance to a first predetermined threshold. In response to the performance being below the first predetermined threshold, the E2 Node takes over optimization of the E2 Node. Otherwise, the Near-RT RIC continues optimization. The E2 Node compares the performance of the E2 Node to a second predetermined threshold. In response to the performance being below the second predetermined threshold, the Near RT RIC resumes handling the optimization. Otherwise, the E2 Node continues to handle the optimization of the performance of the E2 Node. For an Open-RAN Radio Unit (O-RU) Node, the O-RU Node performs local optimization of time-critical functions and a Non-RT RIC is able to perform optimization of non-time critical functions.

Abstract: A package includes a first die with a compute element and first region, a second die with a compute element and second region, and a bridging element connecting the first and second dies. The bridging element includes interconnect regions for electrical coupling, a first photonic path from the first interconnect region to the second, and a second photonic path in the reverse direction. A photonic transceiver is integrated into the bridging element, with one portion sending and receiving optical signals via the photonic paths, and the other portion located in an AMS block in the first die or second die near the memory and compute elements. The transceiver portions are connected by a short electrical interconnect (less than 2 mm).

Abstract: A method for preventing data leakage may include: identifying data that is generated by at least one framework application in response to a data request from a first machine learning (ML) engine of a plurality of ML engines; creating a plurality of data blocks based on the generated data, a category of the first ML engine, and a tag associated with the first ML engine and the at least one framework application; determining whether the plurality of data blocks are valid to share with the first ML engine using an activity block chain associated with each of the plurality of framework applications; based on the plurality of data blocks being valid, sharing the plurality of data blocks with the first ML engine, and otherwise discarding the plurality of data blocks not to share with the first ML engine.

Abstract: Systems and methods for enhanced organizational transparency using a linked activity chain in a ledger are disclosed. In one embodiment, a method may include (1) a back end for an organization comprising at least one computer processor receiving a first communication from a first entity comprising a first customer interaction with the first entity; (2) the back end writing the first communication to a ledger for the organization as a first block in a linked activity chain; (3) the back end receiving a second communication from a second entity comprising a second customer second activity with the second entity; (4) the back end writing the second communication to the ledger for the organization as a second block in the linked activity chain; (5) the back end calculating a summary score for the customer based on the blocks in the linked activity chain.

Abstract: Systems and methods are described for a query conversion system to convert a first query string from a first version of a query language to a second version of the query language. The query conversion system may be associated with a tokenizer and parser, code converter, compatibility library, and a query formatter. The tokenizer and parser may tokenize and parse a query string to create a first node tree with commands. The code converter may parse the first node tree while using the compatibility library to convert the commands and generate a second node tree. The query formatter may create a second query string executable by the second version of the query language.

Abstract: Systems and methods for routing in mixture-of-expert models. In some aspects of the technology, a transformer may have at least one Mixture-of-Experts (“MoE”) layer in each of its encoder and decoder, with the at least one MoE layer of the encoder having a learned gating function configured to route each token of a task to two or more selected expert feed-forward networks, and the at least one MoE layer of the decoder having a learned gating function configured to route each task to two or more selected expert feed-forward networks.

Abstract: A system for issue prediction based on multidimensional data analysis includes a model generator that receives a resolved data item relating to a service issue. The resolved data item includes different attributes corresponding to multiple data dimensions and adjusts a population of attributes based on a statistical data model and a deep learning data model operating independent of each other. The statistical data model operates on the attributes for providing a predictive feature and the deep learning data model operates on the attributes for providing a predictive label based on performance metrics related to the data dimensions. The predictive feature and the predictive label collectively define training data. The model generator also trains a classification model based on the training data for predicting a potential issue related to an unresolved data item. The trained data model provides a trigger based on the potential issue being related to the performance metrics.

Abstract: Example methods and systems for receive side scaling (RSS) are described. In one example, a computer system may generate and send instruction(s) to the programmable physical network interface controller (PNIC) to configure a first flow entry that associates a first packet flow with a first queue and a second flow entry that associates a second packet flow with a second queue. In response to receiving a first packet that is associated with the first packet flow, the programmable PNIC may match the first packet with the first flow entry and steer the first packet towards the first queue for processing by a first processing thread. In response to receiving a second packet that is associated with the second packet flow, the programmable PNIC may match the second packet with the second flow entry and steer the second packet towards the second queue for processing by a second processing thread.

Abstract: A computing system retrieves a value of a device identifier of itself and generates a device claim asserting the value of the device identifier. The device claim is then associated with an identifier of a user of the computing system. The computing system then generates and attach proof code to the device claim to turn the device claim into a verifiable device credential (VDC). The proof code proves that the VDC is issued by the user of the computing system. The VDC is later presented to a relying entity as part of an identity protection system to further protect the user's identity.

Abstract: Various embodiments of the present disclosure disclose improved BIST systems and methods for testing digital devices. A method for testing a digital device includes receiving, based at least in part on an input signal, an output signal from a device under testing (DUT). The output signal is processed to generate a noise signal and a recovered signal for the DUT. The controller may generate a signal to noise power ratio based at least in part on the noise and recovered signals and compare the signal to noise power ratio to a predetermined power threshold to generate a performance metric.

Abstract: A chip includes a merger cell including a first p-type length of diffusion (LOD) region extending in a first direction, a first n-well underneath the first p-type LOD region, a first supply rail configured to receive a first supply voltage, and a first n-tap coupling the first n-well to the first supply rail. The merger cell also includes a second p-type length of diffusion (LOD) region extending in the first direction, a second n-well underneath the second p-type LOD region, a second supply rail configured to receive a second supply voltage different from the first supply voltage, and a second n-tap coupling the second n-well to the second supply rail.

Abstract: Systems and methods of generating interfaces including recommended items selected by a graph-based cold-start (GCS) model are disclosed. A request for an interface is received and a set of interface items is generated for inclusion in the interface. The set of interface items is selected, at least in part, by a GCS model including a semantic similarity component and a viewed-also-viewed component. The set of interface items is generated based on a combination of an output of the semantic similarity component and an output of the viewed-also-viewed component. The interface including the set of interface items is generated and transmitted to a system that generated the request for the interface.

Abstract: In aspects of device access control based on detected user state, a mobile device has a display device to display visual content for viewing in a secondary user mode of operation of the mobile device. The mobile device implements an access control module to detect a user state of a user accessing the mobile device in the secondary user mode. The access control module can then restrict the display of the visual content on the display device based on the user state being a detected first state, or allow the display of the visual content on the display device based on the user state being a detected second state.

Abstract: Implementations described herein relate to generating candidate suggestion(s) that are personalized to a given user locally at an in-vehicle computing device of a vehicle of the given user. For example, implementations can identify an occurrence of a given suggestion state, generate the candidate suggestion(s) that are personalized to the user for the given suggestion state, store the candidate suggestion(s) in on-device storage of the in-vehicle computing device in association with the given suggestion state, and cause a given one of the candidate suggestion(s) to be provided for presentation to the given user. Accordingly, upon a subsequent occurrence of the given suggestion state, implementations can obtain the candidate suggestion(s) stored in association with the given suggestion state, and cause the given one of the candidate suggestion(s), or an additional one of the candidate suggestion(s), to be provided for presentation to the given user.

Abstract: A method, an electronic device and a non-transitory computer readable medium for securing sensor data are provided. The method comprises: obtaining context information by fetching a plurality of sensor data by a plurality of applications, mapping the plurality of sensor data to the plurality of applications and storing the mapped plurality of sensor data, generating pre-processed information based on the context information and the mapped plurality of sensor data, creating an inference category of the pre-processed information based on the pre-processed information and information from a database, and predicting at least one useful inference and at least one harmful inference of the plurality of sensor data based on the inference category, the context information and the plurality of sensor data.

Abstract: Systems and methods are provided for dynamically generating a product description personalized for a target user account. Product description data and/or product comment data associated with the product are obtained from a server via a communication network. Based on the product description data and/or product comment data, a product description template, comprising fields to be populated, is generated and stored in memory. Comment data associated with a product of interest is obtained from a server via the network. The comment data originates from a set of user accounts each having a similarity score with a target user account that is above a similarity threshold. Based on the set of comment data, comment-based description data are generated and stored in memory. Based on the product description template and the comment-based description data, a product description is generated for presentation for the target user account.

Abstract: An embodiment of a graphics apparatus may include a mask buffer to store a mask, a shader communicatively coupled to the mask buffer to apply the mask to a first shader pass, and a resolver communicatively coupled to the mask buffer to apply the mask to a resolve pass. The resolver may be configured to exclude a sample location not covered by the mask in the resolve pass. Other embodiments are disclosed and claimed.

Abstract: Provided is a system and method for enhancing media. The method includes: identifying whether a scene of a first preview frame captured by at least one primary camera was captured in low light based on at least one pre-defined parameter of the first preview frame; based on identifying that the first preview frame was captured in low light, triggering at least one secondary camera to capture a second preview frame of the scene, wherein the second preview frame has an exposure time higher than an exposure time of the first preview frame, and wherein the second preview frame includes one of a higher field of view (FOV) and a same FOV as compared to the first preview frame; and generating an output frame based on the first preview frame, the second preview frame, and at least one of the at least one pre-defined parameter.

Abstract: In aspects of device configuration based on detected user state, a mobile device includes device applications that can be initiated to display visual content or emit audio content in a secondary user mode of operation of the mobile device. The mobile device implements an access control module to detect a user state of a user accessing one or more of the device applications in the secondary user mode. The access control module can then categorize a device application as restricted based on the user state being a detected first state, or categorize the device application as allowed based on the user state being a detected second state.