Abstract: Systems and techniques are provided for path tracing. For example, a process can include establishing a path tracing session associated with path tracing (PT) probe packets from a PT source node of an IPv6 network fabric. A PT probe packet can be received with a first IPv6 Destination Options Header with Path Tracing Option (DOH-PT) header that encodes path tracing information of the PT source node and indicates respective path tracing information for each PT midpoint node along a path from the PT source node to a PT sink node of the IPv6 network fabric. The received PT probe packet can be updated to include a second DOH-PT header that encodes path tracing information of the PT sink node. An updated PT probe packet includes the first and second DOH-PT headers and can be encapsulated with an additional IPv6 header corresponding to forwarding information of a collector node.

Abstract: Systems or techniques for facilitating learnable visual prompt engineering are provided. In various embodiments, a system can access a medical image and a pre-trained machine learning model that is configured to perform a diagnostic or prognostic inferencing task. In various aspects, the system can apply a pre-processing transformation to one or more pixels or voxels of the medical image, thereby yielding a transformed version of the medical image, wherein the pre-processing transformation can convert an input pixel or voxel intensity value to an output pixel or voxel intensity value via one or more parameters that are iteratively learned. In various instances, the system can perform the diagnostic or prognostic inferencing task, by executing the pre-trained machine learning model on the transformed version of the medical image.

Abstract: A computer-implemented method includes receiving, by one or more processors, Process Instruction (PI) information containing instructions for adjudicating a healthcare service request based on a primary fact source; dividing, by the one or more processors and using an Artificial Intelligence (AI) model, the instructions into one or more instruction sets; generating, by the one or more processors and the AI model, an input-output mapping for first ones of the one or more instruction sets having a complexity that does not satisfy a complexity threshold; generating, by the one or more processors and the AI model, code for second ones of the one or more instructions sets having the complexity that satisfies the complexity threshold; generating, by the one or more processors and the AI model, a validation input set for the input-output mapping and for the code; and applying, by the one or more processors and the AI model, the validation input set to the input-output mapping and the code to generate a validation ou

Abstract: A computer-implemented method for targeted monitoring of a patient in a bed comprises: receiving an image of the bed; predicting, based on a posture of the patient in the image, a pressure score for one or more contact regions between the patient and the bed; and providing an indication of the pressure score for the one or more contact regions.

Abstract: A MEMS package includes an interconnect structure disposed on a wafer. A first device substrate including a first MEMS device and a second device substrate including a second MEMS device are laterally separated from each other, disposed on the wafer and bonded to the interconnect structure. A first cap substrate with a first cavity is bonded to the first device substrate. A second cap substrate with a second cavity is bonded to the second device substrate. A getter is disposed on the interconnect structure and directly under the second MEMS device. The first cavity has a first pressure, and the second cavity has a second pressure lower than the first pressure.

Abstract: A method and system for processing a purchase based on image recognition in a video stream being presented by a computing system. A method includes receiving a first user-input defining a first user-request to pause presentation of the video stream, and, responsive to the first user-input, pausing by the computing system the presentation of the video stream at a video frame. Further, the method includes detecting based on computer-vision analysis of the video frame, at least one object depicted by the video frame. Additionally, the method includes correlating the detected object with at least one purchasable item and presenting a prompt for purchase of the at least one purchasable item. Also, the method includes receiving a second user-input requesting to purchase a given one of the at least one purchasable item and processing, responsive to receiving the second user-input, a purchase of the given purchasable item for the user.

Abstract: A memory subsystem and method for performing calibrations therein is disclosed. A memory subsystem includes a memory controller coupled to a memory by a plurality of signal paths. The memory controller is configured to perform an initial calibration to determine respective eye patterns corresponding to the ones of the plurality of signal paths. For a subsequent calibration, updated eye patterns are determined for a subset of the plurality of signal paths. Remaining ones of the plurality of signal paths (not included in the subset), are not active during the subsequent calibrations. Updated eye patterns for the remaining ones of the plurality of signal paths are determined based on information obtained during the initial calibration and information from signal paths in the subset designated proxies for the remaining ones of the plurality of signal paths.

Abstract: Embodiments of the present application discloses an information indicating method, a device and a system. The method includes: sending a physical uplink shared channel (PUSCH), wherein the PUSCH bears uplink control information (UCI), the UCI is used to indicate at least one of the following: remaining MCOT information which is used to indicate a remaining maximum channel occupancy time (MCOT) of a channel occupancy time (COT) within which a user equipment (UE) performs uplink transmission, or a target time period. The target time period includes: a time period for allowing a network device to transmit downlink data within COT within which uplink transmission is performed.

Abstract: Generating object morphisms during object search includes obtaining object-search request data, wherein the object-search request data includes object-search terms, obtaining resolved-request data representing the object-search terms, determining that a first analytical object partially consistent with the resolved-request data is available, wherein the first analytical object is consistent with a first portion of the resolved-request data, generating candidate object-morphism data with respect to the first analytical object in accordance with a second portion of the resolved-request data, outputting object-search response data including the candidate object-morphism data for presentation to a user, obtaining data indicating a selected object morphism from the candidate object-morphism data, generating a second analytical object in accordance with the first analytical object and the selected object morphism, wherein the second analytical object differs from the first analytical object, and outputting response

Abstract: In one embodiment, a method includes: receiving, in a sink device, profile information regarding a communication from a source device; based at least in part on the profile information, determining, in the sink device, a size for a buffer of the sink device, the buffer for storing streaming data of the communication; based at least in part on the profile information, determining, in the sink device, a synchronization interval for the communication; and controlling, via the sink device, the communication of the streaming data from the source device to the sink device via a first wireless protocol based at least in part on the synchronization interval, to cause the sink device to be a synchronized receiver for the communication.

Abstract: Implementations relate to generating multi-modal response(s) through utilization of large language model(s) (LLM(s)) and other generative model(s). Processor(s) of a system can: receive natural language (NL) based input, generate a multi-modal response that is responsive to the NL based output, and cause the multi-modal response to be rendered. In some implementations, and in generating the multi-modal response, the processor(s) can process, using a LLM, LLM input to generate LLM output, and determine, based on the LLM output, textual content and generative multimedia content for inclusion in the multi-modal response. In some implementations, the generative multimedia content can be generated by another generative model (e.g., an image generator, a video generator, an audio generator, etc.) based on generative multimedia content prompt(s) included in the LLM output and that is indicative of the generative multimedia content.

Abstract: Methods, apparatus, and processor-readable storage media for security-related risk detection using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining data related to at least one user associated with at least one interaction; identifying information pertaining to the at least one user by processing at least a portion of the obtained data using one or more artificial intelligence techniques; determining, based at least in part on at least a portion of the identified information, one or more security risks associated with the at least one user within a context of the at least one interaction; and performing one or more automated actions based at least in part on the one or more determined security risks.

Abstract: A smart spider and web scraping system with custom templates, artificial intelligence for custom attribute extraction, artificial intelligence for providing quick fixes for machine learning extracted web page data, and direct HTTP request extraction without crawling.

Abstract: An example apparatus includes: a pullup circuit coupled to a first USB terminal; a first pulldown circuit coupled to the first USB terminal; a second pulldown circuit coupled to a second USB terminal; a third pulldown circuit coupled to a third USB terminal; a fourth pulldown circuit coupled to a fourth USB terminal; a high-speed termination detection circuit including: a current source including a first supply terminal and a second supply terminal, the first supply terminal coupled to the first USB terminal, the second supply terminal coupled to the second USB terminal; a first comparator including a first comparator terminal and a second comparator terminal, the first comparator terminal coupled to the first USB terminal; and a second comparator including a third comparator terminal and a fourth comparator terminal, the third comparator terminal coupled to the second USB terminal; and a controller including a first control terminal and a second control terminal, the first control terminal coupled to the sec

Abstract: A method is provided for determining a pitch angle of a perception system of a vehicle with respect to a road surface on which the vehicle is located. Via the perception system, road perception information is detected from the road surface, and object perception information is detected from objects being different from the road surface. A primary pitch angle is determined by using the road perception information, and a relative pitch angle is determined by using the object perception information. The primary pitch angle and the relative pitch angle are combined in order to determine a final pitch angle of the perception system.

Abstract: The present disclosure provides a system for predicting the difficulty of an exam question in which a training module uses training data to create a machine learning model to predict the difficulty of a question, and the difficulty module collects inputted questions and answers from a teacher that are inputted through an education network into the machine learning model, and the difficulty of the question is displayed.

Abstract: A method for signal processing includes receiving a definition associated with a task, and based on the definition, selecting a first sensor modality having a first operational cost from multiple sensor modalities each associated with respective operational costs. The method further includes capturing a first sensor signal using the first sensor modality, and making a first determination that the first sensor signal is not sufficient to perform the task. The method further includes selecting, from the sensor modalities, a second sensor modality having a second operational cost, the second operational cost being higher than the first operational cost and capturing a second sensor signal using the second sensor modality. The method further includes making a second determination that the second sensor signal may be used to perform the task and using the second sensor signal to perform the task.

Abstract: In general, techniques are described for deploying and managing a virtual router having Data Plane Development Kit (DPDK) functionality to a computing device. In an example, a method includes creating, by a container orchestration platform executing on a computing device, a virtual router custom resource instance of a virtual router custom resource definition, the virtual router custom resource instance for a virtual router to execute on the computing device; based on configuration data for the virtual router custom resource instance, by the container orchestration platform, modifying the virtual router custom resource instance with the configuration data and deploying a first virtual computing instance comprising a virtual router configured according to the modified virtual router custom resource instance; and executing, by the computing device, the virtual router to process a packet.

Abstract: In general, techniques are described for deploying virtualized cell site routers (vCSRs). In an example, a method comprises receiving, at a forwarding plane of a virtualized cell site router (vCSR) of a first Distributed Unit (DU) of a plurality of DU servers of a cell site for a 5G radio access network, the vCSR having a containerized routing protocol process and a forwarding plane configured to perform Layer 2 (L2) switching, L2 packets on a second interface for a second physical link connecting the first DU server to an L2 switch; and switching, by the forwarding plane of the vCSR of the first DU, the L2 packets on a first interface for a first physical link connecting the first DU server to a second DU server of the plurality of DU servers.

Abstract: A data warehouse connector service is described. The data warehouse connector service integrates with an identity resolution system of a customer data platform to systematically communicate identity-resolved customer profile data from the customer data platform to a cloud-based data warehouse. Operation of the data warehouse connector is managed through various configuration settings accessible to an end-user of the customer data platform via a user interface.