Abstract: In various embodiments, a process for determining metrics including resource expenditures of a digital service includes discovering a plurality of configuration items of a computing infrastructure. The process includes identifying a subset of the plurality of configuration items utilized to provide a digital service, obtaining a plurality of resource expenditures respectively associated with at least a portion of the plurality of configuration items, and associating a subset of the plurality of resource expenditures with the subset of the plurality of configuration items. The process includes aggregating the subset of the plurality of resource expenditures to generate a metric of the digital service.

Abstract: Techniques described herein relate to using one or more machine learning models to identify values of variables to be used in application commands for execution. For example, the one or more machine learning models may identify one or more values of variables that are used to replace a different set of one or more values of variables in an application command before executing the command on a host.

Abstract: Systems, methods, and machine-readable media for monitoring a storage system and assigning performance service levels to workloads running on nodes within a cluster are disclosed. A performance manager may estimate the performance demands of each workload within the cluster and assign a performance service level to each workload according to the performance requirements of the workload, and further taking into account an overall budgeting framework. The estimates are performed using historical performance data for each workload. A performance service level may include a service level object, a service level agreement, and latency parameters. These parameters may provide a ceiling to the number of operations per second that a workload may use without guaranteeing the use of the operations per second, a guaranteed number of operations per second that a workload may use before being throttled, and define the permitted delay in completing a request to the workload.

Abstract: A method is described and includes obtaining a list of utterances comprising captions from an item of content; computing sentence transformer embeddings for each of the utterances; dividing the utterances into sentences and extracting a sentence embedding for each sentence; computing a semantic similarity between adjacent sentences; and merging the adjacent sentences into a block comprising a segment if the semantic similarity between the adjacent sentences is greater than a predetermined threshold.

Abstract: This disclosure provides methods, components, devices and systems for access point (AP)-aided downlink transmission opportunity (TXOP) preemption by stations (STAs) with low-latency uplink traffic. Some aspects more specifically relate to how a STA transmits a preemption indication (PRI) associated with a signature of the STA and how an AP, via reception of signature-based PRIs, may obtain information relating to which specific STAs have low-latency traffic ready for uplink transmission. Such signatures may relate to a resource allocation, such as a tone pattern, used to transmit at least a portion of a PRI. In some examples, the AP transmits a preemption scheduling (PRS) frame that includes channel access information, for each of the STA(s) that sent a PRI, associated with a downlink TXOP of the AP. Such channel access information may include at least a grant of permission for STA(s) to attempt uplink preemption of the downlink TXOP.

Abstract: Silicon germanium (SiGe)/silicon containing superlattice structures and methods for forming the same are provided. Various embodiments utilize SiGe layers in a SiGe/Si superlattice structure, which include varying concentrations of germanium throughout the layer. For example, in some embodiments, for each SiGe layer there is a core SiGe film with a low Ge content and two thinner SiGe layers or cladding layers positioned on opposing sides of the core SiGe film with each of the SiGe cladding layers having a higher Ge content then the core SiGe film. Various embodiments provide for SiGe layers having a germanium depth profile enabling strained SiGe superlattice deposition on Si{110} substrates.

Abstract: This disclosure provides methods and devices for introducing a power save protocol (for example, a lower power mode) for a multi-link devices (MLDs). Some aspects more specifically relate to reducing power consumption in an access point (AP) MLD, and more particularly, to a power save protocol (or a lower power mode) for an AP MLD. In some aspects, an AP MLD may initiate a lower power mode to save power for as long as possible while still maintaining minimal receive (RX) and transmit (TX) functionality. When requested by an associated station (STA), the AP MLD may then transition from the lower power mode to a higher power mode with full RX and TX functionality with a minimal delay. The described techniques may also account for trade-offs and constraints which arise due to different use cases and scenarios as well as different device configurations.

Abstract: Techniques for performing a machine learning (ML) cinematic (e.g., movie) question answering are described. According to some examples, a computer-implemented method includes receiving a request from a viewer device at a content delivery service to play a video; sending the video from the content delivery service to the viewer device; receiving, by the content delivery service, a question from the viewer device during playing of the video; generating, by a script context retrieval machine learning model of the content delivery service, a proper subset of a script of the video based on an input of the question; generating, by a cinematic question answering machine learning model of the content delivery service, an answer based on an input of the proper subset of the script of the video; and sending, by the content delivery service, the answer to the viewer device.

Abstract: Disclosed are various embodiments for seamless insertion of modified media content. In one embodiment, a modified portion of video content is received. The modified portion has a start cue point and an end cue point that are set relative to a modification to the video content to indicate respectively when the modification approximately begins and ends compared to the video content. A video coding associated with the video content is identified. The start cue point and/or the end cue point are dynamically adjusted to align the modified portion with the video content based at least in part on the video coding.

Abstract: A method and a system for managing healthcare records of a user are provided. The method includes storing an electronic medical record related to the user in form of a non-fungible token (NFT) written to a blockchain, associating a smart contract to the NFT in the blockchain, authorizing a request to access the electronic medical record related to the user based on the defined ownership of the electronic medical record stored in the blockchain, identifying one or more NFTs from the blockchain comprising one or more electronic medical records related to the user based on processing of the identifier information in associated one or more smart contracts therewith, in response to the request, and sending the one or more electronic medical records corresponding to the identified one or more NFTs to a requestor associated with the request.

Abstract: Embodiments described herein provided for an instruction and associated logic to enable a processing resource including a tensor accelerator to perform optimized computation of sparse submatrix operations. One embodiment provides a parallel processor comprising a processing cluster coupled with the cache memory. The processing cluster includes a plurality of multiprocessors coupled with a data interconnect, where a multiprocessor of the plurality of multiprocessors includes a tensor core configured to load tensor data and metadata associated with the tensor data from the cache memory, wherein the metadata indicates a first numerical transform applied to the tensor data, perform an inverse transform of the first numerical transform, perform a tensor operation on the tensor data after the inverse transform is performed, and write output of the tensor operation to a memory coupled with the processing cluster.

Abstract: Aspects of the disclosure are directed to a high performance connection scheduler for reliable transport protocols in data center networking. The connection scheduler can handle enqueue events, dequeue events, and update events. The connection scheduler can include a connection queue, scheduling queue, and quality of service arbiter to support scheduling a large number of connections at a high rate.

Abstract: A method for providing a management framework for distributed event processing is disclosed. The method includes retrieving data from a distributed event streaming platform based on a data fetch size configuration, the data including event messages; submitting a batch of the data to a consumer thread based on a data polling configuration; loading the batch of the data onto a data structure that enables coordination of processing threads, the data structure including a blocking queue; processing each of the event messages in the batch of the data from the data structure based on predefined logics; publishing each of the processed event messages in the batch of the data to a producer buffer based on a selection logic, the producer buffer including a load balancer; and recording an agreement for each of the published event messages in the batch of the data to a shared collection.

Abstract: A physical layer (PHY) is coupled to a serial, differential link that is to include a number of lanes. The PHY includes a transmitter and a receiver to be coupled to each lane of the number of lanes. The transmitter coupled to each lane is configured to embed a clock with data to be transmitted over the lane, and the PHY periodically issues a blocking link state (BLS) request to cause an agent to enter a BLS to hold off link layer flit transmission for a duration. The PHY utilizes the serial, differential link during the duration for a PHY associated task selected from a group including an in-band reset, an entry into low power state, and an entry into partial width state.

Abstract: An artificial intelligence (AI)-based system and method for autonomous navigation of robotic devices in dynamic human-centric environments are disclosed. The AI-based system comprises an object tracking subsystem, a probabilistic estimation subsystem, a socially compliant behavior subsystem, a constrained space navigation subsystem, a commands processing subsystem, a virtual cost-map layer subsystem, and a path-planning subsystem. The AI-based system obtains sensor data using sensors. The AI-based system employs artificial intelligence (AI) models and machine learning (ML) models for computing probabilistic position data and generating convex hulls. The AI-based system generates high-cost zones for identifying boundaries associated with groups to plan navigation paths. The AI-based system generates waypoints for the robotic devices based on detecting constrained spaces in the dynamic human-centric environments by analyzing the sensor data.

Abstract: A computer-implemented method for performing natural language-based data integration includes causing execution of a data integration application on a remote device via a network and causing surfacing of a GUI corresponding to the data integration application on a display of the remote device. The method includes receiving, via the GUI, a natural language input representing a data integration task, generating, via an LLM, a set of ordered activities corresponding to the data integration task represented by the natural language input, and selecting, via the LLM, one or more APIs for performing each activity within the set of ordered activities. The method also includes generating a data pipeline based on the set of ordered activities and the API(s) for performing each activity, as well as back-translating the data pipeline to a desired data format for execution by the data integration application.

Abstract: Various embodiments of the present disclosure provide machine learning architectures and training techniques for improving predictive functionality of a computer. The techniques apply a multi-layered machine learning model to a target prediction domain to generate a model prediction for an input data object. The techniques may include inputting a vector to layer models of the multi-layered machine learning model to generate a layer code predictions for a code defined within a target coding domain. The techniques include inputting the layer code predictions to a layer metamodels of the multi-layered machine learning model to generate intermediate code predictions for the code. The techniques include inputting intermediate outputs to a fusion model of the multi-layered machine learning model to generate a fused code prediction for the code and outputting a model prediction for the code based on the fused code prediction.

Abstract: A method of gradually revealing a hidden user-interface feature in accordance with performance of a self-care activity is disclosed. The method includes, while a user of an electronic device has performed less than a first threshold amount of a self-care activity, displaying a user interface without displaying a hidden user-interface feature. In accordance with a determination that the user has performed more than the first threshold amount of the self-care activity, the method also includes revealing a first portion of the hidden user-interface feature. In accordance with a determination that the user has performed more than a second threshold amount of the self-care activity, the second threshold amount being greater than the first threshold amount, the method additionally includes: continuing to display the first portion of the hidden user-interface feature, and revealing a second portion of the hidden user-interface feature within the user interface.

Abstract: The present disclosure relates to a system and method for enabling authentication on the bot application. The system may receive video stream along with query from a user computing device associated with a user. The query may be a generic or a privileged query and based on the nature of query, identification and verification of the user is carried out. For privileged services, the authentication procedure may include many levels of authentication processes that may include biometric authentication modules as well. Once the user is verified and authenticated, the response for the user query is provided to the user.

Abstract: A process for recommending items comprises receiving a first input from a user via a user interface and modifying the user interface based on the first input. A second input is received from the user via the user interface. The first and second inputs are used as data for running a set of primary models and a set of secondary models, where each item that the process may recommend corresponds to one and only one primary model and one and only one secondary model. The primary models calculate a confidence level that the user should be recommended the item associated with the primary model, based on the first and second inputs. Items associated with primary models where the confidence level is above a threshold are recommended to the user. For each recommended item, a parameter is generated by the associated secondary model.