Abstract: Described herein is a system for automatically detecting and assigning action items in a real-time conversation and determining whether such action items have been completed. The system detects, during a meeting, a plurality of action items and an utterance that corresponds to a completed action item. Responsive to detecting the utterance, the system generates a similarity score with respect to a first action item of the plurality of action items. The system compares the similarity score to a first threshold. Responsive to determining that the similarity score does not exceed the first threshold, the system generates a second similarity score with respect to a second action item of the plurality of action items. The system compares the second similarity score to a second threshold, which exceeds the first threshold. Responsive to determining that the second similarity score exceeds the second threshold, the system marks the second action item as completed.

Abstract: Embodiments described herein include software, firmware, and hardware that provides techniques to enable deterministic scheduling across multiple general-purpose graphics processing units. One embodiment provides a multi-GPU architecture with uniform latency. One embodiment provides techniques to distribute memory output based on memory chip thermals. One embodiment provides techniques to enable thermally aware workload scheduling. One embodiment provides techniques to enable end to end contracts for workload scheduling on multiple GPUs.

Abstract: Systems and methods described herein are directed to the optimization and implementation of machine-learning models on edge devices. A building management system can receive optimization criteria to optimize a first machine-learning model for a target platform. The first machine-learning model has one or more model parameters. The building management system transforms, based on the target platform and the optimization criteria, at least one datatype of the one or more model parameters of the first machine-learning model to generate a second machine-learning model. The building management system determines, using a verification dataset, an accuracy of the second machine-learning model, and retrains the second machine-learning model using a training dataset responsive to the accuracy being less than a predetermined threshold.

Abstract: Monolithic two-dimensional (2D) arrays of double-sided DRAM cells including a frontside bit cell over a backside bit cell. Each double-sided cell includes a stacked transistor structure having at least a first transistor over a second transistor. Each double-sided cell further includes a first capacitor on a frontside of the stacked transistor structure and electrically coupled to a source/drain of the first transistor. Each double-sided cell further includes a second capacitor on a backside of the stacked transistor structure and electrically coupled to a source/drain of the second transistor. Frontside cell addressing interconnects are electrically coupled to other terminals of at least the first transistor while one or more backside addressing interconnects are electrically coupled to at least one terminal of the second transistor or second capacitor.

Abstract: This application provides methods of inhibiting an inflammation- or hypoxia-induced death of a cell involving inhibiting an RNF213 signaling pathway. The application further provides methods of preventing or treating various diseases and disorders in a subject involving administering to the subject an inhibitor of expression of RNF213 protein or an inhibitor of one or more functions of the RNF213 protein. The application still further provides methods for enhancing the effectiveness of a cancer treatment in a subject where the cancer involves a hypoxic tumor microenvironment involving co-administering the cancer treatment with an inhibitor or activator of different functions of the RNF213 protein. The application also provides methods of eliminating drug-resistant tumor cells by co-administering an inhibitor of the expression of RNF213 protein or by inhibiting or activating specific functions of the RNF213 protein.

Abstract: Techniques are disclosed for migrating one or more services from an edge device to a cloud computing environment. In one example, a migration service receives a request to migrate a first set of services from the edge device to the cloud computing environment. The migration service identifies a hardware profile of a computing device (or devices) of the cloud computing environment that matches the edge device, and then configures the computing device to execute a second set of services that corresponds to the first set of services. The migration service establishes a communication channel between the edge device and the computing device, and then executes a set of migration operations such that the second set of services is configured to execute as the first set of services. The computing device may operate in a virtual bootstrap environment or dedicated region of the cloud computing environment.

Abstract: In an approach for optimizing job preemption using a scheduling mechanism that considers dynamic and static information, a processor, responsive to a pending job being selected to be run, determines that no computing hosts within a computing cluster have available resources capable of running the pending job and non-preemptive measures will not provide required resources for the pending job. A processor identifies candidate jobs for preemption and dynamic information and static information for each candidate job. A processor ranks the candidate jobs for preemption based on the dynamic information and the static information for each candidate job. A processor attempts to preempt a top N candidate jobs whose released resources in combination with the available resources of the computing cluster satisfy the required resources of the pending job. A processor, responsive to successfully preempting the top N candidate jobs, initiates the pending job.

Abstract: A first circuit path communicates a first, asynchronous, signal, and a second path communicates a second signal. A schmoo delay circuit receives the first and second signals and includes shmoo control circuitry and a delay generator. The delay generator receives a delay selector signal from the shmoo control circuitry indicative of an amount of delay. The shmoo delay circuit provides a delayed version of at least one of the first or second signals. A first logic circuit receives the delayed version of the at least one of the first signal or the second signal, and a second logic circuit receives another one of the first signal or the second signal. The shmoo control circuitry modifies the delay selector signal to sweep through a set of different delay amounts applied by the delay generator to generate delayed versions of the at least one of the first signal or the second signal.

Abstract: Described are techniques for disintegrating an entity into smaller entities. A graph (“first graph”) for the entity of records to be disintegrated is constructed, where each vertex of the first graph represents a record in the entity of records to be disintegrated. The edges in the first graph connecting records in the entity of records represent matching links between the records, where each edge is associated with a weight corresponding to a similarity score. Furthermore, two or more additional graphs representing two or more sub-entities of the entity of records to be disintegrated are constructed. Such graphs are constructed based on selecting edges with a maximum weight out of the edges connected between each pair of records in the first graph or based on the number of connections each record has with other records in the first graph exceeding a threshold value.

Abstract: Disclosed herein are deep-learning based systems, methods, and instrumentalities for medical decision-making. A system as described herein may implement an artificial neural network (ANN) that may include multiple encoder neural networks and a decoder neural network. The multiple encoder neural networks may be configured to receive multiple types of patient data (e.g., text and image based patient data) and generate respective encoded representations of the patient data. The decoder neural network (e.g., a transformer decoder) may be configured to receive the encoded representations and generate a medical decision, a medical summary, or a medical questionnaire based on the encoded representations. In examples, the decoder neural network may be configured to implement a large language model (LLM) that may be pre-trained for performing the aforementioned tasks.

Abstract: This disclosure provides methods, components, devices and systems for multi-link wireless communications. According to certain aspects, a wireless node may obtain information regarding a machine learning (ML) model, obtain inputs for the ML model, provide the inputs to the ML model to generate an inference, and use the inference to make a decision regarding a handover of the wireless node from at least a first access point (AP) device to a second AP device.

Abstract: Aspects of the present disclosure relate to real-time invoice error prevention. Embodiments include receiving a value related to an item or service during creation of an invoice by a user via a user interface, and determining a user-level mean and a user-level standard deviation related to the value based on historical invoices of the user. Embodiments include determining a global mean and a global standard deviation related to the value based on historical invoices of a plurality of users. Embodiments include selecting weights for the user-level mean, the user-level standard deviation, the global mean, and the global standard deviation based on a total number of the historical invoices of the user. Embodiments include determining an expected range for the value based on the user-level mean, the user-level standard deviation, the global mean, the global standard deviation, and the weights. Embodiments include determining that the value is outside the expected range.

Abstract: The present disclosure relates to a personal computing device configured to provide a sensor hierarchy for a subscriber comprising: a sensor module, configured to receive or retrieve values from a sensor; a memory module, configured to store data indicative of a sensor hierarchy, wherein the sensor hierarchy comprises a plurality of nodes wherein each node comprises at least one hierarchical identifier and at least one node comprises data indicative of the sensor module; and a sensor hierarchy module, configured to: obtain the data indicative of the sensor hierarchy from the memory module; receive a subscription request from the subscriber, wherein preferably the subscription request comprises data indicative of the hierarchical identifier to subscribe to; optionally locate the hierarchical identifier of the subscription request within the sensor hierarchy; and subscribe the subscriber based on the subscription request.

Abstract: Methods and compositions are described for selecting and identifying orthogonal aminoacyl synthetase-tRNA pairs and their use to incorporate unnatural amino acids in a site-specific manner in proteins. Specifically described is a novel E. coli tyrptophanyl synthetase-tRNA pair that functions as both an opal and amber suppressor and that incorporates tryptophan analogs into proteins.

Abstract: A tag characterizing a portion of a multi-view interactive digital media representation (MVIDMR) may be determined by applying a grammar to natural language data. The MVIDMR may include images of an object and may be navigable in one or more dimensions. An object model location for the tag identifying a location within a three-dimensional object model may be determined by applying the grammar to the natural language data. The tag may then be applied to the MVIDMR by associating it with two or more of the images at positions determined based on the object model location.

Abstract: Certain aspects of the present disclosure provide an apparatus for wireless communication. The apparatus generally includes a processing system configured to generate a message comprising coordination information, wherein the apparatus is associated with a first AP, the message to be used for coordinated communications by the first AP and a second AP, wherein the first AP and the second AP are associated with different basic service sets (BSSs), and an interface configured to output the message for transmission during a networking coordination window of a networking cluster.

Abstract: A guidewire made from a drawn-filled tube composite wire is described. The composite wire has a stainless steel outer sheath jacketing a nitinol core wire. The drawn-filled tube composite wire is ground at its distal end to expose the nitinol core, which has superelastic and kink resistant properties that are desirable for the distal end of a guidewire. The proximal end of the drawn-filled tube is not ground or if ground, the outer sheath of stainless steel is not removed to an extent sufficient to expose the nitinol core.

Abstract: Embodiments are generally directed to graphics processor data access and sharing. An embodiment of an apparatus includes a circuit element to produce a result in processing of an application; a load-store unit to receive the result and generate pre-fetch information for a cache utilizing the result; and a prefetch generator to produce prefetch addresses based at least in part on the pre-fetch information; wherein the load-store unit is to receive software assistance for prefetching, and wherein generation of the pre-fetch information is based at least in part on the software assistance.

Abstract: The present disclosure discloses a calibration slide for calibration of an automated microscope. The slide includes at least one calibration zone defined on at least one major surface of the sample slide. The at least one calibration zone is divided by a cross hair to define a plurality of quadrants. Each of the plurality of quadrants is defined with an array of apertures of varying density of arrays. The automated microscope including the calibration slide of the present disclosure enables corrective maintenance. The method of the present disclosure may be employed across various automated microscopes within a lab or at labs at various locations through offline/online mode to achieve similar results when tested on same sample.

Abstract: This disclosure provides methods and devices for managing the allocation of resources for uplink (UL) and downlink (DL) transmissions associated with a scheduled time period. In some implementations, a wireless station (STA) transmits, to an access point (AP), a request frame indicating a bandwidth or a quantity of spatial streams (or both) for the UL transmissions, and indicating a bandwidth or a quantity of spatial streams (or both) for the DL transmissions. In some instances, the request frame also may indicate the STA's intention to transmit UL data as duplicates carried on different communication links. The STA receives a trigger frame indicating that the STA is scheduled to transmit or receive data during the time period. The STA transmits data to, or receives data from, one or more other devices during the time period.