Abstract: Systems, apparatuses and methods identify a plurality of registers that are associated with a system-on-chip. The plurality of registers includes a first portion dedicated to write operations and a second portion dedicated to read operations. The technology writes data to the first portion of the plurality of registers, and transfers the data from the first portion to the second portion.

Abstract: Dynamic partitioning of a search space of queries is implemented for flexible, heuristic database querying. Search space partitioning refers to dividing the search space for a submitted query into smaller parts by augmenting the queries to append thereto an additional predicate comprising a dynamic partition key and a value(s) selected based on heuristics (e.g., recency and/or relevancy of the value(s)). A plurality of candidate augmentations of the query and corresponding query plans are generated and evaluated based on additional heuristics to determine which can be executed to yield the best results in terms of result quality and latency. This query plan is selected and executed for retrieval of results that satisfy the query, with pagination utilized for presentation of the results. The procedure of generating candidate query plans, selecting one of the candidates for execution, and paginating results is repeated until a search termination criterion is satisfied.

Abstract: Techniques are disclosed herein for generating dynamic vocabularies for conditioning a language model. A dynamic vocabulary is constructed from an input prompt, database schema information for a database to be queried, and programming language information for a programming language to be used for querying the database to condition the language model to predict an output statement in the programming language. The dynamic vocabulary can be included in prompt information that is provided to the language model. The number of tokens in the dynamic vocabulary can be different than a number of tokens included in a vocabulary of the language model. By utilizing a dynamic vocabulary, the language model can be conditioned to predict tokens for the output statement that are contextually consistent with the tokens included the dynamic vocabulary.

Abstract: Coordinating processing of audio queries is provided. A system receives a query. The system provides the query to a first digital assistant component and a second digital assistant component for processing. The system receives a first response to the query from the first digital assistant component, and a second response to the query from the second digital assistant component. The first digital assistant component can be authorized to access a database the second digital assistant component is prohibited from accessing. The system determines, based on a ranking decision function, to select the second response to the query from the second digital assistant component. The system provides, responsive to the selection, the second response from the second digital assistant to a computing device.

Abstract: The present disclosure relates to a custom framework for fine-grained human activity recognition. One or more input videos may be accessed, where the one or more input videos comprise one or more frames depicting one or more actors and one or more objects. A plurality of object-pose interaction graphs may be generated for individual frames from the one or more input videos based at least in part on one or more objects of interest from the one or more objects and on one or more joint keypoints of the one or more actors. A first graph neural network may be trained based at least in part on the plurality of object-pose interaction graphs to identify spatial information for the one or more actors, the one or more objects of interest, and one or more interactions between the one or more actors and the one or more objects of interest.

Abstract: Embodiments herein relate to a flip-flop circuit which uses a single clock signal for both the primary and secondary latches with either a “0” or a “1” being used to write into the primary latch and either a “1” or a “0,” respectively, being used to write into the secondary latch. The flip-flop can retain the data as long as the power supply is available. Additionally, the flip-flop conserves power by disconnecting one or more paths to power or ground automatically based upon the data that is being stored, thus reducing the leakage current during a storage mode of operation.

Abstract: Techniques are described for routing a customer communication to an agent having appropriate expertise to handle the current communication associated with a customer using one or more machine learning models. For example, a computing system includes a memory and one or more processors in communication with the memory. The one or more processors are configured to: receive a set of emotion factor values for communication data of the current communication; generate, using a composite emotion model running on the one or more processors, a composite emotional score for the current communication based on the set of emotion factor values for the current communication; determine a routing recommendation for the current communication that identifies an agent having appropriate expertise to handle the current communication based on at least the composite emotional score; and route the current communication in accordance with the routing recommendation to a computing device of the agent.

Abstract: A method may include receiving a primary document including one or more selection boxes, one or more text lines, and one or more annotations. The method may include determining, a class based on the annotations. The method may include identifying the one or more selection boxes and one or more text lines of the primary document. The method may include generating a graph representing the one or more selection boxes and the one or more text lines. The method may include mapping each of the one or more selection boxes to a respective text line of the one or more text lines of the graph based at least in part on one or more characteristics associated with the selection boxes. The method may include generating a key-value pair associated with each of the one or more text lines and generating a document model of the primary document.

Abstract: A method may include detecting one or more selection boxes and one or more text lines in a primary document. The method may include determining respective vectors associated with the selection box and adjacent text lines to the selection box in a plurality of directions. The method may include determining a set of respective vectors associated with a unique selection box. The method may include determining a variance between respective vectors in the set of respective vectors and identifying a particular direction corresponding to a minimal variance between the respective vectors in the set of respective vectors as compared to a variance of other sets of respective vectors. The method may include generating a key-value pair based on the set of respective vectors characterized by the minimal variance. The method may include generating a document model, including the key-value pair, and extracting data according to the document model.

Abstract: A method comprising: dividing a 3D space into a voxel grid comprising a plurality of voxels; associating a plurality of distance values with the plurality of voxels, each distance value based on a distance to a boundary of an object; selecting an approximate interpolation mode for stepping a ray through a first one or more voxels of the 3D space responsive to the first one or more voxels having distance values greater than a threshold; and detecting the ray reaching a second one or more voxels having distance values less than the first threshold; and responsively selecting a precise interpolation mode for stepping the ray through the second one or more voxels.

Abstract: Techniques are described for generating a set of emotion factor values using one or more machine learning models for customer communications. For example, a computing system includes one or more processors in communication with a memory. The one or more processors are configured to receive communication data of a current communication associated with a customer, apply the communication data to an emotion-based indexer as input wherein the emotion-based indexer includes a set of machine-learning models for a set of emotion factors, generate as output from the emotion-based indexer a set of emotion factor values for the current communication wherein each emotion factor value indicates the measure of a particular emotion factor in the current communication, apply the set of emotion factor values to an emotion classification model, and classify the current communication into an emotion state based on the set of emotion factor values.

Abstract: A method comprising: dividing a 3D space into a voxel grid comprising a plurality of voxels; associating a plurality of distance values with the plurality of voxels, each distance value based on a distance to a boundary of an object; selecting an approximate interpolation mode for stepping a ray through a first one or more voxels of the 3D space responsive to the first one or more voxels having distance values greater than a threshold; and detecting the ray reaching a second one or more voxels having distance values less than the first threshold; and responsively selecting a precise interpolation mode for stepping the ray through the second one or more voxels.

Abstract: Techniques are described herein for generating block extender model. An example method includes a system accessing a base model trained for identifying a base class. The system can access an extender comprising block extenders, the extender class distinct from the base class. The system can connect the extender with the base model to generate an augmented model. The system can input training data to the augmented model, the training data is provided to the base model and the extender, the training data comprising data points associated with the extender class. The system can train the extender model to identify the extender class based at least in part on the training data and the signal received from the base machine learning model. The system can generate a trained extender based at least in part on the training, the extender trained to identify an object associated with the extender class.

Abstract: The present disclosure is directed to a technique for reduction of latency in network traffic data transmissions. The method includes: parsing an online document to determine a messaging identifier used to communicate over an asynchronous network-based communication channel between a computing device and a content provider device; pinging, via the asynchronous network-based communication channel, the content provider device corresponding to the messaging identifier; receiving, from the content provider device, a response to the pinging; verifying, based on the response, whether the content provider device is operational to receive electronic messages over the asynchronous network-based communication channel; and authorizing, responsive to verification of the content provider device, a content generator component to insert the messaging identifier in one or more instances of an online content item.

Abstract: Systems and methods for message delivery prioritization that can include receiving, via an application programming interface, a messaging request of an entity to transmit one or more messages to a plurality of users, selecting one or more message transmission options based on message-associated delivery attributes, and causing the one or more messages to be transmitted to the plurality of users using the selected one or more message transmission options.

Abstract: A method includes, using a processor, identifying a septum and a Left Atrium Appendage (LAA) of a heart of a patient in an anatomical map of at least part of the heart. An entry surface over which a medical device is defined on the anatomical map, which is to be delivered via a sheath that penetrates the septum, is to engage with the LAA. A normal to the entry surface is calculated. A plurality of curves is calculated that each (i) have one end that is tangent to the normal, (ii) have a second end touching the septum, and (iii) comply with specified mechanical properties of the sheath. Multiple candidate locations on the septum are derived from the curves, for transseptal puncture with the sheath. The multiple candidate locations are presented to a user.

Abstract: Techniques for extracting information from unstructured documents that enable an ML model to be trained such that the model can accurately distinguish in-distribution (“in-D”) elements and out-of-distribution (“OO-D”) elements within an unstructured document. Novel training techniques are used that train an ML model using a combination of a regular training dataset and an enhanced augmented training dataset. The regular training dataset is used to train an ML model to identify in-D elements, i.e., to classify an element extracted from a document as belonging to one of the in-D classes contained in the regular training dataset. The augmented training dataset, which is generated based upon the regular training dataset may contain one or more augmented elements which are used to train the model to identify OO-D elements, i.e., to classify an augmented element extracted from a document as belonging to an OO-D class instead of to an in-D class.

Abstract: Embodiments herein relate to a multi-bit flip-flop circuit which uses unidirectional transistors to allow sharing of transistors among a set of flip-flops, while avoiding charge sharing within or between the flip-flops. Clock devices in the circuit can be shared to reduce the clock transistor gate capacitance and associated power consumption. The shared transistors can provide keeper circuits and/or tri-state inverters in a primary latch and a secondary latch in each flip-flop. One example implementation uses tri-state keeper sharing. Another example implementation uses tri-state keeper and/or pass gate sharing. Another example implementation uses pass gate sharing and no keeper.

Abstract: Techniques are described for personalizing customer interactions using one or more machine learning models for customer communications. For example, a computing system includes a memory and one or more processors in communication with the memory. The one or more processors are configured to: retrieve, from a database in memory, one or more sets of emotion factor values for communication data associated with a customer over time; classify, using an emotion propensity model running on the one or more processors, the customer into an emotional profile according to the customer's typical emotional response during customer communications based on the one or more sets of emotion factor values for the communication data associated with the customer over time; and determine a probability that the customer will respond positively to a particular type of customer engagement based on the emotional profile for the customer.

Abstract: In some aspects, the techniques described herein relate to a method including: receiving a request from a client device to join a room, the room associate with a plurality of other client devices streaming multimedia content; adding the client device to the room in response to the request; computing a synchronization time for the client based on time values associated with the client device and the other client devices; and transmitting the synchronization time to the client device, causing the client device to adjust playback of the multimedia content based on the synchronization time.