Abstract: The present disclosure relates to for managing the generation or deletion of record objects based on electronic activities and communication policies. Data of a plurality of electronic activities from one or more electronic accounts of the entity may be identified. It may be determined whether the identified data satisfies a communication policy. The communication policy may include one or more rules based on the electronic activities. Instructions to generate a contact record object or instructions to delete an existing contact record for the entity may be transmitted based on the condition of the communication of the communication policy that is satisfied.

Abstract: A method for standardized model interaction can include: determining a model composition, receiving an input, converting the input into a standard object, converting the standard input object into a model-specific input (MSI) object, executing the model using the MSI object, converting the output from the model-specific output (MSO) object to a standard object, repeating previous steps for each successive model within the model composition, and providing a final model output.

Abstract: The present disclosure relates to linking record objects between systems of record based on a comparison of object field-value pairs to a ground truth. A domain name may be identified from an electronic activity. It may be determined that the electronic activity does not match with any first record objects. A second record object including the domain name as a value may be identified. Object field-value pairs of the second record object may be identified. It may be determined that a third record object matches with the second record object. The electronic activity may be matched to the third second record object or a fourth record object. An association between the electronic activity and the third record object or the fourth record object may be stored.

Abstract: A system receives a plurality of knowledge objects (KOs). The system receives repository structure definition information, the repository structure definition information specifying one or more repository structure definitions that define respective structures for the one or more data repositories. The system groups the plurality of KOs based on the name, type, and tag attributes of the KOs, and storage paths of the underlying unit of structured, semi-structured, and unstructured data at the one or more data repositories corresponding to the KOs to generate a number of groups of KOs. For each group in the groups of KOs, the system determines a count of KOs in the group. The system generates multiple mapping structures with M to N relationships between the groups of KOs to the one or more repository structure definitions, the mapping relationship including the count of associated KOs.

Abstract: A media presentation system includes a page editor enabling the embedding of clips into pages for documenting meetings. The media presentation system is represented by a bot that attends the meetings with recording controls being provided in the pages.

Abstract: This disclosure provides methods for providing information about a person based on facial recognition and various applications thereof, including face-based check-in, face-based personal identification, face-based identification verification, face-based background checks, facial data collaborative network, correlative face search, and personal face-based identification. The disclosed methods are able to provide accurate information about a person in a real-time manner.

Abstract: A method includes uniquely training, using a processing device, one or more deep learning models using one or more sets of training data associated with a plurality of patients to predict immunotherapy treatment responses indicative of a patient survival rate based on a change in volume of a lesion of a patient. The method includes providing a single pre-treatment image of a target lesion of a target patient to the one or more deep learning models that are uniquely trained using the sets of training data to generate the immunotherapy treatment responses. The method includes combining the immunotherapy treatment responses of the one or more deep learning models that are uniquely trained using the sets of training data to generate a predicted treatment response score.

Abstract: Techniques are disclosed for analyzing and learning behavior in an acquired stream of video frames. In one embodiment, a trajectory analyzer clusters trajectories of objects depicted in video frames and builds a trajectory model including the trajectory clusters, a prior probability of assigning a trajectory to each cluster, and an intra-cluster probability distribution indicating the probability that a trajectory mapping to each cluster is least various distances away from the cluster. Given a new trajectory, a score indicating how unusual the trajectory is may be computed based on the product of the probability of the trajectory mapping to a particular cluster and the intra-cluster probability of the trajectory being a computed distance from the cluster. The distance used to match the trajectory to the cluster and determine intra-cluster probability is computed using a parallel Needleman-Wunsch algorithm, with cells in antidiagonals of a matrix and connected sub-matrices being computed in parallel.

Abstract: Systems and methods may utilize a predictive analysis model to analyze a contract or other document. A system may parse a document and/or a repository of information associated with the document. The system may identify one or more terms in the document and corresponding terms in the repository. The system may determine a difference parameter between a first term extracted from the document and a second term extracted from the repository. The system may determine whether the difference between the first term and the second term, represented by the difference parameter, is likely to be acceptable to the user using a predictive analysis model. The system may report a validation parameter indicating a level of acceptability associated with the difference. User feedback on the accuracy of the predictive analysis model is used to train, modify, and improve the predictive analysis model.

Abstract: Described herein are DC-DC converters with a ratio of the power output to volume of at least 2 kW per liter or even at least 4 kW per liter. Such DC-DC converters can operate at power levels of at least 150 kW or even at least 200 kW. A DC-DC converter comprises an enclosure and a front plate sealed against the enclosure using a set of fasteners. The DC-DC converter also comprises a converter unit comprising a switching sub-module, a diode sub-module, and an inductor as well as an additional converter unit comprising an additional switching sub-module, an additional diode sub-module, and an additional inductor. The switching sub-module and the additional switching sub-module or, more generally, the converter unit and the additional converter unit are configured to operate out of phase. The inductors are immersed cooled, the switching sub-modules are conductively cooled, while the diode sub-modules are convectively cooled.

Abstract: Described herein are battery modules comprising immersion-cooled prismatic battery cells and methods of fabricating thereof. A battery module comprises prismatic battery cells that are stacked along the primary module axis. The module also comprises top, bottom, and side covers and two end plates, collectively enclosing these battery cells. Each cover forms two fluid channels, both fluidically open to the prismatic battery cells. Furthermore, the module comprises bus bars that interconnect the cell terminals and protrude into the fluid channels formed by the top cover. One end plate comprises two fluid ports for connecting to a thermal management system. Each port is fluidically coupled to one fluid channel, formed by the top cover, and one fluid channel, formed by the bottom cover. The other end plate fluidically couples the two fluid channels, formed by the top cover, and, separately, the two fluid channels, formed by the bottom cover.

Abstract: The present disclosure relates generally to the generation and deployment of a machine learning-enabled decision engine (MLDE). The MLDE includes decision options that are composed of a discrete list of selectable options. Further, the MLDE includes data inputs that can be used to influence decisions made by the machine learning models of the MLDE. Controls are applied to the MLDE to overlay and bound the decisioning within guidelines established by an operator of the MLDE. Once the MLDE is established, the MLDE is validated and deployed for use by software applications to make decisions.

Abstract: An input dataset is sorted into a first version of data and a second version of data. The first version of data is associated with a first period of time and the second version of data is associated with a second period of time. The second period of time is a shorter period of time than the first period of time. A first set of one or more machine learning models is generated based on the first version of data. A second set of one or more machine learning models is generated based on the second version of data. The first set of one or more machine learning models and the second set of one or more machine learning models are combined to generate an ensemble model. A prediction based on the ensemble model is outputted. The prediction indicates abnormal behavior associated with the input dataset.

Abstract: Various embodiments include methods and devices for transforming a data block into weights for a neural network. Some embodiments may include training a first neural network of a cybernetic engram to reproduce the data block, and replacing the data block in memory with weights used by the first neural network to reproduce the data block.

Abstract: In some examples, the designated set of resources are subsequently monitored for session activities of multiple users that are not of the first group. For each of the multiple users, the computer system utilizes one or more predictive models to determine a likelihood of the user performing a desired type of activity based on one or more session activities detected for that user.

Abstract: Devices, systems, and methods for autonomously separating and sorting a plurality of individual articles from a pile of laundry articles into two or more sorted loads for washing are described. For example, an autonomous sorting and separating system includes a stationary surface configured to receive thereon at a first location the pile of laundry articles. A plurality of actuatable grippers are disposed at spaced apart positions adjacent the stationary surface and comprise a first actuatable gripper configured to grasp, hoist, and deposit at a second location at least one of the plurality of individual articles within reach of a second actuatable gripper. A terminal gripper comprising at least one of the second actuatable gripper and another actuatable gripper is configured to release an individual article into one of the two or more sorted loads. At least one controller is in operable communication with the grippers.

Abstract: A method includes steps of: receiving map data that contains a map of a working area, the map of the working area being at least defined within a closed outer boundary; generating a Voronoi diagram based on the outer boundary, the Voronoi diagram including at least one Voronoi cell having an edge that is composed of a plurality of Voronoi points; selecting at least one of the Voronoi points as a target point; and capturing, at a target location in the working area that corresponds to the target point in the Voronoi diagram, an image of the working area to serve as the visual record.

Abstract: A system for expanding the operational design domain (ODD) of an autonomous agent includes a decision-making platform (equivalently referred to herein as a decision-making architecture). A method for expanding the operational design domain (ODD) includes determining a decision-making architecture for a first domain and adapting the decision-making architecture to a second domain. Additionally or alternatively, the method 200 can include implementing the decision-making architecture S300 and/or any other processes.

Abstract: Systems, methods, and software monitor and identify traffic trends associated with entities in a physical area using multiple video sources. In one implementation a video monitoring system identifies an overhead map that defines a physical area monitored by a plurality of video sources. The video monitoring system further, for each of the video sources, identifies a video stream from the video source, identifies landmark points that map an object in the video stream to an object in the overhead map, and identifies one or more traffic areas in the video stream for movement of one or more entities. The monitoring system also monitors traffic in the video streams, identifies trends from the traffic based on the landmarks and traffic areas, and generates a display of the trends.