Abstract: A computer-implemented method comprising receiving user preference information, based on the received user preference information, determining one or more user settings, processing data to determine a data condition, wherein, to determine the data condition, a plurality of alternate data inputs of different types are processed and normalized, and applied to a series of operations to generate a forecast having a degree of confidence, and the data condition is compared with third party information; providing an electronic notification indicative of the data condition to the user device, wherein the electronic notification includes the data condition compared with the third party information, a confidence indicator associated with the data condition, and a user prompt; in response to a single user input, the user device generating an instruction to execute the user request; and based on the instruction, executing the user request based on the determined one or more user settings.

Abstract: Systems and method for use in assisting a user in data aggregation tasks. A system determines the type of data needed by the user to complete the data aggregation task and, based on an indication of the data needed, queries multiple data sources. The results from the multiple data sources are then collated and aligned as necessary. Inconsistencies in the data are resolved or flagged to the user for attention. A completed form or a presentation set of data is then presented to the user for validation.

Abstract: Systems and methods for routing a document based on the contents of this document. The content of this document is first subjected to a recognition process and then the result is subjected to multiple types of analysis. Based on the results of the analysis (including contextual analysis), a destination is determined along with any timelines detailed in the document. As well, a severity of the document, indicating the severity of consequences if the document is not handled quickly, is determined. Based on these, an urgency tag and/or a severity tag are assigned to the document. A final destination is determined based on the output of the analysis of the severity, the urgency, and of the destination.

Abstract: Systems and methods for automatically applying style characteristics to images. The images may comprise text. Additionally, the images may be synthetically generated. A style template containing information about style characteristics is passed to an extraction module, which extracts that information and thus determines the style characteristics. The style characteristics are then passed to an application module, which also receives an input image. The application module applies the style characteristics to the image, thereby producing an output image in the intended style. The extraction module and the application module may comprise machine learning elements. The output image may be used in later processes, including, among others, in training processes for optical character recognition models.

Abstract: Described herein is a memory architecture that is configured to dynamically determine an address encoding to use to encode multi-dimensional data such as multi-coordinate data in a manner that provides a coordinate bias corresponding to a current memory access pattern. The address encoding may be dynamically generated in response to receiving a memory access request or may be selected from a set of preconfigured address encodings. The dynamically generated or selected address encoding may apply an interleaving technique to bit representations of coordinate values to obtain an encoded memory address. The interleaving technique may interleave a greater number of bits from the bit representation corresponding to the coordinate direction in which a coordinate bias is desired than from bit representations corresponding to other coordinate directions.

Abstract: Deterministic memory allocation for real-time applications. In an embodiment, bitcode is scanned to detect calls by a memory allocation function to a dummy function. Each call uses parameters comprising an identifier of a memory pool and a size of a data type to be stored in the memory pool. For each detected call, an allocation record, comprising the parameters, is generated. Then, a header file is generated based on the allocation records. The header file may comprise a definition of bucket(s) and a definition of memory pools. Each definition of a memory pool may identify at least one bucket.

Abstract: A surveillance system is coupled to a plurality of sensor data sources arranged at locations within a plurality of regions of a site under surveillance. The surveillance system accesses a threat model that identifies contextual events classified as threats. The surveillance system identifies at least one contextual event for a site in real-time by processing sensor data generated by the sensor data sources, and co-occurring contextual data for at least one of the regions. Each identified contextual event is classified as one of a threat and a non-threat by using the threat model.

Abstract: Systems and methods for managing a supply chain. A multi-stage system receives data regarding different components and parts of a supply chain. These data points are formatted, streamed, and classified into a multitude of analysis modules that predictively assess potential problems in the supply chain. Identified potential problems are then further classified, ranked, and routed to relevant users who need to be informed of the potential problems. These users can then implement mitigating actions that mitigate if not prevent the consequences of these potential problems in the supply chain.

Abstract: A method and a system for generating an abstractive summary of a document using an abstractive machine learning algorithm (MLA) and a method and a system for training the abstractive MLA. A document including a plurality of text sequences is received. An extractive summary of the document is generated, the extractive summary including a set of summary text sequences which is a subset of the plurality of text sequences. The abstractive MLA generates, based on the set of summary text sequences and at least a portion of the plurality of text sequences, an abstractive summary of the document including a set of abstractive text sequences, at least one abstractive text sequence not being included in the plurality of text sequences. In some aspects, the extractive summary is generated by an extractive MLA having been trained to generate extractive summaries.

Abstract: A smart makeup mirror device having a display and integrating with an artificial intelligence voice assistant, including: a main body; a display mirror unit rotatably mounted on the main body; and a speaker mounted in the main body to output a sound, where the display mirror unit includes: a display module that outputs an image by implementing a preset display mode based on a voice signal or a touch signal of a user; and a makeup mirror in which a portion of the makeup mirror is configured to reflect a light and another portion of the makeup mirror is configured to transmit an image output from the display module, where the main body includes: a mounting portion configured to hang on a wall space.

Abstract: A smart makeup mirror device having a display and integrating with an artificial intelligence voice assistant, including: a main body; a display mirror unit rotatably mounted in the main body; and a speaker mounted in the main body to output a sound, where the display mirror unit includes: a leg configured to be docked at the main body; a display module that outputs an image by implementing a preset display mode based on a voice signal or a touch signal of a user; and a makeup mirror in which a portion of the makeup mirror is configured to reflect a light and another portion of the makeup mirror is configured to transmit an image output from the display module, and where an insertion groove where leg can be inserted is provided in the upper portion of the main body.

Abstract: Systems and methods are directed to obtaining autonomous vehicle sensor data of an autonomous vehicle. In these system and methods that include determining a direction of motion of a vehicle based on a predicted navigational position of the vehicle, determining, based at least in part on the predicted navigational position, a change in a future light positional information that may be received by one or more sensors compared to a current light positional information being received by the one or more sensors and cleaning the one or more sensors of the vehicle prior to the change in the future light positional information and prior to the vehicle reaching the predicted navigational position.

Abstract: Systems, methods, and non-transitory computer-readable media are provided for implementing a preemptive suspension control for an autonomous vehicle to improve ride quality. Data from one or more sensors onboard the autonomous vehicle can be acquired. A surface imperfection of a road can be identified from the data. A next action for the autonomous vehicle can be determined based on the road condition. A signal can be outputted that causes the autonomous vehicle to act in accordance with the next action after adjusting the suspension preemptively.

Abstract: Systems and methods are disclosed for receiving one or more digital images associated with a tissue specimen, detecting one or more image regions from a background of the one or more digital images, determining a prediction, using a machine learning system, of whether at least one first image region of the one or more image regions comprises at least one external contaminant, the machine learning system having been trained using a plurality of training images to predict a presence of external contaminants and/or a location of any external contaminants present in the tissue specimen, and determining, based on the prediction of whether a first image region comprises an external contaminant, whether to process the image region using an processing algorithm.

Abstract: Systems and methods are disclosed for receiving digital images of a pathology specimen from a patient, the pathology specimen comprising tumor tissue, the one or more digital images being associated with data about a plurality of biomarkers in the tumor tissue and data about a surrounding invasive margin around the tumor tissue; identifying the tumor tissue and the surrounding invasive margin region to be analyzed for each of the one or more digital images; generating, using a machine learning model on the one or more digital images, at least one inference of a presence of the plurality of biomarkers in the tumor tissue and the surrounding invasive margin region; determining a spatial relationship of each of the plurality of biomarkers identified in the tumor tissue and the surrounding invasive margin region to themselves and to other cell types; and determining a prediction for a treatment outcome and/or at least one treatment recommendation for the patient.

Abstract: The technology disclosed provides systems and methods related to preventing exfiltration of training data by feature reconstruction attacks on model instances trained on the training data during a training job. The system comprises a privacy interface that presents a plurality of modulators for a plurality of training parameters. The modulators are configured to respond to selection commands via the privacy interface to trigger procedural calls. The procedural calls modify corresponding training parameters in the plurality of training parameters for respective training cycles in the training job. The system comprises a trainer configured to execute the training cycles in dependence on the modified training parameters. The trainer can determine a performance accuracy of the model instances for each of the executed training cycles.

Abstract: Systems and methods for privacy and sensitive data protection. An image of a document is received at a pre-processing stage and image pre-processing is applied to the image to ensure that the resulting image is sufficient for further processing. Pre-processing may involve processing relating to image quality and image orientation. The image is then passed to an initial processing stage. At the initial processing stage, the relevant data in the document are located and bounding boxes are placed around the data. The resulting image is then passed to a processing stage. At this stage, the type of data within the bounding boxes is determined and suitable replacement data is generated. The replacement data is then inserted into the image to thereby remove and replace the sensitive data in the image.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for explainable machine learning. In one aspect, a method comprises: obtaining a collection of data elements characterizing an entity; generating a plurality of features that collectively define a feature representation of the entity from the collection of data elements characterizing the entity; processing the feature representation of the entity using a machine learning model to generate a prediction for the entity; generating evidence data characterizing data elements from the collection of data elements that explain the prediction generated by the machine learning model for the entity; and providing an output comprising the prediction for the entity and the evidence data characterizing data elements from the collection of data elements that explain the prediction for the entity.

Abstract: A method of delivering advertising in an online environment includes determining a context of a user operating a client computer to interact with an e-commerce website, where the determined context representing an intent of the user to locate a product for purchase, defining a relation between one or more of a plurality of advertisements and the product based on at least one of a plurality of relevance types, and displaying, to the user, at least one of the advertisements having the relation to the product.

Abstract: A method of delivering advertising in an online environment includes determining a context of a user operating a client computer to interact with an e-commerce website, where the determined context representing an intent of the user to locate a product for purchase, defining a relation between one or more of a plurality of advertisements and the product based on at least one of a plurality of relevance types, and displaying, to the user, at least one of the advertisements having the relation to the product.