Abstract: Embodiments of the present disclosure provide a system and a method of controlling a robot for autonomous navigation. The method includes receiving a set of point values defining LIDAR data from a LIDAR sensor scanning a 2D omnidirectional plane, receiving a sensor value from an ultrasonic sensor having a 3D field of view excluding the plane, and resolving an observable field of view for the LIDAR sensor, where the observable field of view includes a blind spot of the LIDAR sensor, and modifying the LIDAR data using the sensor value based on the object being located in the blind spot indicated by the sensor value less than one or more point values corresponding to a portion of the plane extending along the observable field of view, where the modified LIDAR data indicates the object being detected by the LIDAR sensor despite the object located outside the 2D field of view.

Abstract: Embodiments of the present disclosure provide a system and a method of controlling a robot for autonomous navigation. The method includes receiving a set of point values defining LIDAR data from a LIDAR sensor scanning a 2D omnidirectional plane, receiving a sensor value from an ultrasonic sensor having a 3D field of view excluding the plane, and resolving an observable field of view for the LIDAR sensor, where the observable field of view includes a blind spot of the LIDAR sensor, and modifying the LIDAR data using the sensor value based on the object being located in the blind spot indicated by the sensor value less than one or more point values corresponding to a portion of the plane extending along the observable field of view, where the modified LIDAR data indicates the object being detected by the LIDAR sensor despite the object located outside the 2D field of view.

Abstract: Methods and apparatuses are described in which unstructured computer text is analyzed for generation of customized digital documents. A server tokenizes and encodes historical user interactions and historical digital documents into multidimensional vectors. The server trains an interaction classification model using the multidimensional vectors as input to generate a classification for an input user interaction, and trains a language generation model using the multidimensional vectors as input to generate a customized digital document based upon an input user interaction. The server receives a new user interaction and encodes the new user interaction into a new multidimensional vector. The server executes the trained interaction classification model using the new vector as input to generate a digital document classification. The server executes the trained language generation model using the new vector and the classification as input to generate a customized digital document.

Abstract: An AI platform to enable one or more users to design and create AI enabled applications is provided. The AI platform comprises a data module configured to condition data received from a plurality of data sources to generate a corresponding data pipeline; wherein the data module comprises a plurality of reusable data components. The AI platform further comprises an intelligent processing module configured to process a plurality of datasets received on the data pipeline and generate a corresponding artificial intelligence (AI) pipeline; wherein the intelligent processing module comprises a plurality of reusuable data processing components.

Abstract: Embodiments of the present disclosure provide a system and a method of controlling a robot for autonomous navigation. The method includes receiving a set of point values defining LIDAR data from a LIDAR sensor scanning a 2D omnidirectional plane, receiving a sensor value from an ultrasonic sensor having a 3D field of view excluding the plane, and resolving an observable field of view for the LIDAR sensor, where the observable field of view includes a blind spot of the LIDAR sensor, and modifying the LIDAR data using the sensor value based on the object being located in the blind spot indicated by the sensor value less than one or more point values corresponding to a portion of the plane extending along the observable field of view, where the modified LIDAR data indicates the object being detected by the LIDAR sensor despite the object located outside the 2D field of view.

Abstract: Methods and apparatuses are described in which unstructured computer text is analyzed for generation of customized digital documents. A server tokenizes and encodes historical user interactions and historical digital documents into multidimensional vectors. The server trains an interaction classification model using the multidimensional vectors as input to generate a classification for an input user interaction, and trains a language generation model using the multidimensional vectors as input to generate a customized digital document based upon an input user interaction. The server receives a new user interaction and encodes the new user interaction into a new multidimensional vector. The server executes the trained interaction classification model using the new vector as input to generate a digital document classification. The server executes the trained language generation model using the new vector and the classification as input to generate a customized digital document.

Abstract: An AI platform to enable one or more users to design and create AI enabled applications is provided. The AI platform comprises a data module configured to condition data received from a plurality of data sources to generate a corresponding data pipeline; wherein the data module comprises a plurality of reusable data components. The AI platform further comprises an intelligent processing module configured to process a plurality of datasets received on the data pipeline and generate a corresponding artificial intelligence (AI) pipeline; wherein the intelligent processing module comprises a plurality of reusuable data processing components.