Abstract: Various embodiments of the present disclosure relate to operator assistance based on extracting natural language characters from one or more sensed objects. For instance, particular embodiments may generate a natural language utterance based on extracting natural language text in a nearby traffic sign. In an illustrative example, particular embodiments may detect, via object detection and within image data, one or more regions of the image data depicting the traffic sign. Particular embodiments can then extract one or more first natural language characters represented in the traffic sign based at least on performing optical character recognition within the one or more regions of the image data in response to detecting the one or more regions of the image data depicting the traffic sign.

Abstract: Various embodiments of the present disclosure relate to operator assistance based on operator monitoring. For instance, during long drives, a driver may become drowsy or may not otherwise be alert. As such, particular embodiments have the capability of starting a conversation with the driver based on driver interests and/or detecting that the driver is getting drowsy. In an illustrative example, a Driver Monitoring System (DMS) camera of a vehicle may employ a component that derives pixel-level information showing head nodding, hands dropping, or the like. Based on image pattern characteristics in the image data, particular embodiments generate a score representing an alertness level. A representation of the alertness level can be provided as input to a machine learning model so that the model may generate a suitable natural language or other response, such as starting a conversation with personalized trivia, sending a control signal to honk a horn, or the like.

Abstract: In various examples, infrared image data may be used to detect a subcutaneous characteristic(s) (e.g., a palm vein topology) of a person (e.g., a person requesting entry to a vehicle, a vehicle occupant) and authenticate the user based on the detected subcutaneous characteristic(s). For example, infrared image data representing one or more acquired subcutaneous characteristics (e.g., a topology of veins and/or other blood vessels in a region of the authenticating user's palm, hand, neck, forearm, face, fingertip, eye, etc.) may be generated. Hand and/or palm detection may be applied to detect a region depicting the user's hand or palm, and that region (or some subset thereof) may be segmented to generate a representation of an acquired vein topology. The acquired vein topology may be compared with one or more reference vein topologies stored in a database to determine whether the acquired vein topology matches one of the reference vein topologies.

Abstract: A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.

Abstract: In various examples, a virtually animated and interactive agent may be rendered for visual and audible communication with one or more users with an application. For example, a conversational artificial intelligence (AI) assistant may be rendered and displayed for visual communication in addition to audible communication with end-users. As such, the AI assistant may leverage the visual domain—in addition to the audible domain—to more clearly communicate with users, including interacting with a virtual environment in which the AI assistant is rendered. Similarly, the AI assistant may leverage audio, video, and/or text inputs from a user to determine a request, mood, gesture, and/or posture of a user for more accurately responding to and interacting with the user.

Abstract: Systems and methods for a self-adjusting vehicle mirror. The mirror automatically locates the face of the driver or another passenger, and orients the mirror to provide the driver/passenger face with a desired view from the mirror. The mirror may continue to reorient itself as the driver or passenger shifts position, to continuously provide a desired field of view even as he or she changes position over time. In certain embodiments, the mirror system of the disclosure can be a self-contained system, with the mirror, mirror actuator, camera, and computing device all contained within the mirror housing as a single integrated unit.

Abstract: In various examples, a virtually animated and interactive agent may be rendered for visual and audible communication with one or more users with an application. For example, a conversational artificial intelligence (AI) assistant may be rendered and displayed for visual communication in addition to audible communication with end-users. As such, the AI assistant may leverage the visual domain—in addition to the audible domain—to more clearly communicate with users, including interacting with a virtual environment in which the AI assistant is rendered. Similarly, the AI assistant may leverage audio, video, and/or text inputs from a user to determine a request, mood, gesture, and/or posture of a user for more accurately responding to and interacting with the user.

Abstract: In various examples, low power proximity based threat detection using optical flow for vehicle systems and applications are provided. Some embodiments may use a tiered framework that uses sensor fusion techniques to detect and track the movement of a threat candidate, and perform a threat classification and/or intent prediction as the threat candidate approaches approach. Relative depth indications from optical flow, computed using data from image sensors, can be used to initially segment and track a moving object over a sequence of image frames. Additional sensors and processing may be brought online when a moving object becomes close enough to be considered a higher risk threat candidate. A threat response system may generate a risk score based on a predicted intent of a threat candidate, and when the risk score exceeds a certain threshold, then the threat response system may respond accordingly based on the threat classification and/or risk score.

Abstract: In various examples, systems and methods of the present disclosure combine open and closed dialog systems into an intelligent dialog management system. A text query may be processed by a natural language understanding model trained to associate the text query with a domain tag, intent classification, and/or input slots. Using the domain tag, the natural language understanding model may identify information in the text query corresponding to input slots needed for answering the text query. The text query and related information may then be passed to a dialog manager to direct the text query to the proper domain dialog system. Responses retrieved from the domain dialog system may be provided to the user via text output and/or via a text to speech component of the dialog management system.

Abstract: In various examples, systems and methods of the present disclosure combine open and closed dialog systems into an intelligent dialog management system. A text query may be processed by a natural language understanding model trained to associate the text query with a domain tag, intent classification, and/or input slots. Using the domain tag, the natural language understanding model may identify information in the text query corresponding to input slots needed for answering the text query. The text query and related information may then be passed to a dialog manager to direct the text query to the proper domain dialog system. Responses retrieved from the domain dialog system may be provided to the user via text output and/or via a text to speech component of the dialog management system.

Abstract: Apparatuses, systems, and techniques to enable optimizations in storage and processing of media based on identification of repititions between two or more media content. In at least one embodiment, one or more repition of content is identified based on properties of media included.

Abstract: In various examples, systems and methods that use dialogue systems associated with various machine systems and applications are described. For instance, the systems and methods may receive text data representing speech, such as a question associated with a vehicle or other machine type. The systems and methods then use a retrieval system(s) to retrieve a question/answer pair(s) associated with the text data and/or contextual information associated with the text data. In some examples, the contextual information is associated with a knowledge base associated with or corresponding to the vehicle. The systems and methods then generate a prompt using the text data, the question/answer pair(s), and/or the contextual information. Additionally, the systems and methods determine, using a language model(s) and based at least on the prompt, an output associated with the text data. For instance, the output may include information that answers the question associated with the vehicle.

Abstract: In various examples, techniques for using scene-aware context for dialogue systems and applications are described herein. For instance, systems and methods are disclosed that process audio data representing speech in order to determine an intent associated with the speech. Systems and methods are also disclosed that process sensor data representing at least a user in order to determine a point of interest associated with the user. In some examples, the point of interest may include a landmark, a person, and/or any other object within an environment. The systems and methods may then generate a context associated with the point of interest. Additionally, the systems and methods may process the intent and the context using one or more language models. Based on the processing, the language model(s) may output data associated with the speech.

Abstract: A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.

Abstract: Approaches for an advanced AI-assisted vehicle can utilize an extensive suite of sensors inside and outside the vehicle, providing information to a computing platform running one or more neural networks. The neural networks can perform functions such as facial recognition, eye tracking, gesture recognition, head position, and gaze tracking to monitor the condition and safety of the driver and passengers. The system also identifies and tracks body pose and signals of people inside and outside the vehicle to understand their intent and actions. The system can track driver gaze to identify objects the driver might not see, such as cross-traffic and approaching cyclists. The system can provide notification of potential hazards, advice, and warnings. The system can also take corrective action, which may include controlling one or more vehicle subsystems, or when necessary, autonomously controlling the entire vehicle. The system can work with vehicle systems for enhanced analytics and recommendations.

Abstract: In various examples, systems and methods of the present disclosure combine open and closed dialog systems into an intelligent dialog management system. A text query may be processed by a natural language understanding model trained to associate the text query with a domain tag, intent classification, and/or input slots. Using the domain tag, the natural language understanding model may identify information in the text query corresponding to input slots needed for answering the text query. The text query and related information may then be passed to a dialog manager to direct the text query to the proper domain dialog system. Responses retrieved from the domain dialog system may be provided to the user via text output and/or via a text to speech component of the dialog management system.

Abstract: In various examples, sensor data may be captured by sensors of an ego-object, such as a vehicle traveling in a physical environment, and a representation of the sensor data may be streamed from the ego-object to a remote location to facilitate various remote experiences, such as streaming to a remote viewer (e.g., a friend or relative), streaming to a remote or fleet operator, streaming to a mobile app configured to self-park or summon an ego-object, rendering a 3D augmented reality (AR) or virtual reality (VR) representation of the physical environment, and/or others. In some embodiments, the stream includes one or more command channels used to control data collection, rendering, stream content, or even vehicle maneuvers, such as during an emergency, self-park, or summon scenario.

Abstract: In various examples, systems and methods of the present disclosure combine open and closed dialog systems into an intelligent dialog management system. A text query may be processed by a natural language understanding model trained to associate the text query with a domain tag, intent classification, and/or input slots. Using the domain tag, the natural language understanding model may identify information in the text query corresponding to input slots needed for answering the text query. The text query and related information may then be passed to a dialog manager to direct the text query to the proper domain dialog system. Responses retrieved from the domain dialog system may be provided to the user via text output and/or via a text to speech component of the dialog management system.

Abstract: Approaches provide for performance of a complex (e.g., compound) task that may involve multiple discrete tasks not obvious from an instruction to perform the complex task. A set of conditions for an environment can be determined using captured image data, and the instruction analyzed to determine a set of final conditions to exist in the environment after performance of the instruction. These initial and end conditions are used to determine a sequence of discrete tasks to be performed to cause a robot or automated device to perform the instruction. This can involve use of a symbolic or visual planner in at least some embodiments, as well as a search of possible sequences of actions available for the robot or automated device. A robot can be caused to perform the sequence of discrete tasks, and feedback provided such that the sequence of tasks can be modified as appropriate.

Abstract: In various examples, a conversational artificial intelligence (AI) platform uses structured data and unstructured data to generate responses to queries from users. In an example, if data for a response to a query is not stored in a structured data structured, the conversational AI platform searches for the data in an unstructured data structure.