Abstract: A deep neural network(s) (DNN) may be used to perform panoptic segmentation by performing pixel-level class and instance segmentation of a scene using a single pass of the DNN. Generally, one or more images and/or other sensor data may be stitched together, stacked, and/or combined, and fed into a DNN that includes a common trunk and several heads that predict different outputs. The DNN may include a class confidence head that predicts a confidence map representing pixels that belong to particular classes, an instance regression head that predicts object instance data for detected objects, an instance clustering head that predicts a confidence map of pixels that belong to particular instances, and/or a depth head that predicts range values. These outputs may be decoded to identify bounding shapes, class labels, instance labels, and/or range values for detected objects, and used to enable safe path planning and control of an autonomous vehicle.

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: Examples are disclosed herein that are related to providing extended functionalities on-demand to an audio-based wearable device. One example provides a wearable computing device including an acoustic receiver configured to receive speech inputs, a speaker configured to present audio outputs, a communications subsystem configured to connect to an external device, a logic subsystem configured to execute instructions, and a storage subsystem having instructions executable by the logic subsystem to execute a program, connect to the external device via a wireless communications protocol, conduct an audio-based interaction of the program via the speech inputs received at the acoustic receiver and the audio outputs provided by the speaker, upon reaching a screen-based interaction of the program, notify a user via the speaker to interact with the external device, and provide image data to the external device for presentation via a screen of the external device.

Abstract: Various embodiments related to entering text into a computing device via eye-typing are disclosed. For example, one embodiment provides a method that includes receiving a data set including a plurality of gaze samples, each gaze sample including a gaze location and a corresponding point in time. The method further comprises processing the plurality of gaze samples to determine one or more likely terms represented by the data set.

Abstract: Various embodiments related to entering text into a computing device via eye-typing are disclosed. For example, one embodiment provides a method that includes receiving a data set including a plurality of gaze samples, each gaze sample including a gaze location and a corresponding point in time. The method further comprises processing the plurality of gaze samples to determine one or more likely terms represented by the data set.

Abstract: Various embodiments related to entering text into a computing device via eye-typing are disclosed. For example, one embodiment provides a method that includes receiving a data set including a plurality of gaze samples, each gaze sample including a gaze location and a corresponding point in time. The method further comprises processing the plurality of gaze samples to determine one or more likely terms represented by the data set.

Abstract: Various embodiments related to entering text into a computing device via eye-typing are disclosed. For example, one embodiment provides a method that includes receiving a data set including a plurality of gaze samples, each gaze sample including a gaze location and a corresponding point in time. The method further comprises processing the plurality of gaze samples to determine one or more likely terms represented by the data set.