Abstract: In various examples, live perception from sensors of a vehicle may be leveraged to generate object tracking paths for the vehicle to facilitate navigational controls in real-time or near real-time. For example, a deep neural network (DNN) may be trained to compute various outputs—such as feature descriptor maps including feature descriptor vectors corresponding to objects included in a sensor(s) field of view. The outputs may be decoded and/or otherwise post-processed to reconstruct object tracking and to determine proposed or potential paths for navigating the vehicle.

Abstract: In various examples, systems and methods are disclosed relating to generating tokens for traffic modeling. One or more circuits can identify trajectories in a dataset, and generate actions from the identified trajectories. The one or more circuits can generate, based at least on the plurality of actions and at least one trajectory of the plurality of trajectories, a set of tokens representing actions to generate trajectories of one or more agents in a simulation. The one or more circuits may update a transformer model to generate simulated actions for simulated agents based at least on tokens generated from the trajectories in the dataset.

Abstract: Technologies for optimizing post-FEC bit error rate performance of a Forward Error Correction (FEC) system are described. A controller is coupled to an FEC circuit and a receiver circuit. The controller receives FEC symbol error data from the FEC circuit and determines, using the FEC symbol error data, a post-FEC correlated performance metric indicative of an estimated post-FEC BER of the FEC circuit. The controller adjusts, based on the post-FEC correlated performance metric, at least one of a FEC parameter of the FEC circuit or a link parameter of the receiver circuit to decrease the estimated post-FEC BER. This improves the post-FEC BER performance of the FEC circuit.

Abstract: Circuitry and a method of operating a clock monitoring circuit for monitoring a clock signal is disclosed. The method comprises charging a first capacitor connected to a connection between a first pair of transistors and a voltage reference, charging a second capacitor connected to a connection between a second pair of transistors and to the voltage reference, sinking a current from the first and second pair of transistors with a constant current sink, and asserting a clock slow detect (CSD) signal when a voltage at the constant current sink drops below a threshold indicating durations of phases of the clock signal lengthen.

Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.

Abstract: One or more embodiments relate to executing a software testing tool to identify function calls—internal and/or external—of software code and their corresponding errors. Once identified-such as during an information gathering operation-the error codes may be returned in place of actual outputs of the function during testing, and the downstream processing of the software as a result of the errors may be evaluated. As such, an automatic software testing tool may be implemented that not only identifies functions calls and corresponding errors, but also evaluates performance of the software in view of the various different error types associated with the function calls.

Abstract: In various examples, potentially highlight-worthy video clips are identified from a gameplay session that a gamer might then selectively share or store for later viewing. The video clips may be identified in an unsupervised manner based on analyzing game data for durations of predicted interest. A classification model may be trained in an unsupervised manner to classify those video clips without requiring manual labeling of game-specific image or audio data. The gamer can select the video clips as highlights (e.g., to share on social media, store in a highlight reel, etc.). The classification model may be updated and improved based on new video clips, such as by creating new video-clip classes.

Abstract: Apparatuses, systems, and techniques to identify orientations of objects within images. In at least one embodiment, one or more neural networks are trained to identify an orientations of one or more objects based, at least in part, on one or more characteristics of the object other than the object's orientation.

Abstract: Systems and methods are directed toward evaluating auditory inputs against a range of tolerance to provide feedback regarding pronunciation. An auditory input may be evaluated using a trained machine learning system and evaluated for similarity against a target word. Similarity may be scored and then evaluated to determine whether the similarity falls within a range of tolerance, wherein the range of tolerance may be adjusted or modified for particular uses. A score within the range of tolerance is indicative of a word that has been pronounced such that it would be perceptible.

Abstract: Power delivery systems for integrated circuits that include a first metal path traversing first metal layers from a global power domain supply to a voltage regulator, a second metal path traversing second metal layers from a local power domain supply to the voltage regulator, and a third metal path traversing third metal layers from the local power domain supply to an integrated circuit. Electrical isolation gaps are formed between the first metal layers, the second metal layers, and the third metal layers.

Abstract: Reference voltage generators including a header circuit configured to pass current from a power supply to a time-to-digital converter, an amount of the current to pass determined by a thermometer code, and logic to update the thermometer code based on a comparison between an output of the time-to-digital converter and a digital code representing a reference voltage level.

Abstract: A Displaced Micro-mesh (DMM) primitive enables high complexity geometry for ray and path tracing while minimizing the associated builder costs and preserving high efficiency. A structured, hierarchical representation implicitly encodes vertex positions of a triangle micro-mesh based on a barycentric grid, and enables microvertex displacements to be encoded efficiently (e.g., as scalars linearly interpolated between minimum and maximum triangle surfaces). The resulting displaced micro-mesh primitive provides a highly compressed representation of a potentially vast number of displaced microtriangles that can be stored in a small amount of space. Improvements in ray tracing hardware permit automatic processing of such primitive for ray-geometry intersection testing by ray tracing circuits without requiring intermediate reporting to a shader.

Abstract: Machine learning systems and methods that determine gaze direction by using face orientation information, such as facial landmarks, to modify eye direction information determined from images of the subject's eyes. System inputs include eye crops of the eyes of the subject, as well as face orientation information such as facial landmarks of the subject's face in the input image. Facial orientation information, or facial landmark information, is used to determine a coarse prediction of gaze direction as well as to learn a context vector of features describing subject face pose. The context vector is then used to adaptively re-weight the eye direction features determined from the eye crops. The re-weighted features are then combined with the coarse gaze prediction to determine gaze direction.

Abstract: Operations may comprise obtaining a plurality of light detection and ranging (LIDAR) scans of a region. The operations may also comprise identifying a plurality of LIDAR poses that correspond to the plurality of LIDAR scans. In addition, the operations may comprise identifying, as a plurality of keyframes, a plurality of images of the region that are captured during capturing of the plurality of LIDAR scans. The operations may also comprise determining, based on the plurality of LIDAR poses, a plurality of camera poses that correspond to the keyframes. Further, the operations may comprise identifying a plurality of two-dimensional (2D) keypoints in the keyframes. The operations also may comprise generating one or more three-dimensional (3D) keypoints based on the plurality of 2D keypoints and the respective camera poses of the plurality of keyframes.

Abstract: In various examples, a trajectory prediction model provides interpretable trajectory predictions for autonomous and semi-autonomous systems and applications via counterfactual game-theoretic reasoning. Model-based latent variables can be formulated through responsibility evaluations. Responsibility can be broken into multiple components, such as safety and courtesy. Responsibility can be quantified, for example, by answering a counterfactual question: could an agent have executed differently to respect other agents' safety and be more courteous to others' plans? The framework can be used to abstract computed responsibility sequences into different responsibility levels and ground latent levels into a trajectory prediction model able to render interpretable and accurate inferences about trajectory.

Abstract: A process to manage congestion in a network involves converting traffic received from the local endpoints to a bandwidth demand for one or more destination endpoint in a remote group, and determining a sum over the destination endpoints of a minimum of a maximum bandwidth of a link and a bandwidth demand to one or more of the remote endpoints.

Abstract: A method and system are disclosed for training a model that implements a machine-learning algorithm. The technique utilizes latent descriptor vectors to change a multiple-valued output problem into a single-valued output problem and includes the steps of receiving a set of training data, processing, by a model, the set of training data to generate a set of output vectors, and adjusting a set of model parameters and component values for at least one latent descriptor vector in the plurality of latent descriptor vectors based on the set of output vectors. The set of training data includes a plurality of input vectors and a plurality of desired output vectors, and each input vector in the plurality of input vectors is associated with a particular latent descriptor vector in a plurality of latent descriptor vectors. Each latent descriptor vector comprises a plurality of scalar values that are initialized prior to training the model.

Abstract: Embodiments of the present disclosure are directed to apparatuses, systems, and techniques of offloading shader program compilation at a computing system. A detection is made that a set of shader programs are to be compiled for an application executing at a computing system using a first set of processing devices. A second set of processing devices to compile the set of shader programs is identified. Each of the second set of processing devices is different from any processing device of the first set of processing devices. The set of shader programs is provided for compilation using the second set of processing devices in view of state data associated with the computing system to obtain a set of complied shader programs. The set of compiled shader programs is executed using the first set of processing devices.

Abstract: Systems and methods are described for collecting configuration data associated with one or more devices of a network, in association with a configuration of the network. The systems and methods include validating the configuration of the network. Validating the configuration includes determining a stability status associated with the network and the configuration. The systems and methods include generating a data record corresponding to the configuration of the network and storing the data record to a data repository. The data record includes the configuration data and results associated with validating the configuration of the network. The systems and methods include generating a second configuration and simulating the second network based on the second configuration. The second configuration includes the one or more devices, one or more second devices included in the data repository, or both.

Abstract: One embodiment of a method for rendering one or more graphics images includes tracing one or more rays through a graphics scene; computing one or more surface normals associated with intersections of the one or more rays with one or more surfaces, where computing each surface normal includes: computing a plurality of intermediate surface normals associated with a plurality of adjacent voxels of a grid, and interpolating the plurality of intermediate surface normals; and rendering one or more graphics images based on the one or more surface normals.