Abstract: One or more machine learning models (MLMs) may learn implicit 3D representations of geometry of an object and of dynamics of the object from performing an action on the object. Implicit neural representations may be used to reconstruct high-fidelity full geometry of the object and predict a flow-based dynamics field from one or more images, which may provide a partial view of the object. Correspondences between locations of an object may be learned based at least on distances between the locations on a surface corresponding to the object, such as geodesic distances. The distances may be incorporated into a contrastive learning loss function to train one or more MLMs to learn correspondences between locations of the object, such as a correspondence embedding field. The correspondences may be used to evaluate state changes when evaluating one or more actions that may be performed on the object.

Abstract: Volumetric quantification can be performed for various parameters of an object represented in volumetric data. Multiple views of the object can be generated, and those views provided to a set of neural networks that can generate inferences in parallel. The inferences from the different networks can be used to generate pseudo-labels for the data, for comparison purposes, which enables a co-training loss to be determined for the unlabeled data. The co-training loss can then be used to update the relevant network parameters for the overall data analysis network. If supervised data is also available then the network parameters can further be updated using the supervised loss.

Abstract: In various examples, systems and methods are disclosed relating to refinement of safety zones and improving evaluation metrics for the perception modules of autonomous and semi-autonomous systems. Example implementations can exclude areas in the state space that are not safety critical, while retaining the areas that are safety-critical. This can be accomplished by leveraging ego maneuver information and conditioning safety zone computations on ego maneuvers. A maneuver-based decomposition of perception safety zones may leverage a temporal convolution operation with the capability to account for collision at any intermediate time along the way to maneuver completion. This provides a significant reduction in zone volume while maintaining completeness, thus optimizing or otherwise enhancing obstacle perception performance requirements by filtering out regions of state space not relevant to a system's route of travel.

Abstract: Ray tracing hardware accelerators supporting motion blur and moving/deforming geometry are disclosed. For example, dynamic objects in an acceleration data structure are encoded with temporal and spatial information. The hardware includes circuitry that test ray intersections against moving/deforming geometry by applying such temporal and spatial information. Such circuitry accelerates the visibility sampling of moving geometry, including rigid body motion and object deformation, and its associated moving bounding volumes to a performance similar to that of the visibility sampling of static geometry.

Abstract: Systems and methods for cooling a datacenter are disclosed. In at least one embodiment, a first three-way flow controller is associated with a single-phase fluid and a second three-way flow controller is associated with a two-phase fluid, with a first three-way flow controller to enable a first flow path of a single-phase fluid from a coolant distribution unit to a cold plate or to enable a second flow path to a heat exchanger to cool a two-phase fluid to be used in a cold plate, and with a second three-way flow controller to enable a third flow path of a two-phase fluid to a cold plate or to enable a fourth flow path to a heat exchanger.

Abstract: A machine learning framework is described for performing generation of candidate molecules for, e.g., drug discovery or other applications. The framework utilizes a pre-trained encoder-decoder model to interface between representations of molecules and embeddings for those molecules in a latent space. A fusion module is located between the encoder and decoder and is used to fuse an embedding for an input molecule with embeddings for one or more exemplary molecules selected from a database that is constructed according to a design criteria. The fused embedding is decoded using the decoder to generate a candidate molecule. The fusion module is trained to reconstruct a nearest neighbor to the input molecule from the database based on the sample of exemplary molecules. An iterative approach may be used during inference to dynamically update the database to include newly generated candidate molecules.

Abstract: A system can include an optical transmitter having transmitter components and an optical receiver having receiver components and photodetectors. The optical transmitter is configured to receive optical wavelengths of radiation from a multiple wavelength generate, such as a laser, and generate transmitted wavelengths including data wavelengths and excess wavelengths. Each photodetector is configured to receive at least one transmitted wavelength. The photodetectors can include a common photodetector operatively coupled to at least two receiver components and configured to obtain a set of unmodulated carrier frequencies (e.g., a pair of unmodulated carrier frequencies) from the at least two receiver components, and determine clock information therefrom. The clock information can be determined by obtaining a heterodyne frequency from the set of unmodulated carrier frequencies. The heterodyne frequency can be used to synchronize the optical transmitter and the optical receiver.

Abstract: One embodiment of a computer-implemented method for processing ray tracing operations in parallel includes receiving a plurality of rays and a corresponding set of importance sampling instructions for each ray included in the plurality of rays for processing, wherein each ray represents a path from a light source to at least one point within a three-dimensional (3D) environment, and each corresponding set of importance sampling instruction is based at least in part on one or more material properties associated with at least one surface of at least one object included in the 3D environment; assigning each ray included in the plurality of rays to a different processing core included in a plurality of processing cores; and for each ray included in the plurality of rays, causing the processing core assigned to the ray to execute the corresponding set of importance sampling instructions on the ray to generate a direction for a secondary ray that is produced when the ray intersects a surface of an object within the

Abstract: In various examples, an ego-machine may analyze sensor data to identify and track features in the sensor data using. Geometry of the tracked features may be used to analyze motion flow to determine whether the motion flow violates one or more geometrical constraints. As such, tracked features may be identified as dynamic features when the motion flow corresponding to the tracked features violates the one or more static constraints for static features. Tracked features that are determined to be dynamic features may be clustered together according to their location and feature track. Once features have been clustered together, the system may calculate a detection bounding shape for the clustered features. The bounding shape information may then be used by the ego-machine for path planning, control decisions, obstacle avoidance, and/or other operations.

Abstract: Processors, systems and methods are described that synchronize clocks of devices on a second network that uses a second network protocol to a source clock on a first network that uses a first network protocol. Processors, systems and methods are described to cause a first time synchronization message corresponding to a first network communication protocol to be converted to a second time synchronization message corresponding to a second network communication protocol to enable synchronization.

Abstract: Devices and methods to obtain values usable to verify the geographic location of a device. In at least one embodiment, a device comprises a positioning circuit and a cryptoprocessor. The device obtains geographic coordinates of the device's location, using the positioning circuit. The device stores, in the cryptoprocessor, information indicating the state of the device and the geographic coordinates. The device uses the cryptoprocessor to obtain values usable to validate the geographic location of the device.

Abstract: Methods for integrating copper-graphene laminate (CGL) in a multilayer PCB fabrication process and the resulting lamination stacks are disclosed. The methods include providing a core and applying a first graphene layer to the surface of the core. The methods further include applying a metal layer to the first graphene layer and applying a second graphene layer to the metal layer. Further, the methods include applying a photoresist layer to the second graphene layer and applying a protective layer to the photoresist layer. In some embodiments, the methods include applying a metallic plating to lamination stack. The methods further include drilling through the protective layer and at least one of a photoresist layer, the second graphene layer, the metal layer, the first graphene layer, and/or the core.

Abstract: Methods of forming a graphene integrated core for making a printed circuit board (PCB) having enhanced thermal management properties are disclosed. The methods include providing a core body having a core body length and applying a graphene multi-layer to the core body to form a laminated stack, where the graphene multi-layer has a graphene multi-layer length that is shorter than the core body length. At least one conductive layer may be applied to the laminated stack. The graphene multi-layer may be disposed within the graphene integrated core such that the graphene multi-layer is electrically insulated from the at least one conductive layer. Corresponding graphene integrated cores having a graphene multi-layer that is disposed within the graphene integrated core such that the graphene multi-layer is electrically insulated from the at least one conductive layer are also described.

Abstract: Apparatuses, systems, and techniques to generate blue noise masks for real-time image rendering and enhancement. In at least one embodiment, a vector-valued noise mask is generated and applied to one or more images to generate one or more enhanced images for image processing (e.g., real-time image rendering). In at least one embodiment, the noise mask includes vector values per pixel and is able to handle the temporal domain (e.g., add time to the spatial domain) to improve image quality when rendering images over multiple frames.

Abstract: Systems and methods for evaluating cooling characteristics are disclosed. In at least one embodiment, a thermal testing rig for a data center can include one or more pluggable heat-generating elements to direct a heat flux in an upward direction towards one or more thermal distribution elements.

Abstract: An alternate root tree or graph structure for ray and path tracing enables dynamic instancing build time decisions to split any number of geometry acceleration structures in a manner that is developer transparent, nearly memory storage neutral, and traversal efficient. The resulting traversals only need to partially traverse the acceleration structure, which improves efficiency. One example use reduces the number of false positive instance acceleration structure to geometry acceleration structure transitions for many spatially separated instances of the same geometry.

Abstract: Apparatuses, systems, and techniques to perform a cryptographic operation using multiple iterations, wherein each iteration includes two or more stages operating in parallel on inputs derived from a common value, one of the stages computing real data and other stages computing dummy data.

Abstract: User interfaces, methods and structures are described for intuitively and fluidly creating new artifacts from existing artifacts and for exploring latent spaces in a visual manner. In example embodiments, source artifacts are displayed along with a selector. The selector is operable to indicate a selected set of the source artifacts by establishing a selection region that includes portions of one or more of the source artifacts displayed. Source vectors are associated with the source artifacts in the selected set. One or more resultant vectors are determined based on the source vectors, and an output artifact is generated based on the one or more resultant vectors.

Abstract: In various examples, a neural network may be trained for use in vehicle re-identification tasks—e.g., matching appearances and classifications of vehicles across frames—in a camera network. The neural network may be trained to learn an embedding space such that embeddings corresponding to vehicles of the same identify are projected closer to one another within the embedding space, as compared to vehicles representing different identities. To accurately and efficiently learn the embedding space, the neural network may be trained using a contrastive loss function or a triplet loss function. In addition, to further improve accuracy and efficiency, a sampling technique—referred to herein as batch sample—may be used to identify embeddings, during training, that are most meaningful for updating parameters of the neural network.

Abstract: In various examples, live perception from wide-view sensors may be leveraged to detect features in an environment of a vehicle. Sensor data generated by the sensors may be adjusted to represent a virtual field of view different from an actual field of view of the sensor, and the sensor data—with or without virtual adjustment—may be applied to a stereographic projection algorithm to generate a projected image. The projected image may then be applied to a machine learning model—such as a deep neural network (DNN)—to detect and/or classify features or objects represented therein. In some examples, the machine learning model may be pre-trained on training sensor data generated by a sensor having a field of view less than the wide-view sensor such that the virtual adjustment and/or projection algorithm may update the sensor data to be suitable for accurate processing by the pre-trained machine learning model.