NVIDIA Corporation patent applications on March 14th, 2024
Contents
- 1 Patent Applications by NVIDIA Corporation on March 14th, 2024
- 1.1 Gaming and Entertainment Innovations
- 1.2 Autonomous Systems and Applications
- 1.3 Datacenter Cooling and Efficiency
- 1.4 API and Matrix Operations
- 1.5 Image Processing and Accessibility
- 1.6 Ray Tracing and 3D Scene Completion
- 1.7 Occlusion Detection and State Estimation
- 1.8 Conversational AI Systems
Patent Applications by NVIDIA Corporation on March 14th, 2024
NVIDIA Corporation: 12 patent applications
NVIDIA Corporation has applied for patents in the areas of G06T3/40 (4), G06V10/82 (4), G06V20/58 (4), G06N3/08 (4), G06T17/00 (3)
With keywords such as: data, object, determine, systems, clock, network, images, image, used, and neural in patent application abstracts.
NVIDIA Corporation Patent Applications on March 14th, 2024
Aplications span advancements in gaming, autonomous systems, data synchronization, heat exchange in datacenters, API for matrix operations, image processing, ray tracing, 3D semantic scene completion, identifying occluded objects, robust state estimation, and conversational AI systems.
Gaming and Entertainment Innovations
Game Event Recognition: A game-agnostic event detector aims to automatically identify significant game events, enhancing player engagement and feedback through highlight video generation or performance analysis【source†source】.
Autonomous Systems and Applications
Determining Perception Zones for Object Detection in Autonomous Systems and Applications: This patent outlines methods for dynamic modeling in autonomous systems, aiming to enhance safety and interaction between machines and their environments【source†source】. Data Synchronization for Validation and Correction in Autonomous Systems and Applications: Focusing on ensuring data integrity and synchronization across autonomous system circuits to prevent safety-critical errors【source†source】. Time Synchronization and Conversion for Safety Validation in Autonomous Systems and Applications: A method to maintain accurate time synchronization across components of autonomous systems, crucial for safety and efficiency【source†source】.
Datacenter Cooling and Efficiency
Intelligent Rear Door Heat Exchanger for Local Cooling Loops in a Datacenter Cooling System: Innovations in cooling technology for datacenters, aiming to improve energy efficiency and reduce the carbon footprint of large-scale computing operations【source†source】.
API and Matrix Operations
Application Programming Interface to Accelerate Matrix Operations: Development of an API to optimize matrix multiplication algorithms, highlighting NVIDIA's focus on computational efficiency and performance【source†source】.
Image Processing and Accessibility
Image Processing Using Color Vision Deficiency Compensation: A transformative approach to modify images for better viewing by individuals with color vision deficiencies, emphasizing NVIDIA's commitment to accessibility【source†source】.
Ray Tracing and 3D Scene Completion
Generation and Traversal of Partial Acceleration Structures for Ray Tracing: Enhancements in ray tracing technology for more efficient rendering of complex scenes【source†source】. Sparse Voxel Transformer for Camera-Based 3D Semantic Scene Completion: Leveraging AI to convert 2D images into detailed 3D semantic information, useful in autonomous vehicle navigation and simulation【source†source】.
Occlusion Detection and State Estimation
Techniques for Identifying Occluded Objects Using a Neural Network: Methods to detect objects occluded from a vehicle's view, enhancing the safety and reliability of autonomous driving systems【source†source】. Robust State Estimation: Techniques to determine robust state information for subjects, improving the accuracy and reliability of systems monitoring conditions like drowsiness【source†source】.
Conversational AI Systems
Using Scene-Aware Context for Conversational AI Systems and Applications: Introducing scene-aware context into dialogue systems to make conversational AI more relevant and responsive to the user's environment【source†source】. NVIDIA Corporation's patent applications from March 14th, 2024, illustrate the company's enduring commitment to pushing the boundaries of technology. From enhancing gaming experiences and autonomous system safety to pioneering cooling solutions for datacenters and advancing conversational AI, NVIDIA continues to lead in innovation, driving the future of computing, graphics, and artificial intelligence.
Patent Applications by NVIDIA Corporation
20240082704.GAME EVENT RECOGNITION_simplified_abstract_(nvidia corporation)
Inventor(s): Jonathan White of Fort Collins CO (US) for nvidia corporation, Dave Clark of Cary NC (US) for nvidia corporation, Nathan Otterness of Mebane NC (US) for nvidia corporation, Travis Muhlestein of Redmond WA (US) for nvidia corporation, Prabindh Sundareson of Bangalore (IN) for nvidia corporation, Jim van Welzen of Sandy UT (US) for nvidia corporation, Jack van Welzen of Raleigh NC (US) for nvidia corporation
IPC Code(s): A63F13/30, A63F13/426, A63F13/428, A63F13/44, A63F13/79, A63F13/86, G07F17/32, H04N21/234, H04N21/44
Abstract: a game-agnostic event detector can be used to automatically identify game events. game-specific configuration data can be used to specify types of pre-processing to be performed on media for a game session, as well as types of detectors to be used to detect events for the game. event data for detected events can be written to an event log in a form that is both human- and process-readable. the event data can be used for various purposes, such as to generate highlight videos or provide player performance feedback.
Inventor(s): Sever Ioan Topan of Burnaby (CA) for nvidia corporation, Karen Yan Ming Leung of Los Altos CA (US) for nvidia corporation, Yuxiao Chen of Sunnyvale CA (US) for nvidia corporation, Pritish Tupekar of Santa Clara CA (US) for nvidia corporation, Edward Fu Schmerling of Los Altos CA (US) for nvidia corporation, Hans Jonas Nilsson of Los Gatos CA (US) for nvidia corporation, Michael Cox of Menlo Park CA (US) for nvidia corporation, Marco Pavone of Stanford CA (US) for nvidia corporation
IPC Code(s): G05D1/02, G06V20/58
Abstract: in various examples, techniques for determining perception zones for object detection are described. for instance, a system may use a dynamic model associated with an ego-machine, a dynamic model associated with an object, and one or more possible interactions between the ego-machine and the object to determine a perception zone. the system may then perform one or more processes using the perception zone. for instance, if the system is validating a perception system of the ego-machine, the system may determine whether a detection error associated with the object is a safety-critical error based on whether the object is located within the perception zone. additionally, if the system is executing within the ego-machine, the system may determine whether the object is a safety-critical object based on whether the object is located within the perception zone.
Inventor(s): Mohamed Saad Abdelhameed of Dachau (DE) for nvidia corporation
IPC Code(s): G06F1/04
Abstract: in various examples, a corrective operation may be performed based at least in part on detecting that at least one circuit is operating asynchronously with respect to a reference clock. an indication that at least one circuit operating asynchronously was detected may be generated. upon detecting a circuit operating asynchronously, a corrective operation may be performed such that a component that receives data generated using the at least one circuit continues operating in view of the indication.
Inventor(s): Mohamed Saad Abdelhameed of Dachau (DE) for nvidia corporation
IPC Code(s): G06F1/12, G06F1/10
Abstract: in various examples, a time conversion operation may be performed based at least on updating a first local clock of a component based at least on a reference clock of a system including the component. a difference between a current time of the first local clock and a current time of a second local clock of the component may be determined. a state of at least one of the reference clock, the first local clock, or the second local clock may be determined based at least on comparing the time difference to a previously determined difference between a time of the reference clock and a time of the second local clock.
Inventor(s): Ali Heydari of Albany CA (US) for nvidia corporation
IPC Code(s): G06F1/20, G06N3/08, H05K7/20
Abstract: systems and methods for cooling a datacenter are disclosed. in at least one embodiment, a liquid-to-liquid heat exchanger associated with a rear door of a rack exchanges heat between a primary coolant associated with a chilling facility and a secondary coolant or fluid associated with a computing device of the rack.
Inventor(s): Piotr Majcher of Sunnyvale CA (US) for nvidia corporation, Mostafa Hagog of Folsom CA (US) for nvidia corporation, Philippe Vandermersch of San Jose CA (US) for nvidia corporation
IPC Code(s): G06F17/16, G06F9/30, G06N3/08, G06N5/046
Abstract: apparatuses, systems, and techniques to determine a matrix multiplication algorithm for a matrix multiplication operation. in at least one embodiment, a matrix multiplication operation is analyzed to determine an appropriate matrix multiplication algorithm to perform the matrix multiplication algorithm.
Inventor(s): Johan Pontus Andersson of Lund (SE) for nvidia corporation, Cyril Crassin of Meylan (FR) for nvidia corporation, Tomas Akenine-Möller of Lund (SE) for nvidia corporation
IPC Code(s): G06T11/00, G06T3/00, G06T3/40, G06T7/90, H04N9/64
Abstract: the technology disclosed herein involves using a transformation curve to modify colors of images so that those images are more easily viewed by persons with a color vision deficiency (cvd). the transformation curve is applied to spectral versions of images in which each pixel has a spectral representation to modify the spectral versions of the images. a spectral version of an image is modified by, for each pixel of the spectral version of the image, modifying intensities of one or more wavelengths by applying the one or more wavelengths to the transformation curve, which transforms the intensities from source wavelengths to destination wavelengths. the modified spectral version of the image is then modified to a modified version of the image in a color space, such as the rgb color space.
Inventor(s): Greg MUTHLER of Chapel Hill NC (US) for nvidia corporation, John BURGESS of Austin TX (US) for nvidia corporation, Magnus ANDERSSON of Lund (SE) for nvidia corporation, Timo VIITANEN of Uusimaa (FI) for nvidia corporation, Levi OLIVER of Cambridge MA (US) for nvidia corporation
IPC Code(s): G06T15/06, G06T15/00, G06T17/00
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.
Inventor(s): Yiming Li of Jersey City NJ (US) for nvidia corporation, Zhiding Yu of Santa Clara CA (US) for nvidia corporation, Christopher B. Choy of Los Angeles CA (US) for nvidia corporation, Chaowei Xiao of Tempe AZ (US) for nvidia corporation, Jose Manuel Alvarez Lopez of Mountain View CA (US) for nvidia corporation, Sanja Fidler of Toronto (CA) for nvidia corporation, Animashree Anandkumar of Pasadena CA (US) for nvidia corporation
IPC Code(s): G06T17/00, B60W50/14, G06T3/40, G06V10/44, G06V10/771, G06V10/82
Abstract: an artificial intelligence framework is described that incorporates a number of neural networks and a number of transformers for converting a two-dimensional image into three-dimensional semantic information. neural networks convert one or more images into a set of image feature maps, depth information associated with the one or more images, and query proposals based on the depth information. a first transformer implements a cross-attention mechanism to process the set of image feature maps in accordance with the query proposals. the output of the first transformer is combined with a mask token to generate initial voxel features of the scene. a second transformer implements a self-attention mechanism to convert the initial voxel features into refined voxel features, which are up-sampled and processed by a lightweight neural network to generate the three-dimensional semantic information, which may be used by, e.g., an autonomous vehicle for various advanced driver assistance system (adas) functions.
Inventor(s): Siva Kumar Sastry Hari of Sunnyvale CA (US) for nvidia corporation, Jason Lavar Clemons of Leander TX (US) for nvidia corporation, Timothy Kohchih Tsai of Santa Clara CA (US) for nvidia corporation
IPC Code(s): G06V20/58, G06V10/774, G06V10/776, G06V10/82
Abstract: in various examples, techniques for detecting occluded objects within an environment are described. for instance, systems and methods may receive training data representing images and ground truth data indicating whether the images are associated with occluded objects or whether the images are not associated with occluded objects. the systems and methods may then train a neural network to detect occluded objects using the training data and the ground truth data. after training, the systems and methods may use the neural network to detect occluded objects within an environment. for instance, while a vehicle is navigating, the vehicle may process sensor data using the neural network. the neural network may then output data indicating whether an object is located within the environment and occluded from view of the vehicle. in some examples, the neural network may further output additional information associated with the occluded object.
20240087341.ROBUST STATE ESTIMATION_simplified_abstract_(nvidia corporation)
Inventor(s): Yuzhuo Ren of Sunnyvale CA (US) for nvidia corporation, Niranjan Avadhanam of Saratoga CA (US) for nvidia corporation
IPC Code(s): G06V20/59, B60W40/08, G06F18/21, G06N3/045, G06V40/16, G06V40/18
Abstract: state information can be determined for a subject that is robust to different inputs or conditions. for drowsiness, facial landmarks can be determined from captured image data and used to determine a set of blink parameters. these parameters can be used, such as with a temporal network, to estimate a state (e.g., drowsiness) of the subject. to improve robustness, an eye state determination network can determine eye state from the image data, without reliance on intermediate landmarks, that can be used, such as with another temporal network, to estimate the state of the subject. a weighted combination of these values can be used to determine an overall state of the subject. to improve accuracy, individual behavior patterns and context information can be utilized to account for variations in the data due to subject variation or current context rather than changes in state.
Inventor(s): Niral Lalit Pathak of San Jose CA (US) for nvidia corporation, Rajath Shetty of Sunnyvale CA (US) for nvidia corporation, Ratin Kumar of Cupertino CA (US) for nvidia corporation
IPC Code(s): G10L15/18, G06F3/01, G06T7/73, G10L15/16, G10L15/183
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.
- NVIDIA Corporation
- A63F13/30
- A63F13/426
- A63F13/428
- A63F13/44
- A63F13/79
- A63F13/86
- G07F17/32
- H04N21/234
- H04N21/44
- Nvidia corporation
- G05D1/02
- G06V20/58
- G06F1/04
- G06F1/12
- G06F1/10
- G06F1/20
- G06N3/08
- H05K7/20
- G06F17/16
- G06F9/30
- G06N5/046
- G06T11/00
- G06T3/00
- G06T3/40
- G06T7/90
- H04N9/64
- G06T15/06
- G06T15/00
- G06T17/00
- B60W50/14
- G06V10/44
- G06V10/771
- G06V10/82
- G06V10/774
- G06V10/776
- G06V20/59
- B60W40/08
- G06F18/21
- G06N3/045
- G06V40/16
- G06V40/18
- G10L15/18
- G06F3/01
- G06T7/73
- G10L15/16
- G10L15/183
