NVIDIA Corporation patent applications on 2025-06-05
Patent Applications by NVIDIA Corporation on June 5th, 2025
NVIDIA Corporation: 38 patent applications
NVIDIA Corporation has applied for patents in the areas of G06T15/06 (Ray-tracing, 3), H04L51/02 (using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages, 3), G06F9/5016 (Allocation of resources, e.g. of the central processing unit [CPU], 2), G06F9/544 (Interprogram communication, 2), G06T13/40 (of characters, e.g. humans, animals or virtual beings, 2), B60W30/08 ({Active safety systems} predicting or avoiding probable or impending collision {or attempting to minimise its consequences}, 1), G06N20/00 (Machine learning, 1), H04L65/756 (Media network packet handling, 1), H03K17/6872 (PULSE TECHNIQUE (measuring pulse characteristics ; modulating sinusoidal oscillations with pulses ; transmission of digital information ; discriminator circuits detecting phase difference between two signals by counting or integrating cycles of oscillation ; automatic control, starting, synchronisation or stabilisation of generators of electronic oscillations or pulses where the type of generator is irrelevant or unspecified ; coding, decoding or code conversion, in general ), 1), G06V20/597 (IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING, 1)
With keywords such as: data, various, least, examples, sensor, environment, vehicle, representative, view, field in patent application abstracts.
Top Inventors:
- David Nister of Bellevue WA US (1 patents)
- Anton Vorontsov of San Jose CA US (1 patents)
- Gang Pan of Fremont CA US (3 patents)
- Joachim Pehserl of Lynnwood WA US (1 patents)
- Dong Zhang of Clarksville TN US (1 patents)
Patent Applications by NVIDIA Corporation
20250178595. CONTROLLING AUTONOMOUS VEHICLES USING SAFE ARRIVAL TIMES (NVIDIA)
Abstract: in various examples, sensor data representative of a field of view of at least one sensor of a vehicle in an environment is received from the at least one sensor. based at least in part on the sensor data, parameters of an object located in the environment are determined. trajectories of the object are modeled toward target positions based at least in part on the parameters of the object. from the trajectories, safe time intervals (and/or safe arrival times) over which the vehicle occupying the plurality of target positions would not result in a collision with the object are computed. based at least in part on the safe time intervals (and/or safe arrival times) and a position of the vehicle in the environment a trajectory for the vehicle may be generated and/or analyzed.
20250180736. MULTIMODAL OBJECT DETECTION AUTONOMOUS SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, a hazard detection system fuses outputs from multiple sensors over time to determine a probability that a stationary object or hazard exists at a location. the system may then use sensor data to calculate a detection bounding shape for detected objects and, using the bounding shape, may generate a set of particles, each including a confidence value that an object exists at a corresponding location. the system may then capture additional sensor data by one or more sensors of the ego-machine that are different from those used to capture the first sensor data. to improve the accuracy of the confidences of the particles, the system may determine a correspondence between the first sensor data and the additional sensor data (e.g., depth sensor data), which may be used to filter out a portion of the particles and improve the depth predictions corresponding to the object.
20250181138. MULTIMODAL HUMAN-MACHINE INTERACTIONS INTERACTIVE SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, an interactive agent platform that hosts an interactive agent may execute one or more flows that implement the logic of the interactive agent and that specify a sequence of multimodal interactions. for example, an interactive avatar may support any number of simultaneous interaction modalities and corresponding interaction channels to engage with the user, such as channels for character or bot actions (e.g., speech, gestures, postures, movement, vocal bursts, etc.), scene actions (e.g., two-dimensional (2d) gui overlays, 3d scene interactions, visual effects, music, etc.), and user actions (e.g., speech, gesture, posture, movement, etc.). actions based on different modalities may occur sequentially or in parallel (e.g., waving and saying hello). as such, the interactive agent may execute any number of flows that specify a sequence of multimodal actions (e.g., different types of bot or user actions) using any number of supported interaction modalities and corresponding interaction channels.
20250181207. INTERACTIVE VISUAL CONTENT INTERACTIVE SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, an interactive agent platform that hosts development and/or deployment of an interactive agent may use a gui service to execute interactive visual content actions and generate corresponding guis. an interaction modeling api may use an interaction categorization schema that defines a standardized format for specifying (e.g., visual information scene, visual choice, or visual form actions) events that instruct an overlay of visual content supplementing a conversation with the interactive agent. the gui service may translate a standardized representation of a gui specified by an interaction modeling api event into a modular gui configuration defining blocks of visual content specified by the event, and may use these blocks to populate a (e.g., template or shell) visual layout for a gui overlay layout. as such, a visual layout representing a gui specified by an interaction modeling api event may be generated and presented (e.g., via a user interface server).
20250181356. APPLICATION PROGRAMMING INTERFACE CONFIGURE PROCESSOR PARTITIONING (NVIDIA)
Abstract: apparatuses, systems, and techniques to configure processor partitioning for a multi-process service. in at least one embodiment, a multi-process service configures a set of streaming multiprocessors of one or more parallel processing units to perform one or more threads in response to an application programming interface (api).
20250181363. APPLICATION PROGRAMMING INTERFACE GENERATE REPRESENTATION GRAPH CODE (NVIDIA)
Abstract: apparatuses, systems, and techniques to cause a descriptive representation of graph code to be generated. in at least one embodiment, a descriptive representation of graph code is caused to be generated based on, for example, cuda or other parallel computing platform code.
20250181370. EXPECTATION ACTIONS SIGNALING INTERACTIVE SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, an interpreter of an interactive agent platform that hosts an interactive agent may generate interaction modeling api events that communicate an expectation that certain events will occur, and that command corresponding expectation actions, such as turning down speaker volume in anticipation of user speech, enabling computer vision algorithms in anticipation of vision events, and/or signaling to the user that the interactive agent is waiting for an input (e.g., on a designated user interaction modality). interaction modeling api events may include one or more fields that represent an expectation that a specified target event will occur using a standardized interaction categorization schema that identifies expectations as a supported type of action and that represents corresponding expectation events, expected target events, and/or expected input interaction modalities using standardized keywords and/or commands.
20250181393. APPLICATION PROGRAMMING INTERFACE INDICATE MEMORY INFORMATION (NVIDIA)
Abstract: apparatuses, systems, and techniques to execute one or more application programming interface (api) functions to facilitate parallel computing. in at least one embodiment, one or more apis are to indicate information about one or more storage locations using various novel techniques described herein.
20250181394. APPLICATION PROGRAMMING INTERFACE NEURAL NETWORK COMPUTATION (NVIDIA)
Abstract: apparatuses, systems, and techniques to improve neural network computations. in at least one embodiment, a deep neural network library receives computation descriptors from one or more users and generates an optimized execution plan comprising one or more optimized operations to facilitate neural network computing.
20250181424. EVENT-DRIVEN ARCHITECTURE INTERACTIVE SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, an interactive agent platform that hosts an interactive agent may represent and/or communicate human-machine interactions and related events using a standardized interaction modeling api and/or an event-driven architecture. in an example implementation, a standardized interaction modeling api serves as a common protocol in which components use a standardized interaction categorization schema to represent all activities by agents and users as actions in a standardized form, represent states of multimodal actions from users and agents as events in a standardized form, implement standardized mutually exclusive modalities that define how conflicts between standardized categories of actions are resolved (e.g. saying two things at the same time is not possible, while saying something and making a gesture at the same time may be possible), and/or implement standardized protocols for any number of standardized modalities and actions independent of implementation.
20250181427. TECHNIQUES ORCHESTRATING STAGES THREAD SYNCHRONIZATION (NVIDIA)
Abstract: apparatuses, systems, and techniques to execute data-dependent parallel operations in one or more programs utilizing an application programming interface to perform parallel computing, such as cuda, without relying on a synchronization operation between said one or more programs. for example, at least one embodiment pertains to processors or computing systems used to determine which thread in a group of threads finishes modifying shared data last, and that thread is selected to perform additional data-dependent computations from said group of threads.
20250181428. APPLICATION PROGRAMMING INTERFACE IDENTIFY FUNCTION VERSIONS (NVIDIA)
Abstract: apparatuses, systems, and techniques to determine one or more memory address values corresponding to one or more computing functions provided by one or more application programming interfaces to facilitate parallel computing. in at least one embodiment, one or more application programming interfaces to facilitate parallel computing determine one or more memory address values based, at least in part, on one or more function calls to one or more functions provided by said one or more application programming interfaces to facilitate parallel computing using one or more parallel processing units, such as a graphics processing unit.
20250181431. ACCELERATED FIFTH GENERATION (5G) NEW RADIO OPERATIONS (NVIDIA)
Abstract: apparatuses, systems, and techniques to perform fifth generation (5g) new radio operations. in at least one embodiment, an application programming interface (api) is utilized to perform 5g new radio operations on one or more hardware accelerators through an api call.
20250181483. SOFTWARE PROGRAM ERROR TESTING AUTONOMOUS SYSTEMS APPLICATIONS (NVIDIA)
Abstract: one or more embodiments relate to executing a software testing tool to identify function callsâinternal and/or externalâof software code and their corresponding errors. once identifiedâsuch as during an information gathering operationâthe 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.
20250181806. LEARNING-BASED PLACEMENT CONGESTION MITIGATION (NVIDIA)
Abstract: mechanisms to control cell density in circuit layouts to mitigate placement congestion that learn from post-route target outputs of an electronic design automation system and implement an empirical bayes mechanisms to adapt the target to a specific component placer's achievable outputs. the disclosed mechanisms solve for component placement on a global scale and obviate the application of incremental congestion estimation and mitigation.
20250181814. DIFFERENTIABLE GLOBAL ROUTER (NVIDIA)
Abstract: mechanisms for generating metal routing guides in a circuit involve forming a plurality of directed acyclic graphs (dags) embodying routing trees for nets in the circuit, generating 2-pin subnets and 2-pin path candidates from the routing trees, and forming a dag forest from the routing trees, the 2-pin subnets, and the 2-pin path candidates.
20250181847. DEPLOYMENT INTERACTIVE SYSTEMS APPLICATIONS USING LANGUAGE MODELS (NVIDIA)
Abstract: in various examples, an interactive agent platform that hosts development and/or deployment of an interactive agent may use an interaction modeling language and corresponding interpreter that support the use of natural language descriptions and one or more llms to facilitate the development and deployment of more complex and nuanced human-machine interactions. for example, the interpreter may prompt an llm to generate a natural language description of one or more instruction lines defining a flow, generate one or more instruction lines for a specified flow, determine whether an event matches a flow description of an active flow, determine whether an unmatched event matches the name and/or instruction(s) of an active flow, generate a flow in response to an unmatched event, and/or otherwise.
20250181889. API RECURRENT NEURAL NETWORKS (NVIDIA)
Abstract: apparatuses, systems, and techniques to implement a recurrent neural network. in at least one embodiment, an application programming interface receives one or more api calls comprising a graph definition and a recurrence attribute, and executes a recurrent neural network based on the graph definition.
20250181909. SYNTHETIC DATASET REGENERATION AI SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, synthetic dataset regeneration for ai systems and applications is described herein. for instance, systems and methods described herein may use a simulator to generate a synthetic dataset along with data (referred to, in some examples, as âlog dataâ) representing information associated with the generation of the synthetic dataset by the simulator. for instance, the log data may represent at least parameters used to generate synthetic dataset, values for the parameters, assets associated with the parameters, and/or values representing results associated with the synthetic dataset. the systems and methods may then use the log data to recreate, modify, and/or enhance the synthetic dataset. for example, the synthetic dataset may be recreated by providing at least the log data as input to the simulator such that the simulator regenerates the dataset using the same parameters, values, and/or assets.
20250181969. TECHNIQUES TRAINING MACHINE LEARNING MODELS USING SYNTHETICALLY GENERATED DATA (NVIDIA)
Abstract: one embodiment of a method for generating data to train a machine learning model includes generating a prompt based on a template and information associated with an object, generating, via a first machine learning model and based on the prompt, a text description of at least one of a texture or a geometry for the object, generating, via a second machine learning model and based on the text description, the at least one of the texture or the geometry for the object, and performing one or more rendering operations based on the at least one of the texture or the geometry for the object to generate one or more rendered images.
20250182326. TECHNIQUES POSE ESTIMATION TRACKING NOVEL OBJECTS (NVIDIA)
Abstract: one embodiment of a method for determining object poses includes receiving a first image of an object, sampling an initial pose of the object, performing one or more operations to update the initial pose to determine a first pose of the object based on the first image, a first rendered image of the object in the initial pose, and one or more transformer encoders.
20250182344. OPTIMIZING GRID-BASED COMPUTE GRAPHS (NVIDIA)
Abstract: disclosed are apparatuses, systems, and techniques that enable compressed grid-based graph representations for efficient implementations of graph-mapped computing applications. the techniques include but are not limited to selecting a reference grid having a plurality of blocks, assigning nodes of the graph to blocks of the grid, and generating a graph representation that maps directions, relative to the reference grid, of nodal connections of the graph.
20250182365. BACKCHANNELING INTERACTIVE SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, an interactive agent platform that hosts development and/or deployment of an interactive agent such as a digital avatar may employ backchanneling to provide feedback to the user while the user is talking or doing something detectable. for example, backchanneling may be implemented by triggering interactive agent postures (e.g., based on whether the user or the avatar is speaking, or based on the interactive agent waiting for a response from the user), short vocal bursts like âyesâ, âahaâ, or âhmmâ while the user is talking (e.g., signaling to the user that the interactive agent is listening), gestures (e.g., shaking the interactive's agent's head), and/or otherwise. as such, a designer may specify various backchanneling techniques that make conversations with an interactive agent feel more natural.
20250182366. INTERACTIVE BOT ANIMATIONS INTERACTIVE SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, an interactive agent platform that hosts development and/or deployment of interactive agent may include an interpreter that generates interaction modeling api events specifying commands to make agent (e.g., bot) expressions, poses, gestures, or other interactions or movements, which may be translated into corresponding agent animations. the interpreter may generate an interaction modeling api event using a standardized interaction categorization schema, which an action server implementing an animation service may use to identify a corresponding supported animation. the animation service may implement an action state machine and action stack for all events related to a particular interaction modality (e.g., bot gestures), connect with an animation graph that implements a state machine of animation states and transitions between animations, and instruct the animation graph to set a corresponding state variable based on a command to change the state of an agent movement represented by an interaction modeling api event.
20250182378. AVERAGE RATE REGULATOR PARALLEL ADAPTIVE SAMPLER (NVIDIA)
Abstract: a ray tracing method forms a first accumulation of importance values of non-clamped pixels in an image and forms a second accumulation of waste importance of clamped pixels in the image. the first accumulation and the second accumulation are applied to set an updated average sample count for pixels in the image, and the ray tracer generates a number of sampling rays for particular pixels by applying the updated average sample count to a per-pixel importance setting.
20250182379. CROSS-DOMAIN SEGMENTATION ASSIGNING ELECTROMAGNETIC MATERIALS (NVIDIA)
Abstract: embodiments of the present disclosure relate to using ray tracing to simulate physical environments based on scene geometry and electromagnetic material (em) properties (scene properties) which may be assigned to objects in the scene. the scene properties may include relative permittivity, conductivity, and permeability of the objects, as well as effective roughness, and scattering functions. segmentation data may be used to assign materials to objects, providing additional information for calibrating a ray tracer learning the scene properties for an environment via radio propagation. the segmentation data may comprise a segmentation mask with object class identifiers associated with each pixel of an image of the scene. for example, each pixel included within a chair is associated with an object class identifier that is specific to a chair. the segmentation data enables clustering of objects in image space where the objects in each cluster share radio materials and therefore share scene properties.
20250182380. Displaced Micro-meshes Ray Path Tracing (NVIDIA)
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: a global illumination data structure (e.g., a data structure created to store global illumination information for geometry within a scene to be rendered) is computed for the scene. additionally, reservoir-based spatiotemporal importance resampling (restir) is used to perform illumination gathering, utilizing the global illumination data structure. the illumination gathering includes identifying light values for points within the scene, where one or more points are selected within the scene based on the light values in order to perform ray tracing during the rendering of the scene.
20250182404. FOUR-DIMENSIONAL OBJECT SCENE MODEL SYNTHESIS USING GENERATIVE MODELS (NVIDIA)
Abstract: in various examples, systems and methods are disclosed relating to generation of four-dimensional (4d) content models, such as 4d content models to render realistic sequences of frames of 3d data. the systems can initialize a 3d component of the 4d content model, such as a 3d gaussian splatting representation, based at least on a prompt for the 4d content. the system can configure motion and/or dynamics for the sequence of frames by evaluating frames rendered from the 4d content model using one or more latent diffusion models (ldms), including a video ldm. the system can perform operations such as autoregressive generation of frames to create long sequences of content, motion amplification to facilitate realistic, dynamic motion generation, and regularization to facilitate generation of complex dynamics.
20250182435. DETECTING OCCLUDED OBJECTS WITHIN IMAGES AUTONOMOUS SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, detecting occluded objects within images or other sensor data representations for autonomous or semi-autonomous systems and applications is described herein. systems and methods described herein may determine when objects are occluded at portions of images using various techniques. for example, an image may be processed in order to determine classifications associated with objects depicted by the image and, the classifications, along with labels that are projected on the image using a map, may then be used to determine whether one or more of the objects are occluded in the image. for another example, a map may be used to determine first distances to points within an environment and a point cloud may be used to determine second distances to the points within the environment. the distances may then be used to determine whether one or more objects are occluded within the image.
20250182494. DETECTING OCCLUDED OBJECTS WITHIN IMAGES AUTONOMOUS SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, detecting occluded objects within images or other sensor data representations for autonomous or semi-autonomous systems and applications is described herein. systems and methods described herein may determine when objects are occluded at portions of images using various techniques. for example, an image may be processed in order to determine classifications associated with objects depicted by the image and, the classifications, along with labels that are projected on the image using a map, may then be used to determine whether one or more of the objects are occluded in the image. for another example, a map may be used to determine first distances to points within an environment and a point cloud may be used to determine second distances to the points within the environment. the distances may then be used to determine whether one or more objects are occluded within the image.
20250182502. ROBUST STATE ESTIMATION (NVIDIA)
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.
20250183891. LINE DRIVERS LOW-VOLTAGE SIGNALING BETWEEN DIFFERENT VOLTAGE DOMAINS (NVIDIA)
Abstract: line drivers for high-bandwidth wireline transceivers that utilize both nfet and pfet pull-up devices to reduce supply sensitivity of low-voltage signals that cross voltage domains, for example between chips. also ac-coupled latching receivers for level translation and amplification in low-voltage wireline transceivers to reduce supply sensitivity of low-voltage signals that cross voltage domains, for example between chips.
Abstract: in various examples, an interactive agent platform that hosts development and/or deployment of an interactive agent may provide an interpreter or compiler that interprets or executes code written in the interaction modeling language, and a designer may provide customized code written in the interaction modeling language for the interpreter to execute. the interaction modeling language may be used to define a flow of interactions that instruct the interpreter what actions or events to generate in response to a sequence of detected and/or executed human-machine interactions. the interaction categorization schema may classify interactions by standardized interaction modality and/or corresponding standardized action category. as such, a flow may be used to model an agent intent or inferred user intent, which a designer may use to build more complex interaction patterns with the interactive agent.
20250184292. MANAGING INTERACTION FLOWS INTERACTIVE SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, an interactive agent platform that hosts development and/or deployment of an interactive agent may include an interpreter programmed to iterate though one or more flows until reaching an event matcher, a top level flow may specify instruction(s) to activate any number of flows comprising any number of event matchers, the interpreter may use any suitable data structure to keep track of active flows and corresponding event matchers (e.g., using a tree or other representation of nested flow relationships), and the interpreter may employ an event-driven state machine that listens for various events and triggers corresponding actions specified in matching flows (with event matchers that match an incoming interaction modeling api event). as such, the interpreter may execute a primary processing loop that processes incoming interaction modeling api events and generates outgoing interaction modeling api events that implement the interactive agent.
20250184293. SENSORY PROCESSING ACTION EXECUTION INTERACTIVE SYSTEMS APPLICATIONS (NVIDIA)
Abstract: in various examples, an interactive agent platform that hosts development and/or deployment of an interactive agent may include a sensory server for each input interaction channel and an action server for each output interaction channel. sensory server(s) for corresponding input interaction channel(s) may translate inputs or non-standard technical events into the standardized format and generate corresponding interaction modeling api events, an interaction manager may process these incoming interaction modeling api events and generate outgoing interaction modeling api events representing commands to take some type of action, and action server(s) for corresponding output interaction channel(s) may interpret those outgoing interaction modeling api events and execute the corresponding commands. as such, the interactive agent platform may decouple sensory processing, interaction decision-making, and action execution.
20250184383. ENCODING OUTPUT STREAMING APPLICATIONS BASED CLIENT UPSCALING CAPABILITIES (NVIDIA)
Abstract: in various examples, the decoding and upscaling capabilities of a client device are analyzed to determine encoding parameters and operations used by a content streaming server to generate encoded video streams. the quality of the upscaled content of the client device may be monitored by the streaming servers such that the encoding parameters may be updated based on the monitored quality. in this way, the encoding operations of one or more streaming servers may be more effectively matched to the decoding and upscaling abilities of one or more client devise such that an increased number of client devices may be served by the streaming servers.
20250184473. APPLICATIONS DETECTION CAPABILITIES CAMERAS (NVIDIA)
Abstract: in one embodiment, a system receives pixel data from a pair of regions of an image generated by an imaging device, the pair of regions includes a first region and a second region, where the first region includes a first plurality of pixels and the second region includes a second plurality of pixels. the system determines a plurality of pixel pairs, where a pixel pair includes a first pixel from the first plurality of pixels and a second pixel from the second plurality of pixels. the system calculates a plurality of contrasts based on the plurality of pixel pairs. the system determines a contrast distribution based on the plurality of contrasts. the system calculates a value representative of a capability of the imaging device to detect contrast based on the contrast distribution. the system determines a reduction in contrast detectability of the imaging device based on the value.