Some individuals may have hearing impairments and/or may be in situations that include impediments to hearing. The present disclosure relates to a method (800) comprising: generating (810) an audio signal based on sound received by one or more microphones of an open-ear device; and performing (820) a hearing enhancement process in response to user input, the hearing enhancement process comprising: detecting (830) a speech component of the audio signal; applying (840) a gain function to the speech component of the audio signal based on a plurality of gain parameters to generate a modified output signal; and operating (850) one or more loudspeakers of the open-ear device to produce sound according to the modified output signal.
H04R 1/34 - Dispositions pour obtenir la fréquence désirée ou les caractéristiques directionnelles pour obtenir la caractéristique directionnelle désirée uniquement en utilisant un seul transducteur avec des moyens réfléchissant, diffractant, dirigeant ou guidant des sons
Systems and methods for a MEMS microphone package are disclosed. The MEMS microphone package may include a first port to direct sound to a MEMS system, including a die substrate, an acoustic membrane, and one or more plates. The MEMS microphone package may include an ASIC to produce microphone output based on an electrical signal, a PCB, a lid, and a second port. The first port and the second port may define a front volume and a back volume respectively. The second port may increase the back volume to improve sensitivity and reduce the acoustic sensor's noise floor to improve signal-to-noise ratio.
A system and method for typeahead image generation are provided. The method may include receiving, via a user interface during a prompting session, a text prompt describing an image. The method also may include generating, via a trained diffusion model, the image representative of the text prompt. The method further may include determining, via the trained diffusion model, a reconciled risk score based on a determined risk score of the text prompt and a determined risk score of the generated image. The method even further may include causing, via the trained diffusion model in response to the determined reconciled risk score, to (i) approve the generated image in an instance in which the determined reconciled risk score meets or exceeds a predetermined threshold, or (ii) deny the generated image in an instance in which the determined reconciled risk score fails to meet the predetermined threshold.
The present disclosure is generally directed to techniques for editing a portion of a 3D scene represented by a neural field model. Examples of the present disclosure may erase an object from a 3D scene by identifying the object in one or more images of the scene and generating mask regions around (e.g., covering) the object in these images. A neural field model that represents the scene without the object in it may be trained by relying on an image generative model configured for inpainting. When trained, this 'background' neural field model can be used to render the implicit background of light rays that pass through the region of 3D space represented by the mask regions, thereby producing different views of the scene with the object effectively erased from the scene.
A system and method to generate personalized user interfaces are provided. The system may determine one or more items of demographic content associated with at least one user to obtain one or more user attributes. The system may determine one or more signals associated with a communication device associated with the at least one user or one or more user activities associated with the communication device or associated with at least one application associated with the communication device. The system may generate, based on the determined user attributes and the determined one or more signals, a first user interface, including content items and one or more elements, that is tailored or personalized to the at least one user.
Methods and systems are described for audio pipelines between a user and a machine learning (ML) model. The method involves obtaining digital audio data associated with an audio signal from a user's equipment. This data is then analyzed using a trained ML model, which includes one or more neural networks. The ML model determines an indication related to the digital audio data, which can be a prediction of the ending of one or more portions of the data, an intention behind the data, a key term within the data, an action to take based on the data, or the context associated with the data. Based on the determined indication, a response is generated and subsequently transmitted back to the user's equipment.
G10L 25/30 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par la technique d’analyse utilisant des réseaux neuronaux
A system and method for translating speech are provided. The system may detect audio signals associated with speech data of a first user(s) and determine the speech data is associated with a first language. The system may translate words of the speech data associated with the first language to other words associated with a second language. The system may present the other words translated in the second language as text items to a display of a device of a second user(s) or output the other words in the second language as audio to the second user(s). The system may generate, in response to the speech data, a first set of replies in the first language and a corresponding second set of other replies in the second language presented via the display. The other replies may include a translation in the second language of the replies in the first language.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
A system and method for determining interesting text to trigger actions of devices are provided. The system may include one or more head-mounted devices associated with a network. A head mounted device(s) may capture an image(s) and/or a video(s) corresponding to an environment detected in a field of view of a camera(s). The image(s) and/or the video(s) may include one or more text items associated with the environment. The head mounted device may determine whether a text item(s) of the one or more text items is interesting. The head mounted device may extract the text item(s) determined as being interesting and may superimpose the text item(s) at a position in the image(s) and/or the video(s). The head mounted device may trigger, based on the text item(s) determined as being interesting, one or more actions capable of being performed by the head mounted device.
Techniques for enabling users logged-out of a social networking system to access content associated with the social networking system are described. For example, based at least in part on determining a user is unassociated with a social networking system, the social networking system may present content to the user. In some examples, the amount of content available to the user may be limited, in which the user may be prompted to create an account. In some examples, logged-out users may be prompted to pick topics associated with their interests, allowing the social networking system to curate content for logged-out users.
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
A method for user input includes displaying a received message to a user on a user interface, displaying multiple characters as a one-dimensional (1D) list on the user interface, and receiving, from the user through the user interface, a first scrolling selection of a first character from the 1D list. The method further includes providing an input to a language model, the input including the received message and the first character, and responsive to providing the input, receiving a suggested output from the language model and displaying the suggested output on the user interface.
G06F 3/023 - Dispositions pour convertir sous une forme codée des éléments d'information discrets, p. ex. dispositions pour interpréter des codes générés par le clavier comme codes alphanumériques, comme codes d'opérande ou comme codes d'instruction
G06F 3/0488 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels
11.
METHODS AND SYSTEMS FOR INTELLIGENT MESSAGE PLATFORMS
Methods and systems are described for an intelligent messaging platform between users to foster more an immersive and creative messaging environment. In various examples, systems and methods may receive, via a device associated with a user, a media input. Context associated with the media input may be determined. The creation of a media item may be based on the media input and context associated with the media input. The creation of a media item may be based on the use of a machine learning model. The media may be provided to a user or group of users via one or more user devices associated with the users.
H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
H04L 51/52 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel pour la prise en charge des services des réseaux sociaux
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
H04L 51/04 - Messagerie en temps réel ou quasi en temps réel, p. ex. messagerie instantanée [IM]
Disclosed technology provides a solder ball including an outer layer having a first conductive material that is solid at an operating temperature of an electronic device, and an inner region having a second conductive material that flows at the operating temperature of the electronic device, wherein the inner region is surrounded by the outer layer. A method of manufacturing a solder ball includes forming an outer layer comprising a first conductive material that is solid at an operating temperature of an electronic device, wherein the outer layer surrounds an inner region, introducing a hole into the outer layer, injecting a second conductive material through the hole of the outer layer into the inner region, wherein the second conductive material flows at the operating temperature of the electronic device, and sealing the hole of the outer layer such that the second conductive material is retained within the inner region.
B23K 35/02 - Baguettes, électrodes, matériaux ou environnements utilisés pour le brasage, le soudage ou le découpage caractérisés par des propriétés mécaniques, p. ex. par la forme
The present application is at least directed to a method including a step of receiving audio from a user. The method may further include a step of generating, via a trained encoder based upon the received audio, an audio embedding sequence. The method may even further include a step of receiving, via a trained large language model (LLM), the generated audio embedding sequence and a text embedding sequence. The text embedding sequence is arranged before or after the generated audio embedding sequence. The method may yet even further include a step of producing, via the trained LLM based upon text embedding sequence, a textual response associated with the audio received from the user. The method may still even further include a step of causing to display, via a user interface of the user, the produced textual response.
Aspects of the present disclosure may include systems and methods generating visual content. The system may detect input of descriptive text associated with text content or audio content. The system may generate, based on the descriptive text, an initial latent representation by using a finetuned latent diffusion model. The system may apply a denoising process to the initial latent representation to produce a refined latent representation. The system may sample data points from a content distribution associated with prior timesteps and from a style distribution associated with subsequent timesteps, thereby generating a final image latent. The system may decode the final image latent to obtain a visually aligned image(s) corresponding to the descriptive text. The system may output the visually aligned image(s) on a user interface or a display.
content. A change in the modified post is of a first type when the evaluated quality is at or below a threshold or of a second type when the evaluated quality is above a threshold. Even a further step may include transmitting, via the user interface, the modified post for consideration by the user. Yet even a further step may include receiving, via the user interface, an indication of a rejection or an acceptance of the modified post.
Systems and methods are provided for generating adaptive content. The system may implement a machine learning model including training data pre-trained, or trained in real-time based on captured content or prestored content associated with gazes of users, pupil dilations, facial expressions, muscle movements, heart rates, or gaze dwell times of users determined previously or in real-time. The system may determine a gaze(s) of an eye of a user or facial features of a face associated with the user viewing, by a device, items of content in an environment. The system may include determining, based on the gaze(s) or facial features, a state(s) or interest(s) of the user. The system may determine, by implementing the machine learning model and based on the state(s) or interest(s) of the user, content to generate a modification of the items of content or to generate new content items associated with the items of content.
A system and method for removal of unwanted vibration noise are provided. The system may detect, by a microphone(s) of the system, at least one audio signal including audio content output from at least one speaker and other audio data from one or more other sources, or caused by the one or more other sources. The other audio data may include determined undesirable vibration noise causing distortion of the at least one audio signal. The system may determine, by at least one sensor of the system, a subset of the other audio data based in part on determining at least one motion of a user of the system, or motion of one or more other users. The system may remove, or reduce, the undesirable vibration noise from the at least one audio signal to enable output of sound associated with a modification of the at least one audio signal.
H04R 1/40 - Dispositions pour obtenir la fréquence désirée ou les caractéristiques directionnelles pour obtenir la caractéristique directionnelle désirée uniquement en combinant plusieurs transducteurs identiques
18.
3D PRINTING TO FORM AN OPTICAL LENS WITH INTEGRATED ELECTRONICS
In various embodiments, a device includes an optical substrate and one or more electrical components coupled to the optical substrate. The device includes one or more polymer materials additively printed around the one or more electrical components to at least in part encapsulate the one or more electrical components and form at least a portion of an optical lens.
A system and method for determining content to recommend to a user interface are provided. The system may determine contexts of users within environments. The system may implement a machine learning model including training data pre-trained, or trained in real-time based on historical interactions of users with data, or determined interactions with content by the users in real time. The system may analyze an item(s) of context information associated with the contexts to determine content relevant to a user associated with the system capturing content items within an environment. The system may analyze the item(s) of context information or other items of context information to determine contextual variables, of the environments, determined as relevant to the system. The system may utilize the determined content relevant to the user and the contextual variables determined as relevant to the system to determine a recommendation(s) or action(s) to present to a user interface.
In one embodiment, a method includes receiving a first user input from a user from a client system comprising a head-mounted extended-reality (XR) device, determining the user's intent to activate an XR cubic keyboard based on the first user input, rendering the XR cubic keyboard via XR displays of the head-mounted XR device, wherein the XR cubic keyboard comprises input areas representing respective characters in a three-dimensional (3D) space, and wherein the input areas are reachable by respective vectors from a centroid of the XR cubic keyboard in the 3D space, receiving a second user input comprising a hand movement of the user along a direction of a first vector from the centroid of the XR cubic keyboard in the 3D space, determining a first character that the user intended to input, and rendering an indication of the first character via the XR displays.
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
G06F 3/023 - Dispositions pour convertir sous une forme codée des éléments d'information discrets, p. ex. dispositions pour interpréter des codes générés par le clavier comme codes alphanumériques, comme codes d'opérande ou comme codes d'instruction
G06F 3/04815 - Interaction s’effectuant dans un environnement basé sur des métaphores ou des objets avec un affichage tridimensionnel, p. ex. modification du point de vue de l’utilisateur par rapport à l’environnement ou l’objet
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
21.
MULTI-LAYER AND FINE-GRAINED INPUT ROUTING FOR EXTENDED REALITY ENVIRONMENTS
A method implemented by a computing device includes displaying on a display of the computing device an extended reality (XR) environment, and determining one or more virtual characteristics associated with a first virtual content and a second virtual content viewable within the displayed XR environment, in which the second virtual content is at least partially occluded by the first virtual content. The method further includes generating, based on the one or more virtual characteristics, a plurality of user input interception layers to be associated with the first virtual content and the second virtual content, and in response to determining a user intent to interact with the second virtual content, directing one or more user inputs to the second virtual content based on whether or not the one or more user inputs are intercepted by one or more of the plurality of user input interception layers.
Three-dimensional application specific integrated circuit (IC) architecture is described herein. In one aspect, an IC may include a first die including: a first semiconductor layer; a plurality of processing elements (PEs) located on the first semiconductor layer; and a first interface region of the first semiconductor layer, electrically coupled to the plurality of PEs and configured to communicate electrical signals with the plurality of PEs; a second die including: a second semiconductor layer; a plurality of IC elements located on the second semiconductor layer; and a second interface region of the second semiconductor layer, electrically coupled to the plurality of IC elements and configured to communicate electrical signals to the plurality of IC elements, where the first interface region and the second interface region are electrically coupled to each other and configured to transmit electrical signals between the plurality of PEs and the plurality of IC elements.
H01L 25/065 - Ensembles consistant en une pluralité de dispositifs à semi-conducteurs ou d'autres dispositifs à l'état solide les dispositifs étant tous d'un type prévu dans une seule des sous-classes , , , , ou , p. ex. ensembles de diodes redresseuses les dispositifs n'ayant pas de conteneurs séparés les dispositifs étant d'un type prévu dans le groupe
H01L 23/60 - Protection contre les charges ou les décharges électrostatiques, p. ex. écrans Faraday
H01L 25/18 - Ensembles consistant en une pluralité de dispositifs à semi-conducteurs ou d'autres dispositifs à l'état solide les dispositifs étant de types prévus dans plusieurs différents groupes principaux de la même sous-classe , , , , ou
23.
SCENE-BASED TEXT-TO-IMAGE GENERATION WITH HUMAN PRIORS
In one embodiment, a method includes accessing a text input and a scene input corresponding to the text input, wherein the scene input comprises semantic segmentations, generating text tokens for the text input and scene tokens for the scene input by machine-learning models, generating predicted image tokens based on the text tokens and the scene tokens by the machine-learning models, and generating an image corresponding to the text input and the scene input based on the predicted image tokens by the machine-learning models.
G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/70 - Étiquetage du contenu de scène, p. ex. en tirant des représentations syntaxiques ou sémantiques
G06V 40/16 - Visages humains, p. ex. parties du visage, croquis ou expressions
24.
METHODS, APPARATUSES AND COMPUTER PROGRAM PRODUCTS FOR PROVIDING VIRTUAL CAMERAS FOR HARDWARE INPUTS
Systems and methods for providing a camera of a device as a virtual camera for one or more other communication devices are disclosed. The device may receive one or more requests from one or more communication devices to utilize a camera of the device as a virtual camera of the one or more communication devices. The device may allow access to the camera of the device to at least one of the one or more communication devices. The device may enable the at least one communication device to utilize the camera of the device to capture one or more images or videos. The device may enable provision of the captured one or more images or videos to the at least one communication device to enable display of the captured one or more images or videos by the at least one communication device.
H04N 23/661 - Transmission des signaux de commande de la caméra par le biais de réseaux, p. ex. la commande via Internet
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
In one embodiment, a method includes accessing sensor signals associated with a scene in a field of view of cameras of a head-mounted device associated with a first user from the head-mounted device, determining whether one or more criteria are satisfied for triggering a proactive analysis of the scene based on the sensor signals by machine-learning models, analyzing the scene to identify objects of interest to the first user in the scene based on the determination that the criteria are satisfied, generating a description of the objects based on an analysis of the objects and the sensor signals, wherein the description comprises relational information associated with one or more of the objects, and providing instructions to the head-mounted device to present an audio readout of the description to the first user.
In some embodiments, a computer-implemented method includes receiving, at a security agent of a host central processing unit (CPU), accelerator firmware from flash memory; determining, at the security agent, whether the accelerator firmware includes a critical accelerator firmware component or a non-critical accelerator firmware component; authenticating, at the security agent, the critical accelerator firmware component instantaneously upon a determination that the accelerator firmware is the critical accelerator firmware component, wherein authenticating the critical accelerator firmware component yields an authenticated critical accelerator firmware component; and providing the authenticated critical accelerator firmware component to an accelerator via a sideband bus for execution at the accelerator.
G06F 21/44 - Authentification de programme ou de dispositif
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
27.
INTEGRATED CHIPLET-BASED CENTRAL PROCESSING UNITS WITH ACCELERATORS FOR VIDEO PROCESSING
In some embodiments, a method includes receiving, at a central processing unit (CPU)-based demultiplexer of a CPU, an input video data stream; performing, at the CPU, an accelerator decoding configuration assessment of an accelerator decoding configuration of an accelerator; and based upon the accelerator decoding configuration assessment, dynamically decoding CPU-based demultiplexer output from the CPU-based demultiplexer using a CPU-based decoding unit and an accelerator-based decoding unit. In some embodiments of the method, the accelerator decoding configuration assessment includes performing an accelerator-based decoding unit hardware configuration assessment of the accelerator-based decoding unit and a CPU-based decoding unit software configuration assessment of the CPU-based decoding unit software utilized for the CPU-based decoding unit.
G06F 21/44 - Authentification de programme ou de dispositif
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 9/38 - Exécution simultanée d'instructions, p. ex. pipeline ou lecture en mémoire
G06T 1/20 - Architectures de processeursConfiguration de processeurs p. ex. configuration en pipeline
H04L 67/00 - Dispositions ou protocoles de réseau pour la prise en charge de services ou d'applications réseau
H04N 19/127 - Établissement des priorités des ressources en matériel ou en calcul
H04N 19/42 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques caractérisés par les détails de mise en œuvre ou le matériel spécialement adapté à la compression ou à la décompression vidéo, p. ex. la mise en œuvre de logiciels spécialisés
28.
INTEGRATED CHIPLET-BASED CENTRAL PROCESSING UNITS WITH ACCELERATORS
In some embodiments, a system-on-chip, includes a central processing unit (CPU); an accelerator coupled to the CPU via a first die-to-die interconnect; and uniform memory coupled to the CPU via a second die-to-die interconnect. In some embodiments, in order to prevent use of accelerator memory for processing operations by the accelerator, the accelerator utilizes a uniform memory access tunneling system located in the accelerator to tunnel a high-level interconnect protocol associated with the second die-to-die interconnect to a die-to-die interconnect protocol associated with the first die-to-die interconnect, the uniform memory access tunneling system being configured to allow access to the uniform memory using a shared address space.
G06F 21/71 - Protection de composants spécifiques internes ou périphériques, où la protection d'un composant mène à la protection de tout le calculateur pour assurer la sécurité du calcul ou du traitement de l’information
G06F 12/0842 - Systèmes de mémoire cache multi-utilisateurs, multiprocesseurs ou multitraitement pour multitraitement ou multitâche
An audio processing system includes: a receiver configured to receive the original audio data; a processor configured to execute the instructions stored in the memory to cause the audio processing system to: separate a background noise audio data, a first speaker audio data, and a second speaker audio data; recognize first speaker speech, convert the first speaker speech to first speaker text, translate the first speaker text to a second language text, and convert the second language text to a second speech; recognize second speaker speech, convert the second speaker speech to second speaker text, translate the second speaker text to the second language text, and convert the second language text of the second speaker to a second speech for the second speaker; and generate encoded audio data; and a transmitter configured to transmit the encoded audio data to a content user device.
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
G10L 13/00 - Synthèse de la paroleSystèmes de synthèse de la parole à partir de texte
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
The disclosed systems and methods may include (1) presenting a social media interface including visible content, hidden content, and a hidden content entry element that corresponds to the hidden content, where the hidden content is configured to be made visible via the social media interface in response to a digital gesture being applied to the hidden content entry element, (2) receiving user input applying the digital gesture to the hidden content entry element, and (3) in response to receiving the user input, presenting the hidden content via the social media interface.
G06F 3/048 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI]
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
H04L 67/02 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP]
31.
SMART CONTENT RENDERING ON AUGMENTED REALITY SYSTEMS, METHODS, AND DEVICES
A system and method for providing contextually-based content displays are provided. The system may include a device having a display providing content in a viewable region of the display. The device may include a camera device configured to track a scene of a real-world environment captured in a field of view of the camera device. The device may determine a region of interest in the scene. The device may perform object recognition on the scene tracked by the camera device. The device may determine an environmental interaction based on the object recognition and the region of interest. The device may adaptively alter, based on the environmental interaction, a position of the content provided by the display.
A system includes a first integrated circuit package including a first group of one or more artificial intelligence processing units and a first chip-to-chip interconnect communication unit and a second integrated circuit package including a second group of one or more artificial intelligence processing units and a second chip-to-chip interconnect communication unit. The system also includes an interconnect between the first integrated circuit package and the second integrated circuit package, wherein the first chip-to-chip interconnect communication unit and the second chip-to-chip interconnect communication unit manage ethernet-based communication via the interconnect using a layered communication architecture supporting a credit-based data flow control and a retransmission data flow control.
G06F 15/173 - Communication entre processeurs utilisant un réseau d'interconnexion, p. ex. matriciel, de réarrangement, pyramidal, en étoile ou ramifié
G06F 15/78 - Architectures de calculateurs universels à programmes enregistrés comprenant une seule unité centrale
H04L 47/10 - Commande de fluxCommande de la congestion
H04L 69/08 - Protocoles d’interopérabilitéConversion de protocole
33.
ANTICIPATIVE VIDEO TRANSFORMER MODEL FOR FUTURE ACTION ANTICIPATION
In particular embodiments, a computing system may receive a video comprising a plurality of image frames. The system may generate, for each image frame in the plurality of image frames and using a spatial-attention encoder, an image-frame feature corresponding to the image frame. For each image-frame feature, the system may generate, using a temporal-attention decoder, a predicted future feature based on one or more of the image-frame features corresponding to one or more of the plurality of image frames that precede a time associated with the predicted future feature. The system may generate a future action anticipation based on the predicted future feature. The future action anticipation corresponds to an anticipation of a future action occurring after a sequence of actions observed in the plurality of images frames in the video.
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
34.
SYSTEM AND METHOD FOR INCORPORATING AUDIO INTO AUDIOVISUAL CONTENT
In some embodiments, a method includes detecting an incorporation attribute of audiovisual content; analyzing an audio library to determine an audio file that maps to the incorporation attribute; selecting the audio file from the audio library that maps to the incorporation attribute; incorporating the selected audio file into the audiovisual content to generate egocentric audiovisual content; and providing the egocentric audiovisual content to a user for audiovisual consumption. In some embodiments of the method, the incorporation attribute is at least one of a mood of a target of the audiovisual content, an activity of the target of the audiovisual content, and a background of the audiovisual content.
G11B 27/031 - Montage électronique de signaux d'information analogiques numérisés, p. ex. de signaux audio, vidéo
G11B 27/10 - IndexationAdressageMinutage ou synchronisationMesure de l'avancement d'une bande
G06F 16/68 - Recherche de données caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
35.
SELECTIVE ACKNOWLEDGEMENT FRAMEWORK FOR HIGH-PERFORMANCE NETWORKS
According to examples, a selective acknowledgement framework may be implemented within a communication system for efficient communication of acknowledgement packets. A plurality of data packets generated from a message may be transmitted as a segment of data packets to a receiver which generates an acknowledgement packet for the segment of data packets. A compact format of acknowledgement (ACK) or negative acknowledgement (NACK) for the segment of data packets may be implemented in the acknowledgement packet via bits of a selective acknowledgement bit vector. Based on the other values also conveyed in the acknowledgement packet, the transmitter may identify those data packets that were properly received and the data packets that need to be re-transmitted.
A tunable fluorescent quantum dot may be utilized for illumination of artificial reality displays or waveguides. The tunable quantum dot may include a core fluorescence quantum dot and multiple coatings that may activate based on different wavelengths of one or more activation energies.
Methods, systems, and storage media for attributing origination to content creators are disclosed. Exemplary implementations may: determine whether content created by a user is original; in response to determining that the content is original, track the content created by the user through the social media platform; determine whether other users have leveraged the at least one attribute of the content; in response to determining that at least one other user has leveraged the at least one attribute of the content, generate a metric that represents a popularity of the at least one attribute of the content; update the popularity of the at least one attribute of the content; and cause display of the metric through a user interface of the social media platform.
A system for eye tracking is disclosed. The system may detect illumination including a first wavelength emitted from one or more illumination sources. The illumination may propagate along a waveguide(s) to a termination node(s) associated with the waveguide(s). The system may detect the illumination propagating a remote fluorophore located at the termination node(s). The system may determine that the remote fluorophore shifted the first wavelength to a second wavelength such that the illumination includes the second wavelength.
H01S 5/02251 - Découplage de lumière utilisant des fibres optiques
H01S 5/02257 - Découplage de lumière utilisant des fenêtres optiques, p. ex. spécialement adaptées pour réfléchir de la lumière sur un détecteur à l’intérieur du boîtier
Methods, systems, and storage media for facilitating collaboration on video media items are disclosed. Exemplary implementations may: receive, from a first user device, a video media item having core video content and an enhancement; store the received video media item on a server in an editable format; share the video media item, in the editable format, with a second user device; receive, from the second user device, a modification to the shared video media item to create a collaborative video media item; store the collaborative video media item on the server; and cause the collaborative video media item to be published in a non-editable format on a social media platform that supports display of user-created video media items.
H04N 21/231 - Opération de stockage de contenu, p. ex. mise en mémoire cache de films pour stockage à court terme, réplication de données sur plusieurs serveurs, ou établissement de priorité des données pour l'effacement
H04N 21/472 - Interface pour utilisateurs finaux pour la requête de contenu, de données additionnelles ou de servicesInterface pour utilisateurs finaux pour l'interaction avec le contenu, p. ex. pour la réservation de contenu ou la mise en place de rappels, pour la requête de notification d'événement ou pour la transformation de contenus affichés
According to examples, a system for using artificial intelligence (AI) and machine learning (ML) techniques to generate and implement a configurable measurement platform is described. The system may include a processor and a memory storing instructions. The processor, when executing the instructions, may cause the system to access information associated with one or more events occurring on a platform with event activity, log and analyze the one or more events to generate measurement data associated with the event activity, and generate a metric associated with the measurement data. The processor, when executing the instructions, may then generate a computed metric value associated with the metric utilizing the measurement data, implement a platform computation utilizing the computed metric value, and facilitate a decision associated with the platform based on the platform computation.
A system for generating simulated data is disclosed. The system may determine items of content utilized by a network. The system may also retrieve one or more data patterns associated with one or more features associated with the content. The system may also determine a plurality of indices associated with the data patterns. The system may also generate, based on the data patterns and the plurality of indices, simulated data associated with the content.
G06F 18/213 - Extraction de caractéristiques, p. ex. en transformant l'espace des caractéristiquesSynthétisationsMappages, p. ex. procédés de sous-espace
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
42.
SYSTEM AND METHOD FOR INTEGRATED CIRCUIT (IC) NANOMETER RANGE INTERCONNECT FABRICATION
According to examples, an interconnect system for integrated circuits (ICs) may be fabricated by processing a substrate implanted with copper wells with a photoresist layer such that remaining portions of the photoresist layer expose portions of the copper wells; depositing a barrier layer over a top surface of the wafer, depositing a seed copper layer over the barrier layer; depositing a copper layer over the seed copper layer; planarizing the copper layer and portions of the barrier layer; depositing another copper layer over exposed portions of the substrate, the copper wells, and the interconnect cores; removing portions of the other copper layer between interconnects by processing the second copper layer with another photoresist layer; and removing remaining portions of the other photoresist layer on the interconnects.
H01L 21/768 - Fixation d'interconnexions servant à conduire le courant entre des composants distincts à l'intérieur du dispositif
H01L 23/485 - Dispositions pour conduire le courant électrique vers le ou hors du corps à l'état solide pendant son fonctionnement, p. ex. fils de connexion ou bornes formées de couches conductrices inséparables du corps semi-conducteur sur lequel elles ont été déposées formées de structures en couches comprenant des couches conductrices et isolantes, p. ex. contacts planaires
43.
DETECTING SILENT DATA CORRUPTIONS WITHIN A LARGE SCALE INFRASTRUCTURE
Systems, apparatuses and methods provide technology for conducting silent data corruption (SDC) testing in a network including a fleet of production servers comprising generating a first SDC test selected from a repository of SDC tests, submitting the first SDC test for execution on a plurality of servers selected from the fleet of production servers, wherein for each respective server of the plurality of servers the first SDC test is executed as a test workload in co-location with a production workload executed on the respective server, determining a result of the first SDC test performed on a first server of the plurality of servers, and upon determining that the result of the first SDC test performed on the first server is a test failure, removing the first server from a production status, and entering the first server in a quarantine process to investigate and to mitigate the test failure.
Embodiments relate to an integrated circuit package having an integrated circuit die connected to a package substrate through conductors of a flex cable. The flex cable includes an insulating housing made of an insulating material and a plurality of conductors disposed inside the insulating housing. Each conductor of the plurality of conductors is connected to a first contact of a plurality of contacts of the integrated circuit die and a second contact of a plurality of contacts of the package substrate.
H01L 23/498 - Connexions électriques sur des substrats isolants
45.
METHODS, APPARATUSES AND COMPUTER PROGRAM PRODUCTS FOR UTILIZING GESTURES AND EYE TRACKING INFORMATION TO FACILITATE CAMERA OPERATIONS ON ARTIFICIAL REALITY DEVICES
Systems and methods are provided for operating image modules via an artificial reality (AR) device. In various exemplary embodiments, an artificial reality device may initiate a first camera of the AR device to identify a picture region and may track at least one gaze via a second camera of the AR device or at least one gesture via the first camera. The AR device may be a head-mounted device, for example, including a plurality of inward and outward facing cameras. The AR device may determine a region of interest within the picture region based on the at least one tracked gaze or gesture and may focus on the region of interest via the first camera. The focusing operations may include at least one of an auto-exposure operation, an auto-focus operation, or a stabilizing operation.
A social networking system may generate a region of an interactive map and determine a zoom level at which the interactive map is being presented. The social networking system may then determine a first defined geographic region based at least in part on the region being displayed and the zoom level at which the interactive map is being displayed. A quantity of content items that exists that are associated with the first define geographic region can be determined by the system. The social networking system may then present, based at least in part on the quantity, a visual representation on the interactive map of one or more content items associated with at least one of the first defined geographic region or a second defined geographic region that encompasses the first defined geographic region.
Techniques for providing social network maps are described. For example, a social networking system may receive, from a first user account associated with the social networking system, a content item associated with a location. The social networking system presents a control usable to provide multiple different types of feedback associated with the location. In some examples, the social networking system then generates an interactive map which comprises a visual representation of the content item associated with the location on the interactive map to a second user account. Upon receiving input comprising a selection of a particular type of feedback from among the multiple different types of feedback, the social networking system the performs an action associated with the selected particular type of feedback.
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
G06F 16/9537 - Recherche à dépendance spatiale ou temporelle, p. ex. requêtes spatio-temporelles
A semiconductor design that uses high refractive index material between low refractive index material. In particular, a semiconductor wafer and method for creating a semiconductor wafer comprising an inner crack stop structure and a waveguide, wherein the waveguide directs light. And, a method for checking integrity of a semiconductor chip.
G02B 6/12 - Guides de lumièreDétails de structure de dispositions comprenant des guides de lumière et d'autres éléments optiques, p. ex. des moyens de couplage du type guide d'ondes optiques du genre à circuit intégré
G02B 6/13 - Circuits optiques intégrés caractérisés par le procédé de fabrication
G01N 21/95 - Recherche de la présence de criques, de défauts ou de souillures caractérisée par le matériau ou la forme de l'objet à analyser
G02B 6/122 - Éléments optiques de base, p. ex. voies de guidage de la lumière
Techniques are described for a social networking system to provide group or aggregation accounts that allow users to easily and quickly form relationships with multiple other users based on a membership association of the multiple users to the group account. In some cases, the social networking system may be configured to add and/or remove relationships based on changes in association between members and the group account.
H04L 51/52 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel pour la prise en charge des services des réseaux sociaux
50.
SYSTEMS AND METHODS OF UNCERTAINTY-AWARE SELF-SUPERVISED-LEARNING FOR MALWARE AND THREAT DETECTION
A system may be configured to perform self-supervised learning for malware and threat intelligence such that unlabeled data is effectively used. Some embodiments may: obtain training data comprising executable portions of unlabeled information; learn, from the training data, latent representations of the unlabeled information; automatically determine labels from the training data based on the learned latent representations of the unlabeled information; predict, via contrastive learning trained using the labeled training data and deployed using the unlabeled training data, a deterministic distribution of points in a latent space that indicates whether the executable portion(s) belongs to classes or clusters; and estimate, via a machine-learning model, an uncertainty distribution of points around the executable portion(s) indicated as belonging to one of the classes or clusters. The uncertainty distribution may indicate a confidence that the respective determined label accurately describes the latent representation(s) of the one class or cluster.
A system for network optimization using geo-data may access a set of geotagged data samples associated with a cell. The set of geotagged data samples may be obtained from an application associated with one or more user equipment associated with the cell and the cell includes at least one antenna. The system may also determine a metric associated with the cell based on the set of geotagged data samples, generate one or more antenna adjustments based on the metric, and predict, based on the one or more antenna adjustments, a performance improvement associated with the cell.
H04B 7/26 - Systèmes de transmission radio, c.-à-d. utilisant un champ de rayonnement pour communication entre plusieurs postes dont au moins un est mobile
Aspects of the present disclosure are directed to an artificial intelligence ("AI") application running in conjunction with an artificial reality ("XR") space. The AI Builder responds to user commands, verbal or gestural, to build or edit spaces or objects in space. If the requested object is of a type recognized by the AI Builder, then the AI Builder builds the object from one or more stored templates. The new object's location is determined by the objects that already exist in the user's XR environment and on commands or gestures from the user. If the AI Builder does not recognize the requested object, the user can show an image to the AI Builder, and the AI builds a 3D object in the XR space according to that image. To ease collaboration among users, the AI Builder may present its user interface as a non-player character within the XR world.
A63F 13/213 - Dispositions d'entrée pour les dispositifs de jeu vidéo caractérisées par leurs capteurs, leurs finalités ou leurs types comprenant des moyens de photo-détection, p. ex. des caméras, des photodiodes ou des cellules infrarouges
A63F 13/215 - Dispositions d'entrée pour les dispositifs de jeu vidéo caractérisées par leurs capteurs, leurs finalités ou leurs types comprenant des moyens de détection des signaux acoustiques, p. ex. utilisant un microphone
A63F 13/63 - Création ou modification du contenu du jeu avant ou pendant l’exécution du programme de jeu, p. ex. au moyen d’outils spécialement adaptés au développement du jeu ou d’un éditeur de niveau intégré au jeu par le joueur, p. ex. avec un éditeur de niveaux
A63F 13/428 - Traitement des signaux de commande d’entrée des dispositifs de jeu vidéo, p. ex. les signaux générés par le joueur ou dérivés de l’environnement par mappage des signaux d’entrée en commandes de jeu, p. ex. mappage du déplacement d’un stylet sur un écran tactile en angle de braquage d’un véhicule virtuel incluant des signaux d’entrée de mouvement ou de position, p. ex. des signaux représentant la rotation de la manette d’entrée ou les mouvements des bras du joueur détectés par des accéléromètres ou des gyroscopes
A63F 13/424 - Traitement des signaux de commande d’entrée des dispositifs de jeu vidéo, p. ex. les signaux générés par le joueur ou dérivés de l’environnement par mappage des signaux d’entrée en commandes de jeu, p. ex. mappage du déplacement d’un stylet sur un écran tactile en angle de braquage d’un véhicule virtuel incluant des signaux d’entrée acoustiques, p. ex. en utilisant les résultats d’extraction de hauteur tonale ou de rythme ou de reconnaissance vocale
A63F 13/67 - Création ou modification du contenu du jeu avant ou pendant l’exécution du programme de jeu, p. ex. au moyen d’outils spécialement adaptés au développement du jeu ou d’un éditeur de niveau intégré au jeu en s’adaptant à ou par apprentissage des actions de joueurs, p. ex. modification du niveau de compétences ou stockage de séquences de combats réussies en vue de leur réutilisation
Aspects of the present disclosure are directed to creating a skybox for an artificial reality ("XR") world from a two-dimensional ("2D") image. The 2D image is scanned and split into at least two portions. The portions are mapped onto the interior of a virtual enclosed 3D shape, for example, a virtual cube. A generative adversarial network (GAN) interpolates from the information in the areas mapped from the portions to fill in at least some unmapped areas of the interior of the 3D shape. The 3D shape can be placed in a user's XR world to become the skybox surrounding that world.
The present invention provides systems and methods for color tuning optical modules and executing color calibration methods on artificial reality systems and devices. Embodiments can include a lens with a colored coating, a plurality of cameras, including a visible spectrum camera and an infrared camera, each positioned behind the lens, and a processor and memory. The colored coating includes a plurality of regions for selectively transmitting light. The processor and memory can be configured to receive light information indicative of environmental information for executing an operation on the device, identify wavelengths of light reflected by the color profile in front of each camera, determine a color calibration to amplify wavelengths of reflected light, update the environmental information based on the color calibration, and execute the operation on the device.
A radio unit that is configured to perform calibration of its antennas for beamforming is disclosed. The radio unit may comprise a combiner. The combiner may be configured to cause the antennas to transmit calibration signals. The combiner may cause the calibration signals to rotate to different phases. The different phases may cause non-coherent combining of noise of the calibration signals when the calibration signals are combined. The combiner may combine the rotated calibration signals and the noise may be cancelled by the radio unit. The combiner may calibrate the antennas based on the combined calibration signals.
H04B 17/12 - SurveillanceTests d’émetteurs pour l’étalonnage d’antennes d’émission, p. ex. de l’amplitude ou de la phase
H04B 17/21 - SurveillanceTests de récepteurs pour l’étalonnageSurveillanceTests de récepteurs pour la correction des mesures
H01Q 3/26 - Dispositifs pour changer ou faire varier l'orientation ou la forme du diagramme de directivité des ondes rayonnées par une antenne ou un système d'antenne faisant varier la phase relative ou l’amplitude relative et l’énergie d’excitation entre plusieurs éléments rayonnants actifsDispositifs pour changer ou faire varier l'orientation ou la forme du diagramme de directivité des ondes rayonnées par une antenne ou un système d'antenne faisant varier la distribution de l’énergie à travers une ouverture rayonnante
56.
CREST FACTOR REDUCTION (CFR) PULSE CANCELLATION (PC) WITH CONFIGURABLE BANDWIDTH AND CENTER FREQUENCY
A system and method for Crest Factor Reduction (CFR) pulse cancellation (PC) in a single carrier environment or multicarrier telecommunication environment may enable obtaining better signal quality while maintaining Peak to Average Power Ratio (PAPR) and/or power efficiency. A PC signal is generated by multiplying a truncated sinc signal with another window signal. The bandwidth of the PC signal may be greater than the bandwidth of the corresponding carrier signal center. The center frequency of the PC signal may be offset with respect to the center frequency for each given carrier in the multi-carrier scenario to fix the edge effect signal quality/interference problems.
Techniques for generating ephemeral collections of content items are described herein. For example, a social networking system may receive, from a first account, a request to generate a collection of content items, or a "collaborative story." The request may include an identifier associated with a second account that is to be associated with the collaborative story. Based on the request, the social networking system may generate the collaborative story and associate the second account therewith, designating the first account and the second account are as collaborators. In some examples, the social networking system may receive content from the first account and/or the second account and may publish the content in association with the collaborative story via the social networking system.
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
H04W 4/21 - Signalisation de servicesSignalisation de données auxiliaires, c.-à-d. transmission de données par un canal non destiné au trafic pour applications de réseaux sociaux
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
In one embodiment, a method includes accessing a first utterance of a content by a first speaker, generating first discrete speech units from the first utterance based on a speech-learning model, wherein each of the first discrete speech units is associated with a speech cluster, accessing second utterances of the content by second speakers different from the first speaker, and training a speech normalizer by processing each of the second utterances using the speech normalizer to generate second discrete speech units and updating the speech normalizer by using the first discrete speech units as an optimization target for the second discrete speech units associated with each of the second utterances.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
The disclosed computer-implemented method may include (1) determining a first stage estimated passive inter-modulation (PIM) noise using a nonlinear model, the nonlinear model receiving a nonlinear model input based on a transmitted signal, (2) training the nonlinear model using a training signal based on an uncorrected received signal, (3) determining an estimated PIM noise using the first stage estimated PIM noise and a finite impulse response (FIR) filter, (4) training the FIR using a second training signal based on the uncorrected received signal, and (5) subtracting the estimated PIM noise from the uncorrected received signal. Various other methods, systems, and devices are also disclosed.
H04B 1/10 - Dispositifs associés au récepteur pour limiter ou supprimer le bruit et les interférences
H04B 1/525 - Dispositions hybrides, c.-à-d. dispositions pour la transition d’une transmission bilatérale sur une voie à une transmission unidirectionnelle sur chacune des deux voies ou vice versa avec des moyens de réduction de la fuite du signal de l’émetteur vers le récepteur
60.
CODE QUALITY PREDICTION UNDER SUPER EXTREME CLASS IMBALANCE OR RESOURCE CONSTRAINTS
A method may leverage a large model pool to identify a reduced model pool of top model candidates. Empirical lower bounds may be determined on the required training samples to prevent cross validation fold failures while keeping the training size minimal. Subsequently steps are performed for rigorous model validation at larger scales to obtain unbiased estimates for the full model performance distribution. In addition, a Top-K Meta Ensemble (TKME) architecture may combine and perform fine-tuning of the inferences from the reduced model pool.
A computer-implemented method for storing and transmitting video files may include (i) encoding a video file at a group of different resolutions by (a) generating a group of base layers for the video file, each at a different resolution within the different resolutions and (b) generating an enhancement layer for the video file that, when combined with any base layer for the video file, increases the effective resolution of a resulting combined video file over a resolution of the base layer, (ii) receiving a request for the video file at a specified resolution, and (iii) providing the video file at the specified resolution by, in response to receiving the request, selecting an appropriate base layer from the base layers to combine with the enhancement layer to achieve the specified resolution. Various other methods, systems, and computer-readable media are also disclosed.
H04N 19/30 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant des techniques hiérarchiques, p. ex. l'échelonnage
A system is described. The system includes a first group of data ports of one or more first elements of an integrated circuit and a second group of data ports of one or more second elements of the integrated circuit. The system also includes a point-to-point connection between a first data port of the first group of data ports to a second data port of the second group of data ports. In addition, the system includes, for the first data port, a distinct crossbar connected to every data port of the second group of data ports.
Methods, systems, and storage media for sharing content are disclosed. Exemplary implementations may: initiate a conversation through a communication interface of a secure messaging platform; select at least a first content item from a content list; post the first content item to the canvas; play the first content item that was posted to the canvas; select at least a second content item from the content list; post the second content item to the canvas; and queue the second content item to play after the first content item.
According to examples, a system for using artificial intelligence (AI) techniques to generate and deliver funding opportunities for entities based on associated data is described. The system may include a processor and a memory storing instructions. The processor, when executing the instructions, may cause the system to access input information related to a funding opportunity associated with an entity; analyze the input information to generate parameters associated with a funding opportunity model; and implement the funding opportunity model. The processor, when executing the instructions, may then modify an aspect of the funding opportunity model; simulate a funding opportunity with respect to the entity using the funding opportunity model; determine one or more aspects of the funding opportunity; verify the one or more aspects of the funding opportunity; and provide one or more funding options to the entity based on the verified one or more aspects of the funding opportunity.
Methods, systems, and storage video for enhancing region(s) of a subject's face in an augmented reality environment are provided. Exemplary implementations may include an AR face enhancing system that uses spatially-varying masks to enhance region(s) of a subject's face in an augmented reality environment. The AR face enhancing system may utilize a face tracker to smooth skin using one or more regionally-aligned meshes for each frame of a live digital video stream. The AR face enhancing system utilizes information related to regional uniformity and/or non-uniformity of pixels in a digital video stream to determine region(s) to which to apply highlights to, brightening, and/or darkening of a subject's face in an augmented reality environment. Additionally, the AR face enhancing system can adjust a user's skin tone or other facial features in the augmented reality layer by using regionally-applied tone mapping.
Methods, systems, and storage media for outputting a synchronized arrangement of a plurality of video streams are disclosed. Exemplary implementations may: select a stage status for a subset of the plurality of client devices; determine, based on the stage status, that a client device of the plurality of client devices is assigned a stage state; send, based on the stage status and the stage state being assigned to the client device, a server state to each client device of the plurality of client devices; determine, based on the server state, a graphical layout comprising a position and size of each video stream of the plurality of video streams to output to a graphical user interface; and provide, to each client device of the plurality of client devices, instructions to display the synchronized arrangement of the plurality of video streams according to the graphical layout.
Techniques are described for a social networking system to provide collective accounts that allow for multiple holders, editors, and/or managers. In some cases, the social networking system may be configured to distribute content associated with the collective accounts based on metrics and relationships associated with accounts of the contributors to the collective account as well as the collective account itself.
G06Q 10/101 - Création collaborative, p. ex. développement conjoint de produits ou de services
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
68.
SYSTEMS AND METHODS FOR DISAGGREGATED ACCELERATION OF ARTIFICIAL INTELLIGENCE OPERATIONS
A disclosed system may include a disaggregated artificial intelligence (AI) operation accelerator including a dense AI operation accelerator configured to accelerate dense AI operations and a sparse AI operation accelerator, physically separate from the dense AI operation accelerator, configured to accelerate sparse AI operations. The system may also include a scheduler that includes (1) a receiving module that receives an AI operation, (2) an identifying module that identifies the AI operation as a dense AI operation or sparse AI operation, and (3) a directing module that directs (a) the dense AI operation accelerator to accelerate identified dense AI operations, and (b) the sparse AI operation accelerator to accelerate identified sparse AI operations. The system may also include a physical processor that executes the receiving module, the identifying module, and the directing module. Various other methods, systems, and computer-readable media are also disclosed.
G06N 3/063 - Réalisation physique, c.-à-d. mise en œuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurone utilisant des moyens électroniques
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
69.
GENERATION AND DELIVERY OF TEXT-BASED CONTENT USING ARTIFICIAL INTELLIGENCE (AI) BASED TECHNIQUES
According to examples, a system for using artificial intelligence (AI) techniques to generate audio and video content based on text content is described. The system may include a processor and a memory storing instructions. The processor, when executing the instructions, may cause the system to analyze a plurality of text segments associated with a text content item having text content, determine an association between the plurality of text segments and arrange the plurality of text segments based on the determined association, wherein the arranging includes generating one or more text segment clusters. The processor, when executing the instructions, may then order the one or more text segment clusters according to one or more ordering criteria, implement a wording algorithm to generate text for a content item to be generated based on the text content and generate an audio association for the text for the content item to be generated.
Techniques are described for a social networking system to enable multiple users to collaboratively create, publish, receive attribution, and/or edit content. In some cases, the social networking system may be configured to distribute the collaborative content and feedback associated therewith based on metrics and relationships between collaborators of the collaborative content and users of the social networking system.
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
H04L 51/52 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel pour la prise en charge des services des réseaux sociaux
H04L 67/00 - Dispositions ou protocoles de réseau pour la prise en charge de services ou d'applications réseau
71.
TECHNIQUES FOR TRANSACTIONS ASSOCIATED WITH NON-FUNGIBLE TOKENS (NFT) USING ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING (ML)
According to examples, a system for transacting of virtual assets and/or associated non-fungible tokens (NFT) utilizing artificial intelligence (AI) and machine learning (ML) techniques is described. The system may include a processor and a memory storing instructions. The processor, when executing the instructions, may cause the system to generate a virtual asset; generate a non-fungible token (NFT) associated with the virtual asset; and determine a contractual item to facilitate a transaction for the virtual asset and the non-fungible token (NFT). The processor, when executing the instructions, may then generate a badge associated with the non-fungible token (NFT); receive an appraisal associated with the virtual asset; generate a valuation for the virtual asset based on the appraisal; and facilitate the transaction for the virtual asset and the non-fungible token (NFT) based on the valuation.
According to examples, a system for transacting of assets and/or associated non-fungible tokens (NFT) utilizing artificial intelligence (AI) and machine learning (ML) techniques is described. The system may include a processor and a memory storing instructions. The processor, when executing the instructions, may cause the system to identify a candidate asset, generate a transaction asset based on the candidate asset and generate a non-fungible token (NFT) associated with the transaction asset. The processor, when executing the instructions, may then determine a contractual item to facilitate a transaction for the transaction asset and a non-fungible token (NFT) associated with the transaction asset, generate a badge associated with the non-fungible token (NFT) and facilitate a transaction for the transaction asset and the non-fungible token (NFT).
A system including a computer storage and a processor is described. The computer storage is configured to identify a stored data as protected. The processor is configured to perform speculative execution. To perform the speculative execution, the processor is configured to determine, in response to the speculative execution of an instruction to read the stored data, whether the stored data is identified as protected. In response to a determination that the stored data attempted to be read during the speculative execution is protected, the processor is configured to disallow during the speculative execution immediate successful completion of the instruction to read the stored data.
Methods, systems, and storage media for intelligently enhancing media content items are disclosed. Exemplary implementations may: present a user interface for initiating creation of media content items within a media sharing application running on a media capture device, the user interface including one or more selectable media capture modes; receive a selection of one of the selectable media capture mode(s), the one of the selectable media capture mode(s) being configured to intelligently enhance the media content items; receive a plurality of signals from the media capture device and/or the media sharing application; determine at least one enhancement to apply to a captured media content item based upon at least a portion of the plurality of signals; receive a captured media content item; automatically apply the enhancement(s) to the captured media content item to create an enhanced media content item, and cause display of the enhanced media content item in a media preview window of the media sharing application.
H04N 21/462 - Gestion de contenu ou de données additionnelles, p. ex. création d'un guide de programmes électronique maître à partir de données reçues par Internet et d'une tête de réseau ou contrôle de la complexité d'un flux vidéo en dimensionnant la résolution ou le débit en fonction des capacités du client
H04L 51/52 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel pour la prise en charge des services des réseaux sociaux
H04L 65/75 - Gestion des paquets du réseau multimédia
H04L 67/561 - Ajout de données fonctionnelles à l’application ou de données de commande de l’application, p. ex. métadonnées
H04N 21/4788 - Services additionnels, p. ex. affichage de l'identification d'un appelant téléphonique ou application d'achat communication avec d'autres utilisateurs, p. ex. discussion en ligne
H04N 23/63 - Commande des caméras ou des modules de caméras en utilisant des viseurs électroniques
75.
SYSTEMS AND METHODS FOR OPTIMIZING A VIDEO STORAGE FOOTPRINT WHILE MINIMIZING USER IMPACT
The disclosed computer-implemented method may include generating a table for a plurality of encodings of media files stored in at least one data center, the generating including determining a benefit to cost ratio for each encoding listed in the table based on one or more criteria associated with the respective encoding, and assigning a priority to each of the encodings in the table based on the benefit to cost ratio, determining whether a soft quota for an amount of memory for storage of the media files has been exceeded, and in response to determining that a soft quota for an amount of memory for storage of the media files has been exceeded, performing a data storage reduction process based on the priority associated with each of the encodings in the table. Various other methods, systems, and computer-readable media are also disclosed.
H04N 21/231 - Opération de stockage de contenu, p. ex. mise en mémoire cache de films pour stockage à court terme, réplication de données sur plusieurs serveurs, ou établissement de priorité des données pour l'effacement
H04N 21/2343 - Traitement de flux vidéo élémentaires, p. ex. raccordement de flux vidéo ou transformation de graphes de scènes du flux vidéo codé impliquant des opérations de reformatage de signaux vidéo pour la distribution ou la mise en conformité avec les requêtes des utilisateurs finaux ou les exigences des dispositifs des utilisateurs finaux
76.
A NOVEL BUFFER FORMAT FOR A TWO-STAGE VIDEO ENCODING PROCESS
A system that includes a pixel processing stage decoupled from an entropy coding stage is disclosed. The pixel processing results comprise quantized transform coefficients that are divided into component blocks. The component blocks including non-zero data are identified. An optimized version of the pixel processing results for storage in a buffer storage is generated. The optimized version includes an identification of which of the component blocks include non-zero data, and the optimized version includes contents of one or more of the component blocks that include non-zero data, without including contents of one or more of the component blocks that only include zero data. The optimized version of the pixel processing results is provided for storage in the buffer storage. The optimized version of the pixel processing results from the buffer storage is received and processed to generate an unpacked version of the pixel processing results for use in entropy coding.
H04N 19/426 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques caractérisés par les détails de mise en œuvre ou le matériel spécialement adapté à la compression ou à la décompression vidéo, p. ex. la mise en œuvre de logiciels spécialisés caractérisés par les dispositions des mémoires utilisant des procédés de diminution de taille de mémoire
H04N 19/18 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c.-à-d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant un ensemble de coefficients de transformée
77.
INTEGRATED MACHINE LEARNING ALGORITHMS FOR IMAGE FILTERS
Various aspects of the subject technology relate to systems, methods, and machine-readable media for outputting filtered visual media content items. Various aspects may include receiving an input frame of a visual media content item. Aspects may also include training a machine learning algorithm based on a dataset of bracketed images. Aspects may include configuring a neural network based on image filtering of the input frame and via a shader component of a graphics processing unit. Aspects may include determining portions of the input frame that are associated with an extent of darkness. Aspects may include performing an image enhancement operation to the portions of the input frame. Aspects may include providing instructions to display an output frame changed by the image enhancement operation.
Methods, systems, and storage media for generating leads for vendors through a social media program are disclosed. Exemplary implementations may: estimate a conversion rank for an online promotion for a targeted prospect based at least in part on historical data of conversion ranks for a sample of the targeted prospect; simulate the online promotion to the sample of the targeted prospect; calculate a likelihood of conversion based on the simulating of the online promotion to the sample of the targeted prospect.
kkkkkkk orthogonal channel bands are separated by a pre-determined frequency separation that is large enough to avoid interference between the two channel bands, and sending the RF signals to a radio-frequency integrated circuit (RFIC) associated with the wireless communication device, where the RFIC transmits the RF signals wirelessly.
H04B 7/06 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
80.
UPLINK MU-MIMO FUNCTIONAL SPLIT BETWEEN RADIO UNIT AND DISTRIBUTED UNIT
H04B 7/0452 - Systèmes MIMO à plusieurs utilisateurs
H04B 7/08 - Systèmes de diversitéSystèmes à plusieurs antennes, c.-à-d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station de réception
H04L 5/00 - Dispositions destinées à permettre l'usage multiple de la voie de transmission
Methods, systems, and storage media for minting a digital collectible are disclosed. Exemplary implementations may: receive a request from a user to generate a digital collectible comprising user-created content; validate the user-created content was created by the user; receive a designation of a number of copies of the digital collectible that are to be generated; generate the digital collectible based on the user-created content; and record the digital collectible to a blockchain.
G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
G06Q 20/06 - Circuits privés de paiement, p. ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
The disclosed computer-implemented method may include discovering, by a computer processor and based on user information, that an identity of a user generating a live broadcast is enabled for dual streaming. The method may also include determining, by the computer processor and based at least in part on available network bandwidth, that the live broadcast is authorized for dual streaming. The method may further include transmitting separately, by the computer processor at least partly in response to the discovery and the determination, streams of the live broadcast to a plurality of different network nodes of a streaming platform. Various other methods, systems, and computer-readable media are also disclosed.
H04N 21/222 - Serveurs secondaires, p. ex. serveur proxy ou tête de réseau de télévision par câble
H04N 21/231 - Opération de stockage de contenu, p. ex. mise en mémoire cache de films pour stockage à court terme, réplication de données sur plusieurs serveurs, ou établissement de priorité des données pour l'effacement
H04N 21/24 - Surveillance de procédés ou de ressources, p. ex. surveillance de la charge du serveur, de la bande passante disponible ou des requêtes effectuées sur la voie montante
H04N 21/258 - Gestion de données liées aux clients ou aux utilisateurs finaux, p. ex. gestion des capacités des clients, préférences ou données démographiques des utilisateurs, traitement des multiples préférences des utilisateurs finaux pour générer des données collaboratives
H04N 21/274 - Stockage de contenu ou données additionnelles spécifiques aux utilisateurs finaux en réponse aux requêtes des utilisateurs finaux
83.
APPARATUS, SYSTEMS, AND METHODS FOR SOCIAL MEDIA STREAMING DEVICES
An apparatus for a social media streaming device may include (i) a camera connector that connects to and receives streaming video data from an external camera, (ii) a device connector that connects to and sends the streaming video data to a mobile device with network streaming capabilities, and (iii) a video processing module that enables the social media streaming device to, via the mobile device with network streaming capabilities, post the streaming video data to an account on a social media platform on behalf of a user. Various other methods, systems, and computer-readable media are also disclosed.
H04N 21/414 - Plate-formes spécialisées de client, p. ex. récepteur au sein d'une voiture ou intégré dans un appareil mobile
H04N 21/436 - Interfaçage d'un réseau de distribution local, p. ex. communication avec un autre STB ou à l'intérieur de la maison
H04N 21/4788 - Services additionnels, p. ex. affichage de l'identification d'un appelant téléphonique ou application d'achat communication avec d'autres utilisateurs, p. ex. discussion en ligne
H04N 21/2743 - Hébergement vidéo de données téléchargées à partir du dispositif client
H04N 21/4363 - Adaptation du flux vidéo à un réseau local spécifique, p. ex. un réseau Bluetooth®
H04N 21/442 - Surveillance de procédés ou de ressources, p. ex. détection de la défaillance d'un dispositif d'enregistrement, surveillance de la bande passante sur la voie descendante, du nombre de visualisations d'un film, de l'espace de stockage disponible dans le disque dur interne
H04N 21/258 - Gestion de données liées aux clients ou aux utilisateurs finaux, p. ex. gestion des capacités des clients, préférences ou données démographiques des utilisateurs, traitement des multiples préférences des utilisateurs finaux pour générer des données collaboratives
Methods, systems, and storage media for searching for products through a social media platform are disclosed. Exemplary implementations may: receive a selection of an item in a post on the social media platform; generate a digital fingerprint of the item in the post; compare the digital fingerprint with a catalog of digital fingerprints; determine a similarity score between the digital fingerprint and individual digital fingerprints of the catalog of digital fingerprints; determine a subset of digital fingerprints that have similarity scores above a threshold, the subset of digital fingerprints corresponding to a subset of items for sale; and cause display of the subset of items for sale through a user interface of the social media platform.
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
G06F 16/50 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données d’images fixes
85.
DYNAMICALLY IDENTIFYING VISUAL MEDIA CAPTURE FORMATS BASED UPON CONDITIONS
Methods, systems, storage media and computer program products for dynamically identifying visual media capture formats based upon at least one of capture device, resultant visual medium, and/or application-supported conditions are disclosed. Exemplary implementations may: query a visual media capture device for at least a portion of the device-supported visual media capture formats; receive information regarding one or more capture device, resultant visual medium, and/or application-supported conditions relevant to capture of a resultant visual medium; execute an ordered plurality of rules to dynamically identify one or more device-supported visual media capture formats of the device-supported visual media capture formats that is configured to optimize the resultant visual medium; and cause the visual media capture device to initiate capture of the resultant visual medium using one of the identified device-supported visual media capture formats.
A computer-implemented method for identifying candidate videos for audio experiences may include (i) identifying a video with audio content that is a candidate for an audio-primary user experience that enables users to consume the video by listening to the audio content without watching visual content of the video, (ii) determining, at least in part by analyzing the video via a machine learning algorithm, that the audio content of the video is suitable for the audio-primary user experience, and (iii) presenting the audio content of the video to at least one user via an interface designed for the audio-primary user experience in response to determining that the audio content of the video is suitable for the audio-primary user experience. Various other methods, systems, and computer-readable media are also disclosed.
H04N 21/2743 - Hébergement vidéo de données téléchargées à partir du dispositif client
H04N 21/439 - Traitement de flux audio élémentaires
H04N 21/44 - Traitement de flux élémentaires vidéo, p. ex. raccordement d'un clip vidéo récupéré d'un stockage local avec un flux vidéo en entrée ou rendu de scènes selon des graphes de scène du flux vidéo codé
H04N 21/485 - Interface pour utilisateurs finaux pour la configuration du client
G11B 27/02 - Montage, p. ex. variation de l'ordre des signaux d'information enregistrés sur, ou reproduits à partir des supports d'enregistrement ou d'information
H04N 21/266 - Gestion de canal ou de contenu, p. ex. génération et gestion de clés et de messages de titres d'accès dans un système d'accès conditionnel, fusion d'un canal de monodiffusion de VOD dans un canal multidiffusion
87.
SYSTEMS AND METHODS FOR DYNAMIC EARLY TERMINATION OF MODE DECISION IN HARDWARE VIDEO ENCODERS
An example system may include a primary mode decision module, included in a hardware video encoding pipeline, that (1) receives video data for encoding in accordance with a video encoding standard, and (2) identifies, from an initial set of prediction modes supported by the video encoding standard, a primary set of prediction modes for encoding the video data in accordance with the video encoding standard. The example system may also include a secondary mode decision module that (1) determines, for each prediction mode included in the primary set of prediction modes and based on the video data, a cost associated with the prediction mode, and (2) selects, from the primary set of prediction modes and based on the determined costs associated with the prediction modes included in the primary set of prediction modes, a prediction mode for encoding of the video data by the hardware video encoding pipeline.
H04N 19/103 - Sélection du mode de codage ou du mode de prédiction
H04N 19/105 - Sélection de l’unité de référence pour la prédiction dans un mode de codage ou de prédiction choisi, p. ex. choix adaptatif de la position et du nombre de pixels utilisés pour la prédiction
H04N 19/136 - Caractéristiques ou propriétés du signal vidéo entrant
H04N 19/176 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c.-à-d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une zone de l'image, p. ex. un objet la zone étant un bloc, p. ex. un macrobloc
H04N 19/19 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par le procédé d’adaptation, l’outil d’adaptation ou le type d’adaptation utilisés pour le codage adaptatif utilisant l’optimisation basée sur les multiplicateurs de Lagrange
H04N 19/436 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques caractérisés par les détails de mise en œuvre ou le matériel spécialement adapté à la compression ou à la décompression vidéo, p. ex. la mise en œuvre de logiciels spécialisés utilisant des dispositions de calcul parallélisées
88.
ROBOTIC STABILIZATION MECHANISMS AND RELATED METHODS
Stabilization mechanisms may include at least one gripper mounted to a powerline-crawling robot, which may be configured to grasp a powerline supporting the powerline-crawling robot. At least one controller may be configured to control a lateral position of the at least one gripper. At least one inertial measurement unit may be configured to sense at least one of lateral movement and axial rotation of the powerline-crawling robot. The controller may control the lateral position of the gripper based on data from the inertial measurement unit. Various other related systems, devices, mechanisms, and methods are also disclosed.
H02G 1/04 - Méthodes ou appareils spécialement adaptés à l'installation, entretien, réparation, ou démontage des câbles ou lignes électriques pour lignes ou câbles aériens pour les monter ou les tendre
The disclosed device may include a radio frequency (RF) component and a thermal management component establishing a thermal path with the RF component. The device may also include an RF filter electrically that is coupled to the RF component and arranged away from the thermal path. The device may further include a chassis for housing the RF component. The thermal management component and the RF filter may be positioned near an exterior of the chassis. Various other devices, apparatuses, and systems are also disclosed.
A computer-implemented method for anonymizing media files for testing may include (i) identifying a computing process that processes media files, (ii) identifying a media file with at least one characteristic expected to produce output usable for improving the computing process when used as input data to perform a test of the computing process, (iii) anonymizing the media file by replacing content in the media file with predetermined filler content while maintaining the at least one characteristic in a valid state for producing the output usable for improving the computing process, and (iv) initiating the test of the computing process using the anonymized media file as the input data such that the output of the test can be used to improve the computing process. Various other methods, systems, and computer-readable media are also disclosed.
A system (200) may be configured to: obtain, from a first product development entity, a first set of content; obtain, from a second product development entity different from the first product development entity, a second set of content different from the first set of content; generate a user interface (UI) template configured to be first-applied to the first set of content and second-applied to the second set of content; automatically test, via the first-applied template, functionality associated with the first set of content; determine that the functionality satisfies a criterion of the test; and cause presentation of a first preview of the successfully tested content.
The disclosed computer-implemented method may include, for a current frame of a sequence of video frames, determining a frame type label of the current frame. The method may include, in response to determining that the current frame is labeled as an intra frame (I-frame), decoding the current frame and comparing the decoded frame to historical I-frame data. The method may also include, in response to the comparison satisfying a shot-change threshold, flagging the current frame as a shot-change frame, and in response to flagging the current frame as the shot-change frame, storing the current frame for a subsequent shot-change detection. The method may further include updating, based on flagged shot-change frames, shot boundaries for the sequence of video frames. Various other methods, systems, and computer-readable media are also disclosed.
H04N 19/48 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant des techniques de traitement dans le domaine compressé autres que le décodage, p. ex. modification de coefficients de transformées, de données de codage à longueur variable ou de données de codage par longueur de plage
H04N 19/87 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le pré-traitement ou le post-traitement spécialement adaptés pour la compression vidéo mettant en œuvre la détection de coupure ou de changement de scène en combinaison avec la compression vidéo
The disclosed computer-implemented method may include initiating a translucent layer, that includes a user interface element, for displaying over a content layer on a computing device, and receiving, from a content source, video content for the content layer. The method may also include receiving input via the user interface element and sending the input to the content source to direct the content source to modify the video content. The method may further include receiving modified video content from the content source and displaying the modified video content on the content layer. Various other methods, systems, and computer-readable media are also disclosed.
A63F 13/355 - Réalisation d’opérations pour le compte de clients ayant des capacités de traitement restreintes, p. ex. serveurs transformant une scène de jeu qui évolue en flux vidéo codé à transmettre à un téléphone portable ou à un client léger
A63F 13/86 - Regarder des jeux joués par d’autres joueurs
A63F 13/47 - Commande de la progression du jeu vidéo incluant des points de branchement, p. ex. la possibilité à un moment donné de choisir l’un des scénarios possibles
A63F 13/53 - Commande des signaux de sortie en fonction de la progression du jeu incluant des informations visuelles supplémentaires fournies à la scène de jeu, p. ex. en surimpression pour simuler un affichage tête haute [HUD] ou pour afficher une visée laser dans un jeu de tir
G11B 27/10 - IndexationAdressageMinutage ou synchronisationMesure de l'avancement d'une bande
G06F 3/048 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI]
94.
OBJECT-SENSING SYSTEMS AND ROBOTIC SYSTEMS INCLUDING THE SAME
Object-sensing systems including a light transmitter subsystem and a light receiver subsystem. The light transmitter subsystem main be configured to generate a collimated linear beam of light at a predetermined wavelength and having a length of at least 3 inches (7.62 cm). The light receiver subsystem may include a linear sensor array having a length of at least 3 inches (7.62 cm). The linear sensor array may be positioned to receive the collimated linear beam of light and to detect shadows caused by objects blocking at least a portion of the collimated linear beam of light. Various other systems and methods are also disclosed.
G01V 8/20 - Détection, p. ex. en utilisant des barrières de lumière en utilisant plusieurs émetteurs ou récepteurs
F16P 3/14 - Dispositifs de sécurité agissant en conjonction avec la commande ou le fonctionnement d'une machineCommandes exigeant l'emploi simultané de plusieurs parties du corps humain avec dispositifs, p. ex. des éléments sensibles, qui agissent sur la commande ou le fonctionnement de la machine lorsqu'une partie du corps humain se trouve dans ou près de la zone de danger les dispositifs étant des cellules photo-électriques ou d'autres dispositifs sensibles sans contact mécanique
H02G 1/02 - Méthodes ou appareils spécialement adaptés à l'installation, entretien, réparation, ou démontage des câbles ou lignes électriques pour lignes ou câbles aériens
A disclosed system may include a hardware distortion data pipeline that may include (1) a quantization module that generates a quantized data set, (2) an inverse quantization module that generates, from the quantized data set, an inverse quantized data set by executing an inverse quantization of the quantized data set, and (3) an inverse transformation module that generates an inversely transformed data set by executing an inverse transformation of the inverse quantized data set. The system may also include a hardware determination pipeline that determines a distortion metric based on the inversely transformed data set and the residual frame data set, and a hardware token rate pipeline that determines, based on the quantized data set, a token rate for an encoding of the residual frame data set via a video encoding pipeline. Various other methods, systems, and computer-readable media are also disclosed.
H04N 19/423 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques caractérisés par les détails de mise en œuvre ou le matériel spécialement adapté à la compression ou à la décompression vidéo, p. ex. la mise en œuvre de logiciels spécialisés caractérisés par les dispositions des mémoires
H04N 19/436 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques caractérisés par les détails de mise en œuvre ou le matériel spécialement adapté à la compression ou à la décompression vidéo, p. ex. la mise en œuvre de logiciels spécialisés utilisant des dispositions de calcul parallélisées
H04N 19/61 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant un codage par transformée combiné avec un codage prédictif
H04L 47/263 - Modification du taux à la source après avoir reçu des retours
H04L 47/215 - Commande de fluxCommande de la congestion en utilisant le schéma du seau à jetons
H04N 19/164 - Retour d’information en provenance du récepteur ou du canal de transmission
H04N 19/115 - Sélection de la taille du code pour une unité de codage avant le codage
H04N 19/147 - Débit ou quantité de données codées à la sortie du codeur selon des critères de débit-distorsion
96.
SYSTEMS AND METHODS FOR DETERMINING TOKEN RATES WITHIN A RATE–DISTORTION OPTIMIZATION HARDWARE PIPELINE
H04N 19/42 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques caractérisés par les détails de mise en œuvre ou le matériel spécialement adapté à la compression ou à la décompression vidéo, p. ex. la mise en œuvre de logiciels spécialisés
H04N 19/50 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage prédictif
H04N 19/147 - Débit ou quantité de données codées à la sortie du codeur selon des critères de débit-distorsion
97.
CUSTOMIZED DISPLAY COLOR PROFILES FOR INDIVIDUAL COLOR PREFERENCE
Customization of display color profiles is described. A first interface for customizing a global color preference is generated. Feedback from a user is received via the first interface. The feedback describes a customized global color preference. A second interface for customizing a memory color preference is generated. Feedback is received from the user via the second interface. The feedback describes the customized memory color preference. A color preference profile is generated using the customized global color preference and the customized memory color preference. The color preference profile describes the user's preference for how color is presented. The color preference profile is associated with a user profile of the user. Visual content is rendered on a display of the device in accordance with the color preference profile.
G09G 5/02 - Dispositions ou circuits de commande de l'affichage communs à l'affichage utilisant des tubes à rayons cathodiques et à l'affichage utilisant d'autres moyens de visualisation caractérisés par la manière dont la couleur est visualisée
The disclosed system may include a slicing component that has a cutting blade. The cutting blade may be configured to cut a semiconductor wafer into multiple wafer strips, where the wafer strips have flat top surfaces and multiple edges. The system may also include a chuck that has rotatable wafer plate strips that are respectively configured to support the wafer strips. The system may further include a pivot arm that rotates the chuck from a cutting position facing the slicing component to a rotated, polishing position that faces a polishing component. As such, an exposed edge of each wafer strip faces the polishing component. The system may also include a polishing component that is configured to polish at least a portion of the exposed edge of each wafer strip that is facing the polishing component. Various other methods, systems, and computer-readable media are also disclosed.
B24B 9/06 - Machines ou dispositifs pour meuler les bords ou les biseaux des pièces ou pour enlever des bavuresAccessoires à cet effet caractérisés par le fait qu'ils sont spécialement étudiés en fonction des propriétés de la matière propre aux objets à meuler de matière inorganique non métallique, p. ex. de la pierre, des céramiques, de la porcelaine
A computer-implemented method for preserving media streams may include (i) identifying a media stream transmitted by a client device to a server that hosts the media stream for access by additional devices, (ii) detecting that the server is expected to go offline, (iii) sending, in response to detecting that the server is expected to go offline, a message to the client device indicating that the server is expected to go offline, (iv) receiving, at an additional server, a request from the client device to host the media stream, and (v) in response to receiving the request, hosting the media stream at the additional server while ceasing to host the media stream at the server that is expected to go offline. Various other methods, systems, and computer-readable media are also disclosed.
The disclosed computer-implemented method may include combining a first video sequence with a second video sequence to generate a combined video sequence. A video complexity of the first video sequence may differ from that of the second video sequence. The method may also include performing, using a baseline encoder, encoding parameter optimization on the combined video sequence to generate a baseline performance curve and performing, using a target encoder, encoding parameter optimization on the combined video sequence to generate a target performance curve. The method may further include analyzing the target encoder by comparing the target performance curve with the baseline performance curve, and generating a bitrate ladder for the target encoder based on the analysis, wherein the bitrate ladder includes desired bitrate-resolution pairs for encoding. Various other methods, systems, and computer-readable media are also disclosed.
H04N 21/2343 - Traitement de flux vidéo élémentaires, p. ex. raccordement de flux vidéo ou transformation de graphes de scènes du flux vidéo codé impliquant des opérations de reformatage de signaux vidéo pour la distribution ou la mise en conformité avec les requêtes des utilisateurs finaux ou les exigences des dispositifs des utilisateurs finaux
H04N 21/845 - Structuration du contenu, p. ex. décomposition du contenu en segments temporels
H04N 21/234 - Traitement de flux vidéo élémentaires, p. ex. raccordement de flux vidéo ou transformation de graphes de scènes du flux vidéo codé
H04N 19/127 - Établissement des priorités des ressources en matériel ou en calcul
H04N 19/142 - Détection de coupure ou de changement de scène
H04N 19/154 - Qualité visuelle après décodage mesurée ou estimée de façon subjective, p. ex. mesure de la distorsion
H04N 19/179 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c.-à-d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une scène ou une prise de vues
H04N 19/196 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par le procédé d’adaptation, l’outil d’adaptation ou le type d’adaptation utilisés pour le codage adaptatif étant spécialement adaptés au calcul de paramètres de codage, p. ex. en faisant la moyenne de paramètres de codage calculés antérieurement
H04N 19/87 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le pré-traitement ou le post-traitement spécialement adaptés pour la compression vidéo mettant en œuvre la détection de coupure ou de changement de scène en combinaison avec la compression vidéo
brevets
