This disclosure describes systems that generate adaptive function links and cause the adaptive function links to generate modified versions of content items upon detecting an interaction with an adaptive function link. The disclosed systems can receive a request to generate a link for a content item. From the request, the disclosed systems can determine a computer function to embed within a link script of the adaptive function link. Upon an indication of an interaction with the adaptive function link, the disclosed systems can execute the computer function to automatically generate a modified version of the content item. For example, the disclosed systems can, responsive to detecting an interaction with the adaptive function link, generate a redacted version of a content item or a translated version of a content item.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for providing a creativity web browser for content creation that integrates features of a content management system with internet browsing capabilities. Specifically, the disclosed systems provide a creativity web browser that includes specialized interface elements for restructuring web browsing to focus on content-related context, including a digital canvas, a content collection pane, an x-ray pane, and other elements. The disclosed systems can provide access to browsing across multiple systems or platforms, such as internet locations and/or locations within a content management system, within an integrated web browsing environment.
Content items queued for synchronization between a client device and a content management system can be automatically prioritized to improve the sharing process. That is, the content items can be prioritized based on whether a share link has been created to the content item. A share link can enable a user to access the shared content item from a content management system. Content items that have been shared using a share link can be given higher priority to be synchronized prior to content items that have not been shared. The queued content items can be synchronized in the synchronization order resulting from the prioritization. Further, multiple shared content items queued for synchronization can be sub-prioritized based on one or more sub-prioritization criteria.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a context transformer engine, a smart topic agent, and a large language model to generate a smart topic output. In particular, in one or more embodiments, the disclosed systems generate a smart topic output from a transcript of a video call. In some embodiments, the disclosed systems provide a smart topic interface that provides the smart topic output on a client device and receives selections of smart topic elements. In one or more embodiments, the disclosed systems generate a combined smart topic from transcripts of video calls in which client devices that participated are associated with a collaborating user account group.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06Q 10/101 - Création collaborative, p. ex. développement conjoint de produits ou de services
G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel
G10L 15/183 - Classement ou recherche de la parole utilisant une modélisation du langage naturel selon les contextes, p. ex. modèles de langage
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 15/30 - Reconnaissance distribuée, p. ex. dans les systèmes client-serveur, pour les applications en téléphonie mobile ou réseaux
The present technology introduces a simple to use interface that integrates a mechanism to protect content items from use by one or more machine learning algorithms into interfaces of a content management system. In this way, the present technology can make it easy to protect content items where they are stored. The present technology protects against this use by providing options to obfuscate content in a way that can confound artificial intelligence systems during both training and use of the artificial intelligence systems. Additionally, the present technology can control access to content items shared using a link. The content management system can determine not to serve content items when requested by known artificial intelligence systems or services that train them. The present technology can also include automatic content protection rules that can cause the content management system to automatically protect content items when the content item is to be shared.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
6.
CONTEXT-SPECIFIC LARGE LANGUAGE MODEL FUNCTION BUTTONS
This disclosure describes systems that generate a selection of large language model (LLM) function buttons in a floating widget within a web browser of a client device. The disclosed systems can generate or otherwise select the LLM function buttons to include based on context of a webpage within the web browser. Responsive to detecting an indication of an interaction with an LLM function button, the disclosed systems can generate a side panel within the web browser according to the LLM function button. In some embodiments, the disclosed systems can display and utilize a customized LLM function button responsive to detecting a certain webpage or content within the webpage. Further, in some embodiments, the disclosed systems can generate an LLM function button to perform a customized workflow responsive to detecting a certain webpage or content within the webpage.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/04842 - Sélection des objets affichés ou des éléments de texte affichés
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
G06F 16/3329 - Formulation de requêtes en langage naturel
G06F 16/954 - Navigation, p. ex. en utilisant la navigation par catégories
G06N 5/04 - Modèles d’inférence ou de raisonnement
Disclosed are systems, methods, and non-transitory computer-readable storage media for managing content across discrete systems. A content management system can be implemented to manage content items and synchronize content items across devices. A content collaboration system can be implemented to generate documents and facilitate collaboration on documents. To take advantage of the content management system's functionality to manage and synchronize content items while also providing the collaboration functionality of the content collaboration system, the content management system can store and manage references to documents created in the content collaboration system. The document references can be managed by the content management system such that the document references appear to users as if the document references were the referenced document in the collaboration system.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
This disclosure describes systems that generate a single scrollable page within a scroll navigation interface of a client device. The disclosed systems group the content items into stacks and provide the stacks of content items for display within an initial viewing pane of the single scrollable page. Additionally, the disclosed systems generate and provide a set of label elements within the initial viewing pane. Responsive to a selection of a label element of the set of label elements, the disclosed systems add a new viewing pane beneath the initial viewing pane within the single scrollable page and display a subset of the content items related to the label element within the new viewing pane. Further, responsive to receiving an indication of an upward navigational input, the disclosed systems can display the initial viewing pane of the single scrollable page within the scroll navigation interface.
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect utilisant des icônes
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 3/0485 - Défilement ou défilement panoramique
This disclosure describes systems that generate a single scrollable page within a scroll navigation interface of a client device. The disclosed systems group the content items into stacks and provide the stacks of content items for display within an initial viewing pane of the single scrollable page. Additionally, the disclosed systems generate and provide a set of label elements within the initial viewing pane. Responsive to a selection of a label element of the set of label elements, the disclosed systems add a new viewing pane beneath the initial viewing pane within the single scrollable page and display a subset of the content items related to the label element within the new viewing pane. Further, responsive to receiving an indication of an upward navigational input, the disclosed systems can display the initial viewing pane of the single scrollable page within the scroll navigation interface.
The present disclosure relates to systems, methods, and non-transitory computer-readable media for introducing a unique team-centric encryption key that expands a cryptographic security boundary to a team (instead of to users and/or devices). In some embodiments, the disclosed systems can detect a device enrollment request to gain access to team content. associated with a team of enrolled devices. Upon receiving the enrollment request from the device, the disclosed systems can determine a device key associated with that device and a team key associated with the team and can encrypt the team key with the device key (thus generating an encrypted team key). The disclosed systems can also provide the encrypted team key to a requesting device for enrollment and/or can use the encrypted team key to encrypt and/or decrypt team data.
The present disclosure relates to systems, methods, and non-transitory computer-readable media for using rule-based automations that can be executed upon upload of a content item. In some embodiments, upon receiving an upload of a content item, the disclosed systems can determine an automation rule for the content item. In particular, the disclosed systems can process content item data of an uploaded content item and/or extract content item metadata associated with the content item. In some cases, the disclosed systems compare the data and/or the metadata to a set of automation rules associated with a user account. For instance, using the data and/or the metadata, the disclosed systems determine whether an automation rule satisfies a threshold rule score. If so, the disclosed systems select and execute a corresponding automation. If not, the disclosed systems can use secondary measures to select and execute a corresponding automation.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for linking third-party applications to a user account on a content management system. In particular, the disclosed systems can receive browsing data related to browsing activity from a user associated with a user account on a content management system via a software extension on a browser application. The disclosed systems can identify a third-party application external to the content management system based on the browsing data. Upon identifying the third-party application, the disclosed systems can provide for display a selectable connector suggestion on a graphical user interface of a client device. In one or more implementations, based on receiving an indication of a selection of the selectable connector suggestion, the disclosed systems can generate a digital connection that communicatively links the third-party application to the user account on the content management system.
A system, method, and computer readable medium is disclosed for accessing an object that is encrypted within at least a tertiary-level encryption key scheme. This includes receiving a request to access blocks making up an object by content management system and using a top-level encryption key from a key management service, a namespace encryption key from a namespace encryption key database, and a respective block encryption keys protecting the blocks making up the object. Furthermore, the system can rely on ephemeral keys to encrypt the namespace encryption keys, so that namespace encryption keys can be stored at the content management system. Using these keys, the system can decrypt the namespace encryption key using the ephemeral key, decrypt the block encryption keys using the namespace encryption key and decrypt the blocks using the block encryption keys, thereby providing access to the object.
GENERATING A COMPATIBLE FILENAME FOR A CONTENT ITEM AND A FILENAME MAPPING THAT MAPS AN ORIGINAL FILENAME OF THE CONTENT ITEM TO THE COMPATIBLE FILENAME
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating a compatible filename for a content item and generating a filename mapping that maps an original filename for the content item to the compatible filename. In particular, in one or more embodiments, the disclosed systems determine that the original filename for the content item at a first storage location is incompatible with filename conventions at a second storage location and generate a compatible filename for synchronizing the content item to the second storage location. The disclosed systems can also generate a filename mapping that maps the original filename to the compatible filename and, upon receiving an interaction with the content item, the disclosed systems utilize the filename mapping to a propagate modification to the content item at both the first storage location and the second storage location.
The present technology improves the operation and endurance of storage drives by adapting the amount of over-provisioning for a drive to the write profile for the particular service assigned to the drive. The amount of over-provisioning for the drive is determined based on the write profile of the service and the attributes of the drive, such as the drive's specifications and the workload history of the drive. The write profile of the service can be predicted using a model that is empirical or is based on historical data. For example, the write profile can be predicted based on the similarity of the service to services in the historical data. The actual write profile of the service can be monitored, and if it deviates from the predicted write profile the amount of over-provisioning can be dynamically adjusted based on the actual write profile.
Methods and systems provide content searching and retrieval using generative artificial intelligence (AI) Models. The system is configured to receive a user search for content, media or item listings. The system receives a natural language-based input associated with a client device of a user. The system generates a search criterion for the received natural language-based input. The system provides a data set of retrieved content items to one or more large language models that annotate each of the content items in the data set. The system receives a new data set with the content items each including a relevancy annotation. Based on the relevancy annotations in the new data the system determines what additional processing to perform.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating a model application comprising one or more discrete model functions classified into a function category comprising a sense category, a reason category, or an act category. In some embodiments, the disclosed systems can combine a discrete model function with one or more additional model functions to generate a model application that defines data processing for a customized instance of a large language model. The disclosed systems can surface a model interaction interface comprising selectable application elements to instantiate respective applications of a large language model and modify the model interaction interface to surface a recommended source content item within a source selection window to utilize with the large language model.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating a model application comprising one or more discrete model functions classified into a function category comprising a sense category, a reason category, or an act category. In some embodiments, the disclosed systems can combine a discrete model function with one or more additional model functions to generate a model application that defines data processing for a customized instance of a large language model. The disclosed systems can surface a model interaction interface comprising selectable application elements to instantiate respective applications of a large language model and modify the model interaction interface to surface a recommended source content item within a source selection window to utilize with the large language model.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06N 5/04 - Modèles d’inférence ou de raisonnement
Systems or methods are disclosed for dynamically allocating workloads to the most suitable resources within a data center, considering the transient nature of both workload requirements and available resources. The dynamic allocation of workloads may be achieved by testing servers with synthetic workloads and deploying full workloads to the servers or the servers most similar to those that handled the test well. This approach yields more efficient deployment than simply assigning workloads to the first available server.
Systems or methods for mobile data processing racks and modular servers to be dynamically reconfigured to optimize performance and efficiency within a data center. Mobile data processing racks help with reducing latency and network utilization by positioning servers in close physical proximity to each other. Modular server reconfiguration accommodates server requirements by adding or removing components as needed. Some servers on these racks may require additional port interface changes or component upgrades to meet specific server configurations. A reconfiguring automated unit or a gantry can receive instructions to reconfigure the modular server into a specific configuration, causing one of the components to be plugged in to meet the desired specification.
H04L 41/0816 - Réglages de configuration caractérisés par les conditions déclenchant un changement de paramètres la condition étant une adaptation, p. ex. en réponse aux événements dans le réseau
H04L 67/1001 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour accéder à un serveur parmi une pluralité de serveurs répliqués
21.
INTELLIGENTLY GENERATING AND MANAGING THIRD-PARTY SOURCES WITHIN A CONTEXTUAL HUB
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating contextual hubs for organizing and presenting web-accessible content from third-party sources. In particular, the systems described herein can organize and manage within a contextual hub. For instance, the disclosed systems may perform actions on tabs based on analyzing usage signals associated with the tabs. Furthermore, the disclosed systems can organize contextually related content within contextual hubs. The disclosed systems may also facilitate collaboration between users within a contextual hub by synchronizing interactions with content within a contextual hub.
G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
G06F 16/954 - Navigation, p. ex. en utilisant la navigation par catégories
G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p. ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques
G06N 5/04 - Modèles d’inférence ou de raisonnement
H04L 67/125 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance en impliquant la commande des applications des terminaux par un réseau
A system may obtain performance signals associated with at least one of a plurality of servers used in connection with performing a task. A system may provide the performance signals to a machine learning model. A system may receive as output from the machine learning model a health metric related to the at least one of the plurality of servers. A system may determine whether the health metric meets a migration condition. A system may, responsive to the health metric meeting the migration condition, initiate a reallocation of resources for performing the task, wherein the reallocation of resources includes migration of responsibility for performing the task to at least one other server of the plurality of servers.
H04L 67/1008 - Sélection du serveur pour la répartition de charge basée sur les paramètres des serveurs, p. ex. la mémoire disponible ou la charge de travail
H04L 43/0817 - Surveillance ou test en fonction de métriques spécifiques, p. ex. la qualité du service [QoS], la consommation d’énergie ou les paramètres environnementaux en vérifiant la disponibilité en vérifiant le fonctionnement
23.
GENERATING CONTENT COLLECTIONS FROM DIGITAL CONTENT CLUSTERS
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating content clusters from topic data and focus data, generating content collections from content clusters, storing and restoring desktop scene layouts, and storing and arranging video call scenes. In some embodiments, the disclosed systems generate content clusters based on topic data and focus data associated with content items within a content management system and/or accessed via the internet. The disclosed systems can also generate content collections for a user account of the content management system from the content clusters. In some embodiments, the content scene system can further store and restore desktop scene layouts for arranging application windows presenting content items. Further, the disclosed systems can store and arrange particular desktop scene layouts for video call scenes.
Systems and methods for integrating a messaging client application with a content management system are provided. In some examples, a method can include receiving messaging content at a content management system from a messaging client application via an application programming interface, the content management system and the messaging client application being on different cloud-based systems. The method can include associating the messaging content with a workspace in the content management system, the workspace including a plurality of users that are authorized to access the workspace to collaborate with each of the plurality of users. The method can further include providing access to the messaging content to the plurality of users that are authorized to access the workspace of the content management system. The method also can include embedding the messaging content in the workspace of the content management system.
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 65/403 - Dispositions pour la communication multipartite, p. ex. pour les conférences
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
25.
DATA INGESTION UTILIZING A COORDINATOR AND CONNECTORS
The present disclosure relates to systems, non-transitory computer-readable media, and methods for ingesting a dataset from a computer application that is external to a content management system. In particular, the disclosed systems can perform an ingestion process comprising a plurality of transfer runs by linking a content management system to the computer application with a connector. The disclosed systems can utilize a coordinator with computer logic to control the connector to determine a cursor location within a page of data at a failure point during a first transfer run. Moreover, the disclosed systems can store a subset of data from the page that comes after the cursor location and ingest the subset of data from the object queue by continuing the ingestion process according to the cursor location at the failure point of the first transfer run.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
26.
Utilizing a multimodal large language model to generate synthesized responses corresponding to multimodal content items
The present disclosure relates to systems, non-transitory computer-readable media, and methods for processing multimodal content to generate summaries or responses using a multimodal large language model. In one or more embodiments, the disclosed systems the disclosed systems utilize the multimodal large language model to generate various types of synthesized responses corresponding to multimodal content items that contain data and information within images. For example, in some embodiments, in response to receiving a request to generate a synthesized response corresponding to a multimodal content item, the disclosed systems employ preprocessing pipelines that generate thumbnail images from the multimodal content item and use the thumbnail images to generate a data structure for a prompt for the multimodal large language model.
The present technology is directed to a notification manager which provides a consolidated notification assistant interface for managing notifications received across a plurality of sources, such as applications and channels. The notification manager can group similar notifications in the consolidated notification assistant interface. The notification manager can automatically respond to some notifications, and provide a status regarding whether a responsive notification has been sent, or whether a responsive notification has been prepared that needs review, etc. For example, the notification manager can propose responsive notifications to some notifications, and provide a call to action for the user account to review the proposed responsive notification and to send the proposed responsive notification. The user associated with the user account can interact with the notification manager by giving natural language instructions by interacting with a chatbot to instruct the notification manager to take actions.
H04L 51/224 - Surveillance ou traitement des messages en fournissant une notification sur les messages entrants, p. ex. des poussées de notifications des messages reçus
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 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a context transformer engine, a smart topic agent, and a large language model to generate a smart topic output. In particular, in one or more embodiments, the disclosed systems generate a smart topic output from a transcript of a video call. In some embodiments, the disclosed systems provide a smart topic interface that provides the smart topic output on a client device and receives selections of smart topic elements. In one or more embodiments, the disclosed systems generate a combined smart topic from transcripts of video calls in which client devices that participated are associated with a collaborating user account group.
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G10L 15/183 - Classement ou recherche de la parole utilisant une modélisation du langage naturel selon les contextes, p. ex. modèles de langage
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 15/30 - Reconnaissance distribuée, p. ex. dans les systèmes client-serveur, pour les applications en téléphonie mobile ou réseaux
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and suggesting content collections for user accounts of a content management system using combinations of content-based features such as textual signals and visual signals. In some embodiments, the disclosed systems select a seed content item from among a plurality of content items associated with a user account within a content management system. From the seed content item, the disclosed systems can determine one or more germane topics and can cluster additional content items in relation to the germane topic(s). In addition, the disclosed systems can select one or more content items from a content cluster to provide as a suggested content collection.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and searching a hybrid search index. In some embodiments, the disclosed systems generate a hybrid search index that comprises one or more content items stored at a content management system or at external network locations linked to the content management system via software connectors along with world state data associated with the one or more content items. The disclosed systems can generate a search result from the hybrid search index in response to receiving a search query of the hybrid search index. In some cases, the disclosed systems can rank one or more content items included in the search result based on observation layer data of the one or more content items.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating block content elements from meeting data of multiple video calls to add to data blocks of a virtual space. In particular, in one or more embodiments, the discloses systems utilize a large language model to process meeting data across multiple video calls and generate the block content elements for data blocks. For example, in some embodiments, the disclosed systems generate new block content elements based on detecting meeting data from additional video calls. Further, in one or more embodiments, the disclosed systems generate block content elements according to block type of a data block and extract meeting data to generate summaries, action items, document elements, or dates. Moreover, in some embodiments, the disclosed systems provide options and prompts to generate or update a virtual space using meeting date from video calls.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
The present technology addresses a need in the art for providing additional context to a recipient receiving a shared object(s). Sharing messages are generally limited to a brief statement indicating that a user account has shared the object(s). The present technology can automatically create a summary for an object(s) to be shared. Moreover, the present technology provides a user interface that is part of a sharing process for the creation of the summary so that the creation of the summary is very convenient for the user, and can even be completely automatic. Additionally, the present technology includes carefully engineered prompts that result in summaries that are appropriate for the sharing context in which they are intended.
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
33.
CLASSIFYING AND ORGANIZING DIGITAL CONTENT ITEMS AUTOMATICALLY UTILIZING CONTENT ITEM CLASSIFICATION MODELS
The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize machine-learning models to classify content items and automatically organize the content items within a file structure according to their content item classifications. For instance, a content item classification system generates one or more content item classification models to determine classifications for content items and/or folders. In some instances, the classification system detects when new content items are added to a smart folder, determines destination folders to which the content items belong based on classifying the content items, and automatically moves the content items accordingly. In various instances, the classification system generates and utilizes a classification model to organize content items into dynamically-generated folders. In example implementations, the classification system generates and utilizes a classification model to automatically organize existing content items into existing folders.
The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize machine-learning models to classify content items and automatically organize the content items within a file structure according to their content item classifications. For instance, a content item classification system generates one or more content item classification models to determine classifications for content items and/or folders. In some instances, the classification system detects when new content items are added to a smart folder, determines destination folders to which the content items belong based on classifying the content items, and automatically moves the content items accordingly. In various instances, the classification system generates and utilizes a classification model to organize content items into dynamically-generated folders. In example implementations, the classification system generates and utilizes a classification model to automatically organize existing content items into existing folders.
This disclosure describes systems that generate a selection of large language model (LLM) function buttons in a floating widget within a web browser of a client device. The disclosed systems can generate or otherwise select the LLM function buttons to include based on context of a webpage within the web browser. Responsive to detecting an indication of an interaction with an LLM function button, the disclosed systems can generate a side panel within the web browser according to the LLM function button. In some embodiments, the disclosed systems can display and utilize a customized LLM function button responsive to detecting a certain webpage or content within the webpage. Further, in some embodiments, the disclosed systems can generate an LLM function button to perform a customized workflow responsive to detecting a certain webpage or content within the webpage.
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect utilisant des icônes
G06F 3/04842 - Sélection des objets affichés ou des éléments de texte affichés
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
The present disclosure relates to systems, non-transitory computer-readable media, and methods for selecting machine-learning models and hardware environments for executing a task. In particular, in one or more embodiments, the disclosed systems select a designated machine-learning model for executing a task based on workload features of the task and task routing metrics for a plurality of machine-learning models. In addition, in one or more embodiments, the disclosed systems select a designated hardware environment for executing the task based on workload features for the task and task routing metrics for a plurality of hardware environments. In some embodiments, the disclosed systems select a fallback machine-learning model and a fallback hardware environment for executing the task if the designated machine-learning model or designated hardware environment are unavailable. Moreover, in one or more embodiments, the disclosed systems can pause and initiate tasks based on bandwidth availability.
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/20 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel en utilisant un masquage actif du défaut, p. ex. en déconnectant les éléments défaillants ou en insérant des éléments de rechange
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
Methods and systems provide for rich media presentation of recommendations in generative media. In one embodiment, the system presents, via a trained generative AI, a set of media content to a user in a communication session within a platform, the media content including a number of sorted recommended items; monitors and quantifies one or more user responses from the user to the presented media content and one or more associated generative responses from the trained generative AI; based on the monitoring and quantifying, detects one or more mentions of the user to one of the plurality of sorted recommended items; generates, from the one or more detected mentions, one or more labeled training examples; and further trains the trained generative AI based on the one or more labeled training examples to improve the presentation of the media content in future communication sessions.
This disclosure describes systems that identify one or more models (e.g., large language models and/or virtual assistants) permitted to access content items stored for user accounts within a content management system. The disclosed systems can determine a model available to a user account within the content management system from among the one or more models. For example, the disclosed systems can determine one or more relationships between the user accounts within the content management system, large language models utilized by the user accounts, virtual assistants utilized by the user accounts, and content items accessed by the user accounts. The disclosed systems can determine the model for the user account according to the one or more relationships. The disclosed systems can provide a notification corresponding to the model via a user interface of a client device associated with the user account.
G06N 3/006 - Vie artificielle, c.-à-d. agencements informatiques simulant la vie fondés sur des formes de vie individuelles ou collectives simulées et virtuelles, p. ex. simulations sociales ou optimisation par essaims particulaires [PSO]
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
This disclosure describes systems that identify one or more models (e.g., large language models and/or virtual assistants) permitted to access content items stored for user accounts within a content management system. The disclosed systems can determine a model available to a user account within the content management system from among the one or more models. For example, the disclosed systems can determine one or more relationships between the user accounts within the content management system, large language models utilized by the user accounts, virtual assistants utilized by the user accounts, and content items accessed by the user accounts. The disclosed systems can determine the model for the user account according to the one or more relationships. The disclosed systems can provide a notification corresponding to the model via a user interface of a client device associated with the user account.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for capturing snapshots of digital content displayed on a client device and searching through the captured content. The disclosed systems provide a search function for effectively traveling back in time to identify digital content previously displayed on a client device. The disclosed systems provide options for capturing snapshots of content displayed on a display screen, extracting data from the snapshots, and storing the snapshots for use when populating search results. The disclosed systems utilize machine learning models to extract text and/or to generate text versions of snapshots including extracted text, descriptions of images, transcripts of videos, and/or textual summaries from displayed documents or webpages. In response to a search query, the disclosed systems can produce search results that include digital videos including captured snapshots of content displayed by a client device over time.
G06F 16/738 - Présentation des résultats des requêtes
G06F 16/783 - Recherche de données caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
41.
Display screen or portion thereof with a graphical user interface
The present technology enhances workload management of data storage systems by using an internal copy function and/or a zone-append technology. The internal copy function is used, e.g., in merge operations to move data between locations on a disk without using off-disk resources (e.g., processing or memory of a CPU). Zone-append technology uses nameless writes (e.g., write instruction without an assigned destination address on the disk) to combine IO units from different threads to be written to a common zone of a disk (e.g., a shingled magnetic recording (SMR) disk). Sequential addresses are assigned to IO units from different threads based on their order in the write queue, reducing the latency and seek time typically associated with random writes. The zone-append technology, e.g., uses sequential write operations within specified zones, allowing the disk to determine the actual write location and to report post-write logical block addresses (LBAs).
Systems and methods for providing a folder activity user interface, such as a folder activity dashboard, that can provide viewing members with an overview of the sync progress of their own activities, like uploading content items, as well as the activities of other activity-initiating members, such as uploads to shared folders that the viewing members have access to. The folder activity user interface includes status indicators that correspond to the progress related to folder activity information and the respective content items of the shared folder, such as indicating progress towards when a respective content item will be accessible to the viewing member.
One or more embodiments of a content system provide machine-learned storage location recommendations for storing content items. Specifically, an online content management system can train a machine-learning model to identify a storage pattern from previously stored content items in a plurality of storage locations corresponding to a user account of a user. Training the machine-learning model includes training a plurality of classifiers for the plurality of storage locations. The online content management system uses the classifiers to determine whether a content item is similar to the content items in any of the storage locations, and based on the output of the classifiers, provides graphical elements indicating recommended storage locations within a graphical user interface. The user can select a graphical element to move the content item to the corresponding storage location.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and searching a hybrid search index. In some embodiments, the disclosed systems generate a hybrid search index that comprises one or more content items stored at a content management system or at external network locations linked to the content management system via software connectors along with world state data associated with the one or more content items. The disclosed systems can generate a search result from the hybrid search index in response to receiving a search query of the hybrid search index. In some cases, the disclosed systems can rank one or more content items included in the search result based on observation layer data of the one or more content items.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and searching a hybrid search index. In some embodiments, the disclosed systems generate a hybrid search index that comprises one or more content items stored at a content management system or at external network locations linked to the content management system via software connectors along with world state data associated with the one or more content items. The disclosed systems can generate a search result from the hybrid search index in response to receiving a search query of the hybrid search index. In some cases, the disclosed systems can rank one or more content items included in the search result based on observation layer data of the one or more content items.
The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for providing a streamed presentation of a video proxy referencing a cloud-based location of a digital video. For example, the disclosed systems receive a request to edit a digital video stored in a cloud-based location of a content management system. In addition, the disclosed systems generate a video proxy that include a reference to the cloud-based location of the digital video and modifies the video proxy in response to an editing operation. Further, the disclosed systems provide for display a streamed presentation of the video proxy depicting modifications defined by the editing operation.
G11B 27/031 - Montage électronique de signaux d'information analogiques numérisés, p. ex. de signaux audio, vidéo
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p. ex. interaction avec des règles ou des cadrans
48.
IDENTIFYING RELEVANT INFORMATION WITHIN A DOCUMENT HOSTING SYSTEM
This disclosure generally covers systems and methods that identify relevant information for a user based on an object graph for documents and other files hosted by a document hosting system. In particular, certain embodiments of the disclosed systems and methods generate an object graph comprising interconnected nodes representing relationships among documents and other files on the document hosting system. Using the object graph, the disclosed systems and methods can identify relevant information and provide results or recommendations corresponding to that information based on a query or on user input, respectively.
Methods and systems provide content searching and retrieval using generative artificial intelligence (AI) Models. The system is configured to receive a user search for content, media or item listings. The user search is provided to a generative AI based search sub-system and to a traditional search sub-system. A first search result listing is generated by the generative AI based subsystem, and a second search result listing is generated by the traditional search sub-system. The first search result listing and the second search result listing are aggregated together and provided for display to a user client device.
The present disclosure relates to systems, methods, and non-transitory computer-readable media that dynamically capture, organize, and utilize digital media clips. For example, in one or more implementations, the disclosed systems can capture and generate digital media clips of content items that include both content metadata of the content items as well as contextual metadata of contextual signals surrounding the content item. Additionally, in some implementations, the disclosed systems analyze contextual metadata to search, retrieve, discover, and organize new and existing digital media clips. Further, in various implementations, the disclosed systems facilitate generating digital media clip libraries as well as the creation of digital media collections, where different types of digital media clips can be combined in a cohesive interactive graphical user interface.
G06F 16/48 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
The present technology pertains to a predictive thermal model that can be used to intelligently manage thermal events in a data center. The predictive thermal model can be used to predict future temperatures of servers to take action before the server experiences higher than desired temperatures. The present technology also includes several innovative amelioration techniques that can help to keep servers cool when it is predicted that heat in their environment is about to increase. One such amelioration technique is a heat-responsive operation change for storage servers, or at least individual hosts within a storage server. For example, a host can be switched into a mode where it can batch read and write operations to limit the amount of seeking the host needs to perform, which produces less heat.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for modifying a fillable digital document. In particular, the disclosed systems can receive a user interaction requesting to populate one or more aggregated data fields in a fillable digital document. In response to the request, the field object generation system can determine the data relevant to one or more aggregated data fields in the fillable digital document by utilizing a large language model to process one or more source content items for a user account. Further the systems and generate a field object from the data relevant to one or more aggregated data field and modify the fillable digital document by including the field object in the fillable digital document.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and implementing workflow states across multiple devices. In some embodiments, the disclosed systems generate, utilizing a meta layer integrated with a suite of computer applications, a workflow state defining an active computer application and interaction data within the active computer application on a first client device. Further, in some embodiments, the disclosed systems detect a handoff trigger comprising computer instructions for transferring the workflow state from the first client device to a second client device. In response to detecting the handoff trigger, in some embodiments, the disclosed systems access, via the meta layer, the workflow state to cause the second client device to instantiate the active computer application and the interaction data.
A preferred method for dynamically displaying virtual and augmented reality scenes can include determining input parameters, calculating virtual photometric parameters, and rendering a VAR scene with a set of simulated photometric parameters.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating content clusters from topic data and focus data, generating content collections from content clusters, storing and restoring desktop scene layouts, and storing and arranging video call scenes. In some embodiments, the disclosed systems generate content clusters based on topic data and focus data associated with content items within a content management system and/or accessed via the internet. The disclosed systems can also generate content collections for a user account of the content management system from the content clusters. In some embodiments, the content scene system can further store and restore desktop scene layouts for arranging application windows presenting content items. Further, the disclosed systems can store and arrange particular desktop scene layouts for video call scenes.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
56.
Autonomous process execution for large language model function buttons
This disclosure describes systems that generate a selection of large language model (LLM) function buttons in a floating widget within a web browser of a client device. The disclosed systems can generate or otherwise select the LLM function buttons to include based on context of a webpage within the web browser. Responsive to detecting an indication of an interaction with an LLM function button, the disclosed systems can generate a side panel within the web browser according to the LLM function button. In some embodiments, the disclosed systems can display and utilize a customized LLM function button responsive to detecting a certain webpage or content within the webpage. Further, in some embodiments, the disclosed systems can generate an LLM function button to perform a customized workflow responsive to detecting a certain webpage or content within the webpage.
The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating a dynamic facet by using a large language model. For example, the disclosed systems extract raw facet data from a plurality of content items stored in a content management system. In addition, the disclosed systems determine one or more facet content groups by grouping the plurality of content items according to the raw facet data. Further, the disclosed systems generate a facet prompt from the one or more facet content groups. Moreover, the disclosed systems generate a dynamic facet by providing the facet prompt to a large language model.
The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating function code and test code to determine that the function code satisfies an intent query. For example, the disclosed systems utilize a large language model to process an intent query and generate function code that defines one or more processes whose execution satisfies the intent query. In addition, the disclosed systems also utilize the large language model to generate test code that defines a function test for determining that the function code satisfies the intent query. Moreover, the disclosed systems can execute the test code to determine that the function code satisfies the intent query.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating a hybrid prompt for a retrieval augmented generation (RAG) model. In particular, the disclosed systems can generate utilizing a large language model at indexing time for a content item, a topic summary for a topic within the content item. Moreover, the disclosed systems can add the topic summary to a summary knowledge corpus that includes topic summary for a plurality of topics extracted from content items. In one or more cases, at runtime for the RAG model, the disclosed systems can receive prompt language and in response, determine one or more topic summaries that correspond to the prompt language. The disclosed systems can further generate a hybrid prompt by combining the one or more topic summaries with retrieved data accessed by the RAG model in response to the prompt language.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating, storing, and accessing persisted data elements in a large language model framework. For instance, the disclosed systems can generate a code segment that includes a set of parameters and a function with a large language model associated with a context engine. In some cases, the disclosed systems can determine the serialized state of the interpreter based on executing the code segment. In one or more implementations, the disclosed systems can generate a persisted data element from the serialized state of the interpreter and store the persisted data element in an interpreter data store. The disclosed systems can further access the persisted data element from the data store to generate responses or perform tasks in the same or subsequent sessions.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 40/40 - Traitement ou traduction du langage naturel
The present disclosure relates to systems, non-transitory computer-readable media, and methods for maintaining context during multi-turn interactions. In one or more embodiments, the disclosed systems can detect an interruption event during the execution of computer code by an interpreter that pauses the execution of computer code by the interpreter. The disclosed systems can store, based on the interruption event, a serialized state of the interpreter that indicates a pause location in the computer code by encoding the code execution data. In some cases, the disclosed systems can resume execution of the computer code from the serialized state of the interpreter.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
The present disclosure relates to systems, non-transitory computer-readable media, and methods for combining sessions of a large language model. For instance, the disclosed systems can receive a first query from a first collaborating user account and a second query from a second collaborating user account. In one or more cases, the disclosed systems can generate a merged prompt based on the from the first query and second query. In some implementations, the disclosed systems can generate a response to the first query and/or the second query by processing the merged prompt utilizing the large language model.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for linking third-party applications to a user account on a content management system. In particular, the disclosed systems can receive browsing data related to browsing activity from a user associated with a user account on a content management system via a software extension on a browser application. The disclosed systems can identify a third-party application external to the content management system based on the browsing data. Upon identifying the third-party application, the disclosed systems can provide for display a selectable connector suggestion on a graphical user interface of a client device. In one or more implementations, based on receiving an indication of a selection of the selectable connector suggestion, the disclosed systems can generate a digital connection that communicatively links the third-party application to the user account on the content management system.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for ingesting a dataset from a computer application that is external to a content management system. In particular, the disclosed systems can perform an ingestion process comprising a plurality of transfer runs by linking a content management system to the computer application with a connector. The disclosed systems can utilize a coordinator with computer logic to control the connector to determine a cursor location within a page of data at a failure point during a first transfer run. Moreover, the disclosed systems can store a subset of data from the page that comes after the cursor location and ingest the subset of data from the object queue by continuing the ingestion process according to the cursor location at the failure point of the first transfer run.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
The present technology improves the ability of a technician to navigate within a data center by making use of lights on servers, switches, and other infrastructure devices to provide navigation queues to a technician. In particular, the present technology can instruct infrastructure devices along a path to a particular infrastructure device that a technician might need to service to operate lights, (e.g., light emitting diodes (LEDs)) in a way that signals a path to the particular infrastructure device. When a number of infrastructure devices are so instructed, an easy-to-follow and understand pattern can be created. The particular infrastructure device can be instructed to operate its lights in a way that differentiates itself from other surrounding devices that might help the technician recognize the device.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating information flow patterns utilizing a large language model and content item embeddings, and utilizing information flow patterns to determine notifications and modifications. To illustrate, the disclosed methods can extract content item embeddings from content items and provide content item embeddings to a large language model in order to generate information flow patterns that include communication between teams. Accordingly, the disclosed methods can utilize document embeddings from new modifications to generate information flow patterns for a corresponding project. Thus, the disclosed methods can utilize the information flow pattern to determine corresponding notifications or modifications to projects or content indicated by the information flow pattern.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
67.
Contextualizing data to provide computing activity synthesis
This disclosure describes systems that aggregate activity data items for one or more data sources for a user account. The disclosed systems can utilize a large language model to transform the activity data items to synthesized activity items. For example, the disclosed systems can utilize the large language model to transform the activity data items to the synthesized activity items by extracting the contextual content from the activity data items. The disclosed systems can utilize the large language model to process the synthesized activity items to generate an activity meta summary for a specified timeframe. Based on the activity meta summary, the disclosed systems can further identify a subset of synthesized activity items for the specified timeframe. Thereafter, the disclosed systems can provide the subset of synthesized activity items for the specified timeframe for display on a client device associated with the user account.
The present technology provides a versatile content management system that can also support bi-directional synchronization of an organization account. The organization account is maintained as a plurality of root directories that can be mounted under an organization directory top-level folder. The organization directory top-level folder can appear in a user account's view of the organization account, by does not actually exist as a directory in the content management system. The organization directory top-level folder can be a folder created on a client device in which root directories of an organization account are mounted, but the organization directory top-level folder is not a synchronized directory. The organization directory top-level folder gives the appearance of a single directory structure for an organization even though the organization content is actually organized into the plurality of root directories.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and searching a hybrid search index. In some embodiments, the disclosed systems generate a hybrid search index that comprises one or more content items stored at a content management system or at external network locations linked to the content management system via software connectors along with world state data associated with the one or more content items. The disclosed systems can generate a search result from the hybrid search index in response to receiving a search query of the hybrid search index. In some cases, the disclosed systems can rank one or more content items included in the search result based on observation layer data of the one or more content items.
Methods and systems provide content searching and retrieval using generative artificial intelligence (AI) Models. The system is configured to receive a user search for content, media or item listings. The system receives a natural language-based input associated with a client device of a user. The system generates a search criterion for the received natural language-based input. The system provides a data set of retrieved content items to one or more large language models that annotate each of the content items in the data set. The system receives a new data set with the content items each including a relevancy annotation. Based on the relevancy annotations in the new data the system determines what additional processing to perform.
Methods and systems provide content searching and retrieval using generative artificial intelligence (AI) Models. The system is configured to receive a user search for content, media or item listings. The system receives a natural language-based input associated with a client device of a user. The system generates a search criterion for the received natural language-based input. The system, via the generative AI-bases search and retrieval system, generates a relevancy-ranked output listing of content items. The relevancy-ranked output listing content items responsive to the generated search criterion content items having an associated content identifier and a content description. The system generates a carousel display structure definition of the relevancy-ranked content items. The system transmits the carousel display structure definition of the relevancy-ranked content items and the content items to the client device. The client device displays, via a user interface of the client device, relevancy-ranked content items according to the carousel display structure definition.
Methods and systems provide content searching and retrieval using generative artificial intelligence (AI) Models. The system is configured to receive a user search for content, media or item listings. The system receives a natural language-based input associated with a client device of a user. The system generates a search criterion for the received natural language-based input. The system, via the generative AI-bases search and retrieval system, generates a relevancy-ranked output listing of content items. The relevancy-ranked output listing content items responsive to the generated search criterion content items having an associated content identifier and a content description. The system causes portions of the relevancy-ranked output listing to be rendered at the client device of the user.
The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating unified data items from source-specific data items originating from third-party sources. For example, the disclosed systems receive a plurality of source-specific data items from a first third-party source and a second third-party source. For instance, the source-specific data items include data that represents digital activity of multiple client devices using the third-party sources. Further, the disclosed systems generate a plurality of unified data items from the source-specific data items by using a translation layer that maps source-specific data structures to a unified data structure. Moreover, the disclosed systems identify a subset of unified data items based on a request from an administrator device and further provides the subset of unified data items to the administrator device.
The present technology pertains to storing blocks in a storage system that requires fewer I/O operations for processes that are non-latency-sensitive. The present technology collects blocks in a buffer and then performs erasure coding while writing the blocks into storage. The erasure coding can occur without the blocks first being replicated. And the present technology can acknowledge the request to store the blocks to a client providing the blocks even before the blocks are written into the storage.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
75.
GENERATING COACHING PROMPTS FROM KNOWLEDGE GRAPH DATA SOURCES
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing coaching insights using a large language model to process coaching prompts. In some embodiments, the disclosed systems generate a coaching prompt from a knowledge graph encoding data from data sources, such as an observation layer and a world state. The disclosed systems also determine a pulse status of a user account to inform a coaching prompt. Additionally, the disclosed systems provide the coaching prompt to a large language model for generating a coaching insight to improve the pulse status.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing coaching insights using a large language model to process coaching prompts. In some embodiments, the disclosed systems generate a coaching prompt from a knowledge graph encoding data from data sources, such as an observation layer and a world state. The disclosed systems also determine a pulse status of a user account to inform a coaching prompt. Additionally, the disclosed systems provide the coaching prompt to a large language model for generating a coaching insight to improve the pulse status.
This disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that utilize a large language model with user activity data to generate objective timelines for a user account. In particular, the disclosed systems can identify user activity data from a variety of electronic applications utilized by the user account to generate a user account data stream. Furthermore, the disclosed systems can utilize the user account data stream and an identified time objective to generate navigable objective timelines for the user account utilizing a large language model. For instance, the disclosed systems can utilize a large language model with one or more prompts (e.g., time expenditure prompts) generated utilizing the user activity data stream and the time objective. Indeed, the disclosed systems can utilize the large language model with the prompts to generate a navigable objective timeline based on the user activities.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for selecting machine-learning models and hardware environments for executing a task. In particular, in one or more embodiments, the disclosed systems select a designated machine-learning model for executing a task based on workload features of the task and task routing metrics for a plurality of machine-learning models. In addition, in one or more embodiments, the disclosed systems select a designated hardware environment for executing the task based on workload features for the task and task routing metrics for a plurality of hardware environments. In some embodiments, the disclosed systems select a fallback machine-learning model and a fallback hardware environment for executing the task if the designated machine-learning model or designated hardware environment are unavailable. Moreover, in one or more embodiments, the disclosed systems can pause and initiate tasks based on bandwidth availability.
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/20 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel en utilisant un masquage actif du défaut, p. ex. en déconnectant les éléments défaillants ou en insérant des éléments de rechange
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
This disclosure describes systems that generate a selection of large language model (LLM) function buttons in a floating widget within a web browser of a client device. The disclosed systems can generate or otherwise select the LLM function buttons to include based on context of a webpage within the web browser. Responsive to detecting an indication of an interaction with an LLM function button, the disclosed systems can generate a side panel within the web browser according to the LLM function button. In some embodiments, the disclosed systems can display and utilize a customized LLM function button responsive to detecting a certain webpage or content within the webpage. Further, in some embodiments, the disclosed systems can generate an LLM function button to perform a customized workflow responsive to detecting a certain webpage or content within the webpage.
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect utilisant des icônes
G06F 40/166 - Édition, p. ex. insertion ou suppression
80.
UTILIZING MACHINE-LEARNING MODELS TO GENERATE IDENTIFIER EMBEDDINGS AND DETERMINE DIGITAL CONNECTIONS BETWEEN DIGITAL CONTENT ITEMS
The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize machine learning models to generate identifier embeddings from digital content identifiers and then leverage these identifier embeddings to determine digital connections between digital content items. In particular, the disclosed systems can utilize an embedding machine-learning model that comprises a character-level embedding machine-learning model and a word-level embedding machine-learning model. For example, the disclosed systems can combine a character embedding from the character-level embedding machine-learning model and a token embedding from the word-level embedding machine-learning model. The disclosed systems can determine digital connections between the plurality of digital content items by processing these identifier embeddings for a plurality of digital content items utilizing a content management model. Based on the digital connections, the disclosed systems can surface one or more digital content suggestions to a user interface of a client device.
Systems and methods are disclosed herein for enabling consistent caching. The disclosed approach enables consistent caching by maintaining a timestamp that tracks an upper bound for the most recent observed write attempt to any key, regardless of whether the write attempt was successful or unsuccessful. When a server attempts to read a value of a key, it compares the upper bound timestamp of the key to a read timestamp of the key. The read timestamp is stored in the cache and represents a time at which the key was most recently read. If the upper bound timestamp is after the read timestamp, the cache is stale, so the server retrieves the value of the key from data storage rather than the cache. If the upper bound timestamp is before the read timestamp, the server retrieves the value of the key from the cache.
The present disclosure is directed toward systems and methods that efficiently and effectively generate and utilize collections of content items. For example, systems and methods described herein generate a collection content item including one or more content item references. In one or more embodiments, the collection content item can include content item references for content items located internally or externally, with granular levels of permissions settings and version controls. Additionally, in response to a detected selection of a content item reference, systems and methods described herein generate a rendering of the associated content item that can be viewed regardless of any third party software installed on the viewing client computing device.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating a content stack utilizing one or more machine-learning models. In some implementations, the disclosed systems generate and provide, to a user account, a content stack that includes content items corresponding to a topic prompt for the user account. For instance, in some implementations, the disclosed systems utilize content-based signals and account-based signals to generate an account-specific stack formulation graph that represents a plurality of content items and relationships of the content items with each other and with the user account. Additionally, in some implementations, the disclosed systems analyze the account-specific stack formulation graph to generate a content stack from the plurality of content items, the content stack comprising a set of content items corresponding to the topic prompt.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a large language model to generate computer code executable to generate a series of calendar events for completing a target objective. Furthermore, the disclosed systems provide a catalyst calendar interface which includes a chat window and an integrated calendar window to interface to display the series of calendar events. For instance, the disclosed systems utilize the large language model to generate a task curriculum which includes a set of executable tasks whose completion accomplishes the target objective. Furthermore, the disclosed systems can generate computer code executable by a calendar application to generate the series of calendar events corresponding to the set of executable tasks. The disclosed systems can interact with the chat window to provide the series of calendar events incorporating an integrated view of the calendar application, via the integrated calendar window, using rich calendar content.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a large language model to generate computer code executable to generate a series of calendar events for completing a target objective. Furthermore, the disclosed systems provide a catalyst calendar interface which includes a chat window and an integrated calendar window to interface to display the series of calendar events. For instance, the disclosed systems utilize the large language model to generate a task curriculum which includes a set of executable tasks whose completion accomplishes the target objective. Furthermore, the disclosed systems can generate computer code executable by a calendar application to generate the series of calendar events corresponding to the set of executable tasks. The disclosed systems can interact with the chat window to provide the series of calendar events incorporating an integrated view of the calendar application, via the integrated calendar window, using rich calendar content.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating personal responses through retrieval-augmented generation. In particular, the disclosed systems can generate a query embedding from a query generated by an entity and determine data context specific to the entity by comparing the query embedding with a plurality of vectorized segments of content items associated with the entity. The disclosed systems can provide the data context to a large language model and generate a personalized response informed by the data context. Subsequently, the disclosed systems can provide the personalized response for display on a client device associated with the entity.
G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
G06F 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
87.
SYSTEMS AND METHODS FOR MANAGING CONTENT ITEMS HAVING MULTIPLE RESOLUTIONS
Systems, methods, and non-transitory computer readable media for managing content items having multiple resolutions may be provided. In some embodiments, a user device may send a request to access one or more images from a content management system. The one or more images may be categorized on the user device by an expected use that determines that the one or more images be in a first version. A second version of the one or more images may be received while a background download of the first version of the one or more images may be performed. In some embodiments, the first version may correspond to a high-resolution image whereas the second version may correspond to a lower resolution image.
H04L 67/61 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en tenant compte de la qualité de service [QoS] ou des exigences de priorité
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
G06F 16/538 - Présentation des résultats des requêtes
G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/587 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus
H04M 1/72445 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens de soutien local des applications accroissant la fonctionnalité pour donner accès à des applications de navigateur Internet
H04N 1/00 - Balayage, transmission ou reproduction de documents ou similaires, p. ex. transmission de fac-similésLeurs détails
88.
MODIFYING A FILE STORAGE STRUCTURE UTILIZING A MULTI-SECTION GRAPHICAL USER INTERFACE
This disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that can display icons for target digital content items and candidate destination folders within different sections of a multi-section graphical user interface (GUI) and adjust a corresponding file storage structure to reflect organization changes indicated by user interactions that move digital-content-items icons into folder icons. For example, the disclosed system can (i) display, within a first section of a multi-section GUI, icons representing digital content items and (ii) display, within a second section of the multi-section GUI, icons representing folders as candidate destination folders. Then, the disclosed systems can detect user interactions that move digital-content-item icons to folder icons and adjust an underlying file storage structure to reflect the organization indicated by the user interaction.
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect utilisant des icônes
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 16/16 - Opérations sur les fichiers ou les dossiers, p. ex. détails des interfaces utilisateur spécialement adaptées aux systèmes de fichiers
89.
Protecting content from generative artificial intelligence
The present technology introduces a simple to use interface that integrates a mechanism to protect content items from use by one or more machine learning algorithms into interfaces of a content management system. In this way, the present technology can make it easy to protect content items where they are stored. The present technology protects against this use by providing options to obfuscate content in a way that can confound artificial intelligence systems during both training and use of the artificial intelligence systems. Additionally, the present technology can control access to content items shared using a link. The content management system can determine not to serve content items when requested by known artificial intelligence systems or services that train them. The present technology can also include automatic content protection rules that can cause the content management system to automatically protect content items when the content item is to be shared.
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
90.
MODIFYING A FILE STORAGE STRUCTURE UTILIZING A MULTI-SECTION GRAPHICAL USER INTERFACE
This disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that can display icons for target digital content items and candidate destination folders within different sections of a multi-section graphical user interface (GUI) and adjust a corresponding file storage structure to reflect organization changes indicated by user interactions that move digital-content-items icons into folder icons. For example, the disclosed system can (i) display, within a first section of a multi-section GUI, icons representing digital content items and (ii) display, within a second section of the multi-section GUI, icons representing folders as candidate destination folders. Then, the disclosed systems can detect user interactions that move digital-content-item icons to folder icons and adjust an underlying file storage structure to reflect the organization indicated by the user interaction.
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect utilisant des icônes
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 16/16 - Opérations sur les fichiers ou les dossiers, p. ex. détails des interfaces utilisateur spécialement adaptées aux systèmes de fichiers
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating content clusters from topic data and focus data, generating content collections from content clusters, storing and restoring desktop scene layouts, and storing and arranging video call scenes. In some embodiments, the disclosed systems generate content clusters based on topic data and focus data associated with content items within a content management system and/or accessed via the internet. The disclosed systems can also generate content collections for a user account of the content management system from the content clusters. In some embodiments, the content scene system can further store and restore desktop scene layouts for arranging application windows presenting content items. Further, the disclosed systems can store and arrange particular desktop scene layouts for video call scenes.
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
92.
Generating responses using a context engine coupled with a logic engine and time phrase resolution
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating responses to prompts by utilizing a context engine and a logic engine. In one or more embodiments, the disclosed systems can determine a prompt received from a client device involves one or more logical problems with a prompt classification model. Based on identifying the one or more logical problems, the disclosed systems can generate a logic code segment by processing the prompt with one or more large language models within a context engine. The disclosed systems can generate a logic result for the prompt by processing the logic code segment with a logic engine that solves one or more logical problems within the prompt according to the structure of the logic code segment. The disclosed systems can generate a response to the prompt based, at least in part, on the logic result.
The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating function code and test code to determine that the function code satisfies an intent query. For example, the disclosed systems utilize a large language model to process an intent query and generate function code that defines one or more processes whose execution satisfies the intent query. In addition, the disclosed systems also utilize the large language model to generate test code that defines a function test for determining that the function code satisfies the intent query. Moreover, the disclosed systems can execute the test code to determine that the function code satisfies the intent query.
Methods and systems provide for dynamic contextual generation of creative content for product listings. In one embodiment, the system receives initial product facts for a product, user engagement data for a user of a platform, and one or more pieces of contextual information related to how the product will be viewed within the platform; uses this data to train a generative AI model for dynamic creative content generation for the listing; uses the trained generative AI model to dynamically generate creative content for the listing; displays the creative content for the listing on a client device associated with the user; receives feedback regarding user engagement with the creative content in terms of whether an engagement objective has been achieved; and refines the generative AI model based on the received feedback, including optimizing the generative AI model to generate or modify the creative content to achieve the engagement objective.
Disclosed herein is a system and method to determine whether to place an advertisement to a user requesting an address from the user. The system can iteratively determine multiple advertisement metrics of multiple advertisements to obtain multiple metrics. An advertisement metric among the multiple advertising metrics can indicate the value of placing the advertisement to the user. The system can rank multiple advertisements based on the multiple advertisement metrics and present a predetermined percentage of top-ranking advertisements among the multiple advertisements.
In some embodiments, a client application at a client device can receive, from a browser application at the client device, a first message including a unique identifier associated with a session of the browser application at a website associated with a content management system. The client application can extract the unique identifier from the first message, and establish a connection between the client application and the content management system by sending, from the client application to the content management system, a second message including the unique identifier. The client application can then receive, from the content management system through the connection, a third message relayed by the content management system from the website, where the third message is associated with the unique identifier.
H04L 67/02 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP]
H04L 67/1095 - Réplication ou mise en miroir des données, p. ex. l’ordonnancement ou le transport pour la synchronisation des données entre les nœuds du réseau
Disclosed are systems, methods, and non-transitory computer-readable storage media for providing an embedded web view of a folder in a content management system on a web page. For example, a user can request from a content management system code for embedding a web view of a content item or group of content items (e.g., folder) into a web page. After the code is embedded into the webpage, the web page can present a web view of the content item or group of content items that is dynamically updated when the content item or group of content items is updated. Thus, the user is relieved of the burden of updating the web page with new links to reflect changes in content items stored in the online content management system.
Methods and systems provide for a unified presentation of cross-platform content to a user visiting a platform. In one embodiment, the system connects a client device associated with a user to a first content platform; receives a request from the client device to present content to the user at the first content platform; receives content associated with one or more additional content platforms; determines a subset of the content to present to the user; standardizes the subset of the content in a format to be used at the first content platform; presents the subset of the content to the user at the first content platform; processes a set of unified cross-platform metrics for user events related to the user interacting with the subset of the content at the first content platform; and provides a report of the set of unified cross-platform metrics for the user events.
Disclosed here is a system that can obtain attributes of an advertisement, where an attribute has a continuous value, and a range of acceptable values is uncertain. The system can create a file including contents that when provided to a predetermined function produce a value of the attribute. Based on the file, the system can generate values corresponding to the attributes. Based on the generated values, the system can create the advertisement. The system can obtain a response data to the created advertisement and can fit a multidimensional function to the attributes and the user response data. Based on the multidimensional function, the system can determine next values and next ranges, where the next values and the next ranges indicate an improvement in the response data.
This disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that can detect scene types across various portions of media content and display collections that organize segments (or portions) of media content (e.g., videos or images) according to the detected scene types for the media content files. For example, the disclosed systems can automatically identify content segments of media content that belong to one or more identified scene types and display the content segments organized by the different scene types. In order to determine the scene types for the content segments of the media content files, the disclosed systems can utilize machine learning that determines relevancies between data of the media content files and the scene types. Furthermore, the disclosed systems can display, within a GUI, the groupings of media content segments organized by the different scene types.
G06F 16/783 - Recherche de données caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
