The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing synthetic visualizations representative of content collections within a content management system. In some cases, the disclosed systems generate a synthetic visualization based on content features that indicate relevance of content items with respect to a user account to emphasize more relevant content items within the synthetic visualization and/or to represent descriptive content attributes of the content items. For example, the disclosed systems can generate a synthetic phrase that represents a content collection and can further generate a synthetic visualization from the synthetic phrase utilizing a synthetic visualization machine learning model.
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.
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 of resources, e.g. of the central processing unit [CPU]
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
4.
DYNAMICALLY SELECTING ARTIFICIAL INTELLIGENCE MODELS AND HARDWARE ENVIRONMENTS TO EXECUTE TASKS
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 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
5.
PERSONALIZED RETRIEVAL-AUGMENTED GENERATION SYSTEM
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.
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.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
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.
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 16/783 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
9.
INTELLIGENT DOCUMENT CREATION AND REVIEW GENERATED BY A LARGE LANGUAGE MODEL
The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for the intelligent generation and completion of digital documents. For example, the disclosed systems provide a document creation interface for entering inputs to generate and modify digital documents. In some instances, the disclosed systems receive a document generation prompt, generate a digital document using a large language model, and provide an indication of the digital document within the document creation interface. Moreover, the disclosed systems can further generate a document summary of the digital document and provide the document summary for a recipient device via a document review interface. Additionally, the disclosed systems can further generate a suggested document modification element and modify the digital document in response to a user interaction with the suggested document modification element using the large language model.
A content management system obtains at least a portion of a meeting transcript based on an audio stream of a meeting attended by a plurality of users, the meeting transcript obtained in an ongoing manner as words are uttered during the meeting. The content management system detects text entered by a user of the plurality of users into a content item during the meeting. The content management system matches the detected text to at least part of the at least the portion of the meeting transcript. The content management system provides the at least part of the at least the portion of the meeting transcript to the user as a suggested subsequent text.
The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for the intelligent generation and completion of digital documents. For example, the disclosed systems provide a document creation interface for entering inputs to generate and modify digital documents. In some instances, the disclosed systems receive a document generation prompt, generate a digital document using a large language model, and provide an indication of the digital document within the document creation interface. Moreover, the disclosed systems can further generate a document summary of the digital document and provide the document summary for a recipient device via a document review interface. Additionally, the disclosed systems can further generate a suggested document modification element and modify the digital document in response to a user interaction with the suggested document modification element using the large language model.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing intelligent insights for video calls and other virtual meetings. In some embodiments, the disclosed systems analyze stored meeting data from past video calls and other virtual meetings to generate intelligent insights for an upcoming video call. The disclosed systems also generate and provide intelligent insights or coaching tools for ongoing video calls. As part of the intelligent coaching tools for ongoing video calls, the disclosed systems can generate predictions for accomplishing target goals for the video calls. Further, the disclosed systems can generate intelligent insights or coaching tools after video calls take place.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing intelligent insights for video calls and other virtual meetings. In some embodiments, the disclosed systems analyze stored meeting data from past video calls and other virtual meetings to generate intelligent insights for an upcoming video call. The disclosed systems also generate and provide intelligent insights or coaching tools for ongoing video calls. As part of the intelligent coaching tools for ongoing video calls, the disclosed systems can generate predictions for accomplishing target goals for the video calls. Further, the disclosed systems can generate intelligent insights or coaching tools after video calls take place.
A client application sends an application programming interface call to an interface of a content management system. The call specifies one or more content item search criteria. Sending the call causes the content management system to perform a lookup in a content item index to identify at least one content item that satisfies the one or more content item search criteria. Based on sending the call, the client application receives from the content management system a suggestion to attach the at least one content item to a text being displayed by at the computing system.
The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for editing and collaborating with digital videos through interactions with video transcripts. For example, the disclosed systems can provide a user interface for interacting with a video transcript associated with a digital video. Based on interacting with the video transcript, the disclosed systems can perform editing operations and/or collaborating operations in relation to the digital video. For instance, the disclosed systems can edit a digital video at a video portion corresponding to transcript location where a user interaction occurs within a video transcript.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing intelligent insights for video calls and other virtual meetings. In some embodiments, the disclosed systems analyze stored meeting data from past video calls and other virtual meetings to generate intelligent insights for an upcoming video call. The disclosed systems also generate and provide intelligent insights or coaching tools for ongoing video calls. As part of the intelligent coaching tools for ongoing video calls, the disclosed systems can generate predictions for accomplishing target goals for the video calls. Further, the disclosed systems can generate intelligent insights or coaching tools after video calls take place.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing intelligent insights for video calls and other virtual meetings. In some embodiments, the disclosed systems analyze stored meeting data from past video calls and other virtual meetings to generate intelligent insights for an upcoming video call. The disclosed systems also generate and provide intelligent insights or coaching tools for ongoing video calls. As part of the intelligent coaching tools for ongoing video calls, the disclosed systems can generate predictions for accomplishing target goals for the video calls. Further, the disclosed systems can generate intelligent insights or coaching tools after video calls take place.
A client application sends an application programming interface call to an interface of a content management system. The call specifies one or more content item search criteria. Sending the call causes the content management system to perform a lookup in a content item index to identify at least one content item that satisfies the one or more content item search criteria. Based on sending the call, the client application receives from the content management system a suggestion to attach the at least one content item to a text being displayed by at the computing system.
The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for performing a data search for a search request by utilizing a directed acyclic graph. For example, the disclosed systems receive a search request at a search engine of a content management system. In addition, the disclosed systems determine (e.g., in response to the search request) a node path from a directed acyclic graph that includes a plurality of interconnected nodes defining computer operations. Further, the determined node path includes a set of nodes that corresponds to the search request. Moreover, the disclosed systems perform the data search for the search request by executing operations defined by nodes along the node path within the directed acyclic graph.
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 technology provides a solution that can bring organization to the accumulated data and can surface insights derived from an analysis of stored objects. More specifically, the present technology is directed to an object analysis and classification service which is a configurable platform for identifying objects relevant to a topic and providing analysis of the objects relevant to that topic. The object analysis and classification service can include one or more technologies for identifying objects relevant to a topic. The topic can be configured by a user account or can be a predefined topic selected by the user account. The topic can include parameters that can be used by the one or more technologies for identifying objects relevant to a topic and to provide insights defined by the topic.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for integrating a content management system plugin with a large language model. In particular, in some embodiments, the disclosed systems integrate, into a computing environment of a large language model, a content management system plugin comprising computer code for an application programming interface (API) that facilitates operations by the large language model on content items stored in a content management system. Moreover, in some embodiments, the disclosed systems receive, from the large language model via the content management system plugin, a function call requesting performance of an API operation on a content item stored in the content management system. Furthermore, in some implementations, the disclosed systems execute the API operation on the content item stored in the content management system in response to the function call from the content management system plugin integrated within the large language model.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and visualizing effectivity scores from features extracted for different data of a time period. The disclosed systems generate a meeting effectivity score, a flow state effectivity score, and/or a work about work effectivity score that reflect measures of effectiveness or productivity. To generate the effectivity scores, the disclosed systems can leverage software connectors that extract features relevant to the respective effectivity scores for inputting into effectivity-score-generating models. Based on the effectivity scores, the disclosed systems can further generate recommendations for improving one or more of the effectivity scores. The disclosed systems can also generate and provide graphical visualizations of effectivity scores for display on a client device, together with recommendations for improving the effectivity scores.
The present technology is a cache that provides an implied guarantee that data returned in response to a query is current. The cache uses two techniques together to guarantee that data returned in response to a query from the cache is current. The first technique is a guaranteed clock value. The is a clock value for which all changes that have occurred before it have been written to the authoritative database. Any query having a clock value greater than the guaranteed clock value is invalid. The second technique is a data invalidation technique, where the cache repeatedly polls the authoritative database for information about changes and invalidates objects associated with changes. If no change has happened, the cache can confidently conclude it is up to date since the cache knows that it is aware of all changes as of the guaranteed clock value.
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 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
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 - Server selection for load balancing based on parameters of servers, e.g. available memory or workload
H04L 43/0817 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
27.
SYSTEM AND METHOD FOR DETECTING PROMPT INJECTION ATTACKS TO LARGE LANGUAGE MODELS
A computing system receives a prompt to be provided as input to a large language model. The computing system generates generating an input string to the large language model by appending a plurality of contexts to the prompt. The plurality of contexts defines rules for the large language model to follow when generating the prompt. The plurality of contexts includes a negative context. Based on the prompt and the plurality of contexts, the computing system generates an attention matrix representing relationships between the prompt and the plurality of contexts. The computing system provides the attention matrix to a trained neural network to determine a likelihood that the prompt is malicious. Responsive to determining that the prompt is likely a malicious prompt, the computing system initiates a remedial action.
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 relates to systems, non-transitory computer-readable media, and methods for using a large language model and digital content items (e.g., digital files) stored in a content management system to generate workflow outputs for external computing platforms. For instance, in some embodiments, the disclosed systems receive a workflow request that includes a natural language description of an objective to be accomplished via a workflow. The disclosed systems determine an action plan for completing the workflow and executes the action plan by accessing digital content items (e.g., digital files) stored in a content management system and extracting or generating data from the contents of the digital content items. Further, the disclosed systems use a large language model to generate a workflow output that is provided to an external computing platform for use.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for decomposing high-order objectives to implement automated or semi-automated changes to software applications. In particular, in one or more embodiments, the disclosed systems receive, from a client device, a high-order objective to be achieved within a computing system. In addition, in some embodiments, the disclosed systems determine, from the high-order objective, a set of sub-processes available to the computing system that combine to accomplish the high-order objective. Moreover, in some implementations, the disclosed systems generate, for a sub-process from among the set of sub-processes, a logic breakdown comprising a description of the sub-process and its predicted effect toward the high-order objective. Furthermore, in some embodiments, the disclosed systems provide the logic breakdown for display via the client device.
A content management system synchronizes content items across client computing systems connected by a network. Each client device has a storage allocation for synchronized shared content items. If the storage allocation for shared content items on a client device is exceeded by the request to add or edit a content item such that it is enlarged, or open a large content item remote to the client device, a client application or the host of content management system selects content items to remove from residence on the client device but keep remotely on content management system. Upon removal of the selected content items, the client application creates shadow items, representing the content item but only containing the metadata of the content item. This creates sufficient space for the initial request to be completed while maintaining user access to all synchronized shared content items.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
G06F 16/16 - File or folder operations, e.g. details of user interfaces specifically adapted to file systems
G06F 16/178 - Techniques for file synchronisation in file systems
H04L 67/1095 - Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
The present technology pertains to displaying granular viewer interactions for how viewers are viewing shared content items, such as videos, over time. A sharing and tracking service of a sharing platform associated with or managed by a content management system provides the granular viewer interactions of viewer interactions that retrace a full journey of views of shared content items in a content item interaction analytics timeline. The content item interaction analytics timeline may provide a visual representation of how the viewer interacts with the content item (e.g., how the user is scrolling through the different segments) throughout the viewing.
Disclosed are systems, methods, and non-transitory computer-readable storage media for managing projects in a content management system. For example, the content management system can create a project folder (e.g., shared folder) for managing data associated with a project. The project folder can be shared with content management system users (e.g., project members) who are contributors to the project. The content management system can store project data (e.g., content items, communications, comments, tasks, etc.) related to the project in the project folder. When the project folder is selected by a user, the content management system can generate a project folder view that presents the project data associated with the project folder and/or project in a convenient and easy to access graphical user interface. The content management system can aggregate project data from various content items associated with the project and present the project data in a single graphical user interface.
G06F 16/16 - File or folder operations, e.g. details of user interfaces specifically adapted to file systems
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/06 - Resources, workflows, human or project managementEnterprise or organisation planningEnterprise or organisation modelling
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and displaying a preview tile. In particular, in one or more embodiments, the disclosed systems select content item segments from a content item stored for a content management system and generate a preview tile by generating hotspot frames that reflect digital content in the content items segments. Further, in one or more embodiments, the disclosed systems provide the preview tile on a client device and, based on an input location relative to the preview tile, determine a hotspot frame to display within the preview tile.
Systems and methods for creating and accessing content items are provided. In some examples, a method can include receiving a user selection of an interface element located in a persistent user interface of an operating system desktop of a client device associated with a user account, identifying, based on a query to a meeting service, a meeting associated with the user account, displaying, in response to the user selection of the interface element, a set of user options for the meeting, the set of user options comprising an option to access a content item for the meeting, receiving a user selection of the option to access the content item for the meeting, and accessing, in response to the user selection, the content item.
H04L 65/401 - Support for services or applications wherein the services involve a main real-time session and one or more additional parallel real-time or time sensitive sessions, e.g. white board sharing or spawning of a subconference
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06Q 10/1093 - Calendar-based scheduling for persons or groups
H04L 12/18 - Arrangements for providing special services to substations for broadcast or conference
36.
TECHNIQUES FOR CAPTURING AND DISPLAYING PARTIAL MOTION IN VIRTUAL OR AUGMENTED REALITY SCENES
The present disclosure relates to techniques for capturing and displaying partial motion in VAR scenes. VAR scenes can include a plurality of images combined and oriented over any suitable geometry. Although VAR scenes may provide an immersive view of a static scene, current systems do not generally support VAR scenes that include dynamic content (e.g., content that varies over time). Embodiments of the present invention can capture, generate, and/or share VAR scenes. This immersive, yet static, view of the VAR scene lacks dynamic content (e.g., content which varies over time). Embodiments of the present invention can efficiently add dynamic content to the VAR scene, allowing VAR scenes including dynamic content to be uploaded, shared, or otherwise transmitted without prohibitive resource requirements. Dynamic content can be captured by device and combined with a preexisting or simultaneously captured VAR scene, and the dynamic content may be played back upon selection.
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.
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 renders, via a user interface, at least a portion of the relevancy-ranked content items.
G06F 16/2457 - Query processing with adaptation to user needs
G06F 7/08 - Sorting, i.e. grouping record carriers in numerical or other ordered sequence according to the classification of at least some of the information they carry
A system and method are provided for automatically selecting a subset of photos to be backed up by an intelligent photo upload service provided by a content management system. The intelligent photo upload service is provided to a client application on a client device that uses one or more machine-learning models to determine which photos have the one or more attributes. The photos that have been determined to have the one or more attributes may be uploaded. Once uploaded the one or more attributes may be used to label the respective photos with metadata indicating the presence of the one or more attributes. The one or more attributes may be used to filter photos at the content management system.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
G06V 10/94 - Hardware or software architectures specially adapted for image or video understanding
G06V 20/30 - ScenesScene-specific elements in albums, collections or shared content, e.g. social network photos or video
G06V 20/70 - Labelling scene content, e.g. deriving syntactic or semantic representations
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 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
H04L 51/216 - Handling conversation history, e.g. grouping of messages in sessions or threads
Computer-implemented techniques encompass using distinct machine learning sub-models to score respective types of candidate content for the purpose of providing personalized content suggestions to end-users of a content management system. The relevancy scores generated by the distinct sub-models are mapped to expected end-user interaction scores of the candidate content scored. Content suggestions are provided at end-users' computing devices where the suggested content is selected from the candidate content based on the expected end-user interaction scores of the candidate content. For each distinct sub-model, a normalizing mapping function is solved using an optimizer that maps the relevancy scores generated by the sub-model for the candidate content to expected end-user interaction scores for the candidate content. The expected end-user interaction scores are comparable across the distinct sub-models and can be used to rank content suggestions across the distinct sub-models.
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 is directed toward systems, methods, and non-transitory computer-readable media for generating context engine outputs by utilizing an interpreter purpose-built to execute code generated by large language models. For example, the disclosed systems generate computer code executable for responding to a query by utilizing a large language model. In addition, the disclosed systems execute the model-generated computer code utilizing an interpreter integrated with the context engine that further includes swappable logic interchangeable across multiple executors. Moreover, the disclosed systems can further generate as part of executing the computer code utilizing the interpreter, a first context engine output by implementing the interpreter at a first executor. Additionally, the disclosed systems can further generate a second context engine output by implementing the interpreter at a second executor.
The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating context engine outputs by utilizing an interpreter purpose-built to execute code generated by large language models. For example, the disclosed systems generate computer code executable for responding to a query by utilizing a large language model. In addition, the disclosed systems execute the model-generated computer code utilizing an interpreter integrated with the context engine that further includes swappable logic interchangeable across multiple executors. Moreover, the disclosed systems can further generate as part of executing the computer code utilizing the interpreter, a first context engine output by implementing the interpreter at a first executor. Additionally, the disclosed systems can further generate a second context engine output by implementing the interpreter at a second executor.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating composite actions for a user account. In particular, in one or more embodiments, the disclosed systems determine a set of tasks performable by the user account using software tools on a client device. In some embodiments, the disclosed systems generate a task initialization prompt to provide to a large language model. Additionally, in some implementations, the disclosed systems generate a composite action comprising a hybridized combination of the set of tasks performable by the user account along with a set of content items relevant to the set of tasks. Moreover, in some embodiments, the disclosed systems provide access to the composite action and the set of content items via a user interface of the client device. Furthermore, in some implementations, the disclosed systems generate and insert predicted content into a content item without user input.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing an aggregated feed interface that includes or presents aggregate summaries for thread data across multiple data feeds of a user account. In some embodiments, the disclosed systems generate an aggregate summary by extracting digital communications and other thread data from a variety of data feeds across multiple computer applications and by utilizing a summary generation model to generate an aggregate summary that combines and condenses the thread data from the different data feeds. For example, the disclosed systems determine topics associated with thread data from various data feeds and generates different aggregate summaries for different topics. The disclosed systems can further rank aggregate summaries and/or other digital communications to present within the aggregated feed interface according to an account-specific ranking algorithm resulting a customized per-account presentation of the aggregated feed interface.
A system receives a request for a data block, in which the data block corresponds to a set of fragments, and the data block can be fully reconstructed using a threshold number of the set of fragments. A first subset of the set of fragments are stored in a first storage system, and a second subset of the set of fragments are stored in a second storage system characterized by a higher average latency than the first storage system. A system, responsive to receiving the request for the data block, requests the first subset of the set of fragments. A system receives at least the threshold number of the first subset of the fragments. A system reconstructs the data block using the received fragments of the first subset of the fragments. A system provides the reconstructed data block.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating composite actions for a user account. In particular, in one or more embodiments, the disclosed systems determine a set of tasks performable by the user account using software tools on a client device. In some embodiments, the disclosed systems generate a task initialization prompt to provide to a large language model. Additionally, in some implementations, the disclosed systems generate a composite action comprising a hybridized combination of the set of tasks performable by the user account along with a set of content items relevant to the set of tasks. Moreover, in some embodiments, the disclosed systems provide access to the composite action and the set of content items via a user interface of the client device. Furthermore, in some implementations, the disclosed systems generate and insert predicted content into a content item without user input.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing an aggregated feed interface that includes or presents aggregate summaries for thread data across multiple data feeds of a user account. In some embodiments, the disclosed systems generate an aggregate summary by extracting digital communications and other thread data from a variety of data feeds across multiple computer applications and by utilizing a summary generation model to generate an aggregate summary that combines and condenses the thread data from the different data feeds. For example, the disclosed systems determine topics associated with thread data from various data feeds and generates different aggregate summaries for different topics. The disclosed systems can further rank aggregate summaries and/or other digital communications to present within the aggregated feed interface according to an account-specific ranking algorithm resulting a customized per-account presentation of the aggregated feed interface.
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 relates to systems, non-transitory computer-readable media, and methods for generating content-item-specific large language model responses from content items by segmenting a content item and selecting relevant sections of the content item to provide to a large language model to generate a corresponding output. In particular, in one or more embodiments, the disclosed systems can generate a text representation that includes a plurality of text segments each comprising a number of tokens of the text representation. Further, the systems can extract, from the plurality of text segments, segment-specific text embeddings that correspond to respective portions of the text representation of the content item. Additionally, the systems can determine a segment-specific text embedding corresponding to a model output request. Moreover, the systems can generate a model output by passing a text segment corresponding to the segment-specific text embedding to a large language model together with the model output request.
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.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and providing customized content labels as elements for seamless integration within a graphical interface. For instance, the disclosed systems provide generative options utilizing contextual data to more effectively incorporate a content label (textual and/or visual) based on the surrounding graphical elements, the functionality of the label within the interface, and the purpose of the label or interface. In this way, the disclosed systems generate contextual labels with appropriate textual content and that are appropriately sized, styled, and positioned based on their relevance within the context of the graphical interface.
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.
Methods and systems provide for cross-relevant refinement of generative artificial intelligence models for creative content across multiple platforms. In one embodiment, the system receives creative content related to a first product listing for a product within a first platform, user engagement data for a user of a second platform, and one or more pieces of contextual information; trains a refinement of a second generative AI model for dynamic creative content generation for a modified version of the first product listing for the second platform; generates and displays one or more pieces of creative content for a second product listing to be published on the second platform; receives feedback regarding user engagement with the pieces of creative content in terms of whether an engagement objective has been achieved; and refines the first generative AI model and the second generative AI model via a network of cross-refinement.
Methods and systems provide for dynamically optimized recommendations in generative media. In one embodiment, the system receives, through a conversational interface, input submissions from a user engaging in a conversation with a generative artificial intelligence (AI) system; generates, via the generative AI system, a search query for a search engine backend of the platform; sends the search query to the search engine backend of the platform to retrieve at least a subset of a prompt as input to the generative AI system, the subset of the prompt including a sorted list of search results from the search engine backend; processes the prompt to generate a set of personalized recommendations for the user; and presents, within the platform presented at the client device, the set of personalized recommendations for the user, the presentation incorporating media content representing at least a portion of the search result items.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for improving digital transcripts of a meeting based on user information. For example, a digital transcription system creates a digital transcription model to automatically transcribe audio from a meeting based on documents associated with meeting participants, event details, user features, and other meeting context data. In one or more embodiments, the digital transcription model creates a digital lexicon based on the user information, which the digital transcription system uses to generate the digital transcript. In some embodiments, the digital transcription model trains and utilizes a digital transcription neural network to generate the digital transcript.
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 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.
G10L 15/18 - Speech classification or search using natural language modelling
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G10L 15/183 - Speech classification or search using natural language modelling using context dependencies, e.g. language models
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
G10L 15/30 - Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
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.
A collaborative content management system (CMS) is disclosed herein for generating templates for received documents. The disclosed CMS recognizes that a document selected by a user for processing was previously processed by the CMS and that a user has previously added particular overlaid fillable fields to the document. When the determination is made, the system generates a recommendation to create a template of the document with the previously added overlaid fillable fields. In some embodiments, the CMS makes the recommendation to generate a template when the user creates, in a received document, identical overlaid fillable fields or field types to those created in the previously processed document.
A collaborative content management system identifies an application installed on one or more client devices that is susceptible to an attack by using the API calls of the application. The collaborative content management system obtains API calls made by the application and derives API call features. The collaborative content management system inputs the API call features into a machine learning model and receives, as output from the model, a determination of whether the set of API calls represents a C2 attack. In some embodiments, the collaborative content management system, responsive to determining that the set of API calls represents a C2 attack, may take a security action.
The system obtains performance signals associated with respective hard disks of a volume of hard disks including a plurality of hard disks that are dedicated to activities of a service. The system determines a volume failure prediction for the volume of hard disks by, for each respective hard disk of the volume of hard disks, determining a hard disk failure prediction. The system determines a hard disk failure prediction by: inputting the respective performance signals into a supervised machine learning model; and receiving as output from the machine learning model the hard disk failure prediction for the respective hard disk. The system based on the received outputs, determines that the volume failure prediction is associated with a migration condition. The system, responsive to determining that the volume failure prediction is associated with the migration condition, migrates data from the volume of hard disks to a second volume of hard disks.
Disclosed are systems, methods, and non-transitory computer-readable storage media for managing projects using references between the project and project items. Project items can be, for example, synchronized content items, collaborative content items, other projects, folders, tasks, user accounts, etc. The content management system can create a project identifier for managing data and/or people associated with a project. In various implementations, the content management system can store references between the project and project items in one or more folders associated with the project, in a database, in content item metadata, etc. In some implementations, the storage location of a content item does not affect whether it is associated with the project. When a project is selected by a user, the content management system can generate project view that presents various project items associated with the project in a convenient and easy to access graphical user interface.
G06Q 10/101 - Collaborative creation, e.g. joint development of products or services
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 16/16 - File or folder operations, e.g. details of user interfaces specifically adapted to file systems
G06F 16/25 - Integrating or interfacing systems involving database management systems
G06F 16/955 - Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
G06Q 10/06 - Resources, workflows, human or project managementEnterprise or organisation planningEnterprise or organisation modelling
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
65.
GENERATING AND MANAGING MULTILOCATIONAL DATA BLOCKS
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and managing multilocational data blocks, generating and summarizing content blocks within a virtual space interface, and generating and providing a content block browser as part of a virtual space platform. In some embodiments, the disclosed systems generate a multilocational data block that includes a block identifier that is tied to a source identifier for embedding digital content from a network location indicated by the source identifier. The disclosed systems can also generate block summaries from content blocks for presenting and modifying digital content embedded within the content blocks via block identifiers and source identifiers. In some embodiments, the content block system can provide a content-block-based web browser in the form of a virtual space that includes embedded content blocks that integrate webpage functionality.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
G06F 3/06 - Digital input from, or digital output to, record carriers
G06Q 10/101 - Collaborative creation, e.g. joint development of products or services
Techniques for learning and using content type embeddings. The content type embeddings have the useful property that a distance in an embedding space between two content type embeddings corresponds to a semantic similarity between the two content types represented by the two content type embeddings. The closer the distance in the space, the more the two content types are semantically similar. The farther the distance in the space, the less the two content types are semantically similar. The learned content type embeddings can be used in a content suggestion system as machine learning features to improve content suggestions to end-users.
G06F 16/957 - Browsing optimisation, e.g. caching or content distillation
G06F 16/178 - Techniques for file synchronisation in file systems
G06F 16/2457 - Query processing with adaptation to user needs
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
G06N 20/10 - Machine learning using kernel methods, e.g. support vector machines [SVM]
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
67.
PROCESSING ELECTRONIC SIGNATURE DATA IN A COLLABORATIVE ENVIRONMENT
A collaborative content management system (CMS) is disclosed herein for processing electronic signature data in a collaborative environment and performing actions based on the received data. The CMS may receive a selection of a content item to be electronically signed by one or more users. Upon receipt of the selection, the CMS may generate a fillable form and send the fillable form to be electronically filled out signed. When each user fills out and signs the form, the CMS may receive that form data and aggregate the form data with previously received form data. The CMS may determine whether the aggregated form data meets one or more conditions stored within the CMS and perform appropriate actions based on one or more conditions that are met.
Embodiments relate to identifying an error in a form that is incorrectly filled out and apply corrections to the form. A module may identify inputs of a form (e.g., webpage) and apply an autofill template to the identified inputs, where the autofill template specifies input types of the identified inputs and content to be applied to the input types. The module may automatically detect an input error. The module may, responsive to detecting the input error, receive a correction indication specifying a first input of the form (e.g., webpage) and an input type of the first input. The module may update the autofill template according to the correction indication. The module may apply the updated autofill template to the first input of the form (e.g., webpage).
Embodiments relate to improved classification techniques for classifying form (e.g., webpage) forms and inputs for password auto fill applications. A module may detect a client device accessing a form (e.g., webpage) and may identify inputs of the form (e.g., webpage). The module may group two or more of the identified inputs into a bundle and apply the bundle to one or more machine learned bundle classifier models configured to determine a form type of the bundle. The module may also apply the bundle to the selected input classifier model. The module may automatically fill one or more inputs of the form (e.g., webpage) according to the input types identified by the selected input classifier model.
Systems or methods for generating a plurality of different custom links that have different viewing options for viewing the same shared content item in customized content item players and displaying engagement analytics for how viewers are viewing shared content items, such as videos, are disclosed. A custom link to view the shared content item is generated in association with settings that are customized by an administrator. Once the custom link is accessed, a customized content item player is generated based on the settings. Once the content item is being played in a customized content item player, the engagement analytics are populated in real-time in a graphical display. The different engagement levels and graphical representations of segments of viewing are distinguished based on the engagement levels.
A content management system synchronizes content items across client computing systems connected by a network. Each client device has a storage allocation for synchronized shared content items. If the storage allocation for shared content items on a client device is exceeded by the request to add or edit a content item such that it is enlarged, or open a large content item remote to the client device, a client application or the host of content management system selects content items to remove from residence on the client device but keep remotely on content management system. Upon removal of the selected content items, the client application creates shadow items, representing the content item but only containing the metadata of the content item. This creates sufficient space for the initial request to be completed while maintaining user access to all synchronized shared content items.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
G06F 16/16 - File or folder operations, e.g. details of user interfaces specifically adapted to file systems
G06F 16/178 - Techniques for file synchronisation in file systems
H04L 67/1095 - Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
72.
BACKUP FEATURE PROVIDED BY BIDIRECTIONAL SYNCHRONIZED CONTENT MANAGEMENT SYSTEM
The present technology is directed to providing a backup service utilizing a bi-directional synchronization architecture. In order to support both a backup service and a bi-directional synchronization service, the present technology can utilize a special object called an anchor that only permits unidirectional synchronization. Additionally, the present technology separates the backup service from the bi-directional synchronization service. This separation includes utilizing a separate backup directory and bi-directional synchronization directory on a client device, which in turn benefits from the use of a separate instance of the synchronization service on the client device. Further, at the content management system various steps are taken to separate the backup directory from the bi-directional synchronization directory to ensure no objects from the backup directory appear in a user interface related to bi-directional synchronization, and vice versa.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/25 - Integrating or interfacing systems involving database management systems
73.
PER-NODE METADATA FOR CUSTOM NODE BEHAVIORS ACROSS PLATFORMS
Technologies for implementing customized behaviors for content items are provided. An example method can include receiving, from a user account registered with a content management system, a request to access a content item managed by the content management system for the user account, the content item having one or more behaviors configured for an attribute associated with the content item and/or the content item associated with the attribute; obtaining, from a representation of a remote state of content items associated with the user account, metadata defining the attribute associated with the content item; based on the metadata, determining the one or more behaviors configured for the attribute and/or the content item associated with the attribute; and applying the one or more behaviors to the content item.
G06F 16/178 - Techniques for file synchronisation in file systems
G06F 16/13 - File access structures, e.g. distributed indices
G06F 16/16 - File or folder operations, e.g. details of user interfaces specifically adapted to file systems
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
74.
GENERATING AND PROVIDING MORPHING ASSISTANT INTERFACES THAT TRANSFORM ACCORDING TO ARTIFICIAL INTELLIGENCE SIGNALS
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing an intelligent assistant interface that integrates with a large language model and a knowledge graph to adaptively change its appearance for presenting and interacting with different content items from various sources. In some embodiments, the disclosed systems provide an intelligent assistant interface that includes a set of interface elements selectable to interact with a large language model. Based on an input intent, the disclosed systems can utilize the large language model to analyze a knowledge graph for accessing and/or generating content items for display within the intelligent assistant interface.
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.
Disclosed are systems, methods, and non-transitory computer-readable storage media for shared folder backed integrated workspaces. In some implementations, a content management system can provide a graphical user interface (GUI) that integrates communications and content management into a single user interface. The user interface can include mechanisms that allow a user to provide input to generate a new workspace. The user interface can provide a mechanism to allow a user to view conversations related to the workspace and/or content items associated with the workspace. The user interface can present representations of content items associated with the workspace and allow the user to provide input to generate, view, edit, and share content items associated with the workspace.
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06F 3/04842 - Selection of displayed objects or displayed text elements
G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
G06F 16/16 - File or folder operations, e.g. details of user interfaces specifically adapted to file systems
G06F 16/178 - Techniques for file synchronisation in file systems
G06F 16/25 - Integrating or interfacing systems involving database management systems
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
H04L 12/18 - Arrangements for providing special services to substations for broadcast or conference
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
H04L 51/046 - Interoperability with other network applications or services
H04L 51/08 - Annexed information, e.g. attachments
H04L 51/216 - Handling conversation history, e.g. grouping of messages in sessions or threads
H04L 51/224 - Monitoring or handling of messages providing notification on incoming messages, e.g. pushed notifications of received messages
H04L 51/42 - Mailbox-related aspects, e.g. synchronisation of mailboxes
H04L 51/48 - Message addressing, e.g. address format or anonymous messages, aliases
H04L 51/52 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
H04L 51/56 - Unified messaging, e.g. interactions between e-mail, instant messaging or converged IP messaging [CPM]
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
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.
This disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that can utilize language neural networks to automatically generate draft electronic communications for a user account. For example, the disclosed systems leverage composition parameters of a user account (determined from historical electronic communications of the user account, digital content items corresponding to the user account, and/or other application data) with a neural network to automatically generate draft electronic communications that reflect a composition style of a user account and accurately addresses a context of a communication thread. In addition, the disclosed systems can generate electronic communications using the communication generation neural network and save the electronic communication as a draft (e.g., for review by a user of the user account) and/or automatically transmit the electronic message to a recipient user account.
A system can selectively synchronize content based on synchronization settings. In some examples, a client stores a local tree representing a local set of content items associated with an account on a content management system, the local tree including respective local nodes corresponding to the local set of content items. The client stores a remote tree representing a remote set of content items associated with the account, the remote set being stored at the content management system and including respective remote nodes corresponding to the remote set of content items. The client receives a synchronization setting disabling local storage of the content item. In response, the client deletes a local copy of the content item, removes a corresponding local node from the local tree, and adds, to a remote node on the remote tree, an attribute indicating that local storage of the content item has been disabled.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
G06F 1/04 - Generating or distributing clock signals or signals derived directly therefrom
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 12/14 - Protection against unauthorised use of memory
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
G06F 16/13 - File access structures, e.g. distributed indices
G06F 16/14 - Details of searching files based on file metadata
G06F 16/16 - File or folder operations, e.g. details of user interfaces specifically adapted to file systems
G06F 16/17 - Details of further file system functions
G06F 16/172 - Caching, prefetching or hoarding of files
G06F 16/174 - Redundancy elimination performed by the file system
G06F 16/176 - Support for shared access to filesFile sharing support
G06F 16/178 - Techniques for file synchronisation in file systems
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
H04L 67/06 - Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
H04L 67/1095 - Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
The present disclosure relates to systems, non-transitory computer-readable media, and methods for controlling the display of rich digital content within a digital document. For instance, in some embodiments, the rich content toggling system provides a rich content toggle element for enabling and disabling display of rich content within a digital document, all while maintaining the data for the rich content as part of the digital document. In addition to the rich content toggle element, the rich content toggling system can provide more granular options for selecting or controlling which types of rich content items to display or not display within a digital document. In addition, the disclosed systems can provide a magnifier cursor that is moveable to scroll over the digital document to reveal hidden or removed rich content items that have been toggled off.
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.
A system and method for displaying pinned content in a user interface is described herein. A collaborative content management system displays pins in an order personalized to a user. The collaborative content management system receives a command to output a user interface with a set of pins corresponding to a collaborative content item. For each pin, the collaborative content management system inputs data corresponding to the pin into a machine learning model and receives from the model the probability that the user is interested in the pin. The collaborative content management system ranks the set of pins based on the computed probability and outputs the user interface with at least one pin based on the ranking of the set of pins.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and managing multilocational data blocks, generating and summarizing content blocks within a virtual space interface, and generating and providing a content block browser as part of a virtual space platform. In some embodiments, the disclosed systems generate a multilocational data block that includes a block identifier that is tied to a source identifier for embedding digital content from a network location indicated by the source identifier. The disclosed systems can also generate block summaries from content blocks for presenting and modifying digital content embedded within the content blocks via block identifiers and source identifiers. In some embodiments, the content block system can provide a content-block-based web browser in the form of a virtual space that includes embedded content blocks that integrate webpage functionality.
Methods, systems, and non-transitory computer readable storage media are disclosed for generating meeting insights based on media data and device input data. In one or more embodiments, the system analyzes media data and inputs to client devices associated with a meeting to determine a portion of the meeting that is relevant for a user. In one or more embodiments, the system generates a meeting summary, meeting highlights, or action items related to the media data to provide to the client device. In one or more embodiments, the system also uses the summary, highlights, or action items to train a machine-learning model for use with future meetings.
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and applying audio signatures to digital documents based on receiving audible approval for a signature. In particular, in one or more embodiments, the disclosed systems field prompt audio files that include prompts for signable fields within a document. Further, in one or more embodiments, the disclosed systems receive audible approval in response to a field prompt audio file. In some embodiments, based on the audible approval, the disclosed systems generate an audio signature and apply the audio signature to the signable field of the digital document.
One or more embodiments allow a user to search a gallery of digital content. In particular, a user can interact with a digital content system to search for, and identify, one or more digital content items (e.g., photos, videos, audio) within a collection of digital content. For instance, the digital content system can maintain tokens with respect to a collection of digital content and associate the tokens with digital content items within the collection of digital content. The digital content system can also provide a gallery of digital content items within a view area of a graphical user interface. Upon receiving a search query, the digital content system can identify a token and identify digital content items corresponding to the token. The digital content system can further provide a new or modified gallery within the view area of the graphical user interface based on the identified digital content items.
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 16/58 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
G06F 16/587 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
87.
GENERATING, APPLYING, AND VERIFYING AUDIO SIGNATURES FOR DIGITAL DOCUMENTS
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and applying audio signatures to digital documents based on receiving audible approval for a signature. In particular, in one or more embodiments, the disclosed systems field prompt audio files that include prompts for signable fields within a document. Further, in one or more embodiments, the disclosed systems receive audible approval in response to a field prompt audio file. In some embodiments, based on the audible approval, the disclosed systems generate an audio signature and apply the audio signature to the signable field of the digital document.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
software for the storage, sharing, access, backup, recovery, management, organization, tracking, research of data, files and documents; Software applications; Games software; Software; Packaged software; Software compiler; Programming software; Operating software; Education software; Graphics software; Communication software; Software drivers; Collaboration software; Community software; Antimalware software; Security software; Workflow software; Multimedia software; Utility software; Media software; Privacy software; Debugging software; Platform software; Mobile software; Editing software; Telecommunications software; Adaptive software; Training software; Interactive software; Authentication software; Server software; Map software; Plugin software; AI software; Payment software; Optimisation software; Publishing software; Presentation software; Navigation software; Business software; Collaborative software; Networking software; Social software; Banking software; Retail software; Reference software; Reporting software; Collaboration software platforms [software]; Embedded software; Enterprise software; Gambling software; Application software; Logistics software; Computer software; Computer telephony software; Desktop publishing software; E-commerce software; Software development programmes; Downloadable application software; Data communications software; Data processing software; Downloadable computer software; Search engine software; Database management software; Website development software; Music-composition software; Computer firewall software; Mobile application software; Augmented reality software; Voice recognition software; Software for televisions; Speech recognition software; Facial recognition software; File management software; Speech analytics software; Image recognition software; File synchronization software; Business technology software; Parental control software; Virtual classroom software; File sharing software; Printer spooler software; Vehicle control software; Machine learning software; Web application software; Instant messaging software; Cloud computing software; Business management software; Character recognition software; Artificial intelligence software; Data mining software; Day trading software; Content control software; Information retrieval software; Digital dashboard software; Video conference software; Content management software; Reservation systems software; Risk detection software; Health monitoring software; Environmental monitoring software; Cloud server software; Database synchronization software; Downloadable translation software; Smart home software; File server software; Media server software; Database server software; Online payment software; Interactive database software; Industrial automation software; Building management software; Software for smartphones; Computer application software; Casino management software; Software for card readers; Computer operating system software; Computer software for education; Computer software for advertising; Software for tablet computers; Vehicle control assistance software; Cloud network monitoring software; Media and publishing software; Software for product development; Downloadable cloud computing software; Software for Smart Contracts; Application software for robot; Satellite imagery photo-interpretation software; Software for use in advertising; Computer software for business purposes; Application software for smart TV; Computer-aided design (CAD) software; Customer relation management [CRM] software; Virtual reality software for telecommunications; Digital solutions provider [DSP] software; Virtual and augmented reality software; Utility, security and cryptography software; Web application and server software; Machine learning software for analysis; Artificial intelligence software for vehicles; Artificial intelligence software for surveillance; Artificial intelligence software for healthcare; Machine learning software for surveillance; Intrusion detection system [IDS] software; VPN [virtual private network] operating software; Computer software supplied on the Internet; Computer software to automate data warehousing; Application software for cloud computing services; Data processing software for word processing; Virtual reality software for medical teaching; E-commerce and e-payment software; Artificial intelligence and machine learning software; Communication, networking and social networking software; Computer software for tracking driver behaviour; Computer chatbot software for simulating conversations; Software for processing images, graphics and text; Interactive software based on artificial intelligence; Computer software for scanning images and documents; Computer software for authorising access to databases; Computer software for processing digital music files; Software for designing online advertising on websites; System and system support software, and firmware; Data and file management and database software; Computer software for the control of lighting; Computer screen saver software, recorded or downloadable; Computer software for use in remote meter reading; Computer software for use in computer access control; Computer software in the field of electronic publishing; Computer software for the compilation of positioning data; Software to control and improve audio equipment sound quality; Software for searching and retrieving information across a computer network; Computer software for creating searchable databases of information and data; Downloadable software for remotely accessing and controlling a computer; Software for monitoring, analysing, controlling and running physical world operations; Computer software adapted for use in the operation of computers; Recorded computer programmes; Computer programmes stored in digital form; Plug-in connectors; Document management software; Data management software; Workflow management system software; Big data management software; Downloadable digital music files authenticated by non-fungible tokens [NFTs]; Downloadable image files; Downloadable music files; Downloadable video files; Recorded data files; Downloadable multimedia files; Self-synchronizing digital encryptors; Navigation, guidance, tracking, targeting and map making devices; Collaboration tools [software]; Project management software; Databases; Data networks; Data carriers; Data transmission apparatus; Data transmitting apparatus; Electronic databases; Computer databases; Interactive databases; Electronic data carriers; Data processing programs; Data communications hardware; Data storage programs; Electronic data processing equipment; Data storage devices and media; Computer networking and data communications equipment; Electronic databases recorded on computer media; Electrical and electronic instruments for storing data; Computer software to enable searching of data; Computer software to enable retrieval of data; Data processing equipment and accessories (electrical and mechanical); Downloadable software applications; Downloadable software; Computer software platforms for social networking; Computer software for entertainment; Testware. Data management; Business project management services; Data searches in computerised files for others; Data search in computer files for others; Retail services in relation to downloadable music files; Computerized management of medical records and files; Retail services relating to downloadable digital image files authenticated by non-fungible tokens [NFTs]; Business project management; Maintaining personal medical history records and files; Data transcription; Database management; Database marketing; Computerised data verification; Data entry and data processing; Electronic data processing; Collection of data; Compilation of data; Data processing management; Transcription of data; Provision of business data; Computer database management services; Data processing, systematisation and management; Subscriptions to telecommunications database services; Administrative support and data processing services; Office services for electronically manipulating data; Business data research; Business management; Computerized file management; Systemization of information into computer databases; Collection and systematisation of information into computer databases; Advice relating to marketing management; Analysis of business management systems; Advice and information concerning commercial business management; Business management and organization consultancy; Advertising; Direct marketing; Market research; Assistance and advice regarding business organisation and management; Data processing verification; Computerised data processing; Data processing for the collection of data for business purposes; Data processing for businesses; Automated data processing; Online data processing services; Data processing; Computerised business information processing services; Data management services; Advisory services relating to electronic data processing; Advisory services relating to data processing; Business consultancy services relating to data processing; Information services relating to data processing; Computerised business information retrieval; Management and compilation of computerised databases; Compilation and systematisation of information in databanks; Compilation of information into computer databases; Consultancy relating to data processing; Business assistance, management and administrative services; Business analysis and information services, and market research; Collecting information for business; Compilation of computer databases; Compilation of statistical data for use in scientific research; Compilation of statistical data relating to medical research; Compilation of statistical data relating to business; Compilation of statistics [for business or commercial purposes]; Compilation of direct mailing lists; Compilation of business directories; Preparation of business statistical data; Data compilation for others; Compilation and systemization of information into computer databases; Drawing up of business statistical information; Consultancy relating to the preparation of business statistics; Records management services, namely, document indexing for others; Compilation of statistics; Computerised compilation of stock control records; Computerised compilation of order lists; Computerised compilation of customer indexes; Obtaining business statistics [for others]; Compilation of business statistics and commercial information; Compilation of business statistics; Business consultancy and advisory services; Administrative data processing. Platform as a service [PaaS] featuring software platforms for the storage, sharing, access, backup, recovery, management, organization, tracking, research of data, files and documents; Software creation; Software development; Software design; Computer software engineering; Computer software integration; Development of software; Software consulting services; Installation of software; Software maintenance services; Software design for others; Update of computer software; Computer software advisory services; Software as a service; Maintenance of computer software; Updating of software databases; Computer software programming services; Design of virtual reality software; Rental of software for computers; Services for updating computer software; Design of graphic software systems; Hosting services, software as a service, and rental of software; Software development, programming and implementation; Providing online, non-downloadable software; Software as a service [SaaS]; Software as a service [SAAS] services; Creation, maintenance and adaptation of software; Updating and design of computer software; Programming of software for inventory management; Programming of software for database management; Programming of software for Internet platforms; Design of online social networking software; Development of software for communication systems; Software as a service [SaaS] featuring computer software platforms for artificial intelligence; Software engineering services for data processing; Installation, maintenance and repair of computer software; Hosting of software for use in library management; Design and development of computer software for logistics; Design, maintenance, rental and updating of computer software; Providing temporary use of online non-downloadable software; Platforms for gaming as software as a service [SaaS]; Providing on-line non-downloadable software for database management; Design and development of software for importing and managing data; Design and development of computer software for supply chain management; Platforms for artificial intelligence as software as a service [SaaS]; Duplicating computer programmes; Consultancy in the field of security software; Remote computer backup services; Electronic data back-up; Electronic data storage and data back-up services; Providing back-up computer programs and facilities; Data back-up services; Hosting online web facilities for others for sharing online content; Providing temporary use of non-downloadable software to enable sharing of multimedia content and comments among users; Computer time sharing facilities (Provision of -); Cloud storage services for electronic files; Electronic storage of files and documents; Hosting of computerized data, files, applications and information; Providing temporary use of non-downloadable software to enable content providers to track multimedia content; Hosting software platforms for virtual reality-based work collaboration; IT project management; Electronic storage of archived e-mails; Electronic storage of documents and archived e-mails; Electronic storage services for archiving databases, images and other electronic data; Data mining; Data warehousing; Database design; Data recovery services; Data security services; Data migration services; Online data storage; Data security consultancy; Electronic data storage; Data duplication and conversion services, data coding services; Recovery of computer data; Data storage via blockchain; Data authentication via blockchain; Electronic data back-up services; Rental of database management software; Rental of computer database software; Cloud-based data protection services; Maintenance of databases; Reconstitution of databases; Hosting of databases; Data security services [firewalls]; Electronic storage of data; Engineering services relating to data processing technology; IT consultancy, advisory and information services; IT services; IT services for data protection; Computer programming for others; Electronic storage of audio files; Platform as a service [PaaS] featuring software platforms for transmission of images, audio-visual content, video content and messages; Development of hardware for audio and video operators; Design of software for audio and video operators; Product development for others; Providing temporary use of on-line non-downloadable software for the management of information; Providing temporary use of on-line non-downloadable software for the management of data; Development of computer software for logistics, supply chain management and e-business portals; Updating of computer software for others; Providing technical advice relating to computer hardware and software; Providing temporary use of non-downloadable business software; Programming of software for e-commerce platforms; Design of computer machine and computer software for commercial analysis and reporting; Providing temporary use of non-downloadable software for analyzing financial data and generating reports; Rental of computer software for collecting, analyzing and organizing data in the field of deep learning; Providing temporary use of online non-downloadable computer software for collecting, analyzing and organizing data in the field of deep learning; Hosting platforms on the Internet; Engineering project management services; Enterprise content management; Rental of a database server (to third parties); Installation, maintenance and updating of database software; Consultancy relating to computer database programs; Providing online non-downloadable computer software; Providing temporary use of on-line non-downloadable operating software for accessing and using a cloud computing network; Artificial intelligence consultancy; Providing artificial intelligence computer programs on data networks; Design of information systems relating to management; Product research; Technical research; Computer software research; Computer research services; Product research and development; Research into new products; Research relating to data processing; Technical research projects and studies; Research relating to computer programs; Research relating to computer programming; Research and development of new products; Research and development of computer software; Hosting web sites; Testing, authentication and quality control; Design services; Scientific technological services; Hosting of memory space on the Internet for storing digital photographs; Hosting a website for the electronic storage of digital photographs and videos; Editing of computer programs; Design of instruments; Packaging design; Website design; Software engineering; Computer software design; Cloud computing; Computer hardware development; Rental of computer hardware and facilities; IT security, protection and restoration; Computer system analysis; Computer analysis; Design services relating to the development of computerised information processing systems; Computer network design for others; Computer specification design; Computer system design; Design services for data processing systems; Database design and development; Design and development of computer hardware and software; Design and development of networks; Preparation of computer programs for data processing; Comparative analysis studies of the performance of computer systems; Evaluation of performance of computer systems against bench-mark references; Evaluation of performance of data-processing against bench-mark references; Updating websites for others; Rental and maintenance of computer software; Rental of computer hardware and computer software; Computer rental and updating of computer software; Rental of computers and computer software; Integration of computer systems and networks; Computer project management services; Comparative analysis studies of the efficiency of computer systems; Development of systems for the processing of data; Development of systems for the storage of data; Development of systems for the transmission of data; Development of computer systems; Development of computer based networks; Research relating to computers; Computer graphics design services; Computer systems integration services; Design services relating to data processing test tools; Design services relating to data processing tools; Design services relating to data processors; Design services relating to data transmission test tools; Design services relating to the creation of networks; Design services relating to computer hardware and to computer programmes; Computer design and programming services; Computer design services; Computer network configuration services; Computer diagnostic services; Troubleshooting of computer hardware and software problems; Updating of memory banks of computer systems; Computer network services; Digital watermarking; Technological services relating to computers; Platform as a Service [PaaS]; computer security threat analysis for protecting data; Development of technologies for the protection of electronic networks; Data encryption and decoding services; Data decryption services; Data encryption services; Quality checking and testing; Providing quality assurance services; Conducting of quality control tests.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
software for the storage, sharing, access, backup, recovery, management, organization, tracking, research of data, files and documents; Software applications; Games software; Software; Packaged software; Software compiler; Programming software; Operating software; Education software; Graphics software; Communication software; Software drivers; Collaboration software; Community software; Antimalware software; Security software; Workflow software; Multimedia software; Utility software; Media software; Privacy software; Debugging software; Platform software; Mobile software; Editing software; Telecommunications software; Adaptive software; Training software; Interactive software; Authentication software; Server software; Map software; Plugin software; AI software; Payment software; Optimisation software; Publishing software; Presentation software; Navigation software; Business software; Collaborative software; Networking software; Social software; Banking software; Retail software; Reference software; Reporting software; Collaboration software platforms [software]; Embedded software; Enterprise software; Gambling software; Application software; Logistics software; Computer software; Computer telephony software; Desktop publishing software; E-commerce software; Software development programmes; Downloadable application software; Data communications software; Data processing software; Downloadable computer software; Search engine software; Database management software; Website development software; Music-composition software; Computer firewall software; Mobile application software; Augmented reality software; Voice recognition software; Software for televisions; Speech recognition software; Facial recognition software; File management software; Speech analytics software; Image recognition software; File synchronization software; Business technology software; Parental control software; Virtual classroom software; File sharing software; Printer spooler software; Vehicle control software; Machine learning software; Web application software; Instant messaging software; Cloud computing software; Business management software; Character recognition software; Artificial intelligence software; Data mining software; Day trading software; Content control software; Information retrieval software; Digital dashboard software; Video conference software; Content management software; Reservation systems software; Risk detection software; Health monitoring software; Environmental monitoring software; Cloud server software; Database synchronization software; Downloadable translation software; Smart home software; File server software; Media server software; Database server software; Online payment software; Interactive database software; Industrial automation software; Building management software; Software for smartphones; Computer application software; Casino management software; Software for card readers; Computer operating system software; Computer software for education; Computer software for advertising; Software for tablet computers; Vehicle control assistance software; Cloud network monitoring software; Media and publishing software; Software for product development; Downloadable cloud computing software; Software for Smart Contracts; Application software for robot; Satellite imagery photo-interpretation software; Software for use in advertising; Computer software for business purposes; Application software for smart TV; Computer-aided design (CAD) software; Customer relation management [CRM] software; Virtual reality software for telecommunications; Digital solutions provider [DSP] software; Virtual and augmented reality software; Utility, security and cryptography software; Web application and server software; Machine learning software for analysis; Artificial intelligence software for vehicles; Artificial intelligence software for surveillance; Artificial intelligence software for healthcare; Machine learning software for surveillance; Intrusion detection system [IDS] software; VPN [virtual private network] operating software; Computer software supplied on the Internet; Computer software to automate data warehousing; Application software for cloud computing services; Data processing software for word processing; Virtual reality software for medical teaching; E-commerce and e-payment software; Artificial intelligence and machine learning software; Communication, networking and social networking software; Computer software for tracking driver behaviour; Computer chatbot software for simulating conversations; Software for processing images, graphics and text; Interactive software based on artificial intelligence; Computer software for scanning images and documents; Computer software for authorising access to databases; Computer software for processing digital music files; Software for designing online advertising on websites; System and system support software, and firmware; Data and file management and database software; Computer software for the control of lighting; Computer screen saver software, recorded or downloadable; Computer software for use in remote meter reading; Computer software for use in computer access control; Computer software in the field of electronic publishing; Computer software for the compilation of positioning data; Software to control and improve audio equipment sound quality; Software for searching and retrieving information across a computer network; Computer software for creating searchable databases of information and data; Downloadable software for remotely accessing and controlling a computer; Software for monitoring, analysing, controlling and running physical world operations; Computer software adapted for use in the operation of computers; Recorded computer programmes; Computer programmes stored in digital form; Plug-in connectors; Document management software; Data management software; Workflow management system software; Big data management software; Downloadable digital music files authenticated by non-fungible tokens [NFTs]; Downloadable image files; Downloadable music files; Downloadable video files; Recorded data files; Downloadable multimedia files; Self-synchronizing digital encryptors; Navigation, guidance, tracking, targeting and map making devices; Collaboration tools [software]; Project management software; Databases; Data networks; Data carriers; Data transmission apparatus; Data transmitting apparatus; Electronic databases; Computer databases; Interactive databases; Electronic data carriers; Data processing programs; Data communications hardware; Data storage programs; Electronic data processing equipment; Data storage devices and media; Computer networking and data communications equipment; Electronic databases recorded on computer media; Electrical and electronic instruments for storing data; Computer software to enable searching of data; Computer software to enable retrieval of data; Data processing equipment and accessories (electrical and mechanical); Downloadable software applications; Downloadable software; Computer software platforms for social networking; Computer software for entertainment; Testware. Data management; Business project management services; Data searches in computerised files for others; Data search in computer files for others; Retail services in relation to downloadable music files; Computerized management of medical records and files; Retail services relating to downloadable digital image files authenticated by non-fungible tokens [NFTs]; Business project management; Maintaining personal medical history records and files; Data transcription; Database management; Database marketing; Computerised data verification; Data entry and data processing; Electronic data processing; Collection of data; Compilation of data; Data processing management; Transcription of data; Provision of business data; Computer database management services; Data processing, systematisation and management; Subscriptions to telecommunications database services; Administrative support and data processing services; Office services for electronically manipulating data; Business data research; Business management; Computerized file management; Systemization of information into computer databases; Collection and systematisation of information into computer databases; Advice relating to marketing management; Analysis of business management systems; Advice and information concerning commercial business management; Business management and organization consultancy; Advertising; Direct marketing; Market research; Assistance and advice regarding business organisation and management; Data processing verification; Computerised data processing; Data processing for the collection of data for business purposes; Data processing for businesses; Automated data processing; Online data processing services; Data processing; Computerised business information processing services; Data management services; Advisory services relating to electronic data processing; Advisory services relating to data processing; Business consultancy services relating to data processing; Information services relating to data processing; Computerised business information retrieval; Management and compilation of computerised databases; Compilation and systematisation of information in databanks; Compilation of information into computer databases; Consultancy relating to data processing; Business assistance, management and administrative services; Business analysis and information services, and market research; Collecting information for business; Compilation of computer databases; Compilation of statistical data for use in scientific research; Compilation of statistical data relating to medical research; Compilation of statistical data relating to business; Compilation of statistics [for business or commercial purposes]; Compilation of direct mailing lists; Compilation of business directories; Preparation of business statistical data; Data compilation for others; Compilation and systemization of information into computer databases; Drawing up of business statistical information; Consultancy relating to the preparation of business statistics; Records management services, namely, document indexing for others; Compilation of statistics; Computerised compilation of stock control records; Computerised compilation of order lists; Computerised compilation of customer indexes; Obtaining business statistics [for others]; Compilation of business statistics and commercial information; Compilation of business statistics; Business consultancy and advisory services; Administrative data processing. Platform as a service [PaaS] featuring software platforms for the storage, sharing, access, backup, recovery, management, organization, tracking, research of data, files and documents; Software creation; Software development; Software design; Computer software engineering; Computer software integration; Development of software; Software consulting services; Installation of software; Software maintenance services; Software design for others; Update of computer software; Computer software advisory services; Software as a service; Maintenance of computer software; Updating of software databases; Computer software programming services; Design of virtual reality software; Rental of software for computers; Services for updating computer software; Design of graphic software systems; Hosting services, software as a service, and rental of software; Software development, programming and implementation; Providing online, non-downloadable software; Software as a service [SaaS]; Software as a service [SAAS] services; Creation, maintenance and adaptation of software; Updating and design of computer software; Programming of software for inventory management; Programming of software for database management; Programming of software for Internet platforms; Design of online social networking software; Development of software for communication systems; Software as a service [SaaS] featuring computer software platforms for artificial intelligence; Software engineering services for data processing; Installation, maintenance and repair of computer software; Hosting of software for use in library management; Design and development of computer software for logistics; Design, maintenance, rental and updating of computer software; Providing temporary use of online non-downloadable software; Platforms for gaming as software as a service [SaaS]; Providing on-line non-downloadable software for database management; Design and development of software for importing and managing data; Design and development of computer software for supply chain management; Platforms for artificial intelligence as software as a service [SaaS]; Duplicating computer programmes; Consultancy in the field of security software; Remote computer backup services; Electronic data back-up; Electronic data storage and data back-up services; Providing back-up computer programs and facilities; Data back-up services; Hosting online web facilities for others for sharing online content; Providing temporary use of non-downloadable software to enable sharing of multimedia content and comments among users; Computer time sharing facilities (Provision of -); Cloud storage services for electronic files; Electronic storage of files and documents; Hosting of computerized data, files, applications and information; Providing temporary use of non-downloadable software to enable content providers to track multimedia content; Hosting software platforms for virtual reality-based work collaboration; IT project management; Electronic storage of archived e-mails; Electronic storage of documents and archived e-mails; Electronic storage services for archiving databases, images and other electronic data; Data mining; Data warehousing; Database design; Data recovery services; Data security services; Data migration services; Online data storage; Data security consultancy; Electronic data storage; Data duplication and conversion services, data coding services; Recovery of computer data; Data storage via blockchain; Data authentication via blockchain; Electronic data back-up services; Rental of database management software; Rental of computer database software; Cloud-based data protection services; Maintenance of databases; Reconstitution of databases; Hosting of databases; Data security services [firewalls]; Electronic storage of data; Engineering services relating to data processing technology; IT consultancy, advisory and information services; IT services; IT services for data protection; Computer programming for others; Electronic storage of audio files; Platform as a service [PaaS] featuring software platforms for transmission of images, audio-visual content, video content and messages; Development of hardware for audio and video operators; Design of software for audio and video operators; Product development for others; Providing temporary use of on-line non-downloadable software for the management of information; Providing temporary use of on-line non-downloadable software for the management of data; Development of computer software for logistics, supply chain management and e-business portals; Updating of computer software for others; Providing technical advice relating to computer hardware and software; Providing temporary use of non-downloadable business software; Programming of software for e-commerce platforms; Design of computer machine and computer software for commercial analysis and reporting; Providing temporary use of non-downloadable software for analyzing financial data and generating reports; Rental of computer software for collecting, analyzing and organizing data in the field of deep learning; Providing temporary use of online non-downloadable computer software for collecting, analyzing and organizing data in the field of deep learning; Hosting platforms on the Internet; Engineering project management services; Enterprise content management; Rental of a database server (to third parties); Installation, maintenance and updating of database software; Consultancy relating to computer database programs; Providing online non-downloadable computer software; Providing temporary use of on-line non-downloadable operating software for accessing and using a cloud computing network; Artificial intelligence consultancy; Providing artificial intelligence computer programs on data networks; Design of information systems relating to management; Product research; Technical research; Computer software research; Computer research services; Product research and development; Research into new products; Research relating to data processing; Technical research projects and studies; Research relating to computer programs; Research relating to computer programming; Research and development of new products; Research and development of computer software; Hosting web sites; Testing, authentication and quality control; Design services; Scientific technological services; Hosting of memory space on the Internet for storing digital photographs; Hosting a website for the electronic storage of digital photographs and videos; Editing of computer programs; Design of instruments; Packaging design; Website design; Software engineering; Computer software design; Cloud computing; Computer hardware development; Rental of computer hardware and facilities; IT security, protection and restoration; Computer system analysis; Computer analysis; Design services relating to the development of computerised information processing systems; Computer network design for others; Computer specification design; Computer system design; Design services for data processing systems; Database design and development; Design and development of computer hardware and software; Design and development of networks; Preparation of computer programs for data processing; Comparative analysis studies of the performance of computer systems; Evaluation of performance of computer systems against bench-mark references; Evaluation of performance of data-processing against bench-mark references; Updating websites for others; Rental and maintenance of computer software; Rental of computer hardware and computer software; Computer rental and updating of computer software; Rental of computers and computer software; Integration of computer systems and networks; Computer project management services; Comparative analysis studies of the efficiency of computer systems; Development of systems for the processing of data; Development of systems for the storage of data; Development of systems for the transmission of data; Development of computer systems; Development of computer based networks; Research relating to computers; Computer graphics design services; Computer systems integration services; Design services relating to data processing test tools; Design services relating to data processing tools; Design services relating to data processors; Design services relating to data transmission test tools; Design services relating to the creation of networks; Design services relating to computer hardware and to computer programmes; Computer design and programming services; Computer design services; Computer network configuration services; Computer diagnostic services; Troubleshooting of computer hardware and software problems; Updating of memory banks of computer systems; Computer network services; Digital watermarking; Technological services relating to computers; Platform as a Service [PaaS]; computer security threat analysis for protecting data; Development of technologies for the protection of electronic networks; Data encryption and decoding services; Data decryption services; Data encryption services; Quality checking and testing; Providing quality assurance services; Conducting of quality control tests.
90.
Generating and providing synthesized tasks presented in a consolidated graphical user interface
The present disclosure relates to systems, non-transitory computer-readable media, and methods for collecting, organizing, and managing third-party content from multiple sources associated with a user account to present as synthesized tasks in a consolidated graphical user interface and minimize the distraction provided by multiple interfaces. In particular, in one or more embodiments, the disclosed systems analyze content from various web-based data sources, collect relevant content, create synthesized tasks associated with the relevant content, and present the relevant content to the user grouped into synthesized tasks in a single graphical user interface. Additionally, the disclosed systems can prioritize the generated synthesized tasks within the graphical user interface and provide productivity metrics based on the degree to which an associated user interacts with the synthesized tasks.
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 9/451 - Execution arrangements for user interfaces
G06F 9/48 - Program initiatingProgram switching, e.g. by interrupt
The present disclosure relates to systems, non-transitory computer-readable media, and methods for controlling editing permissions associated with individual user accounts for collaborative documents without affecting the editing permissions associated with additional user accounts using a straightforward and concise presentation. For instance, the disclosed systems provide uncomplicated options for presentation on a client device, which provide account-based control of the editing permissions associated with a user account for collaborative digital content items while maintaining the existing editing permissions associated with additional user accounts for the collaborative content items. In particular, the disclosed systems can identify a collaborative content item associated with a user account, determine editing permissions associated with the user account, provide an option to modify the editing permissions associated with the user account, and modify the editing permissions associated with the user account all without affecting the editing permissions associated with other accounts.
The present disclosure is directed toward systems and methods to quickly and accurately identify boundaries of a displayed document in a live camera image feed, and provide a document boundary indicator within the live camera image feed. For example, systems and methods described herein utilize different display document detection processes in parallel to generate and provide a document boundary indicator that accurately corresponds with a displayed document within a live camera image feed. Thus, a user of the mobile computing device can easily see whether the document identification system has correctly identified the displayed document within the camera viewfinder feed.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 20/40 - ScenesScene-specific elements in video content
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and managing multilocational data blocks, generating and summarizing content blocks within a virtual space interface, and generating and providing a content block browser as part of a virtual space platform. In some embodiments, the disclosed systems generate a multilocational data block that includes a block identifier that is tied to a source identifier for embedding digital content from a network location indicated by the source identifier. The disclosed systems can also generate block summaries from content blocks for presenting and modifying digital content embedded within the content blocks via block identifiers and source identifiers. In some embodiments, the content block system can provide a content-block-based web browser in the form of a virtual space that includes embedded content blocks that integrate webpage functionality.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and managing multilocational data blocks, generating and summarizing content blocks within a virtual space interface, and generating and providing a content block browser as part of a virtual space platform. In some embodiments, the disclosed systems generate a multilocational data block that includes a block identifier that is tied to a source identifier for embedding digital content from a network location indicated by the source identifier. The disclosed systems can also generate block summaries from content blocks for presenting and modifying digital content embedded within the content blocks via block identifiers and source identifiers. In some embodiments, the content block system can provide a content-block-based web browser in the form of a virtual space that includes embedded content blocks that integrate webpage functionality.
The disclosed technology addresses the need in the art for a content management system that can be highly flexible to the needs of its subjects. The present technology permits any object to be shared by providing a robust and flexible access control list mechanism. The present technology utilizes a data structure that is highly efficient that both minimizes the amount of information that needs to be written into any database, but also allows for fast reads and writes of information from authoritative tables that are a source of truth for the content management system, while allowing for maintenance of indexes containing more refined data that allow for efficient retrieval of certain information that would normally need to be calculated when it is needed.
G06F 16/21 - Design, administration or maintenance of databases
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
96.
INTELLIGENTLY IDENTIFYING AND PRESENTING DIGITAL DOCUMENTS
One or more embodiments of a document organization system quickly and conveniently provide digital documents to a user on a client device based on a physical object. In particular, the document organization system can receive an image of a physical document and an identifier from a first client device, identify digital documents that match the physical document, and provide the matching digital documents to a second client device, which displays the identifier. In another embodiment, the document organization system allows a user to bind digital documents to a physical object and later recall the digital documents using the physical object. In addition, the document organization system can store and recall the layout arrangement of digital documents on a client device when binding and recalling the digital documents to the physical object.
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.
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 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/9535 - Search customisation based on user profiles and personalisation
99.
Generating and summarizing content blocks within a virtual space interface
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and managing multilocational data blocks, generating and summarizing content blocks within a virtual space interface, and generating and providing a content block browser as part of a virtual space platform. In some embodiments, the disclosed systems generate a multilocational data block that includes a block identifier that is tied to a source identifier for embedding digital content from a network location indicated by the source identifier. The disclosed systems can also generate block summaries from content blocks for presenting and modifying digital content embedded within the content blocks via block identifiers and source identifiers. In some embodiments, the content block system can provide a content-block-based web browser in the form of a virtual space that includes embedded content blocks that integrate webpage functionality.
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and managing multilocational data blocks, generating and summarizing content blocks within a virtual space interface, and generating and providing a content block browser as part of a virtual space platform. In some embodiments, the disclosed systems generate a multilocational data block that includes a block identifier that is tied to a source identifier for embedding digital content from a network location indicated by the source identifier. The disclosed systems can also generate block summaries from content blocks for presenting and modifying digital content embedded within the content blocks via block identifiers and source identifiers. In some embodiments, the content block system can provide a content-block-based web browser in the form of a virtual space that includes embedded content blocks that integrate webpage functionality.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
G06F 3/06 - Digital input from, or digital output to, record carriers
G06Q 10/101 - Collaborative creation, e.g. joint development of products or services
