475 results about "Content creation" patented technology

A behavioral authorship verification system captures and analyzes multi-modal behavioral patterns during content creation to authenticate human authorship. The system comprises a processor executing behavioral analysis modules that generate comprehensive behavioral fingerprints distinguishing genuine human authors from AI-generated content and impostor authorship. A sentence progression mapping module detects sentence boundaries and captures intermediate composition states including additions, deletions, and modifications. A multi-modal input analysis module monitors keystroke dynamics including flight time and dwell time while detecting paste events and input method transitions. A behavioral pattern recognition engine generates user-specific baselines from historical sessions and computes deviation scores using statistical distance metrics. An anomaly correlation module aggregates behavioral deviation signals using weighted fusion algorithms to detect sophisticated mimicry attempts. An authorship scoring engine synthesizes outputs into unified confidence scores while maintaining temporal authorship chains. The system enables real-time authorship verification during content creation rather than post-hoc analysis.

An AI-powered content generation system that creates consistent, coherent, and engaging multi-modal content by integrating multiple specialized AI components. The system analyzes user input, identifies key elements, and maintains continuity throughout the generation process. It incorporates a feedback loop to learn and adapt based on user preferences, enabling personalized content experiences. The modular architecture allows for seamless integration of AI components focusing on text, images, audio, and interactive elements. The system ensures consistency across modalities and over extended periods, while managing rights, licenses, and royalties using blockchain technology. This advanced platform revolutionizes content creation, consumption, and management in the digital age.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a generative interface panel having multiple automated assistant services. Each assistant service may access a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Systems and methods are described for providing for display a user interface to facilitate creation of a three-dimensional (3D) environment. The disclosed techniques may generate the 3D environment based on one or more inputs received via the user interface, and perform visual processing of the 3D environment to obtain a natural language description of the 3D environment. The disclosed techniques may determine a context of the 3D environment based at least in part on the natural language description and may store the context in a data structure. A 3D content library may be queried, based on the natural language description of the 3D environment, to identify at least one recommended 3D object that is relevant to the stored context of the 3D environment. The disclosed techniques may providing for display, at the user interface, selectable option(s) to add the at least one recommended 3D object to the 3D environment.

Technology is disclosed herein for personalized writing assistance via an LLM integration in a software application. In an implementation, a computing device identifies user-specific preferences for content creation. The computing device submits a prompt to an LLM that includes selected content associated with a user and the user-specific preferences, along with a request for the LLM to suggest an intent to modify the selected content in view of the user-specific preferences. The computing device receives a reply from the LLM including the intent to modify the selected content. When the user accepts the suggestion, the computing device generates and submits a second prompt to the LLM including a request for the LLM to modify the selected content according to the intent. The computing device receives a reply from the LLM including a modified version of the selected content and displays the modified version of the selected content.

The invention belongs to the technical field of digital content security, and discloses a multi-mode AI content security risk traceability and identification detection system. Through obtaining multi-source heterogeneous data of content creation, editing, distribution and presentation of a full link, a content full link feature fingerprint is constructed, and cross-modal consistency analysis and link continuity verification are realized. According to the method, traceability map construction is introduced, potential tampering points are used as map nodes, content risks are quantified through tampering probability weights and risk transfer intensity, and tampering sources and propagation paths are accurately identified. The method has comprehensiveness and accuracy, deep analysis and risk assessment can be carried out on the multi-modal content, and the tampered content is effectively recognized and synthesized.

The invention discloses a content creation and multi-mode display platform based on AIGC. The system comprises six modules of user interaction, content creation intelligent collaboration, AIGC auxiliary creation, data management, multi-modal deep fusion display and user feedback. The user interaction module supports various inputs and provides a creation template; the content creation intelligent collaboration module analyzes the intention and intelligently distributes tasks; the AIGC auxiliary creation module provides multi-mode creation assistance; the data management module stores various data; the multi-modal deep fusion display module is used for mining modal connection to realize deep fusion display; and the user feedback module collects and feeds back optimization contents and algorithms. Through cooperative work of the modules, the problems that an existing platform is difficult in creation cooperation, single in content generation, insufficient in multi-mode display and the like are effectively solved, creation efficiency and content quality are improved, immersive experience is brought to users, and innovative development of the field of content creation and display is promoted.

An AI-based system generates personalized educational content tailored to individual students' abilities and needs. The platform analyzes academic standards, curriculum guidelines, and student data including IEP status using natural language processing to build customized profiles. Large language models (LLMs) including GPTs, BERT, and custom models as well as generative adversarial networks (GANs), diffusion models, and other AI algorithms are leveraged to dynamically generate lessons, assignments, recommendations, visual aids, and other educational content adapted for each learner. The system stores output in JSON format for further transformation. Educators can review auto-generated content, provide guiding prompts, and collaborate via social features. Administrative controls enable customization across districts and schools. By leveraging AI to automate personalized content creation, the system reduces teacher workload while improving educational outcomes.

Building on U.S. Provisional Patent Application No. 63 / 693,803, paragraphs for 2D-to-3D conversion and [0023]-[0024] for secure content verification, the Matrix 3D AI Polygon Mesh Hash Key System revolutionizes transforming 2D content into secure, interactive 3D AR / VR assets. Integrating AI and LiDAR, it enables real-time 3D mesh generation with precise geospatial anchoring. Users can reshape 3D content instantly via natural language commands, enhancing interactivity. Quantum-resistant encryption, using AES-256 and CRYSTALS-Kyber, ensures robust asset security. The system excels in gaming, surveillance, content verification, military operations, space exploration, deepfake detection, and pharmaceutical research, offering unmatched precision and scalability. Its multi-stage rendering pipeline, powered by distributed AI-driven bots, supports efficient real-time 3D mesh generation, achieving 95% accuracy and 1 cm resolution. This AR / VR technology advancement transforms industries with scalable, secure solutions for interactive 3D content creation and management, setting a new standard for precision and versatility.

The invention relates to a new media AI marketing content creation method and device, equipment and a medium. The method comprises the steps of obtaining user demand configuration, and obtaining a creation intention vector through natural language analysis; based on the platform characteristic knowledge base, extracting a corresponding structure specification and a propagation mechanism according to the target platform, and encoding to obtain a platform characteristic vector; obtaining historical content interaction data corresponding to the audience group, and generating a user-content interaction vector by adopting collaborative filtering and a label similarity algorithm in combination with the content keyword; and calling an artificial intelligence large model, and performing content generation according to the creation intention vector, the platform feature vector and the user-content interaction vector to obtain content creation data. By adopting the method, the goal of automatic, high-quality and personalized new media marketing content creation in a multi-platform environment can be realized by means of natural language analysis, knowledge structure extraction, large model generation constraint and the like.

The invention discloses a new media content creation and distribution platform, and the platform comprises a user portrait construction module which is used for collecting user behavior data and generating a multi-dimensional interest label; the multi-modal content generation module supports automatic generation and editing of texts, images, audios and videos; an advanced algorithm is integrated through a multi-modal content generation module, intelligent collaborative production of texts, images, audios and videos is achieved, creation efficiency is improved, title variant generation and style imitation are supported, and the manual creative bottleneck is broken through; the intelligent distribution engine adopts reinforcement learning to dynamically optimize weight distribution and combines a platform feature analyzer and an A / B test unit to improve cross-platform distribution accuracy and traffic conversion rate; the block chain evidence storage and cross-platform crawler system constructs a full-link copyright protection network, so that content fingerprints can be quickly chained, infringement contents can be automatically released, and the right protection efficiency is improved; and the virtual digital human driving module and the multi-mode conversion unit extend the content adaptability, so that the immersion of the user is enhanced.

The invention provides an automatic SEO setting system and method in a station building CMS, and belongs to the technical field of station building CMS. According to the method, the AI technology is utilized, the keywords are deeply mined and screened, the keywords with high conversion potential and the long tail keywords are accurately recognized, the real demands of users are insighted, the competition situation of the keywords is intelligently evaluated, and the popularity change is predicted. In the aspect of content creation, a content outline, a first draft and a specific paragraph can be generated according to a target keyword and a user portrait, optimization suggestions can be provided in the aspects of readability, keyword layout and the like, and content personalized recommendation is achieved. Compared with a traditional SEO technology, the method has the advantages that the keyword screening efficiency and the long tail keyword coverage rate are improved, the matching degree of content and user requirements is optimized, ranking and flow of websites in a search engine are improved, and the method is efficient and accurate.

The invention discloses a method and equipment for constructing a multi-role cooperative processing task based on a large language model. The method comprises the steps that the identity of a large language model is endowed to be a universal role agent, the universal role agent creates a plurality of task role agents based on the content of a task instruction, and the identities of the task role agents are different; updating the identity of the large language model as a task splitting agent, splitting the task into a plurality of sub-tasks by the task splitting agent based on the obtained identity of each task role agent, and allocating the plurality of sub-tasks to the corresponding task role agents; each task role agent executes the corresponding sub-task to obtain a sub-task result and submits each sub-task result; and updating the identity of the large language model as a task result summarization agent, and summarizing each subtask result by the task result summarization agent to obtain an execution result corresponding to the task. By means of the mode, multi-role cooperative task processing can be achieved, and the execution quality and the execution efficiency are improved.

The invention discloses a social blog management system and method based on Vue and SpringBoot, belongs to the technical field of social networks, and solves the problems that an existing system only focuses on user information collection, activity registration and basic data storage and cannot meet the complex requirements of a blog platform for content creation, personalized recommendation and multi-dimensional social interaction, and the social blog management efficiency is improved. The system comprises a front-end module, a rear-end module and a database module, and the front-end module and the rear-end module carry out data interaction through AJAX and RESTful API (Application Program Interface); according to the system, a front-end and back-end separation framework of Vue.js and SpringBoot is adopted, and a relational database MySQL, a memory database Redis and OSS storage are combined, so that efficient storage and cache management of data are realized, the system performance is optimized, a back-end module can generate personalized recommendation information by analyzing user blog information, the user experience is improved, and the user experience is improved. Rich user management and social contact functions are provided, and interaction between users is enhanced.

The invention discloses an application development method, an application development device and XR equipment, and relates to the technical field of augmented reality, and the method comprises the steps: receiving a preset XR scene component dragged by a user to an XR scene template through a visual editor; in response to a user request, calling an AIGC model to generate an XR content material, and inserting the XR content material into a specified position of a current XR scene; and receiving the configuration of the user on the interaction logic, converting the current XR scene and the interaction logic into an executable format of the target XR glasses through the adaptation layer, and outputting an application package adaptive to the target XR glasses. Visual development and AIGC automatic content generation are combined, so that the XR content creation threshold is reduced, the development efficiency is improved, and diversified application scenes are supported.

Aspects of the disclosed technology include machine-learning systems and methods for generating user interface elements that allow user control over generative content creation by machine-learned generative models. A generative user interface (UI) system is configured to generate, as output of one or more machine-learned sequence processing models, computer-executable functional code to process a user query in association with a content item. The system is configured to generate computer-executable interface code for a user interface that includes a user interface element associated with at least one parameter of the computer-executable functional code for modifying the content item. The system is configured to determine data for the at least one parameter of the computer-executable functional code based at least in part on a user input to the user interface element and generate a modified content item using the computer-executable functional code and the data for the at least one parameter.

The invention relates to the field of artificial intelligence, financial science and technology and digital medical treatment, and discloses an image-based video generation method and device, equipment and a storage medium. The method comprises the following steps: receiving and preprocessing an input static image to generate a multi-scale feature; based on the multi-scale features, determining an optimal space-time processing path through differentiable search of a space-time architecture generator, and generating output features fused with time sequence dynamic information; generating a video frame based on the time sequence recurrent neural network and the output features; and inputting the video frames into the video frame sequence, and generating a target video through the video frame sequence. According to the method, the optimal space-time processing path can be automatically determined through differential search, manual intervention is avoided, the time sequence coherence and detail authenticity of the video are ensured by dynamically generating the output characteristics of the fusion time sequence information and generating the video, the video generation quality and efficiency are improved, and the video quality is improved. The method is suitable for high-precision video generation such as video synthesis, content creation and virtual reality in the fields of finance and medical treatment.

A method for generating a résumé may receive at least an experience parameter and a job title parameter. Related job titles in a historical résumé dataset may be selected that are semantically related to the job title parameter by using a semantically similar job title selector. The historical résumé dataset may be filtered based on at least the experience parameter and the related job titles to obtain a filtered résumé dataset. A list of user skills may be obtained by selecting skills from the filtered résumé dataset. A list of curated skills may be obtained by selecting curated skills from a curated skills dataset based on at least the experience parameter and the one or more related job titles. A list of candidate skills may be obtained by mapping skills from the list of user skills to corresponding curated skills. Selected candidate skills may be incorporated into a résumé.

A method for automating roadmap software content creation is provided. The method may include gathering data, by at least one processor, from one or more data sources; filtering, by the at least one processor, the data based on a predetermined criteria to identify one or more requests to update a software application being unsupported by an external cloud environment; and creating content automatically for a roadmap software tool, based on the one or more requests, by using a content generating workflow software tool.

New and improved interfaces for the live streaming of content by a content creator are provided. In a preferred embodiment the interface comprises a first area for displaying a live streaming video; a second area for displaying a live chat simultaneously with the live streaming video and a third area for displaying a plurality of advertisement opportunities simultaneously with the live streaming video and the live chat wherein each advertisement opportunity in the plurality of advertisement opportunities includes a script that can be read by the content creator during the live streaming video.

An authentication system for verifying creation of digital content includes a machine learning classifier configured to analyze data points related to a content creation process, a programmatic rules-based analysis component configured to apply predefined criteria to the data points, and a human-viewable replay component configured to provide a visual representation of the content creation process. The authentication system is configured to determine whether the digital content was created by a human or generated by artificial intelligence (AI) based on outputs from the machine learning classifier, the programmatic rules-based analysis component, and the human-viewable replay component. The data points may include keystroke dynamics, syntax and style analysis, error patterns and corrections, content revision history, behavioral data, content creation timeline, gestures and touch interactions, brushstrokes and drawing patterns, voice and audio analysis, physical interaction with devices, eye tracking and gaze patterns, and biometric data.

The invention provides a music generation method, a music generation device, electronic equipment and a storage medium, and the music generation method comprises the steps: after receiving a music generation instruction, generating an accompaniment audio and a singing audio according to the music generation instruction, carrying out the audio synthesis of the accompaniment audio and the singing audio, and generating and outputting target music. Therefore, when the method is applied to the vehicle intelligent cabin scene, the accompaniment audio and the singing audio are respectively generated by adopting an artificial intelligence technology, and the accompaniment audio and the singing audio are synthesized to obtain the target music, so that the adaptation degree of the accompaniment audio and the singing audio in music content creation can be effectively improved; the accompaniment audio and the singing audio are closely fused in multiple dimensions such as rhythm, tone and emotional expression, so that the user experience is greatly improved.

The present disclosure relates to the technical field of multimedia, and relates to a generation method and apparatus for interactive multimedia content, and a computer-readable storage medium. The generation method for interactive multimedia content comprises: receiving content input by a user; displaying one or more plot nodes and a logic relationship between the one or more plot nodes, wherein the one or more plot nodes and the logic relationship are generated on the basis of a processing result of a first generation model in respect of the content input by the user; displaying plot content of at least one plot node, wherein the plot content is generated on the basis of a processing result of the first generation model in respect of the one or more plot nodes and the logic relationship; and using the plot content of the one or more plot nodes to create interactive multimedia content.

A method employs a simulation-driven environment for Al model training in filmmaking, using virtual scenes, filmmaking metadata, and Lidar data to enhance video generation capabilities. A system includes processors and memory to generate virtual scenes, integrate Lidar data with filmmaking metadata, and train Al models for improved video content creation. A computer-readable medium contains instructions for generating virtual scenes, integrating Lidar data and filmmaking metadata, and training Al models to enhance video content generation without constant new real-world data.

The invention discloses a holographic content editing method and device based on multi-modal semantics, equipment and a storage medium, and relates to the technical field of communication, and the method comprises the steps: obtaining and processing multi-modal culture content and real environment information inputted by a user; and generating unified and optimized target semantic features by using a dynamic semantic weighting strategy and a semantic alignment comparison method. The holographic content is generated in combination with the condition fusion generation model, the structure perception graph neural network is fused with the real environment, and finally personalized editing optimization is performed according to a user instruction, so that the semantic consistency, editing efficiency and fusion suitability of holographic content creation are improved.

A data processing system implements receiving, from a sender device, a request to personalize and distribute a design content item based on content consumption needs and / or preferences of recipients, wherein the content consumption needs and / or preferences include a data type; constructing a prompt by appending the design content item and the content consumption needs and / or preferences to an instruction string, the instruction string including instructions to a generative model to transform per recipient the design content item into a personalized content item based at least one of a content consumption need or a content consumption preference of a respective recipient; providing as an input the prompt to the generative model and receiving as an output the personalized content item from the generative model; providing the personalized content item to a recipient device; and causing a user interface of the recipient device to render the personalized content item.

The invention belongs to the technical field of content creation, and particularly relates to a full-habitat content intelligent operation ecosystem, which comprises a user layer, an application layer, a data layer and a technical layer, and is characterized in that the user layer comprises a creator used for providing creation tools and resources for the content creator to perform content creation and issuing works on a platform; the enterprise user is used for enabling an enterprise with content marketing and brand promotion requirements to customize exclusive content through the platform, manage content marketing activities and cooperate with a creator; and the common user is used for enabling a consumer of the content to browse, read and watch various contents on the platform, and can interact with a creator and other users in the modes of liking, commenting and sharing. According to the method, four goals of improving creation efficiency, realizing personalized customization, promoting diversified innovation and optimizing distribution and propagation are clearly set, key links of a content creation ecosystem are comprehensively covered, and the development direction and core appeals are clarified.

To create a report for a funder with appropriate contents, where social impact caused by a project conducted by a fund provision object person having received the fund provision from the funder is visualized.SOLUTION: A social impact presentation system includes: an impact-related information acquisition unit 11 which acquires impact-related information contributing to visualization of social impact which is caused by a project conducted by a fund provision object person; an investor attribute acquisition unit 21 which acquires investor attribute which is attribute information of an investor, from an investor terminal 10'; a report creation unit 15 which creates a report including contents specified according to the investor attribute, by using the acquired impact-related information; and a report presentation unit 16 which presents the created report to the investor terminal 10'. The social impact presentation system is configured to create a report for the investor where the social impact is visualized with appropriate contents, by creating a report with contents according to the investor attribute.SELECTED DRAWING: Figure 8

The invention discloses a dynamic intelligent multi-module real-time content recommendation system based on multi-channel behavior data. The dynamic intelligent multi-module real-time content recommendation system comprises a basic tool module, a creation tool module, a content stream module, a creation agent module, a multi-channel data acquisition and analysis system and a cross-module dynamic linkage recommendation module. The method can accurately predict user demands and actively position related contents, greatly reduces user browsing and searching time, improves first screen content matching degree, improves content acquisition efficiency, can trigger and dynamically adjust content display strategies and function arrangement sequences of functional modules according to user behaviors, breaks barriers among the modules, and improves user experience. According to the method, intelligent linkage among multiple modules is achieved, more personalized creation experience is provided for a user, the core problems of content homogenization, module isolation and poor user experience of a current AI content creation platform can be effectively solved, and a dynamic intelligent multi-module real-time content recommendation system based on multi-channel behavior data is provided for the user.

The invention relates to the technical field of shopping services, in particular to a user contribution-based donation rebate method and a layered cash rebate system. According to the technical scheme, encryption collection points are arranged at multiple positions of an e-commerce platform by using a block chain technology, and multi-source data such as user purchase, social recommendation and content creation are collected and safely stored. And performing deep analysis on the data by using an artificial intelligence algorithm, and performing intelligent layering according to a user contribution evaluation model. And formulating differentiated buying and commission rebating strategies according to user levels, and dynamically adjusting in combination with factors such as markets and the like. And when the user recommends that the new user succeeds in purchasing, the system carries out real-time commission rebate and issues gifts based on the block chain smart contract. And data are collected and analyzed again according to a set period, the user hierarchy is dynamically updated, and a visual report is provided. Through multi-source data acquisition, intelligent layering, dynamic strategy making and the like, the data security is guaranteed, the user experience is improved, and the platform competitiveness and the intelligent level are enhanced.