12 results about "Derivative work" patented technology

A system may receive a request to transform predetermined music content using generative artificial intelligence, wherein the predetermined music content is protected by a copyright and is digitally controlled by a cloud-based authorization server. A system may receive a user request to create a derivative work using the generative artificial intelligence, wherein the request includes a prompt from the user to cause the generative artificial intelligence to create the derivative work as a function of the predetermined music content and a user specific theme for the derivative work. A system may model an owner of the copyright with an Al model and approve creation of the derivative work in response to the modeling predicting that the owner would approve the request. A system may create the derivative work using the generative artificial intelligence and may mark the work with a digital watermark for tracking use of the derivative work.

A system for generating derivative works comprises a content derivation platform with at least one processor configured to receive predetermined content and a request to transform it into a derivative work with a requested theme. The system uses generative artificial intelligence to create the derivative work comprising audio, video, or images based on the requested theme. A content approval machine learning model with a neural network determines an approval score based on content owner preferences and text embeddings identifying items in the derivative work. When the score exceeds a predetermined minimum, the system applies a digital watermark, configures an authorization server to govern use based on the digital watermark, and provides access to the approved derivative work. The requested theme may be determined through a chatbot interview using a Large Language Model. The generative artificial intelligence may comprise a diffusion model. The content may comprise music or audio.

A system for generating derivative works comprises a content derivation platform with at least one processor configured to receive predetermined content and a request to transform it into a derivative work with a requested theme. The system uses generative artificial intelligence to create the derivative work comprising audio, video, or images based on the requested theme. A content approval machine learning model with a neural network determines an approval score based on content owner preferences and text embeddings identifying items in the derivative work. When the score exceeds a predetermined minimum, the system applies a digital watermark, configures an authorization server to govern use based on the digital watermark, and provides access to the approved derivative work. The requested theme may be determined through a chatbot interview using a Large Language Model. The generative artificial intelligence may comprise a diffusion model. The content may comprise music or audio.

Herein disclosed is receiving predetermined content, receiving a request to transform the predetermined content into a derivative work, receiving a requested theme for the derivative work, using generative artificial intelligence to create the derivative work generated as a function of the predetermined content and the requested theme, determining if the generated derivative work is approved, in response to determining the generated derivative work is approved, applying a digital watermark to the approved derivative work, configuring an authorization server to govern use of the approved derivative work based on the digital watermark and providing user access to the authorized derivative work. The requested theme may be determined using a Large Language Model (LLM) and a chatbot interview. The generative artificial intelligence may comprise a diffusion model. The content may comprise music.

The application provides a copyright incentive protection method and system based on a directed acyclic graph and a decay model, and belongs to the technical field of blockchains. The method comprises the following steps: system initialization, defining participating nodes in a copyright incentive protection platform, including user nodes, platform verification nodes, incentive distribution nodes and audit nodes; defining a DAG graph for expressing a propagation relationship and a copyright node index database structure; according to original works and derivative works uploaded by user nodes, using a smart contract, calling the copyright node index database to perform on-chain transactions, updating index data and incentive record tables of the copyright node index database, and updating the DAG graph according to reference behaviors between works; defining an integral calculation rule for the nodes, adjusting calculation parameters according to a propagation index, adjusting the total value of author integrals, calculating incentive distribution in combination with a propagation path, realizing linkage between secondary creation benefits and original author contributions, ensuring that the original author obtains benefits in each derivative propagation, and realizing fair tracing and continuous benefit distribution.

Herein disclosed is receiving predetermined content, receiving a request to transform the predetermined content into a derivative work, receiving a requested theme for the derivative work, using generative artificial intelligence to create the derivative work generated as a function of the predetermined content and the requested theme, determining if the generated derivative work is approved, in response to determining the generated derivative work is approved, applying a digital watermark to the approved derivative work, configuring an authorization server to govern use of the approved derivative work based on the digital watermark and providing user access to the authorized derivative work. The requested theme may be determined using a Large Language Model (LLM) and a chatbot interview. The generative artificial intelligence may comprise a diffusion model. The content may comprise music.

A system may receive a request to transform predetermined music content using generative artificial intelligence, wherein the predetermined music content is protected by a copyright and is digitally controlled by a cloud-based authorization server. A system may receive a user request to create a derivative work using the generative artificial intelligence, wherein the request includes a prompt from the user to cause the generative artificial intelligence to create the derivative work as a function of the predetermined music content and a user specific theme for the derivative work. A system may model an owner of the copyright with an AI model and approve creation of the derivative work in response to the modeling predicting that the owner would approve the request. A system may create the derivative work using the generative artificial intelligence and may mark the work with a digital watermark for tracking use of the derivative work.

A system may receive a request to transform predetermined music content using generative artificial intelligence, wherein the predetermined music content is protected by a copyright and is digitally controlled by a cloud-based authorization server. A system may receive a user request to create a derivative work using the generative artificial intelligence, wherein the request includes a prompt from the user to cause the generative artificial intelligence to create the derivative work as a function of the predetermined music content and a user specific theme for the derivative work. A system may model an owner of the copyright with an AI model and approve creation of the derivative work in response to the modeling predicting that the owner would approve the request. A system may create the derivative work using the generative artificial intelligence and may mark the work with a digital watermark for tracking use of the derivative work.

Program instructions on a non-transitory computer-readable medium are executable by at least one processor to receive predetermined content, a request to transform the predetermined content into a derivative work, and one or more user-specified parameters. Generative artificial intelligence is used to generate the derivative work as a function of the predetermined content and the one or more user-specified parameters. The derivative work includes audio, video, or images. Based on a content approval machine learning model, a determination is made as to whether the derivative work is approved based on a content approval score. The content approval score is based on at least one content owner preference and the derivative work. In response to determining the content approval score exceeds a threshold, a digital watermark is applied to the derivative work, an authorization server is configured to govern use of the derivative work, and access to the derivative work is provided.

A system and method for creating AI-generated derivative works from predetermined content with copyright compliance and content owner control. In some aspects, the system receives predetermined content and a user-requested transformation theme, then employs generative artificial intelligence to create a derivative work. The system may enable scalable rights management for AI-generated content across music, video, text, and other media formats.

A system may receive a request to transform predetermined music content using generative artificial intelligence, wherein the predetermined music content is protected by a copyright and is digitally controlled by a cloud-based authorization server. A system may receive a user request to create a derivative work using the generative artificial intelligence, wherein the request includes a prompt from the user to cause the generative artificial intelligence to create the derivative work as a function of the predetermined music content and a user specific theme for the derivative work. A system may model an owner of the copyright with an Al model and approve creation of the derivative work in response to the modeling predicting that the owner would approve the request. A system may create the derivative work using the generative artificial intelligence and may mark the work with a digital watermark for tracking use of the derivative work.

Program instructions on a non-transitory computer-readable medium are executable by at least one processor to receive predetermined content, a request to transform the predetermined content into a derivative work, and one or more user-specified parameters. Generative artificial intelligence is used to generate the derivative work as a function of the predetermined content and the one or more user-specified parameters. The derivative work includes audio, video, or images. Based on a content approval machine learning model, a determination is made as to whether the derivative work is approved based on a content approval score. The content approval score is based on at least one content owner preference and the derivative work. In response to determining the content approval score exceeds a threshold, a digital watermark is applied to the derivative work, an authorization server is configured to govern use of the derivative work, and access to the derivative work is provided.