# US 11,907,705 B1 · Systems and methods for generating dynamically updated metadata using real-time artificial intelligence models > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,907,705 B1 - Document ID: US11907705B1 - Status: Granted - Kind: B1 - Application number: 18/494,291 - Filed: 2023-10-25 - Granted: 2024-02-20 - Earliest claimed: 2023-05-30 - Assignees: Winchester Global Trust Company Limited - Applicants: Winchester Global Trust Company Limited - Inventors: Fawad Zafar; Michael Joseph Karlin - Web page: https://patentgrep.com/patent/US11907705B1 ## CPC - G06Q 30/0185: {Product, service or business identity fraud} - G06F 8/65: Updates (security arrangements therefor G06F21/57) - G06Q 10/40: Business processes related to social networking or social networking services - G06Q 30/0201: Market modelling; Market analysis; Collecting market data - G06Q 30/0225: {Avoiding frauds} - G06Q 30/0248: {Avoiding fraud} - G06Q 30/0251: Targeted advertisements - G06Q 30/0276: {Advertisement creation} - G06Q 30/0277: {Online advertisement} - G06Q 50/184: {Intellectual property management} - G06N 3/044: Recurrent networks, e.g. Hopfield networks - G06N 3/0455: Auto-encoder networks; Encoder-decoder networks - G06N 3/0464: Convolutional networks [CNN, ConvNet] - G06N 3/0475: Generative networks - G06N 3/084: Backpropagation, e.g. using gradient descent - G06N 3/09: Supervised learning - G06N 5/01: Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound - G06N 5/02: Knowledge representation; Symbolic representation - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G06Q 2220/00: Business processing using cryptography - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract Systems and methods for generating dynamically updated metadata using real-time artificial intelligence models. For example, the system may receive a first metadata tag requirement for first metadata of a first media asset. The system may determine a first metadata field for the first metadata based on the first metadata tag requirement. The system may determine a first content population function for the first metadata field. The system may generate the first metadata with the first content population function. The system may generate the first media asset with the first metadata. ## Claims ### Claim 1 One or more non-transitory, computer-readable mediums comprising instructions that when executed by one or more processors cause operations comprising: receiving a first metadata requirement for first metadata of a first media asset; determining a first metadata field of a plurality of metadata fields for the first metadata based on the first metadata requirement; determining a first content population function for the first metadata field, wherein the first content population function comprises a self-contained block of code that performs a verification task; generating the first metadata with the first content population function, wherein the first metadata indicates first information attributed to the first media asset; generating the first media asset with the first metadata; subsequent to generating the first media asset with the first metadata, generating second metadata with the first content population function, wherein the second metadata indicates second information attributed to the first media asset; and updating the first media asset with the second metadata. ### Claim 2 A method for generating dynamically updated metadata using real-time artificial intelligence models, the method comprising: receiving a first metadata requirement for first metadata of a first media asset; determining a first metadata field for the first metadata based on the first metadata requirement; determining a first content population function for the first metadata field, wherein the first content population function comprises a self-contained block of code that performs a verification task; generating the first metadata with the first content population function, wherein the first metadata indicates first information attributed to the first media asset; generating the first media asset with the first metadata; subsequent to generating the first media asset with the first metadata, generating second metadata with the first content population function, wherein the second metadata indicates second information attributed to the first media asset; and updating the first media asset with the second metadata. ### Claim 3 (depends on 2) The method of claim 2, further comprising: receiving third metadata of a second media asset; and using the third metadata and the first content population function to generate the first metadata. ### Claim 4 (depends on 2) The method of claim 2, further comprising: receiving user-generated metadata; and using the user-generated metadata and the first content population function to generate the first metadata. ### Claim 5 (depends on 2) The method of claim 2, further comprising: receiving user profile data; and using the user profile data and the first content population function to generate the first metadata. ### Claim 6 (depends on 2) The method of claim 2, further comprising: receiving third metadata, wherein the third metadata comprises a probability or confidence related to the second metadata; and using the third metadata and the first content population function to generate the second metadata. ### Claim 7 (depends on 2) The method of claim 2, further comprising: receiving third metadata, wherein the third metadata comprises a condition used to provide a search function; and using the third metadata and the first content population function to generate the second metadata. ### Claim 8 (depends on 2) The method of claim 2, further comprising: receiving third metadata, wherein the third metadata comprises an update period for the first content population function; and using the third metadata and the first content population function to generate the second metadata. ### Claim 9 (depends on 2) The method of claim 2, further comprising: receiving third metadata, wherein the third metadata comprises an artificial intelligence model determination for the first content population function; and using the artificial intelligence model to generate the second metadata. ### Claim 10 (depends on 2) The method of claim 2, further comprising: receiving third metadata, wherein the third metadata comprises a communication path for the first content population function; and using the communication path to update the first media asset. ### Claim 11 (depends on 2) The method of claim 2, further comprising: receiving a second metadata requirement for third metadata of a second media asset; determining a second metadata field for the third metadata based on the second metadata requirement; determining a second content population function for the second metadata field, wherein second content population function generates metadata based on metadata updates to the first media asset; generating the third metadata with the second content population function; generating the second media asset with the third metadata; subsequent to generating the second media asset with the third metadata, generating fourth metadata with the second content population function based on updating the first media asset with the second metadata; and updating the second media asset with the fourth metadata. ### Claim 12 (depends on 2) The method of claim 2, wherein receiving the first metadata requirement for the first metadata of the first media asset further comprises: determining a first type of the first media asset; and determining the first metadata requirement based on the first type. ### Claim 13 (depends on 2) The method of claim 2, wherein determining the first content population function for the first metadata field further comprises: determining an input type for the first content population function; and determining an output type for the first content population function. ### Claim 14 (depends on 2) The method of claim 2, wherein generating the first metadata with the first content population function further comprises: determining an algorithm for the first content population function; and determining the first metadata for the first media asset using the algorithm. ### Claim 15 (depends on 2) The method of claim 2, wherein generating the first metadata with the first content population function further comprises: determining a content type for the first content population function; and populating the first metadata with the content type. ### Claim 16 (depends on 2) The method of claim 2, wherein generating the first metadata with the first content population function further comprises: determining a search criterion for the first content population function; and performing a search based on the search criterion. ### Claim 17 (depends on 2) The method of claim 2, wherein generating the first metadata with the first content population function further comprises: determining an operation frequency for the first content population function; and performing the first content population function based on the operation frequency. ### Claim 18 (depends on 2) The method of claim 2, wherein generating the first metadata with the first content population function further comprises: determining a data source for the first content population function; and determining the first metadata for the first media asset based on the data source. ### Claim 19 (depends on 2) The method of claim 2, wherein generating the first metadata with the first content population function further comprises: parsing a data source using the first content population function; and determining the first metadata for the first media asset based on parsing the data source. ### Claim 20 (depends on 2) The method of claim 2, wherein generating the first metadata with the first content population function further comprises: automatically extracting third-party data from a data source using the first content population function; and determining the first metadata for the first media asset based on the third-party data.