System

Abstract

A system is provided.SOLUTION: A system comprising: means for a plurality of users who post generative models to upload their generative models; means for a plurality of other users who access the store to purchase generative models; means for executing the purchased generative models to generate digital content; means for making the generated digital content available for download; and means for calculating and distributing rewards to the users who post the generative models based on usage of the generative models.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Companies and local governments considering digital utilization face the problem of high costs and time-consuming digital content production. Furthermore, many companies and local governments lack the skills to use generative models. This creates a need for a simple, low-cost way to generate high-quality digital content, but such a service does not currently exist. To solve this problem, a system is needed that provides an environment for quickly mastering generative models. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes a means for multiple users who post generative models to upload their own generative models, a means for listing the generative models in a store, a means for multiple other users who access the store to purchase the generative models, a means for executing the purchased generative models to generate digital content, a means for making the generated digital content available for download, and a means for calculating rewards based on usage of the generative models and allocating them to the users who posted the generative models, thereby making it possible to provide an efficient and effective digital content generation environment for both creators and users of generative models.

[0006] "Generative model" refers to an artificial intelligence algorithm or program used to generate digital content such as text, images, video, or audio.

[0007] "User" refers to any person or organization that accesses the system and submits or uses Generative Models.

[0008] "Store" refers to an online platform where multiple generative models are listed and where users can purchase these models.

[0009] "Digital Content" refers to material in digital form, such as text, images, video, or audio, that is generated by a generative model.

[0010] "Download" refers to the act of a user saving digital content generated by a Generative Model to their own device.

[0011] "Reward" refers to monetary compensation paid to the user who posted the generative model based on its usage.

[0012] "Upload" refers to the act of a user sending and saving their own generative model to the system.

[0013] "Execution" refers to the process of generating digital content using a Generative Model purchased by a user. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] This invention provides a store platform where users can post, buy, sell, and execute generative models, thereby reducing the cost and effort required for digital content creation and resolving the lack of skills required for using generative models. In particular, the invention provides a series of processes that allow users to easily post, buy, sell, and execute generative models.

[0036] User Registration and Login

[0037] First, the user accesses the server and registers. The server saves the entered registration information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated and the server updates the user status to "active."

[0038] Submitting a Generative Model

[0039] A user who has registered as a generative model creator logs in to the server and accesses the dashboard. The server provides a "Post Generative Model" button, and clicking this displays a form for submitting a generative model. The creator enters and uploads the name, description, usage fee, and model file of the generative model. The server receives this information, stores it in the database, and lists the new generative model on the store page.

[0040] Purchasing Generative Models

[0041] A user who has registered as a generative model user logs in to the server and accesses the store page. The server displays a list of available generative models, and the user adds the generative model of interest to the cart and proceeds with the purchase. The server processes the purchase, verifies the payment information, and then grants the user access rights.

[0042] Execution of generative models and generation of digital content

[0043] After logging in, a user who has purchased a generative model accesses their personal page and selects the model they wish to run from a list of generative models they have purchased. The server provides an interface for running the generative model, displaying a screen for entering the necessary input data (e.g., text prompts, image settings, etc.). When the user provides the input data and clicks the "Run" button, the server runs the generative model and generates digital content based on the specified input data. The generated content is stored on the server, and a download link is provided to the user. The user can download the generated content from the provided link.

[0044] Reward distribution

[0045] The server periodically aggregates the usage status of generative models and calculates the reward for the generative model creator. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and the server reflects this reward in the creator's account and notifies them later. The generative model creator can check the reward and withdraw it if necessary. The server processes the withdrawal request and transfers the reward to the creator.

[0046] Specific examples

[0047] Example 1: A generative model creator submits an image generation model

[0048] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[0049] 2. Creators click the "Post Generative Model" button and enter the name, description, usage fee, etc. of the image generation AI. They also select and upload the model file (e.g., .h5 file) required for image generation.

[0050] 3. The server receives the input data and uploaded files from the creator, stores them in the database, and adds a list of this AI model to the store page.

[0051] Example 2: When a user purchases and runs an image generation model

[0052] 1. The user accesses the server and checks the store page of the generated model.

[0053] 2. The user finds the image generation model they want to use, adds it to their cart, checks the items they need, and clicks the purchase button.

[0054] 3. The server processes the purchase and grants the user access to the purchased Generative Model.

[0055] 4. The user accesses the interface for running the AI ​​and enters prompts and other settings for the image they want to generate.

[0056] 5. The server receives the configuration and runs the generative model to generate the image.

[0057] 6. The server saves the generated image in storage and provides the user with a download link.

[0058] 7. The user obtains the generated image from the provided download link.

[0059] This will enable companies and local governments to quickly generate high-quality digital content without specialized skills, and generative model creators will be able to earn revenue by utilizing their technology.

[0060] The processing flow will be explained below.

[0061] User Registration and Login

[0062] Step 1:

[0063] User: Access the server and display the user registration screen.

[0064] Step 2:

[0065] Server: Displays a user registration form and prompts the user to enter required information such as name, email address, and password.

[0066] Step 3:

[0067] User: Enter the required information in the registration form and click the "Register" button.

[0068] Step 4:

[0069] Server: Stores the entered information in a database and sends a confirmation email to the user.

[0070] Step 5:

[0071] Users: Click the link in the confirmation email to activate their account.

[0072] Step 6:

[0073] Server: Checks for account activation and updates user status to "enabled".

[0074] Submitting a Generative Model

[0075] Step 1:

[0076] Generative AI Creator (User): After logging in, access the dashboard.

[0077] Step 2:

[0078] Server: Display the creator dashboard.

[0079] Step 3:

[0080] Generative AI Creator: Click the "Post Generative Model" button in the dashboard.

[0081] Step 4:

[0082] Server: Display the generated model submission form.

[0083] Step 5:

[0084] Generation AI Creator: Enter and upload the AI ​​model name, description, usage fee, and model file (e.g., .h5, .pth file).

[0085] Step 6:

[0086] Server: Receives entered information and uploaded files and stores them in a database and storage.

[0087] Step 7:

[0088] Server: Update the store page with the new generative model list.

[0089] Purchasing Generative Models

[0090] Step 1:

[0091] User: After logging in, access the store page.

[0092] Step 2:

[0093] Server: Display the store page and list the available generative models.

[0094] Step 3:

[0095] User: Selects the generative model they are interested in and clicks the "Add to Cart" button.

[0096] Step 4:

[0097] Server: Saves and displays the generative models added to the cart in a list.

[0098] Step 5:

[0099] User: Check the contents on the cart page and click the "Purchase" button.

[0100] Step 6:

[0101] Server: Processes purchases and verifies payment information.

[0102] Step 7:

[0103] Server: After confirming the payment, grant the user access to the generative model and update the database.

[0104] Execution of generative models and generation of digital content

[0105] Step 1:

[0106] User: After logging in, access My Page to view a list of generative models you have purchased.

[0107] Step 2:

[0108] Server: Displays My Page and provides a list of Generative Models to which the user has access.

[0109] Step 3:

[0110] User: Select the generative model you want to run and click the "Run" button.

[0111] Step 4:

[0112] Server: Displays the interface for running the generative model and displays the required input fields (e.g., text prompts, image settings, etc.).

[0113] Step 5:

[0114] User: Enter the required input data and click the "Execute" button.

[0115] Step 6:

[0116] Server: Receives input data and executes it by calling the generative model in the backend.

[0117] Step 7:

[0118] Server: Stores the generated digital content in storage and provides users with a download link.

[0119] Step 8:

[0120] User: Downloads the generated digital content from the provided download link.

[0121] Reward distribution

[0122] Step 1:

[0123] Server: Periodically aggregates the usage status of the generative model.

[0124] Step 2:

[0125] Server: Calculates the reward amount for the generative model creator based on the aggregated data.

[0126] Step 3:

[0127] Server: Reflects the calculated rewards in the creator's account and notifies them.

[0128] Step 4:

[0129] Generating AI Creator (User): Check the reward amount on the dashboard and withdraw it if necessary.

[0130] Step 5:

[0131] Server: Processes withdrawal requests and transfers rewards to the creator's designated account.

[0132] The above is the specific flow of the program's processing. This system provides a series of processes that allow users to easily post, buy, sell, and execute generative models, solving the challenges of digital content creation.

[0133] Example 1

[0134] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0135] In modern digital content creation, the revenue model of posting one's own generative models and allowing other users to purchase and execute them is becoming increasingly common. However, existing systems have faced challenges such as a lack of user skills and difficulty in operation. Furthermore, the effort and cost involved in managing generative models and distributing rewards are also issues. It is necessary to solve these issues and provide a user-friendly platform that significantly reduces the effort required for posting, buying and selling, and executing generative models.

[0136] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0137] In this invention, the server includes: means for multiple users who post generative models to upload their own generative models; means for adding the generative models to a list and making them accessible; means for multiple users who access the list to purchase generative models; means for executing the purchased generative models to generate content; means for saving the generated content and making it available for download; means for calculating rewards based on the usage status of the generative models and distributing them to the users who posted the generative models; means for performing user authentication regarding the posting, purchase, and execution of the generative models; and means for sending notifications during the processes of posting, purchasing, and executing the generative models. This makes it easy for the server to manage and use generative models, enabling users to generate high-quality digital content and earn revenue.

[0138] A "generative model" is a machine learning algorithm or artificial intelligence program that automatically generates content based on user-provided data.

[0139] A "User" is an individual or organization that accesses the System and submits, purchases, runs, or uses Generative Models.

[0140] "Means for posting generative models" is a function that allows users to upload and register their own generative models in the system.

[0141] The "means of adding to a list and making it accessible" is a function that makes the posted Generative Model public and makes it available for other users to view and purchase.

[0142] "Means to purchase" refers to the functionality that allows users to pay a fee to access a generative model and obtain usage rights.

[0143] The "means for executing and generating content" is a function for executing a generative model purchased by a user and generating content based on specific data.

[0144] "Means for storing and making available for download" refers to a function for storing generated content in the system and allowing users to download it.

[0145] The "means for calculating and allocating rewards" is a function for calculating rewards for contributors based on the usage of the generative model and allocating those rewards appropriately.

[0146] "Means for user authentication" refers to a function for verifying the identity of a user and appropriately controlling access to a system.

[0147] The "means for sending notifications" is a function for notifying users of necessary information during each process of posting, purchasing, and executing a Generative Model.

[0148] The present invention provides a store platform for using generative models, and is a system that allows users to easily post, purchase, and run generative models. The system includes a means for posting generative models, a means for adding generative models to a list and making them accessible, a means for purchasing generative models, a means for running generative models to generate digital content, a means for saving the generated content and making it available for download, a means for calculating and allocating rewards based on the usage status of the generative models, a means for user authentication, and a means for sending notifications.

[0149] Hardware and software used

[0150] Server: This system is operated using multiple servers. The servers include general web servers, database servers, and storage systems. Specific examples of servers include AWS (registered trademark) EC2 instances and Google (registered trademark) Cloud Compute Engine.

[0151] Database: A relational database management system (RDBMS) is used to store user information, generative model information, purchase history, execution history, etc. Examples include MySQL (registered trademark) and PostgreSQL.

[0152] Storage system: Use cloud-based storage to store generative model files and generated content. Examples include AWS S3, Google Cloud Storage, etc.

[0153] Front-end: The user interface is built using JavaScript libraries such as React.

[0154] Backend: The application logic is implemented using Python web frameworks such as Flask or Django.

[0155] Payment Gateway: You use a third-party payment service, such as Stripe, to process payments from your users.

[0156] Notification system: Notifications to users are sent using an SMTP mail server (e.g., SendGrid).

[0157] Specific example explanation

[0158] Example 1: Posting a generative model

[0159] We will explain the case where a generative model creator (user) posts his or her own generative model.

[0160] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[0161] 2. After logging in, the creator clicks the "Submit Generative Model" button on the dashboard. At this time, the server displays the submission form.

[0162] 3. The creator enters the name, description, and usage fee of the generative model, and uploads the generative model file (e.g., the .h5 file for an image generative model).

[0163] 4. The server receives this information and stores it in the database. After that, the new generative model is listed on the store page.

[0164] Example prompt:

[0165] To create a new image generation model, please provide the following information: model name, description, usage fee, and model file (e.g., .h5 file).

[0166] Example 2: Purchasing and running a generative model

[0167] This section explains the process when a Generative Model user purchases and runs a Generative Model.

[0168] 1. The user accesses the server and checks the store page of the generated model.

[0169] 2. Find the generative model you want to use, add it to your cart, and check out. The server verifies your payment information and completes the purchase.

[0170] 3. After the purchase is complete, the user accesses their My Page and selects the model to run from the list of generative models they have purchased.

[0171] 4. The server provides an execution interface for the generated model, and the user inputs prompt statements and configuration data.

[0172] 5. When the user clicks the "Run" button, the server executes the generative model and generates the digital content.

[0173] 6. The generated content is stored on the server and a download link is provided to the user.

[0174] Example prompt:

[0175] To run the image generation model, please enter the following information: a text prompt for the image you want to generate, and image settings (e.g., resolution).

[0176] As described above, this system can efficiently carry out a series of processes, from managing generative models to generating and distributing digital content, and calculating and allocating rewards.

[0177] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0178] Step 1: Registering a user

[0179] 1. A user enters their name, email address, and password on a registration page.

[0180] 2. The server receives this information and stores it in a database.

[0181] 3. The server will send a confirmation email to the email address you entered.

[0182] 4. When the user clicks on the link in the confirmation email, the server updates the account status to "active."

[0183] Specific behavior: The server sends a confirmation email using the SMTP protocol (e.g. SendGrid), and the data is stored in MySQL or PostgreSQL. The input is the user's registration information, and the output is sending a confirmation email and updating the account status.

[0184] Step 2: User Login

[0185] 1. The user enters their email address and password on the login page.

[0186] 2. The server checks the entered information against its database.

[0187] 3. If there is a match, the server issues a session ID to the user.

[0188] 4. The server redirects the user to the dashboard screen.

[0189] Specific operation: Redis is used for session management, and the session ID is generated using JWT. The input is the user's login information, and the output is the issuance of a session ID and a redirect to the dashboard screen.

[0190] Step 3: Submitting the generative model

[0191] 1. After the creator (user) logs in, they click the "Post Generative Model" button on the dashboard.

[0192] 2. The server displays a submission form, and the user enters and uploads the name, description, usage fee, and model file of the generated model.

[0193] 3. The server stores this information in a database and lists the new generative model on the store page.

[0194] Specific operation: Uploading is done using AWS S3 or Google Cloud Storage, and the input data is stored in a database. The input is the generative model information submitted by the user, and the output is saved in the database and listed on the store page.

[0195] Step 4: Buy a generative model

[0196] 1. The user adds the generated model they want to purchase to their cart on the store page.

[0197] 2. The user enters the required payment information and proceeds with the purchase.

[0198] 3. The server processes the payment and grants access to the user after the purchase is complete.

[0199] Specific operation: Stripe is used for payment processing, and access rights are updated in the database after payment is confirmed. The input is the user's payment information, and the output is granting access rights and a notification of payment completion.

[0200] Step 5: Running the generative model

[0201] 1. The user selects the generative model they purchased from their My Page.

[0202] 2. The server provides an interface for running the generative model, and the user enters input data (e.g., text prompts).

[0203] 3. When the user clicks the "Run" button, the server runs the generative model and generates the content.

[0204] 4. The server saves the generated content to storage and provides a download link to the user.

[0205] Specific operation: TENSORFLOW (registered trademark) or PyTorch is used to execute the generative model, and the generated content is stored in AWS S3 or Google Cloud Storage. The input is the user's prompt data, and the output is the generated content and its access link.

[0206] Step 6: Reward Distribution

[0207] 1. The server periodically aggregates the usage status of the generative model.

[0208] 2. The server calculates the creator's reward and reflects it in the creator's account.

[0209] 3. The creator will process the withdrawal if necessary.

[0210] 4. The server processes the withdrawal request and transfers the reward to the creator.

[0211] Specific operation: Reward calculation is performed by collecting data from the database, and notifications are sent using an SMTP mail server. The input is the usage history of the generative model, and the output is the calculation and transfer of the creator's reward amount.

[0212] (Application example 1)

[0213] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0214] Conventional digital content generation systems require a lot of effort and specialized skills to post, buy, sell, and execute generative models, making them inaccessible to the general public. Furthermore, the scope of use of generative models is limited, making it difficult to apply them in virtual spaces. Therefore, there is a need for a system that improves the efficiency of digital content generation and the convenience of virtual stores.

[0215] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0216] In this invention, the server includes: means for multiple users who post generative models to upload their own generative models; means for listing the generative models in a store; means for multiple other users who access the store to purchase generative models; means for executing the purchased generative models to generate digital content that can be used in a virtual store; means for making the generated digital content available for download; and means for calculating rewards based on the usage status of the generative models and allocating them to the users who posted the generative models. This makes it easy to generate and use digital content in a virtual store, enabling users to generate and utilize high-quality digital content without specialized skills.

[0217] A "generative model" refers to a model that uses machine learning algorithms to automatically generate new digital content from specific input data.

[0218] "User" refers to a user of the System who can post, purchase, and run Generative Models.

[0219] "Store" means the online platform through which Users can post, list, and purchase Generative Models.

[0220] A "virtual store" refers to a digital store that provides various services and products in a virtual space and that users can access.

[0221] "Digital content" refers to information in electronic media (images, text, audio, etc.) created using generative models.

[0222] "Means for posting" refers to the function that allows users to upload their own generative models to the server.

[0223] "Means for listing" refers to the function for displaying posted Generative Models in the Store.

[0224] "Means for purchasing" refers to the functionality that allows users to select a generative model from the store and complete the purchase process.

[0225] "Means for executing" refers to the functionality for generating digital content based on input data using the purchased Generative Model.

[0226] "Means for making available for download" refers to the functionality that allows users to obtain the generated digital content.

[0227] "Means for calculating and allocating rewards" refers to a function for calculating rewards based on the usage status of the generative model and distributing the rewards to the user who posted the generative model.

[0228] The system of this invention aims to streamline the process of posting, buying and selling Generative Models, and running them in a virtual store. Specifically, the server provides a set of functions that allow multiple users to post Generative Models, which other users can purchase, and generate digital content.

[0229] The server uses the following hardware and software: The server uses the Django framework and PostgreSQL as the database. TensorFlow and PyTorch are used to run the generative model. The front end is built using React.

[0230] User Registration and Login

[0231] User registration: The user accesses the server using a smartphone or head-mounted display and registers as a user. The server saves the entered information in a database and sends a confirmation email. The user clicks on the confirmation link to activate the account.

[0232] Login: A registered user enters a username and password on the login screen to access the server.

[0233] Submitting a Generative Model

[0234] Posting a Generative Model: A user of the Generative Model Creator logs in to the server and uploads the name, description, usage fee, and model file of the Generative Model by clicking the "Post a Generative Model" button on the dashboard. The server saves these in the database and lists them on the store page.

[0235] Purchasing and running generative models

[0236] Purchasing a Generative Model: A Generative Model user accesses the store page, adds the Generative Model to their cart, and completes the purchase process. The server verifies the payment information and grants the user access to the Generative Model.

[0237] Executing a Generative Model: To execute a purchased generative model, a user accesses their personal page, selects the generative model, and enters the necessary input data (such as text prompts and image settings). When the user clicks the "Execute" button, the server executes the generative model and generates digital content.

[0238] Downloading digital content

[0239] Make available for download: The generated digital content is stored by the server and a download link is provided to the user, who can then download the content from this link.

[0240] Reward distribution

[0241] Reward calculation and distribution: The server periodically compiles the usage status of the generative model and calculates the reward. This reward is distributed to the user who worked on the generative model and reflected in the user's account. The user can check the reward and withdraw it.

[0242] Specific examples

[0243] For example, if you want to generate your own avatar in a virtual store, you can create a custom avatar for yourself by inputting the following prompts into the generative AI model:

[0244] Please create an avatar with blue hair, almond-shaped eyes, and casual clothing.

[0245] In this way, users can quickly generate high-quality digital content without any specialized knowledge and use it in virtual stores. This system lowers the barrier to entry for digital content creation and enables the widespread use of generative models.

[0246] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0247] Step 1:

[0248] User Registration and Login

[0249] Input: User's registration information (username, email address, password).

[0250] Processing: The server saves this registration information in a database (PostgreSQL) and sends a confirmation email. Once the user clicks on the confirmation link, the account is activated.

[0251] Output: Activated user account information.

[0252] Step 2:

[0253] Submitting a Generative Model

[0254] Inputs: The name, description, usage fee, and model file of the Generative Model entered by the Generative Model creator.

[0255] Processing: The server saves the input data and uploaded model files to the database and lists them on the store page.

[0256] Output: Generated model information listed on the store page.

[0257] Step 3:

[0258] Purchasing Generative Models

[0259] Input: Purchase request from the Generative Model Consumer (selected Generative Model ID, payment information).

[0260] Processing: The server verifies the payment information and, if successful, stores the data in the database to grant access to the Generative Model User.

[0261] Output: Generated model access rights to the generated model consumer.

[0262] Step 4:

[0263] Running the generative model

[0264] Input: Prompt statements and configuration data entered by the user of the generative model.

[0265] Processing: The server runs the purchased generative model and generates digital content based on the input data (using TensorFlow or PyTorch).

[0266] Output: The generated digital content files.

[0267] Step 5:

[0268] Downloading digital content

[0269] Input: A request to download the generated digital content.

[0270] Processing: The server retrieves the generated digital content from storage and generates and provides a download link.

[0271] Output: A link for the user to download.

[0272] Step 6:

[0273] Reward calculation and allocation

[0274] Input: Usage data for the generative model (number of purchases and frequency of use).

[0275] Processing: The server calculates the reward based on this information and reflects it in the Generative Model Creator's account. The creator checks this and can withdraw the money if necessary.

[0276] Output: Reward amount and withdrawal information for the generative model creator.

[0277] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0278] This invention realizes optimal digital content generation based on user emotions by combining a store platform where generative models can be posted, traded, and executed with a user emotion engine. The invention provides a series of processes that allow users to easily post, trade, and execute generative models, and further improves the quality of generated content using the emotion engine.

[0279] User Registration and Login

[0280] First, the user accesses the server and registers. The server saves the entered registration information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated and the server updates the user status to "active."

[0281] Submitting a Generative Model

[0282] A user who has registered as a generative model creator logs in to the server and accesses the dashboard. The server provides a "Post Generative Model" button, and clicking this displays a form for submitting a generative model. The creator enters and uploads the name, description, usage fee, and model file of the generative model. The server receives this information, stores it in the database, and lists the new generative model on the store page.

[0283] Purchasing Generative Models

[0284] A user who has registered as a generative model user logs in to the server and accesses the store page. The server displays a list of available generative models, and the user adds the generative model of interest to the cart and proceeds with the purchase. The server processes the purchase, verifies the payment information, and then grants the user access rights.

[0285] Execution of generative models and generation of digital content

[0286] After logging in, a user who has purchased a generative model accesses their personal page and selects the model they wish to run from a list of generative models they have purchased. The server provides an interface for running the generative model and displays a screen for entering the necessary input data (e.g., text prompts, image settings, etc.). When the user provides the input data and clicks the "Run" button, the server runs the generative model and generates digital content based on the specified input data.

[0287] Furthermore, by using an emotion engine, it is possible to recognize the user's emotional state in real time and adjust the output of the generative model. This allows the generated content to be provided in a form that is more suited to the user's emotions. The generated content is stored on a server, and a download link is provided to the user. The user can download the generated content from the provided link.

[0288] Reward distribution

[0289] The server periodically aggregates the usage status of generative models and calculates the reward for the generative model creator. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and the server reflects this reward in the creator's account and notifies them later. The generative model creator can check the reward and withdraw it if necessary. The server processes the withdrawal request and transfers the reward to the creator.

[0290] Specific examples

[0291] Example 1: A generative model creator submits an image generation model

[0292] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[0293] 2. Creators click the "Post Generative Model" button and enter the name, description, usage fee, etc. of the image generation AI. They also select and upload the model file (e.g., .h5 file) required for image generation.

[0294] 3. The server receives the input data and uploaded files from the creator, stores them in the database, and adds a list of this AI model to the store page.

[0295] Example 2: When a user purchases and runs an image generation model

[0296] 1. The user accesses the server and checks the store page of the generated model.

[0297] 2. The user finds the image generation model they want to use, adds it to their cart, checks the items they need, and clicks the purchase button.

[0298] 3. The server processes the purchase and grants the user access to the purchased Generative Model.

[0299] 4. The user accesses the interface for running the AI ​​and enters prompts and other settings for the image they want to generate.

[0300] 5. The server receives the configuration and runs the generative model to generate the image.

[0301] 6. The server saves the generated image in storage and provides the user with a download link.

[0302] 7. The user obtains the generated image from the provided download link.

[0303] Example 3: Content generation using an emotion engine

[0304] 1. When purchasing a generative model with an emotion engine, the user selects the option to enable the emotion engine.

[0305] 2. The user accesses the server, checks the store page for the generative model, and configures the emotion engine for use.

[0306] 3. When a user runs a generative model with the emotion engine enabled, the server collects the user's emotion data in real time and adjusts the output of the generative model.

[0307] 4. Optimal digital content is generated and provided based on the user's emotions.

[0308] In this way, by combining the user's emotion engine, the present invention can realize more personalized digital content generation and improve the user experience.

[0309] The processing flow will be explained below.

[0310] User Registration and Login

[0311] Step 1:

[0312] User: Access the server and display the user registration screen.

[0313] Step 2:

[0314] Server: Displays a user registration form and prompts the user to enter required information such as name, email address, and password.

[0315] Step 3:

[0316] User: Enter the required information in the registration form and click the "Register" button.

[0317] Step 4:

[0318] Server: Stores the entered information in a database and sends a confirmation email to the user.

[0319] Step 5:

[0320] Users: Click the link in the confirmation email to activate their account.

[0321] Step 6:

[0322] Server: Checks for account activation and updates user status to "enabled".

[0323] Submitting a Generative Model

[0324] Step 1:

[0325] Generative model creator (user): After logging in, access the dashboard.

[0326] Step 2:

[0327] Server: Display the creator dashboard.

[0328] Step 3:

[0329] Generative Model Creator: Click the "Submit Generative Model" button in the dashboard.

[0330] Step 4:

[0331] Server: Display the generated model submission form.

[0332] Step 5:

[0333] Generative Model Creator: Enter and upload the generated model name, description, usage fee, and model file (e.g., .h5, .pth file).

[0334] Step 6:

[0335] Server: Receives entered information and uploaded files and stores them in a database and storage.

[0336] Step 7:

[0337] Server: Update the store page with the new generative model list.

[0338] Purchasing Generative Models

[0339] Step 1:

[0340] User: After logging in, access the store page.

[0341] Step 2:

[0342] Server: Display the store page and list the available generative models.

[0343] Step 3:

[0344] User: Selects the generative model they are interested in and clicks the "Add to Cart" button.

[0345] Step 4:

[0346] Server: Saves and displays the generative models added to the cart in a list.

[0347] Step 5:

[0348] User: Check the contents on the cart page and click the "Purchase" button.

[0349] Step 6:

[0350] Server: Processes purchases and verifies payment information.

[0351] Step 7:

[0352] Server: After confirming the payment, grant the user access to the generative model and update the database.

[0353] Execution of generative models and generation of digital content

[0354] Step 1:

[0355] User: After logging in, access My Page to view a list of generative models you have purchased.

[0356] Step 2:

[0357] Server: Displays My Page and provides a list of Generative Models to which the user has access.

[0358] Step 3:

[0359] User: Select the generative model you want to run and click the "Run" button.

[0360] Step 4:

[0361] Server: Displays the interface for running the generative model and displays the required input fields (e.g., text prompts, image settings, etc.).

[0362] Step 5:

[0363] User: Enter the required input data and click the "Execute" button.

[0364] Step 6:

[0365] Server: Receives input data and executes it by calling the generative model in the backend.

[0366] Step 7:

[0367] Server: Stores the generated digital content in storage and provides users with a download link.

[0368] Step 8:

[0369] User: Downloads the generated digital content from the provided download link.

[0370] Content generation using emotion engine

[0371] Step 1:

[0372] Users: When purchasing a generative model with an emotion engine, select the option to enable the emotion engine.

[0373] Step 2:

[0374] User: Accesses the server, checks the store page for the generative model, and configures the emotion engine.

[0375] Step 3:

[0376] Server: Reflects the emotion engine settings and displays an option to enable the emotion engine on the generative model execution screen.

[0377] Step 4:

[0378] User: Enables the emotion engine and provides input data to run the generative model.

[0379] Step 5:

[0380] Server: Analyzes user emotion data in real time using an emotion engine and feeds the results back to the generative model.

[0381] Step 6:

[0382] Server: Executes the generative model based on data from the emotion engine and generates optimal digital content.

[0383] Step 7:

[0384] Server: Stores the generated digital content in storage and provides users with a download link.

[0385] Step 8:

[0386] User: Downloads the generated digital content from the provided download link.

[0387] Reward distribution

[0388] Step 1:

[0389] Server: Periodically aggregates the usage status of the generative model.

[0390] Step 2:

[0391] Server: Calculates the reward amount for the generative model creator based on the aggregated data.

[0392] Step 3:

[0393] Server: Reflects the calculated rewards in the creator's account and notifies them.

[0394] Step 4:

[0395] Generative model creator (user): Check the reward amount on the dashboard and withdraw it if necessary.

[0396] Step 5:

[0397] Server: Processes withdrawal requests and transfers rewards to the creator's designated account.

[0398] The above are the specific processing steps of the invention that combines an emotion engine. This system provides more personalized digital content and improves the user experience by adjusting the output of the generative model to adapt to the user's emotions.

[0399] Example 2

[0400] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0401] Conventional digital content generation systems using generative models have problems such as a lack of personalization in the user experience and difficulty in improving the quality of content. Furthermore, there is a need for improved transparency and efficiency in the distribution of rewards to generative model creators.

[0402] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to upload their own generative model, a means for listing the generative model in a store, a means for other users who access the store to purchase generative models, a means for executing the purchased generative model to generate digital content, a means for making the generated digital content available for download, a means for calculating a reward based on the usage status of the generative model and distributing it to the user who posted the generative model, and a means for the user to adjust the output of the generative model in real time using an emotion engine. This enables the generation of more personalized, high-quality digital content based on user emotions. Furthermore, reward distribution to creators can be transparent and efficient.

[0403] A "User" is an individual or organization that uses the system and can upload, purchase, and run Generative Models.

[0404] A "generative model" is a computational tool that uses machine learning techniques to generate new digital content based on specific input data.

[0405] "Uploading" is the act of a generative model creator sending and saving their generative model to a server.

[0406] A "store" is an online platform that resides on a server and lists generative models, allowing users to purchase them.

[0407] "Listing" refers to the process and procedure of placing an uploaded Generative Model on the Store.

[0408] "Purchase" refers to the act of a user paying a fee for a generative model offered in the store and obtaining the right to use it.

[0409] "Execution" refers to the process of generating specific digital content using the Generative Model purchased by the user.

[0410] "Digital content" is data created by the execution of a generative model, and can take the form of images, text, audio, etc.

[0411] "Making it available for download" means providing the generated digital content as a link or file so that users can save it to their own devices.

[0412] "Remuneration" means the compensation a Generative Model Creator receives based on the use or sale of a Generative Model.

[0413] An "emotion engine" is a technology for detecting the user's emotional state and adjusting the output of a generative model.

[0414] These definitions are used to clarify the technical scope of the patent and to provide an understanding of the specific content of the invention.

[0415] This invention is a system that combines a store platform where users can post, buy, sell, and execute generative models with a user emotion engine. The invention facilitates the process of generating generative models and realizes optimal digital content generation based on user emotions.

[0416] User Registration and Login

[0417] First, the user accesses the server from their own device and registers as a user. The server receives the registration information (name, email address, password, etc.) entered by the user and stores it in a database. The server then sends a confirmation email to the user, and when the user clicks on the link, the account is activated. After completing registration, the user can log in by entering their email address and password on the login screen and access the dashboard.

[0418] Submitting a Generative Model

[0419] A user who has registered as a generative model creator logs in to the server and clicks the "Post Generative Model" button on the dashboard. The creator enters the name, description, usage fee, and model file (e.g., .h5 file) of the generative model and uploads it to the server. The server saves this information in the database and lists the new generative model on the store page.

[0420] Purchasing Generative Models

[0421] A user who has registered as a Generative Model user logs in to the server and accesses the store page. The server displays a list of available Generative Models, and the user adds the Generative Model of interest to the cart and proceeds with the purchase. When the user enters payment information and clicks the submit button, the server processes the payment and grants the user access to the purchased Generative Model.

[0422] Execution of generative models and generation of digital content

[0423] After purchasing a generative model, a user logs in to the server, accesses their personal page, and selects the model they wish to run from a list of purchased generative models. The server displays the generative model execution interface, and the user provides the required input data (e.g., text prompts, image settings, etc.). The user clicks the "Run" button, and the server runs the generative model based on the input data and generates digital content. The generated content is stored on the server, and a download link is provided to the user.

[0424] Use of emotion engine

[0425] When using the emotion engine, the server recognizes the user's emotional state in real time and adjusts the output of the generative model, making the generated content more personalized and optimized for the user's emotions.

[0426] Reward distribution

[0427] The server periodically aggregates the usage status of generative models and calculates the reward for generative model creators. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and is reflected in the creator's account. Creators can request a withdrawal under certain conditions, and the server processes this request and transfers the reward to the creator.

[0428] A concrete example of this system is a case where a generative model creator enters a prompt such as, "Generate a promotional image for a new product. The product is a small, portable speaker. Obtain positive feedback from user reviews and generate an image with a positive atmosphere based on that." A user can purchase this image generation model, enter a similar prompt, and run it to generate a promotional image that meets their needs.

[0429] As described above, this invention improves the user experience and enables the generation of high-quality digital content by combining the posting, buying and selling, and execution of generative models with an emotion engine.

[0430] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0431] Step 1: User Registration

[0432] Input: The user accesses the server from their device and enters registration information such as their name, email address, and password.

[0433] Data processing and output: The server receives the entered information, stores it in a database, and sends a confirmation email to the user.

[0434] What happens: The server validates the input information and, if there are no problems, saves it to the database and sends the user an email containing a confirmation link.

[0435] Step 2: User authentication

[0436] Input: User clicks on the link in the confirmation email.

[0437] Data processing and output: The server checks the validity of the link and updates the user status to "valid".

[0438] Specific operation: The server analyzes the link in the email, retrieves the corresponding user account information from the database, and updates it.

[0439] Step 3: User Login

[0440] Input: The user enters their email address and password on the login screen.

[0441] Data processing and output: The server checks the entered information against the database, and if correct, authenticates the user and redirects them to the dashboard.

[0442] Specific behavior: The server checks the entered email address and password, and if successful, starts a session for the user.

[0443] Step 4: Submitting the generative model

[0444] Input: The Generative Model creator accesses the dashboard and enters and uploads the name, description, usage fee, and model file (e.g., .h5 file) of the Generative Model.

[0445] Data processing and output: The server receives this information, stores it in a database, and lists the new generative model on the store page.

[0446] What happens: The server validates the information submitted in the form, records it in a database, and updates the listing on the store page.

[0447] Step 5: Buy a generative model

[0448] Input: A user adds a generative model of interest to their cart on the store page and proceeds to checkout.

[0449] Data processing and output: The server receives payment information, processes the transaction, and grants the user access to the purchased generative model.

[0450] What happens: The server validates the payment information and processes the payment. If successful, it grants access to the user's account and sends a notification.

[0451] Step 6: Execute the generative model and generate digital content

[0452] Input: The user accesses My Page, selects the generative model they wish to run from the purchased models, and provides the required input data (e.g., text prompts, image settings, etc.).

[0453] Data processing and output: The server runs the generative model based on the input data to generate digital content, which is then stored on the server and a download link is provided to the user.

[0454] Specific operation: The server allocates computing resources to run the generative model and runs the model based on the input data. The generated content is saved to storage and a link is sent to the user.

[0455] Step 7: Use the Emotion Engine

[0456] Input: User enables the emotion engine and runs the generative model.

[0457] Data processing and output: The server recognizes the user's emotional state in real time and adjusts the output of the generative model, thereby generating digital content optimized for the user.

[0458] Specific operation: The server analyzes the user's emotional data using an emotion recognition algorithm and adjusts the parameters of the generative model based on the results.

[0459] Step 8: Reward Distribution

[0460] Input: The server periodically aggregates the usage of the generative model.

[0461] Data processing and output: The server calculates rewards based on the number of times the generative model is used and the amount of sales, and reflects them in the creator's account.

[0462] Specific operation: The server periodically collects usage data from the database and calculates the reward amount using the reward calculation algorithm. The calculation results are reflected in the creator's account and notified.

[0463] This clarifies the specific operations performed at each processing step, making it easier to understand the flow of the entire system.

[0464] (Application example 2)

[0465] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0466] Conventional digital content generation systems using generative models have difficulty providing personalized advertising content because they do not take into account the user's emotional state. Furthermore, there has been no effective means of collecting real-time emotional data from users and generating advertising content that reflects this data.

[0467] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: a means for multiple users who post generative models to upload their own generative models; a means for listing the generative models in a store; a means for multiple other users who access the store to purchase generative models; a means for executing the purchased generative models to generate digital content; a means for making the generated digital content available for download; a means for calculating a reward based on the usage status of the generative model and distributing it to the user who posted the generative model; and a means for generating digital content by combining an emotion engine that recognizes the user's emotional state in real time and adjusts the output of the generative model. This makes it possible to generate advertising content that is appropriate for the user's emotional state.

[0468] A "generative model" is an algorithm or machine learning model that generates specific digital content submitted by users.

[0469] The "Store" is an online platform where generative models are listed and available for purchase by other users.

[0470] "Digital content" refers to electronic media content such as images, text, and videos created using generative models.

[0471] An "emotion engine" is a system that recognizes the user's real-time emotional state and adjusts the output of the generative model based on that data.

[0472] "User" refers to anyone who uses the system, including creators who post generative models and users who purchase those generative models and generate content.

[0473] "Reward" is calculated based on the usage of the generative model and is paid to the user who posted the generative model.

[0474] This invention provides optimal digital content generation based on user emotions by combining a user's emotion engine with a store platform where users can post, trade, and execute generative models. This system is implemented using smart glasses and a server.

[0475] The system program is structured as follows:

[0476] 1. User Registration and Login

[0477] The server saves the user's registered information in a database and sends a confirmation email, which the user must click to activate their account.

[0478] Software used: Database management system (e.g., MySQL)

[0479] 2. Submitting a Generative Model

[0480] Users who are registered as generative model creators log in to the server and upload their models using the generative model submission form. The model information and files are stored in the database and listed on the store page.

[0481] Software used: Cloud storage system (e.g. Amazon S3)

[0482] 3. Purchasing a Generative Model

[0483] The server displays a list of generative models on a store page, allowing users to add them to their cart and purchase them. After completing the purchase process, access rights are granted.

[0484] Software used: Electronic payment systems (e.g., Stripe)

[0485] 4. Execution of generative models and generation of digital content

[0486] An interface is provided for running purchased generative models. The user provides input data such as prompt statements and executes the generative model.

[0487] Software used: Generative AI model (e.g., GPT-3 (registered trademark))

[0488] 5. Use of Emotion Engine

[0489] The camera built into the smart glasses analyzes the user's facial expressions in real time, and the emotion engine acquires emotional data.

[0490] Hardware used: Built-in camera in smart glasses

[0491] Software used: Facial expression recognition library (e.g., OpenCV), emotion analysis model

[0492] 6. Emotional content optimization

[0493] The emotion engine adjusts the output of the generative model based on the user's emotional state to generate more personalized digital content.

[0494] Software used: Sentiment analysis model

[0495] 7. Reward Distribution

[0496] The server calculates rewards based on the usage of the generative model and pays them to the generative model creator.

[0497] Software used: Remuneration calculation system

[0498] For example:

[0499] If the user's emotion is "joy":

[0500] Prompt: "Create a fun and cheerful video ad."

[0501] Based on the prompt, the server generates an advertisement for a home electronic device featuring a smiling family enjoying a holiday.

[0502] If the user's emotion is "sadness":

[0503] Prompt: "Generate a quiet ad that provides warmth and comfort."

[0504] Based on this prompt, the server generates a soothing product advertisement that conveys a gentle message accompanied by quiet music.

[0505] In this way, the system of the present invention can improve the user experience by generating more suitable digital content based on the user's real-time emotional data.

[0506] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0507] Step 1:

[0508] User registration and login.

[0509] The server receives the user's registration information (e.g., name, email address, password) and stores it in a database. It then sends a confirmation email and the user activates their account by clicking the link in the confirmation email. This updates the user status to "active."

[0510] Input: User registration information (name, email address, password)

[0511] Output: Send confirmation email, update user status

[0512] Step 2:

[0513] Posting generative models.

[0514] Users who have registered as generative model creators log in to the server using their terminal and enter and upload the model file (e.g., .h5 file) and necessary information (e.g., model name, description, and usage fee) into the generative model submission form. The server receives this data, stores it in the database, and lists it as a new generative model on the store page.

[0515] Input: Generated model file, model name, description, usage fee

[0516] Output: Save to database, add list to store page

[0517] Step 3:

[0518] Purchasing generative models.

[0519] Other users who access the store log in to the server and check the list of Generative Models. The user adds the Generative Model they want to purchase to their cart and completes the payment process. The server verifies the payment information and completes the purchase. The server grants the user access to the purchased Generative Model.

[0520] Input: Add to Cart, Payment Information

[0521] Output: Purchase procedure completed, access granted

[0522] Step 4:

[0523] Execution of generative models and digital content generation.

[0524] To run a purchased generative model, a user logs in and accesses their personal page. They select the model they want to run and provide input data (e.g., a prompt). The server runs the generative model and generates digital content based on the specified input data.

[0525] Input: Input data such as prompt statements

[0526] Output: Generated digital content

[0527] Step 5:

[0528] Leveraging the emotion engine.

[0529] The smart glasses' built-in camera captures the user's facial expression data in real time, and the emotion engine analyzes this data to recognize the user's emotional state.

[0530] Input: User's facial expression data

[0531] Output: Real-time emotional state

[0532] Step 6:

[0533] Emotion-based content optimization.

[0534] Based on the user's emotional data acquired by the emotion engine, the server adjusts the output of the generative model to generate digital content more suitable for the user. For example, if the user is in a "joy" emotional state, it generates a bright and cheerful advertisement. If the user is in a "sad" emotional state, it generates a quiet advertisement that provides warmth and comfort.

[0535] Input: Real-time emotional state, prompt sentence

[0536] Output: Emotion-based digital content

[0537] Step 7:

[0538] Providing generated digital content.

[0539] The server stores the generated digital content in storage and provides a download link to the user, who then downloads the generated content via the link.

[0540] Input: Generated digital content

[0541] Output: Download link

[0542] Step 8:

[0543] Distribution of rewards.

[0544] The server periodically compiles the usage status of generative models and calculates the reward for the generative model creator. The reward is determined based on the number of times the generative model is used and the amount of sales, and is reflected in the creator's account. The creator can then perform a withdrawal procedure, and the server processes the withdrawal request and transfers the reward to the creator.

[0545] Input: Generative model usage data

[0546] Output: Reward calculation, notification to creator

[0547] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0548] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0549] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0550] [Second embodiment]

[0551] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0552] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0553] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0554] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0555] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0556] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0557] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0558] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0559] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0560] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0561] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0562] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0563] This invention provides a store platform where users can post, buy, sell, and execute generative models, thereby reducing the cost and effort required for digital content creation and resolving the lack of skills required for using generative models. In particular, the invention provides a series of processes that allow users to easily post, buy, sell, and execute generative models.

[0564] User Registration and Login

[0565] First, the user accesses the server and registers. The server saves the entered registration information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated and the server updates the user status to "active."

[0566] Submitting a Generative Model

[0567] A user who has registered as a generative model creator logs in to the server and accesses the dashboard. The server provides a "Post Generative Model" button, and clicking this displays a form for submitting a generative model. The creator enters and uploads the name, description, usage fee, and model file of the generative model. The server receives this information, stores it in the database, and lists the new generative model on the store page.

[0568] Purchasing Generative Models

[0569] A user who has registered as a generative model user logs in to the server and accesses the store page. The server displays a list of available generative models, and the user adds the generative model of interest to the cart and proceeds with the purchase. The server processes the purchase, verifies the payment information, and then grants the user access rights.

[0570] Execution of generative models and generation of digital content

[0571] After logging in, a user who has purchased a generative model accesses their personal page and selects the model they wish to run from a list of generative models they have purchased. The server provides an interface for running the generative model, displaying a screen for entering the necessary input data (e.g., text prompts, image settings, etc.). When the user provides the input data and clicks the "Run" button, the server runs the generative model and generates digital content based on the specified input data. The generated content is stored on the server, and a download link is provided to the user. The user can download the generated content from the provided link.

[0572] Reward distribution

[0573] The server periodically aggregates the usage status of generative models and calculates the reward for the generative model creator. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and the server reflects this reward in the creator's account and notifies them later. The generative model creator can check the reward and withdraw it if necessary. The server processes the withdrawal request and transfers the reward to the creator.

[0574] Specific examples

[0575] Example 1: A generative model creator submits an image generation model

[0576] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[0577] 2. Creators click the "Post Generative Model" button and enter the name, description, usage fee, etc. of the image generation AI. They also select and upload the model file (e.g., .h5 file) required for image generation.

[0578] 3. The server receives the input data and uploaded files from the creator, stores them in the database, and adds a list of this AI model to the store page.

[0579] Example 2: When a user purchases and runs an image generation model

[0580] 1. The user accesses the server and checks the store page of the generated model.

[0581] 2. The user finds the image generation model they want to use, adds it to their cart, checks the items they need, and clicks the purchase button.

[0582] 3. The server processes the purchase and grants the user access to the purchased Generative Model.

[0583] 4. The user accesses the interface for running the AI ​​and enters prompts and other settings for the image they want to generate.

[0584] 5. The server receives the configuration and runs the generative model to generate the image.

[0585] 6. The server saves the generated image in storage and provides the user with a download link.

[0586] 7. The user obtains the generated image from the provided download link.

[0587] This will enable companies and local governments to quickly generate high-quality digital content without specialized skills, and generative model creators will be able to earn revenue by utilizing their technology.

[0588] The processing flow will be explained below.

[0589] User Registration and Login

[0590] Step 1:

[0591] User: Access the server and display the user registration screen.

[0592] Step 2:

[0593] Server: Displays a user registration form and prompts the user to enter required information such as name, email address, and password.

[0594] Step 3:

[0595] User: Enter the required information in the registration form and click the "Register" button.

[0596] Step 4:

[0597] Server: Stores the entered information in a database and sends a confirmation email to the user.

[0598] Step 5:

[0599] Users: Click the link in the confirmation email to activate their account.

[0600] Step 6:

[0601] Server: Checks for account activation and updates user status to "enabled".

[0602] Submitting a Generative Model

[0603] Step 1:

[0604] Generative AI Creator (User): After logging in, access the dashboard.

[0605] Step 2:

[0606] Server: Display the creator dashboard.

[0607] Step 3:

[0608] Generative AI Creator: Click the "Post Generative Model" button in the dashboard.

[0609] Step 4:

[0610] Server: Display the generated model submission form.

[0611] Step 5:

[0612] Generation AI Creator: Enter and upload the AI ​​model name, description, usage fee, and model file (e.g., .h5, .pth file).

[0613] Step 6:

[0614] Server: Receives entered information and uploaded files and stores them in a database and storage.

[0615] Step 7:

[0616] Server: Update the store page with the new generative model list.

[0617] Purchasing Generative Models

[0618] Step 1:

[0619] User: After logging in, access the store page.

[0620] Step 2:

[0621] Server: Display the store page and list the available generative models.

[0622] Step 3:

[0623] User: Selects the generative model they are interested in and clicks the "Add to Cart" button.

[0624] Step 4:

[0625] Server: Saves and displays the generative models added to the cart in a list.

[0626] Step 5:

[0627] User: Check the contents on the cart page and click the "Purchase" button.

[0628] Step 6:

[0629] Server: Processes purchases and verifies payment information.

[0630] Step 7:

[0631] Server: After confirming the payment, grant the user access to the generative model and update the database.

[0632] Execution of generative models and generation of digital content

[0633] Step 1:

[0634] User: After logging in, access My Page to view a list of generative models you have purchased.

[0635] Step 2:

[0636] Server: Displays My Page and provides a list of Generative Models to which the user has access.

[0637] Step 3:

[0638] User: Select the generative model you want to run and click the "Run" button.

[0639] Step 4:

[0640] Server: Displays the interface for running the generative model and displays the required input fields (e.g., text prompts, image settings, etc.).

[0641] Step 5:

[0642] User: Enter the required input data and click the "Execute" button.

[0643] Step 6:

[0644] Server: Receives input data and executes it by calling the generative model in the backend.

[0645] Step 7:

[0646] Server: Stores the generated digital content in storage and provides users with a download link.

[0647] Step 8:

[0648] User: Downloads the generated digital content from the provided download link.

[0649] Reward distribution

[0650] Step 1:

[0651] Server: Periodically aggregates the usage status of the generative model.

[0652] Step 2:

[0653] Server: Calculates the reward amount for the generative model creator based on the aggregated data.

[0654] Step 3:

[0655] Server: Reflects the calculated rewards in the creator's account and notifies them.

[0656] Step 4:

[0657] Generating AI Creator (User): Check the reward amount on the dashboard and withdraw it if necessary.

[0658] Step 5:

[0659] Server: Processes withdrawal requests and transfers rewards to the creator's designated account.

[0660] The above is the specific flow of the program's processing. This system provides a series of processes that allow users to easily post, buy, sell, and execute generative models, solving the challenges of digital content creation.

[0661] Example 1

[0662] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0663] In modern digital content creation, the revenue model of posting one's own generative models and allowing other users to purchase and execute them is becoming increasingly common. However, existing systems have faced challenges such as a lack of user skills and difficulty in operation. Furthermore, the effort and cost involved in managing generative models and distributing rewards are also issues. It is necessary to solve these issues and provide a user-friendly platform that significantly reduces the effort required for posting, buying and selling, and executing generative models.

[0664] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0665] In this invention, the server includes: means for multiple users who post generative models to upload their own generative models; means for adding the generative models to a list and making them accessible; means for multiple users who access the list to purchase generative models; means for executing the purchased generative models to generate content; means for saving the generated content and making it available for download; means for calculating rewards based on the usage status of the generative models and distributing them to the users who posted the generative models; means for performing user authentication regarding the posting, purchase, and execution of the generative models; and means for sending notifications during the processes of posting, purchasing, and executing the generative models. This makes it easy for the server to manage and use generative models, enabling users to generate high-quality digital content and earn revenue.

[0666] A "generative model" is a machine learning algorithm or artificial intelligence program that automatically generates content based on user-provided data.

[0667] A "User" is an individual or organization that accesses the System and submits, purchases, runs, or uses Generative Models.

[0668] "Means for posting generative models" is a function that allows users to upload and register their own generative models in the system.

[0669] The "means of adding to a list and making it accessible" is a function that makes the posted Generative Model public and makes it available for other users to view and purchase.

[0670] "Means to purchase" refers to the functionality that allows users to pay a fee to access a generative model and obtain usage rights.

[0671] The "means for executing and generating content" is a function for executing a generative model purchased by a user and generating content based on specific data.

[0672] "Means for storing and making available for download" refers to a function for storing generated content in the system and allowing users to download it.

[0673] The "means for calculating and allocating rewards" is a function for calculating rewards for contributors based on the usage of the generative model and allocating those rewards appropriately.

[0674] "Means for user authentication" refers to a function for verifying the identity of a user and appropriately controlling access to a system.

[0675] The "means for sending notifications" is a function for notifying users of necessary information during each process of posting, purchasing, and executing a Generative Model.

[0676] The present invention provides a store platform for using generative models, and is a system that allows users to easily post, purchase, and run generative models. The system includes a means for posting generative models, a means for adding generative models to a list and making them accessible, a means for purchasing generative models, a means for running generative models to generate digital content, a means for saving the generated content and making it available for download, a means for calculating and allocating rewards based on the usage status of the generative models, a means for user authentication, and a means for sending notifications.

[0677] Hardware and software used

[0678] Servers: This system is operated using multiple servers. These servers include common web servers, database servers, and storage systems. Specific examples of servers include AWS EC2 instances and Google Cloud Compute Engine.

[0679] Database: A relational database management system (RDBMS) is used to store user information, generative model information, purchase history, execution history, etc. Examples include MySQL and PostgreSQL.

[0680] Storage system: Use cloud-based storage to store generative model files and generated content. Examples include AWS S3, Google Cloud Storage, etc.

[0681] Front-end: The user interface is built using JavaScript libraries such as React.

[0682] Backend: The application logic is implemented using Python web frameworks such as Flask or Django.

[0683] Payment Gateway: You use a third-party payment service, such as Stripe, to process payments from your users.

[0684] Notification system: Notifications to users are sent using an SMTP mail server (e.g., SendGrid).

[0685] Specific example explanation

[0686] Example 1: Posting a generative model

[0687] We will explain the case where a generative model creator (user) posts his or her own generative model.

[0688] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[0689] 2. After logging in, the creator clicks the "Submit Generative Model" button on the dashboard. At this time, the server displays the submission form.

[0690] 3. The creator enters the name, description, and usage fee of the generative model, and uploads the generative model file (e.g., the .h5 file for an image generative model).

[0691] 4. The server receives this information and stores it in the database. After that, the new generative model is listed on the store page.

[0692] Example prompt:

[0693] To create a new image generation model, please provide the following information: model name, description, usage fee, and model file (e.g., .h5 file).

[0694] Example 2: Purchasing and running a generative model

[0695] This section explains the process when a Generative Model user purchases and runs a Generative Model.

[0696] 1. The user accesses the server and checks the store page of the generated model.

[0697] 2. Find the generative model you want to use, add it to your cart, and check out. The server verifies your payment information and completes the purchase.

[0698] 3. After the purchase is complete, the user accesses their My Page and selects the model to run from the list of generative models they have purchased.

[0699] 4. The server provides an execution interface for the generated model, and the user inputs prompt statements and configuration data.

[0700] 5. When the user clicks the "Run" button, the server executes the generative model and generates the digital content.

[0701] 6. The generated content is stored on the server and a download link is provided to the user.

[0702] Example prompt:

[0703] To run the image generation model, please enter the following information: a text prompt for the image you want to generate, and image settings (e.g., resolution).

[0704] As described above, this system can efficiently carry out a series of processes, from managing generative models to generating and distributing digital content, and calculating and allocating rewards.

[0705] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0706] Step 1: Registering a user

[0707] 1. A user enters their name, email address, and password on a registration page.

[0708] 2. The server receives this information and stores it in a database.

[0709] 3. The server will send a confirmation email to the email address you entered.

[0710] 4. When the user clicks on the link in the confirmation email, the server updates the account status to "active."

[0711] Specific behavior: The server sends a confirmation email using the SMTP protocol (e.g. SendGrid), and the data is stored in MySQL or PostgreSQL. The input is the user's registration information, and the output is sending a confirmation email and updating the account status.

[0712] Step 2: User Login

[0713] 1. The user enters their email address and password on the login page.

[0714] 2. The server checks the entered information against its database.

[0715] 3. If there is a match, the server issues a session ID to the user.

[0716] 4. The server redirects the user to the dashboard screen.

[0717] Specific operation: Redis is used for session management, and the session ID is generated using JWT. The input is the user's login information, and the output is the issuance of a session ID and a redirect to the dashboard screen.

[0718] Step 3: Submitting the generative model

[0719] 1. After the creator (user) logs in, they click the "Post Generative Model" button on the dashboard.

[0720] 2. The server displays a submission form, and the user enters and uploads the name, description, usage fee, and model file of the generated model.

[0721] 3. The server stores this information in a database and lists the new generative model on the store page.

[0722] Specific operation: Uploading is done using AWS S3 or Google Cloud Storage, and the input data is stored in a database. The input is the generative model information submitted by the user, and the output is saved in the database and listed on the store page.

[0723] Step 4: Buy a generative model

[0724] 1. The user adds the generated model they want to purchase to their cart on the store page.

[0725] 2. The user enters the required payment information and proceeds with the purchase.

[0726] 3. The server processes the payment and grants access to the user after the purchase is complete.

[0727] Specific operation: Stripe is used for payment processing, and access rights are updated in the database after payment is confirmed. The input is the user's payment information, and the output is granting access rights and a notification of payment completion.

[0728] Step 5: Running the generative model

[0729] 1. The user selects the generative model they purchased from their My Page.

[0730] 2. The server provides an interface for running the generative model, and the user enters input data (e.g., text prompts).

[0731] 3. When the user clicks the "Run" button, the server runs the generative model and generates the content.

[0732] 4. The server saves the generated content to storage and provides a download link to the user.

[0733] Specific operation: TensorFlow or PyTorch is used to run the generative model, and the generated content is stored in AWS S3 or Google Cloud Storage. The input is the user's prompt data, and the output is the generated content and its access link.

[0734] Step 6: Reward Distribution

[0735] 1. The server periodically aggregates the usage status of the generative model.

[0736] 2. The server calculates the creator's reward and reflects it in the creator's account.

[0737] 3. The creator will process the withdrawal if necessary.

[0738] 4. The server processes the withdrawal request and transfers the reward to the creator.

[0739] Specific operation: Reward calculation is performed by collecting data from the database, and notifications are sent using an SMTP mail server. The input is the usage history of the generative model, and the output is the calculation and transfer of the creator's reward amount.

[0740] (Application example 1)

[0741] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0742] Conventional digital content generation systems require a lot of effort and specialized skills to post, buy, sell, and execute generative models, making them inaccessible to the general public. Furthermore, the scope of use of generative models is limited, making it difficult to apply them in virtual spaces. Therefore, there is a need for a system that improves the efficiency of digital content generation and enhances the convenience of virtual stores.

[0743] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0744] In this invention, the server includes: means for multiple users who post generative models to upload their own generative models; means for listing the generative models in a store; means for multiple other users who access the store to purchase generative models; means for executing the purchased generative models to generate digital content that can be used in a virtual store; means for making the generated digital content available for download; and means for calculating rewards based on the usage status of the generative models and allocating them to the users who posted the generative models. This makes it easy to generate and use digital content in a virtual store, enabling users to generate and utilize high-quality digital content without specialized skills.

[0745] A "generative model" refers to a model that uses machine learning algorithms to automatically generate new digital content from specific input data.

[0746] "User" refers to a user of the System who can post, purchase, and run Generative Models.

[0747] "Store" means the online platform through which Users can post, list, and purchase Generative Models.

[0748] A "virtual store" refers to a digital store that provides various services and products in a virtual space and that users can access.

[0749] "Digital content" refers to information in electronic media (images, text, audio, etc.) created using generative models.

[0750] "Means for posting" refers to the function that allows users to upload their own generative models to the server.

[0751] "Means for listing" refers to the function for displaying posted Generative Models in the Store.

[0752] "Means for purchasing" refers to the functionality that allows users to select a generative model from the store and complete the purchase process.

[0753] "Means for executing" refers to the functionality for generating digital content based on input data using the purchased Generative Model.

[0754] "Means for making available for download" refers to the functionality that allows users to obtain the generated digital content.

[0755] "Means for calculating and allocating rewards" refers to a function for calculating rewards based on the usage status of the generative model and distributing the rewards to the user who posted the generative model.

[0756] The system of this invention aims to streamline the process of posting, buying and selling Generative Models, and running them in a virtual store. Specifically, the server provides a set of functions that allow multiple users to post Generative Models, which other users can purchase, and generate digital content.

[0757] The server uses the following hardware and software: The server uses the Django framework and PostgreSQL as the database. TensorFlow and PyTorch are used to run the generative model. The front end is built using React.

[0758] User Registration and Login

[0759] User registration: The user accesses the server using a smartphone or head-mounted display and registers as a user. The server saves the entered information in a database and sends a confirmation email. The user clicks on the confirmation link to activate the account.

[0760] Login: A registered user enters a username and password on the login screen to access the server.

[0761] Submitting a Generative Model

[0762] Posting a Generative Model: A user of the Generative Model Creator logs in to the server and uploads the name, description, usage fee, and model file of the Generative Model by clicking the "Post a Generative Model" button on the dashboard. The server saves these in the database and lists them on the store page.

[0763] Purchasing and running generative models

[0764] Purchasing a Generative Model: A Generative Model user accesses the store page, adds the Generative Model to their cart, and completes the purchase process. The server verifies the payment information and grants the user access to the Generative Model.

[0765] Executing a Generative Model: To execute a purchased generative model, a user accesses their personal page, selects the generative model, and enters the necessary input data (such as text prompts and image settings). When the user clicks the "Execute" button, the server executes the generative model and generates digital content.

[0766] Downloading digital content

[0767] Make available for download: The generated digital content is stored by the server and a download link is provided to the user, who can then download the content from this link.

[0768] Reward distribution

[0769] Reward calculation and distribution: The server periodically compiles the usage status of the generative model and calculates the reward. This reward is distributed to the user who worked on the generative model and reflected in the user's account. The user can check the reward and withdraw it.

[0770] Specific examples

[0771] For example, if you want to generate your own avatar in a virtual store, you can create a custom avatar for yourself by inputting the following prompts into the generative AI model:

[0772] Please create an avatar with blue hair, almond-shaped eyes, and casual clothing.

[0773] In this way, users can quickly generate high-quality digital content without any specialized knowledge and use it in virtual stores. This system lowers the barrier to entry for digital content creation and enables the widespread use of generative models.

[0774] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0775] Step 1:

[0776] User Registration and Login

[0777] Input: User's registration information (username, email address, password).

[0778] Processing: The server saves this registration information in a database (PostgreSQL) and sends a confirmation email. Once the user clicks on the confirmation link, the account is activated.

[0779] Output: Activated user account information.

[0780] Step 2:

[0781] Submitting a Generative Model

[0782] Inputs: The name, description, usage fee, and model file of the Generative Model entered by the Generative Model creator.

[0783] Processing: The server saves the input data and uploaded model files to the database and lists them on the store page.

[0784] Output: Generated model information listed on the store page.

[0785] Step 3:

[0786] Purchasing Generative Models

[0787] Input: Purchase request from the Generative Model Consumer (selected Generative Model ID, payment information).

[0788] Processing: The server verifies the payment information and, if successful, stores the data in the database to grant access to the Generative Model User.

[0789] Output: Generated model access rights to the generated model consumer.

[0790] Step 4:

[0791] Running the generative model

[0792] Input: Prompt statements and configuration data entered by the user of the generative model.

[0793] Processing: The server runs the purchased generative model and generates digital content based on the input data (using TensorFlow or PyTorch).

[0794] Output: The generated digital content files.

[0795] Step 5:

[0796] Downloading digital content

[0797] Input: A request to download the generated digital content.

[0798] Processing: The server retrieves the generated digital content from storage and generates and provides a download link.

[0799] Output: A link for the user to download.

[0800] Step 6:

[0801] Reward calculation and allocation

[0802] Input: Usage data for the generative model (number of purchases and frequency of use).

[0803] Processing: The server calculates the reward based on this information and reflects it in the Generative Model Creator's account. The creator checks this and can withdraw the money if necessary.

[0804] Output: Reward amount and withdrawal information for the generative model creator.

[0805] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0806] This invention realizes optimal digital content generation based on user emotions by combining a store platform where generative models can be posted, traded, and executed with a user emotion engine. The invention provides a series of processes that allow users to easily post, trade, and execute generative models, and further improves the quality of generated content using the emotion engine.

[0807] User Registration and Login

[0808] First, the user accesses the server and registers. The server saves the entered registration information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated and the server updates the user status to "active."

[0809] Submitting a Generative Model

[0810] A user who has registered as a generative model creator logs in to the server and accesses the dashboard. The server provides a "Post Generative Model" button, and clicking this displays a form for submitting a generative model. The creator enters and uploads the name, description, usage fee, and model file of the generative model. The server receives this information, stores it in the database, and lists the new generative model on the store page.

[0811] Purchasing Generative Models

[0812] A user who has registered as a generative model user logs in to the server and accesses the store page. The server displays a list of available generative models, and the user adds the generative model of interest to the cart and proceeds with the purchase. The server processes the purchase, verifies the payment information, and then grants the user access rights.

[0813] Execution of generative models and generation of digital content

[0814] After logging in, a user who has purchased a generative model accesses their personal page and selects the model they wish to run from a list of generative models they have purchased. The server provides an interface for running the generative model and displays a screen for entering the necessary input data (e.g., text prompts, image settings, etc.). When the user provides the input data and clicks the "Run" button, the server runs the generative model and generates digital content based on the specified input data.

[0815] Furthermore, by using an emotion engine, it is possible to recognize the user's emotional state in real time and adjust the output of the generative model. This allows the generated content to be provided in a form that is more suited to the user's emotions. The generated content is stored on a server, and a download link is provided to the user. The user can download the generated content from the provided link.

[0816] Reward distribution

[0817] The server periodically aggregates the usage status of generative models and calculates the reward for the generative model creator. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and the server reflects this reward in the creator's account and notifies them later. The generative model creator can check the reward and withdraw it if necessary. The server processes the withdrawal request and transfers the reward to the creator.

[0818] Specific examples

[0819] Example 1: A generative model creator submits an image generation model

[0820] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[0821] 2. Creators click the "Post Generative Model" button and enter the name, description, usage fee, etc. of the image generation AI. They also select and upload the model file (e.g., .h5 file) required for image generation.

[0822] 3. The server receives the input data and uploaded files from the creator, stores them in the database, and adds a list of this AI model to the store page.

[0823] Example 2: When a user purchases and runs an image generation model

[0824] 1. The user accesses the server and checks the store page of the generated model.

[0825] 2. The user finds the image generation model they want to use, adds it to their cart, checks the items they need, and clicks the purchase button.

[0826] 3. The server processes the purchase and grants the user access to the purchased Generative Model.

[0827] 4. The user accesses the interface for running the AI ​​and enters prompts and other settings for the image they want to generate.

[0828] 5. The server receives the configuration and runs the generative model to generate the image.

[0829] 6. The server saves the generated image in storage and provides the user with a download link.

[0830] 7. The user obtains the generated image from the provided download link.

[0831] Example 3: Content generation using an emotion engine

[0832] 1. When purchasing a generative model with an emotion engine, the user selects the option to enable the emotion engine.

[0833] 2. The user accesses the server, checks the store page for the generative model, and configures the emotion engine for use.

[0834] 3. When a user runs a generative model with the emotion engine enabled, the server collects the user's emotion data in real time and adjusts the output of the generative model.

[0835] 4. Optimal digital content is generated and provided based on the user's emotions.

[0836] In this way, by combining the user's emotion engine, the present invention can realize more personalized digital content generation and improve the user experience.

[0837] The processing flow will be explained below.

[0838] User Registration and Login

[0839] Step 1:

[0840] User: Access the server and display the user registration screen.

[0841] Step 2:

[0842] Server: Displays a user registration form and prompts the user to enter required information such as name, email address, and password.

[0843] Step 3:

[0844] User: Enter the required information in the registration form and click the "Register" button.

[0845] Step 4:

[0846] Server: Stores the entered information in a database and sends a confirmation email to the user.

[0847] Step 5:

[0848] Users: Click the link in the confirmation email to activate their account.

[0849] Step 6:

[0850] Server: Checks for account activation and updates user status to "enabled".

[0851] Submitting a Generative Model

[0852] Step 1:

[0853] Generative model creator (user): After logging in, access the dashboard.

[0854] Step 2:

[0855] Server: Display the creator dashboard.

[0856] Step 3:

[0857] Generative Model Creator: Click the "Submit Generative Model" button in the dashboard.

[0858] Step 4:

[0859] Server: Display the generated model submission form.

[0860] Step 5:

[0861] Generative Model Creator: Enter and upload the generated model name, description, usage fee, and model file (e.g., .h5, .pth file).

[0862] Step 6:

[0863] Server: Receives entered information and uploaded files and stores them in a database and storage.

[0864] Step 7:

[0865] Server: Update the store page with the new generative model list.

[0866] Purchasing Generative Models

[0867] Step 1:

[0868] User: After logging in, access the store page.

[0869] Step 2:

[0870] Server: Display the store page and list the available generative models.

[0871] Step 3:

[0872] User: Selects the generative model they are interested in and clicks the "Add to Cart" button.

[0873] Step 4:

[0874] Server: Saves and displays the generative models added to the cart in a list.

[0875] Step 5:

[0876] User: Check the contents on the cart page and click the "Purchase" button.

[0877] Step 6:

[0878] Server: Processes purchases and verifies payment information.

[0879] Step 7:

[0880] Server: After confirming the payment, grant the user access to the generative model and update the database.

[0881] Execution of generative models and generation of digital content

[0882] Step 1:

[0883] User: After logging in, access My Page to view a list of generative models you have purchased.

[0884] Step 2:

[0885] Server: Displays My Page and provides a list of Generative Models to which the user has access.

[0886] Step 3:

[0887] User: Select the generative model you want to run and click the "Run" button.

[0888] Step 4:

[0889] Server: Displays the interface for running the generative model and displays the required input fields (e.g., text prompts, image settings, etc.).

[0890] Step 5:

[0891] User: Enter the required input data and click the "Execute" button.

[0892] Step 6:

[0893] Server: Receives input data and executes it by calling the generative model in the backend.

[0894] Step 7:

[0895] Server: Stores the generated digital content in storage and provides users with a download link.

[0896] Step 8:

[0897] User: Downloads the generated digital content from the provided download link.

[0898] Content generation using emotion engine

[0899] Step 1:

[0900] Users: When purchasing a generative model with an emotion engine, select the option to enable the emotion engine.

[0901] Step 2:

[0902] User: Accesses the server, checks the store page for the generative model, and configures the emotion engine.

[0903] Step 3:

[0904] Server: Reflects the emotion engine settings and displays an option to enable the emotion engine on the generative model execution screen.

[0905] Step 4:

[0906] User: Enables the emotion engine and provides input data to run the generative model.

[0907] Step 5:

[0908] Server: Analyzes user emotion data in real time using an emotion engine and feeds the results back to the generative model.

[0909] Step 6:

[0910] Server: Executes the generative model based on data from the emotion engine and generates optimal digital content.

[0911] Step 7:

[0912] Server: Stores the generated digital content in storage and provides users with a download link.

[0913] Step 8:

[0914] User: Downloads the generated digital content from the provided download link.

[0915] Reward distribution

[0916] Step 1:

[0917] Server: Periodically aggregates the usage status of the generative model.

[0918] Step 2:

[0919] Server: Calculates the reward amount for the generative model creator based on the aggregated data.

[0920] Step 3:

[0921] Server: Reflects the calculated rewards in the creator's account and notifies them.

[0922] Step 4:

[0923] Generative model creator (user): Check the reward amount on the dashboard and withdraw it if necessary.

[0924] Step 5:

[0925] Server: Processes withdrawal requests and transfers rewards to the creator's designated account.

[0926] The above are the specific processing steps of the invention that combines an emotion engine. This system provides more personalized digital content and improves the user experience by adjusting the output of the generative model to adapt to the user's emotions.

[0927] Example 2

[0928] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0929] Conventional digital content generation systems using generative models have problems such as a lack of personalization in the user experience and difficulty in improving the quality of content. Furthermore, there is a need for improved transparency and efficiency in the distribution of rewards to generative model creators.

[0930] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to upload their own generative model, a means for listing the generative model in a store, a means for other users who access the store to purchase generative models, a means for executing the purchased generative model to generate digital content, a means for making the generated digital content available for download, a means for calculating a reward based on the usage status of the generative model and distributing it to the user who posted the generative model, and a means for the user to adjust the output of the generative model in real time using an emotion engine. This enables the generation of more personalized, high-quality digital content based on user emotions. Furthermore, reward distribution to creators can be transparent and efficient.

[0931] A "User" is an individual or organization that uses the system and can upload, purchase, and run Generative Models.

[0932] A "generative model" is a computational tool that uses machine learning techniques to generate new digital content based on specific input data.

[0933] "Uploading" is the act of a generative model creator sending and saving their generative model to a server.

[0934] A "store" is an online platform that resides on a server and lists generative models, allowing users to purchase them.

[0935] "Listing" refers to the process and procedure of placing an uploaded Generative Model on the Store.

[0936] "Purchase" refers to the act of a user paying a fee for a generative model offered in the store and obtaining the right to use it.

[0937] "Execution" refers to the process of generating specific digital content using the Generative Model purchased by the user.

[0938] "Digital content" is data created by the execution of a generative model, and can take the form of images, text, audio, etc.

[0939] "Making it available for download" means providing the generated digital content as a link or file so that users can save it to their own devices.

[0940] "Remuneration" means the compensation a Generative Model Creator receives based on the use or sale of a Generative Model.

[0941] An "emotion engine" is a technology for detecting the user's emotional state and adjusting the output of a generative model.

[0942] These definitions are used to clarify the technical scope of the patent and to provide an understanding of the specific content of the invention.

[0943] This invention is a system that combines a store platform where users can post, buy, sell, and execute generative models with a user emotion engine. The invention facilitates the process of generating generative models and realizes optimal digital content generation based on user emotions.

[0944] User Registration and Login

[0945] First, the user accesses the server from their own device and registers as a user. The server receives the registration information (name, email address, password, etc.) entered by the user and stores it in a database. The server then sends a confirmation email to the user, and when the user clicks on the link, the account is activated. After completing registration, the user can log in by entering their email address and password on the login screen and access the dashboard.

[0946] Submitting a Generative Model

[0947] A user who has registered as a generative model creator logs in to the server and clicks the "Post Generative Model" button on the dashboard. The creator enters the name, description, usage fee, and model file (e.g., .h5 file) of the generative model and uploads it to the server. The server saves this information in the database and lists the new generative model on the store page.

[0948] Purchasing Generative Models

[0949] A user who has registered as a Generative Model user logs in to the server and accesses the store page. The server displays a list of available Generative Models, and the user adds the Generative Model of interest to the cart and proceeds with the purchase. When the user enters payment information and clicks the submit button, the server processes the payment and grants the user access to the purchased Generative Model.

[0950] Execution of generative models and generation of digital content

[0951] After purchasing a generative model, a user logs in to the server, accesses their personal page, and selects the model they wish to run from a list of purchased generative models. The server displays the generative model execution interface, and the user provides the required input data (e.g., text prompts, image settings, etc.). The user clicks the "Run" button, and the server runs the generative model based on the input data and generates digital content. The generated content is stored on the server, and a download link is provided to the user.

[0952] Use of emotion engine

[0953] When using the emotion engine, the server recognizes the user's emotional state in real time and adjusts the output of the generative model, making the generated content more personalized and optimized for the user's emotions.

[0954] Reward distribution

[0955] The server periodically aggregates the usage status of generative models and calculates the reward for generative model creators. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and is reflected in the creator's account. Creators can request a withdrawal under certain conditions, and the server processes this request and transfers the reward to the creator.

[0956] A concrete example of this system is a case where a generative model creator enters a prompt such as, "Generate a promotional image for a new product. The product is a small, portable speaker. Obtain positive feedback from user reviews and generate an image with a positive atmosphere based on that." A user can purchase this image generation model, enter a similar prompt, and run it to generate a promotional image that meets their needs.

[0957] As described above, this invention improves the user experience and enables the generation of high-quality digital content by combining the posting, buying and selling, and execution of generative models with an emotion engine.

[0958] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0959] Step 1: User Registration

[0960] Input: The user accesses the server from their device and enters registration information such as their name, email address, and password.

[0961] Data processing and output: The server receives the entered information, stores it in a database, and sends a confirmation email to the user.

[0962] What happens: The server validates the input information and, if there are no problems, saves it to the database and sends the user an email containing a confirmation link.

[0963] Step 2: User authentication

[0964] Input: User clicks on the link in the confirmation email.

[0965] Data processing and output: The server checks the validity of the link and updates the user status to "valid".

[0966] Specific operation: The server analyzes the link in the email, retrieves the corresponding user account information from the database, and updates it.

[0967] Step 3: User Login

[0968] Input: The user enters their email address and password on the login screen.

[0969] Data processing and output: The server checks the entered information against the database, and if correct, authenticates the user and redirects them to the dashboard.

[0970] Specific behavior: The server checks the entered email address and password, and if successful, starts a session for the user.

[0971] Step 4: Submitting the generative model

[0972] Input: The Generative Model creator accesses the dashboard and enters and uploads the name, description, usage fee, and model file (e.g., .h5 file) of the Generative Model.

[0973] Data processing and output: The server receives this information, stores it in a database, and lists the new generative model on the store page.

[0974] What happens: The server validates the information submitted in the form, records it in a database, and updates the listing on the store page.

[0975] Step 5: Buy a generative model

[0976] Input: A user adds a generative model of interest to their cart on the store page and proceeds to checkout.

[0977] Data processing and output: The server receives payment information, processes the transaction, and grants the user access to the purchased generative model.

[0978] What happens: The server validates the payment information and processes the payment. If successful, it grants access to the user's account and sends a notification.

[0979] Step 6: Execute the generative model and generate digital content

[0980] Input: The user accesses My Page, selects the generative model they wish to run from the purchased models, and provides the required input data (e.g., text prompts, image settings, etc.).

[0981] Data processing and output: The server runs the generative model based on the input data to generate digital content, which is then stored on the server and a download link is provided to the user.

[0982] Specific operation: The server allocates computing resources to run the generative model and runs the model based on the input data. The generated content is saved to storage and a link is sent to the user.

[0983] Step 7: Use the Emotion Engine

[0984] Input: User enables the emotion engine and runs the generative model.

[0985] Data processing and output: The server recognizes the user's emotional state in real time and adjusts the output of the generative model, thereby generating digital content optimized for the user.

[0986] Specific operation: The server analyzes the user's emotional data using an emotion recognition algorithm and adjusts the parameters of the generative model based on the results.

[0987] Step 8: Reward Distribution

[0988] Input: The server periodically aggregates the usage of the generative model.

[0989] Data processing and output: The server calculates rewards based on the number of times the generative model is used and the amount of sales, and reflects them in the creator's account.

[0990] Specific operation: The server periodically collects usage data from the database and calculates the reward amount using the reward calculation algorithm. The calculation results are reflected in the creator's account and notified.

[0991] This clarifies the specific operations performed at each processing step, making it easier to understand the flow of the entire system.

[0992] (Application example 2)

[0993] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0994] Conventional digital content generation systems using generative models have difficulty providing personalized advertising content because they do not take into account the user's emotional state. Furthermore, there has been no effective means of collecting real-time emotional data from users and generating advertising content that reflects this data.

[0995] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: a means for multiple users who post generative models to upload their own generative models; a means for listing the generative models in a store; a means for multiple other users who access the store to purchase generative models; a means for executing the purchased generative models to generate digital content; a means for making the generated digital content available for download; a means for calculating a reward based on the usage status of the generative model and distributing it to the user who posted the generative model; and a means for generating digital content by combining an emotion engine that recognizes the user's emotional state in real time and adjusts the output of the generative model. This makes it possible to generate advertising content that is appropriate for the user's emotional state.

[0996] A "generative model" is an algorithm or machine learning model that generates specific digital content submitted by users.

[0997] The "Store" is an online platform where generative models are listed and available for purchase by other users.

[0998] "Digital content" refers to electronic media content such as images, text, and videos created using generative models.

[0999] An "emotion engine" is a system that recognizes the user's real-time emotional state and adjusts the output of the generative model based on that data.

[1000] "User" refers to anyone who uses the system, including creators who post generative models and users who purchase those generative models and generate content.

[1001] "Reward" is calculated based on the usage of the generative model and is paid to the user who posted the generative model.

[1002] This invention provides optimal digital content generation based on user emotions by combining a user's emotion engine with a store platform where users can post, trade, and execute generative models. This system is implemented using smart glasses and a server.

[1003] The system program is structured as follows:

[1004] 1. User Registration and Login

[1005] The server saves the user's registered information in a database and sends a confirmation email, which the user must click to activate their account.

[1006] Software used: Database management system (e.g., MySQL)

[1007] 2. Submitting a Generative Model

[1008] Users who are registered as generative model creators log in to the server and upload their models using the generative model submission form. The model information and files are stored in the database and listed on the store page.

[1009] Software used: Cloud storage system (e.g. Amazon S3)

[1010] 3. Purchasing a Generative Model

[1011] The server displays a list of generative models on a store page, allowing users to add them to their cart and purchase them. After completing the purchase process, access rights are granted.

[1012] Software used: Electronic payment systems (e.g., Stripe)

[1013] 4. Execution of generative models and generation of digital content

[1014] An interface is provided for running purchased generative models. The user provides input data such as prompt statements and executes the generative model.

[1015] Software used: Generative AI models (e.g., GPT-3)

[1016] 5. Use of Emotion Engine

[1017] The camera built into the smart glasses analyzes the user's facial expressions in real time, and the emotion engine acquires emotional data.

[1018] Hardware used: Built-in camera in smart glasses

[1019] Software used: Facial expression recognition library (e.g., OpenCV), emotion analysis model

[1020] 6. Emotional content optimization

[1021] The emotion engine adjusts the output of the generative model based on the user's emotional state to generate more personalized digital content.

[1022] Software used: Sentiment analysis model

[1023] 7. Reward Distribution

[1024] The server calculates rewards based on the usage of the generative model and pays them to the generative model creator.

[1025] Software used: Remuneration calculation system

[1026] For example:

[1027] If the user's emotion is "joy":

[1028] Prompt: "Create a fun and cheerful video ad."

[1029] Based on the prompt, the server generates an advertisement for a home electronic device featuring a smiling family enjoying a holiday.

[1030] If the user's emotion is "sadness":

[1031] Prompt: "Generate a quiet ad that provides warmth and comfort."

[1032] Based on this prompt, the server generates a soothing product advertisement that conveys a gentle message accompanied by quiet music.

[1033] In this way, the system of the present invention can improve the user experience by generating more suitable digital content based on the user's real-time emotional data.

[1034] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1035] Step 1:

[1036] User registration and login.

[1037] The server receives the user's registration information (e.g., name, email address, password) and stores it in a database. It then sends a confirmation email and the user activates their account by clicking the link in the confirmation email. This updates the user status to "active."

[1038] Input: User registration information (name, email address, password)

[1039] Output: Send confirmation email, update user status

[1040] Step 2:

[1041] Posting generative models.

[1042] Users who have registered as generative model creators log in to the server using their terminal and enter and upload the model file (e.g., .h5 file) and necessary information (e.g., model name, description, and usage fee) into the generative model submission form. The server receives this data, stores it in the database, and lists it as a new generative model on the store page.

[1043] Input: Generated model file, model name, description, usage fee

[1044] Output: Save to database, add list to store page

[1045] Step 3:

[1046] Purchasing generative models.

[1047] Other users who access the store log in to the server and check the list of Generative Models. The user adds the Generative Model they want to purchase to their cart and completes the payment process. The server verifies the payment information and completes the purchase. The server grants the user access to the purchased Generative Model.

[1048] Input: Add to Cart, Payment Information

[1049] Output: Purchase procedure completed, access granted

[1050] Step 4:

[1051] Execution of generative models and digital content generation.

[1052] To run a purchased generative model, a user logs in and accesses their personal page. They select the model they want to run and provide input data (e.g., a prompt). The server runs the generative model and generates digital content based on the specified input data.

[1053] Input: Input data such as prompt statements

[1054] Output: Generated digital content

[1055] Step 5:

[1056] Leveraging the emotion engine.

[1057] The smart glasses' built-in camera captures the user's facial expression data in real time, and the emotion engine analyzes this data to recognize the user's emotional state.

[1058] Input: User's facial expression data

[1059] Output: Real-time emotional state

[1060] Step 6:

[1061] Emotion-based content optimization.

[1062] Based on the user's emotional data acquired by the emotion engine, the server adjusts the output of the generative model to generate digital content more suitable for the user. For example, if the user is in a "joy" emotional state, it generates a bright and cheerful advertisement. If the user is in a "sad" emotional state, it generates a quiet advertisement that provides warmth and comfort.

[1063] Input: Real-time emotional state, prompt sentence

[1064] Output: Emotion-based digital content

[1065] Step 7:

[1066] Providing generated digital content.

[1067] The server stores the generated digital content in storage and provides a download link to the user, who then downloads the generated content via the link.

[1068] Input: Generated digital content

[1069] Output: Download link

[1070] Step 8:

[1071] Distribution of rewards.

[1072] The server periodically compiles the usage status of generative models and calculates the reward for the generative model creator. The reward is determined based on the number of times the generative model is used and the amount of sales, and is reflected in the creator's account. The creator can then perform a withdrawal procedure, and the server processes the withdrawal request and transfers the reward to the creator.

[1073] Input: Generative model usage data

[1074] Output: Reward calculation, notification to creator

[1075] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1076] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1077] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1078] [Third embodiment]

[1079] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1080] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1081] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1082] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1083] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1084] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1085] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1086] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1087] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1088] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1089] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1090] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1091] This invention provides a store platform where users can post, buy, sell, and execute generative models, thereby reducing the cost and effort required for digital content creation and resolving the lack of skills required for using generative models. In particular, the invention provides a series of processes that allow users to easily post, buy, sell, and execute generative models.

[1092] User Registration and Login

[1093] First, the user accesses the server and registers. The server saves the entered registration information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated and the server updates the user status to "active."

[1094] Submitting a Generative Model

[1095] A user who has registered as a generative model creator logs in to the server and accesses the dashboard. The server provides a "Post Generative Model" button, and clicking this displays a form for submitting a generative model. The creator enters and uploads the name, description, usage fee, and model file of the generative model. The server receives this information, stores it in the database, and lists the new generative model on the store page.

[1096] Purchasing Generative Models

[1097] A user who has registered as a generative model user logs in to the server and accesses the store page. The server displays a list of available generative models, and the user adds the generative model of interest to the cart and proceeds with the purchase. The server processes the purchase, verifies the payment information, and then grants the user access rights.

[1098] Execution of generative models and generation of digital content

[1099] After logging in, a user who has purchased a generative model accesses their personal page and selects the model they wish to run from a list of generative models they have purchased. The server provides an interface for running the generative model, displaying a screen for entering the necessary input data (e.g., text prompts, image settings, etc.). When the user provides the input data and clicks the "Run" button, the server runs the generative model and generates digital content based on the specified input data. The generated content is stored on the server, and a download link is provided to the user. The user can download the generated content from the provided link.

[1100] Reward distribution

[1101] The server periodically aggregates the usage status of generative models and calculates the reward for the generative model creator. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and the server reflects this reward in the creator's account and notifies them later. The generative model creator can check the reward and withdraw it if necessary. The server processes the withdrawal request and transfers the reward to the creator.

[1102] Specific examples

[1103] Example 1: A generative model creator submits an image generation model

[1104] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[1105] 2. Creators click the "Post Generative Model" button and enter the name, description, usage fee, etc. of the image generation AI. They also select and upload the model file (e.g., .h5 file) required for image generation.

[1106] 3. The server receives the input data and uploaded files from the creator, stores them in the database, and adds a list of this AI model to the store page.

[1107] Example 2: When a user purchases and runs an image generation model

[1108] 1. The user accesses the server and checks the store page of the generated model.

[1109] 2. The user finds the image generation model they want to use, adds it to their cart, checks the items they need, and clicks the purchase button.

[1110] 3. The server processes the purchase and grants the user access to the purchased Generative Model.

[1111] 4. The user accesses the interface for running the AI ​​and enters prompts and other settings for the image they want to generate.

[1112] 5. The server receives the configuration and runs the generative model to generate the image.

[1113] 6. The server saves the generated image in storage and provides the user with a download link.

[1114] 7. The user obtains the generated image from the provided download link.

[1115] This will enable companies and local governments to quickly generate high-quality digital content without specialized skills, and generative model creators will be able to earn revenue by utilizing their technology.

[1116] The processing flow will be explained below.

[1117] User Registration and Login

[1118] Step 1:

[1119] User: Access the server and display the user registration screen.

[1120] Step 2:

[1121] Server: Displays a user registration form and prompts the user to enter required information such as name, email address, and password.

[1122] Step 3:

[1123] User: Enter the required information in the registration form and click the "Register" button.

[1124] Step 4:

[1125] Server: Stores the entered information in a database and sends a confirmation email to the user.

[1126] Step 5:

[1127] Users: Click the link in the confirmation email to activate their account.

[1128] Step 6:

[1129] Server: Checks for account activation and updates user status to "enabled".

[1130] Submitting a Generative Model

[1131] Step 1:

[1132] Generative AI Creator (User): After logging in, access the dashboard.

[1133] Step 2:

[1134] Server: Display the creator dashboard.

[1135] Step 3:

[1136] Generative AI Creator: Click the "Post Generative Model" button in the dashboard.

[1137] Step 4:

[1138] Server: Display the generated model submission form.

[1139] Step 5:

[1140] Generation AI Creator: Enter and upload the AI ​​model name, description, usage fee, and model file (e.g., .h5, .pth file).

[1141] Step 6:

[1142] Server: Receives entered information and uploaded files and stores them in a database and storage.

[1143] Step 7:

[1144] Server: Update the store page with the new generative model list.

[1145] Purchasing Generative Models

[1146] Step 1:

[1147] User: After logging in, access the store page.

[1148] Step 2:

[1149] Server: Display the store page and list the available generative models.

[1150] Step 3:

[1151] User: Selects the generative model they are interested in and clicks the "Add to Cart" button.

[1152] Step 4:

[1153] Server: Saves and displays the generative models added to the cart in a list.

[1154] Step 5:

[1155] User: Check the contents on the cart page and click the "Purchase" button.

[1156] Step 6:

[1157] Server: Processes purchases and verifies payment information.

[1158] Step 7:

[1159] Server: After confirming the payment, grant the user access to the generative model and update the database.

[1160] Execution of generative models and generation of digital content

[1161] Step 1:

[1162] User: After logging in, access My Page to view a list of generative models you have purchased.

[1163] Step 2:

[1164] Server: Displays My Page and provides a list of Generative Models to which the user has access.

[1165] Step 3:

[1166] User: Select the generative model you want to run and click the "Run" button.

[1167] Step 4:

[1168] Server: Displays the interface for running the generative model and displays the required input fields (e.g., text prompts, image settings, etc.).

[1169] Step 5:

[1170] User: Enter the required input data and click the "Execute" button.

[1171] Step 6:

[1172] Server: Receives input data and executes it by calling the generative model in the backend.

[1173] Step 7:

[1174] Server: Stores the generated digital content in storage and provides users with a download link.

[1175] Step 8:

[1176] User: Downloads the generated digital content from the provided download link.

[1177] Reward distribution

[1178] Step 1:

[1179] Server: Periodically aggregates the usage status of the generative model.

[1180] Step 2:

[1181] Server: Calculates the reward amount for the generative model creator based on the aggregated data.

[1182] Step 3:

[1183] Server: Reflects the calculated rewards in the creator's account and notifies them.

[1184] Step 4:

[1185] Generating AI Creator (User): Check the reward amount on the dashboard and withdraw it if necessary.

[1186] Step 5:

[1187] Server: Processes withdrawal requests and transfers rewards to the creator's designated account.

[1188] The above is the specific flow of the program's processing. This system provides a series of processes that allow users to easily post, buy, sell, and execute generative models, solving the challenges of digital content creation.

[1189] Example 1

[1190] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1191] In modern digital content creation, the revenue model of posting one's own generative models and allowing other users to purchase and execute them is becoming increasingly common. However, existing systems have faced challenges such as a lack of user skills and difficulty in operation. Furthermore, the effort and cost involved in managing generative models and distributing rewards are also issues. It is necessary to solve these issues and provide a user-friendly platform that significantly reduces the effort required for posting, buying and selling, and executing generative models.

[1192] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1193] In this invention, the server includes: means for multiple users who post generative models to upload their own generative models; means for adding the generative models to a list and making them accessible; means for multiple users who access the list to purchase generative models; means for executing the purchased generative models to generate content; means for saving the generated content and making it available for download; means for calculating rewards based on the usage status of the generative models and distributing them to the users who posted the generative models; means for performing user authentication regarding the posting, purchase, and execution of the generative models; and means for sending notifications during the processes of posting, purchasing, and executing the generative models. This makes it easy for the server to manage and use generative models, enabling users to generate high-quality digital content and earn revenue.

[1194] A "generative model" is a machine learning algorithm or artificial intelligence program that automatically generates content based on user-provided data.

[1195] A "User" is an individual or organization that accesses the System and submits, purchases, runs, or uses Generative Models.

[1196] "Means for posting generative models" is a function that allows users to upload and register their own generative models in the system.

[1197] The "means of adding to a list and making it accessible" is a function that makes the posted Generative Model public and makes it available for other users to view and purchase.

[1198] "Means to purchase" refers to the functionality that allows users to pay a fee to access a generative model and obtain usage rights.

[1199] The "means for executing and generating content" is a function for executing a generative model purchased by a user and generating content based on specific data.

[1200] "Means for storing and making available for download" refers to a function for storing generated content in the system and allowing users to download it.

[1201] The "means for calculating and allocating rewards" is a function for calculating rewards for contributors based on the usage of the generative model and allocating those rewards appropriately.

[1202] "Means for user authentication" refers to a function for verifying the identity of a user and appropriately controlling access to a system.

[1203] The "means for sending notifications" is a function for notifying users of necessary information during each process of posting, purchasing, and executing a Generative Model.

[1204] The present invention provides a store platform for using generative models, and is a system that allows users to easily post, purchase, and run generative models. The system includes a means for posting generative models, a means for adding generative models to a list and making them accessible, a means for purchasing generative models, a means for running generative models to generate digital content, a means for saving the generated content and making it available for download, a means for calculating and allocating rewards based on the usage status of the generative models, a means for user authentication, and a means for sending notifications.

[1205] Hardware and software used

[1206] Servers: This system is operated using multiple servers. These servers include common web servers, database servers, and storage systems. Specific examples of servers include AWS EC2 instances and Google Cloud Compute Engine.

[1207] Database: A relational database management system (RDBMS) is used to store user information, generative model information, purchase history, execution history, etc. Examples include MySQL and PostgreSQL.

[1208] Storage system: Use cloud-based storage to store generative model files and generated content. Examples include AWS S3, Google Cloud Storage, etc.

[1209] Front-end: The user interface is built using JavaScript libraries such as React.

[1210] Backend: The application logic is implemented using Python web frameworks such as Flask or Django.

[1211] Payment Gateway: You use a third-party payment service, such as Stripe, to process payments from your users.

[1212] Notification system: Notifications to users are sent using an SMTP mail server (e.g., SendGrid).

[1213] Specific example explanation

[1214] Example 1: Posting a generative model

[1215] We will explain the case where a generative model creator (user) posts his or her own generative model.

[1216] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[1217] 2. After logging in, the creator clicks the "Submit Generative Model" button on the dashboard. At this time, the server displays the submission form.

[1218] 3. The creator enters the name, description, and usage fee of the generative model, and uploads the generative model file (e.g., the .h5 file for an image generative model).

[1219] 4. The server receives this information and stores it in the database. After that, the new generative model is listed on the store page.

[1220] Example prompt:

[1221] To create a new image generation model, please provide the following information: model name, description, usage fee, and model file (e.g., .h5 file).

[1222] Example 2: Purchasing and running a generative model

[1223] This section explains the process when a Generative Model user purchases and runs a Generative Model.

[1224] 1. The user accesses the server and checks the store page of the generated model.

[1225] 2. Find the generative model you want to use, add it to your cart, and check out. The server verifies your payment information and completes the purchase.

[1226] 3. After the purchase is complete, the user accesses their My Page and selects the model to run from the list of generative models they have purchased.

[1227] 4. The server provides an execution interface for the generated model, and the user inputs prompt statements and configuration data.

[1228] 5. When the user clicks the "Run" button, the server executes the generative model and generates the digital content.

[1229] 6. The generated content is stored on the server and a download link is provided to the user.

[1230] Example prompt:

[1231] To run the image generation model, please enter the following information: a text prompt for the image you want to generate, and image settings (e.g., resolution).

[1232] As described above, this system can efficiently carry out a series of processes, from managing generative models to generating and distributing digital content, and calculating and allocating rewards.

[1233] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1234] Step 1: Registering a user

[1235] 1. A user enters their name, email address, and password on a registration page.

[1236] 2. The server receives this information and stores it in a database.

[1237] 3. The server will send a confirmation email to the email address you entered.

[1238] 4. When the user clicks on the link in the confirmation email, the server updates the account status to "active."

[1239] Specific behavior: The server sends a confirmation email using the SMTP protocol (e.g. SendGrid), and the data is stored in MySQL or PostgreSQL. The input is the user's registration information, and the output is sending a confirmation email and updating the account status.

[1240] Step 2: User Login

[1241] 1. The user enters their email address and password on the login page.

[1242] 2. The server checks the entered information against its database.

[1243] 3. If there is a match, the server issues a session ID to the user.

[1244] 4. The server redirects the user to the dashboard screen.

[1245] Specific operation: Redis is used for session management, and the session ID is generated using JWT. The input is the user's login information, and the output is the issuance of a session ID and a redirect to the dashboard screen.

[1246] Step 3: Submitting the generative model

[1247] 1. After the creator (user) logs in, they click the "Post Generative Model" button on the dashboard.

[1248] 2. The server displays a submission form, and the user enters and uploads the name, description, usage fee, and model file of the generated model.

[1249] 3. The server stores this information in a database and lists the new generative model on the store page.

[1250] Specific operation: Uploading is done using AWS S3 or Google Cloud Storage, and the input data is stored in a database. The input is the generative model information submitted by the user, and the output is saved in the database and listed on the store page.

[1251] Step 4: Buy a generative model

[1252] 1. The user adds the generated model they want to purchase to their cart on the store page.

[1253] 2. The user enters the required payment information and proceeds with the purchase.

[1254] 3. The server processes the payment and grants access to the user after the purchase is complete.

[1255] Specific operation: Stripe is used for payment processing, and access rights are updated in the database after payment is confirmed. The input is the user's payment information, and the output is granting access rights and a notification of payment completion.

[1256] Step 5: Running the generative model

[1257] 1. The user selects the generative model they purchased from their My Page.

[1258] 2. The server provides an interface for running the generative model, and the user enters input data (e.g., text prompts).

[1259] 3. When the user clicks the "Run" button, the server runs the generative model and generates the content.

[1260] 4. The server saves the generated content to storage and provides a download link to the user.

[1261] Specific operation: TensorFlow or PyTorch is used to run the generative model, and the generated content is stored in AWS S3 or Google Cloud Storage. The input is the user's prompt data, and the output is the generated content and its access link.

[1262] Step 6: Reward Distribution

[1263] 1. The server periodically aggregates the usage status of the generative model.

[1264] 2. The server calculates the creator's reward and reflects it in the creator's account.

[1265] 3. The creator will process the withdrawal if necessary.

[1266] 4. The server processes the withdrawal request and transfers the reward to the creator.

[1267] Specific operation: Reward calculation is performed by collecting data from the database, and notifications are sent using an SMTP mail server. The input is the usage history of the generative model, and the output is the calculation and transfer of the creator's reward amount.

[1268] (Application example 1)

[1269] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1270] Conventional digital content generation systems require a lot of effort and specialized skills to post, buy, sell, and execute generative models, making them inaccessible to the general public. Furthermore, the scope of use of generative models is limited, making it difficult to apply them in virtual spaces. Therefore, there is a need for a system that improves the efficiency of digital content generation and the convenience of virtual stores.

[1271] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1272] In this invention, the server includes: means for multiple users who post generative models to upload their own generative models; means for listing the generative models in a store; means for multiple other users who access the store to purchase generative models; means for executing the purchased generative models to generate digital content that can be used in a virtual store; means for making the generated digital content available for download; and means for calculating rewards based on the usage status of the generative models and allocating them to the users who posted the generative models. This makes it easy to generate and use digital content in a virtual store, enabling users to generate and utilize high-quality digital content without specialized skills.

[1273] A "generative model" refers to a model that uses machine learning algorithms to automatically generate new digital content from specific input data.

[1274] "User" refers to a user of the System who can post, purchase, and run Generative Models.

[1275] "Store" means the online platform through which Users can post, list, and purchase Generative Models.

[1276] A "virtual store" refers to a digital store that provides various services and products in a virtual space and that users can access.

[1277] "Digital content" refers to information in electronic media (images, text, audio, etc.) created using generative models.

[1278] "Means for posting" refers to the function that allows users to upload their own generative models to the server.

[1279] "Means for listing" refers to the function for displaying posted Generative Models in the Store.

[1280] "Means for purchasing" refers to the functionality that allows users to select a generative model from the store and complete the purchase process.

[1281] "Means for executing" refers to the functionality for generating digital content based on input data using the purchased Generative Model.

[1282] "Means for making available for download" refers to the functionality that allows users to obtain the generated digital content.

[1283] "Means for calculating and allocating rewards" refers to a function for calculating rewards based on the usage status of the generative model and distributing the rewards to the user who posted the generative model.

[1284] The system of this invention aims to streamline the process of posting, buying and selling Generative Models, and running them in a virtual store. Specifically, the server provides a set of functions that allow multiple users to post Generative Models, which other users can purchase, and generate digital content.

[1285] The server uses the following hardware and software: The server uses the Django framework and PostgreSQL as the database. TensorFlow and PyTorch are used to run the generative model. The front end is built using React.

[1286] User Registration and Login

[1287] User registration: The user accesses the server using a smartphone or head-mounted display and registers as a user. The server saves the entered information in a database and sends a confirmation email. The user clicks on the confirmation link to activate the account.

[1288] Login: A registered user enters a username and password on the login screen to access the server.

[1289] Submitting a Generative Model

[1290] Posting a Generative Model: A user of the Generative Model Creator logs in to the server and uploads the name, description, usage fee, and model file of the Generative Model by clicking the "Post a Generative Model" button on the dashboard. The server saves these in the database and lists them on the store page.

[1291] Purchasing and running generative models

[1292] Purchasing a Generative Model: A Generative Model user accesses the store page, adds the Generative Model to their cart, and completes the purchase process. The server verifies the payment information and grants the user access to the Generative Model.

[1293] Executing a Generative Model: To execute a purchased generative model, a user accesses their personal page, selects the generative model, and enters the necessary input data (such as text prompts and image settings). When the user clicks the "Execute" button, the server executes the generative model and generates digital content.

[1294] Downloading digital content

[1295] Make available for download: The generated digital content is stored by the server and a download link is provided to the user, who can then download the content from this link.

[1296] Reward distribution

[1297] Reward calculation and distribution: The server periodically compiles the usage status of the generative model and calculates the reward. This reward is distributed to the user who worked on the generative model and reflected in the user's account. The user can check the reward and withdraw it.

[1298] Specific examples

[1299] For example, if you want to generate your own avatar in a virtual store, you can create a custom avatar for yourself by inputting the following prompts into the generative AI model:

[1300] Please create an avatar with blue hair, almond-shaped eyes, and casual clothing.

[1301] In this way, users can quickly generate high-quality digital content without any specialized knowledge and use it in virtual stores. This system lowers the barrier to entry for digital content creation and enables the widespread use of generative models.

[1302] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1303] Step 1:

[1304] User Registration and Login

[1305] Input: User's registration information (username, email address, password).

[1306] Processing: The server saves this registration information in a database (PostgreSQL) and sends a confirmation email. Once the user clicks on the confirmation link, the account is activated.

[1307] Output: Activated user account information.

[1308] Step 2:

[1309] Submitting a Generative Model

[1310] Inputs: The name, description, usage fee, and model file of the Generative Model entered by the Generative Model creator.

[1311] Processing: The server saves the input data and uploaded model files to the database and lists them on the store page.

[1312] Output: Generated model information listed on the store page.

[1313] Step 3:

[1314] Purchasing Generative Models

[1315] Input: Purchase request from the Generative Model Consumer (selected Generative Model ID, payment information).

[1316] Processing: The server verifies the payment information and, if successful, stores the data in the database to grant access to the Generative Model User.

[1317] Output: Generated model access rights to the generated model consumer.

[1318] Step 4:

[1319] Running the generative model

[1320] Input: Prompt statements and configuration data entered by the user of the generative model.

[1321] Processing: The server runs the purchased generative model and generates digital content based on the input data (using TensorFlow or PyTorch).

[1322] Output: The generated digital content files.

[1323] Step 5:

[1324] Downloading digital content

[1325] Input: A request to download the generated digital content.

[1326] Processing: The server retrieves the generated digital content from storage and generates and provides a download link.

[1327] Output: A link for the user to download.

[1328] Step 6:

[1329] Reward calculation and allocation

[1330] Input: Usage data for the generative model (number of purchases and frequency of use).

[1331] Processing: The server calculates the reward based on this information and reflects it in the Generative Model Creator's account. The creator checks this and can withdraw the money if necessary.

[1332] Output: Reward amount and withdrawal information for the generative model creator.

[1333] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1334] This invention realizes optimal digital content generation based on user emotions by combining a store platform where generative models can be posted, traded, and executed with a user emotion engine. The invention provides a series of processes that allow users to easily post, trade, and execute generative models, and further improves the quality of generated content using the emotion engine.

[1335] User Registration and Login

[1336] First, the user accesses the server and registers. The server saves the entered registration information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated and the server updates the user status to "active."

[1337] Submitting a Generative Model

[1338] A user who has registered as a generative model creator logs in to the server and accesses the dashboard. The server provides a "Post Generative Model" button, and clicking this displays a form for submitting a generative model. The creator enters and uploads the name, description, usage fee, and model file of the generative model. The server receives this information, stores it in the database, and lists the new generative model on the store page.

[1339] Purchasing Generative Models

[1340] A user who has registered as a generative model user logs in to the server and accesses the store page. The server displays a list of available generative models, and the user adds the generative model of interest to the cart and proceeds with the purchase. The server processes the purchase, verifies the payment information, and then grants the user access rights.

[1341] Execution of generative models and generation of digital content

[1342] After logging in, a user who has purchased a generative model accesses their personal page and selects the model they wish to run from a list of generative models they have purchased. The server provides an interface for running the generative model and displays a screen for entering the necessary input data (e.g., text prompts, image settings, etc.). When the user provides the input data and clicks the "Run" button, the server runs the generative model and generates digital content based on the specified input data.

[1343] Furthermore, by using an emotion engine, it is possible to recognize the user's emotional state in real time and adjust the output of the generative model. This allows the generated content to be provided in a form that is more suited to the user's emotions. The generated content is stored on a server, and a download link is provided to the user. The user can download the generated content from the provided link.

[1344] Reward distribution

[1345] The server periodically aggregates the usage status of generative models and calculates the reward for the generative model creator. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and the server reflects this reward in the creator's account and notifies them later. The generative model creator can check the reward and withdraw it if necessary. The server processes the withdrawal request and transfers the reward to the creator.

[1346] Specific examples

[1347] Example 1: A generative model creator submits an image generation model

[1348] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[1349] 2. Creators click the "Post Generative Model" button and enter the name, description, usage fee, etc. of the image generation AI. They also select and upload the model file (e.g., .h5 file) required for image generation.

[1350] 3. The server receives the input data and uploaded files from the creator, stores them in the database, and adds a list of this AI model to the store page.

[1351] Example 2: When a user purchases and runs an image generation model

[1352] 1. The user accesses the server and checks the store page of the generated model.

[1353] 2. The user finds the image generation model they want to use, adds it to their cart, checks the items they need, and clicks the purchase button.

[1354] 3. The server processes the purchase and grants the user access to the purchased Generative Model.

[1355] 4. The user accesses the interface for running the AI ​​and enters prompts and other settings for the image they want to generate.

[1356] 5. The server receives the configuration and runs the generative model to generate the image.

[1357] 6. The server saves the generated image in storage and provides the user with a download link.

[1358] 7. The user obtains the generated image from the provided download link.

[1359] Example 3: Content generation using an emotion engine

[1360] 1. When purchasing a generative model with an emotion engine, the user selects the option to enable the emotion engine.

[1361] 2. The user accesses the server, checks the store page for the generative model, and configures the emotion engine for use.

[1362] 3. When a user runs a generative model with the emotion engine enabled, the server collects the user's emotion data in real time and adjusts the output of the generative model.

[1363] 4. Optimal digital content is generated and provided based on the user's emotions.

[1364] In this way, by combining the user's emotion engine, the present invention can realize more personalized digital content generation and improve the user experience.

[1365] The processing flow will be explained below.

[1366] User Registration and Login

[1367] Step 1:

[1368] User: Access the server and display the user registration screen.

[1369] Step 2:

[1370] Server: Displays a user registration form and prompts the user to enter required information such as name, email address, and password.

[1371] Step 3:

[1372] User: Enter the required information in the registration form and click the "Register" button.

[1373] Step 4:

[1374] Server: Stores the entered information in a database and sends a confirmation email to the user.

[1375] Step 5:

[1376] Users: Click the link in the confirmation email to activate their account.

[1377] Step 6:

[1378] Server: Checks for account activation and updates user status to "enabled".

[1379] Submitting a Generative Model

[1380] Step 1:

[1381] Generative model creator (user): After logging in, access the dashboard.

[1382] Step 2:

[1383] Server: Display the creator dashboard.

[1384] Step 3:

[1385] Generative Model Creator: Click the "Submit Generative Model" button in the dashboard.

[1386] Step 4:

[1387] Server: Display the generated model submission form.

[1388] Step 5:

[1389] Generative Model Creator: Enter and upload the generated model name, description, usage fee, and model file (e.g., .h5, .pth file).

[1390] Step 6:

[1391] Server: Receives entered information and uploaded files and stores them in a database and storage.

[1392] Step 7:

[1393] Server: Update the store page with the new generative model list.

[1394] Purchasing Generative Models

[1395] Step 1:

[1396] User: After logging in, access the store page.

[1397] Step 2:

[1398] Server: Display the store page and list the available generative models.

[1399] Step 3:

[1400] User: Selects the generative model they are interested in and clicks the "Add to Cart" button.

[1401] Step 4:

[1402] Server: Saves and displays the generative models added to the cart in a list.

[1403] Step 5:

[1404] User: Check the contents on the cart page and click the "Purchase" button.

[1405] Step 6:

[1406] Server: Processes purchases and verifies payment information.

[1407] Step 7:

[1408] Server: After confirming the payment, grant the user access to the generative model and update the database.

[1409] Execution of generative models and generation of digital content

[1410] Step 1:

[1411] User: After logging in, access My Page to view a list of generative models you have purchased.

[1412] Step 2:

[1413] Server: Displays My Page and provides a list of Generative Models to which the user has access.

[1414] Step 3:

[1415] User: Select the generative model you want to run and click the "Run" button.

[1416] Step 4:

[1417] Server: Displays the interface for running the generative model and displays the required input fields (e.g., text prompts, image settings, etc.).

[1418] Step 5:

[1419] User: Enter the required input data and click the "Execute" button.

[1420] Step 6:

[1421] Server: Receives input data and executes it by calling the generative model in the backend.

[1422] Step 7:

[1423] Server: Stores the generated digital content in storage and provides users with a download link.

[1424] Step 8:

[1425] User: Downloads the generated digital content from the provided download link.

[1426] Content generation using emotion engine

[1427] Step 1:

[1428] Users: When purchasing a generative model with an emotion engine, select the option to enable the emotion engine.

[1429] Step 2:

[1430] User: Accesses the server, checks the store page for the generative model, and configures the emotion engine.

[1431] Step 3:

[1432] Server: Reflects the emotion engine settings and displays an option to enable the emotion engine on the generative model execution screen.

[1433] Step 4:

[1434] User: Enables the emotion engine and provides input data to run the generative model.

[1435] Step 5:

[1436] Server: Analyzes user emotion data in real time using an emotion engine and feeds the results back to the generative model.

[1437] Step 6:

[1438] Server: Executes the generative model based on data from the emotion engine and generates optimal digital content.

[1439] Step 7:

[1440] Server: Stores the generated digital content in storage and provides users with a download link.

[1441] Step 8:

[1442] User: Downloads the generated digital content from the provided download link.

[1443] Reward distribution

[1444] Step 1:

[1445] Server: Periodically aggregates the usage status of the generative model.

[1446] Step 2:

[1447] Server: Calculates the reward amount for the generative model creator based on the aggregated data.

[1448] Step 3:

[1449] Server: Reflects the calculated rewards in the creator's account and notifies them.

[1450] Step 4:

[1451] Generative model creator (user): Check the reward amount on the dashboard and withdraw it if necessary.

[1452] Step 5:

[1453] Server: Processes withdrawal requests and transfers rewards to the creator's designated account.

[1454] The above are the specific processing steps of the invention that combines an emotion engine. This system provides more personalized digital content and improves the user experience by adjusting the output of the generative model to adapt to the user's emotions.

[1455] Example 2

[1456] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1457] Conventional digital content generation systems using generative models have problems such as a lack of personalization in the user experience and difficulty in improving the quality of content. Furthermore, there is a need for improved transparency and efficiency in the distribution of rewards to generative model creators.

[1458] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to upload their own generative model, a means for listing the generative model in a store, a means for other users who access the store to purchase generative models, a means for executing the purchased generative model to generate digital content, a means for making the generated digital content available for download, a means for calculating a reward based on the usage status of the generative model and distributing it to the user who posted the generative model, and a means for the user to adjust the output of the generative model in real time using an emotion engine. This enables the generation of more personalized, high-quality digital content based on user emotions. Furthermore, reward distribution to creators can be transparent and efficient.

[1459] A "User" is an individual or organization that uses the system and can upload, purchase, and run Generative Models.

[1460] A "generative model" is a computational tool that uses machine learning techniques to generate new digital content based on specific input data.

[1461] "Uploading" is the act of a generative model creator sending and saving their generative model to a server.

[1462] A "store" is an online platform that resides on a server and lists generative models, allowing users to purchase them.

[1463] "Listing" refers to the process and procedure of placing an uploaded Generative Model on the Store.

[1464] "Purchase" refers to the act of a user paying a fee for a generative model offered in the store and obtaining the right to use it.

[1465] "Execution" refers to the process of generating specific digital content using the Generative Model purchased by the user.

[1466] "Digital content" is data created by the execution of a generative model, and can take the form of images, text, audio, etc.

[1467] "Making it available for download" means providing the generated digital content as a link or file so that users can save it to their own devices.

[1468] "Remuneration" means the compensation a Generative Model Creator receives based on the use or sale of a Generative Model.

[1469] An "emotion engine" is a technology for detecting the user's emotional state and adjusting the output of a generative model.

[1470] These definitions are used to clarify the technical scope of the patent and to provide an understanding of the specific content of the invention.

[1471] This invention is a system that combines a store platform where users can post, buy, sell, and execute generative models with a user emotion engine. The invention facilitates the process of generating generative models and realizes optimal digital content generation based on user emotions.

[1472] User Registration and Login

[1473] First, the user accesses the server from their own device and registers as a user. The server receives the registration information (name, email address, password, etc.) entered by the user and stores it in a database. The server then sends a confirmation email to the user, and when the user clicks on the link, the account is activated. After completing registration, the user can log in by entering their email address and password on the login screen and access the dashboard.

[1474] Submitting a Generative Model

[1475] A user who has registered as a generative model creator logs in to the server and clicks the "Post Generative Model" button on the dashboard. The creator enters the name, description, usage fee, and model file (e.g., .h5 file) of the generative model and uploads it to the server. The server saves this information in the database and lists the new generative model on the store page.

[1476] Purchasing Generative Models

[1477] A user who has registered as a Generative Model user logs in to the server and accesses the store page. The server displays a list of available Generative Models, and the user adds the Generative Model of interest to the cart and proceeds with the purchase. When the user enters payment information and clicks the submit button, the server processes the payment and grants the user access to the purchased Generative Model.

[1478] Execution of generative models and generation of digital content

[1479] After purchasing a generative model, a user logs in to the server, accesses their personal page, and selects the model they wish to run from a list of purchased generative models. The server displays the generative model execution interface, and the user provides the required input data (e.g., text prompts, image settings, etc.). The user clicks the "Run" button, and the server runs the generative model based on the input data and generates digital content. The generated content is stored on the server, and a download link is provided to the user.

[1480] Use of emotion engine

[1481] When using the emotion engine, the server recognizes the user's emotional state in real time and adjusts the output of the generative model, making the generated content more personalized and optimized for the user's emotions.

[1482] Reward distribution

[1483] The server periodically aggregates the usage status of generative models and calculates the reward for generative model creators. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and is reflected in the creator's account. Creators can request a withdrawal under certain conditions, and the server processes this request and transfers the reward to the creator.

[1484] A concrete example of this system is a case where a generative model creator enters a prompt such as, "Generate a promotional image for a new product. The product is a small, portable speaker. Obtain positive feedback from user reviews and generate an image with a positive atmosphere based on that." A user can purchase this image generation model, enter a similar prompt, and run it to generate a promotional image that meets their needs.

[1485] As described above, this invention improves the user experience and enables the generation of high-quality digital content by combining the posting, buying and selling, and execution of generative models with an emotion engine.

[1486] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1487] Step 1: User Registration

[1488] Input: The user accesses the server from their device and enters registration information such as their name, email address, and password.

[1489] Data processing and output: The server receives the entered information, stores it in a database, and sends a confirmation email to the user.

[1490] What happens: The server validates the input information and, if there are no problems, saves it to the database and sends the user an email containing a confirmation link.

[1491] Step 2: User authentication

[1492] Input: User clicks on the link in the confirmation email.

[1493] Data processing and output: The server checks the validity of the link and updates the user status to "valid".

[1494] Specific operation: The server analyzes the link in the email, retrieves the corresponding user account information from the database, and updates it.

[1495] Step 3: User Login

[1496] Input: The user enters their email address and password on the login screen.

[1497] Data processing and output: The server checks the entered information against the database, and if correct, authenticates the user and redirects them to the dashboard.

[1498] Specific behavior: The server checks the entered email address and password, and if successful, starts a session for the user.

[1499] Step 4: Submitting the generative model

[1500] Input: The Generative Model creator accesses the dashboard and enters and uploads the name, description, usage fee, and model file (e.g., .h5 file) of the Generative Model.

[1501] Data processing and output: The server receives this information, stores it in a database, and lists the new generative model on the store page.

[1502] What happens: The server validates the information submitted in the form, records it in a database, and updates the listing on the store page.

[1503] Step 5: Buy a generative model

[1504] Input: A user adds a generative model of interest to their cart on the store page and proceeds to checkout.

[1505] Data processing and output: The server receives payment information, processes the transaction, and grants the user access to the purchased generative model.

[1506] What happens: The server validates the payment information and processes the payment. If successful, it grants access to the user's account and sends a notification.

[1507] Step 6: Execute the generative model and generate digital content

[1508] Input: The user accesses My Page, selects the generative model they wish to run from the purchased models, and provides the required input data (e.g., text prompts, image settings, etc.).

[1509] Data processing and output: The server runs the generative model based on the input data to generate digital content, which is then stored on the server and a download link is provided to the user.

[1510] Specific operation: The server allocates computing resources to run the generative model and runs the model based on the input data. The generated content is saved to storage and a link is sent to the user.

[1511] Step 7: Use the Emotion Engine

[1512] Input: User enables the emotion engine and runs the generative model.

[1513] Data processing and output: The server recognizes the user's emotional state in real time and adjusts the output of the generative model, thereby generating digital content optimized for the user.

[1514] Specific operation: The server analyzes the user's emotional data using an emotion recognition algorithm and adjusts the parameters of the generative model based on the results.

[1515] Step 8: Reward Distribution

[1516] Input: The server periodically aggregates the usage of the generative model.

[1517] Data processing and output: The server calculates rewards based on the number of times the generative model is used and the amount of sales, and reflects them in the creator's account.

[1518] Specific operation: The server periodically collects usage data from the database and calculates the reward amount using the reward calculation algorithm. The calculation results are reflected in the creator's account and notified.

[1519] This clarifies the specific operations performed at each processing step, making it easier to understand the flow of the entire system.

[1520] (Application example 2)

[1521] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1522] Conventional digital content generation systems using generative models have difficulty providing personalized advertising content because they do not take into account the user's emotional state. Furthermore, there has been no effective means of collecting real-time emotional data from users and generating advertising content that reflects this data.

[1523] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: a means for multiple users who post generative models to upload their own generative models; a means for listing the generative models in a store; a means for multiple other users who access the store to purchase generative models; a means for executing the purchased generative models to generate digital content; a means for making the generated digital content available for download; a means for calculating a reward based on the usage status of the generative model and distributing it to the user who posted the generative model; and a means for generating digital content by combining an emotion engine that recognizes the user's emotional state in real time and adjusts the output of the generative model. This makes it possible to generate advertising content that is appropriate for the user's emotional state.

[1524] A "generative model" is an algorithm or machine learning model that generates specific digital content submitted by users.

[1525] The "Store" is an online platform where generative models are listed and available for purchase by other users.

[1526] "Digital content" refers to electronic media content such as images, text, and videos created using generative models.

[1527] An "emotion engine" is a system that recognizes the user's real-time emotional state and adjusts the output of the generative model based on that data.

[1528] "User" refers to anyone who uses the system, including creators who post generative models and users who purchase those generative models and generate content.

[1529] "Reward" is calculated based on the usage of the generative model and is paid to the user who posted the generative model.

[1530] This invention provides optimal digital content generation based on user emotions by combining a user's emotion engine with a store platform where users can post, trade, and execute generative models. This system is implemented using smart glasses and a server.

[1531] The system program is structured as follows:

[1532] 1. User Registration and Login

[1533] The server saves the user's registered information in a database and sends a confirmation email, which the user must click to activate their account.

[1534] Software used: Database management system (e.g., MySQL)

[1535] 2. Submitting a Generative Model

[1536] Users who are registered as generative model creators log in to the server and upload their models using the generative model submission form. The model information and files are stored in the database and listed on the store page.

[1537] Software used: Cloud storage system (e.g. Amazon S3)

[1538] 3. Purchasing a Generative Model

[1539] The server displays a list of generative models on a store page, allowing users to add them to their cart and purchase them. After completing the purchase process, access rights are granted.

[1540] Software used: Electronic payment systems (e.g., Stripe)

[1541] 4. Execution of generative models and generation of digital content

[1542] An interface is provided for running purchased generative models. The user provides input data such as prompt statements and executes the generative model.

[1543] Software used: Generative AI models (e.g., GPT-3)

[1544] 5. Use of Emotion Engine

[1545] The camera built into the smart glasses analyzes the user's facial expressions in real time, and the emotion engine acquires emotional data.

[1546] Hardware used: Built-in camera in smart glasses

[1547] Software used: Facial expression recognition library (e.g., OpenCV), emotion analysis model

[1548] 6. Emotional content optimization

[1549] The emotion engine adjusts the output of the generative model based on the user's emotional state to generate more personalized digital content.

[1550] Software used: Sentiment analysis model

[1551] 7. Reward Distribution

[1552] The server calculates rewards based on the usage of the generative model and pays them to the generative model creator.

[1553] Software used: Remuneration calculation system

[1554] For example:

[1555] If the user's emotion is "joy":

[1556] Prompt: "Create a fun and cheerful video ad."

[1557] Based on the prompt, the server generates an advertisement for a home electronic device featuring a smiling family enjoying a holiday.

[1558] If the user's emotion is "sadness":

[1559] Prompt: "Generate a quiet ad that provides warmth and comfort."

[1560] Based on this prompt, the server generates a soothing product advertisement that conveys a gentle message accompanied by quiet music.

[1561] In this way, the system of the present invention can improve the user experience by generating more suitable digital content based on the user's real-time emotional data.

[1562] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1563] Step 1:

[1564] User registration and login.

[1565] The server receives the user's registration information (e.g., name, email address, password) and stores it in a database. It then sends a confirmation email and the user activates their account by clicking the link in the confirmation email. This updates the user status to "active."

[1566] Input: User registration information (name, email address, password)

[1567] Output: Send confirmation email, update user status

[1568] Step 2:

[1569] Posting generative models.

[1570] Users who have registered as generative model creators log in to the server using their terminal and enter and upload the model file (e.g., .h5 file) and necessary information (e.g., model name, description, and usage fee) into the generative model submission form. The server receives this data, stores it in the database, and lists it as a new generative model on the store page.

[1571] Input: Generated model file, model name, description, usage fee

[1572] Output: Save to database, add list to store page

[1573] Step 3:

[1574] Purchasing generative models.

[1575] Other users who access the store log in to the server and check the list of Generative Models. The user adds the Generative Model they want to purchase to their cart and completes the payment process. The server verifies the payment information and completes the purchase. The server grants the user access to the purchased Generative Model.

[1576] Input: Add to Cart, Payment Information

[1577] Output: Purchase procedure completed, access granted

[1578] Step 4:

[1579] Execution of generative models and digital content generation.

[1580] To run a purchased generative model, a user logs in and accesses their personal page. They select the model they want to run and provide input data (e.g., a prompt). The server runs the generative model and generates digital content based on the specified input data.

[1581] Input: Input data such as prompt statements

[1582] Output: Generated digital content

[1583] Step 5:

[1584] Leveraging the emotion engine.

[1585] The smart glasses' built-in camera captures the user's facial expression data in real time, and the emotion engine analyzes this data to recognize the user's emotional state.

[1586] Input: User's facial expression data

[1587] Output: Real-time emotional state

[1588] Step 6:

[1589] Emotion-based content optimization.

[1590] Based on the user's emotional data acquired by the emotion engine, the server adjusts the output of the generative model to generate digital content more suitable for the user. For example, if the user is in a "joy" emotional state, it generates a bright and cheerful advertisement. If the user is in a "sad" emotional state, it generates a quiet advertisement that provides warmth and comfort.

[1591] Input: Real-time emotional state, prompt sentence

[1592] Output: Emotion-based digital content

[1593] Step 7:

[1594] Providing generated digital content.

[1595] The server stores the generated digital content in storage and provides a download link to the user, who then downloads the generated content via the link.

[1596] Input: Generated digital content

[1597] Output: Download link

[1598] Step 8:

[1599] Distribution of rewards.

[1600] The server periodically compiles the usage status of generative models and calculates the reward for the generative model creator. The reward is determined based on the number of times the generative model is used and the amount of sales, and is reflected in the creator's account. The creator can then perform a withdrawal procedure, and the server processes the withdrawal request and transfers the reward to the creator.

[1601] Input: Generative model usage data

[1602] Output: Reward calculation, notification to creator

[1603] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1604] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1605] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1606] [Fourth embodiment]

[1607] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1608] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1609] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1610] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1611] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1612] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1613] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1614] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1615] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1616] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1617] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1618] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1619] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1620] This invention provides a store platform where users can post, buy, sell, and execute generative models, thereby reducing the cost and effort required for digital content creation and resolving the lack of skills required for using generative models. In particular, the invention provides a series of processes that allow users to easily post, buy, sell, and execute generative models.

[1621] User Registration and Login

[1622] First, the user accesses the server and registers. The server saves the entered registration information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated and the server updates the user status to "active."

[1623] Submitting a Generative Model

[1624] A user who has registered as a generative model creator logs in to the server and accesses the dashboard. The server provides a "Post Generative Model" button, and clicking this displays a form for submitting a generative model. The creator enters and uploads the name, description, usage fee, and model file of the generative model. The server receives this information, stores it in the database, and lists the new generative model on the store page.

[1625] Purchasing Generative Models

[1626] A user who has registered as a generative model user logs in to the server and accesses the store page. The server displays a list of available generative models, and the user adds the generative model of interest to the cart and proceeds with the purchase. The server processes the purchase, verifies the payment information, and then grants the user access rights.

[1627] Execution of generative models and generation of digital content

[1628] After logging in, a user who has purchased a generative model accesses their personal page and selects the model they wish to run from a list of generative models they have purchased. The server provides an interface for running the generative model, displaying a screen for entering the necessary input data (e.g., text prompts, image settings, etc.). When the user provides the input data and clicks the "Run" button, the server runs the generative model and generates digital content based on the specified input data. The generated content is stored on the server, and a download link is provided to the user. The user can download the generated content from the provided link.

[1629] Reward distribution

[1630] The server periodically aggregates the usage status of generative models and calculates the reward for the generative model creator. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and the server reflects this reward in the creator's account and notifies them later. The generative model creator can check the reward and withdraw it if necessary. The server processes the withdrawal request and transfers the reward to the creator.

[1631] Specific examples

[1632] Example 1: A generative model creator submits an image generation model

[1633] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[1634] 2. Creators click the "Post Generative Model" button and enter the name, description, usage fee, etc. of the image generation AI. They also select and upload the model file (e.g., .h5 file) required for image generation.

[1635] 3. The server receives the input data and uploaded files from the creator, stores them in the database, and adds a list of this AI model to the store page.

[1636] Example 2: When a user purchases and runs an image generation model

[1637] 1. The user accesses the server and checks the store page of the generated model.

[1638] 2. The user finds the image generation model they want to use, adds it to their cart, checks the items they need, and clicks the purchase button.

[1639] 3. The server processes the purchase and grants the user access to the purchased Generative Model.

[1640] 4. The user accesses the interface for running the AI ​​and enters prompts and other settings for the image they want to generate.

[1641] 5. The server receives the configuration and runs the generative model to generate the image.

[1642] 6. The server saves the generated image in storage and provides the user with a download link.

[1643] 7. The user obtains the generated image from the provided download link.

[1644] This will enable companies and local governments to quickly generate high-quality digital content without specialized skills, and generative model creators will be able to earn revenue by utilizing their technology.

[1645] The processing flow will be explained below.

[1646] User Registration and Login

[1647] Step 1:

[1648] User: Access the server and display the user registration screen.

[1649] Step 2:

[1650] Server: Displays a user registration form and prompts the user to enter required information such as name, email address, and password.

[1651] Step 3:

[1652] User: Enter the required information in the registration form and click the "Register" button.

[1653] Step 4:

[1654] Server: Stores the entered information in a database and sends a confirmation email to the user.

[1655] Step 5:

[1656] Users: Click the link in the confirmation email to activate their account.

[1657] Step 6:

[1658] Server: Checks for account activation and updates user status to "enabled".

[1659] Submitting a Generative Model

[1660] Step 1:

[1661] Generative AI Creator (User): After logging in, access the dashboard.

[1662] Step 2:

[1663] Server: Display the creator dashboard.

[1664] Step 3:

[1665] Generative AI Creator: Click the "Post Generative Model" button in the dashboard.

[1666] Step 4:

[1667] Server: Display the generated model submission form.

[1668] Step 5:

[1669] Generation AI Creator: Enter and upload the AI ​​model name, description, usage fee, and model file (e.g., .h5, .pth file).

[1670] Step 6:

[1671] Server: Receives entered information and uploaded files and stores them in a database and storage.

[1672] Step 7:

[1673] Server: Update the store page with the new generative model list.

[1674] Purchasing Generative Models

[1675] Step 1:

[1676] User: After logging in, access the store page.

[1677] Step 2:

[1678] Server: Display the store page and list the available generative models.

[1679] Step 3:

[1680] User: Selects the generative model they are interested in and clicks the "Add to Cart" button.

[1681] Step 4:

[1682] Server: Saves and displays the generative models added to the cart in a list.

[1683] Step 5:

[1684] User: Check the contents on the cart page and click the "Purchase" button.

[1685] Step 6:

[1686] Server: Processes purchases and verifies payment information.

[1687] Step 7:

[1688] Server: After confirming the payment, grant the user access to the generative model and update the database.

[1689] Execution of generative models and generation of digital content

[1690] Step 1:

[1691] User: After logging in, access My Page to view a list of generative models you have purchased.

[1692] Step 2:

[1693] Server: Displays My Page and provides a list of Generative Models to which the user has access.

[1694] Step 3:

[1695] User: Select the generative model you want to run and click the "Run" button.

[1696] Step 4:

[1697] Server: Displays the interface for running the generative model and displays the required input fields (e.g., text prompts, image settings, etc.).

[1698] Step 5:

[1699] User: Enter the required input data and click the "Execute" button.

[1700] Step 6:

[1701] Server: Receives input data and executes it by calling the generative model in the backend.

[1702] Step 7:

[1703] Server: Stores the generated digital content in storage and provides users with a download link.

[1704] Step 8:

[1705] User: Downloads the generated digital content from the provided download link.

[1706] Reward distribution

[1707] Step 1:

[1708] Server: Periodically aggregates the usage status of the generative model.

[1709] Step 2:

[1710] Server: Calculates the reward amount for the generative model creator based on the aggregated data.

[1711] Step 3:

[1712] Server: Reflects the calculated rewards in the creator's account and notifies them.

[1713] Step 4:

[1714] Generating AI Creator (User): Check the reward amount on the dashboard and withdraw it if necessary.

[1715] Step 5:

[1716] Server: Processes withdrawal requests and transfers rewards to the creator's designated account.

[1717] The above is the specific flow of the program's processing. This system provides a series of processes that allow users to easily post, buy, sell, and execute generative models, solving the challenges of digital content creation.

[1718] Example 1

[1719] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1720] In modern digital content creation, the revenue model of posting one's own generative models and allowing other users to purchase and execute them is becoming increasingly common. However, existing systems have faced challenges such as a lack of user skills and difficulty in operation. Furthermore, the effort and cost involved in managing generative models and distributing rewards are also issues. It is necessary to solve these issues and provide a user-friendly platform that significantly reduces the effort required for posting, buying and selling, and executing generative models.

[1721] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1722] In this invention, the server includes: means for multiple users who post generative models to upload their own generative models; means for adding the generative models to a list and making them accessible; means for multiple users who access the list to purchase generative models; means for executing the purchased generative models to generate content; means for saving the generated content and making it available for download; means for calculating rewards based on the usage status of the generative models and distributing them to the users who posted the generative models; means for performing user authentication regarding the posting, purchase, and execution of the generative models; and means for sending notifications during the processes of posting, purchasing, and executing the generative models. This makes it easy for the server to manage and use generative models, enabling users to generate high-quality digital content and earn revenue.

[1723] A "generative model" is a machine learning algorithm or artificial intelligence program that automatically generates content based on user-provided data.

[1724] A "User" is an individual or organization that accesses the System and submits, purchases, runs, or uses Generative Models.

[1725] "Means for posting generative models" is a function that allows users to upload and register their own generative models in the system.

[1726] The "means of adding to a list and making it accessible" is a function that makes the posted Generative Model public and makes it available for other users to view and purchase.

[1727] "Means to purchase" refers to the functionality that allows users to pay a fee to access a generative model and obtain usage rights.

[1728] The "means for executing and generating content" is a function for executing a generative model purchased by a user and generating content based on specific data.

[1729] "Means for storing and making available for download" refers to a function for storing generated content in the system and allowing users to download it.

[1730] The "means for calculating and allocating rewards" is a function for calculating rewards for contributors based on the usage of the generative model and allocating those rewards appropriately.

[1731] "Means for user authentication" refers to a function for verifying the identity of a user and appropriately controlling access to a system.

[1732] The "means for sending notifications" is a function for notifying users of necessary information during each process of posting, purchasing, and executing a Generative Model.

[1733] The present invention provides a store platform for using generative models, and is a system that allows users to easily post, purchase, and run generative models. The system includes a means for posting generative models, a means for adding generative models to a list and making them accessible, a means for purchasing generative models, a means for running generative models to generate digital content, a means for saving the generated content and making it available for download, a means for calculating and allocating rewards based on the usage status of the generative models, a means for user authentication, and a means for sending notifications.

[1734] Hardware and software used

[1735] Servers: This system is operated using multiple servers. These servers include common web servers, database servers, and storage systems. Specific examples of servers include AWS EC2 instances and Google Cloud Compute Engine.

[1736] Database: A relational database management system (RDBMS) is used to store user information, generative model information, purchase history, execution history, etc. Examples include MySQL and PostgreSQL.

[1737] Storage system: Use cloud-based storage to store generative model files and generated content. Examples include AWS S3, Google Cloud Storage, etc.

[1738] Front-end: The user interface is built using JavaScript libraries such as React.

[1739] Backend: The application logic is implemented using Python web frameworks such as Flask or Django.

[1740] Payment Gateway: You use a third-party payment service, such as Stripe, to process payments from your users.

[1741] Notification system: Notifications to users are sent using an SMTP mail server (e.g., SendGrid).

[1742] Specific example explanation

[1743] Example 1: Posting a generative model

[1744] We will explain the case where a generative model creator (user) posts his or her own generative model.

[1745] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[1746] 2. After logging in, the creator clicks the "Submit Generative Model" button on the dashboard. At this time, the server displays the submission form.

[1747] 3. The creator enters the name, description, and usage fee of the generative model, and uploads the generative model file (e.g., the .h5 file for an image generative model).

[1748] 4. The server receives this information and stores it in the database. After that, the new generative model is listed on the store page.

[1749] Example prompt:

[1750] To create a new image generation model, please provide the following information: model name, description, usage fee, and model file (e.g., .h5 file).

[1751] Example 2: Purchasing and running a generative model

[1752] This section explains the process when a Generative Model user purchases and runs a Generative Model.

[1753] 1. The user accesses the server and checks the store page of the generated model.

[1754] 2. Find the generative model you want to use, add it to your cart, and check out. The server verifies your payment information and completes the purchase.

[1755] 3. After the purchase is complete, the user accesses their My Page and selects the model to run from the list of generative models they have purchased.

[1756] 4. The server provides an execution interface for the generated model, and the user inputs prompt statements and configuration data.

[1757] 5. When the user clicks the "Run" button, the server executes the generative model and generates the digital content.

[1758] 6. The generated content is stored on the server and a download link is provided to the user.

[1759] Example prompt:

[1760] To run the image generation model, please enter the following information: a text prompt for the image you want to generate, and image settings (e.g., resolution).

[1761] As described above, this system can efficiently carry out a series of processes, from managing generative models to generating and distributing digital content, and calculating and allocating rewards.

[1762] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1763] Step 1: Registering a user

[1764] 1. A user enters their name, email address, and password on a registration page.

[1765] 2. The server receives this information and stores it in a database.

[1766] 3. The server will send a confirmation email to the email address you entered.

[1767] 4. When the user clicks on the link in the confirmation email, the server updates the account status to "active."

[1768] Specific behavior: The server sends a confirmation email using the SMTP protocol (e.g. SendGrid), and the data is stored in MySQL or PostgreSQL. The input is the user's registration information, and the output is sending a confirmation email and updating the account status.

[1769] Step 2: User Login

[1770] 1. The user enters their email address and password on the login page.

[1771] 2. The server checks the entered information against its database.

[1772] 3. If there is a match, the server issues a session ID to the user.

[1773] 4. The server redirects the user to the dashboard screen.

[1774] Specific operation: Redis is used for session management, and the session ID is generated using JWT. The input is the user's login information, and the output is the issuance of a session ID and a redirect to the dashboard screen.

[1775] Step 3: Submitting the generative model

[1776] 1. After the creator (user) logs in, they click the "Post Generative Model" button on the dashboard.

[1777] 2. The server displays a submission form, and the user enters and uploads the name, description, usage fee, and model file of the generated model.

[1778] 3. The server stores this information in a database and lists the new generative model on the store page.

[1779] Specific operation: Uploading is done using AWS S3 or Google Cloud Storage, and the input data is stored in a database. The input is the generative model information submitted by the user, and the output is saved in the database and listed on the store page.

[1780] Step 4: Buy a generative model

[1781] 1. The user adds the generated model they want to purchase to their cart on the store page.

[1782] 2. The user enters the required payment information and proceeds with the purchase.

[1783] 3. The server processes the payment and grants access to the user after the purchase is complete.

[1784] Specific operation: Stripe is used for payment processing, and access rights are updated in the database after payment is confirmed. The input is the user's payment information, and the output is granting access rights and a notification of payment completion.

[1785] Step 5: Running the generative model

[1786] 1. The user selects the generative model they purchased from their My Page.

[1787] 2. The server provides an interface for running the generative model, and the user enters input data (e.g., text prompts).

[1788] 3. When the user clicks the "Run" button, the server runs the generative model and generates the content.

[1789] 4. The server saves the generated content to storage and provides a download link to the user.

[1790] Specific operation: TensorFlow or PyTorch is used to run the generative model, and the generated content is stored in AWS S3 or Google Cloud Storage. The input is the user's prompt data, and the output is the generated content and its access link.

[1791] Step 6: Reward Distribution

[1792] 1. The server periodically aggregates the usage status of the generative model.

[1793] 2. The server calculates the creator's reward and reflects it in the creator's account.

[1794] 3. The creator will process the withdrawal if necessary.

[1795] 4. The server processes the withdrawal request and transfers the reward to the creator.

[1796] Specific operation: Reward calculation is performed by collecting data from the database, and notifications are sent using an SMTP mail server. The input is the usage history of the generative model, and the output is the calculation and transfer of the creator's reward amount.

[1797] (Application example 1)

[1798] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1799] Conventional digital content generation systems require a lot of effort and specialized skills to post, buy, sell, and execute generative models, making them inaccessible to the general public. Furthermore, the scope of use of generative models is limited, making it difficult to apply them in virtual spaces. Therefore, there is a need for a system that improves the efficiency of digital content generation and the convenience of virtual stores.

[1800] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1801] In this invention, the server includes: means for multiple users who post generative models to upload their own generative models; means for listing the generative models in a store; means for multiple other users who access the store to purchase generative models; means for executing the purchased generative models to generate digital content that can be used in a virtual store; means for making the generated digital content available for download; and means for calculating rewards based on the usage status of the generative models and allocating them to the users who posted the generative models. This makes it easy to generate and use digital content in a virtual store, enabling users to generate and utilize high-quality digital content without specialized skills.

[1802] A "generative model" refers to a model that uses machine learning algorithms to automatically generate new digital content from specific input data.

[1803] "User" refers to a user of the System who can post, purchase, and run Generative Models.

[1804] "Store" means the online platform through which Users can post, list, and purchase Generative Models.

[1805] A "virtual store" refers to a digital store that provides various services and products in a virtual space and that users can access.

[1806] "Digital content" refers to information in electronic media (images, text, audio, etc.) created using generative models.

[1807] "Means for posting" refers to the function that allows users to upload their own generative models to the server.

[1808] "Means for listing" refers to the function for displaying posted Generative Models in the Store.

[1809] "Means for purchasing" refers to the functionality that allows users to select a generative model from the store and complete the purchase process.

[1810] "Means for executing" refers to the functionality for generating digital content based on input data using the purchased Generative Model.

[1811] "Means for making available for download" refers to the functionality that allows users to obtain the generated digital content.

[1812] "Means for calculating and allocating rewards" refers to a function for calculating rewards based on the usage status of the generative model and distributing the rewards to the user who posted the generative model.

[1813] The system of this invention aims to streamline the process of posting, buying and selling Generative Models, and running them in a virtual store. Specifically, the server provides a set of functions that allow multiple users to post Generative Models, which other users can purchase, and generate digital content.

[1814] The server uses the following hardware and software: The server uses the Django framework and PostgreSQL as the database. TensorFlow and PyTorch are used to run the generative model. The front end is built using React.

[1815] User Registration and Login

[1816] User registration: The user accesses the server using a smartphone or head-mounted display and registers as a user. The server saves the entered information in a database and sends a confirmation email. The user clicks on the confirmation link to activate the account.

[1817] Login: A registered user enters a username and password on the login screen to access the server.

[1818] Submitting a Generative Model

[1819] Posting a Generative Model: A user of the Generative Model Creator logs in to the server and uploads the name, description, usage fee, and model file of the Generative Model by clicking the "Post a Generative Model" button on the dashboard. The server saves these in the database and lists them on the store page.

[1820] Purchasing and running generative models

[1821] Purchasing a Generative Model: A Generative Model user accesses the store page, adds the Generative Model to their cart, and completes the purchase process. The server verifies the payment information and grants the user access to the Generative Model.

[1822] Executing a Generative Model: To execute a purchased generative model, a user accesses their personal page, selects the generative model, and enters the necessary input data (such as text prompts and image settings). When the user clicks the "Execute" button, the server executes the generative model and generates digital content.

[1823] Downloading digital content

[1824] Make available for download: The generated digital content is stored by the server and a download link is provided to the user, who can then download the content from this link.

[1825] Reward distribution

[1826] Reward calculation and distribution: The server periodically compiles the usage status of the generative model and calculates the reward. This reward is distributed to the user who worked on the generative model and reflected in the user's account. The user can check the reward and withdraw it.

[1827] Specific examples

[1828] For example, if you want to generate your own avatar in a virtual store, you can create a custom avatar for yourself by inputting the following prompts into the generative AI model:

[1829] Please create an avatar with blue hair, almond-shaped eyes, and casual clothing.

[1830] In this way, users can quickly generate high-quality digital content without any specialized knowledge and use it in virtual stores. This system lowers the barrier to entry for digital content creation and enables the widespread use of generative models.

[1831] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1832] Step 1:

[1833] User Registration and Login

[1834] Input: User's registration information (username, email address, password).

[1835] Processing: The server saves this registration information in a database (PostgreSQL) and sends a confirmation email. Once the user clicks on the confirmation link, the account is activated.

[1836] Output: Activated user account information.

[1837] Step 2:

[1838] Submitting a Generative Model

[1839] Inputs: The name, description, usage fee, and model file of the Generative Model entered by the Generative Model creator.

[1840] Processing: The server saves the input data and uploaded model files to the database and lists them on the store page.

[1841] Output: Generated model information listed on the store page.

[1842] Step 3:

[1843] Purchasing Generative Models

[1844] Input: Purchase request from the Generative Model Consumer (selected Generative Model ID, payment information).

[1845] Processing: The server verifies the payment information and, if successful, stores the data in the database to grant access to the Generative Model User.

[1846] Output: Generated model access rights to the generated model consumer.

[1847] Step 4:

[1848] Running the generative model

[1849] Input: Prompt statements and configuration data entered by the user of the generative model.

[1850] Processing: The server runs the purchased generative model and generates digital content based on the input data (using TensorFlow or PyTorch).

[1851] Output: The generated digital content files.

[1852] Step 5:

[1853] Downloading digital content

[1854] Input: A request to download the generated digital content.

[1855] Processing: The server retrieves the generated digital content from storage and generates and provides a download link.

[1856] Output: A link for the user to download.

[1857] Step 6:

[1858] Reward calculation and allocation

[1859] Input: Usage data for the generative model (number of purchases and frequency of use).

[1860] Processing: The server calculates the reward based on this information and reflects it in the Generative Model Creator's account. The creator checks this and can withdraw the money if necessary.

[1861] Output: Reward amount and withdrawal information for the generative model creator.

[1862] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1863] This invention realizes optimal digital content generation based on user emotions by combining a store platform where generative models can be posted, traded, and executed with a user emotion engine. The invention provides a series of processes that allow users to easily post, trade, and execute generative models, and further improves the quality of generated content using the emotion engine.

[1864] User Registration and Login

[1865] First, the user accesses the server and registers. The server saves the entered registration information in a database and sends a confirmation email. When the user clicks the link in the confirmation email, the account is activated and the server updates the user status to "active."

[1866] Submitting a Generative Model

[1867] A user who has registered as a generative model creator logs in to the server and accesses the dashboard. The server provides a "Post Generative Model" button, and clicking this displays a form for submitting a generative model. The creator enters and uploads the name, description, usage fee, and model file of the generative model. The server receives this information, stores it in the database, and lists the new generative model on the store page.

[1868] Purchasing Generative Models

[1869] A user who has registered as a generative model user logs in to the server and accesses the store page. The server displays a list of available generative models, and the user adds the generative model of interest to the cart and proceeds with the purchase. The server processes the purchase, verifies the payment information, and then grants the user access rights.

[1870] Execution of generative models and generation of digital content

[1871] After logging in, a user who has purchased a generative model accesses their personal page and selects the model they wish to run from a list of generative models they have purchased. The server provides an interface for running the generative model and displays a screen for entering the necessary input data (e.g., text prompts, image settings, etc.). When the user provides the input data and clicks the "Run" button, the server runs the generative model and generates digital content based on the specified input data.

[1872] Furthermore, by using an emotion engine, it is possible to recognize the user's emotional state in real time and adjust the output of the generative model. This allows the generated content to be provided in a form that is more suited to the user's emotions. The generated content is stored on a server, and a download link is provided to the user. The user can download the generated content from the provided link.

[1873] Reward distribution

[1874] The server periodically aggregates the usage status of generative models and calculates the reward for the generative model creator. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and the server reflects this reward in the creator's account and notifies them later. The generative model creator can check the reward and withdraw it if necessary. The server processes the withdrawal request and transfers the reward to the creator.

[1875] Specific examples

[1876] Example 1: A generative model creator submits an image generation model

[1877] 1. The creator (user) accesses the server and logs in using their account on the login screen.

[1878] 2. Creators click the "Post Generative Model" button and enter the name, description, usage fee, etc. of the image generation AI. They also select and upload the model file (e.g., .h5 file) required for image generation.

[1879] 3. The server receives the input data and uploaded files from the creator, stores them in the database, and adds a list of this AI model to the store page.

[1880] Example 2: When a user purchases and runs an image generation model

[1881] 1. The user accesses the server and checks the store page of the generated model.

[1882] 2. The user finds the image generation model they want to use, adds it to their cart, checks the items they need, and clicks the purchase button.

[1883] 3. The server processes the purchase and grants the user access to the purchased Generative Model.

[1884] 4. The user accesses the interface for running the AI ​​and enters prompts and other settings for the image they want to generate.

[1885] 5. The server receives the configuration and runs the generative model to generate the image.

[1886] 6. The server saves the generated image in storage and provides the user with a download link.

[1887] 7. The user obtains the generated image from the provided download link.

[1888] Example 3: Content generation using an emotion engine

[1889] 1. When purchasing a generative model with an emotion engine, the user selects the option to enable the emotion engine.

[1890] 2. The user accesses the server, checks the store page for the generative model, and configures the emotion engine for use.

[1891] 3. When a user runs a generative model with the emotion engine enabled, the server collects the user's emotion data in real time and adjusts the output of the generative model.

[1892] 4. Optimal digital content is generated and provided based on the user's emotions.

[1893] In this way, by combining the user's emotion engine, the present invention can realize more personalized digital content generation and improve the user experience.

[1894] The processing flow will be explained below.

[1895] User Registration and Login

[1896] Step 1:

[1897] User: Access the server and display the user registration screen.

[1898] Step 2:

[1899] Server: Displays a user registration form and prompts the user to enter required information such as name, email address, and password.

[1900] Step 3:

[1901] User: Enter the required information in the registration form and click the "Register" button.

[1902] Step 4:

[1903] Server: Stores the entered information in a database and sends a confirmation email to the user.

[1904] Step 5:

[1905] Users: Click the link in the confirmation email to activate their account.

[1906] Step 6:

[1907] Server: Checks for account activation and updates user status to "enabled".

[1908] Submitting a Generative Model

[1909] Step 1:

[1910] Generative model creator (user): After logging in, access the dashboard.

[1911] Step 2:

[1912] Server: Display the creator dashboard.

[1913] Step 3:

[1914] Generative Model Creator: Click the "Submit Generative Model" button in the dashboard.

[1915] Step 4:

[1916] Server: Display the generated model submission form.

[1917] Step 5:

[1918] Generative Model Creator: Enter and upload the generated model name, description, usage fee, and model file (e.g., .h5, .pth file).

[1919] Step 6:

[1920] Server: Receives entered information and uploaded files and stores them in a database and storage.

[1921] Step 7:

[1922] Server: Update the store page with the new generative model list.

[1923] Purchasing Generative Models

[1924] Step 1:

[1925] User: After logging in, access the store page.

[1926] Step 2:

[1927] Server: Display the store page and list the available generative models.

[1928] Step 3:

[1929] User: Selects the generative model they are interested in and clicks the "Add to Cart" button.

[1930] Step 4:

[1931] Server: Saves and displays the generative models added to the cart in a list.

[1932] Step 5:

[1933] User: Check the contents on the cart page and click the "Purchase" button.

[1934] Step 6:

[1935] Server: Processes purchases and verifies payment information.

[1936] Step 7:

[1937] Server: After confirming the payment, grant the user access to the generative model and update the database.

[1938] Execution of generative models and generation of digital content

[1939] Step 1:

[1940] User: After logging in, access My Page to view a list of generative models you have purchased.

[1941] Step 2:

[1942] Server: Displays My Page and provides a list of Generative Models to which the user has access.

[1943] Step 3:

[1944] User: Select the generative model you want to run and click the "Run" button.

[1945] Step 4:

[1946] Server: Displays the interface for running the generative model and displays the required input fields (e.g., text prompts, image settings, etc.).

[1947] Step 5:

[1948] User: Enter the required input data and click the "Execute" button.

[1949] Step 6:

[1950] Server: Receives input data and executes it by calling the generative model in the backend.

[1951] Step 7:

[1952] Server: Stores the generated digital content in storage and provides users with a download link.

[1953] Step 8:

[1954] User: Downloads the generated digital content from the provided download link.

[1955] Content generation using emotion engine

[1956] Step 1:

[1957] Users: When purchasing a generative model with an emotion engine, select the option to enable the emotion engine.

[1958] Step 2:

[1959] User: Accesses the server, checks the store page for the generative model, and configures the emotion engine.

[1960] Step 3:

[1961] Server: Reflects the emotion engine settings and displays an option to enable the emotion engine on the generative model execution screen.

[1962] Step 4:

[1963] User: Enables the emotion engine and provides input data to run the generative model.

[1964] Step 5:

[1965] Server: Analyzes user emotion data in real time using an emotion engine and feeds the results back to the generative model.

[1966] Step 6:

[1967] Server: Executes the generative model based on data from the emotion engine and generates optimal digital content.

[1968] Step 7:

[1969] Server: Stores the generated digital content in storage and provides users with a download link.

[1970] Step 8:

[1971] User: Downloads the generated digital content from the provided download link.

[1972] Reward distribution

[1973] Step 1:

[1974] Server: Periodically aggregates the usage status of the generative model.

[1975] Step 2:

[1976] Server: Calculates the reward amount for the generative model creator based on the aggregated data.

[1977] Step 3:

[1978] Server: Reflects the calculated rewards in the creator's account and notifies them.

[1979] Step 4:

[1980] Generative model creator (user): Check the reward amount on the dashboard and withdraw it if necessary.

[1981] Step 5:

[1982] Server: Processes withdrawal requests and transfers rewards to the creator's designated account.

[1983] The above are the specific processing steps of the invention that combines an emotion engine. This system provides more personalized digital content and improves the user experience by adjusting the output of the generative model to adapt to the user's emotions.

[1984] Example 2

[1985] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1986] Conventional digital content generation systems using generative models have problems such as a lack of personalization in the user experience and difficulty in improving the quality of content. Furthermore, there is a need for improved transparency and efficiency in the distribution of rewards to generative model creators.

[1987] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to upload their own generative model, a means for listing the generative model in a store, a means for other users who access the store to purchase generative models, a means for executing the purchased generative model to generate digital content, a means for making the generated digital content available for download, a means for calculating a reward based on the usage status of the generative model and distributing it to the user who posted the generative model, and a means for the user to adjust the output of the generative model in real time using an emotion engine. This enables the generation of more personalized, high-quality digital content based on user emotions. Furthermore, reward distribution to creators can be transparent and efficient.

[1988] A "User" is an individual or organization that uses the system and can upload, purchase, and run Generative Models.

[1989] A "generative model" is a computational tool that uses machine learning techniques to generate new digital content based on specific input data.

[1990] "Uploading" is the act of a generative model creator sending and saving their generative model to a server.

[1991] A "store" is an online platform that resides on a server and lists generative models, allowing users to purchase them.

[1992] "Listing" refers to the process and procedure of placing an uploaded Generative Model on the Store.

[1993] "Purchase" refers to the act of a user paying a fee for a generative model offered in the store and obtaining the right to use it.

[1994] "Execution" refers to the process of generating specific digital content using the Generative Model purchased by the user.

[1995] "Digital content" is data created by the execution of a generative model, and can take the form of images, text, audio, etc.

[1996] "Making it available for download" means providing the generated digital content as a link or file so that users can save it to their own devices.

[1997] "Remuneration" means the compensation a Generative Model Creator receives based on the use or sale of a Generative Model.

[1998] An "emotion engine" is a technology for detecting the user's emotional state and adjusting the output of a generative model.

[1999] These definitions are used to clarify the technical scope of the patent and to provide an understanding of the specific content of the invention.

[2000] This invention is a system that combines a store platform where users can post, buy, sell, and execute generative models with a user emotion engine. The invention facilitates the process of generating generative models and realizes optimal digital content generation based on user emotions.

[2001] User Registration and Login

[2002] First, the user accesses the server from their own device and registers as a user. The server receives the registration information (name, email address, password, etc.) entered by the user and stores it in a database. The server then sends a confirmation email to the user, and when the user clicks on the link, the account is activated. After completing registration, the user can log in by entering their email address and password on the login screen and access the dashboard.

[2003] Submitting a Generative Model

[2004] A user who has registered as a generative model creator logs in to the server and clicks the "Post Generative Model" button on the dashboard. The creator enters the name, description, usage fee, and model file (e.g., .h5 file) of the generative model and uploads it to the server. The server saves this information in the database and lists the new generative model on the store page.

[2005] Purchasing Generative Models

[2006] A user who has registered as a Generative Model user logs in to the server and accesses the store page. The server displays a list of available Generative Models, and the user adds the Generative Model of interest to the cart and proceeds with the purchase. When the user enters payment information and clicks the submit button, the server processes the payment and grants the user access to the purchased Generative Model.

[2007] Execution of generative models and generation of digital content

[2008] After purchasing a generative model, a user logs in to the server, accesses their personal page, and selects the model they wish to run from a list of purchased generative models. The server displays the generative model execution interface, and the user provides the required input data (e.g., text prompts, image settings, etc.). The user clicks the "Run" button, and the server runs the generative model based on the input data and generates digital content. The generated content is stored on the server, and a download link is provided to the user.

[2009] Use of emotion engine

[2010] When using the emotion engine, the server recognizes the user's emotional state in real time and adjusts the output of the generative model, making the generated content more personalized and optimized for the user's emotions.

[2011] Reward distribution

[2012] The server periodically aggregates the usage status of generative models and calculates the reward for generative model creators. The reward amount is determined based on the number of times the generative model is used and the amount of sales, and is reflected in the creator's account. Creators can request a withdrawal under certain conditions, and the server processes this request and transfers the reward to the creator.

[2013] A concrete example of this system is a case where a generative model creator enters a prompt such as, "Generate a promotional image for a new product. The product is a small, portable speaker. Obtain positive feedback from user reviews and generate an image with a positive atmosphere based on that." A user can purchase this image generation model, enter a similar prompt, and run it to generate a promotional image that meets their needs.

[2014] As described above, this invention improves the user experience and enables the generation of high-quality digital content by combining the posting, buying and selling, and execution of generative models with an emotion engine.

[2015] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2016] Step 1: User Registration

[2017] Input: The user accesses the server from their device and enters registration information such as their name, email address, and password.

[2018] Data processing and output: The server receives the entered information, stores it in a database, and sends a confirmation email to the user.

[2019] What happens: The server validates the input information and, if there are no problems, saves it to the database and sends the user an email containing a confirmation link.

[2020] Step 2: User authentication

[2021] Input: User clicks on the link in the confirmation email.

[2022] Data processing and output: The server checks the validity of the link and updates the user status to "valid".

[2023] Specific operation: The server analyzes the link in the email, retrieves the corresponding user account information from the database, and updates it.

[2024] Step 3: User Login

[2025] Input: The user enters their email address and password on the login screen.

[2026] Data processing and output: The server checks the entered information against the database, and if correct, authenticates the user and redirects them to the dashboard.

[2027] Specific behavior: The server checks the entered email address and password, and if successful, starts a session for the user.

[2028] Step 4: Submitting the generative model

[2029] Input: The Generative Model creator accesses the dashboard and enters and uploads the name, description, usage fee, and model file (e.g., .h5 file) of the Generative Model.

[2030] Data processing and output: The server receives this information, stores it in a database, and lists the new generative model on the store page.

[2031] What happens: The server validates the information submitted in the form, records it in a database, and updates the listing on the store page.

[2032] Step 5: Buy a generative model

[2033] Input: A user adds a generative model of interest to their cart on the store page and proceeds to checkout.

[2034] Data processing and output: The server receives payment information, processes the transaction, and grants the user access to the purchased generative model.

[2035] What happens: The server validates the payment information and processes the payment. If successful, it grants access to the user's account and sends a notification.

[2036] Step 6: Execute the generative model and generate digital content

[2037] Input: The user accesses My Page, selects the generative model they wish to run from the purchased models, and provides the required input data (e.g., text prompts, image settings, etc.).

[2038] Data processing and output: The server runs the generative model based on the input data to generate digital content, which is then stored on the server and a download link is provided to the user.

[2039] Specific operation: The server allocates computing resources to run the generative model and runs the model based on the input data. The generated content is saved to storage and a link is sent to the user.

[2040] Step 7: Use the Emotion Engine

[2041] Input: User enables the emotion engine and runs the generative model.

[2042] Data processing and output: The server recognizes the user's emotional state in real time and adjusts the output of the generative model, thereby generating digital content optimized for the user.

[2043] Specific operation: The server analyzes the user's emotional data using an emotion recognition algorithm and adjusts the parameters of the generative model based on the results.

[2044] Step 8: Reward Distribution

[2045] Input: The server periodically aggregates the usage of the generative model.

[2046] Data processing and output: The server calculates rewards based on the number of times the generative model is used and the amount of sales, and reflects them in the creator's account.

[2047] Specific operation: The server periodically collects usage data from the database and calculates the reward amount using the reward calculation algorithm. The calculation results are reflected in the creator's account and notified.

[2048] This clarifies the specific operations performed at each processing step, making it easier to understand the flow of the entire system.

[2049] (Application example 2)

[2050] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2051] Conventional digital content generation systems using generative models have difficulty providing personalized advertising content because they do not take into account the user's emotional state. Furthermore, there has been no effective means of collecting real-time emotional data from users and generating advertising content that reflects this data.

[2052] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: a means for multiple users who post generative models to upload their own generative models; a means for listing the generative models in a store; a means for multiple other users who access the store to purchase generative models; a means for executing the purchased generative models to generate digital content; a means for making the generated digital content available for download; a means for calculating a reward based on the usage status of the generative model and distributing it to the user who posted the generative model; and a means for generating digital content by combining an emotion engine that recognizes the user's emotional state in real time and adjusts the output of the generative model. This makes it possible to generate advertising content that is appropriate for the user's emotional state.

[2053] A "generative model" is an algorithm or machine learning model that generates specific digital content submitted by users.

[2054] The "Store" is an online platform where generative models are listed and available for purchase by other users.

[2055] "Digital content" refers to electronic media content such as images, text, and videos created using generative models.

[2056] An "emotion engine" is a system that recognizes the user's real-time emotional state and adjusts the output of the generative model based on that data.

[2057] "User" refers to anyone who uses the system, including creators who post generative models and users who purchase those generative models and generate content.

[2058] "Reward" is calculated based on the usage of the generative model and is paid to the user who posted the generative model.

[2059] This invention provides optimal digital content generation based on user emotions by combining a user's emotion engine with a store platform where users can post, trade, and execute generative models. This system is implemented using smart glasses and a server.

[2060] The system program is structured as follows:

[2061] 1. User Registration and Login

[2062] The server saves the user's registered information in a database and sends a confirmation email, which the user must click to activate their account.

[2063] Software used: Database management system (e.g., MySQL)

[2064] 2. Submitting a Generative Model

[2065] Users who are registered as generative model creators log in to the server and upload their models using the generative model submission form. The model information and files are stored in the database and listed on the store page.

[2066] Software used: Cloud storage system (e.g. Amazon S3)

[2067] 3. Purchasing a Generative Model

[2068] The server displays a list of generative models on a store page, allowing users to add them to their cart and purchase them. After completing the purchase process, access rights are granted.

[2069] Software used: Electronic payment systems (e.g., Stripe)

[2070] 4. Execution of generative models and generation of digital content

[2071] An interface is provided for running purchased generative models. The user provides input data such as prompt statements and executes the generative model.

[2072] Software used: Generative AI models (e.g., GPT-3)

[2073] 5. Use of Emotion Engine

[2074] The camera built into the smart glasses analyzes the user's facial expressions in real time, and the emotion engine acquires emotional data.

[2075] Hardware used: Built-in camera in smart glasses

[2076] Software used: Facial expression recognition library (e.g., OpenCV), emotion analysis model

[2077] 6. Emotional content optimization

[2078] The emotion engine adjusts the output of the generative model based on the user's emotional state to generate more personalized digital content.

[2079] Software used: Sentiment analysis model

[2080] 7. Reward Distribution

[2081] The server calculates rewards based on the usage of the generative model and pays them to the generative model creator.

[2082] Software used: Remuneration calculation system

[2083] For example:

[2084] If the user's emotion is "joy":

[2085] Prompt: "Create a fun and cheerful video ad."

[2086] Based on the prompt, the server generates an advertisement for a home electronic device featuring a smiling family enjoying a holiday.

[2087] If the user's emotion is "sadness":

[2088] Prompt: "Generate a quiet ad that provides warmth and comfort."

[2089] Based on this prompt, the server generates a soothing product advertisement that conveys a gentle message accompanied by quiet music.

[2090] In this way, the system of the present invention can improve the user experience by generating more suitable digital content based on the user's real-time emotional data.

[2091] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2092] Step 1:

[2093] User registration and login.

[2094] The server receives the user's registration information (e.g., name, email address, password) and stores it in a database. It then sends a confirmation email and the user activates their account by clicking the link in the confirmation email. This updates the user status to "active."

[2095] Input: User registration information (name, email address, password)

[2096] Output: Send confirmation email, update user status

[2097] Step 2:

[2098] Posting generative models.

[2099] Users who have registered as generative model creators log in to the server using their terminal and enter and upload the model file (e.g., .h5 file) and necessary information (e.g., model name, description, and usage fee) into the generative model submission form. The server receives this data, stores it in the database, and lists it as a new generative model on the store page.

[2100] Input: Generated model file, model name, description, usage fee

[2101] Output: Save to database, add list to store page

[2102] Step 3:

[2103] Purchasing generative models.

[2104] Other users who access the store log in to the server and check the list of Generative Models. The user adds the Generative Model they want to purchase to their cart and completes the payment process. The server verifies the payment information and completes the purchase. The server grants the user access to the purchased Generative Model.

[2105] Input: Add to Cart, Payment Information

[2106] Output: Purchase procedure completed, access granted

[2107] Step 4:

[2108] Execution of generative models and digital content generation.

[2109] To run a purchased generative model, a user logs in and accesses their personal page. They select the model they want to run and provide input data (e.g., a prompt). The server runs the generative model and generates digital content based on the specified input data.

[2110] Input: Input data such as prompt statements

[2111] Output: Generated digital content

[2112] Step 5:

[2113] Leveraging the emotion engine.

[2114] The smart glasses' built-in camera captures the user's facial expression data in real time, and the emotion engine analyzes this data to recognize the user's emotional state.

[2115] Input: User's facial expression data

[2116] Output: Real-time emotional state

[2117] Step 6:

[2118] Emotion-based content optimization.

[2119] Based on the user's emotional data acquired by the emotion engine, the server adjusts the output of the generative model to generate digital content more suitable for the user. For example, if the user is in a "joy" emotional state, it generates a bright and cheerful advertisement. If the user is in a "sad" emotional state, it generates a quiet advertisement that provides warmth and comfort.

[2120] Input: Real-time emotional state, prompt sentence

[2121] Output: Emotion-based digital content

[2122] Step 7:

[2123] Providing generated digital content.

[2124] The server stores the generated digital content in storage and provides a download link to the user, who then downloads the generated content via the link.

[2125] Input: Generated digital content

[2126] Output: Download link

[2127] Step 8:

[2128] Distribution of rewards.

[2129] The server periodically compiles the usage status of generative models and calculates the reward for the generative model creator. The reward is determined based on the number of times the generative model is used and the amount of sales, and is reflected in the creator's account. The creator can then perform a withdrawal procedure, and the server processes the withdrawal request and transfers the reward to the creator.

[2130] Input: Generative model usage data

[2131] Output: Reward calculation, notification to creator

[2132] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2133] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2134] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2135] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2136] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2137] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2138] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2139] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2140] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2141] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2142] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2143] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2144] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2145] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2146] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2147] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2148] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2149] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2150] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2151] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2152] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2153] The following is further disclosed regarding the above embodiment.

[2154] (Claim 1)

[2155] A means for multiple users to upload their own generative models;

[2156] means for listing the generative model in a store;

[2157] A means for other users who access the store to purchase generative models;

[2158] means for executing the purchased generative model to generate digital content;

[2159] means for making the generated digital content available for download;

[2160] A means for calculating a reward based on the usage status of the generative model and allocating the reward to the user who posted the generative model;

[2161] A system including:

[2162] (Claim 2)

[2163] The system of claim 1 , wherein the generative model is a sentence generation model.

[2164] (Claim 3)

[2165] The system of claim 1 , wherein the generative model is an image generative model.

[2166] (Claim 4)

[2167] The system of claim 1 , wherein the generative model is an animation generative model.

[2168] (Claim 5)

[2169] The system of claim 1 , wherein the generative model is a...

Claims

1. A means for multiple users to upload their own generative models; means for listing the generative model in a store; A means for other users who access the store to purchase generative models; means for executing the purchased generative model to generate digital content; means for making the generated digital content available for download; A means for calculating a reward based on the usage status of the generative model and allocating the reward to the user who posted the generative model; A system including:

2. The system of claim 1 , wherein the generative model is a sentence generation model.

3. The system of claim 1 , wherein the generative model is an image generative model.

4. The system of claim 1 , wherein the generative model is an animation generative model.

5. The system of claim 1 , wherein the generative model is a speech generative model.

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