System

Abstract

A system is provided.SOLUTION: In a platform that aggregates generated AI models, a system comprising: means for storing registered prompts and generated AI models in a database; means for publishing aggregated prompts and generated AI models online; means for receiving purchase requests from users and receiving payment through a settlement system; means for providing the generated AI models and prompts to the users after the purchase is completed; and means for sharing the revenue of the purchase payment between the prompt producer and the platform operator.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] In modern society, many companies and individuals are increasingly seeking to improve their business efficiency by utilizing generative AI models. However, it is extremely difficult for individual companies and individuals to independently develop generative AI models and prompts and maximize their effectiveness, requiring significant resources and time. Furthermore, because generative AI models and prompts are distributed, it is not easy to find the optimal model or prompt. Furthermore, the purchasing and revenue sharing mechanisms are not centralized, making transactions between providers and users complicated. The present invention aims to solve these problems. [Means for solving the problem]

[0005] The system of the present invention provides a platform for aggregating generative AI models and includes the following means:

[0006] 1. Centralize all data by providing a means to store registered prompts and generative AI models in a database.

[0007] 2. Provide a means to publish aggregated prompts and generative AI models online, making them easily viewable and searchable by users.

[0008] 3. Implement a means to receive purchase requests from users and receive payment through a payment system, simplifying the purchasing process.

[0009] 4. Provide a means to provide users with generative AI models and prompts after purchase completion, making data available quickly.

[0010] 5. A means will be provided for sharing revenue from purchases between prompt creators and platform operators, ensuring fair revenue sharing.

[0011] 6. Provide a way for users to customize prompts and generative AI models and re-register those customizations with the platform, ensuring new data is constantly added.

[0012] These measures will enable centralized information management, efficient transactions, and fair revenue distribution, providing an environment in which companies and individuals can smoothly utilize generative AI models.

[0013] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to generate content such as text and images.

[0014] A "prompt" is the input data or instructions used by a generative AI model, and refers to an element that directly affects the quality and content of the generated content.

[0015] A "database" refers to a collection of information that is constructed to centrally manage specific data and to efficiently search, retrieve, and update it.

[0016] "Platform" refers to a web-based system or service for aggregating, publishing, trading, and managing generative AI models and prompts.

[0017] "User" means any individual or business that uses the Platform to register, purchase, or customize generative AI models or prompts.

[0018] "Revenue sharing" refers to the process of appropriately dividing revenue generated from the purchase of generative AI models and prompts between prompt creators and platform operators.

[0019] "Payment System" means an electronic payment instrument or mechanism for accepting payments from users and completing transactions securely and efficiently.

[0020] "Customization" refers to the process of modifying and improving existing generative AI models and prompts to suit the user's own needs. [Brief explanation of the drawings]

[0021] [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

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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."

[0042] The present invention relates to a platform that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and sells or provides them. The system of the present invention is embodied in the following form.

[0043] 1. Aggregation of prompt and generative AI models

[0044] Registering prompt and generative AI models

[0045] Users register their own prompts and generative AI models on the platform by entering information such as the prompt name, detailed description, use case, and pricing on the registration screen and clicking the "Submit" button.

[0046] Data Receipt and Validation

[0047] The server receives the prompts sent by the user and the data from the generative AI model. The received data is verified to ensure that the format and required fields are entered correctly. Once verified, the data is stored in a database.

[0048] 2. Publishing generative AI models and prompts

[0049] Preparation for release

[0050] The server converts the metadata of the prompts and generative AI models registered in the database into a searchable format and prepares it for display on a web page.

[0051] public

[0052] The server publishes the ready-to-publish prompts and generative AI models on an online platform, where they can be browsed and searched by users.

[0053] 3. Purchase procedure

[0054] Selecting a prompt

[0055] Users choose what they need from the published prompts and generative AI models and click the "Purchase" button.

[0056] Receiving a purchase request

[0057] The server receives the user's purchase request and checks its contents.

[0058] Enter your payment information

[0059] The user follows the server's instructions and enters payment information (credit card information, electronic payment service information, etc.).

[0060] Payment Processing

[0061] The server receives the user's purchase payment through the payment system, and once payment is complete, sends the user a purchase completion notification.

[0062] Providing generative AI models and prompts

[0063] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by sending the user a download link and API key.

[0064] 4. Revenue Sharing

[0065] Calculating revenue

[0066] The server calculates the revenue share based on the purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[0067] Revenue sharing execution

[0068] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[0069] 5. Customization and Re-provision

[0070] Customizing prompts and generative AI models

[0071] Users can download the generative AI models and prompts they purchase and customize them to suit their needs.

[0072] Re-registering a customized version

[0073] The user can then re-register the customized generative AI model and prompts on the platform by entering the necessary information on the prompt registration screen again and submitting it.

[0074] Re-registration process

[0075] The server verifies the data format and required items of the re-registered customized prompts and generative AI models, stores them in the database, and then prepares them for publication and publishes them again.

[0076] Specific examples

[0077] For example, a user can create a new natural language generation prompt and register it on the platform. The prompt is then published, and other users can purchase it. After completing the purchase, the user can customize the prompt and register it again on the platform. In this way, new prompts and generative AI models are constantly being aggregated, published, and revenues are shared.

[0078] The system of the present invention is implemented in the above manner, providing centralized information management, efficient transactions, and fair revenue distribution, thereby realizing an environment in which companies and individuals can smoothly utilize generative AI models.

[0079] The processing flow will be explained below.

[0080] Step 1:

[0081] Users open a dedicated registration screen to register their own prompts and generative AI models on the platform. On the registration screen, they enter the required information, such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[0082] Step 2:

[0083] The server receives the prompts sent by the user and the data from the generative AI model. It verifies that the received data is correctly formatted and that all required fields are entered. If the data is determined to be correct, it stores the data in a database.

[0084] Step 3:

[0085] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format, preparing them for efficient search and browsing by users through the platform.

[0086] Step 4:

[0087] The server uses the converted metadata to publish the prompts and generative AI models on a webpage, where users can freely browse and search them.

[0088] Step 5:

[0089] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[0090] Step 6:

[0091] The server receives the user's purchase request, verifies its contents, and then provides the user with a screen for entering payment information.

[0092] Step 7:

[0093] The user follows the instructions of the server and enters payment information such as credit card information and electronic payment service information, then clicks the "Submit" button to complete the payment.

[0094] Step 8:

[0095] The server receives payment from the user through the payment system. Once payment is complete, the server sends a notification to the user that the purchase has been completed.

[0096] Step 9:

[0097] The server provides the user with the prompts and generated AI model data for which the purchase has been completed, and the user is sent a download link and API key, allowing them to immediately use the purchased data.

[0098] Step 10:

[0099] The server calculates the revenue share based on the user's purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[0100] Step 11:

[0101] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[0102] Step 12:

[0103] Users can customize the purchased prompts and generative AI models to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[0104] Step 13:

[0105] The server receives the customized prompts and generated AI model data registered by the user, verifies their format and required items, and stores the verified data in a database.

[0106] Step 14:

[0107] The server then converts the metadata of the customized prompts and generative AI models stored in the database into a searchable format and republishes them on the webpage, allowing new prompts and generative AI models to be constantly updated and made public.

[0108] Example 1

[0109] 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."

[0110] Today, businesses and individuals lack a platform for effectively managing and trading generative AI models and prompts. Therefore, there is a need for a system that allows users to easily register, sell, and reuse their generated prompts and AI models. Furthermore, the purchasing procedures and revenue distribution processes are complex, and an efficient and fair method is needed.

[0111] 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.

[0112] In this invention, the server includes means for a user to input prompts and generative AI models and send the contents to the server, means for the server to receive the data sent from the user and verify the format and necessary items, means for storing the verified data in a database and notifying the user, means for converting the stored data into a searchable format and publishing it on an online platform, means for receiving purchase requests from users and receiving payment through a payment system, means for providing generative AI models and prompts after purchase is completed, and means for sharing revenue from the purchase price. This allows users to efficiently register, publish, sell, and reuse prompts and generative AI models, and enables fair and smooth revenue sharing.

[0113] "User" means an individual or entity that uses the Platform to register, purchase, and customize prompts and generative AI models.

[0114] A "prompt" is text data or instructions input into a generative AI model that determines the output content generated.

[0115] A "generative AI model" is an artificial intelligence model that performs natural language processing or generative tasks, including algorithms for generating output in response to prompts.

[0116] "Server" is a central control device that manages the entire system and performs various processes such as receiving, verifying, storing, publishing, payment processing, and revenue distribution of data.

[0117] "Database" means a storage system for centrally managing and storing data, including prompts and generative AI models.

[0118] "Payment system" means a system for processing payments for user purchases, including credit cards and electronic payment services.

[0119] "Revenue sharing" is a system in which revenue earned when users sell prompts or generative AI models is divided fairly between prompt creators and platform operators.

[0120] "Customization" refers to the process by which users edit and modify the generative AI models and prompts they purchase to adapt them to their own specific needs.

[0121] "Online Platform" means a web-based system that enables users to register, publish, sell, buy, and customize prompt and generative AI models.

[0122] "Re-registration" refers to the act of a user customizing the prompts and generative AI models that were initially registered and then registering them again on the platform.

[0123] The present invention relates to a platform for aggregating prompts and generative AI models created by companies and individuals using generative AI models, and for selling and providing them. This platform is composed of components such as a server, terminals, databases, online interfaces, and payment systems.

[0124] Process Overview

[0125] 1. Registering a prompt and generate AI model

[0126] The user uses a device to access the platform's registration screen, enters the prompts and details of the generated AI model (such as name, detailed description, use case, pricing, etc.), and clicks the "Submit" button.

[0127] The server receives the data sent by the user and verifies whether the data format and required items have been entered correctly. Once the verification is complete, the data is stored in a database.

[0128] 2. Publishing generative AI models and prompts

[0129] The server converts the metadata of the prompts and generative AI models registered in the database into a searchable format and generates a user interface, allowing users to browse and search the published prompts and generative AI models on an online platform.

[0130] 3. Purchase procedure

[0131] Users select a published prompt or generative AI model, click the "Purchase" button, and enter their payment information.

[0132] The server receives the purchase request and payment information from the user, receives the payment through the payment system, and sends a notification of purchase completion to the user once the payment is complete.

[0133] 4. Providing generative AI models and prompts

[0134] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by emailing the user a download link and API key.

[0135] 5. Revenue Sharing

[0136] The server calculates the revenue share based on the purchase price, distributes the revenue according to the distribution ratio between the prompt creator and the platform operator, and transfers the revenue share to the prompt creator's bank account or electronic wallet.

[0137] 6. Customization and Re-provision

[0138] Users can customize the generative AI models and prompts they purchase to suit their own needs.

[0139] Users can then re-register their customized generative AI models and prompts on the platform, where the re-registered data will be verified by the server again, stored in the database, and published again on the online platform once it is ready to be published.

[0140] Specific examples

[0141] For example, suppose a user creates a new natural language generation prompt and registers it on the platform. The prompt is then published and other users can purchase it. Here is an example of a prompt:

[0142] "Example Natural Language Generation Prompt: Generate a conversation about a topic of interest to a college student."

[0143] After completing the purchase, the user can customize the prompt and register again on the platform, thus constantly collecting and publishing new prompts and generative AI models, and sharing revenues.

[0144] The system of the present invention provides centralized information management, efficient transactions, and fair revenue distribution, creating an environment in which companies and individuals can smoothly utilize generative AI models.

[0145] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0146] Step 1: User Data Entry

[0147] Users use their device to access the platform's registration screen and enter prompts and details about the generated AI model (such as name, detailed description, use cases, and pricing).

[0148] Input: Prompt and details about the generated AI model.

[0149] Output: Input data temporarily stored on the device.

[0150] Specific behavior: The user enters data into the input field and clicks the "Submit" button. The device temporarily stores the entered data.

[0151] Step 2: Sending data

[0152] The terminal transmits the saved input data to the server.

[0153] Input: User input data.

[0154] Output: The data sent to the server.

[0155] Specific operation: The device generates an HTTP request and sends the input data to the server.

[0156] Step 3: Receiving and verifying data

[0157] The server receives the data sent by the user and verifies whether the format and required items have been entered correctly.

[0158] Input: The user's data received by the server.

[0159] Output: Validation results and data to be stored in the database.

[0160] Specific behavior: The server checks the format and required fields of the received data, and generates an error message if there is invalid data.

[0161] Step 4: Store the data

[0162] The server stores the verified data in a database.

[0163] Input: The user's data after validation.

[0164] Output: Data stored in the database and notification to the user.

[0165] What happens: The server generates the SQL commands to insert the data into the database, then notifies the user that the registration is complete.

[0166] Step 5: Convert metadata and prepare for publishing

[0167] The server converts the metadata registered in the database into a searchable format and generates a user interface.

[0168] Input: Metadata stored in a database.

[0169] Output: A search index and a user interface.

[0170] What it does: The server indexes the metadata and dynamically generates the web page.

[0171] Step 6: Publish online

[0172] The server publishes the ready generative AI models and prompts on an online platform.

[0173] Input: Prepared prompts and metadata for the generative AI model.

[0174] Output: The published prompt and / or generative AI model.

[0175] What happens: The server updates the web page to display the published prompt and generative AI model.

[0176] Step 7: User selects prompt

[0177] Users can browse published prompts and generative AI models on the platform and click the "Purchase" button for the one they need.

[0178] Input: A list of published prompts and generative AI models.

[0179] Output: Selected prompts and generative AI models.

[0180] What happens: The user navigates through the web interface, selects the item they want to purchase, and clicks the "Buy" button.

[0181] Step 8: Receiving a Purchase Request

[0182] The server receives the user's purchase request and payment information and verifies the contents.

[0183] Input: User purchase request and payment information.

[0184] Output: Confirmed request and payment information.

[0185] Specific operation: The server generates a token for payment information and sends it to the payment system.

[0186] Step 9: Payment Processing

[0187] The server receives payment through the payment system, and once payment is complete, sends a notification to the user that the purchase is complete.

[0188] Input: Payment information.

[0189] Output: Payment completion notification.

[0190] Specific operation: The server calls the payment system API and notifies the user when the payment is successful.

[0191] Step 10: Providing generative AI models and prompts

[0192] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by emailing the user a download link and API key.

[0193] Input: Purchase completion data.

[0194] Output: Download link and API key.

[0195] What happens: The server uses an email service to send the user an email containing the necessary download link and API key.

[0196] Step 11: Calculate Revenue Share

[0197] The server calculates the revenue share amount based on the purchase price and distributes the revenue according to the distribution ratio between the prompt creator and the platform operator.

[0198] Input: Purchase price data and distribution percentage.

[0199] Output: Calculated distribution amount.

[0200] Specific operation: The server executes the calculation algorithm and calculates the distribution amount.

[0201] Step 12: Implementing Revenue Sharing

[0202] The server transfers the calculated revenue share amount to the prompt creator's registered bank account or electronic wallet.

[0203] Input: Calculated distribution amount.

[0204] Output: Remittance completion notification.

[0205] Specific operation: The server calls the API of the bank or electronic wallet to transfer the distribution amount, and then sends a notification of the completion of the transfer to the creator.

[0206] Step 13: Customizing prompts and generative AI models

[0207] Users can download the generative AI models and prompts they purchase and customize them to suit their needs.

[0208] Input: Downloaded generative AI model and prompts.

[0209] Output: Customized generative AI models and prompts.

[0210] Specific operation: The user edits and modifies the generated AI model and prompts in the local environment.

[0211] Step 14: Re-register your customizations

[0212] Users can re-register their customized generative AI models and prompts to the platform by entering the necessary information on the prompt registration screen again and clicking the "Submit" button.

[0213] Input: Customized generative AI models and prompts.

[0214] Output: Re-enrollment data sent to the platform.

[0215] Specific behavior: The user enters the required information on the re-registration screen and the customized data is sent to the server.

[0216] Step 15: Receiving and verifying re-enrollment data

[0217] The server receives the registered prompt and generated AI model data again and verifies that the format and required fields have been entered correctly.

[0218] Input: Re-registered data.

[0219] Output: Validation results and data to be stored in the database.

[0220] Specific operation: The server verifies the data format and required items, just as it did during initial registration.

[0221] Step 16: Store and republish resubmission data

[0222] The server stores the re-registered data in a database and makes it available again on the online platform.

[0223] Input: Your verified re-enrollment data.

[0224] Output: Published re-registration data.

[0225] Specific operation: The server stores the data after validation in a database and makes it public once it is ready.

[0226] (Application example 1)

[0227] 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."

[0228] Platforms that utilize generative AI models are required to provide an environment where users can smoothly and efficiently complete the entire process of registering, searching, purchasing, and customizing prompts and generative AI models. A system is also required that allows users to easily customize and re-register purchased prompts. Conventional systems make these processes cumbersome, and one issue is that they do not adequately support operation on smart devices.

[0229] 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.

[0230] In this invention, the server includes a platform that aggregates generative AI models, a means for storing registered prompts and generative AI models in a database, a means for publishing the aggregated prompts and generative AI models online, and a means for receiving purchase requests from users and receiving payment through a payment system. This allows users to intuitively perform a series of operations using their smartphones to register, search, purchase, and customize prompts and generative AI models. Furthermore, the ease of performing a series of operations to register and publish user-customized prompts on the platform further expands the scope of use of generative AI models.

[0231] A "generative AI model" is a model that automatically generates content and data using artificial intelligence algorithms.

[0232] A "prompt" is an instruction or command that is input to a generative AI model, and is a phrase that specifies the type and content of the content to be generated.

[0233] "Platform" means an online system for aggregating, registering, publishing, purchasing, customizing, and re-registering generative AI models and prompts.

[0234] "Database" means a data storage system for storing and managing registered generative AI models and prompts.

[0235] "Means for online publication" refers to a method for publishing the generative AI model and prompt information stored in the database in a form accessible via the Internet.

[0236] The "means for receiving purchase requests" refers to the mechanism by which requests are received when a user applies to purchase a generative AI model or prompt through the platform.

[0237] "Payment System" means a system for processing and completing payments required when a user purchases a generative AI model or prompt.

[0238] "Customization" refers to the act of modifying the content of generative AI models or prompts purchased or acquired by a user to suit their own needs.

[0239] "Means for re-registration" refers to a method by which a user can re-register their customized generative AI model or prompts on the platform.

[0240] A "smartphone" is a portable information terminal that has Internet connectivity and can be used by installing various applications.

[0241] The present invention relates to a platform that utilizes generative AI models to aggregate and sell or provide prompts and generative AI models created by companies and individuals. The following describes in detail an embodiment of the present invention.

[0242] Hardware and Software

[0243] The system of this invention includes a server, a smartphone, a database, and a payment system. The server hosts an online platform and runs a web application using Flask. The database uses SQLite, and the payment system uses Stripe.

[0244] System Operation

[0245] Registration Process

[0246] Users register the prompts and generative AI models they have created using their smartphones. The information entered by the user, such as the prompt name, detailed description, use case, and pricing, is sent to the server. The server verifies the format and required items of the received data, and stores the verified data in an SQLite database. Once verification is complete, a notification of registration completion is sent to the user.

[0247] Publishing Process

[0248] The server converts the prompts and generative AI model information stored in the database into a searchable format, making these prompts available for other users to search and view on the online platform.

[0249] Purchase Process

[0250] The user selects what they need from prompts and generative AI models published on the online platform and submits a purchase request. The server receives this request and receives the user's purchase payment through a payment system (Stripe). Once the purchase is complete, the server sends the user a download link and API key and notifies them of the purchase completion.

[0251] Customization and Re-registration Process

[0252] Users can customize the generative AI models and prompts they have purchased on their smartphones. After customization, they send a request to the server to re-register them on the platform. The server again verifies the format and required items of the received data and re-registers them in the database. Once re-registration is complete, the customized generative AI models and prompts are made public again.

[0253] Specific examples

[0254] For example, consider a scenario where a user registers an "automated script generation prompt," which is then purchased by other users and used to generate movie scripts. The purchasing user can generate a script based on the prompt and customize it to suit their needs. The customized prompt can then be registered back on the platform and made available to other users.

[0255] Example prompt sentence:

[0256] "Automatic script generation prompt: This AI prompt is used to generate a movie script. Input the specified theme and character settings and it will automatically generate everything from the plot to the dialogue."

[0257] In this way, the present invention provides a comprehensive platform for efficiently aggregating, publishing, and trading generative AI models and prompts.

[0258] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0259] Step 1:

[0260] The server receives input from the user's smartphone when registering a prompt or generative AI model. The input includes information such as the prompt's name, detailed description, use case, and pricing. The server verifies that the format and required fields of this data are correct, and stores the verified data in an SQLite database. Once registration is complete, the server sends a notification to the user that registration is complete.

[0261] Step 2:

[0262] The server converts the information about the prompts and generative AI models stored in the database into a searchable format. Specifically, it extracts the metadata of the prompts and generative AI models, indexes them, and prepares them for display on a web page, allowing other users to search and view these prompts on an online platform from their smartphones.

[0263] Step 3:

[0264] The user selects the prompt or generative AI model they need from those published on the online platform and sends a purchase request to the server. The server receives this request and retrieves the price information of the corresponding prompt from a database. The server then charges the user for the purchase price through the payment system (Stripe) and completes the payment process. Once payment is complete, a download link and API key are generated and sent to the user, along with a notification that the purchase is complete.

[0265] Step 4:

[0266] Users customize the generative AI model and prompts they purchased on their smartphones. For example, they can change the prompt text or settings. The customized prompts are then sent to the server via a registration request. The server again verifies the format and required fields of the received data and stores it in the database. Once re-registration is complete, the customized prompts and generative AI models are made public again.

[0267] Step 5:

[0268] The server calculates the revenue share between the prompt creator and the platform operator based on the published prompts and the viewing and purchase history of the generating AI model. After calculating the revenue, the server transfers the revenue to the prompt creator's registered bank account or electronic wallet and notifies the prompt creator that the revenue share is complete.

[0269] 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.

[0270] The present invention relates to a system that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and combines an emotion engine with a platform for selling and providing these. The system of the present invention can be implemented in the following forms.

[0271] 1. Aggregation of prompt and generative AI models

[0272] Registering prompt and generative AI models

[0273] Users open a dedicated registration screen to register their created prompts and generative AI models on the platform, enter the required information such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[0274] Data Receipt and Validation

[0275] The server receives the prompts sent by the user and the generated AI model data, verifies that the format and required fields are correct, and stores the verified data in a database.

[0276] 2. Introducing the Emotion Engine

[0277] Collecting Emotional Data

[0278] The server is equipped with an emotion engine for collecting emotion data from inputs and operations of users accessing the platform, such as through keyboard input, mouse operation, facial expression recognition, and voice analysis.

[0279] Sentiment Data Analysis

[0280] The server analyzes the collected emotion data with an emotion engine to determine the user's emotional state, for example, whether the user is stressed, excited, or calm.

[0281] 3. Publishing the generative AI model and prompts and displaying recommendations

[0282] Preparation for release

[0283] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable form and prepares it for display on a web page.

[0284] public

[0285] The server uses the converted metadata to publish the prompts and generative AI models on an online platform, where users can freely browse and search them.

[0286] Recommendation display

[0287] The server then recommends the most appropriate generative AI model and prompts for the user based on the emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[0288] 4. Purchase procedure

[0289] Selecting a prompt

[0290] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[0291] Receiving and settling purchase requests

[0292] The server receives the user's purchase request, checks its contents, provides the user with a screen for entering payment information, and receives payment through the payment system after the payment information is entered. Once payment is complete, the server sends a notification of purchase completion to the user.

[0293] Providing generative AI models and prompts

[0294] The server provides the user with the prompts and generated AI model data for which the purchase has been completed. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data.

[0295] 5. Revenue Sharing

[0296] Calculating revenue

[0297] The server calculates the revenue share based on the purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[0298] Revenue sharing execution

[0299] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[0300] 6. Customization and Re-provision

[0301] Customizing prompts and generative AI models

[0302] Users can customize the generative AI models and prompts they purchase to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[0303] Re-registration process

[0304] The server receives the customized prompts and generated AI model data that the user has re-registered, verifies their format and required items, stores them in the database, and makes them public again.

[0305] Specific examples

[0306] For example, suppose a user creates a new natural language generation prompt and registers it on the platform. The prompt is then made public, and other users purchase it. After completing the purchase, the user customizes the prompt and registers it again on the platform. Furthermore, the emotion engine analyzes the user's emotional state, and based on the results, recommends the most suitable generation AI model and prompt for the user. This allows users to make efficient and satisfying selections.

[0307] The system of the present invention is implemented in the above manner, providing centralized information management, efficient transactions, fair revenue distribution, and dynamic recommendation display based on the user's emotional state, thereby realizing an environment in which companies and individuals can smoothly utilize generative AI models.

[0308] The processing flow will be explained below.

[0309] Step 1:

[0310] To register their own prompts and generative AI models on the platform, users open a dedicated registration screen, enter information such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[0311] Step 2:

[0312] The server receives the prompts sent by the user and the generated AI model data. It verifies that the data format and required fields have been entered correctly. Once the verification is complete, the data is stored in a database.

[0313] Step 3:

[0314] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format, preparing them for efficient search and browsing by users through the platform.

[0315] Step 4:

[0316] The server uses the converted metadata to publish the prompts and generative AI models on a webpage, where users can freely browse and search them.

[0317] Step 5:

[0318] The server runs an emotion engine that collects emotional data from the input and operations of users accessing the platform, including through keyboard input, mouse operation, facial expression recognition, and voice analysis.

[0319] Step 6:

[0320] The server uses an emotion engine to analyze the collected emotion data and determine the user's emotional state, for example, whether the user is stressed, excited, or calm.

[0321] Step 7:

[0322] The server then recommends the optimal generative AI model and prompts to the user based on the emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[0323] Step 8:

[0324] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[0325] Step 9:

[0326] The server receives the user's purchase request, verifies its contents, and then provides the user with a screen for entering payment information.

[0327] Step 10:

[0328] The user follows the server's instructions and enters payment information (credit card information, electronic payment service information, etc.). After entering the information, the user clicks the "Submit" button to complete the payment.

[0329] Step 11:

[0330] The server receives the user's purchase payment through the payment system. Once payment is complete, the server sends a purchase completion notification to the user.

[0331] Step 12:

[0332] The server provides the user with the prompts and generated AI model data for which the purchase has been completed. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data.

[0333] Step 13:

[0334] The server calculates the revenue share based on the user's purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[0335] Step 14:

[0336] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[0337] Step 15:

[0338] Users can customize the purchased prompts and generative AI models to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[0339] Step 16:

[0340] The server receives the customized prompts and generated AI model data registered by the user, verifies their format and required items, and stores the verified data in a database.

[0341] Step 17:

[0342] The server then converts the metadata of the customized prompts and generative AI models stored in the database into a searchable format and republishes them on the webpage, allowing new prompts and generative AI models to be constantly updated and made public.

[0343] Example 2

[0344] 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."

[0345] Current platforms that aggregate and provide generative AI models and prompts provide generic prompts and models without considering the user's emotional state, which means they are unable to provide optimal suggestions based on the user's needs and emotional state. Another problem is that the procedures for registering, purchasing, and customizing prompts and generative AI models are complicated, making it difficult to achieve efficient transactions.

[0346] The identification process 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 platform that aggregates prompts and generative AI models, a means for storing registered prompts and generative AI models in a database, a means for publishing the aggregated prompts and generative AI models online, a means for receiving a purchase request from a user and receiving payment through a payment system, a means for providing the user with a generative AI model or prompt after the purchase is completed, a means for having an emotion engine that collects emotional data from the user's input and operation, a means for analyzing the collected emotional data and determining the user's emotional state, and a means for recommending and displaying the generative AI model or prompt that is optimal for the user based on the emotional state. This makes it possible to recommend the optimal generative AI model or prompt according to the user's emotional state, thereby achieving an efficient and satisfying selection.

[0347] A "prompt" is input data that allows a user to give instructions or questions to a generative AI model.

[0348] A "generative AI model" is an algorithm that uses artificial intelligence to generate a response or output for a specific purpose.

[0349] A "database" is an information system for efficiently storing and managing large amounts of data.

[0350] An "emotion engine" is a system that collects emotional data from user input and operations, analyzes it, and determines the user's emotional state.

[0351] "Metadata" is data that describes information related to prompts and generative AI models, making them easier to search and organize within the database.

[0352] A "payment system" is a system for processing payments in online transactions.

[0353] "Revenue sharing" is the process of dividing revenue among the parties involved (prompt creators and platform operators).

[0354] "Customization" refers to the act of a user adjusting and modifying prompts and generative AI models to meet their specific needs.

[0355] The present invention relates to a system that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and combines an emotion engine with a platform for selling and providing them. This system is implemented as follows.

[0356] This system is primarily composed of a user, a terminal, and a server. The user uses the terminal to register the prompts and generative AI models they have created on the platform. The terminal provides an interface for entering information such as the prompt's name, detailed description, use case, and pricing using a registration screen. When the user clicks the "Submit" button, the terminal sends this data to the server.

[0357] The server receives the prompts and generated AI model data sent by the user and automatically verifies that the format and required fields are entered correctly. Once verified, the data is stored in a database. Specifically, the server uses a management system such as an SQL database to properly store and manage the data.

[0358] Furthermore, the server is equipped with an emotion engine that collects emotion data from user input and operations. Emotion data is collected through user keyboard input, mouse operation, facial expression recognition, and voice analysis. For example, software is used that uses a camera and microphone to analyze the user's facial expressions and voice. This is expected to use "Face API" for facial expression recognition and "Google Cloud Speech-to-Text API" for voice analysis.

[0359] The collected emotional data is analyzed by an emotion engine in the server to determine the user's emotional state. Emotional states include stress, excitement, and calmness. The analysis results are used to display recommendations to the user. For example, if the server determines that the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[0360] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format and prepares it for display on a web page, allowing users to freely browse and search the prompts and generative AI models on the online platform.

[0361] When a user selects a prompt or generative AI model and clicks the "Purchase" button, the purchase request is sent to the server, which receives payment through a payment system and notifies the user that the purchase is complete. This payment system uses online payment services such as PayPal or Stripe.

[0362] Once the purchase is complete, the server provides the generated AI model and prompt data to the user, for example, by sending a download link or API key, making the data immediately available to the user.

[0363] Users can also customize the generative AI models and prompts they have purchased to suit their needs and re-register the customized versions on the platform. The server receives the re-registered data, verifies the format and required items, stores it in the database, and makes it public again.

[0364] Specific examples

[0365] For example, when a user creates a new natural language generation prompt and registers it on the platform, they enter information such as the prompt name "Business Strategy Proposal Generator," detailed description "Prompt to generate a business report," pricing "1,000 yen," and use case "Generating a business report," and click the "Submit" button.

[0366] This allows the prompts created by users to be registered in a database and made public. If a registered prompt is purchased by another user, the purchaser can use the prompt, customize it as needed, and register it again on the platform.

[0367] Prompt Sentence Examples

[0368] “I want to use generative AI to create a natural language generation model that is best suited to a specific business scenario. I want it to first gather customer insights and then generate sales strategy ideas based on those insights.”

[0369] By implementing the system of the present invention in the above manner, it is possible to realize dynamic recommendation display based on the user's emotional state, efficient transaction procedures, and fair revenue distribution, providing an environment in which companies and individuals can smoothly utilize generative AI models.

[0370] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0371] Step 1:

[0372] Users open a dedicated registration screen on their device to register the prompts and generative AI models they have created on the platform.

[0373] Input: Prompt name, detailed description, usage example, pricing

[0374] Specific operations: Display the registration screen on the device, enter the required information, and then click the send button.

[0375] Output: Prompts and generated AI model data are sent from the device to the server.

[0376] Step 2:

[0377] The server receives user-submitted prompts and generated AI model data.

[0378] Input: Data submitted by the user

[0379] Specific operation: The server receives the data and automatically verifies that the format and required fields are entered correctly.

[0380] Output: Verification results for format and required items. Data that has been verified is stored in a database.

[0381] Step 3:

[0382] The server collects emotion data from user input and operations.

[0383] Input: User keyboard input, mouse operation, facial expression recognition, voice analysis

[0384] How it works: Emotion data is collected in real time using an emotion engine, specifically software that analyzes data captured from cameras and microphones.

[0385] Output: Collected emotion data

[0386] Step 4:

[0387] The server analyzes the collected emotional data to determine the user's emotional state.

[0388] Input: Emotion data

[0389] Specific operation: The emotion engine is used to analyze emotion data and determine emotional states such as stress, excitement, and calmness.

[0390] Output: User's emotional state

[0391] Step 5:

[0392] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable form and prepares it for display on a web page.

[0393] Input: Metadata stored in a database

[0394] Specific operation: The server converts the metadata based on a search algorithm and generates a search index.

[0395] Output: Data for display in search indexes and web pages

[0396] Step 6:

[0397] The server uses the converted metadata to publish the prompts and generative AI models on an online platform.

[0398] Input: Search index and web page display data

[0399] Specific operation: The server displays the data on a web page, allowing users to freely browse and search it.

[0400] Output: prompts and generative AI models published to an online platform

[0401] Step 7:

[0402] The server recommends the most appropriate generative AI model and prompts to the user based on their emotional state.

[0403] Input: User emotional state, published prompts, and generative AI model data

[0404] Specific operation: The server applies a recommendation algorithm that reflects the emotional state and displays a generative AI model and prompts appropriate for the user.

[0405] Output: Recommended generative AI models and prompts

[0406] Step 8:

[0407] Users choose what they need from the published prompts and generative AI models and click the "Purchase" button.

[0408] Input: Data selected from a list of published prompts and generative AI models

[0409] Specific operation: The user clicks the purchase button and a purchase request is sent to the server.

[0410] Output: Purchase request

[0411] Step 9:

[0412] The server receives the purchase request from the user and checks the contents of the request.

[0413] Input: Purchase Request

[0414] Specific operation: The server confirms the purchase request and provides the user with a screen for entering payment information.

[0415] Output: Payment information input screen

[0416] Step 10:

[0417] The server receives the user's payment information and receives payment through the payment system.

[0418] Input: User's payment information

[0419] What it does: Processes payments using payment systems (e.g., PayPal, credit card systems).

[0420] Output: Payment completion notification

[0421] Step 11:

[0422] The server provides the user with the generated AI model and prompt data that have been purchased.

[0423] Input: Payment completion information, purchase data

[0424] Specific operation: The server generates a download link and API key and sends them to the user.

[0425] Output: Data provided to the user

[0426] Step 12:

[0427] Users can customize the generative AI models and prompts they purchase to suit their needs and then register the customized versions back on the platform.

[0428] Input: Purchased generative AI models, prompts, and customizations

[0429] Specific operation: The user makes customizations and uses the re-registration screen to send the customized version to the server.

[0430] Output: Customized prompts and generative AI models

[0431] Step 13:

[0432] The server receives the registered data again, verifies the format and necessary items, stores it in the database, and makes it public again.

[0433] Input: Re-registration data

[0434] Specific operation: The server receives the data, verifies the format and required items, stores it in the database, and then makes it available online again.

[0435] Output: Republished customized prompts and generative AI models

[0436] (Application example 2)

[0437] 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."

[0438] In modern digital marketplaces, there are efficient systems for aggregating, publishing, and purchasing generative AI models and prompts. However, there is a lack of a means for optimally displaying generative AI model recommendations that take into account the user's emotional state. Furthermore, without dynamic recommendations that reflect the user's emotions during the purchasing process, the user experience may be limited. Furthermore, there is a need for appropriate and fair revenue distribution.

[0439] 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, in a platform that aggregates generative AI models, means for storing registered prompts and generative AI models in a database, means for publishing the aggregated prompts and generative AI models online, means for receiving purchase requests from users and receiving payment through a payment system, means for providing the user with the generative AI model or prompt after the purchase is completed, means for sharing the revenue from the purchase price between the prompt creator and the platform operator, means for using an emotion analysis engine to collect emotional data from user inputs and operations, and means for recommending and displaying the generative AI model or prompt that is optimal for the user based on the emotional data. This makes it possible to analyze the user's emotional state and recommend the optimal generative AI model or prompt, improving the user experience and realizing efficient transactions.

[0440] A "generative AI model" is an algorithm or program that uses artificial intelligence to perform specific tasks such as natural language generation or image generation.

[0441] A "prompt" is data such as text or images that is input to a generative AI model to guide the generated output.

[0442] The "database" is an information management system for organizing and storing registered prompts and generative AI models.

[0443] The "Platform" is an online system for aggregating, publishing, and purchasing generative AI models and prompts.

[0444] A "payment system" is a financial transaction system for safely and efficiently processing purchase payments from users.

[0445] An "emotion analysis engine" is a technology or algorithm that analyzes a user's emotional state based on data obtained from the user's input and operations.

[0446] "Recommendation display" refers to proposing and displaying the optimal generative AI model and prompts to the user based on emotional data analyzed by the emotion analysis engine.

[0447] "Revenue sharing" means the process of calculating and transferring the purchase price to be appropriately divided between the prompt creator and the platform operator.

[0448] "Customization" refers to the act of modifying and adjusting the generative AI model or prompts purchased by a user to suit their own needs.

[0449] "Online publishing means" refers to methods or technologies that allow registered prompts and generative AI models to be viewed and purchased by users on the Internet.

[0450] The present invention relates to a system that combines a sentiment analysis engine with a platform for aggregating, selling, and delivering generative AI models and prompts, implemented using the following means:

[0451] First, the user registers the generative AI model or prompt on the platform. To do this, they open a dedicated registration screen, enter the required information such as the prompt's name, detailed description, use case, and pricing, and click the "Submit" button. The server receives the submitted data and verifies that the format and required fields have been entered correctly, and once verified, the data is stored in the database.

[0452] Next, an emotion analysis engine is used to collect emotional data from user input and operations. Emotional data is collected through the user's keyboard input, mouse operation, facial expression recognition, voice analysis, etc. The server analyzes the collected emotional data and determines the user's emotional state.

[0453] For example, if a user enters "I've been feeling stressed at work lately," the server will use its emotion analysis engine to determine the user's emotion as "stress." Based on this emotion data, the server will recommend the optimal generative AI model and prompts for the user. In this example, the server will recommend a "generative AI model that helps you relax."

[0454] Once the recommended generative AI models and prompts are made public, users can freely browse and search them. The user selects the prompt or generative AI model they need and clicks the "Purchase" button. The server receives the purchase request, checks its contents, and then provides the user with a screen for entering payment information. After the payment information is entered, the server receives payment through the payment system. Once the payment is complete, the server sends the user a notification that the purchase is complete.

[0455] The server then provides the user with the data for the generative AI model or prompt that has been purchased. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data. Users can also customize the generative AI model or prompt they purchased to suit their own needs and re-register the customized version on the platform. The server receives the re-registered data, verifies its format and required items, stores it in the database, and publishes it again.

[0456] Furthermore, a revenue sharing system will calculate a revenue share based on the purchase price, which will be divided appropriately between the prompt creator and the platform operator and transferred to the prompt creator's registered bank account or electronic wallet.

[0457] As described above, this system analyzes the user's emotional state to recommend the optimal generative AI model and prompts, enabling efficient and satisfying transactions, while ensuring fair and appropriate revenue distribution.

[0458] For example, if a user inputs "I've been feeling stressed at work lately," the server will perform emotion analysis and recommend a "generative AI model that will help you relax." In this way, the user experience can be improved by providing the optimal prompts and generative AI models according to the user's emotional state.

[0459] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0460] Step 1:

[0461] Users register generated AI models and prompts on the platform.

[0462] Input: The user enters information such as the name, description, use case, and pricing of the generated AI model or prompt.

[0463] Data processing: The user enters the necessary information on a dedicated registration screen and clicks the "Submit" button.

[0464] Output: Generated AI model and prompt data are sent to the server.

[0465] Step 2:

[0466] The server receives the data and verifies that the format and required fields are correct.

[0467] Input: The generative AI model and prompt data sent in Step 1.

[0468] Data processing: Automated scripts are run to check for missing or incorrect data.

[0469] Output: Data that has been validated. If there are no problems with the format or required items, proceed to the next step.

[0470] Step 3:

[0471] The server stores the validated data in the database.

[0472] Input: Data for the generative AI model and prompts that have been validated in Step 2.

[0473] Data manipulation: Inserting data into the appropriate tables in the database.

[0474] Output: Generative AI models and prompts stored in a database.

[0475] Step 4:

[0476] Use a sentiment analysis engine to collect emotional data from user input and actions.

[0477] Input: Data such as user keyboard input, mouse actions, facial expression recognition, and voice analysis.

[0478] Data calculation: The sentiment analysis engine analyzes these data in real time to determine the user's emotional state.

[0479] Output: Determined user emotion data.

[0480] Step 5:

[0481] Based on the emotional data, the server recommends the most suitable generative AI model and prompts for the user.

[0482] Input: User emotion data determined in step 4.

[0483] Data computation: Search and filter relevant generative AI models and prompts based on emotion data.

[0484] Output: The generated AI model and prompts that are displayed to the user.

[0485] Step 6:

[0486] The user selects a recommended generative AI model or prompt and clicks the "Purchase" button.

[0487] Input: User selection and payment information.

[0488] Data processing: Send a purchase request to the server and enter payment information on the payment screen.

[0489] Output: Purchase request and payment information is sent to the server.

[0490] Step 7:

[0491] The server receives the purchase request and verifies its contents.

[0492] Input: Purchase request and payment information submitted in step 6.

[0493] Data processing: Receive payment through the payment system.

[0494] Output: A notification of payment completion is sent to the user.

[0495] Step 8:

[0496] Provide users with generative AI models and prompts upon purchase completion.

[0497] Input: Data from the generative AI model or prompt that you purchased.

[0498] Data processing: Generate and provide download links and API keys to users.

[0499] Output: A link or key that allows users to access the generated AI model and prompts.

[0500] Step 9:

[0501] Customize the generative AI models and prompts you purchase to fit your needs.

[0502] Input: Data from purchased generative AI models and prompts.

[0503] Data calculation: User adjusts programs and parameters.

[0504] Output: Customized generative AI models and prompts.

[0505] Step 10:

[0506] The user re-registers the customization.

[0507] Input: Data for customized generative AI models and prompts.

[0508] Data processing: Send data from the re-registration screen.

[0509] Output: Data re-registered on the server.

[0510] Step 11:

[0511] The server receives the re-registered data and re-verifies its format and required items.

[0512] Input: The generative AI model and prompt data retrained in step 10.

[0513] Data calculation: Re-verification of data format and required items.

[0514] Output: The validated data.

[0515] Step 12:

[0516] The server stores the verified data in the database and makes it public again.

[0517] Input: The data that has passed validation in step 11.

[0518] Data processing: Re-insert the data into the appropriate tables in the database and set it to public.

[0519] Output: The published customization stored in the database.

[0520] Step 13:

[0521] The revenue sharing system calculates and distributes the revenue share amount based on the purchase price.

[0522] Input: User purchase data and revenue sharing rules.

[0523] Data calculation: Calculation of revenue share.

[0524] Output: Revenue share remittance to prompt creators and platform operators.

[0525] 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.

[0526] 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.

[0527] 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.

[0528] [Second embodiment]

[0529] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0530] 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.

[0531] 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).

[0532] 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.

[0533] 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.

[0534] 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).

[0535] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0536] 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.

[0537] 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.

[0538] 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.

[0539] 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.

[0540] 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."

[0541] The present invention relates to a platform that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and sells or provides them. The system of the present invention is embodied in the following form.

[0542] 1. Aggregation of prompt and generative AI models

[0543] Registering prompt and generative AI models

[0544] Users register their own prompts and generative AI models on the platform by entering information such as the prompt name, detailed description, use case, and pricing on the registration screen and clicking the "Submit" button.

[0545] Data Receipt and Validation

[0546] The server receives the prompts sent by the user and the data from the generative AI model. The received data is verified to ensure that the format and required fields are entered correctly. Once verified, the data is stored in a database.

[0547] 2. Publishing generative AI models and prompts

[0548] Preparation for release

[0549] The server converts the metadata of the prompts and generative AI models registered in the database into a searchable format and prepares it for display on a web page.

[0550] public

[0551] The server publishes the ready-to-publish prompts and generative AI models on an online platform, where they can be browsed and searched by users.

[0552] 3. Purchase procedure

[0553] Selecting a prompt

[0554] Users choose what they need from the published prompts and generative AI models and click the "Purchase" button.

[0555] Receiving a purchase request

[0556] The server receives the user's purchase request and checks its contents.

[0557] Enter your payment information

[0558] The user follows the server's instructions and enters payment information (credit card information, electronic payment service information, etc.).

[0559] Payment Processing

[0560] The server receives the user's purchase payment through the payment system, and once payment is complete, sends the user a purchase completion notification.

[0561] Providing generative AI models and prompts

[0562] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by sending the user a download link and API key.

[0563] 4. Revenue Sharing

[0564] Calculating revenue

[0565] The server calculates the revenue share based on the purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[0566] Revenue sharing execution

[0567] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[0568] 5. Customization and Re-provision

[0569] Customizing prompts and generative AI models

[0570] Users can download the generative AI models and prompts they purchase and customize them to suit their needs.

[0571] Re-registering a customized version

[0572] The user can then re-register the customized generative AI model and prompts on the platform by entering the necessary information on the prompt registration screen again and submitting it.

[0573] Re-registration process

[0574] The server verifies the data format and required items of the re-registered customized prompts and generative AI models, stores them in the database, and then prepares them for publication and publishes them again.

[0575] Specific examples

[0576] For example, a user can create a new natural language generation prompt and register it on the platform. The prompt is then published, and other users can purchase it. After completing the purchase, the user can customize the prompt and register it again on the platform. In this way, new prompts and generative AI models are constantly being aggregated, published, and revenues are shared.

[0577] The system of the present invention is implemented in the above manner, providing centralized information management, efficient transactions, and fair revenue distribution, thereby realizing an environment in which companies and individuals can smoothly utilize generative AI models.

[0578] The processing flow will be explained below.

[0579] Step 1:

[0580] Users open a dedicated registration screen to register their own prompts and generative AI models on the platform. On the registration screen, they enter the required information, such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[0581] Step 2:

[0582] The server receives the prompts sent by the user and the data from the generative AI model. It verifies that the received data is correctly formatted and that all required fields are entered. If the data is determined to be correct, it stores the data in a database.

[0583] Step 3:

[0584] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format, preparing them for efficient search and browsing by users through the platform.

[0585] Step 4:

[0586] The server uses the converted metadata to publish the prompts and generative AI models on a webpage, where users can freely browse and search them.

[0587] Step 5:

[0588] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[0589] Step 6:

[0590] The server receives the user's purchase request, verifies its contents, and then provides the user with a screen for entering payment information.

[0591] Step 7:

[0592] The user follows the instructions of the server and enters payment information such as credit card information and electronic payment service information, then clicks the "Submit" button to complete the payment.

[0593] Step 8:

[0594] The server receives payment from the user through the payment system. Once payment is complete, the server sends a notification to the user that the purchase has been completed.

[0595] Step 9:

[0596] The server provides the user with the prompts and generated AI model data for which the purchase has been completed, and the user is sent a download link and API key, allowing them to immediately use the purchased data.

[0597] Step 10:

[0598] The server calculates the revenue share based on the user's purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[0599] Step 11:

[0600] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[0601] Step 12:

[0602] Users can customize the purchased prompts and generative AI models to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[0603] Step 13:

[0604] The server receives the customized prompts and generated AI model data registered by the user, verifies their format and required items, and stores the verified data in a database.

[0605] Step 14:

[0606] The server then converts the metadata of the customized prompts and generative AI models stored in the database into a searchable format and republishes them on the webpage, allowing new prompts and generative AI models to be constantly updated and made public.

[0607] Example 1

[0608] 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."

[0609] Today, businesses and individuals lack a platform for effectively managing and trading generative AI models and prompts. Therefore, there is a need for a system that allows users to easily register, sell, and reuse their generated prompts and AI models. Furthermore, the purchasing procedures and revenue distribution processes are complex, and an efficient and fair method is needed.

[0610] 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.

[0611] In this invention, the server includes means for a user to input prompts and generative AI models and send the contents to the server, means for the server to receive the data sent from the user and verify the format and necessary items, means for storing the verified data in a database and notifying the user, means for converting the stored data into a searchable format and publishing it on an online platform, means for receiving purchase requests from users and receiving payment through a payment system, means for providing generative AI models and prompts after purchase is completed, and means for sharing revenue from the purchase price. This allows users to efficiently register, publish, sell, and reuse prompts and generative AI models, and enables fair and smooth revenue sharing.

[0612] "User" means an individual or entity that uses the Platform to register, purchase, and customize prompts and generative AI models.

[0613] A "prompt" is text data or instructions input into a generative AI model that determines the output content generated.

[0614] A "generative AI model" is an artificial intelligence model that performs natural language processing or generative tasks, including algorithms for generating output in response to prompts.

[0615] "Server" is a central control device that manages the entire system and performs various processes such as receiving, verifying, storing, publishing, payment processing, and revenue distribution of data.

[0616] "Database" means a storage system for centrally managing and storing data, including prompts and generative AI models.

[0617] "Payment system" means a system for processing payments for user purchases, including credit cards and electronic payment services.

[0618] "Revenue sharing" is a system in which revenue earned when users sell prompts or generative AI models is divided fairly between prompt creators and platform operators.

[0619] "Customization" refers to the process by which users edit and modify the generative AI models and prompts they purchase to adapt them to their own specific needs.

[0620] "Online Platform" means a web-based system that enables users to register, publish, sell, buy, and customize prompt and generative AI models.

[0621] "Re-registration" refers to the act of a user customizing the prompts and generative AI models that were initially registered and then registering them again on the platform.

[0622] The present invention relates to a platform for aggregating prompts and generative AI models created by companies and individuals using generative AI models, and for selling and providing them. This platform is composed of components such as a server, terminals, databases, online interfaces, and payment systems.

[0623] Process Overview

[0624] 1. Registering a prompt and generate AI model

[0625] The user uses a device to access the platform's registration screen, enters the prompts and details of the generated AI model (such as name, detailed description, use case, pricing, etc.), and clicks the "Submit" button.

[0626] The server receives the data sent by the user and verifies whether the data format and required items have been entered correctly. Once the verification is complete, the data is stored in a database.

[0627] 2. Publishing generative AI models and prompts

[0628] The server converts the metadata of the prompts and generative AI models registered in the database into a searchable format and generates a user interface, allowing users to browse and search the published prompts and generative AI models on an online platform.

[0629] 3. Purchase procedure

[0630] Users select a published prompt or generative AI model, click the "Purchase" button, and enter their payment information.

[0631] The server receives the purchase request and payment information from the user, receives the payment through the payment system, and sends a notification of purchase completion to the user once the payment is complete.

[0632] 4. Providing generative AI models and prompts

[0633] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by emailing the user a download link and API key.

[0634] 5. Revenue Sharing

[0635] The server calculates the revenue share based on the purchase price, distributes the revenue according to the distribution ratio between the prompt creator and the platform operator, and transfers the revenue share to the prompt creator's bank account or electronic wallet.

[0636] 6. Customization and Re-provision

[0637] Users can customize the generative AI models and prompts they purchase to suit their own needs.

[0638] Users can then re-register their customized generative AI models and prompts on the platform, where the re-registered data will be verified by the server again, stored in the database, and published again on the online platform once it is ready to be published.

[0639] Specific examples

[0640] For example, suppose a user creates a new natural language generation prompt and registers it on the platform. The prompt is then published and other users can purchase it. Here is an example of a prompt:

[0641] "Example Natural Language Generation Prompt: Generate a conversation about a topic of interest to a college student."

[0642] After completing the purchase, the user can customize the prompt and register again on the platform, thus constantly collecting and publishing new prompts and generative AI models, and sharing revenues.

[0643] The system of the present invention provides centralized information management, efficient transactions, and fair revenue distribution, creating an environment in which companies and individuals can smoothly utilize generative AI models.

[0644] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0645] Step 1: User Data Entry

[0646] Users use their device to access the platform's registration screen and enter prompts and details about the generated AI model (such as name, detailed description, use cases, and pricing).

[0647] Input: Prompt and details about the generated AI model.

[0648] Output: Input data temporarily stored on the device.

[0649] Specific behavior: The user enters data into the input field and clicks the "Submit" button. The device temporarily stores the entered data.

[0650] Step 2: Sending data

[0651] The terminal transmits the saved input data to the server.

[0652] Input: User input data.

[0653] Output: The data sent to the server.

[0654] Specific operation: The device generates an HTTP request and sends the input data to the server.

[0655] Step 3: Receiving and verifying data

[0656] The server receives the data sent by the user and verifies whether the format and required items have been entered correctly.

[0657] Input: The user's data received by the server.

[0658] Output: Validation results and data to be stored in the database.

[0659] Specific behavior: The server checks the format and required fields of the received data, and generates an error message if there is invalid data.

[0660] Step 4: Store the data

[0661] The server stores the verified data in a database.

[0662] Input: The user's data after validation.

[0663] Output: Data stored in the database and notification to the user.

[0664] What happens: The server generates the SQL commands to insert the data into the database, then notifies the user that the registration is complete.

[0665] Step 5: Convert metadata and prepare for publishing

[0666] The server converts the metadata registered in the database into a searchable format and generates a user interface.

[0667] Input: Metadata stored in a database.

[0668] Output: A search index and a user interface.

[0669] What it does: The server indexes the metadata and dynamically generates the web page.

[0670] Step 6: Publish online

[0671] The server publishes the ready generative AI models and prompts on an online platform.

[0672] Input: Prepared prompts and metadata for the generative AI model.

[0673] Output: The published prompt and / or generative AI model.

[0674] What happens: The server updates the web page to display the published prompt and generative AI model.

[0675] Step 7: User selects prompt

[0676] Users can browse published prompts and generative AI models on the platform and click the "Purchase" button for the one they need.

[0677] Input: A list of published prompts and generative AI models.

[0678] Output: Selected prompts and generative AI models.

[0679] What happens: The user navigates through the web interface, selects the item they want to purchase, and clicks the "Buy" button.

[0680] Step 8: Receiving a Purchase Request

[0681] The server receives the user's purchase request and payment information and verifies the contents.

[0682] Input: User purchase request and payment information.

[0683] Output: Confirmed request and payment information.

[0684] Specific operation: The server generates a token for payment information and sends it to the payment system.

[0685] Step 9: Payment Processing

[0686] The server receives payment through the payment system, and once payment is complete, sends a notification to the user that the purchase is complete.

[0687] Input: Payment information.

[0688] Output: Payment completion notification.

[0689] Specific operation: The server calls the payment system API and notifies the user when the payment is successful.

[0690] Step 10: Providing generative AI models and prompts

[0691] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by emailing the user a download link and API key.

[0692] Input: Purchase completion data.

[0693] Output: Download link and API key.

[0694] What happens: The server uses an email service to send the user an email containing the necessary download link and API key.

[0695] Step 11: Calculate Revenue Share

[0696] The server calculates the revenue share amount based on the purchase price and distributes the revenue according to the distribution ratio between the prompt creator and the platform operator.

[0697] Input: Purchase price data and distribution percentage.

[0698] Output: Calculated distribution amount.

[0699] Specific operation: The server executes the calculation algorithm and calculates the distribution amount.

[0700] Step 12: Implementing Revenue Sharing

[0701] The server transfers the calculated revenue share amount to the prompt creator's registered bank account or electronic wallet.

[0702] Input: Calculated distribution amount.

[0703] Output: Remittance completion notification.

[0704] Specific operation: The server calls the API of the bank or electronic wallet to transfer the distribution amount, and then sends a notification of the completion of the transfer to the creator.

[0705] Step 13: Customizing prompts and generative AI models

[0706] Users can download the generative AI models and prompts they purchase and customize them to suit their needs.

[0707] Input: Downloaded generative AI model and prompts.

[0708] Output: Customized generative AI models and prompts.

[0709] Specific operation: The user edits and modifies the generated AI model and prompts in the local environment.

[0710] Step 14: Re-register your customizations

[0711] Users can re-register their customized generative AI models and prompts to the platform by entering the necessary information on the prompt registration screen again and clicking the "Submit" button.

[0712] Input: Customized generative AI models and prompts.

[0713] Output: Re-enrollment data sent to the platform.

[0714] Specific behavior: The user enters the required information on the re-registration screen and the customized data is sent to the server.

[0715] Step 15: Receiving and verifying re-enrollment data

[0716] The server receives the registered prompt and generated AI model data again and verifies that the format and required fields have been entered correctly.

[0717] Input: Re-registered data.

[0718] Output: Validation results and data to be stored in the database.

[0719] Specific operation: The server verifies the data format and required items, just as it did during initial registration.

[0720] Step 16: Store and republish resubmission data

[0721] The server stores the re-registered data in a database and makes it available again on the online platform.

[0722] Input: Your verified re-enrollment data.

[0723] Output: Published re-registration data.

[0724] Specific operation: The server stores the data after validation in a database and makes it public once it is ready.

[0725] (Application example 1)

[0726] 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."

[0727] Platforms that utilize generative AI models are required to provide an environment where users can smoothly and efficiently complete the entire process of registering, searching, purchasing, and customizing prompts and generative AI models. A system is also required that allows users to easily customize and re-register purchased prompts. Conventional systems make these processes cumbersome, and one issue is that they do not adequately support operation on smart devices.

[0728] 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.

[0729] In this invention, the server includes a platform that aggregates generative AI models, a means for storing registered prompts and generative AI models in a database, a means for publishing the aggregated prompts and generative AI models online, and a means for receiving purchase requests from users and receiving payment through a payment system. This allows users to intuitively perform a series of operations using their smartphones to register, search, purchase, and customize prompts and generative AI models. Furthermore, the ease of performing a series of operations to register and publish user-customized prompts on the platform further expands the scope of use of generative AI models.

[0730] A "generative AI model" is a model that automatically generates content and data using artificial intelligence algorithms.

[0731] A "prompt" is an instruction or command that is input to a generative AI model, and is a phrase that specifies the type and content of the content to be generated.

[0732] "Platform" means an online system for aggregating, registering, publishing, purchasing, customizing, and re-registering generative AI models and prompts.

[0733] "Database" means a data storage system for storing and managing registered generative AI models and prompts.

[0734] "Means for online publication" refers to a method for publishing the generative AI model and prompt information stored in the database in a form accessible via the Internet.

[0735] The "means for receiving purchase requests" refers to the mechanism by which requests are received when a user applies to purchase a generative AI model or prompt through the platform.

[0736] "Payment System" means a system for processing and completing payments required when a user purchases a generative AI model or prompt.

[0737] "Customization" refers to the act of modifying the content of generative AI models or prompts purchased or acquired by a user to suit their own needs.

[0738] "Means for re-registration" refers to a method by which a user can re-register their customized generative AI model or prompts on the platform.

[0739] A "smartphone" is a portable information terminal that has Internet connectivity and can be used by installing various applications.

[0740] The present invention relates to a platform that utilizes generative AI models to aggregate and sell or provide prompts and generative AI models created by companies and individuals. The following describes in detail an embodiment of the present invention.

[0741] Hardware and Software

[0742] The system of this invention includes a server, a smartphone, a database, and a payment system. The server hosts an online platform and runs a web application using Flask. The database uses SQLite, and the payment system uses Stripe.

[0743] System Operation

[0744] Registration Process

[0745] Users register the prompts and generative AI models they have created using their smartphones. The information entered by the user, such as the prompt name, detailed description, use case, and pricing, is sent to the server. The server verifies the format and required items of the received data, and stores the verified data in an SQLite database. Once verification is complete, a notification of registration completion is sent to the user.

[0746] Publishing Process

[0747] The server converts the prompts and generative AI model information stored in the database into a searchable format, making these prompts available for other users to search and view on the online platform.

[0748] Purchase Process

[0749] The user selects what they need from prompts and generative AI models published on the online platform and submits a purchase request. The server receives this request and receives the user's purchase payment through a payment system (Stripe). Once the purchase is complete, the server sends the user a download link and API key and notifies them of the purchase completion.

[0750] Customization and Re-registration Process

[0751] Users can customize the generative AI models and prompts they have purchased on their smartphones. After customization, they send a request to the server to re-register them on the platform. The server again verifies the format and required items of the received data and re-registers them in the database. Once re-registration is complete, the customized generative AI models and prompts are made public again.

[0752] Specific examples

[0753] For example, consider a scenario where a user registers an "automated script generation prompt," which is then purchased by other users and used to generate movie scripts. The purchasing user can generate a script based on the prompt and customize it to suit their needs. The customized prompt can then be registered back on the platform and made available to other users.

[0754] Example prompt sentence:

[0755] "Automatic script generation prompt: This AI prompt is used to generate a movie script. Input the specified theme and character settings and it will automatically generate everything from the plot to the dialogue."

[0756] In this way, the present invention provides a comprehensive platform for efficiently aggregating, publishing, and trading generative AI models and prompts.

[0757] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0758] Step 1:

[0759] The server receives input from the user's smartphone when registering a prompt or generative AI model. The input includes information such as the prompt's name, detailed description, use case, and pricing. The server verifies that the format and required fields of this data are correct, and stores the verified data in an SQLite database. Once registration is complete, the server sends a notification to the user that registration is complete.

[0760] Step 2:

[0761] The server converts the information about the prompts and generative AI models stored in the database into a searchable format. Specifically, it extracts the metadata of the prompts and generative AI models, indexes them, and prepares them for display on a web page, allowing other users to search and view these prompts on an online platform from their smartphones.

[0762] Step 3:

[0763] The user selects the prompt or generative AI model they need from those published on the online platform and sends a purchase request to the server. The server receives this request and retrieves the price information of the corresponding prompt from a database. The server then charges the user for the purchase price through the payment system (Stripe) and completes the payment process. Once payment is complete, a download link and API key are generated and sent to the user, along with a notification that the purchase is complete.

[0764] Step 4:

[0765] Users customize the generative AI model and prompts they purchased on their smartphones. For example, they can change the prompt text or settings. The customized prompts are then sent to the server via a registration request. The server again verifies the format and required fields of the received data and stores it in the database. Once re-registration is complete, the customized prompts and generative AI models are made public again.

[0766] Step 5:

[0767] The server calculates the revenue share between the prompt creator and the platform operator based on the published prompts and the viewing and purchase history of the generating AI model. After calculating the revenue, the server transfers the revenue to the prompt creator's registered bank account or electronic wallet and notifies the prompt creator that the revenue share is complete.

[0768] 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.

[0769] The present invention relates to a system that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and combines an emotion engine with a platform for selling and providing these. The system of the present invention can be implemented in the following forms.

[0770] 1. Aggregation of prompt and generative AI models

[0771] Registering prompt and generative AI models

[0772] Users open a dedicated registration screen to register their created prompts and generative AI models on the platform, enter the required information such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[0773] Data Receipt and Validation

[0774] The server receives the prompts sent by the user and the generated AI model data, verifies that the format and required fields are correct, and stores the verified data in a database.

[0775] 2. Introducing the Emotion Engine

[0776] Collecting Emotional Data

[0777] The server is equipped with an emotion engine for collecting emotion data from inputs and operations of users accessing the platform, such as through keyboard input, mouse operation, facial expression recognition, and voice analysis.

[0778] Sentiment Data Analysis

[0779] The server analyzes the collected emotion data with an emotion engine to determine the user's emotional state, for example, whether the user is stressed, excited, or calm.

[0780] 3. Publishing the generative AI model and prompts and displaying recommendations

[0781] Preparation for release

[0782] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable form and prepares it for display on a web page.

[0783] public

[0784] The server uses the converted metadata to publish the prompts and generative AI models on an online platform, where users can freely browse and search them.

[0785] Recommendation display

[0786] The server then recommends the most appropriate generative AI model and prompts for the user based on the emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[0787] 4. Purchase procedure

[0788] Selecting a prompt

[0789] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[0790] Receiving and settling purchase requests

[0791] The server receives the user's purchase request, checks its contents, provides the user with a screen for entering payment information, and receives payment through the payment system after the payment information is entered. Once payment is complete, the server sends a notification of purchase completion to the user.

[0792] Providing generative AI models and prompts

[0793] The server provides the user with the prompts and generated AI model data for which the purchase has been completed. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data.

[0794] 5. Revenue Sharing

[0795] Calculating revenue

[0796] The server calculates the revenue share based on the purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[0797] Revenue sharing execution

[0798] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[0799] 6. Customization and Re-provision

[0800] Customizing prompts and generative AI models

[0801] Users can customize the generative AI models and prompts they purchase to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[0802] Re-registration process

[0803] The server receives the customized prompts and generated AI model data that the user has re-registered, verifies their format and required items, stores them in the database, and makes them public again.

[0804] Specific examples

[0805] For example, suppose a user creates a new natural language generation prompt and registers it on the platform. The prompt is then made public, and other users purchase it. After completing the purchase, the user customizes the prompt and registers it again on the platform. Furthermore, the emotion engine analyzes the user's emotional state, and based on the results, recommends the most suitable generation AI model and prompt for the user. This allows users to make efficient and satisfying selections.

[0806] The system of the present invention is implemented in the above manner, providing centralized information management, efficient transactions, fair revenue distribution, and dynamic recommendation display based on the user's emotional state, thereby realizing an environment in which companies and individuals can smoothly utilize generative AI models.

[0807] The processing flow will be explained below.

[0808] Step 1:

[0809] To register their own prompts and generative AI models on the platform, users open a dedicated registration screen, enter information such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[0810] Step 2:

[0811] The server receives the prompts sent by the user and the generated AI model data. It verifies that the data format and required fields have been entered correctly. Once the verification is complete, the data is stored in a database.

[0812] Step 3:

[0813] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format, preparing them for efficient search and browsing by users through the platform.

[0814] Step 4:

[0815] The server uses the converted metadata to publish the prompts and generative AI models on a webpage, where users can freely browse and search them.

[0816] Step 5:

[0817] The server runs an emotion engine that collects emotional data from the input and operations of users accessing the platform, including through keyboard input, mouse operation, facial expression recognition, and voice analysis.

[0818] Step 6:

[0819] The server uses an emotion engine to analyze the collected emotion data and determine the user's emotional state, for example, whether the user is stressed, excited, or calm.

[0820] Step 7:

[0821] The server then recommends the optimal generative AI model and prompts to the user based on the emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[0822] Step 8:

[0823] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[0824] Step 9:

[0825] The server receives the user's purchase request, verifies its contents, and then provides the user with a screen for entering payment information.

[0826] Step 10:

[0827] The user follows the server's instructions and enters payment information (credit card information, electronic payment service information, etc.). After entering the information, the user clicks the "Submit" button to complete the payment.

[0828] Step 11:

[0829] The server receives the user's purchase payment through the payment system. Once payment is complete, the server sends a purchase completion notification to the user.

[0830] Step 12:

[0831] The server provides the user with the prompts and generated AI model data for which the purchase has been completed. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data.

[0832] Step 13:

[0833] The server calculates the revenue share based on the user's purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[0834] Step 14:

[0835] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[0836] Step 15:

[0837] Users can customize the purchased prompts and generative AI models to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[0838] Step 16:

[0839] The server receives the customized prompts and generated AI model data registered by the user, verifies their format and required items, and stores the verified data in a database.

[0840] Step 17:

[0841] The server then converts the metadata of the customized prompts and generative AI models stored in the database into a searchable format and republishes them on the webpage, allowing new prompts and generative AI models to be constantly updated and made public.

[0842] Example 2

[0843] 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."

[0844] Current platforms that aggregate and provide generative AI models and prompts provide generic prompts and models without considering the user's emotional state, which means they are unable to provide optimal suggestions based on the user's needs and emotional state. Another problem is that the procedures for registering, purchasing, and customizing prompts and generative AI models are complicated, making it difficult to achieve efficient transactions.

[0845] The identification process 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 platform that aggregates prompts and generative AI models, a means for storing registered prompts and generative AI models in a database, a means for publishing the aggregated prompts and generative AI models online, a means for receiving a purchase request from a user and receiving payment through a payment system, a means for providing the user with a generative AI model or prompt after the purchase is completed, a means for having an emotion engine that collects emotional data from the user's input and operation, a means for analyzing the collected emotional data and determining the user's emotional state, and a means for recommending and displaying the generative AI model or prompt that is optimal for the user based on the emotional state. This makes it possible to recommend the optimal generative AI model or prompt according to the user's emotional state, thereby achieving an efficient and satisfying selection.

[0846] A "prompt" is input data that allows a user to give instructions or questions to a generative AI model.

[0847] A "generative AI model" is an algorithm that uses artificial intelligence to generate a response or output for a specific purpose.

[0848] A "database" is an information system for efficiently storing and managing large amounts of data.

[0849] An "emotion engine" is a system that collects emotional data from user input and operations, analyzes it, and determines the user's emotional state.

[0850] "Metadata" is data that describes information related to prompts and generative AI models, making them easier to search and organize within the database.

[0851] A "payment system" is a system for processing payments in online transactions.

[0852] "Revenue sharing" is the process of dividing revenue among the parties involved (prompt creators and platform operators).

[0853] "Customization" refers to the act of a user adjusting and modifying prompts and generative AI models to meet their specific needs.

[0854] The present invention relates to a system that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and combines an emotion engine with a platform for selling and providing them. This system is implemented as follows.

[0855] This system is primarily composed of a user, a terminal, and a server. The user uses the terminal to register the prompts and generative AI models they have created on the platform. The terminal provides an interface for entering information such as the prompt's name, detailed description, use case, and pricing using a registration screen. When the user clicks the "Submit" button, the terminal sends this data to the server.

[0856] The server receives the prompts and generated AI model data sent by the user and automatically verifies that the format and required fields are entered correctly. Once verified, the data is stored in a database. Specifically, the server uses a management system such as an SQL database to properly store and manage the data.

[0857] Furthermore, the server is equipped with an emotion engine that collects emotion data from user input and operations. Emotion data is collected through user keyboard input, mouse operation, facial expression recognition, and voice analysis. For example, software is used that uses a camera and microphone to analyze the user's facial expressions and voice. This is expected to use "Face API" for facial expression recognition and "Google Cloud Speech-to-Text API" for voice analysis.

[0858] The collected emotional data is analyzed by an emotion engine in the server to determine the user's emotional state. Emotional states include stress, excitement, and calmness. The analysis results are used to display recommendations to the user. For example, if the server determines that the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[0859] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format and prepares it for display on a web page, allowing users to freely browse and search the prompts and generative AI models on the online platform.

[0860] When a user selects a prompt or generative AI model and clicks the "Purchase" button, the purchase request is sent to the server, which receives payment through a payment system and notifies the user that the purchase is complete. This payment system uses online payment services such as PayPal or Stripe.

[0861] Once the purchase is complete, the server provides the generated AI model and prompt data to the user, for example, by sending a download link or API key, making the data immediately available to the user.

[0862] Users can also customize the generative AI models and prompts they have purchased to suit their needs and re-register the customized versions on the platform. The server receives the re-registered data, verifies the format and required items, stores it in the database, and makes it public again.

[0863] Specific examples

[0864] For example, when a user creates a new natural language generation prompt and registers it on the platform, they enter information such as the prompt name "Business Strategy Proposal Generator," detailed description "Prompt to generate a business report," pricing "1,000 yen," and use case "Generating a business report," and click the "Submit" button.

[0865] This allows the prompts created by users to be registered in a database and made public. If a registered prompt is purchased by another user, the purchaser can use the prompt, customize it as needed, and register it again on the platform.

[0866] Prompt Sentence Examples

[0867] “I want to use generative AI to create a natural language generation model that is best suited to a specific business scenario. I want it to first gather customer insights and then generate sales strategy ideas based on those insights.”

[0868] By implementing the system of the present invention in the above manner, it is possible to realize dynamic recommendation display based on the user's emotional state, efficient transaction procedures, and fair revenue distribution, providing an environment in which companies and individuals can smoothly utilize generative AI models.

[0869] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0870] Step 1:

[0871] Users open a dedicated registration screen on their device to register the prompts and generative AI models they have created on the platform.

[0872] Input: Prompt name, detailed description, usage example, pricing

[0873] Specific operations: Display the registration screen on the device, enter the required information, and then click the send button.

[0874] Output: Prompts and generated AI model data are sent from the device to the server.

[0875] Step 2:

[0876] The server receives user-submitted prompts and generated AI model data.

[0877] Input: Data submitted by the user

[0878] Specific operation: The server receives the data and automatically verifies that the format and required fields are entered correctly.

[0879] Output: Verification results for format and required items. Data that has been verified is stored in a database.

[0880] Step 3:

[0881] The server collects emotion data from user input and operations.

[0882] Input: User keyboard input, mouse operation, facial expression recognition, voice analysis

[0883] How it works: Emotion data is collected in real time using an emotion engine, specifically software that analyzes data captured from cameras and microphones.

[0884] Output: Collected emotion data

[0885] Step 4:

[0886] The server analyzes the collected emotional data to determine the user's emotional state.

[0887] Input: Emotion data

[0888] Specific operation: The emotion engine is used to analyze emotion data and determine emotional states such as stress, excitement, and calmness.

[0889] Output: User's emotional state

[0890] Step 5:

[0891] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable form and prepares it for display on a web page.

[0892] Input: Metadata stored in a database

[0893] Specific operation: The server converts the metadata based on a search algorithm and generates a search index.

[0894] Output: Data for display in search indexes and web pages

[0895] Step 6:

[0896] The server uses the converted metadata to publish the prompts and generative AI models on an online platform.

[0897] Input: Search index and web page display data

[0898] Specific operation: The server displays the data on a web page, allowing users to freely browse and search it.

[0899] Output: prompts and generative AI models published to an online platform

[0900] Step 7:

[0901] The server recommends the most appropriate generative AI model and prompts to the user based on their emotional state.

[0902] Input: User emotional state, published prompts, and generative AI model data

[0903] Specific operation: The server applies a recommendation algorithm that reflects the emotional state and displays a generative AI model and prompts appropriate for the user.

[0904] Output: Recommended generative AI models and prompts

[0905] Step 8:

[0906] Users choose what they need from the published prompts and generative AI models and click the "Purchase" button.

[0907] Input: Data selected from a list of published prompts and generative AI models

[0908] Specific operation: The user clicks the purchase button and a purchase request is sent to the server.

[0909] Output: Purchase request

[0910] Step 9:

[0911] The server receives the purchase request from the user and checks the contents of the request.

[0912] Input: Purchase Request

[0913] Specific operation: The server confirms the purchase request and provides the user with a screen for entering payment information.

[0914] Output: Payment information input screen

[0915] Step 10:

[0916] The server receives the user's payment information and receives payment through the payment system.

[0917] Input: User's payment information

[0918] What it does: Processes payments using payment systems (e.g., PayPal, credit card systems).

[0919] Output: Payment completion notification

[0920] Step 11:

[0921] The server provides the user with the generated AI model and prompt data that have been purchased.

[0922] Input: Payment completion information, purchase data

[0923] Specific operation: The server generates a download link and API key and sends them to the user.

[0924] Output: Data provided to the user

[0925] Step 12:

[0926] Users can customize the generative AI models and prompts they purchase to suit their needs and then register the customized versions back on the platform.

[0927] Input: Purchased generative AI models, prompts, and customizations

[0928] Specific operation: The user makes customizations and uses the re-registration screen to send the customized version to the server.

[0929] Output: Customized prompts and generative AI models

[0930] Step 13:

[0931] The server receives the registered data again, verifies the format and necessary items, stores it in the database, and makes it public again.

[0932] Input: Re-registration data

[0933] Specific operation: The server receives the data, verifies the format and required items, stores it in the database, and then makes it available online again.

[0934] Output: Republished customized prompts and generative AI models

[0935] (Application example 2)

[0936] 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."

[0937] In modern digital marketplaces, there are efficient systems for aggregating, publishing, and purchasing generative AI models and prompts. However, there is a lack of a means for optimally displaying generative AI model recommendations that take into account the user's emotional state. Furthermore, without dynamic recommendations that reflect the user's emotions during the purchasing process, the user experience may be limited. Furthermore, there is a need for appropriate and fair revenue distribution.

[0938] 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, in a platform that aggregates generative AI models, means for storing registered prompts and generative AI models in a database, means for publishing the aggregated prompts and generative AI models online, means for receiving purchase requests from users and receiving payment through a payment system, means for providing the user with the generative AI model or prompt after the purchase is completed, means for sharing the revenue from the purchase price between the prompt creator and the platform operator, means for using an emotion analysis engine to collect emotional data from user inputs and operations, and means for recommending and displaying the generative AI model or prompt that is optimal for the user based on the emotional data. This makes it possible to analyze the user's emotional state and recommend the optimal generative AI model or prompt, improving the user experience and realizing efficient transactions.

[0939] A "generative AI model" is an algorithm or program that uses artificial intelligence to perform specific tasks such as natural language generation or image generation.

[0940] A "prompt" is data such as text or images that is input to a generative AI model to guide the generated output.

[0941] The "database" is an information management system for organizing and storing registered prompts and generative AI models.

[0942] The "Platform" is an online system for aggregating, publishing, and purchasing generative AI models and prompts.

[0943] A "payment system" is a financial transaction system for safely and efficiently processing purchase payments from users.

[0944] An "emotion analysis engine" is a technology or algorithm that analyzes a user's emotional state based on data obtained from the user's input and operations.

[0945] "Recommendation display" refers to proposing and displaying the optimal generative AI model and prompts to the user based on emotional data analyzed by the emotion analysis engine.

[0946] "Revenue sharing" means the process of calculating and transferring the purchase price to be appropriately divided between the prompt creator and the platform operator.

[0947] "Customization" refers to the act of modifying and adjusting the generative AI model or prompts purchased by a user to suit their own needs.

[0948] "Online publishing means" refers to methods or technologies that allow registered prompts and generative AI models to be viewed and purchased by users on the Internet.

[0949] The present invention relates to a system that combines a sentiment analysis engine with a platform for aggregating, selling, and delivering generative AI models and prompts, implemented using the following means:

[0950] First, the user registers the generative AI model or prompt on the platform. To do this, they open a dedicated registration screen, enter the required information such as the prompt's name, detailed description, use case, and pricing, and click the "Submit" button. The server receives the submitted data and verifies that the format and required fields have been entered correctly, and once verified, the data is stored in the database.

[0951] Next, an emotion analysis engine is used to collect emotional data from user input and operations. Emotional data is collected through the user's keyboard input, mouse operation, facial expression recognition, voice analysis, etc. The server analyzes the collected emotional data and determines the user's emotional state.

[0952] For example, if a user enters "I've been feeling stressed at work lately," the server will use its emotion analysis engine to determine the user's emotion as "stress." Based on this emotion data, the server will recommend the optimal generative AI model and prompts for the user. In this example, the server will recommend a "generative AI model that helps you relax."

[0953] Once the recommended generative AI models and prompts are made public, users can freely browse and search them. The user selects the prompt or generative AI model they need and clicks the "Purchase" button. The server receives the purchase request, checks its contents, and then provides the user with a screen for entering payment information. After the payment information is entered, the server receives payment through the payment system. Once the payment is complete, the server sends the user a notification that the purchase is complete.

[0954] The server then provides the user with the data for the generative AI model or prompt that has been purchased. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data. Users can also customize the generative AI model or prompt they purchased to suit their own needs and re-register the customized version on the platform. The server receives the re-registered data, verifies its format and required items, stores it in the database, and publishes it again.

[0955] Furthermore, a revenue sharing system will calculate a revenue share based on the purchase price, which will be divided appropriately between the prompt creator and the platform operator and transferred to the prompt creator's registered bank account or electronic wallet.

[0956] As described above, this system analyzes the user's emotional state to recommend the optimal generative AI model and prompts, enabling efficient and satisfying transactions, while ensuring fair and appropriate revenue distribution.

[0957] For example, if a user inputs "I've been feeling stressed at work lately," the server will perform emotion analysis and recommend a "generative AI model that will help you relax." In this way, the user experience can be improved by providing the optimal prompts and generative AI models according to the user's emotional state.

[0958] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0959] Step 1:

[0960] Users register generated AI models and prompts on the platform.

[0961] Input: The user enters information such as the name, description, use case, and pricing of the generated AI model or prompt.

[0962] Data processing: The user enters the necessary information on a dedicated registration screen and clicks the "Submit" button.

[0963] Output: Generated AI model and prompt data are sent to the server.

[0964] Step 2:

[0965] The server receives the data and verifies that the format and required fields are correct.

[0966] Input: The generative AI model and prompt data sent in Step 1.

[0967] Data processing: Automated scripts are run to check for missing or incorrect data.

[0968] Output: Data that has been validated. If there are no problems with the format or required items, proceed to the next step.

[0969] Step 3:

[0970] The server stores the validated data in the database.

[0971] Input: Data for the generative AI model and prompts that have been validated in Step 2.

[0972] Data manipulation: Inserting data into the appropriate tables in the database.

[0973] Output: Generative AI models and prompts stored in a database.

[0974] Step 4:

[0975] Use a sentiment analysis engine to collect emotional data from user input and actions.

[0976] Input: Data such as user keyboard input, mouse actions, facial expression recognition, and voice analysis.

[0977] Data calculation: The sentiment analysis engine analyzes these data in real time to determine the user's emotional state.

[0978] Output: Determined user emotion data.

[0979] Step 5:

[0980] Based on the emotional data, the server recommends the most suitable generative AI model and prompts for the user.

[0981] Input: User emotion data determined in step 4.

[0982] Data computation: Search and filter relevant generative AI models and prompts based on emotion data.

[0983] Output: The generated AI model and prompts that are displayed to the user.

[0984] Step 6:

[0985] The user selects a recommended generative AI model or prompt and clicks the "Purchase" button.

[0986] Input: User selection and payment information.

[0987] Data processing: Send a purchase request to the server and enter payment information on the payment screen.

[0988] Output: Purchase request and payment information is sent to the server.

[0989] Step 7:

[0990] The server receives the purchase request and verifies its contents.

[0991] Input: Purchase request and payment information submitted in step 6.

[0992] Data processing: Receive payment through the payment system.

[0993] Output: A notification of payment completion is sent to the user.

[0994] Step 8:

[0995] Provide users with generative AI models and prompts upon purchase completion.

[0996] Input: Data from the generative AI model or prompt that you purchased.

[0997] Data processing: Generate and provide download links and API keys to users.

[0998] Output: A link or key that allows users to access the generated AI model and prompts.

[0999] Step 9:

[1000] Customize the generative AI models and prompts you purchase to fit your needs.

[1001] Input: Data from purchased generative AI models and prompts.

[1002] Data calculation: User adjusts programs and parameters.

[1003] Output: Customized generative AI models and prompts.

[1004] Step 10:

[1005] The user re-registers the customization.

[1006] Input: Data for customized generative AI models and prompts.

[1007] Data processing: Send data from the re-registration screen.

[1008] Output: Data re-registered on the server.

[1009] Step 11:

[1010] The server receives the re-registered data and re-verifies its format and required items.

[1011] Input: The generative AI model and prompt data retrained in step 10.

[1012] Data calculation: Re-verification of data format and required items.

[1013] Output: The validated data.

[1014] Step 12:

[1015] The server stores the verified data in the database and makes it public again.

[1016] Input: The data that has passed validation in step 11.

[1017] Data processing: Re-insert the data into the appropriate tables in the database and set it to public.

[1018] Output: The published customization stored in the database.

[1019] Step 13:

[1020] The revenue sharing system calculates and distributes the revenue share amount based on the purchase price.

[1021] Input: User purchase data and revenue sharing rules.

[1022] Data calculation: Calculation of revenue share.

[1023] Output: Revenue share remittance to prompt creators and platform operators.

[1024] 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.

[1025] 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.

[1026] 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.

[1027] [Third embodiment]

[1028] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1029] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1030] 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).

[1031] 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.

[1032] 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.

[1033] 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).

[1034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1035] 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.

[1036] 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.

[1037] 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.

[1038] 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.

[1039] 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."

[1040] The present invention relates to a platform that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and sells or provides them. The system of the present invention is embodied in the following form.

[1041] 1. Aggregation of prompt and generative AI models

[1042] Registering prompt and generative AI models

[1043] Users register their own prompts and generative AI models on the platform by entering information such as the prompt name, detailed description, use case, and pricing on the registration screen and clicking the "Submit" button.

[1044] Data Receipt and Validation

[1045] The server receives the prompts sent by the user and the data from the generative AI model. The received data is verified to ensure that the format and required fields are entered correctly. Once verified, the data is stored in a database.

[1046] 2. Publishing generative AI models and prompts

[1047] Preparation for release

[1048] The server converts the metadata of the prompts and generative AI models registered in the database into a searchable format and prepares it for display on a web page.

[1049] public

[1050] The server publishes the ready-to-publish prompts and generative AI models on an online platform, where they can be browsed and searched by users.

[1051] 3. Purchase procedure

[1052] Selecting a prompt

[1053] Users choose what they need from the published prompts and generative AI models and click the "Purchase" button.

[1054] Receiving a purchase request

[1055] The server receives the user's purchase request and checks its contents.

[1056] Enter your payment information

[1057] The user follows the server's instructions and enters payment information (credit card information, electronic payment service information, etc.).

[1058] Payment Processing

[1059] The server receives the user's purchase payment through the payment system, and once payment is complete, sends the user a purchase completion notification.

[1060] Providing generative AI models and prompts

[1061] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by sending the user a download link and API key.

[1062] 4. Revenue Sharing

[1063] Calculating revenue

[1064] The server calculates the revenue share based on the purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[1065] Revenue sharing execution

[1066] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[1067] 5. Customization and Re-provision

[1068] Customizing prompts and generative AI models

[1069] Users can download the generative AI models and prompts they purchase and customize them to suit their needs.

[1070] Re-registering a customized version

[1071] The user can then re-register the customized generative AI model and prompts on the platform by entering the necessary information on the prompt registration screen again and submitting it.

[1072] Re-registration process

[1073] The server verifies the data format and required items of the re-registered customized prompts and generative AI models, stores them in the database, and then prepares them for publication and publishes them again.

[1074] Specific examples

[1075] For example, a user can create a new natural language generation prompt and register it on the platform. The prompt is then published, and other users can purchase it. After completing the purchase, the user can customize the prompt and register it again on the platform. In this way, new prompts and generative AI models are constantly being aggregated, published, and revenues are shared.

[1076] The system of the present invention is implemented in the above manner, providing centralized information management, efficient transactions, and fair revenue distribution, thereby realizing an environment in which companies and individuals can smoothly utilize generative AI models.

[1077] The processing flow will be explained below.

[1078] Step 1:

[1079] Users open a dedicated registration screen to register their own prompts and generative AI models on the platform. On the registration screen, they enter the required information, such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[1080] Step 2:

[1081] The server receives the prompts sent by the user and the data from the generative AI model. It verifies that the received data is correctly formatted and that all required fields are entered. If the data is determined to be correct, it stores the data in a database.

[1082] Step 3:

[1083] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format, preparing them for efficient search and browsing by users through the platform.

[1084] Step 4:

[1085] The server uses the converted metadata to publish the prompts and generative AI models on a webpage, where users can freely browse and search them.

[1086] Step 5:

[1087] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[1088] Step 6:

[1089] The server receives the user's purchase request, verifies its contents, and then provides the user with a screen for entering payment information.

[1090] Step 7:

[1091] The user follows the instructions of the server and enters payment information such as credit card information and electronic payment service information, then clicks the "Submit" button to complete the payment.

[1092] Step 8:

[1093] The server receives payment from the user through the payment system. Once payment is complete, the server sends a notification to the user that the purchase has been completed.

[1094] Step 9:

[1095] The server provides the user with the prompts and generated AI model data for which the purchase has been completed, and the user is sent a download link and API key, allowing them to immediately use the purchased data.

[1096] Step 10:

[1097] The server calculates the revenue share based on the user's purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[1098] Step 11:

[1099] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[1100] Step 12:

[1101] Users can customize the purchased prompts and generative AI models to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[1102] Step 13:

[1103] The server receives the customized prompts and generated AI model data registered by the user, verifies their format and required items, and stores the verified data in a database.

[1104] Step 14:

[1105] The server then converts the metadata of the customized prompts and generative AI models stored in the database into a searchable format and republishes them on the webpage, allowing new prompts and generative AI models to be constantly updated and made public.

[1106] Example 1

[1107] 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."

[1108] Today, businesses and individuals lack a platform for effectively managing and trading generative AI models and prompts. Therefore, there is a need for a system that allows users to easily register, sell, and reuse their generated prompts and AI models. Furthermore, the purchasing procedures and revenue distribution processes are complex, and an efficient and fair method is needed.

[1109] 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.

[1110] In this invention, the server includes means for a user to input prompts and generative AI models and send the contents to the server, means for the server to receive the data sent from the user and verify the format and necessary items, means for storing the verified data in a database and notifying the user, means for converting the stored data into a searchable format and publishing it on an online platform, means for receiving purchase requests from users and receiving payment through a payment system, means for providing generative AI models and prompts after purchase is completed, and means for sharing revenue from the purchase price. This allows users to efficiently register, publish, sell, and reuse prompts and generative AI models, and enables fair and smooth revenue sharing.

[1111] "User" means an individual or entity that uses the Platform to register, purchase, and customize prompts and generative AI models.

[1112] A "prompt" is text data or instructions input into a generative AI model that determines the output content generated.

[1113] A "generative AI model" is an artificial intelligence model that performs natural language processing or generative tasks, including algorithms for generating output in response to prompts.

[1114] "Server" is a central control device that manages the entire system and performs various processes such as receiving, verifying, storing, publishing, payment processing, and revenue distribution of data.

[1115] "Database" means a storage system for centrally managing and storing data, including prompts and generative AI models.

[1116] "Payment system" means a system for processing payments for user purchases, including credit cards and electronic payment services.

[1117] "Revenue sharing" is a system in which revenue earned when users sell prompts or generative AI models is divided fairly between prompt creators and platform operators.

[1118] "Customization" refers to the process by which users edit and modify the generative AI models and prompts they purchase to adapt them to their own specific needs.

[1119] "Online Platform" means a web-based system that enables users to register, publish, sell, buy, and customize prompt and generative AI models.

[1120] "Re-registration" refers to the act of a user customizing the prompts and generative AI models that were initially registered and then registering them again on the platform.

[1121] The present invention relates to a platform for aggregating prompts and generative AI models created by companies and individuals using generative AI models, and for selling and providing them. This platform is composed of components such as a server, terminals, databases, online interfaces, and payment systems.

[1122] Process Overview

[1123] 1. Registering a prompt and generate AI model

[1124] The user uses a device to access the platform's registration screen, enters the prompts and details of the generated AI model (such as name, detailed description, use case, pricing, etc.), and clicks the "Submit" button.

[1125] The server receives the data sent by the user and verifies whether the data format and required items have been entered correctly. Once the verification is complete, the data is stored in a database.

[1126] 2. Publishing generative AI models and prompts

[1127] The server converts the metadata of the prompts and generative AI models registered in the database into a searchable format and generates a user interface, allowing users to browse and search the published prompts and generative AI models on an online platform.

[1128] 3. Purchase procedure

[1129] Users select a published prompt or generative AI model, click the "Purchase" button, and enter their payment information.

[1130] The server receives the purchase request and payment information from the user, receives the payment through the payment system, and sends a notification of purchase completion to the user once the payment is complete.

[1131] 4. Providing generative AI models and prompts

[1132] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by emailing the user a download link and API key.

[1133] 5. Revenue Sharing

[1134] The server calculates the revenue share based on the purchase price, distributes the revenue according to the distribution ratio between the prompt creator and the platform operator, and transfers the revenue share to the prompt creator's bank account or electronic wallet.

[1135] 6. Customization and Re-provision

[1136] Users can customize the generative AI models and prompts they purchase to suit their own needs.

[1137] Users can then re-register their customized generative AI models and prompts on the platform, where the re-registered data will be verified by the server again, stored in the database, and published again on the online platform once it is ready to be published.

[1138] Specific examples

[1139] For example, suppose a user creates a new natural language generation prompt and registers it on the platform. The prompt is then published and other users can purchase it. Here is an example of a prompt:

[1140] "Example Natural Language Generation Prompt: Generate a conversation about a topic of interest to a college student."

[1141] After completing the purchase, the user can customize the prompt and register again on the platform, thus constantly collecting and publishing new prompts and generative AI models, and sharing revenues.

[1142] The system of the present invention provides centralized information management, efficient transactions, and fair revenue distribution, creating an environment in which companies and individuals can smoothly utilize generative AI models.

[1143] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1144] Step 1: User Data Entry

[1145] Users use their device to access the platform's registration screen and enter prompts and details about the generated AI model (such as name, detailed description, use cases, and pricing).

[1146] Input: Prompt and details about the generated AI model.

[1147] Output: Input data temporarily stored on the device.

[1148] Specific behavior: The user enters data into the input field and clicks the "Submit" button. The device temporarily stores the entered data.

[1149] Step 2: Sending data

[1150] The terminal transmits the saved input data to the server.

[1151] Input: User input data.

[1152] Output: The data sent to the server.

[1153] Specific operation: The device generates an HTTP request and sends the input data to the server.

[1154] Step 3: Receiving and verifying data

[1155] The server receives the data sent by the user and verifies whether the format and required items have been entered correctly.

[1156] Input: The user's data received by the server.

[1157] Output: Validation results and data to be stored in the database.

[1158] Specific behavior: The server checks the format and required fields of the received data, and generates an error message if there is invalid data.

[1159] Step 4: Store the data

[1160] The server stores the verified data in a database.

[1161] Input: The user's data after validation.

[1162] Output: Data stored in the database and notification to the user.

[1163] What happens: The server generates the SQL commands to insert the data into the database, then notifies the user that the registration is complete.

[1164] Step 5: Convert metadata and prepare for publishing

[1165] The server converts the metadata registered in the database into a searchable format and generates a user interface.

[1166] Input: Metadata stored in a database.

[1167] Output: A search index and a user interface.

[1168] What it does: The server indexes the metadata and dynamically generates the web page.

[1169] Step 6: Publish online

[1170] The server publishes the ready generative AI models and prompts on an online platform.

[1171] Input: Prepared prompts and metadata for the generative AI model.

[1172] Output: The published prompt and / or generative AI model.

[1173] What happens: The server updates the web page to display the published prompt and generative AI model.

[1174] Step 7: User selects prompt

[1175] Users can browse published prompts and generative AI models on the platform and click the "Purchase" button for the one they need.

[1176] Input: A list of published prompts and generative AI models.

[1177] Output: Selected prompts and generative AI models.

[1178] What happens: The user navigates through the web interface, selects the item they want to purchase, and clicks the "Buy" button.

[1179] Step 8: Receiving a Purchase Request

[1180] The server receives the user's purchase request and payment information and verifies the contents.

[1181] Input: User purchase request and payment information.

[1182] Output: Confirmed request and payment information.

[1183] Specific operation: The server generates a token for payment information and sends it to the payment system.

[1184] Step 9: Payment Processing

[1185] The server receives payment through the payment system, and once payment is complete, sends a notification to the user that the purchase is complete.

[1186] Input: Payment information.

[1187] Output: Payment completion notification.

[1188] Specific operation: The server calls the payment system API and notifies the user when the payment is successful.

[1189] Step 10: Providing generative AI models and prompts

[1190] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by emailing the user a download link and API key.

[1191] Input: Purchase completion data.

[1192] Output: Download link and API key.

[1193] What happens: The server uses an email service to send the user an email containing the necessary download link and API key.

[1194] Step 11: Calculate Revenue Share

[1195] The server calculates the revenue share amount based on the purchase price and distributes the revenue according to the distribution ratio between the prompt creator and the platform operator.

[1196] Input: Purchase price data and distribution percentage.

[1197] Output: Calculated distribution amount.

[1198] Specific operation: The server executes the calculation algorithm and calculates the distribution amount.

[1199] Step 12: Implementing Revenue Sharing

[1200] The server transfers the calculated revenue share amount to the prompt creator's registered bank account or electronic wallet.

[1201] Input: Calculated distribution amount.

[1202] Output: Remittance completion notification.

[1203] Specific operation: The server calls the API of the bank or electronic wallet to transfer the distribution amount, and then sends a notification of the completion of the transfer to the creator.

[1204] Step 13: Customizing prompts and generative AI models

[1205] Users can download the generative AI models and prompts they purchase and customize them to suit their needs.

[1206] Input: Downloaded generative AI model and prompts.

[1207] Output: Customized generative AI models and prompts.

[1208] Specific operation: The user edits and modifies the generated AI model and prompts in the local environment.

[1209] Step 14: Re-register your customizations

[1210] Users can re-register their customized generative AI models and prompts to the platform by entering the necessary information on the prompt registration screen again and clicking the "Submit" button.

[1211] Input: Customized generative AI models and prompts.

[1212] Output: Re-enrollment data sent to the platform.

[1213] Specific behavior: The user enters the required information on the re-registration screen and the customized data is sent to the server.

[1214] Step 15: Receiving and verifying re-enrollment data

[1215] The server receives the registered prompt and generated AI model data again and verifies that the format and required fields have been entered correctly.

[1216] Input: Re-registered data.

[1217] Output: Validation results and data to be stored in the database.

[1218] Specific operation: The server verifies the data format and required items, just as it did during initial registration.

[1219] Step 16: Store and republish resubmission data

[1220] The server stores the re-registered data in a database and makes it available again on the online platform.

[1221] Input: Your verified re-enrollment data.

[1222] Output: Published re-registration data.

[1223] Specific operation: The server stores the data after validation in a database and makes it public once it is ready.

[1224] (Application example 1)

[1225] 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."

[1226] Platforms that utilize generative AI models are required to provide an environment where users can smoothly and efficiently complete the entire process of registering, searching, purchasing, and customizing prompts and generative AI models. A system is also required that allows users to easily customize and re-register purchased prompts. Conventional systems make these processes cumbersome, and one issue is that they do not adequately support operation on smart devices.

[1227] 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.

[1228] In this invention, the server includes a platform that aggregates generative AI models, a means for storing registered prompts and generative AI models in a database, a means for publishing the aggregated prompts and generative AI models online, and a means for receiving purchase requests from users and receiving payment through a payment system. This allows users to intuitively perform a series of operations using their smartphones to register, search, purchase, and customize prompts and generative AI models. Furthermore, the ease of performing a series of operations to register and publish user-customized prompts on the platform further expands the scope of use of generative AI models.

[1229] A "generative AI model" is a model that automatically generates content and data using artificial intelligence algorithms.

[1230] A "prompt" is an instruction or command that is input to a generative AI model, and is a phrase that specifies the type and content of the content to be generated.

[1231] "Platform" means an online system for aggregating, registering, publishing, purchasing, customizing, and re-registering generative AI models and prompts.

[1232] "Database" means a data storage system for storing and managing registered generative AI models and prompts.

[1233] "Means for online publication" refers to a method for publishing the generative AI model and prompt information stored in the database in a form accessible via the Internet.

[1234] The "means for receiving purchase requests" refers to the mechanism by which requests are received when a user applies to purchase a generative AI model or prompt through the platform.

[1235] "Payment System" means a system for processing and completing payments required when a user purchases a generative AI model or prompt.

[1236] "Customization" refers to the act of modifying the content of generative AI models or prompts purchased or acquired by a user to suit their own needs.

[1237] "Means for re-registration" refers to a method by which a user can re-register their customized generative AI model or prompts on the platform.

[1238] A "smartphone" is a portable information terminal that has Internet connectivity and can be used by installing various applications.

[1239] The present invention relates to a platform that utilizes generative AI models to aggregate and sell or provide prompts and generative AI models created by companies and individuals. The following describes in detail an embodiment of the present invention.

[1240] Hardware and Software

[1241] The system of this invention includes a server, a smartphone, a database, and a payment system. The server hosts an online platform and runs a web application using Flask. The database uses SQLite, and the payment system uses Stripe.

[1242] System Operation

[1243] Registration Process

[1244] Users register the prompts and generative AI models they have created using their smartphones. The information entered by the user, such as the prompt name, detailed description, use case, and pricing, is sent to the server. The server verifies the format and required items of the received data, and stores the verified data in an SQLite database. Once verification is complete, a notification of registration completion is sent to the user.

[1245] Publishing Process

[1246] The server converts the prompts and generative AI model information stored in the database into a searchable format, making these prompts available for other users to search and view on the online platform.

[1247] Purchase Process

[1248] The user selects what they need from prompts and generative AI models published on the online platform and submits a purchase request. The server receives this request and receives the user's purchase payment through a payment system (Stripe). Once the purchase is complete, the server sends the user a download link and API key and notifies them of the purchase completion.

[1249] Customization and Re-registration Process

[1250] Users can customize the generative AI models and prompts they have purchased on their smartphones. After customization, they send a request to the server to re-register them on the platform. The server again verifies the format and required items of the received data and re-registers them in the database. Once re-registration is complete, the customized generative AI models and prompts are made public again.

[1251] Specific examples

[1252] For example, consider a scenario where a user registers an "automated script generation prompt," which is then purchased by other users and used to generate movie scripts. The purchasing user can generate a script based on the prompt and customize it to suit their needs. The customized prompt can then be registered back on the platform and made available to other users.

[1253] Example prompt sentence:

[1254] "Automatic script generation prompt: This AI prompt is used to generate a movie script. Input the specified theme and character settings and it will automatically generate everything from the plot to the dialogue."

[1255] In this way, the present invention provides a comprehensive platform for efficiently aggregating, publishing, and trading generative AI models and prompts.

[1256] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1257] Step 1:

[1258] The server receives input from the user's smartphone when registering a prompt or generative AI model. The input includes information such as the prompt's name, detailed description, use case, and pricing. The server verifies that the format and required fields of this data are correct, and stores the verified data in an SQLite database. Once registration is complete, the server sends a notification to the user that registration is complete.

[1259] Step 2:

[1260] The server converts the information about the prompts and generative AI models stored in the database into a searchable format. Specifically, it extracts the metadata of the prompts and generative AI models, indexes them, and prepares them for display on a web page, allowing other users to search and view these prompts on an online platform from their smartphones.

[1261] Step 3:

[1262] The user selects the prompt or generative AI model they need from those published on the online platform and sends a purchase request to the server. The server receives this request and retrieves the price information of the corresponding prompt from a database. The server then charges the user for the purchase price through the payment system (Stripe) and completes the payment process. Once payment is complete, a download link and API key are generated and sent to the user, along with a notification that the purchase is complete.

[1263] Step 4:

[1264] Users customize the generative AI model and prompts they purchased on their smartphones. For example, they can change the prompt text or settings. The customized prompts are then sent to the server via a registration request. The server again verifies the format and required fields of the received data and stores it in the database. Once re-registration is complete, the customized prompts and generative AI models are made public again.

[1265] Step 5:

[1266] The server calculates the revenue share between the prompt creator and the platform operator based on the published prompts and the viewing and purchase history of the generating AI model. After calculating the revenue, the server transfers the revenue to the prompt creator's registered bank account or electronic wallet and notifies the prompt creator that the revenue share is complete.

[1267] 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.

[1268] The present invention relates to a system that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and combines an emotion engine with a platform for selling and providing these. The system of the present invention can be implemented in the following forms.

[1269] 1. Aggregation of prompt and generative AI models

[1270] Registering prompt and generative AI models

[1271] Users open a dedicated registration screen to register their created prompts and generative AI models on the platform, enter the required information such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[1272] Data Receipt and Validation

[1273] The server receives the prompts sent by the user and the generated AI model data, verifies that the format and required fields are correct, and stores the verified data in a database.

[1274] 2. Introducing the Emotion Engine

[1275] Collecting Emotional Data

[1276] The server is equipped with an emotion engine for collecting emotion data from inputs and operations of users accessing the platform, such as through keyboard input, mouse operation, facial expression recognition, and voice analysis.

[1277] Sentiment Data Analysis

[1278] The server analyzes the collected emotion data with an emotion engine to determine the user's emotional state, for example, whether the user is stressed, excited, or calm.

[1279] 3. Publishing the generative AI model and prompts and displaying recommendations

[1280] Preparation for release

[1281] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable form and prepares it for display on a web page.

[1282] public

[1283] The server uses the converted metadata to publish the prompts and generative AI models on an online platform, where users can freely browse and search them.

[1284] Recommendation display

[1285] The server then recommends the most appropriate generative AI model and prompts for the user based on the emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[1286] 4. Purchase procedure

[1287] Selecting a prompt

[1288] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[1289] Receiving and settling purchase requests

[1290] The server receives the user's purchase request, checks its contents, provides the user with a screen for entering payment information, and receives payment through the payment system after the payment information is entered. Once payment is complete, the server sends a notification of purchase completion to the user.

[1291] Providing generative AI models and prompts

[1292] The server provides the user with the prompts and generated AI model data for which the purchase has been completed. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data.

[1293] 5. Revenue Sharing

[1294] Calculating revenue

[1295] The server calculates the revenue share based on the purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[1296] Revenue sharing execution

[1297] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[1298] 6. Customization and Re-provision

[1299] Customizing prompts and generative AI models

[1300] Users can customize the generative AI models and prompts they purchase to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[1301] Re-registration process

[1302] The server receives the customized prompts and generated AI model data that the user has re-registered, verifies their format and required items, stores them in the database, and makes them public again.

[1303] Specific examples

[1304] For example, suppose a user creates a new natural language generation prompt and registers it on the platform. The prompt is then made public, and other users purchase it. After completing the purchase, the user customizes the prompt and registers it again on the platform. Furthermore, the emotion engine analyzes the user's emotional state, and based on the results, recommends the most suitable generation AI model and prompt for the user. This allows users to make efficient and satisfying selections.

[1305] The system of the present invention is implemented in the above manner, providing centralized information management, efficient transactions, fair revenue distribution, and dynamic recommendation display based on the user's emotional state, thereby realizing an environment in which companies and individuals can smoothly utilize generative AI models.

[1306] The processing flow will be explained below.

[1307] Step 1:

[1308] To register their own prompts and generative AI models on the platform, users open a dedicated registration screen, enter information such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[1309] Step 2:

[1310] The server receives the prompts sent by the user and the generated AI model data. It verifies that the data format and required fields have been entered correctly. Once the verification is complete, the data is stored in a database.

[1311] Step 3:

[1312] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format, preparing them for efficient search and browsing by users through the platform.

[1313] Step 4:

[1314] The server uses the converted metadata to publish the prompts and generative AI models on a webpage, where users can freely browse and search them.

[1315] Step 5:

[1316] The server runs an emotion engine that collects emotional data from the input and operations of users accessing the platform, including through keyboard input, mouse operation, facial expression recognition, and voice analysis.

[1317] Step 6:

[1318] The server uses an emotion engine to analyze the collected emotion data and determine the user's emotional state, for example, whether the user is stressed, excited, or calm.

[1319] Step 7:

[1320] The server then recommends the optimal generative AI model and prompts to the user based on the emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[1321] Step 8:

[1322] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[1323] Step 9:

[1324] The server receives the user's purchase request, verifies its contents, and then provides the user with a screen for entering payment information.

[1325] Step 10:

[1326] The user follows the server's instructions and enters payment information (credit card information, electronic payment service information, etc.). After entering the information, the user clicks the "Submit" button to complete the payment.

[1327] Step 11:

[1328] The server receives the user's purchase payment through the payment system. Once payment is complete, the server sends a purchase completion notification to the user.

[1329] Step 12:

[1330] The server provides the user with the prompts and generated AI model data for which the purchase has been completed. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data.

[1331] Step 13:

[1332] The server calculates the revenue share based on the user's purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[1333] Step 14:

[1334] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[1335] Step 15:

[1336] Users can customize the purchased prompts and generative AI models to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[1337] Step 16:

[1338] The server receives the customized prompts and generated AI model data registered by the user, verifies their format and required items, and stores the verified data in a database.

[1339] Step 17:

[1340] The server then converts the metadata of the customized prompts and generative AI models stored in the database into a searchable format and republishes them on the webpage, allowing new prompts and generative AI models to be constantly updated and made public.

[1341] Example 2

[1342] 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."

[1343] Current platforms that aggregate and provide generative AI models and prompts provide generic prompts and models without considering the user's emotional state, which means they are unable to provide optimal suggestions based on the user's needs and emotional state. Another problem is that the procedures for registering, purchasing, and customizing prompts and generative AI models are complicated, making it difficult to achieve efficient transactions.

[1344] The identification process 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 platform that aggregates prompts and generative AI models, a means for storing registered prompts and generative AI models in a database, a means for publishing the aggregated prompts and generative AI models online, a means for receiving a purchase request from a user and receiving payment through a payment system, a means for providing the user with a generative AI model or prompt after the purchase is completed, a means for having an emotion engine that collects emotional data from the user's input and operation, a means for analyzing the collected emotional data and determining the user's emotional state, and a means for recommending and displaying the generative AI model or prompt that is optimal for the user based on the emotional state. This makes it possible to recommend the optimal generative AI model or prompt according to the user's emotional state, thereby achieving an efficient and satisfying selection.

[1345] A "prompt" is input data that allows a user to give instructions or questions to a generative AI model.

[1346] A "generative AI model" is an algorithm that uses artificial intelligence to generate a response or output for a specific purpose.

[1347] A "database" is an information system for efficiently storing and managing large amounts of data.

[1348] An "emotion engine" is a system that collects emotional data from user input and operations, analyzes it, and determines the user's emotional state.

[1349] "Metadata" is data that describes information related to prompts and generative AI models, making them easier to search and organize within the database.

[1350] A "payment system" is a system for processing payments in online transactions.

[1351] "Revenue sharing" is the process of dividing revenue among the parties involved (prompt creators and platform operators).

[1352] "Customization" refers to the act of a user adjusting and modifying prompts and generative AI models to meet their specific needs.

[1353] The present invention relates to a system that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and combines an emotion engine with a platform for selling and providing them. This system is implemented as follows.

[1354] This system is primarily composed of a user, a terminal, and a server. The user uses the terminal to register the prompts and generative AI models they have created on the platform. The terminal provides an interface for entering information such as the prompt's name, detailed description, use case, and pricing using a registration screen. When the user clicks the "Submit" button, the terminal sends this data to the server.

[1355] The server receives the prompts and generated AI model data sent by the user and automatically verifies that the format and required fields are entered correctly. Once verified, the data is stored in a database. Specifically, the server uses a management system such as an SQL database to properly store and manage the data.

[1356] Furthermore, the server is equipped with an emotion engine that collects emotion data from user input and operations. Emotion data is collected through user keyboard input, mouse operation, facial expression recognition, and voice analysis. For example, software is used that uses a camera and microphone to analyze the user's facial expressions and voice. This is expected to use "Face API" for facial expression recognition and "Google Cloud Speech-to-Text API" for voice analysis.

[1357] The collected emotional data is analyzed by an emotion engine in the server to determine the user's emotional state. Emotional states include stress, excitement, and calmness. The analysis results are used to display recommendations to the user. For example, if the server determines that the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[1358] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format and prepares it for display on a web page, allowing users to freely browse and search the prompts and generative AI models on the online platform.

[1359] When a user selects a prompt or generative AI model and clicks the "Purchase" button, the purchase request is sent to the server, which receives payment through a payment system and notifies the user that the purchase is complete. This payment system uses online payment services such as PayPal or Stripe.

[1360] Once the purchase is complete, the server provides the generated AI model and prompt data to the user, for example, by sending a download link or API key, making the data immediately available to the user.

[1361] Users can also customize the generative AI models and prompts they have purchased to suit their needs and re-register the customized versions on the platform. The server receives the re-registered data, verifies the format and required items, stores it in the database, and makes it public again.

[1362] Specific examples

[1363] For example, when a user creates a new natural language generation prompt and registers it on the platform, they enter information such as the prompt name "Business Strategy Proposal Generator," detailed description "Prompt to generate a business report," pricing "1,000 yen," and use case "Generating a business report," and click the "Submit" button.

[1364] This allows the prompts created by users to be registered in a database and made public. If a registered prompt is purchased by another user, the purchaser can use the prompt, customize it as needed, and register it again on the platform.

[1365] Prompt Sentence Examples

[1366] “I want to use generative AI to create a natural language generation model that is best suited to a specific business scenario. I want it to first gather customer insights and then generate sales strategy ideas based on those insights.”

[1367] By implementing the system of the present invention in the above manner, it is possible to realize dynamic recommendation display based on the user's emotional state, efficient transaction procedures, and fair revenue distribution, providing an environment in which companies and individuals can smoothly utilize generative AI models.

[1368] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1369] Step 1:

[1370] Users open a dedicated registration screen on their device to register the prompts and generative AI models they have created on the platform.

[1371] Input: Prompt name, detailed description, usage example, pricing

[1372] Specific operations: Display the registration screen on the device, enter the required information, and then click the send button.

[1373] Output: Prompts and generated AI model data are sent from the device to the server.

[1374] Step 2:

[1375] The server receives user-submitted prompts and generated AI model data.

[1376] Input: Data submitted by the user

[1377] Specific operation: The server receives the data and automatically verifies that the format and required fields are entered correctly.

[1378] Output: Verification results for format and required items. Data that has been verified is stored in a database.

[1379] Step 3:

[1380] The server collects emotion data from user input and operations.

[1381] Input: User keyboard input, mouse operation, facial expression recognition, voice analysis

[1382] How it works: Emotion data is collected in real time using an emotion engine, specifically software that analyzes data captured from cameras and microphones.

[1383] Output: Collected emotion data

[1384] Step 4:

[1385] The server analyzes the collected emotional data to determine the user's emotional state.

[1386] Input: Emotion data

[1387] Specific operation: The emotion engine is used to analyze emotion data and determine emotional states such as stress, excitement, and calmness.

[1388] Output: User's emotional state

[1389] Step 5:

[1390] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable form and prepares it for display on a web page.

[1391] Input: Metadata stored in a database

[1392] Specific operation: The server converts the metadata based on a search algorithm and generates a search index.

[1393] Output: Data for display in search indexes and web pages

[1394] Step 6:

[1395] The server uses the converted metadata to publish the prompts and generative AI models on an online platform.

[1396] Input: Search index and web page display data

[1397] Specific operation: The server displays the data on a web page, allowing users to freely browse and search it.

[1398] Output: prompts and generative AI models published to an online platform

[1399] Step 7:

[1400] The server recommends the most appropriate generative AI model and prompts to the user based on their emotional state.

[1401] Input: User emotional state, published prompts, and generative AI model data

[1402] Specific operation: The server applies a recommendation algorithm that reflects the emotional state and displays a generative AI model and prompts appropriate for the user.

[1403] Output: Recommended generative AI models and prompts

[1404] Step 8:

[1405] Users choose what they need from the published prompts and generative AI models and click the "Purchase" button.

[1406] Input: Data selected from a list of published prompts and generative AI models

[1407] Specific operation: The user clicks the purchase button and a purchase request is sent to the server.

[1408] Output: Purchase request

[1409] Step 9:

[1410] The server receives the purchase request from the user and checks the contents of the request.

[1411] Input: Purchase Request

[1412] Specific operation: The server confirms the purchase request and provides the user with a screen for entering payment information.

[1413] Output: Payment information input screen

[1414] Step 10:

[1415] The server receives the user's payment information and receives payment through the payment system.

[1416] Input: User's payment information

[1417] What it does: Processes payments using payment systems (e.g., PayPal, credit card systems).

[1418] Output: Payment completion notification

[1419] Step 11:

[1420] The server provides the user with the generated AI model and prompt data that have been purchased.

[1421] Input: Payment completion information, purchase data

[1422] Specific operation: The server generates a download link and API key and sends them to the user.

[1423] Output: Data provided to the user

[1424] Step 12:

[1425] Users can customize the generative AI models and prompts they purchase to suit their needs and then register the customized versions back on the platform.

[1426] Input: Purchased generative AI models, prompts, and customizations

[1427] Specific operation: The user makes customizations and uses the re-registration screen to send the customized version to the server.

[1428] Output: Customized prompts and generative AI models

[1429] Step 13:

[1430] The server receives the registered data again, verifies the format and necessary items, stores it in the database, and makes it public again.

[1431] Input: Re-registration data

[1432] Specific operation: The server receives the data, verifies the format and required items, stores it in the database, and then makes it available online again.

[1433] Output: Republished customized prompts and generative AI models

[1434] (Application example 2)

[1435] 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."

[1436] In modern digital marketplaces, there are efficient systems for aggregating, publishing, and purchasing generative AI models and prompts. However, there is a lack of a means for optimally displaying generative AI model recommendations that take into account the user's emotional state. Furthermore, without dynamic recommendations that reflect the user's emotions during the purchasing process, the user experience may be limited. Furthermore, there is a need for appropriate and fair revenue distribution.

[1437] 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, in a platform that aggregates generative AI models, means for storing registered prompts and generative AI models in a database, means for publishing the aggregated prompts and generative AI models online, means for receiving purchase requests from users and receiving payment through a payment system, means for providing the user with the generative AI model or prompt after the purchase is completed, means for sharing the revenue from the purchase price between the prompt creator and the platform operator, means for using an emotion analysis engine to collect emotional data from user inputs and operations, and means for recommending and displaying the generative AI model or prompt that is optimal for the user based on the emotional data. This makes it possible to analyze the user's emotional state and recommend the optimal generative AI model or prompt, improving the user experience and realizing efficient transactions.

[1438] A "generative AI model" is an algorithm or program that uses artificial intelligence to perform specific tasks such as natural language generation or image generation.

[1439] A "prompt" is data such as text or images that is input to a generative AI model to guide the generated output.

[1440] The "database" is an information management system for organizing and storing registered prompts and generative AI models.

[1441] The "Platform" is an online system for aggregating, publishing, and purchasing generative AI models and prompts.

[1442] A "payment system" is a financial transaction system for safely and efficiently processing purchase payments from users.

[1443] An "emotion analysis engine" is a technology or algorithm that analyzes a user's emotional state based on data obtained from the user's input and operations.

[1444] "Recommendation display" refers to proposing and displaying the optimal generative AI model and prompts to the user based on emotional data analyzed by the emotion analysis engine.

[1445] "Revenue sharing" means the process of calculating and transferring the purchase price to be appropriately divided between the prompt creator and the platform operator.

[1446] "Customization" refers to the act of modifying and adjusting the generative AI model or prompts purchased by a user to suit their own needs.

[1447] "Online publishing means" refers to methods or technologies that allow registered prompts and generative AI models to be viewed and purchased by users on the Internet.

[1448] The present invention relates to a system that combines a sentiment analysis engine with a platform for aggregating, selling, and delivering generative AI models and prompts, implemented using the following means:

[1449] First, the user registers the generative AI model or prompt on the platform. To do this, they open a dedicated registration screen, enter the required information such as the prompt's name, detailed description, use case, and pricing, and click the "Submit" button. The server receives the submitted data and verifies that the format and required fields have been entered correctly, and once verified, the data is stored in the database.

[1450] Next, an emotion analysis engine is used to collect emotional data from user input and operations. Emotional data is collected through the user's keyboard input, mouse operation, facial expression recognition, voice analysis, etc. The server analyzes the collected emotional data and determines the user's emotional state.

[1451] For example, if a user enters "I've been feeling stressed at work lately," the server will use its emotion analysis engine to determine the user's emotion as "stress." Based on this emotion data, the server will recommend the optimal generative AI model and prompts for the user. In this example, the server will recommend a "generative AI model that helps you relax."

[1452] Once the recommended generative AI models and prompts are made public, users can freely browse and search them. The user selects the prompt or generative AI model they need and clicks the "Purchase" button. The server receives the purchase request, checks its contents, and then provides the user with a screen for entering payment information. After the payment information is entered, the server receives payment through the payment system. Once the payment is complete, the server sends the user a notification that the purchase is complete.

[1453] The server then provides the user with the data for the generative AI model or prompt that has been purchased. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data. Users can also customize the generative AI model or prompt they purchased to suit their own needs and re-register the customized version on the platform. The server receives the re-registered data, verifies its format and required items, stores it in the database, and publishes it again.

[1454] Furthermore, a revenue sharing system will calculate a revenue share based on the purchase price, which will be divided appropriately between the prompt creator and the platform operator and transferred to the prompt creator's registered bank account or electronic wallet.

[1455] As described above, this system analyzes the user's emotional state to recommend the optimal generative AI model and prompts, enabling efficient and satisfying transactions, while ensuring fair and appropriate revenue distribution.

[1456] For example, if a user inputs "I've been feeling stressed at work lately," the server will perform emotion analysis and recommend a "generative AI model that will help you relax." In this way, the user experience can be improved by providing the optimal prompts and generative AI models according to the user's emotional state.

[1457] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1458] Step 1:

[1459] Users register generated AI models and prompts on the platform.

[1460] Input: The user enters information such as the name, description, use case, and pricing of the generated AI model or prompt.

[1461] Data processing: The user enters the necessary information on a dedicated registration screen and clicks the "Submit" button.

[1462] Output: Generated AI model and prompt data are sent to the server.

[1463] Step 2:

[1464] The server receives the data and verifies that the format and required fields are correct.

[1465] Input: The generative AI model and prompt data sent in Step 1.

[1466] Data processing: Automated scripts are run to check for missing or incorrect data.

[1467] Output: Data that has been validated. If there are no problems with the format or required items, proceed to the next step.

[1468] Step 3:

[1469] The server stores the validated data in the database.

[1470] Input: Data for the generative AI model and prompts that have been validated in Step 2.

[1471] Data manipulation: Inserting data into the appropriate tables in the database.

[1472] Output: Generative AI models and prompts stored in a database.

[1473] Step 4:

[1474] Use a sentiment analysis engine to collect emotional data from user input and actions.

[1475] Input: Data such as user keyboard input, mouse actions, facial expression recognition, and voice analysis.

[1476] Data calculation: The sentiment analysis engine analyzes these data in real time to determine the user's emotional state.

[1477] Output: Determined user emotion data.

[1478] Step 5:

[1479] Based on the emotional data, the server recommends the most suitable generative AI model and prompts for the user.

[1480] Input: User emotion data determined in step 4.

[1481] Data computation: Search and filter relevant generative AI models and prompts based on emotion data.

[1482] Output: The generated AI model and prompts that are displayed to the user.

[1483] Step 6:

[1484] The user selects a recommended generative AI model or prompt and clicks the "Purchase" button.

[1485] Input: User selection and payment information.

[1486] Data processing: Send a purchase request to the server and enter payment information on the payment screen.

[1487] Output: Purchase request and payment information is sent to the server.

[1488] Step 7:

[1489] The server receives the purchase request and verifies its contents.

[1490] Input: Purchase request and payment information submitted in step 6.

[1491] Data processing: Receive payment through the payment system.

[1492] Output: A notification of payment completion is sent to the user.

[1493] Step 8:

[1494] Provide users with generative AI models and prompts upon purchase completion.

[1495] Input: Data from the generative AI model or prompt that you purchased.

[1496] Data processing: Generate and provide download links and API keys to users.

[1497] Output: A link or key that allows users to access the generated AI model and prompts.

[1498] Step 9:

[1499] Customize the generative AI models and prompts you purchase to fit your needs.

[1500] Input: Data from purchased generative AI models and prompts.

[1501] Data calculation: User adjusts programs and parameters.

[1502] Output: Customized generative AI models and prompts.

[1503] Step 10:

[1504] The user re-registers the customization.

[1505] Input: Data for customized generative AI models and prompts.

[1506] Data processing: Send data from the re-registration screen.

[1507] Output: Data re-registered on the server.

[1508] Step 11:

[1509] The server receives the re-registered data and re-verifies its format and required items.

[1510] Input: The generative AI model and prompt data retrained in step 10.

[1511] Data calculation: Re-verification of data format and required items.

[1512] Output: The validated data.

[1513] Step 12:

[1514] The server stores the verified data in the database and makes it public again.

[1515] Input: The data that has passed validation in step 11.

[1516] Data processing: Re-insert the data into the appropriate tables in the database and set it to public.

[1517] Output: The published customization stored in the database.

[1518] Step 13:

[1519] The revenue sharing system calculates and distributes the revenue share amount based on the purchase price.

[1520] Input: User purchase data and revenue sharing rules.

[1521] Data calculation: Calculation of revenue share.

[1522] Output: Revenue share remittance to prompt creators and platform operators.

[1523] 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.

[1524] 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.

[1525] 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.

[1526] [Fourth embodiment]

[1527] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1528] 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.

[1529] 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).

[1530] 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.

[1531] 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.

[1532] 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).

[1533] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1534] 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.

[1535] 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.

[1536] 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.

[1537] 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.

[1538] 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.

[1539] 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."

[1540] The present invention relates to a platform that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and sells or provides them. The system of the present invention is embodied in the following form.

[1541] 1. Aggregation of prompt and generative AI models

[1542] Registering prompt and generative AI models

[1543] Users register their own prompts and generative AI models on the platform by entering information such as the prompt name, detailed description, use case, and pricing on the registration screen and clicking the "Submit" button.

[1544] Data Receipt and Validation

[1545] The server receives the prompts sent by the user and the data from the generative AI model. The received data is verified to ensure that the format and required fields are entered correctly. Once verified, the data is stored in a database.

[1546] 2. Publishing generative AI models and prompts

[1547] Preparation for release

[1548] The server converts the metadata of the prompts and generative AI models registered in the database into a searchable format and prepares it for display on a web page.

[1549] public

[1550] The server publishes the ready-to-publish prompts and generative AI models on an online platform, where they can be browsed and searched by users.

[1551] 3. Purchase procedure

[1552] Selecting a prompt

[1553] Users choose what they need from the published prompts and generative AI models and click the "Purchase" button.

[1554] Receiving a purchase request

[1555] The server receives the user's purchase request and checks its contents.

[1556] Enter your payment information

[1557] The user follows the server's instructions and enters payment information (credit card information, electronic payment service information, etc.).

[1558] Payment Processing

[1559] The server receives the user's purchase payment through the payment system, and once payment is complete, sends the user a purchase completion notification.

[1560] Providing generative AI models and prompts

[1561] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by sending the user a download link and API key.

[1562] 4. Revenue Sharing

[1563] Calculating revenue

[1564] The server calculates the revenue share based on the purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[1565] Revenue sharing execution

[1566] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[1567] 5. Customization and Re-provision

[1568] Customizing prompts and generative AI models

[1569] Users can download the generative AI models and prompts they purchase and customize them to suit their needs.

[1570] Re-registering a customized version

[1571] The user can then re-register the customized generative AI model and prompts on the platform by entering the necessary information on the prompt registration screen again and submitting it.

[1572] Re-registration process

[1573] The server verifies the data format and required items of the re-registered customized prompts and generative AI models, stores them in the database, and then prepares them for publication and publishes them again.

[1574] Specific examples

[1575] For example, a user can create a new natural language generation prompt and register it on the platform. The prompt is then published, and other users can purchase it. After completing the purchase, the user can customize the prompt and register it again on the platform. In this way, new prompts and generative AI models are constantly being aggregated, published, and revenues are shared.

[1576] The system of the present invention is implemented in the above manner, providing centralized information management, efficient transactions, and fair revenue distribution, thereby realizing an environment in which companies and individuals can smoothly utilize generative AI models.

[1577] The processing flow will be explained below.

[1578] Step 1:

[1579] Users open a dedicated registration screen to register their own prompts and generative AI models on the platform. On the registration screen, they enter the required information, such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[1580] Step 2:

[1581] The server receives the prompts sent by the user and the data from the generative AI model. It verifies that the received data is correctly formatted and that all required fields are entered. If the data is determined to be correct, it stores the data in a database.

[1582] Step 3:

[1583] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format, preparing them for efficient search and browsing by users through the platform.

[1584] Step 4:

[1585] The server uses the converted metadata to publish the prompts and generative AI models on a webpage, where users can freely browse and search them.

[1586] Step 5:

[1587] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[1588] Step 6:

[1589] The server receives the user's purchase request, verifies its contents, and then provides the user with a screen for entering payment information.

[1590] Step 7:

[1591] The user follows the instructions of the server and enters payment information such as credit card information and electronic payment service information, then clicks the "Submit" button to complete the payment.

[1592] Step 8:

[1593] The server receives payment from the user through the payment system. Once payment is complete, the server sends a notification to the user that the purchase has been completed.

[1594] Step 9:

[1595] The server provides the user with the prompts and generated AI model data for which the purchase has been completed, and the user is sent a download link and API key, allowing them to immediately use the purchased data.

[1596] Step 10:

[1597] The server calculates the revenue share based on the user's purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[1598] Step 11:

[1599] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[1600] Step 12:

[1601] Users can customize the purchased prompts and generative AI models to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[1602] Step 13:

[1603] The server receives the customized prompts and generated AI model data registered by the user, verifies their format and required items, and stores the verified data in a database.

[1604] Step 14:

[1605] The server then converts the metadata of the customized prompts and generative AI models stored in the database into a searchable format and republishes them on the webpage, allowing new prompts and generative AI models to be constantly updated and made public.

[1606] Example 1

[1607] 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."

[1608] Today, businesses and individuals lack a platform for effectively managing and trading generative AI models and prompts. Therefore, there is a need for a system that allows users to easily register, sell, and reuse their generated prompts and AI models. Furthermore, the purchasing procedures and revenue distribution processes are complex, and an efficient and fair method is needed.

[1609] 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.

[1610] In this invention, the server includes means for a user to input prompts and generative AI models and send the contents to the server, means for the server to receive the data sent from the user and verify the format and necessary items, means for storing the verified data in a database and notifying the user, means for converting the stored data into a searchable format and publishing it on an online platform, means for receiving purchase requests from users and receiving payment through a payment system, means for providing generative AI models and prompts after purchase is completed, and means for sharing revenue from the purchase price. This allows users to efficiently register, publish, sell, and reuse prompts and generative AI models, and enables fair and smooth revenue sharing.

[1611] "User" means an individual or entity that uses the Platform to register, purchase, and customize prompts and generative AI models.

[1612] A "prompt" is text data or instructions input into a generative AI model that determines the output content generated.

[1613] A "generative AI model" is an artificial intelligence model that performs natural language processing or generative tasks, including algorithms for generating output in response to prompts.

[1614] "Server" is a central control device that manages the entire system and performs various processes such as receiving, verifying, storing, publishing, payment processing, and revenue distribution of data.

[1615] "Database" means a storage system for centrally managing and storing data, including prompts and generative AI models.

[1616] "Payment system" means a system for processing payments for user purchases, including credit cards and electronic payment services.

[1617] "Revenue sharing" is a system in which revenue earned when users sell prompts or generative AI models is divided fairly between prompt creators and platform operators.

[1618] "Customization" refers to the process by which users edit and modify the generative AI models and prompts they purchase to adapt them to their own specific needs.

[1619] "Online Platform" means a web-based system that enables users to register, publish, sell, buy, and customize prompt and generative AI models.

[1620] "Re-registration" refers to the act of a user customizing the prompts and generative AI models that were initially registered and then registering them again on the platform.

[1621] The present invention relates to a platform for aggregating prompts and generative AI models created by companies and individuals using generative AI models, and for selling and providing them. This platform is composed of components such as a server, terminals, databases, online interfaces, and payment systems.

[1622] Process Overview

[1623] 1. Registering a prompt and generate AI model

[1624] The user uses a device to access the platform's registration screen, enters the prompts and details of the generated AI model (such as name, detailed description, use case, pricing, etc.), and clicks the "Submit" button.

[1625] The server receives the data sent by the user and verifies whether the data format and required items have been entered correctly. Once the verification is complete, the data is stored in a database.

[1626] 2. Publishing generative AI models and prompts

[1627] The server converts the metadata of the prompts and generative AI models registered in the database into a searchable format and generates a user interface, allowing users to browse and search the published prompts and generative AI models on an online platform.

[1628] 3. Purchase procedure

[1629] Users select a published prompt or generative AI model, click the "Purchase" button, and enter their payment information.

[1630] The server receives the purchase request and payment information from the user, receives the payment through the payment system, and sends a notification of purchase completion to the user once the payment is complete.

[1631] 4. Providing generative AI models and prompts

[1632] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by emailing the user a download link and API key.

[1633] 5. Revenue Sharing

[1634] The server calculates the revenue share based on the purchase price, distributes the revenue according to the distribution ratio between the prompt creator and the platform operator, and transfers the revenue share to the prompt creator's bank account or electronic wallet.

[1635] 6. Customization and Re-provision

[1636] Users can customize the generative AI models and prompts they purchase to suit their own needs.

[1637] Users can then re-register their customized generative AI models and prompts on the platform, where the re-registered data will be verified by the server again, stored in the database, and published again on the online platform once it is ready to be published.

[1638] Specific examples

[1639] For example, suppose a user creates a new natural language generation prompt and registers it on the platform. The prompt is then published and other users can purchase it. Here is an example of a prompt:

[1640] "Example Natural Language Generation Prompt: Generate a conversation about a topic of interest to a college student."

[1641] After completing the purchase, the user can customize the prompt and register again on the platform, thus constantly collecting and publishing new prompts and generative AI models, and sharing revenues.

[1642] The system of the present invention provides centralized information management, efficient transactions, and fair revenue distribution, creating an environment in which companies and individuals can smoothly utilize generative AI models.

[1643] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1644] Step 1: User Data Entry

[1645] Users use their device to access the platform's registration screen and enter prompts and details about the generated AI model (such as name, detailed description, use cases, and pricing).

[1646] Input: Prompt and details about the generated AI model.

[1647] Output: Input data temporarily stored on the device.

[1648] Specific behavior: The user enters data into the input field and clicks the "Submit" button. The device temporarily stores the entered data.

[1649] Step 2: Sending data

[1650] The terminal transmits the saved input data to the server.

[1651] Input: User input data.

[1652] Output: The data sent to the server.

[1653] Specific operation: The device generates an HTTP request and sends the input data to the server.

[1654] Step 3: Receiving and verifying data

[1655] The server receives the data sent by the user and verifies whether the format and required items have been entered correctly.

[1656] Input: The user's data received by the server.

[1657] Output: Validation results and data to be stored in the database.

[1658] Specific behavior: The server checks the format and required fields of the received data, and generates an error message if there is invalid data.

[1659] Step 4: Store the data

[1660] The server stores the verified data in a database.

[1661] Input: The user's data after validation.

[1662] Output: Data stored in the database and notification to the user.

[1663] What happens: The server generates the SQL commands to insert the data into the database, then notifies the user that the registration is complete.

[1664] Step 5: Convert metadata and prepare for publishing

[1665] The server converts the metadata registered in the database into a searchable format and generates a user interface.

[1666] Input: Metadata stored in a database.

[1667] Output: A search index and a user interface.

[1668] What it does: The server indexes the metadata and dynamically generates the web page.

[1669] Step 6: Publish online

[1670] The server publishes the ready generative AI models and prompts on an online platform.

[1671] Input: Prepared prompts and metadata for the generative AI model.

[1672] Output: The published prompt and / or generative AI model.

[1673] What happens: The server updates the web page to display the published prompt and generative AI model.

[1674] Step 7: User selects prompt

[1675] Users can browse published prompts and generative AI models on the platform and click the "Purchase" button for the one they need.

[1676] Input: A list of published prompts and generative AI models.

[1677] Output: Selected prompts and generative AI models.

[1678] What happens: The user navigates through the web interface, selects the item they want to purchase, and clicks the "Buy" button.

[1679] Step 8: Receiving a Purchase Request

[1680] The server receives the user's purchase request and payment information and verifies the contents.

[1681] Input: User purchase request and payment information.

[1682] Output: Confirmed request and payment information.

[1683] Specific operation: The server generates a token for payment information and sends it to the payment system.

[1684] Step 9: Payment Processing

[1685] The server receives payment through the payment system, and once payment is complete, sends a notification to the user that the purchase is complete.

[1686] Input: Payment information.

[1687] Output: Payment completion notification.

[1688] Specific operation: The server calls the payment system API and notifies the user when the payment is successful.

[1689] Step 10: Providing generative AI models and prompts

[1690] The server provides the user with the generated AI model and prompt data after the purchase is completed, specifically by emailing the user a download link and API key.

[1691] Input: Purchase completion data.

[1692] Output: Download link and API key.

[1693] What happens: The server uses an email service to send the user an email containing the necessary download link and API key.

[1694] Step 11: Calculate Revenue Share

[1695] The server calculates the revenue share amount based on the purchase price and distributes the revenue according to the distribution ratio between the prompt creator and the platform operator.

[1696] Input: Purchase price data and distribution percentage.

[1697] Output: Calculated distribution amount.

[1698] Specific operation: The server executes the calculation algorithm and calculates the distribution amount.

[1699] Step 12: Implementing Revenue Sharing

[1700] The server transfers the calculated revenue share amount to the prompt creator's registered bank account or electronic wallet.

[1701] Input: Calculated distribution amount.

[1702] Output: Remittance completion notification.

[1703] Specific operation: The server calls the API of the bank or electronic wallet to transfer the distribution amount, and then sends a notification of the completion of the transfer to the creator.

[1704] Step 13: Customizing prompts and generative AI models

[1705] Users can download the generative AI models and prompts they purchase and customize them to suit their needs.

[1706] Input: Downloaded generative AI model and prompts.

[1707] Output: Customized generative AI models and prompts.

[1708] Specific operation: The user edits and modifies the generated AI model and prompts in the local environment.

[1709] Step 14: Re-register your customizations

[1710] Users can re-register their customized generative AI models and prompts to the platform by entering the necessary information on the prompt registration screen again and clicking the "Submit" button.

[1711] Input: Customized generative AI models and prompts.

[1712] Output: Re-enrollment data sent to the platform.

[1713] Specific behavior: The user enters the required information on the re-registration screen and the customized data is sent to the server.

[1714] Step 15: Receiving and verifying re-enrollment data

[1715] The server receives the registered prompt and generated AI model data again and verifies that the format and required fields have been entered correctly.

[1716] Input: Re-registered data.

[1717] Output: Validation results and data to be stored in the database.

[1718] Specific operation: The server verifies the data format and required items, just as it did during initial registration.

[1719] Step 16: Store and republish resubmission data

[1720] The server stores the re-registered data in a database and makes it available again on the online platform.

[1721] Input: Your verified re-enrollment data.

[1722] Output: Published re-registration data.

[1723] Specific operation: The server stores the data after validation in a database and makes it public once it is ready.

[1724] (Application example 1)

[1725] 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."

[1726] Platforms that utilize generative AI models are required to provide an environment where users can smoothly and efficiently complete the entire process of registering, searching, purchasing, and customizing prompts and generative AI models. A system is also required that allows users to easily customize and re-register purchased prompts. Conventional systems make these processes cumbersome, and one issue is that they do not adequately support operation on smart devices.

[1727] 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.

[1728] In this invention, the server includes a platform that aggregates generative AI models, a means for storing registered prompts and generative AI models in a database, a means for publishing the aggregated prompts and generative AI models online, and a means for receiving purchase requests from users and receiving payment through a payment system. This allows users to intuitively perform a series of operations using their smartphones to register, search, purchase, and customize prompts and generative AI models. Furthermore, the ease of performing a series of operations to register and publish user-customized prompts on the platform further expands the scope of use of generative AI models.

[1729] A "generative AI model" is a model that automatically generates content and data using artificial intelligence algorithms.

[1730] A "prompt" is an instruction or command that is input to a generative AI model, and is a phrase that specifies the type and content of the content to be generated.

[1731] "Platform" means an online system for aggregating, registering, publishing, purchasing, customizing, and re-registering generative AI models and prompts.

[1732] "Database" means a data storage system for storing and managing registered generative AI models and prompts.

[1733] "Means for online publication" refers to a method for publishing the generative AI model and prompt information stored in the database in a form accessible via the Internet.

[1734] The "means for receiving purchase requests" refers to the mechanism by which requests are received when a user applies to purchase a generative AI model or prompt through the platform.

[1735] "Payment System" means a system for processing and completing payments required when a user purchases a generative AI model or prompt.

[1736] "Customization" refers to the act of modifying the content of generative AI models or prompts purchased or acquired by a user to suit their own needs.

[1737] "Means for re-registration" refers to a method by which a user can re-register their customized generative AI model or prompts on the platform.

[1738] A "smartphone" is a portable information terminal that has Internet connectivity and can be used by installing various applications.

[1739] The present invention relates to a platform that utilizes generative AI models to aggregate and sell or provide prompts and generative AI models created by companies and individuals. The following describes in detail an embodiment of the present invention.

[1740] Hardware and Software

[1741] The system of this invention includes a server, a smartphone, a database, and a payment system. The server hosts an online platform and runs a web application using Flask. The database uses SQLite, and the payment system uses Stripe.

[1742] System Operation

[1743] Registration Process

[1744] Users register the prompts and generative AI models they have created using their smartphones. The information entered by the user, such as the prompt name, detailed description, use case, and pricing, is sent to the server. The server verifies the format and required items of the received data, and stores the verified data in an SQLite database. Once verification is complete, a notification of registration completion is sent to the user.

[1745] Publishing Process

[1746] The server converts the prompts and generative AI model information stored in the database into a searchable format, making these prompts available for other users to search and view on the online platform.

[1747] Purchase Process

[1748] The user selects what they need from prompts and generative AI models published on the online platform and submits a purchase request. The server receives this request and receives the user's purchase payment through a payment system (Stripe). Once the purchase is complete, the server sends the user a download link and API key and notifies them of the purchase completion.

[1749] Customization and Re-registration Process

[1750] Users can customize the generative AI models and prompts they have purchased on their smartphones. After customization, they send a request to the server to re-register them on the platform. The server again verifies the format and required items of the received data and re-registers them in the database. Once re-registration is complete, the customized generative AI models and prompts are made public again.

[1751] Specific examples

[1752] For example, consider a scenario where a user registers an "automated script generation prompt," which is then purchased by other users and used to generate movie scripts. The purchasing user can generate a script based on the prompt and customize it to suit their needs. The customized prompt can then be registered back on the platform and made available to other users.

[1753] Example prompt sentence:

[1754] "Automatic script generation prompt: This AI prompt is used to generate a movie script. Input the specified theme and character settings and it will automatically generate everything from the plot to the dialogue."

[1755] In this way, the present invention provides a comprehensive platform for efficiently aggregating, publishing, and trading generative AI models and prompts.

[1756] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1757] Step 1:

[1758] The server receives input from the user's smartphone when registering a prompt or generative AI model. The input includes information such as the prompt's name, detailed description, use case, and pricing. The server verifies that the format and required fields of this data are correct, and stores the verified data in an SQLite database. Once registration is complete, the server sends a notification to the user that registration is complete.

[1759] Step 2:

[1760] The server converts the information about the prompts and generative AI models stored in the database into a searchable format. Specifically, it extracts the metadata of the prompts and generative AI models, indexes them, and prepares them for display on a web page, allowing other users to search and view these prompts on an online platform from their smartphones.

[1761] Step 3:

[1762] The user selects the prompt or generative AI model they need from those published on the online platform and sends a purchase request to the server. The server receives this request and retrieves the price information of the corresponding prompt from a database. The server then charges the user for the purchase price through the payment system (Stripe) and completes the payment process. Once payment is complete, a download link and API key are generated and sent to the user, along with a notification that the purchase is complete.

[1763] Step 4:

[1764] Users customize the generative AI model and prompts they purchased on their smartphones. For example, they can change the prompt text or settings. The customized prompts are then sent to the server via a registration request. The server again verifies the format and required fields of the received data and stores it in the database. Once re-registration is complete, the customized prompts and generative AI models are made public again.

[1765] Step 5:

[1766] The server calculates the revenue share between the prompt creator and the platform operator based on the published prompts and the viewing and purchase history of the generating AI model. After calculating the revenue, the server transfers the revenue to the prompt creator's registered bank account or electronic wallet and notifies the prompt creator that the revenue share is complete.

[1767] 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.

[1768] The present invention relates to a system that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and combines an emotion engine with a platform for selling and providing these. The system of the present invention can be implemented in the following forms.

[1769] 1. Aggregation of prompt and generative AI models

[1770] Registering prompt and generative AI models

[1771] Users open a dedicated registration screen to register their created prompts and generative AI models on the platform, enter the required information such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[1772] Data Receipt and Validation

[1773] The server receives the prompts sent by the user and the generated AI model data, verifies that the format and required fields are correct, and stores the verified data in a database.

[1774] 2. Introducing the Emotion Engine

[1775] Collecting Emotional Data

[1776] The server is equipped with an emotion engine for collecting emotion data from inputs and operations of users accessing the platform, such as through keyboard input, mouse operation, facial expression recognition, and voice analysis.

[1777] Sentiment Data Analysis

[1778] The server analyzes the collected emotion data with an emotion engine to determine the user's emotional state, for example, whether the user is stressed, excited, or calm.

[1779] 3. Publishing the generative AI model and prompts and displaying recommendations

[1780] Preparation for release

[1781] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable form and prepares it for display on a web page.

[1782] public

[1783] The server uses the converted metadata to publish the prompts and generative AI models on an online platform, where users can freely browse and search them.

[1784] Recommendation display

[1785] The server then recommends the most appropriate generative AI model and prompts for the user based on the emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[1786] 4. Purchase procedure

[1787] Selecting a prompt

[1788] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[1789] Receiving and settling purchase requests

[1790] The server receives the user's purchase request, checks its contents, provides the user with a screen for entering payment information, and receives payment through the payment system after the payment information is entered. Once payment is complete, the server sends a notification of purchase completion to the user.

[1791] Providing generative AI models and prompts

[1792] The server provides the user with the prompts and generated AI model data for which the purchase has been completed. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data.

[1793] 5. Revenue Sharing

[1794] Calculating revenue

[1795] The server calculates the revenue share based on the purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[1796] Revenue sharing execution

[1797] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[1798] 6. Customization and Re-provision

[1799] Customizing prompts and generative AI models

[1800] Users can customize the generative AI models and prompts they purchase to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[1801] Re-registration process

[1802] The server receives the customized prompts and generated AI model data that the user has re-registered, verifies their format and required items, stores them in the database, and makes them public again.

[1803] Specific examples

[1804] For example, suppose a user creates a new natural language generation prompt and registers it on the platform. The prompt is then made public, and other users purchase it. After completing the purchase, the user customizes the prompt and registers it again on the platform. Furthermore, the emotion engine analyzes the user's emotional state, and based on the results, recommends the most suitable generation AI model and prompt for the user. This allows users to make efficient and satisfying selections.

[1805] The system of the present invention is implemented in the above manner, providing centralized information management, efficient transactions, fair revenue distribution, and dynamic recommendation display based on the user's emotional state, thereby realizing an environment in which companies and individuals can smoothly utilize generative AI models.

[1806] The processing flow will be explained below.

[1807] Step 1:

[1808] To register their own prompts and generative AI models on the platform, users open a dedicated registration screen, enter information such as the prompt name, detailed description, use case, and pricing, and click the "Submit" button.

[1809] Step 2:

[1810] The server receives the prompts sent by the user and the generated AI model data. It verifies that the data format and required fields have been entered correctly. Once the verification is complete, the data is stored in a database.

[1811] Step 3:

[1812] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format, preparing them for efficient search and browsing by users through the platform.

[1813] Step 4:

[1814] The server uses the converted metadata to publish the prompts and generative AI models on a webpage, where users can freely browse and search them.

[1815] Step 5:

[1816] The server runs an emotion engine that collects emotional data from the input and operations of users accessing the platform, including through keyboard input, mouse operation, facial expression recognition, and voice analysis.

[1817] Step 6:

[1818] The server uses an emotion engine to analyze the collected emotion data and determine the user's emotional state, for example, whether the user is stressed, excited, or calm.

[1819] Step 7:

[1820] The server then recommends the optimal generative AI model and prompts to the user based on the emotional data analyzed by the emotion engine. For example, if the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[1821] Step 8:

[1822] Users select what they want from the published prompts and generative AI models and click the "Purchase" button, which sends a purchase request to the server.

[1823] Step 9:

[1824] The server receives the user's purchase request, verifies its contents, and then provides the user with a screen for entering payment information.

[1825] Step 10:

[1826] The user follows the server's instructions and enters payment information (credit card information, electronic payment service information, etc.). After entering the information, the user clicks the "Submit" button to complete the payment.

[1827] Step 11:

[1828] The server receives the user's purchase payment through the payment system. Once payment is complete, the server sends a purchase completion notification to the user.

[1829] Step 12:

[1830] The server provides the user with the prompts and generated AI model data for which the purchase has been completed. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data.

[1831] Step 13:

[1832] The server calculates the revenue share based on the user's purchase price, taking into account the share ratio between the prompt creator and the platform operator.

[1833] Step 14:

[1834] The server transfers the revenue share to the prompt creator's registered bank account or electronic wallet, and the operator's share is also processed internally.

[1835] Step 15:

[1836] Users can customize the purchased prompts and generative AI models to suit their needs, and once customization is complete, they can register the customized versions back on the platform.

[1837] Step 16:

[1838] The server receives the customized prompts and generated AI model data registered by the user, verifies their format and required items, and stores the verified data in a database.

[1839] Step 17:

[1840] The server then converts the metadata of the customized prompts and generative AI models stored in the database into a searchable format and republishes them on the webpage, allowing new prompts and generative AI models to be constantly updated and made public.

[1841] Example 2

[1842] 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."

[1843] Current platforms that aggregate and provide generative AI models and prompts provide generic prompts and models without considering the user's emotional state, which means they are unable to provide optimal suggestions based on the user's needs and emotional state. Another problem is that the procedures for registering, purchasing, and customizing prompts and generative AI models are complicated, making it difficult to achieve efficient transactions.

[1844] The identification process 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 platform that aggregates prompts and generative AI models, a means for storing registered prompts and generative AI models in a database, a means for publishing the aggregated prompts and generative AI models online, a means for receiving a purchase request from a user and receiving payment through a payment system, a means for providing the user with a generative AI model or prompt after the purchase is completed, a means for having an emotion engine that collects emotional data from the user's input and operation, a means for analyzing the collected emotional data and determining the user's emotional state, and a means for recommending and displaying the generative AI model or prompt that is optimal for the user based on the emotional state. This makes it possible to recommend the optimal generative AI model or prompt according to the user's emotional state, thereby achieving an efficient and satisfying selection.

[1845] A "prompt" is input data that allows a user to give instructions or questions to a generative AI model.

[1846] A "generative AI model" is an algorithm that uses artificial intelligence to generate a response or output for a specific purpose.

[1847] A "database" is an information system for efficiently storing and managing large amounts of data.

[1848] An "emotion engine" is a system that collects emotional data from user input and operations, analyzes it, and determines the user's emotional state.

[1849] "Metadata" is data that describes information related to prompts and generative AI models, making them easier to search and organize within the database.

[1850] A "payment system" is a system for processing payments in online transactions.

[1851] "Revenue sharing" is the process of dividing revenue among the parties involved (prompt creators and platform operators).

[1852] "Customization" refers to the act of a user adjusting and modifying prompts and generative AI models to meet their specific needs.

[1853] The present invention relates to a system that utilizes generative AI models, aggregates prompts and generative AI models created by companies and individuals, and combines an emotion engine with a platform for selling and providing them. This system is implemented as follows.

[1854] This system is primarily composed of a user, a terminal, and a server. The user uses the terminal to register the prompts and generative AI models they have created on the platform. The terminal provides an interface for entering information such as the prompt's name, detailed description, use case, and pricing using a registration screen. When the user clicks the "Submit" button, the terminal sends this data to the server.

[1855] The server receives the prompts and generated AI model data sent by the user and automatically verifies that the format and required fields are entered correctly. Once verified, the data is stored in a database. Specifically, the server uses a management system such as an SQL database to properly store and manage the data.

[1856] Furthermore, the server is equipped with an emotion engine that collects emotion data from user input and operations. Emotion data is collected through user keyboard input, mouse operation, facial expression recognition, and voice analysis. For example, software is used that uses a camera and microphone to analyze the user's facial expressions and voice. This is expected to use "Face API" for facial expression recognition and "Google Cloud Speech-to-Text API" for voice analysis.

[1857] The collected emotional data is analyzed by an emotion engine in the server to determine the user's emotional state. Emotional states include stress, excitement, and calmness. The analysis results are used to display recommendations to the user. For example, if the server determines that the user is feeling stressed, it will recommend a generative AI model with a relaxing effect.

[1858] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable format and prepares it for display on a web page, allowing users to freely browse and search the prompts and generative AI models on the online platform.

[1859] When a user selects a prompt or generative AI model and clicks the "Purchase" button, the purchase request is sent to the server, which receives payment through a payment system and notifies the user that the purchase is complete. This payment system uses online payment services such as PayPal or Stripe.

[1860] Once the purchase is complete, the server provides the generated AI model and prompt data to the user, for example, by sending a download link or API key, making the data immediately available to the user.

[1861] Users can also customize the generative AI models and prompts they have purchased to suit their needs and re-register the customized versions on the platform. The server receives the re-registered data, verifies the format and required items, stores it in the database, and makes it public again.

[1862] Specific examples

[1863] For example, when a user creates a new natural language generation prompt and registers it on the platform, they enter information such as the prompt name "Business Strategy Proposal Generator," detailed description "Prompt to generate a business report," pricing "1,000 yen," and use case "Generating a business report," and click the "Submit" button.

[1864] This allows the prompts created by users to be registered in a database and made public. If a registered prompt is purchased by another user, the purchaser can use the prompt, customize it as needed, and register it again on the platform.

[1865] Prompt Sentence Examples

[1866] “I want to use generative AI to create a natural language generation model that is best suited to a specific business scenario. I want it to first gather customer insights and then generate sales strategy ideas based on those insights.”

[1867] By implementing the system of the present invention in the above manner, it is possible to realize dynamic recommendation display based on the user's emotional state, efficient transaction procedures, and fair revenue distribution, providing an environment in which companies and individuals can smoothly utilize generative AI models.

[1868] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1869] Step 1:

[1870] Users open a dedicated registration screen on their device to register the prompts and generative AI models they have created on the platform.

[1871] Input: Prompt name, detailed description, usage example, pricing

[1872] Specific operations: Display the registration screen on the device, enter the required information, and then click the send button.

[1873] Output: Prompts and generated AI model data are sent from the device to the server.

[1874] Step 2:

[1875] The server receives user-submitted prompts and generated AI model data.

[1876] Input: Data submitted by the user

[1877] Specific operation: The server receives the data and automatically verifies that the format and required fields are entered correctly.

[1878] Output: Verification results for format and required items. Data that has been verified is stored in a database.

[1879] Step 3:

[1880] The server collects emotion data from user input and operations.

[1881] Input: User keyboard input, mouse operation, facial expression recognition, voice analysis

[1882] How it works: Emotion data is collected in real time using an emotion engine, specifically software that analyzes data captured from cameras and microphones.

[1883] Output: Collected emotion data

[1884] Step 4:

[1885] The server analyzes the collected emotional data to determine the user's emotional state.

[1886] Input: Emotion data

[1887] Specific operation: The emotion engine is used to analyze emotion data and determine emotional states such as stress, excitement, and calmness.

[1888] Output: User's emotional state

[1889] Step 5:

[1890] The server converts the metadata of the prompts and generative AI models stored in the database into a searchable form and prepares it for display on a web page.

[1891] Input: Metadata stored in a database

[1892] Specific operation: The server converts the metadata based on a search algorithm and generates a search index.

[1893] Output: Data for display in search indexes and web pages

[1894] Step 6:

[1895] The server uses the converted metadata to publish the prompts and generative AI models on an online platform.

[1896] Input: Search index and web page display data

[1897] Specific operation: The server displays the data on a web page, allowing users to freely browse and search it.

[1898] Output: prompts and generative AI models published to an online platform

[1899] Step 7:

[1900] The server recommends the most appropriate generative AI model and prompts to the user based on their emotional state.

[1901] Input: User emotional state, published prompts, and generative AI model data

[1902] Specific operation: The server applies a recommendation algorithm that reflects the emotional state and displays a generative AI model and prompts appropriate for the user.

[1903] Output: Recommended generative AI models and prompts

[1904] Step 8:

[1905] Users choose what they need from the published prompts and generative AI models and click the "Purchase" button.

[1906] Input: Data selected from a list of published prompts and generative AI models

[1907] Specific operation: The user clicks the purchase button and a purchase request is sent to the server.

[1908] Output: Purchase request

[1909] Step 9:

[1910] The server receives the purchase request from the user and checks the contents of the request.

[1911] Input: Purchase Request

[1912] Specific operation: The server confirms the purchase request and provides the user with a screen for entering payment information.

[1913] Output: Payment information input screen

[1914] Step 10:

[1915] The server receives the user's payment information and receives payment through the payment system.

[1916] Input: User's payment information

[1917] What it does: Processes payments using payment systems (e.g., PayPal, credit card systems).

[1918] Output: Payment completion notification

[1919] Step 11:

[1920] The server provides the user with the generated AI model and prompt data that have been purchased.

[1921] Input: Payment completion information, purchase data

[1922] Specific operation: The server generates a download link and API key and sends them to the user.

[1923] Output: Data provided to the user

[1924] Step 12:

[1925] Users can customize the generative AI models and prompts they purchase to suit their needs and then register the customized versions back on the platform.

[1926] Input: Purchased generative AI models, prompts, and customizations

[1927] Specific operation: The user makes customizations and uses the re-registration screen to send the customized version to the server.

[1928] Output: Customized prompts and generative AI models

[1929] Step 13:

[1930] The server receives the registered data again, verifies the format and necessary items, stores it in the database, and makes it public again.

[1931] Input: Re-registration data

[1932] Specific operation: The server receives the data, verifies the format and required items, stores it in the database, and then makes it available online again.

[1933] Output: Republished customized prompts and generative AI models

[1934] (Application example 2)

[1935] 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."

[1936] In modern digital marketplaces, there are efficient systems for aggregating, publishing, and purchasing generative AI models and prompts. However, there is a lack of a means for optimally displaying generative AI model recommendations that take into account the user's emotional state. Furthermore, without dynamic recommendations that reflect the user's emotions during the purchasing process, the user experience may be limited. Furthermore, there is a need for appropriate and fair revenue distribution.

[1937] 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, in a platform that aggregates generative AI models, means for storing registered prompts and generative AI models in a database, means for publishing the aggregated prompts and generative AI models online, means for receiving purchase requests from users and receiving payment through a payment system, means for providing the user with the generative AI model or prompt after the purchase is completed, means for sharing the revenue from the purchase price between the prompt creator and the platform operator, means for using an emotion analysis engine to collect emotional data from user inputs and operations, and means for recommending and displaying the generative AI model or prompt that is optimal for the user based on the emotional data. This makes it possible to analyze the user's emotional state and recommend the optimal generative AI model or prompt, improving the user experience and realizing efficient transactions.

[1938] A "generative AI model" is an algorithm or program that uses artificial intelligence to perform specific tasks such as natural language generation or image generation.

[1939] A "prompt" is data such as text or images that is input to a generative AI model to guide the generated output.

[1940] The "database" is an information management system for organizing and storing registered prompts and generative AI models.

[1941] The "Platform" is an online system for aggregating, publishing, and purchasing generative AI models and prompts.

[1942] A "payment system" is a financial transaction system for safely and efficiently processing purchase payments from users.

[1943] An "emotion analysis engine" is a technology or algorithm that analyzes a user's emotional state based on data obtained from the user's input and operations.

[1944] "Recommendation display" refers to proposing and displaying the optimal generative AI model and prompts to the user based on emotional data analyzed by the emotion analysis engine.

[1945] "Revenue sharing" means the process of calculating and transferring the purchase price to be appropriately divided between the prompt creator and the platform operator.

[1946] "Customization" refers to the act of modifying and adjusting the generative AI model or prompts purchased by a user to suit their own needs.

[1947] "Online publishing means" refers to methods or technologies that allow registered prompts and generative AI models to be viewed and purchased by users on the Internet.

[1948] The present invention relates to a system that combines a sentiment analysis engine with a platform for aggregating, selling, and delivering generative AI models and prompts, implemented using the following means:

[1949] First, the user registers the generative AI model or prompt on the platform. To do this, they open a dedicated registration screen, enter the required information such as the prompt's name, detailed description, use case, and pricing, and click the "Submit" button. The server receives the submitted data and verifies that the format and required fields have been entered correctly, and once verified, the data is stored in the database.

[1950] Next, an emotion analysis engine is used to collect emotional data from user input and operations. Emotional data is collected through the user's keyboard input, mouse operation, facial expression recognition, voice analysis, etc. The server analyzes the collected emotional data and determines the user's emotional state.

[1951] For example, if a user enters "I've been feeling stressed at work lately," the server will use its emotion analysis engine to determine the user's emotion as "stress." Based on this emotion data, the server will recommend the optimal generative AI model and prompts for the user. In this example, the server will recommend a "generative AI model that helps you relax."

[1952] Once the recommended generative AI models and prompts are made public, users can freely browse and search them. The user selects the prompt or generative AI model they need and clicks the "Purchase" button. The server receives the purchase request, checks its contents, and then provides the user with a screen for entering payment information. After the payment information is entered, the server receives payment through the payment system. Once the payment is complete, the server sends the user a notification that the purchase is complete.

[1953] The server then provides the user with the data for the generative AI model or prompt that has been purchased. Specifically, the user is sent a download link and API key, allowing them to immediately use the purchased data. Users can also customize the generative AI model or prompt they purchased to suit their own needs and re-register the customized version on the platform. The server receives the re-registered data, verifies its format and required items, stores it in the database, and publishes it again.

[1954] Furthermore, a revenue sharing system will calculate a revenue share based on the purchase price, which will be divided appropriately between the prompt creator and the platform operator and transferred to the prompt creator's registered bank account or electronic wallet.

[1955] As described above, this system analyzes the user's emotional state to recommend the optimal generative AI model and prompts, enabling efficient and satisfying transactions, while ensuring fair and appropriate revenue distribution.

[1956] For example, if a user inputs "I've been feeling stressed at work lately," the server will perform emotion analysis and recommend a "generative AI model that will help you relax." In this way, the user experience can be improved by providing the optimal prompts and generative AI models according to the user's emotional state.

[1957] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1958] Step 1:

[1959] Users register generated AI models and prompts on the platform.

[1960] Input: The user enters information such as the name, description, use case, and pricing of the generated AI model or prompt.

[1961] Data processing: The user enters the necessary information on a dedicated registration screen and clicks the "Submit" button.

[1962] Output: Generated AI model and prompt data are sent to the server.

[1963] Step 2:

[1964] The server receives the data and verifies that the format and required fields are correct.

[1965] Input: The generative AI model and prompt data sent in Step 1.

[1966] Data processing: Automated scripts are run to check for missing or incorrect data.

[1967] Output: Data that has been validated. If there are no problems with the format or required items, proceed to the next step.

[1968] Step 3:

[1969] The server stores the validated data in the database.

[1970] Input: Data for the generative AI model and prompts that have been validated in Step 2.

[1971] Data manipulation: Inserting data into the appropriate tables in the database.

[1972] Output: Generative AI models and prompts stored in a database.

[1973] Step 4:

[1974] Use a sentiment analysis engine to collect emotional data from user input and actions.

[1975] Input: Data such as user keyboard input, mouse actions, facial expression recognition, and voice analysis.

[1976] Data calculation: The sentiment analysis engine analyzes these data in real time to determine the user's emotional state.

[1977] Output: Determined user emotion data.

[1978] Step 5:

[1979] Based on the emotional data, the server recommends the most suitable generative AI model and prompts for the user.

[1980] Input: User emotion data determined in step 4.

[1981] Data computation: Search and filter relevant generative AI models and prompts based on emotion data.

[1982] Output: The generated AI model and prompts that are displayed to the user.

[1983] Step 6:

[1984] The user selects a recommended generative AI model or prompt and clicks the "Purchase" button.

[1985] Input: User selection and payment information.

[1986] Data processing: Send a purchase request to the server and enter payment information on the payment screen.

[1987] Output: Purchase request and payment information is sent to the server.

[1988] Step 7:

[1989] The server receives the purchase request and verifies its contents.

[1990] Input: Purchase request and payment information submitted in step 6.

[1991] Data processing: Receive payment through the payment system.

[1992] Output: A notification of payment completion is sent to the user.

[1993] Step 8:

[1994] Provide users with generative AI models and prompts upon purchase completion.

[1995] Input: Data from the generative AI model or prompt that you purchased.

[1996] Data processing: Generate and provide download links and API keys to users.

[1997] Output: A link or key that allows users to access the generated AI model and prompts.

[1998] Step 9:

[1999] Customize the generative AI models and prompts you purchase to fit your needs.

[2000] Input: Data from purchased generative AI models and prompts.

[2001] Data calculation: User adjusts programs and parameters.

[2002] Output: Customized generative AI models and prompts.

[2003] Step 10:

[2004] The user re-registers the customization.

[2005] Input: Data for customized generative AI models and prompts.

[2006] Data processing: Send data from the re-registration screen.

[2007] Output: Data re-registered on the server.

[2008] Step 11:

[2009] The server receives the re-registered data and re-verifies its format and required items.

[2010] Input: The generative AI model and prompt data retrained in step 10.

[2011] Data calculation: Re-verification of data format and required items.

[2012] Output: The validated data.

[2013] Step 12:

[2014] The server stores the verified data in the database and makes it public again.

[2015] Input: The data that has passed validation in step 11.

[2016] Data processing: Re-insert the data into the appropriate tables in the database and set it to public.

[2017] Output: The published customization stored in the database.

[2018] Step 13:

[2019] The revenue sharing system calculates and distributes the revenue share amount based on the purchase price.

[2020] Input: User purchase data and revenue sharing rules.

[2021] Data calculation: Calculation of revenue share.

[2022] Output: Revenue share remittance to prompt creators and platform operators.

[2023] 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.

[2024] 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.

[2025] 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.

[2026] 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.

[2027] 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.

[2028] 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.

[2029] 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).

[2030] 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.

[2031] 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."

[2032] 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.

[2033] 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).

[2034] 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.

[2035] 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 p...

Claims

1. A platform that aggregates generative AI models A means for storing registered prompts and generative AI models in a database; A means to publish aggregated prompts and generative AI models online; and means for receiving a purchase request from a user and receiving payment through a payment system; A means of providing the user with generative AI models and prompts after a purchase is completed; and A means of sharing the purchase revenue between the prompt creator and the platform operator; A system including:

2. A means for users to customize prompts and generative AI models and then re-register those customized versions on the platform. A means to store and publish the re-registered generative AI models and prompts in the database again, The system of claim 1 , comprising:

3. When users register prompts or generative AI models, a means to verify the format and required items of the data, and means for registering the verified data in a database and sending a notification of the completion of registration to the user; The system of claim 1 , comprising:

Images