system

Abstract

Provide a system. A method for users to create and upload prompts; a means for the server to receive the uploaded prompt and verify the prompt content; A means for the server to hash the prompt and store the result in a database; a means for the server to evaluate and assign a value to the prompt; a means for the server to publicly publish the valued prompts; A means for a user to select a published prompt and submit a request to use it; A means for the server to receive a usage request and check the usage fee, and a means for the user to pay the usage fee; a means for the server to verify the payment, release and provide an encrypted prompt; and a means for the server to return a portion of the usage fee obtained to the creator.

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] Recently, many prompts have been created to utilize generative models and artificial intelligence, but because these prompts are not properly valued, there is a problem of a lack of high-quality prompts in circulation. Furthermore, there is no established system for creators to receive appropriate compensation for using prompts, which leads to a decline in motivation. Furthermore, prompt management is insufficient, which raises security and fraud risks. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following system: A means for a user to create and upload prompts is provided. A server is provided to receive the uploaded prompts and verify the contents of the prompts. The server is then provided to hash the prompts and store the results in a database. The server is also provided to rate the prompts and assign values ​​to them. A means is provided to make the valued prompts publicly available, and a means is provided for a user to select a published prompt and submit a usage request. The server is also provided to receive the usage request and verify the usage fee, and a means is provided for the user to pay the usage fee. After verifying payment, the server is provided to release and provide the encrypted prompts. Finally, by providing a means to return a portion of the usage fee obtained to the creators, a system is realized that promotes the distribution of high-quality prompts and provides appropriate rewards to creators.

[0006] "User" means the entity that creates and consumes prompts and is an individual or legal entity that interacts with the system.

[0007] A "server" is a computer system that provides a set of functions such as receiving prompts, storing them, managing them, assessing their value, publishing them, processing usage requests, checking fees, releasing cryptocurrency, and returning profits.

[0008] A "prompt" is the input data or instructions that a generative model or artificial intelligence needs to generate a specific output.

[0009] "Hashing" is the process of taking a fixed length of data generated using a specific algorithm to convert the contents of the prompt into a unique identifier.

[0010] "Database" means a storage device on the system for efficiently managing and storing prompts and related information.

[0011] "Rating" is the process the server goes through to judge the quality of a prompt, which then determines its value.

[0012] "Value" is an economic valuation assigned to the prompt based on the evaluation.

[0013] "Publishing" is the act of the server making a valued prompt publicly available for operation, a process that allows it to be displayed in a list that users can select from.

[0014] A "use request" is a request that a user sends to the server to use a selected prompt.

[0015] A "usage fee" is the amount a user pays for using the prompt.

[0016] "Encryption" is the process of converting the contents of a prompt into a form that cannot be easily understood by others.

[0017] "Release" is the process of decrypting the prompt and providing the content to the user after payment is verified.

[0018] "Rebate" refers to returning a portion of the usage fee earned to the creator of the prompt. [Brief explanation of the drawings]

[0019] [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 illustrating 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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] The "Prompt Bank" system of this invention is a platform that values, manages, and distributes prompts created by users. This system consists of three main components: a server, terminals, and users.

[0041] System Overview

[0042] (User prompt registration)

[0043] The user creates a prompt and uploads it to the system. The prompt is uploaded by the user, who sets the input data for the prompt on the input screen. When the user uploads a new prompt to the system, the server receives the prompt.

[0044] (receive and acknowledge prompts)

[0045] The server receives the uploaded prompt and checks its content. Specifically, the server analyzes the prompt to ensure it is formatted and properly formatted, and performs format and content checks as necessary. Based on the results of this analysis, the server proceeds to the next step.

[0046] (prompt hashing and saving)

[0047] The server hashes the prompt content and stores the result in a database using an algorithm such as SHA-256 to generate a unique identifier for the prompt, which uniquely identifies the prompt within the database.

[0048] (Evaluating and Valuing Prompts)

[0049] The server evaluates the prompt and assigns a value to it. This evaluation is based on the judgment of machine learning models and evaluators, and an economic value is assigned according to the quality and usefulness of the prompt. For example, the server evaluates the prompt and assigns a value of 100 yen as a result.

[0050] (Public release of prompts)

[0051] The server publishes the valued prompts to the public, either as a web page or an API response that can be accessed by users. The prompts are displayed in an appropriate format upon publication, and users can choose the prompts they want to use.

[0052] (Using user prompts)

[0053] The user selects the prompt they want to use from the published prompts and sends a usage request from the terminal to the server. The terminal then sends the hash code of the selected prompt to the server and makes a usage request.

[0054] (Payment and confirmation of usage fees)

[0055] The server receives the usage request and checks the usage fee. The user pays the requested fee. Based on the analysis results, the server returns fee information to the user, who then completes the payment. Payment is made by credit card, electronic money, or other means, and the server confirms the payment.

[0056] (Release encrypted prompt)

[0057] Once the server confirms the payment, it releases the encrypted prompt and provides it to the user. At this time, the server decrypts the prompt and sends it to the user's device. Once this transmission is complete, the user can use the prompt they specified.

[0058] (Return of profits)

[0059] The server returns a portion of the usage fee to the prompt creator. This return is based on a revenue sharing algorithm, and the server reflects the return amount in the creator's account. For example, if the prompt usage fee is 100 yen, the server can return 50 yen to the creator.

[0060] Specific examples

[0061] As a specific example of use, user A creates a "prompt for generating cat images" and uploads it to the system. The server receives the prompt, hashes it, rates it, and publishes it with a value of 100 yen. User B selects the published prompt and wishes to use it, sending a usage request to the server. User B pays the 100 yen usage fee, and after the server confirms the payment, it releases the encrypted prompt and provides it to user B. Finally, the server returns 50 yen of the 100 yen obtained to user A.

[0062] In this way, the Prompt Bank system values ​​and distributes prompts created by users, thereby promoting the spread of high-quality prompts and providing appropriate compensation to their creators.

[0063] The processing flow will be explained below.

[0064] Step 1:

[0065] A user creates a prompt and uploads it to the system.

[0066] Specifically, the user enters the required data on the prompt input screen and presses the "upload" button.

[0067] Step 2:

[0068] The server receives the uploaded prompts from the user.

[0069] Specifically, the server receives the HTTP POST request and stores the prompt data in a temporary storage directory.

[0070] Step 3:

[0071] The server checks the uploaded prompt.

[0072] Specifically, the server checks the file format, analyzes some of the content, and verifies whether it is in the correct format.

[0073] Step 4:

[0074] The server hashes the prompt to generate a unique identifier.

[0075] Specifically, the hash value of the prompt is calculated using the SHA-256 algorithm and the result is obtained.

[0076] Step 5:

[0077] The server stores the hashed prompts in a database.

[0078] Specifically, relevant information such as the prompt's hash value, original content, and creation time is recorded in a database.

[0079] Step 6:

[0080] The server evaluates the prompt and assigns a value.

[0081] Specifically, the quality is evaluated using machine learning models and human evaluators, and an appropriate monetary value (e.g., 100 yen) is set.

[0082] Step 7:

[0083] The server lists the valued prompts and makes them publicly available.

[0084] Specifically, a prompt list is generated as a public HTML page or API response, making it accessible to users.

[0085] Step 8:

[0086] The user selects the prompt they want to use from the publicly available prompts.

[0087] Specifically, the user selects a specific prompt (e.g., hash code abc123) from a list of published prompts.

[0088] Step 9:

[0089] The user's terminal transmits the hash code of the selected prompt to the server and makes a usage request.

[0090] As a specific example, an HTTP POST request is used to send a hash code of the prompt to communicate intent to the server.

[0091] Step 10:

[0092] The server receives the usage request and checks the usage fee.

[0093] Specifically, the value information of the prompt is obtained from the database, and the usage fee (e.g., 100 yen) is extracted and communicated to the user.

[0094] Step 11:

[0095] The user pays a usage fee.

[0096] Specifically, the payment procedure is completed using a payment method such as a credit card or electronic money.

[0097] Step 12:

[0098] The server verifies the user's payment.

[0099] Specifically, it receives a response from the payment service and records in a database whether the payment was successful.

[0100] Step 13:

[0101] The server releases the encrypted prompt and provides it to the user.

[0102] Specifically, the prompt is decrypted and the prompt content is sent to the user's terminal.

[0103] Step 14:

[0104] The server returns a portion of the usage fee earned to the creator of the prompt.

[0105] Specifically, the amount is calculated based on a revenue distribution algorithm and reflected in the creator's account.

[0106] Example 1

[0107] 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."

[0108] There is a lack of a platform for properly evaluating, managing, and distributing prompts for generative AI models. It is necessary to guarantee the quality of user-created prompts and assign economic value to them, thereby providing appropriate rewards to prompt creators and promoting the spread of high-quality prompts. Furthermore, there is no system for efficiently publishing prompts and making them available to other users.

[0109] 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.

[0110] In this invention, the server includes: a means for a user to create and upload prompts for a generative AI model; a means for the server to receive the uploaded prompts and verify their format and content; a means for the server to hash the prompts using the SHA-256 algorithm and store the results in a database; a means for the server to evaluate the prompts using a machine learning model or an evaluator and assign values ​​to them; a means for the server to publicly publish the valued prompts via a webpage or API response; a means for a user to select a published prompt and send a usage request; a means for receiving a usage request and confirming the proposed usage fee; a means for a user to pay the usage fee by credit card or electronic money; a means for confirming the payment, releasing the encrypted prompt, and providing it to the user's device; and a means for returning a portion of the obtained usage fee to the prompt creator based on a revenue sharing algorithm. This allows for efficient management of the entire process from prompt creation to evaluation, publication, usage, and reward distribution, enabling the spread of high-quality prompts and appropriate rewards to creators.

[0111] "User" refers to a person or organization that creates prompts for generative AI models and registers and uses them in the system.

[0112] "Prompts for a Generative AI Model" refers to instructions or datasets created to be input to a Generative AI Model.

[0113] "Uploading a prompt" refers to the act of sending a prompt created by a user to the server and registering it.

[0114] "Server" refers to a computer system that receives, validates, hashes, evaluates, stores, and publishes prompts, processes redemption requests, verifies fees, releases prompts, and redeems them.

[0115] The "SHA-256 algorithm" is a hash function used to uniquely identify the contents of a prompt.

[0116] "Hashing" refers to the process of converting the contents of the prompt into a fixed-length string and generating a unique identifier.

[0117] A "machine learning model" is a type of artificial intelligence used to evaluate prompts.

[0118] "Evaluator" refers to an entity responsible for judging the quality of prompts using machine learning models or manually.

[0119] "Assigning a value" refers to the process of determining an economic value for a prompt based on the results of the prompt evaluation.

[0120] "Web Page" refers to the interface that a user accesses to review prompts, make selections, and make utilization requests.

[0121] "API response" refers to the response data returned by a server through an application program interface.

[0122] "Usage Request" refers to a request sent by a user to use a published prompt.

[0123] "Usage Fee" refers to the amount paid by a user to use a prompt.

[0124] "Credit cards and electronic money" refers to electronic payment methods used by users to pay usage fees.

[0125] "Encryption" refers to the process of converting the contents of a prompt into an unreadable form for security purposes.

[0126] "Releasing" refers to decrypting the encrypted prompt and making it available for use after the user pays the usage fee.

[0127] "Revenue Share Algorithm" refers to the calculation method used to appropriately return earned royalties to prompt creators.

[0128] This invention relates to a system called "Prompt Bank" for valuing, managing, and distributing prompts for generative AI models. This system is mainly composed of three elements: a server, a terminal, and a user.

[0129] System components and specific operations

[0130] Prompt registration for users

[0131] A user creates a prompt for a generative AI model and enters the prompt content into the device's input screen. The user then presses the "Register" button to send the prompt to the server. This operation is the first step for the user to widely publish their prompt and earn revenue by having other users use it. A specific example is when a user creates a "prompt for drawing a cat."

[0132] Receiving and acknowledging prompts

[0133] The server receives the prompt sent by the user and checks its format and content. During this check, the server analyzes the prompt to determine whether it is in the correct format and whether the content is inappropriate. This analysis process can be performed using commonly known software tools or custom-developed scripts.

[0134] Hashing and saving prompts

[0135] The server hashes the prompt using the SHA-256 algorithm. This hashing process generates a unique identifier. The generated hash value is stored in a database, ensuring the uniqueness of the prompt. A server computer is used as the hardware for high-speed calculations.

[0136] Evaluating and valuing prompts

[0137] The server evaluates the prompt using a machine learning model or evaluators. This evaluation determines the quality of the prompt and assigns an economic value to it. For example, a text analysis algorithm or a natural language processing model is used as the evaluation model. Based on the evaluation result of the prompt, a value of, for example, 100 yen is assigned.

[0138] Publicly available prompts

[0139] The server exposes the valued prompts to the public through web pages or API responses, where they are listed and categorized for easy user access, and a search function is provided to help users efficiently find the prompts they need.

[0140] User prompt usage request

[0141] The user selects a prompt from the published prompts and sends a usage request to the server from the device, requesting a specific prompt using the prompt's hash code.

[0142] Payment and confirmation of usage fees

[0143] The server receives the usage request and checks the proposed usage fee. The user pays the specified usage fee using a credit card or electronic money. The server verifies and confirms the completion of the payment.

[0144] Releasing the encrypted prompt

[0145] Once payment is confirmed, the server releases the encrypted prompts and provides them to the user's device, where they are decrypted and the user can use the purchased prompts.

[0146] Return of profits

[0147] The server returns a portion of the usage fee to the prompt creator based on a revenue sharing algorithm. For example, if the usage fee is 100 yen, 50 yen of that will be returned to the creator. This return will serve as an incentive for prompt creators to continue providing high-quality prompts.

[0148] Specific examples

[0149] For example, User A creates a "prompt to generate a picture of a cat" and uploads it to the "Prompt Bank" system. The server receives the prompt, hashes it using the SHA-256 algorithm, assigns a value of 100 yen, and publishes it. User B selects that prompt, sends a usage request, and makes payment. After the server confirms the payment, it releases the prompt and provides it to User B, and User A receives 50 yen in revenue. This process allows users to receive compensation for the valuable prompts they send out.

[0150] This allows the Prompt Bank system to seamlessly implement the entire process of registering, evaluating, publishing, using, and giving back prompts, efficiently promoting the dissemination of prompts and providing fair rewards to creators.

[0151] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0152] Processing flow and specific explanation

[0153] Step 1:

[0154] User creates and uploads prompts

[0155] Input: Prompt "Prompt to generate a picture of a cat"

[0156] Output: Sending a prompt to the server

[0157] Specific actions

[0158] The user creates a prompt for the generative AI model and enters it into the device's input screen. When the user presses the "Register" button, the prompt is sent to the server.

[0159] Step 2:

[0160] The server receives the prompt and confirms it.

[0161] Input: User uploaded prompt text

[0162] Output: Check the format and content of the prompt statement

[0163] Specific actions

[0164] The server analyzes and checks the format (e.g., text format) and content (e.g., whether it contains useful information) of the received prompt. The server uses a specific algorithm to evaluate the appropriateness of the content and filter out inappropriate content.

[0165] Step 3:

[0166] The server hashes and stores the prompt

[0167] Input: Confirmed prompt text

[0168] Output: Hash value of the prompt statement and the record stored in the database

[0169] Specific actions

[0170] The server hashes the prompt using the SHA-256 algorithm to generate a unique identifier, and stores the hash value and the original prompt in an internal database.

[0171] Step 4:

[0172] Server prompt evaluation and rating

[0173] Input: hashed prompt text

[0174] Output: Valued prompt sentences and their evaluation results

[0175] Specific actions

[0176] The server evaluates the prompt using machine learning models and evaluators. Based on the evaluation results, the server assigns an economic value (e.g., 100 yen) to the prompt. This evaluation is performed using text analysis and natural language processing models.

[0177] Step 5:

[0178] Server prompt public

[0179] Input: Valued prompt sentence

[0180] Output: List of published prompt statements

[0181] Specific actions

[0182] The server exposes the valued prompts as publicly accessible web pages or API responses, including appropriate formatting and search functionality.

[0183] Step 6:

[0184] The user selects the prompt and submits a request for use.

[0185] Input:Select the published prompt sentence

[0186] Output: Usage request to the server

[0187] Specific actions

[0188] The user selects a prompt from the list of available prompts and sends a usage request to the server from their device. The request includes the hash code of the prompt.

[0189] Step 7:

[0190] The server checks the usage fee

[0191] Input: User request

[0192] Output: Usage fee and payment confirmation

[0193] Specific actions

[0194] The server receives the usage request and checks the proposed usage fee. The user pays using a credit card or electronic money, and the server verifies and confirms the payment.

[0195] Step 8:

[0196] Server releases encrypted prompt

[0197] Input: Payment confirmed request

[0198] Output: Decoded prompt sentence

[0199] Specific actions

[0200] Once the payment is confirmed, the server decrypts the original encrypted prompt text and provides it to the user's terminal, where the user can use the specified prompt text.

[0201] Step 9:

[0202] Server returns profits

[0203] Input: Usage Fee Revenue

[0204] Output: Reward amount to prompt creator

[0205] Specific actions

[0206] The server will then return a portion of the fee to the prompt creator based on a revenue sharing algorithm. For example, if the fee is 100 yen, 50 yen will be returned to the creator. The refund amount will be reflected in the creator's account.

[0207] (Application example 1)

[0208] 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."

[0209] In conventional prompt management systems, the value of prompts created by users is evaluated centrally, which hinders the smooth distribution of prompts among users. Furthermore, the quality and usefulness of prompts are not adequately evaluated, which means that high-quality prompts are sometimes not properly evaluated. Furthermore, it is difficult for users to efficiently find prompts, which hinders the promotion of prompt usage.

[0210] 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.

[0211] In this invention, the server includes means for rating and assigning values ​​to prompts based on rating information from other users, means for prioritizing prompts based on the rating information and recommending them to other users, and means for analyzing the content of prompts and checking whether they are in an appropriate format. This facilitates the smooth distribution of prompts among users, ensures that high-quality prompts are appropriately rated, and enables users to efficiently find the prompts they need.

[0212] A "User" is an individual or organization that uses the system to create, upload, rate, select, pay for, or otherwise interact with prompts.

[0213] A "prompt" is text data that includes input instructions, guidelines, scripts, commands, etc. for a generative AI model.

[0214] "Server" means a computer system that receives, analyzes, hashes, stores, evaluates, and publishes prompts, and releases and provides encrypted prompts.

[0215] "Hashing" is the process of converting the contents of the prompt into a unique identifier using an algorithm such as SHA-256.

[0216] The "database" is a collection of information for managing hashed prompts, their evaluation information, and usage history.

[0217] "Valuing" is the process of calculating and assigning an economic value to a prompt based on its quality and usefulness.

[0218] "Publicly available" means making the valued prompt accessible to multiple users.

[0219] A "use request" is a request that a user sends to a server to use a particular prompt.

[0220] A "usage fee" is a fee paid by a user to use a published prompt.

[0221] "Rating information" is information about ratings and feedback given by other users to a particular prompt.

[0222] "Priority" refers to the display order when recommending a prompt to other users based on the prompt's evaluation information.

[0223] "Recommending" means preferentially displaying a particular prompt to other users and promoting its use.

[0224] The system for implementing this invention allows users to create and upload prompts, and manages their value assessment, publication, use, payment, and redemption. The main components of the system are a user interface for uploading prompts, a server, and a user interface for using prompts.

[0225] 1. Prompt registration of users

[0226] Users create prompts and upload them to the system from their smartphones or other devices. The uploaded prompts are received by the server. Specifically, users enter text data, such as a "prompt to generate a cat image," and send it to the system.

[0227] 2. Receiving and confirming the prompt on the server

[0228] The server checks the content of the received prompt and parses it to ensure it is in the correct format. Improperly formatted prompts are filtered out at this stage.

[0229] 3. Hashing and storing prompts

[0230] The server hashes the prompt using the SHA-256 algorithm and stores the result in a database, which uniquely identifies the prompt.

[0231] 4. Evaluating and Valuing Prompts

[0232] The server determines the value of prompts based on the rating information received from other users, and also prioritizes and recommends prompts to other users.

[0233] 5. Publicly displaying prompts

[0234] The valued prompts are then published as user-accessible web pages or API responses, allowing users to easily view and select from them.

[0235] 6. User Prompts

[0236] The user selects a published prompt and sends a request to the server to use it, along with the hash code of the prompt they want to use.

[0237] 7. Payment and Confirmation of Usage Fees

[0238] The server receives the usage request and checks the usage fee. The user pays using a credit card or electronic money. The server checks the payment and updates the information.

[0239] 8. Releasing the Encrypted Prompt

[0240] After the server verifies the payment, it releases and provides the encrypted prompt to the user, allowing them to use the prompt they specified.

[0241] 9. Return of profits

[0242] The server returns a portion of the usage fee to the prompt creator, the user, so that the user can receive appropriate compensation for the high-quality prompts they have created.

[0243] As a concrete example, consider a "prompt for generating cat images." A user uploads this prompt to the system, and other users rate it, assigning it a value. After that, another user selects a published prompt, confirms its value, and pays a fee to use it. After the server confirms the payment, it releases the encrypted prompt and provides it to the user. This entire process is performed automatically by the system.

[0244] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0245] Step 1:

[0246] A user creates a prompt and uploads it to the system using a terminal. To do this, the user enters text data, such as "a prompt to generate a cat image," and clicks the upload button. The input is the text data, and the output is the prompt sent to the server.

[0247] Step 2:

[0248] The server receives the uploaded prompt and checks its content. Specifically, the server parses the prompt to see if it is valid and checks its format and content. The input is the uploaded prompt, and the output is the parsing result (valid or invalid).

[0249] Step 3:

[0250] The server hashes the prompt using the SHA-256 algorithm and stores the result in a database. The input is the prompt text data, and the output is the hashed data.

[0251] Step 4:

[0252] The server evaluates the value of the prompt based on the rating information received from other users. This evaluation is performed using a machine learning model, which assigns an economic value to the prompt. The input is the rating information and the prompt, and the output is the valued prompt.

[0253] Step 5:

[0254] The server publishes the valued prompts to the public, where they are displayed as user-accessible web pages or API responses. The input is the valued prompt, and the output is the published prompt.

[0255] Step 6:

[0256] The user selects a published prompt and sends a usage request from the terminal to the server. The input is the published prompt and its hash code, and the output is the usage request sent to the server.

[0257] Step 7:

[0258] The server receives the usage request and checks the usage fee. At this time, the server retrieves the fee information from the database and presents it to the user. The input is the usage request, and the output is the fee information.

[0259] Step 8:

[0260] The user pays the displayed usage fee. This payment is made by means of a credit card, electronic money, etc. The input is fee information and payment information, and the output is confirmation of payment completion.

[0261] Step 9:

[0262] After the server confirms the payment, it releases the encrypted prompt and provides it to the user. Specifically, the server decrypts the prompt and sends it to the user's device. The input is the payment confirmation and the encrypted prompt, and the output is the decrypted prompt.

[0263] Step 10:

[0264] The server returns a portion of the earned usage fees to the prompt creator. The server calculates the amount of the return based on a revenue sharing algorithm and reflects it in the creator's account. The input is the usage fee and creator information, and the output is a reflection of the return amount.

[0265] 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.

[0266] The "Prompt Bank" system of this invention is a platform for assigning value to, managing, and distributing prompts created by users. The system includes the main components of a server, terminals, and users, and by combining it with an emotion engine, it has the ability to evaluate prompts and make recommendations based on the user's emotions.

[0267] System Overview

[0268] (User prompt registration)

[0269] The user creates a prompt and uploads it to the system. The prompt is uploaded from the user's terminal. At this time, the emotion engine recognizes the user's emotional state and sends data including the user's current emotion to the server as prompt information.

[0270] (receive and acknowledge prompts)

[0271] The server receives the prompt uploaded by the user, validates it, including checking that it is in the correct format, hashes it, generates a unique identifier, and stores it in a database.

[0272] (Evaluating and Valuing Prompts)

[0273] The server evaluates prompts by using an emotion engine to modify their value based on the user's emotion. Specifically, the emotion engine analyzes the user's emotion data and evaluates the quality of the prompt according to the emotion. Based on this evaluation result, the server assigns an economic value (e.g., 100 yen) to the prompt.

[0274] (Public release of prompts)

[0275] The server lists the valued prompts and makes them publicly available, allowing users to select from the list.

[0276] (Using user prompts and emotion recognition)

[0277] The user selects a prompt from the published prompts and sends a request to use it from the device to the server. The device then sends the hash code of the selected prompt along with the latest emotion data recognized by the emotion engine to the server.

[0278] (Payment and confirmation of usage fees)

[0279] The server receives the usage request and checks the usage fee. It analyzes the user's level of interest based on emotional data from the emotion engine and fine-tunes the fee if necessary. The user pays the proposed usage fee and the payment is completed. After the server confirms the payment, it releases an encrypted prompt and sends it to the user's device.

[0280] (Recommendation based on emotional data)

[0281] The emotion engine continuously collects user emotional data and stores it in a database. The server analyzes this data to recommend personalized prompts based on the user's interests and emotions. For example, if a user is feeling stressed, the server can recommend prompts with a relaxing effect.

[0282] (Return of profits)

[0283] The server returns a portion of the obtained usage fee to the creator of the prompt. The amount of the refund based on the usage fee is also recorded in the database using the user's usage emotion data generated by the emotion engine.

[0284] Specific examples

[0285] As a concrete example, user A creates a "prompt for generating a cat image" and uploads it to the system. The emotion engine recognizes the user's emotion at the time of uploading as "excitement," and this is added to the prompt information. The server receives the prompt, evaluates its quality, and assigns a value of 100 yen, taking the emotion information into consideration. When this prompt is made public and user B wishes to use it and sends a usage request to the server, the emotion engine recognizes the user's current emotion as "excitement." The server presents a usage fee of 100 yen, and user B pays. After confirming the payment, the server releases the encrypted prompt and sends it to user B's device. Finally, the server returns 50 yen of the 100 yen revenue to user A, the prompt creator.

[0286] In this way, the "Prompt Bank" system, which combines an emotion engine, utilizes users' emotional data to value and recommend prompts, thereby promoting the spread of high-quality prompts and providing appropriate rewards to their creators.

[0287] The processing flow will be explained below.

[0288] Step 1:

[0289] A user creates a prompt and uploads it to the system.

[0290] Specifically, the user inputs the required prompt content on the device's input screen, and the emotion engine recognizes the user's emotional state in real time. When the user presses the "upload" button, the prompt data and emotion data are sent to the server.

[0291] Step 2:

[0292] The server receives the uploaded prompts from the user.

[0293] The server receives the HTTP POST request and stores the prompt data and emotion data in a temporary directory.

[0294] Step 3:

[0295] The server checks the uploaded prompt.

[0296] Specifically, the server checks the format of the prompt, parses the content for correctness, and notifies the user of formatting errors or incomplete content if necessary.

[0297] Step 4:

[0298] The server hashes the prompt to generate a unique identifier.

[0299] The server generates a hash code of the prompt using the SHA-256 algorithm and retrieves the result.

[0300] Step 5:

[0301] The server stores the hashed prompts in a database.

[0302] The server records the prompt's hash value, original content, emotion data, and creation time in a database.

[0303] Step 6:

[0304] The server evaluates the prompt and assigns a value.

[0305] The server uses an emotion engine to analyze the user's emotion data, evaluates the quality of the prompt based on the results, and assigns an economic value to the prompt (e.g., 100 yen).

[0306] Step 7:

[0307] The server publishes the valued prompts to the public.

[0308] Specifically, the server generates a list of valued prompts as an HTML page or API response and makes it publicly available.

[0309] Step 8:

[0310] The user selects the prompt they want to use from the publicly available prompts.

[0311] The user selects a specific prompt (e.g., hash code abc123) from the list of published prompts and presses the "Use" button.

[0312] Step 9:

[0313] The user's terminal transmits the hash code and emotion data of the selected prompt to the server.

[0314] Specifically, the latest emotion data is sent to the server along with the hash code of the prompt using an HTTP POST request from the user's device.

[0315] Step 10:

[0316] The server receives the usage request and checks the usage fee.

[0317] The server retrieves the value information of the prompt from the database, extracts the usage fee (e.g., 100 yen), and presents it to the user.

[0318] Step 11:

[0319] The user pays a usage fee.

[0320] Specifically, the user enters their credit card information to complete the payment process, and the payment information is encrypted and sent to the server.

[0321] Step 12:

[0322] The server verifies the user's payment.

[0323] The server receives the response from the payment service, verifies whether the payment was successful, and records the payment information in a database.

[0324] Step 13:

[0325] The server releases the encrypted prompt and provides it to the user.

[0326] The server decodes the prompt and sends it to the user's device, possibly along with associated emotional data.

[0327] Step 14:

[0328] The server returns a portion of the usage fee earned to the creator.

[0329] The server will then credit a portion of the revenue earned based on a revenue sharing algorithm to the creator's account and record the amount in a database. For example, 50 yen out of a 100 yen usage fee will be returned to the creator.

[0330] Step 15:

[0331] The server recommends prompts based on the emotion data.

[0332] Specifically, the server analyzes the user's emotional data collected from the emotion engine and recommends personalized prompts to the user. For example, if the user is feeling stressed, it will recommend prompts that have a relaxing effect.

[0333] Example 2

[0334] 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."

[0335] Conventional prompt management systems evaluate and value prompts without considering the user's emotions, which makes it difficult to value and recommend prompts that are in line with the user's needs and emotions. It is also difficult to provide appropriate rewards to prompt creators.

[0336] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0337] In this invention, the server includes means for acquiring user emotion data using an emotion engine and adding it to prompt information, means for the server to evaluate prompts and assign values ​​based on the emotion data, and means for the emotion engine to collect, save, and analyze user emotion data to make personalized recommendations. This makes it possible to evaluate and assign values ​​to prompts based on user emotions, thereby enabling the spread of high-quality prompts and the provision of appropriate rewards to their creators.

[0338] "User" means an entity that uses the system to create, upload, or use prompts.

[0339] A "prompt" refers to text data that expresses instructions or requests to a generative AI model.

[0340] "Terminal" refers to a digital device used by a user, such as a computer, smartphone, or tablet.

[0341] "Server" refers to a central digital computer system that receives, evaluates, hashs, stores, publishes, etc., prompts.

[0342] An "emotion engine" refers to software or hardware that recognizes a user's emotional state and processes it as data.

[0343] "Hashing" refers to a cryptographic technique for converting a prompt into a unique identifier.

[0344] "Database" means a digital collection of information for managing and storing prompts and related data.

[0345] "Assigning a value" refers to the process of assigning an economic value to a prompt.

[0346] "Public" refers to making a valued prompt available for other users to view.

[0347] "Usage Request" refers to a request sent by a user to use a published prompt.

[0348] "Usage Fee" refers to the cost incurred when using Prompt.

[0349] "Rebate" refers to returning a portion of the usage fee to the prompt creator as compensation.

[0350] "Personalized recommendations" refers to suggesting prompts that are individually optimized based on the user's emotional data.

[0351] A "machine learning model" refers to an algorithmic method that learns from data and evaluates prompts based on the analysis results.

[0352] The "Prompt Bank" system of this invention is a platform for assigning value to, managing, and distributing prompts created by users. In addition to the main components of the system, which are a server, terminals, and users, it also combines an emotion engine to enable prompt evaluation and recommendations based on the user's emotions.

[0353] Hardware and software configuration

[0354] server

[0355] The server functions as a central processing unit and performs the following processes:

[0356] Receiving and hashing prompts

[0357] Save prompts to the database

[0358] Data analysis from the emotion engine

[0359] Valuing and Evaluating Prompts

[0360] Processing public availability and usage requests

[0361] Checking usage fees and processing payments

[0362] Fee rebates and management

[0363] Terminal

[0364] The devices used by users include computers, smartphones, tablets, etc. These devices perform the following functions:

[0365] Prompt creation and upload

[0366] Select a prompt and submit a request

[0367] Collecting and transmitting emotional data

[0368] Emotion Engine

[0369] The emotion engine has the following functions:

[0370] Recognizing the user's emotional state in real time

[0371] Collecting user emotion data

[0372] Adding emotional data to prompt information

[0373] Recommending prompts based on emotion data

[0374] Data processing and calculation

[0375] When a user creates a prompt and uploads it to the system from their device, the emotion engine collects the user's emotional state and sends it to the server as prompt information. The server receives the prompt, checks its content, and checks whether it is in the correct format. The server then hashes the prompt to generate a unique identifier and stores it in a database.

[0376] The server analyzes the data from the emotion engine and evaluates the quality of the prompts. Based on the evaluation results, the server assigns economic values ​​to the prompts. The server then makes the valued prompts public, allowing users to select prompts.

[0377] When a user requests to use a published prompt, the device sends a usage request including emotion data to the server. The server receives the usage request, checks and adjusts the usage fee based on the emotion data, and completes the payment once the user pays the fee. After the server confirms the payment, it releases the encrypted prompt and sends it to the device.

[0378] The emotion engine continuously collects user emotion data, and the server analyzes the data to recommend personalized prompts.

[0379] Specific examples

[0380] For example, user A creates a "prompt for generating a cat image" and uploads it to the system. The emotion at the time of uploading is recognized as "excitement," and this is added to the prompt information. The server receives the prompt, evaluates its quality, and assigns a value of 100 yen, taking into account the emotional information. This prompt is made public, and user B wants to use it. When a usage request is sent to the server, the emotion engine recognizes the user's current emotion as "excitement." The server presents a usage fee of 100 yen, and user B pays. After confirming the payment, the server releases the encrypted prompt and sends it to user B's device. Finally, the server returns 50 yen of the 100 yen revenue to user A.

[0381] By combining this system with an emotion engine, it is possible to value and recommend prompts based on the user's emotions, thereby promoting the spread of high-quality prompts and providing appropriate rewards to their creators.

[0382] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0383] Step 1: User creates and uploads prompt

[0384] The user opens the prompt creation screen on their device and enters a prompt for the generative AI model. When the user presses the upload button, the device sends the prompt to the server. At this time, the emotion engine recognizes the user's emotional state in real time and sends the emotional data along with it. The input is the prompt and emotional data, and the output is uploaded to the server.

[0385] Step 2: Receive and confirm the prompt

[0386] The server receives prompts uploaded by users. At this time, it checks whether the prompts are in the correct format. Specifically, it checks the text length of the prompt and whether it contains specific keywords. The input is the uploaded prompt and emotion data, and the output is the prompt format check result.

[0387] Step 3: Hash and save the prompt

[0388] The server hashes the prompt sentence and generates a unique identifier. The server then stores the prompt sentence, emotion data, and unique identifier in a database. The input is the confirmed prompt sentence and emotion data, and the output is storage in the database.

[0389] Step 4: Evaluate and value the prompt

[0390] The server uses an emotion engine to analyze the user's emotional data. Based on the results of this analysis, the server evaluates the quality of the prompt and assigns an economic value (e.g., 100 yen). The input is the emotional data and the prompt, and the output is the assigned value.

[0391] Step 5: Make the prompt public

[0392] The server compiles a list of valued prompts and makes it publicly available for users to view. The input is the valued prompt text, and the output is the published list of prompts.

[0393] Step 6: User requests prompt usage

[0394] The user browses a list of publicly available prompts on their device and selects the prompt they want to use. Then, they send a usage request from their device to the server. At this time, the emotion engine recognizes the user's latest emotion data and sends it along with the request to the server. The input is the usage request and emotion data, and the output is the request sent to the server.

[0395] Step 7: Check and settle usage fees

[0396] The server receives the usage request and analyzes the emotional data to assess the user's interest level. Based on this, it checks and possibly fine-tunes the usage fee. The user pays the fee, and the server confirms the payment. The input is the usage request and emotional data, and the output is the adjusted usage fee and its payment confirmation.

[0397] Step 8: Sending the Encrypted Prompt

[0398] After the server confirms the payment, it releases the encrypted prompt and sends it to the user's terminal. The input is the payment confirmation and the prompt text, and the output is the prompt sent to the terminal.

[0399] Step 9: Recommendation based on emotion data

[0400] The emotion engine continuously collects user emotion data, and the server analyzes the data to generate personalized recommendations. The input is the collected emotion data, and the output is personalized prompt recommendations.

[0401] Step 10: Returning profits

[0402] The server returns a portion of the revenue based on the prompt usage by the user to the prompt creator. The server also references the emotion data collected by the emotion engine to calculate the amount of return. The input is the usage fee and emotion data, and the output is the calculation and reflection of the return amount.

[0403] (Application example 2)

[0404] 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."

[0405] Conventional prompt management systems do not evaluate or recommend prompts based on the user's emotions, making it difficult to accurately evaluate the quality of prompts or to provide customized recommendations for individual users. Furthermore, it is difficult to provide content that matches the user's current emotional state, resulting in a decrease in user satisfaction. The present invention aims to solve these problems by enabling prompt evaluation and recommendation based on the user's emotions and providing content in accordance with emotional data.

[0406] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0407] In this invention, the server includes means for a user to create and upload prompts, means for the server to receive the uploaded prompts and check the contents of the prompts, means for the server to hash the prompts and store the hashed results in a database, means for the server to rate and assign values ​​to the prompts, means for the server to publicly publish the valued prompts, means for a user to select a published prompt and send a usage request, means for the server to receive the usage request and check a usage fee, means for the user to pay the usage fee, means for the server to confirm the payment and release and provide the encrypted prompts, and means for the server to return a portion of the usage fee to the creator, as well as means for rating and recommending prompts based on the user's emotions using an emotion engine, and means for recommending content according to the user's emotion data. This not only enables proper evaluation of the quality of prompts and recommendation of customized prompts to individual users, but also makes it possible to provide appropriate content according to the user's current emotional state.

[0408] A "prompt" is a statement written in the form of an instruction, question, or command given to a generative AI model.

[0409] "Uploading" is the act of a user sending data or files from their device to a server.

[0410] A "server" is a computer system that provides services to other computers (clients) on a network.

[0411] "Hashing" is a cryptographic process that converts original data into a fixed-length string of characters that can be used as a unique identifier.

[0412] A "database" is a collection of structured data that allows for efficient management and retrieval of large amounts of data.

[0413] An "emotion engine" is a software technology for analyzing a user's emotional state and collecting and utilizing that data.

[0414] "Valuing" is the act of assigning economic value or valuation to specific data or items.

[0415] "Publishing" means making certain data or information accessible to other users within the system.

[0416] A "use request" is a request that a user sends to the effect that he or she wishes to use a published prompt or service.

[0417] "Usage Fee" means money paid for the use of a particular service or item.

[0418] "Encryption" is a technology that codes data using a specific algorithm to protect it from easy access by third parties.

[0419] "Return" is the act of giving back a portion of the revenue or profits earned to a specific cause or person.

[0420] "Emotional Data" means information about the user's emotional state that is analyzed and collected by the Emotion Engine.

[0421] "Recommendation" is the act of a system suggesting optimal content or services based on a user's behavior and emotions.

[0422] "Content" refers to digital data and information such as music, video, text, and images provided through systems and services.

[0423] This invention relates to a prompt bank system incorporating an emotion engine. Specifically, it provides a method for uploading prompts created by users and analyzing and evaluating them using the emotion engine. The server assigns an appropriate value based on the prompt evaluation results and publishes them. Furthermore, the system provides recommended content based on the user's latest emotion data.

[0424] Hardware and Software Configuration

[0425] 1. The Server is the central processing unit for managing, evaluating, storing, and publishing prompts. It includes hashing technology, database management systems, and machine learning models (such as TENSORFLOW®).

[0426] 2. An emotion engine is a software technology that analyzes a user's emotional data, recognizes their emotional state, and generates corresponding data. A typical emotion analysis module is the sentiment_analysis library.

[0427] 3. User terminals are devices used to create, upload, view, and process payments for prompts. These include smartphones, tablets, and PCs.

[0428] 4. The payment processing module is a system that allows users to make payments and uses the APIs of Stripe and PayPal.

[0429] System details

[0430] 1. Create and upload a prompt:

[0431] Users create prompts and upload them to the system from their own devices. For example, if a user creates a prompt called "Relaxing music for stress relief," the system will recognize the user's current emotional state as "Relaxed" using the emotion engine.

[0432] 2. Receiving and Evaluating Prompts:

[0433] The server receives the uploaded prompts, hashes them, and stores them in a database. It then uses an emotion engine to analyze the user's emotional data and evaluate the quality of the prompts. Based on the evaluation results, economic values ​​are assigned to the prompts.

[0434] 3. Publishing and Recommending Prompts:

[0435] The server publishes the valued prompts to the public. Other users can browse the published prompts and select the prompts they want to use. The emotion engine then recommends the most appropriate prompts to the user based on the latest emotional data analyzed.

[0436] 4. Payment Processing and Prompts:

[0437] The user selects a published prompt and sends a usage request to the server. The server checks the usage fee, and the user pays. Once the payment is confirmed, the server releases the encrypted prompt and sends it to the user's device.

[0438] 5. Return of profits:

[0439] The server returns a portion of the usage fee to the prompt creator. Using usage emotion data from the emotion engine, the server accurately calculates the monetary amount of the return and records it in a database.

[0440] Example prompt

[0441] For example, if User A wants to recommend "relaxing music to relieve stress," he or she can create a prompt like this:

[0442] "Recommend relaxing music for stress relief."

[0443] This system improves the user experience by enabling the user to value prompts based on their emotional state and recommend content that is best suited to each individual user.

[0444] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0445] Step 1:

[0446] The user creates a prompt and uploads it from the device to the server. The input includes the prompt text "Please recommend some relaxing music to relieve stress." and the user's current emotional data. The device creates the prompt, recognizes the user's emotional state using an emotion engine, and sends the data including the prompt to the server. The server then receives this data.

[0447] Step 2:

[0448] The server verifies the received prompt, hashes it, and stores it in a database. The input includes the uploaded prompt data. The server verifies the prompt content, checks that it is in the correct format, and then uses hashing techniques to generate a unique identifier. The server then stores the hashed prompt in a database. The output is the hashed data.

[0449] Step 3:

[0450] The server evaluates the prompt content using an emotion engine and assigns a value. The input includes the prompt content and the user's emotion data. The server uses the emotion engine to analyze the user's emotion data and evaluates the quality of the prompt based on this. Based on the evaluation result, an economic value is assigned to the prompt. For example, a value of 100 yen is assigned. The output is the evaluation result and the prompt with the assigned value.

[0451] Step 4:

[0452] The server publishes valued prompts to the public. The input includes the valued prompt data. The server publishes the prompts to the public in a list format that can be accessed by other users. The output is a list of published prompts.

[0453] Step 5:

[0454] The user selects a published prompt and sends a usage request from the device to the server. The input includes a list of published prompts and the user's selection. The user browses the published prompts on the device and selects the prompt they want to use. The latest emotion data is also sent along with the usage request. The output is the selected prompt and the associated emotion data.

[0455] Step 6:

[0456] The server receives the usage request and checks the usage fee. The input includes the user's usage request and associated emotion data. The server checks the usage fee and possibly fine-tunes the fee based on the analysis results of the emotion engine. The output is the proposed usage fee.

[0457] Step 7:

[0458] The user pays the usage fee. The input includes the proposed usage fee and the user's payment information. The terminal uses the payment processing module to pay the usage fee. The server confirms the payment. The output is payment confirmation information.

[0459] Step 8:

[0460] The server verifies the payment, releases and provides an encrypted prompt. The input includes the payment confirmation information and the encrypted prompt. The server reverses the encryption process and sends the prompt to the user's terminal. The output is the released prompt.

[0461] Step 9:

[0462] The server returns a portion of the earned usage fee to the prompt creator. The input includes the usage fee and related prompt information. The server uses data from the emotion engine to calculate the refund amount and send it to the creator. The output is information indicating that the refund process has been completed.

[0463] Step 10:

[0464] The server continuously collects user emotion data and stores it in a database. The input includes the user emotion data. The server uses an emotion engine to retrieve the emotion data and stores it in a database. The output is an updated database.

[0465] Step 11:

[0466] The server analyzes the collected emotional data and recommends appropriate content to the user. The input includes the emotional data stored in the database. The server analyzes the emotional data using a machine learning model and recommends the most suitable content to the user. The output is the recommended content.

[0467] 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.

[0468] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0469] 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.

[0470] [Second embodiment]

[0471] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0472] 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.

[0473] 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).

[0474] 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.

[0475] 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.

[0476] 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).

[0477] 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.

[0478] 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.

[0479] 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.

[0480] 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.

[0481] 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.

[0482] 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."

[0483] The "Prompt Bank" system of this invention is a platform that values, manages, and distributes prompts created by users. This system consists of three main components: a server, terminals, and users.

[0484] System Overview

[0485] (User prompt registration)

[0486] The user creates a prompt and uploads it to the system. The prompt is uploaded by the user, who sets the input data for the prompt on the input screen. When the user uploads a new prompt to the system, the server receives the prompt.

[0487] (receive and acknowledge prompts)

[0488] The server receives the uploaded prompt and checks its content. Specifically, the server analyzes the prompt to ensure it is formatted and properly formatted, and performs format and content checks as necessary. Based on the results of this analysis, the server proceeds to the next step.

[0489] (prompt hashing and saving)

[0490] The server hashes the prompt content and stores the result in a database using an algorithm such as SHA-256 to generate a unique identifier for the prompt, which uniquely identifies the prompt within the database.

[0491] (Evaluating and Valuing Prompts)

[0492] The server evaluates the prompt and assigns a value to it. This evaluation is based on the judgment of machine learning models and evaluators, and an economic value is assigned according to the quality and usefulness of the prompt. For example, the server evaluates the prompt and assigns a value of 100 yen as a result.

[0493] (Public release of prompts)

[0494] The server publishes the valued prompts to the public, either as a web page or an API response that can be accessed by users. The prompts are displayed in an appropriate format upon publication, and users can choose the prompts they want to use.

[0495] (Using user prompts)

[0496] The user selects the prompt they want to use from the published prompts and sends a usage request from the terminal to the server. The terminal then sends the hash code of the selected prompt to the server and makes a usage request.

[0497] (Payment and confirmation of usage fees)

[0498] The server receives the usage request and checks the usage fee. The user pays the requested fee. Based on the analysis results, the server returns fee information to the user, who then completes the payment. Payment is made by credit card, electronic money, or other means, and the server confirms the payment.

[0499] (Release encrypted prompt)

[0500] Once the server confirms the payment, it releases the encrypted prompt and provides it to the user. At this time, the server decrypts the prompt and sends it to the user's device. Once this transmission is complete, the user can use the prompt they specified.

[0501] (Return of profits)

[0502] The server returns a portion of the usage fee to the prompt creator. This return is based on a revenue sharing algorithm, and the server reflects the return amount in the creator's account. For example, if the prompt usage fee is 100 yen, the server can return 50 yen to the creator.

[0503] Specific examples

[0504] As a specific example of use, user A creates a "prompt for generating cat images" and uploads it to the system. The server receives the prompt, hashes it, rates it, and publishes it with a value of 100 yen. User B selects the published prompt and wishes to use it, sending a usage request to the server. User B pays the 100 yen usage fee, and after the server confirms the payment, it releases the encrypted prompt and provides it to user B. Finally, the server returns 50 yen of the 100 yen obtained to user A.

[0505] In this way, the Prompt Bank system values ​​and distributes prompts created by users, thereby promoting the spread of high-quality prompts and providing appropriate compensation to their creators.

[0506] The processing flow will be explained below.

[0507] Step 1:

[0508] A user creates a prompt and uploads it to the system.

[0509] Specifically, the user enters the required data on the prompt input screen and presses the "upload" button.

[0510] Step 2:

[0511] The server receives the uploaded prompts from the user.

[0512] Specifically, the server receives the HTTP POST request and stores the prompt data in a temporary storage directory.

[0513] Step 3:

[0514] The server checks the uploaded prompt.

[0515] Specifically, the server checks the file format, analyzes some of the content, and verifies whether it is in the correct format.

[0516] Step 4:

[0517] The server hashes the prompt to generate a unique identifier.

[0518] Specifically, the hash value of the prompt is calculated using the SHA-256 algorithm and the result is obtained.

[0519] Step 5:

[0520] The server stores the hashed prompts in a database.

[0521] Specifically, relevant information such as the prompt's hash value, original content, and creation time is recorded in a database.

[0522] Step 6:

[0523] The server evaluates the prompt and assigns a value.

[0524] Specifically, the quality is evaluated using machine learning models and human evaluators, and an appropriate monetary value (e.g., 100 yen) is set.

[0525] Step 7:

[0526] The server lists the valued prompts and makes them publicly available.

[0527] Specifically, a prompt list is generated as a public HTML page or API response, making it accessible to users.

[0528] Step 8:

[0529] The user selects the prompt they want to use from the publicly available prompts.

[0530] Specifically, the user selects a specific prompt (e.g., hash code abc123) from a list of published prompts.

[0531] Step 9:

[0532] The user's terminal transmits the hash code of the selected prompt to the server and makes a usage request.

[0533] As a specific example, an HTTP POST request is used to send a hash code of the prompt to communicate intent to the server.

[0534] Step 10:

[0535] The server receives the usage request and checks the usage fee.

[0536] Specifically, the value information of the prompt is obtained from the database, and the usage fee (e.g., 100 yen) is extracted and communicated to the user.

[0537] Step 11:

[0538] The user pays a usage fee.

[0539] Specifically, the payment procedure is completed using a payment method such as a credit card or electronic money.

[0540] Step 12:

[0541] The server verifies the user's payment.

[0542] Specifically, it receives a response from the payment service and records in a database whether the payment was successful.

[0543] Step 13:

[0544] The server releases the encrypted prompt and provides it to the user.

[0545] Specifically, the prompt is decrypted and the prompt content is sent to the user's terminal.

[0546] Step 14:

[0547] The server returns a portion of the usage fee earned to the creator of the prompt.

[0548] Specifically, the amount is calculated based on a revenue distribution algorithm and reflected in the creator's account.

[0549] Example 1

[0550] 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."

[0551] There is a lack of a platform for properly evaluating, managing, and distributing prompts for generative AI models. It is necessary to guarantee the quality of user-created prompts and assign economic value to them, thereby providing appropriate rewards to prompt creators and promoting the spread of high-quality prompts. Furthermore, there is no system for efficiently publishing prompts and making them available to other users.

[0552] 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.

[0553] In this invention, the server includes: a means for a user to create and upload prompts for a generative AI model; a means for the server to receive the uploaded prompts and verify their format and content; a means for the server to hash the prompts using the SHA-256 algorithm and store the results in a database; a means for the server to evaluate the prompts using a machine learning model or an evaluator and assign values ​​to them; a means for the server to publicly publish the valued prompts via a webpage or API response; a means for a user to select a published prompt and send a usage request; a means for receiving a usage request and confirming the proposed usage fee; a means for a user to pay the usage fee by credit card or electronic money; a means for confirming the payment, releasing the encrypted prompt, and providing it to the user's device; and a means for returning a portion of the obtained usage fee to the prompt creator based on a revenue sharing algorithm. This allows for efficient management of the entire process from prompt creation to evaluation, publication, usage, and reward distribution, enabling the spread of high-quality prompts and appropriate rewards to creators.

[0554] "User" refers to a person or organization that creates prompts for generative AI models and registers and uses them in the system.

[0555] "Prompts for a Generative AI Model" refers to instructions or datasets created to be input to a Generative AI Model.

[0556] "Uploading a prompt" refers to the act of sending a prompt created by a user to the server and registering it.

[0557] "Server" refers to a computer system that receives, validates, hashes, evaluates, stores, and publishes prompts, processes redemption requests, verifies fees, releases prompts, and redeems them.

[0558] The "SHA-256 algorithm" is a hash function used to uniquely identify the contents of a prompt.

[0559] "Hashing" refers to the process of converting the contents of the prompt into a fixed-length string and generating a unique identifier.

[0560] A "machine learning model" is a type of artificial intelligence used to evaluate prompts.

[0561] "Evaluator" refers to an entity responsible for judging the quality of prompts using machine learning models or manually.

[0562] "Assigning a value" refers to the process of determining an economic value for a prompt based on the results of the prompt evaluation.

[0563] "Web Page" refers to the interface that a user accesses to review prompts, make selections, and make utilization requests.

[0564] "API response" refers to the response data returned by a server through an application program interface.

[0565] "Usage Request" refers to a request sent by a user to use a published prompt.

[0566] "Usage Fee" refers to the amount paid by a user to use a prompt.

[0567] "Credit cards and electronic money" refers to electronic payment methods used by users to pay usage fees.

[0568] "Encryption" refers to the process of converting the contents of a prompt into an unreadable form for security purposes.

[0569] "Releasing" refers to decrypting the encrypted prompt and making it available for use after the user pays the usage fee.

[0570] "Revenue Share Algorithm" refers to the calculation method used to appropriately return earned royalties to prompt creators.

[0571] This invention relates to a system called "Prompt Bank" for valuing, managing, and distributing prompts for generative AI models. This system is mainly composed of three elements: a server, a terminal, and a user.

[0572] System components and specific operations

[0573] Prompt registration for users

[0574] A user creates a prompt for a generative AI model and enters the prompt content into the device's input screen. The user then presses the "Register" button to send the prompt to the server. This operation is the first step for the user to widely publish their prompt and earn revenue by having other users use it. A specific example is when a user creates a "prompt for drawing a cat."

[0575] Receiving and acknowledging prompts

[0576] The server receives the prompt sent by the user and checks its format and content. During this check, the server analyzes the prompt to determine whether it is in the correct format and whether the content is inappropriate. This analysis process can be performed using commonly known software tools or custom-developed scripts.

[0577] Hashing and saving prompts

[0578] The server hashes the prompt using the SHA-256 algorithm. This hashing process generates a unique identifier. The generated hash value is stored in a database, ensuring the uniqueness of the prompt. A server computer is used as the hardware for high-speed calculations.

[0579] Evaluating and valuing prompts

[0580] The server evaluates the prompt using a machine learning model or evaluators. This evaluation determines the quality of the prompt and assigns an economic value to it. For example, a text analysis algorithm or a natural language processing model is used as the evaluation model. Based on the evaluation result of the prompt, a value of, for example, 100 yen is assigned.

[0581] Publicly available prompts

[0582] The server exposes the valued prompts to the public through web pages or API responses, where they are listed and categorized for easy user access, and a search function is provided to help users efficiently find the prompts they need.

[0583] User prompt usage request

[0584] The user selects a prompt from the published prompts and sends a usage request to the server from the device, requesting a specific prompt using the prompt's hash code.

[0585] Payment and confirmation of usage fees

[0586] The server receives the usage request and checks the proposed usage fee. The user pays the specified usage fee using a credit card or electronic money. The server verifies and confirms the completion of the payment.

[0587] Releasing the encrypted prompt

[0588] Once payment is confirmed, the server releases the encrypted prompts and provides them to the user's device, where they are decrypted and the user can use the purchased prompts.

[0589] Return of profits

[0590] The server returns a portion of the usage fee to the prompt creator based on a revenue sharing algorithm. For example, if the usage fee is 100 yen, 50 yen of that will be returned to the creator. This return will serve as an incentive for prompt creators to continue providing high-quality prompts.

[0591] Specific examples

[0592] For example, User A creates a "prompt to generate a picture of a cat" and uploads it to the "Prompt Bank" system. The server receives the prompt, hashes it using the SHA-256 algorithm, assigns a value of 100 yen, and publishes it. User B selects that prompt, sends a usage request, and makes payment. After the server confirms the payment, it releases the prompt and provides it to User B, and User A receives 50 yen in revenue. This process allows users to receive compensation for the valuable prompts they send out.

[0593] This allows the Prompt Bank system to seamlessly implement the entire process of registering, evaluating, publishing, using, and giving back prompts, efficiently promoting the dissemination of prompts and providing fair rewards to creators.

[0594] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0595] Processing flow and specific explanation

[0596] Step 1:

[0597] User creates and uploads prompts

[0598] Input: Prompt "Prompt to generate a picture of a cat"

[0599] Output: Sending a prompt to the server

[0600] Specific actions

[0601] The user creates a prompt for the generative AI model and enters it into the device's input screen. When the user presses the "Register" button, the prompt is sent to the server.

[0602] Step 2:

[0603] The server receives the prompt and confirms it.

[0604] Input: User uploaded prompt text

[0605] Output: Check the format and content of the prompt statement

[0606] Specific actions

[0607] The server analyzes and checks the format (e.g., text format) and content (e.g., whether it contains useful information) of the received prompt. The server uses a specific algorithm to evaluate the appropriateness of the content and filter out inappropriate content.

[0608] Step 3:

[0609] The server hashes and stores the prompt

[0610] Input: Confirmed prompt text

[0611] Output: Hash value of the prompt statement and the record stored in the database

[0612] Specific actions

[0613] The server hashes the prompt using the SHA-256 algorithm to generate a unique identifier, and stores the hash value and the original prompt in an internal database.

[0614] Step 4:

[0615] Server prompt evaluation and rating

[0616] Input: hashed prompt text

[0617] Output: Valued prompt sentences and their evaluation results

[0618] Specific actions

[0619] The server evaluates the prompt using machine learning models and evaluators. Based on the evaluation results, the server assigns an economic value (e.g., 100 yen) to the prompt. This evaluation is performed using text analysis and natural language processing models.

[0620] Step 5:

[0621] Server prompt public

[0622] Input: Valued prompt sentence

[0623] Output: List of published prompt statements

[0624] Specific actions

[0625] The server exposes the valued prompts as publicly accessible web pages or API responses, including appropriate formatting and search functionality.

[0626] Step 6:

[0627] The user selects the prompt and submits a request for use.

[0628] Input:Select the published prompt sentence

[0629] Output: Usage request to the server

[0630] Specific actions

[0631] The user selects a prompt from the list of available prompts and sends a usage request to the server from their device. The request includes the hash code of the prompt.

[0632] Step 7:

[0633] The server checks the usage fee

[0634] Input: User request

[0635] Output: Usage fee and payment confirmation

[0636] Specific actions

[0637] The server receives the usage request and checks the proposed usage fee. The user pays using a credit card or electronic money, and the server verifies and confirms the payment.

[0638] Step 8:

[0639] Server releases encrypted prompt

[0640] Input: Payment confirmed request

[0641] Output: Decoded prompt sentence

[0642] Specific actions

[0643] Once the payment is confirmed, the server decrypts the original encrypted prompt text and provides it to the user's terminal, where the user can use the specified prompt text.

[0644] Step 9:

[0645] Server returns profits

[0646] Input: Usage Fee Revenue

[0647] Output: Reward amount to prompt creator

[0648] Specific actions

[0649] The server will then return a portion of the fee to the prompt creator based on a revenue sharing algorithm. For example, if the fee is 100 yen, 50 yen will be returned to the creator. The refund amount will be reflected in the creator's account.

[0650] (Application example 1)

[0651] 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."

[0652] In conventional prompt management systems, the value of prompts created by users is evaluated centrally, which hinders the smooth distribution of prompts among users. Furthermore, the quality and usefulness of prompts are not adequately evaluated, which means that high-quality prompts are sometimes not properly evaluated. Furthermore, it is difficult for users to efficiently find prompts, which hinders the promotion of prompt usage.

[0653] 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.

[0654] In this invention, the server includes means for rating and assigning values ​​to prompts based on rating information from other users, means for prioritizing prompts based on the rating information and recommending them to other users, and means for analyzing the content of prompts and checking whether they are in an appropriate format. This facilitates the smooth distribution of prompts among users, ensures that high-quality prompts are appropriately rated, and enables users to efficiently find the prompts they need.

[0655] A "User" is an individual or organization that uses the system to create, upload, rate, select, pay for, or otherwise interact with prompts.

[0656] A "prompt" is text data that includes input instructions, guidelines, scripts, commands, etc. for a generative AI model.

[0657] "Server" means a computer system that receives, analyzes, hashes, stores, evaluates, and publishes prompts, and releases and provides encrypted prompts.

[0658] "Hashing" is the process of converting the contents of the prompt into a unique identifier using an algorithm such as SHA-256.

[0659] The "database" is a collection of information for managing hashed prompts, their evaluation information, and usage history.

[0660] "Valuing" is the process of calculating and assigning an economic value to a prompt based on its quality and usefulness.

[0661] "Publicly available" means making the valued prompt accessible to multiple users.

[0662] A "use request" is a request that a user sends to a server to use a particular prompt.

[0663] A "usage fee" is a fee paid by a user to use a published prompt.

[0664] "Rating information" is information about ratings and feedback given by other users to a particular prompt.

[0665] "Priority" refers to the display order when recommending a prompt to other users based on the prompt's evaluation information.

[0666] "Recommending" means preferentially displaying a particular prompt to other users and promoting its use.

[0667] The system for implementing this invention allows users to create and upload prompts, and manages their value assessment, publication, use, payment, and redemption. The main components of the system are a user interface for uploading prompts, a server, and a user interface for using prompts.

[0668] 1. Prompt registration of users

[0669] Users create prompts and upload them to the system from their smartphones or other devices. The uploaded prompts are received by the server. Specifically, users enter text data, such as a "prompt to generate a cat image," and send it to the system.

[0670] 2. Receiving and confirming the prompt on the server

[0671] The server checks the content of the received prompt and parses it to ensure it is in the correct format. Improperly formatted prompts are filtered out at this stage.

[0672] 3. Hashing and storing prompts

[0673] The server hashes the prompt using the SHA-256 algorithm and stores the result in a database, which uniquely identifies the prompt.

[0674] 4. Evaluating and Valuing Prompts

[0675] The server determines the value of prompts based on the rating information received from other users, and also prioritizes and recommends prompts to other users.

[0676] 5. Publicly displaying prompts

[0677] The valued prompts are then published as user-accessible web pages or API responses, allowing users to easily view and select from them.

[0678] 6. User Prompts

[0679] The user selects a published prompt and sends a request to the server to use it, along with the hash code of the prompt they want to use.

[0680] 7. Payment and Confirmation of Usage Fees

[0681] The server receives the usage request and checks the usage fee. The user pays using a credit card or electronic money. The server checks the payment and updates the information.

[0682] 8. Releasing the Encrypted Prompt

[0683] After the server verifies the payment, it releases and provides the encrypted prompt to the user, allowing them to use the prompt they specified.

[0684] 9. Return of profits

[0685] The server returns a portion of the usage fee to the prompt creator, the user, so that the user can receive appropriate compensation for the high-quality prompts they have created.

[0686] As a concrete example, consider a "prompt for generating cat images." A user uploads this prompt to the system, and other users rate it, assigning it a value. After that, another user selects a published prompt, confirms its value, and pays a fee to use it. After the server confirms the payment, it releases the encrypted prompt and provides it to the user. This entire process is performed automatically by the system.

[0687] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0688] Step 1:

[0689] A user creates a prompt and uploads it to the system using a terminal. To do this, the user enters text data, such as "a prompt to generate a cat image," and clicks the upload button. The input is the text data, and the output is the prompt sent to the server.

[0690] Step 2:

[0691] The server receives the uploaded prompt and checks its content. Specifically, the server parses the prompt to see if it is valid and checks its format and content. The input is the uploaded prompt, and the output is the parsing result (valid or invalid).

[0692] Step 3:

[0693] The server hashes the prompt using the SHA-256 algorithm and stores the result in a database. The input is the prompt text data, and the output is the hashed data.

[0694] Step 4:

[0695] The server evaluates the value of the prompt based on the rating information received from other users. This evaluation is performed using a machine learning model, which assigns an economic value to the prompt. The input is the rating information and the prompt, and the output is the valued prompt.

[0696] Step 5:

[0697] The server publishes the valued prompts to the public, where they are displayed as user-accessible web pages or API responses. The input is the valued prompt, and the output is the published prompt.

[0698] Step 6:

[0699] The user selects a published prompt and sends a usage request from the terminal to the server. The input is the published prompt and its hash code, and the output is the usage request sent to the server.

[0700] Step 7:

[0701] The server receives the usage request and checks the usage fee. At this time, the server retrieves the fee information from the database and presents it to the user. The input is the usage request, and the output is the fee information.

[0702] Step 8:

[0703] The user pays the displayed usage fee. This payment is made by means of a credit card, electronic money, etc. The input is fee information and payment information, and the output is confirmation of payment completion.

[0704] Step 9:

[0705] After the server confirms the payment, it releases the encrypted prompt and provides it to the user. Specifically, the server decrypts the prompt and sends it to the user's device. The input is the payment confirmation and the encrypted prompt, and the output is the decrypted prompt.

[0706] Step 10:

[0707] The server returns a portion of the earned usage fees to the prompt creator. The server calculates the amount of the return based on a revenue sharing algorithm and reflects it in the creator's account. The input is the usage fee and creator information, and the output is a reflection of the return amount.

[0708] 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.

[0709] The "Prompt Bank" system of this invention is a platform for assigning value to, managing, and distributing prompts created by users. The system includes the main components of a server, terminals, and users, and by combining it with an emotion engine, it has the ability to evaluate prompts and make recommendations based on the user's emotions.

[0710] System Overview

[0711] (User prompt registration)

[0712] The user creates a prompt and uploads it to the system. The prompt is uploaded from the user's terminal. At this time, the emotion engine recognizes the user's emotional state and sends data including the user's current emotion to the server as prompt information.

[0713] (receive and acknowledge prompts)

[0714] The server receives the prompt uploaded by the user, validates it, including checking that it is in the correct format, hashes it, generates a unique identifier, and stores it in a database.

[0715] (Evaluating and Valuing Prompts)

[0716] The server evaluates prompts by using an emotion engine to modify their value based on the user's emotion. Specifically, the emotion engine analyzes the user's emotion data and evaluates the quality of the prompt according to the emotion. Based on this evaluation result, the server assigns an economic value (e.g., 100 yen) to the prompt.

[0717] (Public release of prompts)

[0718] The server lists the valued prompts and makes them publicly available, allowing users to select from the list.

[0719] (Using user prompts and emotion recognition)

[0720] The user selects a prompt from the published prompts and sends a request to use it from the device to the server. The device then sends the hash code of the selected prompt along with the latest emotion data recognized by the emotion engine to the server.

[0721] (Payment and confirmation of usage fees)

[0722] The server receives the usage request and checks the usage fee. It analyzes the user's level of interest based on emotional data from the emotion engine and fine-tunes the fee if necessary. The user pays the proposed usage fee and the payment is completed. After the server confirms the payment, it releases an encrypted prompt and sends it to the user's device.

[0723] (Recommendation based on emotional data)

[0724] The emotion engine continuously collects user emotional data and stores it in a database. The server analyzes this data to recommend personalized prompts based on the user's interests and emotions. For example, if a user is feeling stressed, the server can recommend prompts with a relaxing effect.

[0725] (Return of profits)

[0726] The server returns a portion of the obtained usage fee to the creator of the prompt. The amount of the refund based on the usage fee is also recorded in the database using the user's usage emotion data generated by the emotion engine.

[0727] Specific examples

[0728] As a concrete example, user A creates a "prompt for generating a cat image" and uploads it to the system. The emotion engine recognizes the user's emotion at the time of uploading as "excitement," and this is added to the prompt information. The server receives the prompt, evaluates its quality, and assigns a value of 100 yen, taking the emotion information into consideration. When this prompt is made public and user B wishes to use it and sends a usage request to the server, the emotion engine recognizes the user's current emotion as "excitement." The server presents a usage fee of 100 yen, and user B pays. After confirming the payment, the server releases the encrypted prompt and sends it to user B's device. Finally, the server returns 50 yen of the 100 yen revenue to user A, the prompt creator.

[0729] In this way, the "Prompt Bank" system, which combines an emotion engine, utilizes users' emotional data to value and recommend prompts, thereby promoting the spread of high-quality prompts and providing appropriate rewards to their creators.

[0730] The processing flow will be explained below.

[0731] Step 1:

[0732] A user creates a prompt and uploads it to the system.

[0733] Specifically, the user inputs the required prompt content on the device's input screen, and the emotion engine recognizes the user's emotional state in real time. When the user presses the "upload" button, the prompt data and emotion data are sent to the server.

[0734] Step 2:

[0735] The server receives the uploaded prompts from the user.

[0736] The server receives the HTTP POST request and stores the prompt data and emotion data in a temporary directory.

[0737] Step 3:

[0738] The server checks the uploaded prompt.

[0739] Specifically, the server checks the format of the prompt, parses the content for correctness, and notifies the user of formatting errors or incomplete content if necessary.

[0740] Step 4:

[0741] The server hashes the prompt to generate a unique identifier.

[0742] The server generates a hash code of the prompt using the SHA-256 algorithm and retrieves the result.

[0743] Step 5:

[0744] The server stores the hashed prompts in a database.

[0745] The server records the prompt's hash value, original content, emotion data, and creation time in a database.

[0746] Step 6:

[0747] The server evaluates the prompt and assigns a value.

[0748] The server uses an emotion engine to analyze the user's emotion data, evaluates the quality of the prompt based on the results, and assigns an economic value to the prompt (e.g., 100 yen).

[0749] Step 7:

[0750] The server publishes the valued prompts to the public.

[0751] Specifically, the server generates a list of valued prompts as an HTML page or API response and makes it publicly available.

[0752] Step 8:

[0753] The user selects the prompt they want to use from the publicly available prompts.

[0754] The user selects a specific prompt (e.g., hash code abc123) from the list of published prompts and presses the "Use" button.

[0755] Step 9:

[0756] The user's terminal transmits the hash code and emotion data of the selected prompt to the server.

[0757] Specifically, the latest emotion data is sent to the server along with the hash code of the prompt using an HTTP POST request from the user's device.

[0758] Step 10:

[0759] The server receives the usage request and checks the usage fee.

[0760] The server retrieves the value information of the prompt from the database, extracts the usage fee (e.g., 100 yen), and presents it to the user.

[0761] Step 11:

[0762] The user pays a usage fee.

[0763] Specifically, the user enters their credit card information to complete the payment process, and the payment information is encrypted and sent to the server.

[0764] Step 12:

[0765] The server verifies the user's payment.

[0766] The server receives the response from the payment service, verifies whether the payment was successful, and records the payment information in a database.

[0767] Step 13:

[0768] The server releases the encrypted prompt and provides it to the user.

[0769] The server decodes the prompt and sends it to the user's device, possibly along with associated emotional data.

[0770] Step 14:

[0771] The server returns a portion of the usage fee earned to the creator.

[0772] The server will then credit a portion of the revenue earned based on a revenue sharing algorithm to the creator's account and record the amount in a database. For example, 50 yen out of a 100 yen usage fee will be returned to the creator.

[0773] Step 15:

[0774] The server recommends prompts based on the emotion data.

[0775] Specifically, the server analyzes the user's emotional data collected from the emotion engine and recommends personalized prompts to the user. For example, if the user is feeling stressed, it will recommend prompts that have a relaxing effect.

[0776] Example 2

[0777] 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."

[0778] Conventional prompt management systems evaluate and value prompts without considering the user's emotions, which makes it difficult to value and recommend prompts that are in line with the user's needs and emotions. It is also difficult to provide appropriate rewards to prompt creators.

[0779] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0780] In this invention, the server includes means for acquiring user emotion data using an emotion engine and adding it to prompt information, means for the server to evaluate prompts and assign values ​​based on the emotion data, and means for the emotion engine to collect, save, and analyze user emotion data to make personalized recommendations. This makes it possible to evaluate and assign values ​​to prompts based on user emotions, thereby enabling the spread of high-quality prompts and the provision of appropriate rewards to their creators.

[0781] "User" means an entity that uses the system to create, upload, or use prompts.

[0782] A "prompt" refers to text data that expresses instructions or requests to a generative AI model.

[0783] "Terminal" refers to a digital device used by a user, such as a computer, smartphone, or tablet.

[0784] "Server" refers to a central digital computer system that receives, evaluates, hashs, stores, publishes, etc., prompts.

[0785] An "emotion engine" refers to software or hardware that recognizes a user's emotional state and processes it as data.

[0786] "Hashing" refers to a cryptographic technique for converting a prompt into a unique identifier.

[0787] "Database" means a digital collection of information for managing and storing prompts and related data.

[0788] "Assigning a value" refers to the process of assigning an economic value to a prompt.

[0789] "Public" refers to making a valued prompt available for other users to view.

[0790] "Usage Request" refers to a request sent by a user to use a published prompt.

[0791] "Usage Fee" refers to the cost incurred when using Prompt.

[0792] "Rebate" refers to returning a portion of the usage fee to the prompt creator as compensation.

[0793] "Personalized recommendations" refers to suggesting prompts that are individually optimized based on the user's emotional data.

[0794] A "machine learning model" refers to an algorithmic method that learns from data and evaluates prompts based on the analysis results.

[0795] The "Prompt Bank" system of this invention is a platform for assigning value to, managing, and distributing prompts created by users. In addition to the main components of the system, which are a server, terminals, and users, it also combines an emotion engine to enable prompt evaluation and recommendations based on the user's emotions.

[0796] Hardware and software configuration

[0797] server

[0798] The server functions as a central processing unit and performs the following processes:

[0799] Receiving and hashing prompts

[0800] Save prompts to the database

[0801] Data analysis from the emotion engine

[0802] Valuing and Evaluating Prompts

[0803] Processing public availability and usage requests

[0804] Checking usage fees and processing payments

[0805] Fee rebates and management

[0806] Terminal

[0807] The devices used by users include computers, smartphones, tablets, etc. These devices perform the following functions:

[0808] Prompt creation and upload

[0809] Select a prompt and submit a request

[0810] Collecting and transmitting emotional data

[0811] Emotion Engine

[0812] The emotion engine has the following functions:

[0813] Recognizing the user's emotional state in real time

[0814] Collecting user emotion data

[0815] Adding emotional data to prompt information

[0816] Recommending prompts based on emotion data

[0817] Data processing and calculation

[0818] When a user creates a prompt and uploads it to the system from their device, the emotion engine collects the user's emotional state and sends it to the server as prompt information. The server receives the prompt, checks its content, and checks whether it is in the correct format. The server then hashes the prompt to generate a unique identifier and stores it in a database.

[0819] The server analyzes the data from the emotion engine and evaluates the quality of the prompts. Based on the evaluation results, the server assigns economic values ​​to the prompts. The server then makes the valued prompts public, allowing users to select prompts.

[0820] When a user requests to use a published prompt, the device sends a usage request including emotion data to the server. The server receives the usage request, checks and adjusts the usage fee based on the emotion data, and completes the payment once the user pays the fee. After the server confirms the payment, it releases the encrypted prompt and sends it to the device.

[0821] The emotion engine continuously collects user emotion data, and the server analyzes the data to recommend personalized prompts.

[0822] Specific examples

[0823] For example, user A creates a "prompt for generating a cat image" and uploads it to the system. The emotion at the time of uploading is recognized as "excitement," and this is added to the prompt information. The server receives the prompt, evaluates its quality, and assigns a value of 100 yen, taking into account the emotional information. This prompt is made public, and user B wants to use it. When a usage request is sent to the server, the emotion engine recognizes the user's current emotion as "excitement." The server presents a usage fee of 100 yen, and user B pays. After confirming the payment, the server releases the encrypted prompt and sends it to user B's device. Finally, the server returns 50 yen of the 100 yen revenue to user A.

[0824] By combining this system with an emotion engine, it is possible to value and recommend prompts based on the user's emotions, thereby promoting the spread of high-quality prompts and providing appropriate rewards to their creators.

[0825] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0826] Step 1: User creates and uploads prompt

[0827] The user opens the prompt creation screen on their device and enters a prompt for the generative AI model. When the user presses the upload button, the device sends the prompt to the server. At this time, the emotion engine recognizes the user's emotional state in real time and sends the emotional data along with it. The input is the prompt and emotional data, and the output is uploaded to the server.

[0828] Step 2: Receive and confirm the prompt

[0829] The server receives prompts uploaded by users. At this time, it checks whether the prompts are in the correct format. Specifically, it checks the text length of the prompt and whether it contains specific keywords. The input is the uploaded prompt and emotion data, and the output is the prompt format check result.

[0830] Step 3: Hash and save the prompt

[0831] The server hashes the prompt sentence and generates a unique identifier. The server then stores the prompt sentence, emotion data, and unique identifier in a database. The input is the confirmed prompt sentence and emotion data, and the output is storage in the database.

[0832] Step 4: Evaluate and value the prompt

[0833] The server uses an emotion engine to analyze the user's emotional data. Based on the results of this analysis, the server evaluates the quality of the prompt and assigns an economic value (e.g., 100 yen). The input is the emotional data and the prompt, and the output is the assigned value.

[0834] Step 5: Make the prompt public

[0835] The server compiles a list of valued prompts and makes it publicly available for users to view. The input is the valued prompt text, and the output is the published list of prompts.

[0836] Step 6: User requests prompt usage

[0837] The user browses a list of publicly available prompts on their device and selects the prompt they want to use. Then, they send a usage request from their device to the server. At this time, the emotion engine recognizes the user's latest emotion data and sends it along with the request to the server. The input is the usage request and emotion data, and the output is the request sent to the server.

[0838] Step 7: Check and settle usage fees

[0839] The server receives the usage request and analyzes the emotional data to assess the user's interest level. Based on this, it checks and possibly fine-tunes the usage fee. The user pays the fee, and the server confirms the payment. The input is the usage request and emotional data, and the output is the adjusted usage fee and its payment confirmation.

[0840] Step 8: Sending the Encrypted Prompt

[0841] After the server confirms the payment, it releases the encrypted prompt and sends it to the user's terminal. The input is the payment confirmation and the prompt text, and the output is the prompt sent to the terminal.

[0842] Step 9: Recommendation based on emotion data

[0843] The emotion engine continuously collects user emotion data, and the server analyzes the data to generate personalized recommendations. The input is the collected emotion data, and the output is personalized prompt recommendations.

[0844] Step 10: Returning profits

[0845] The server returns a portion of the revenue based on the prompt usage by the user to the prompt creator. The server also references the emotion data collected by the emotion engine to calculate the amount of return. The input is the usage fee and emotion data, and the output is the calculation and reflection of the return amount.

[0846] (Application example 2)

[0847] 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."

[0848] Conventional prompt management systems do not evaluate or recommend prompts based on the user's emotions, making it difficult to accurately evaluate the quality of prompts or to provide customized recommendations for individual users. Furthermore, it is difficult to provide content that matches the user's current emotional state, resulting in a decrease in user satisfaction. The present invention aims to solve these problems by enabling prompt evaluation and recommendation based on the user's emotions and providing content in accordance with emotional data.

[0849] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0850] In this invention, the server includes means for a user to create and upload prompts, means for the server to receive the uploaded prompts and check the contents of the prompts, means for the server to hash the prompts and store the hashed results in a database, means for the server to rate and assign values ​​to the prompts, means for the server to publicly publish the valued prompts, means for a user to select a published prompt and send a usage request, means for the server to receive the usage request and check a usage fee, means for the user to pay the usage fee, means for the server to confirm the payment and release and provide the encrypted prompts, and means for the server to return a portion of the usage fee to the creator, as well as means for rating and recommending prompts based on the user's emotions using an emotion engine, and means for recommending content according to the user's emotion data. This not only enables proper evaluation of the quality of prompts and recommendation of customized prompts to individual users, but also makes it possible to provide appropriate content according to the user's current emotional state.

[0851] A "prompt" is a statement written in the form of an instruction, question, or command given to a generative AI model.

[0852] "Uploading" is the act of a user sending data or files from their device to a server.

[0853] A "server" is a computer system that provides services to other computers (clients) on a network.

[0854] "Hashing" is a cryptographic process that converts original data into a fixed-length string of characters that can be used as a unique identifier.

[0855] A "database" is a collection of structured data that allows for efficient management and retrieval of large amounts of data.

[0856] An "emotion engine" is a software technology for analyzing a user's emotional state and collecting and utilizing that data.

[0857] "Valuing" is the act of assigning economic value or valuation to specific data or items.

[0858] "Publishing" means making certain data or information accessible to other users within the system.

[0859] A "use request" is a request that a user sends to the effect that he or she wishes to use a published prompt or service.

[0860] "Usage Fee" means money paid for the use of a particular service or item.

[0861] "Encryption" is a technology that codes data using a specific algorithm to protect it from easy access by third parties.

[0862] "Return" is the act of giving back a portion of the revenue or profits earned to a specific cause or person.

[0863] "Emotional Data" means information about the user's emotional state that is analyzed and collected by the Emotion Engine.

[0864] "Recommendation" is the act of a system suggesting optimal content or services based on a user's behavior and emotions.

[0865] "Content" refers to digital data and information such as music, video, text, and images provided through systems and services.

[0866] This invention relates to a prompt bank system incorporating an emotion engine. Specifically, it provides a method for uploading prompts created by users and analyzing and evaluating them using the emotion engine. The server assigns an appropriate value based on the prompt evaluation results and publishes them. Furthermore, the system provides recommended content based on the user's latest emotion data.

[0867] Hardware and Software Configuration

[0868] 1. The server is the central processing unit for managing, evaluating, storing, and publishing prompts. It includes hashing technology, a database management system, and machine learning models (e.g., TensorFlow).

[0869] 2. An emotion engine is a software technology that analyzes a user's emotional data, recognizes their emotional state, and generates corresponding data. A typical emotion analysis module is the sentiment_analysis library.

[0870] 3. User terminals are devices used to create, upload, view, and process payments for prompts. These include smartphones, tablets, and PCs.

[0871] 4. The payment processing module is a system that allows users to make payments and uses the APIs of Stripe and PayPal.

[0872] System details

[0873] 1. Create and upload a prompt:

[0874] Users create prompts and upload them to the system from their own devices. For example, if a user creates a prompt called "Relaxing music for stress relief," the system will recognize the user's current emotional state as "Relaxed" using the emotion engine.

[0875] 2. Receiving and Evaluating Prompts:

[0876] The server receives the uploaded prompts, hashes them, and stores them in a database. It then uses an emotion engine to analyze the user's emotional data and evaluate the quality of the prompts. Based on the evaluation results, economic values ​​are assigned to the prompts.

[0877] 3. Publishing and Recommending Prompts:

[0878] The server publishes the valued prompts to the public. Other users can browse the published prompts and select the prompts they want to use. The emotion engine then recommends the most appropriate prompts to the user based on the latest emotional data analyzed.

[0879] 4. Payment Processing and Prompts:

[0880] The user selects a published prompt and sends a usage request to the server. The server checks the usage fee, and the user pays. Once the payment is confirmed, the server releases the encrypted prompt and sends it to the user's device.

[0881] 5. Return of profits:

[0882] The server returns a portion of the usage fee to the prompt creator. Using usage emotion data from the emotion engine, the server accurately calculates the monetary amount of the return and records it in a database.

[0883] Example prompt

[0884] For example, if User A wants to recommend "relaxing music to relieve stress," he or she can create a prompt like this:

[0885] "Recommend relaxing music for stress relief."

[0886] This system improves the user experience by enabling the user to value prompts based on their emotional state and recommend content that is best suited to each individual user.

[0887] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0888] Step 1:

[0889] The user creates a prompt and uploads it from the device to the server. The input includes the prompt text "Please recommend some relaxing music to relieve stress." and the user's current emotional data. The device creates the prompt, recognizes the user's emotional state using an emotion engine, and sends the data including the prompt to the server. The server then receives this data.

[0890] Step 2:

[0891] The server verifies the received prompt, hashes it, and stores it in a database. The input includes the uploaded prompt data. The server verifies the prompt content, checks that it is in the correct format, and then uses hashing techniques to generate a unique identifier. The server then stores the hashed prompt in a database. The output is the hashed data.

[0892] Step 3:

[0893] The server evaluates the prompt content using an emotion engine and assigns a value. The input includes the prompt content and the user's emotion data. The server uses the emotion engine to analyze the user's emotion data and evaluates the quality of the prompt based on this. Based on the evaluation result, an economic value is assigned to the prompt. For example, a value of 100 yen is assigned. The output is the evaluation result and the prompt with the assigned value.

[0894] Step 4:

[0895] The server publishes valued prompts to the public. The input includes the valued prompt data. The server publishes the prompts to the public in a list format that can be accessed by other users. The output is a list of published prompts.

[0896] Step 5:

[0897] The user selects a published prompt and sends a usage request from the device to the server. The input includes a list of published prompts and the user's selection. The user browses the published prompts on the device and selects the prompt they want to use. The latest emotion data is also sent along with the usage request. The output is the selected prompt and the associated emotion data.

[0898] Step 6:

[0899] The server receives the usage request and checks the usage fee. The input includes the user's usage request and associated emotion data. The server checks the usage fee and possibly fine-tunes the fee based on the analysis results of the emotion engine. The output is the proposed usage fee.

[0900] Step 7:

[0901] The user pays the usage fee. The input includes the proposed usage fee and the user's payment information. The terminal uses the payment processing module to pay the usage fee. The server confirms the payment. The output is payment confirmation information.

[0902] Step 8:

[0903] The server verifies the payment, releases and provides an encrypted prompt. The input includes the payment confirmation information and the encrypted prompt. The server reverses the encryption process and sends the prompt to the user's terminal. The output is the released prompt.

[0904] Step 9:

[0905] The server returns a portion of the earned usage fee to the prompt creator. The input includes the usage fee and related prompt information. The server uses data from the emotion engine to calculate the refund amount and send it to the creator. The output is information indicating that the refund process has been completed.

[0906] Step 10:

[0907] The server continuously collects user emotion data and stores it in a database. The input includes the user emotion data. The server uses an emotion engine to retrieve the emotion data and stores it in a database. The output is an updated database.

[0908] Step 11:

[0909] The server analyzes the collected emotional data and recommends appropriate content to the user. The input includes the emotional data stored in the database. The server analyzes the emotional data using a machine learning model and recommends the most suitable content to the user. The output is the recommended content.

[0910] 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.

[0911] 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.

[0912] 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.

[0913] [Third embodiment]

[0914] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0915] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0916] 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).

[0917] 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.

[0918] 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.

[0919] 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).

[0920] 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.

[0921] 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.

[0922] 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.

[0923] 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.

[0924] 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.

[0925] 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."

[0926] The "Prompt Bank" system of this invention is a platform that values, manages, and distributes prompts created by users. This system consists of three main components: a server, terminals, and users.

[0927] System Overview

[0928] (User prompt registration)

[0929] The user creates a prompt and uploads it to the system. The prompt is uploaded by the user, who sets the input data for the prompt on the input screen. When the user uploads a new prompt to the system, the server receives the prompt.

[0930] (receive and acknowledge prompts)

[0931] The server receives the uploaded prompt and checks its content. Specifically, the server analyzes the prompt to ensure it is formatted and properly formatted, and performs format and content checks as necessary. Based on the results of this analysis, the server proceeds to the next step.

[0932] (prompt hashing and saving)

[0933] The server hashes the prompt content and stores the result in a database using an algorithm such as SHA-256 to generate a unique identifier for the prompt, which uniquely identifies the prompt within the database.

[0934] (Evaluating and Valuing Prompts)

[0935] The server evaluates the prompt and assigns a value to it. This evaluation is based on the judgment of machine learning models and evaluators, and an economic value is assigned according to the quality and usefulness of the prompt. For example, the server evaluates the prompt and assigns a value of 100 yen as a result.

[0936] (Public release of prompts)

[0937] The server publishes the valued prompts to the public, either as a web page or an API response that can be accessed by users. The prompts are displayed in an appropriate format upon publication, and users can choose the prompts they want to use.

[0938] (Using user prompts)

[0939] The user selects the prompt they want to use from the published prompts and sends a usage request from the terminal to the server. The terminal then sends the hash code of the selected prompt to the server and makes a usage request.

[0940] (Payment and confirmation of usage fees)

[0941] The server receives the usage request and checks the usage fee. The user pays the requested fee. Based on the analysis results, the server returns fee information to the user, who then completes the payment. Payment is made by credit card, electronic money, or other means, and the server confirms the payment.

[0942] (Release encrypted prompt)

[0943] Once the server confirms the payment, it releases the encrypted prompt and provides it to the user. At this time, the server decrypts the prompt and sends it to the user's device. Once this transmission is complete, the user can use the prompt they specified.

[0944] (Return of profits)

[0945] The server returns a portion of the usage fee to the prompt creator. This return is based on a revenue sharing algorithm, and the server reflects the return amount in the creator's account. For example, if the prompt usage fee is 100 yen, the server can return 50 yen to the creator.

[0946] Specific examples

[0947] As a specific example of use, user A creates a "prompt for generating cat images" and uploads it to the system. The server receives the prompt, hashes it, rates it, and publishes it with a value of 100 yen. User B selects the published prompt and wishes to use it, sending a usage request to the server. User B pays the 100 yen usage fee, and after the server confirms the payment, it releases the encrypted prompt and provides it to user B. Finally, the server returns 50 yen of the 100 yen obtained to user A.

[0948] In this way, the Prompt Bank system values ​​and distributes prompts created by users, thereby promoting the spread of high-quality prompts and providing appropriate compensation to their creators.

[0949] The processing flow will be explained below.

[0950] Step 1:

[0951] A user creates a prompt and uploads it to the system.

[0952] Specifically, the user enters the required data on the prompt input screen and presses the "upload" button.

[0953] Step 2:

[0954] The server receives the uploaded prompts from the user.

[0955] Specifically, the server receives the HTTP POST request and stores the prompt data in a temporary storage directory.

[0956] Step 3:

[0957] The server checks the uploaded prompt.

[0958] Specifically, the server checks the file format, analyzes some of the content, and verifies whether it is in the correct format.

[0959] Step 4:

[0960] The server hashes the prompt to generate a unique identifier.

[0961] Specifically, the hash value of the prompt is calculated using the SHA-256 algorithm and the result is obtained.

[0962] Step 5:

[0963] The server stores the hashed prompts in a database.

[0964] Specifically, relevant information such as the prompt's hash value, original content, and creation time is recorded in a database.

[0965] Step 6:

[0966] The server evaluates the prompt and assigns a value.

[0967] Specifically, the quality is evaluated using machine learning models and human evaluators, and an appropriate monetary value (e.g., 100 yen) is set.

[0968] Step 7:

[0969] The server lists the valued prompts and makes them publicly available.

[0970] Specifically, a prompt list is generated as a public HTML page or API response, making it accessible to users.

[0971] Step 8:

[0972] The user selects the prompt they want to use from the publicly available prompts.

[0973] Specifically, the user selects a specific prompt (e.g., hash code abc123) from a list of published prompts.

[0974] Step 9:

[0975] The user's terminal transmits the hash code of the selected prompt to the server and makes a usage request.

[0976] As a specific example, an HTTP POST request is used to send a hash code of the prompt to communicate intent to the server.

[0977] Step 10:

[0978] The server receives the usage request and checks the usage fee.

[0979] Specifically, the value information of the prompt is obtained from the database, and the usage fee (e.g., 100 yen) is extracted and communicated to the user.

[0980] Step 11:

[0981] The user pays a usage fee.

[0982] Specifically, the payment procedure is completed using a payment method such as a credit card or electronic money.

[0983] Step 12:

[0984] The server verifies the user's payment.

[0985] Specifically, it receives a response from the payment service and records in a database whether the payment was successful.

[0986] Step 13:

[0987] The server releases the encrypted prompt and provides it to the user.

[0988] Specifically, the prompt is decrypted and the prompt content is sent to the user's terminal.

[0989] Step 14:

[0990] The server returns a portion of the usage fee earned to the creator of the prompt.

[0991] Specifically, the amount is calculated based on a revenue distribution algorithm and reflected in the creator's account.

[0992] Example 1

[0993] 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."

[0994] There is a lack of a platform for properly evaluating, managing, and distributing prompts for generative AI models. It is necessary to guarantee the quality of user-created prompts and assign economic value to them, thereby providing appropriate rewards to prompt creators and promoting the spread of high-quality prompts. Furthermore, there is no system for efficiently publishing prompts and making them available to other users.

[0995] 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.

[0996] In this invention, the server includes: a means for a user to create and upload prompts for a generative AI model; a means for the server to receive the uploaded prompts and verify their format and content; a means for the server to hash the prompts using the SHA-256 algorithm and store the results in a database; a means for the server to evaluate the prompts using a machine learning model or an evaluator and assign values ​​to them; a means for the server to publicly publish the valued prompts via a webpage or API response; a means for a user to select a published prompt and send a usage request; a means for receiving a usage request and confirming the proposed usage fee; a means for a user to pay the usage fee by credit card or electronic money; a means for confirming the payment, releasing the encrypted prompt, and providing it to the user's device; and a means for returning a portion of the obtained usage fee to the prompt creator based on a revenue sharing algorithm. This allows for efficient management of the entire process from prompt creation to evaluation, publication, usage, and reward distribution, enabling the spread of high-quality prompts and appropriate rewards to creators.

[0997] "User" refers to a person or organization that creates prompts for generative AI models and registers and uses them in the system.

[0998] "Prompts for a Generative AI Model" refers to instructions or datasets created to be input to a Generative AI Model.

[0999] "Uploading a prompt" refers to the act of sending a prompt created by a user to the server and registering it.

[1000] "Server" refers to a computer system that receives, validates, hashes, evaluates, stores, and publishes prompts, processes redemption requests, verifies fees, releases prompts, and redeems them.

[1001] The "SHA-256 algorithm" is a hash function used to uniquely identify the contents of a prompt.

[1002] "Hashing" refers to the process of converting the contents of the prompt into a fixed-length string and generating a unique identifier.

[1003] A "machine learning model" is a type of artificial intelligence used to evaluate prompts.

[1004] "Evaluator" refers to an entity responsible for judging the quality of prompts using machine learning models or manually.

[1005] "Assigning a value" refers to the process of determining an economic value for a prompt based on the results of the prompt evaluation.

[1006] "Web Page" refers to the interface that a user accesses to review prompts, make selections, and make utilization requests.

[1007] "API response" refers to the response data returned by a server through an application program interface.

[1008] "Usage Request" refers to a request sent by a user to use a published prompt.

[1009] "Usage Fee" refers to the amount paid by a user to use a prompt.

[1010] "Credit cards and electronic money" refers to electronic payment methods used by users to pay usage fees.

[1011] "Encryption" refers to the process of converting the contents of a prompt into an unreadable form for security purposes.

[1012] "Releasing" refers to decrypting the encrypted prompt and making it available for use after the user pays the usage fee.

[1013] "Revenue Share Algorithm" refers to the calculation method used to appropriately return earned royalties to prompt creators.

[1014] This invention relates to a system called "Prompt Bank" for valuing, managing, and distributing prompts for generative AI models. This system is mainly composed of three elements: a server, a terminal, and a user.

[1015] System components and specific operations

[1016] Prompt registration for users

[1017] A user creates a prompt for a generative AI model and enters the prompt content into the device's input screen. The user then presses the "Register" button to send the prompt to the server. This operation is the first step for the user to widely publish their prompt and earn revenue by having other users use it. A specific example is when a user creates a "prompt for drawing a cat."

[1018] Receiving and acknowledging prompts

[1019] The server receives the prompt sent by the user and checks its format and content. During this check, the server analyzes the prompt to determine whether it is in the correct format and whether the content is inappropriate. This analysis process can be performed using commonly known software tools or custom-developed scripts.

[1020] Hashing and saving prompts

[1021] The server hashes the prompt using the SHA-256 algorithm. This hashing process generates a unique identifier. The generated hash value is stored in a database, ensuring the uniqueness of the prompt. A server computer is used as the hardware for high-speed calculations.

[1022] Evaluating and valuing prompts

[1023] The server evaluates the prompt using a machine learning model or evaluators. This evaluation determines the quality of the prompt and assigns an economic value to it. For example, a text analysis algorithm or a natural language processing model is used as the evaluation model. Based on the evaluation result of the prompt, a value of, for example, 100 yen is assigned.

[1024] Publicly available prompts

[1025] The server exposes the valued prompts to the public through web pages or API responses, where they are listed and categorized for easy user access, and a search function is provided to help users efficiently find the prompts they need.

[1026] User prompt usage request

[1027] The user selects a prompt from the published prompts and sends a usage request to the server from the device, requesting a specific prompt using the prompt's hash code.

[1028] Payment and confirmation of usage fees

[1029] The server receives the usage request and checks the proposed usage fee. The user pays the specified usage fee using a credit card or electronic money. The server verifies and confirms the completion of the payment.

[1030] Releasing the encrypted prompt

[1031] Once payment is confirmed, the server releases the encrypted prompts and provides them to the user's device, where they are decrypted and the user can use the purchased prompts.

[1032] Return of profits

[1033] The server returns a portion of the usage fee to the prompt creator based on a revenue sharing algorithm. For example, if the usage fee is 100 yen, 50 yen of that will be returned to the creator. This return will serve as an incentive for prompt creators to continue providing high-quality prompts.

[1034] Specific examples

[1035] For example, User A creates a "prompt to generate a picture of a cat" and uploads it to the "Prompt Bank" system. The server receives the prompt, hashes it using the SHA-256 algorithm, assigns a value of 100 yen, and publishes it. User B selects that prompt, sends a usage request, and makes payment. After the server confirms the payment, it releases the prompt and provides it to User B, and User A receives 50 yen in revenue. This process allows users to receive compensation for the valuable prompts they send out.

[1036] This allows the Prompt Bank system to seamlessly implement the entire process of registering, evaluating, publishing, using, and giving back prompts, efficiently promoting the dissemination of prompts and providing fair rewards to creators.

[1037] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1038] Processing flow and specific explanation

[1039] Step 1:

[1040] User creates and uploads prompts

[1041] Input: Prompt "Prompt to generate a picture of a cat"

[1042] Output: Sending a prompt to the server

[1043] Specific actions

[1044] The user creates a prompt for the generative AI model and enters it into the device's input screen. When the user presses the "Register" button, the prompt is sent to the server.

[1045] Step 2:

[1046] The server receives the prompt and confirms it.

[1047] Input: User uploaded prompt text

[1048] Output: Check the format and content of the prompt statement

[1049] Specific actions

[1050] The server analyzes and checks the format (e.g., text format) and content (e.g., whether it contains useful information) of the received prompt. The server uses a specific algorithm to evaluate the appropriateness of the content and filter out inappropriate content.

[1051] Step 3:

[1052] The server hashes and stores the prompt

[1053] Input: Confirmed prompt text

[1054] Output: Hash value of the prompt statement and the record stored in the database

[1055] Specific actions

[1056] The server hashes the prompt using the SHA-256 algorithm to generate a unique identifier, and stores the hash value and the original prompt in an internal database.

[1057] Step 4:

[1058] Server prompt evaluation and rating

[1059] Input: hashed prompt text

[1060] Output: Valued prompt sentences and their evaluation results

[1061] Specific actions

[1062] The server evaluates the prompt using machine learning models and evaluators. Based on the evaluation results, the server assigns an economic value (e.g., 100 yen) to the prompt. This evaluation is performed using text analysis and natural language processing models.

[1063] Step 5:

[1064] Server prompt public

[1065] Input: Valued prompt sentence

[1066] Output: List of published prompt statements

[1067] Specific actions

[1068] The server exposes the valued prompts as publicly accessible web pages or API responses, including appropriate formatting and search functionality.

[1069] Step 6:

[1070] The user selects the prompt and submits a request for use.

[1071] Input:Select the published prompt sentence

[1072] Output: Usage request to the server

[1073] Specific actions

[1074] The user selects a prompt from the list of available prompts and sends a usage request to the server from their device. The request includes the hash code of the prompt.

[1075] Step 7:

[1076] The server checks the usage fee

[1077] Input: User request

[1078] Output: Usage fee and payment confirmation

[1079] Specific actions

[1080] The server receives the usage request and checks the proposed usage fee. The user pays using a credit card or electronic money, and the server verifies and confirms the payment.

[1081] Step 8:

[1082] Server releases encrypted prompt

[1083] Input: Payment confirmed request

[1084] Output: Decoded prompt sentence

[1085] Specific actions

[1086] Once the payment is confirmed, the server decrypts the original encrypted prompt text and provides it to the user's terminal, where the user can use the specified prompt text.

[1087] Step 9:

[1088] Server returns profits

[1089] Input: Usage Fee Revenue

[1090] Output: Reward amount to prompt creator

[1091] Specific actions

[1092] The server will then return a portion of the fee to the prompt creator based on a revenue sharing algorithm. For example, if the fee is 100 yen, 50 yen will be returned to the creator. The refund amount will be reflected in the creator's account.

[1093] (Application example 1)

[1094] 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."

[1095] In conventional prompt management systems, the value of prompts created by users is evaluated centrally, which hinders the smooth distribution of prompts among users. Furthermore, the quality and usefulness of prompts are not adequately evaluated, which means that high-quality prompts are sometimes not properly evaluated. Furthermore, it is difficult for users to efficiently find prompts, which hinders the promotion of prompt usage.

[1096] 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.

[1097] In this invention, the server includes means for rating and assigning values ​​to prompts based on rating information from other users, means for prioritizing prompts based on the rating information and recommending them to other users, and means for analyzing the content of prompts and checking whether they are in an appropriate format. This facilitates the smooth distribution of prompts among users, ensures that high-quality prompts are appropriately rated, and enables users to efficiently find the prompts they need.

[1098] A "User" is an individual or organization that uses the system to create, upload, rate, select, pay for, or otherwise interact with prompts.

[1099] A "prompt" is text data that includes input instructions, guidelines, scripts, commands, etc. for a generative AI model.

[1100] "Server" means a computer system that receives, analyzes, hashes, stores, evaluates, and publishes prompts, and releases and provides encrypted prompts.

[1101] "Hashing" is the process of converting the contents of the prompt into a unique identifier using an algorithm such as SHA-256.

[1102] The "database" is a collection of information for managing hashed prompts, their evaluation information, and usage history.

[1103] "Valuing" is the process of calculating and assigning an economic value to a prompt based on its quality and usefulness.

[1104] "Publicly available" means making the valued prompt accessible to multiple users.

[1105] A "use request" is a request that a user sends to a server to use a particular prompt.

[1106] A "usage fee" is a fee paid by a user to use a published prompt.

[1107] "Rating information" is information about ratings and feedback given by other users to a particular prompt.

[1108] "Priority" refers to the display order when recommending a prompt to other users based on the prompt's evaluation information.

[1109] "Recommending" means preferentially displaying a particular prompt to other users and promoting its use.

[1110] The system for implementing this invention allows users to create and upload prompts, and manages their value assessment, publication, use, payment, and redemption. The main components of the system are a user interface for uploading prompts, a server, and a user interface for using prompts.

[1111] 1. Prompt registration of users

[1112] Users create prompts and upload them to the system from their smartphones or other devices. The uploaded prompts are received by the server. Specifically, users enter text data, such as a "prompt to generate a cat image," and send it to the system.

[1113] 2. Receiving and confirming the prompt on the server

[1114] The server checks the content of the received prompt and parses it to ensure it is in the correct format. Improperly formatted prompts are filtered out at this stage.

[1115] 3. Hashing and storing prompts

[1116] The server hashes the prompt using the SHA-256 algorithm and stores the result in a database, which uniquely identifies the prompt.

[1117] 4. Evaluating and Valuing Prompts

[1118] The server determines the value of prompts based on the rating information received from other users, and also prioritizes and recommends prompts to other users.

[1119] 5. Publicly displaying prompts

[1120] The valued prompts are then published as user-accessible web pages or API responses, allowing users to easily view and select from them.

[1121] 6. User Prompts

[1122] The user selects a published prompt and sends a request to the server to use it, along with the hash code of the prompt they want to use.

[1123] 7. Payment and Confirmation of Usage Fees

[1124] The server receives the usage request and checks the usage fee. The user pays using a credit card or electronic money. The server checks the payment and updates the information.

[1125] 8. Releasing the Encrypted Prompt

[1126] After the server verifies the payment, it releases and provides the encrypted prompt to the user, allowing them to use the prompt they specified.

[1127] 9. Return of profits

[1128] The server returns a portion of the usage fee to the prompt creator, the user, so that the user can receive appropriate compensation for the high-quality prompts they have created.

[1129] As a concrete example, consider a "prompt for generating cat images." A user uploads this prompt to the system, and other users rate it, assigning it a value. After that, another user selects a published prompt, confirms its value, and pays a fee to use it. After the server confirms the payment, it releases the encrypted prompt and provides it to the user. This entire process is performed automatically by the system.

[1130] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1131] Step 1:

[1132] A user creates a prompt and uploads it to the system using a terminal. To do this, the user enters text data, such as "a prompt to generate a cat image," and clicks the upload button. The input is the text data, and the output is the prompt sent to the server.

[1133] Step 2:

[1134] The server receives the uploaded prompt and checks its content. Specifically, the server parses the prompt to see if it is valid and checks its format and content. The input is the uploaded prompt, and the output is the parsing result (valid or invalid).

[1135] Step 3:

[1136] The server hashes the prompt using the SHA-256 algorithm and stores the result in a database. The input is the prompt text data, and the output is the hashed data.

[1137] Step 4:

[1138] The server evaluates the value of the prompt based on the rating information received from other users. This evaluation is performed using a machine learning model, which assigns an economic value to the prompt. The input is the rating information and the prompt, and the output is the valued prompt.

[1139] Step 5:

[1140] The server publishes the valued prompts to the public, where they are displayed as user-accessible web pages or API responses. The input is the valued prompt, and the output is the published prompt.

[1141] Step 6:

[1142] The user selects a published prompt and sends a usage request from the terminal to the server. The input is the published prompt and its hash code, and the output is the usage request sent to the server.

[1143] Step 7:

[1144] The server receives the usage request and checks the usage fee. At this time, the server retrieves the fee information from the database and presents it to the user. The input is the usage request, and the output is the fee information.

[1145] Step 8:

[1146] The user pays the displayed usage fee. This payment is made by means of a credit card, electronic money, etc. The input is fee information and payment information, and the output is confirmation of payment completion.

[1147] Step 9:

[1148] After the server confirms the payment, it releases the encrypted prompt and provides it to the user. Specifically, the server decrypts the prompt and sends it to the user's device. The input is the payment confirmation and the encrypted prompt, and the output is the decrypted prompt.

[1149] Step 10:

[1150] The server returns a portion of the earned usage fees to the prompt creator. The server calculates the amount of the return based on a revenue sharing algorithm and reflects it in the creator's account. The input is the usage fee and creator information, and the output is a reflection of the return amount.

[1151] 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.

[1152] The "Prompt Bank" system of this invention is a platform for assigning value to, managing, and distributing prompts created by users. The system includes the main components of a server, terminals, and users, and by combining it with an emotion engine, it has the ability to evaluate prompts and make recommendations based on the user's emotions.

[1153] System Overview

[1154] (User prompt registration)

[1155] The user creates a prompt and uploads it to the system. The prompt is uploaded from the user's terminal. At this time, the emotion engine recognizes the user's emotional state and sends data including the user's current emotion to the server as prompt information.

[1156] (receive and acknowledge prompts)

[1157] The server receives the prompt uploaded by the user, validates it, including checking that it is in the correct format, hashes it, generates a unique identifier, and stores it in a database.

[1158] (Evaluating and Valuing Prompts)

[1159] The server evaluates prompts by using an emotion engine to modify their value based on the user's emotion. Specifically, the emotion engine analyzes the user's emotion data and evaluates the quality of the prompt according to the emotion. Based on this evaluation result, the server assigns an economic value (e.g., 100 yen) to the prompt.

[1160] (Public release of prompts)

[1161] The server lists the valued prompts and makes them publicly available, allowing users to select from the list.

[1162] (Using user prompts and emotion recognition)

[1163] The user selects a prompt from the published prompts and sends a request to use it from the device to the server. The device then sends the hash code of the selected prompt along with the latest emotion data recognized by the emotion engine to the server.

[1164] (Payment and confirmation of usage fees)

[1165] The server receives the usage request and checks the usage fee. It analyzes the user's level of interest based on emotional data from the emotion engine and fine-tunes the fee if necessary. The user pays the proposed usage fee and the payment is completed. After the server confirms the payment, it releases an encrypted prompt and sends it to the user's device.

[1166] (Recommendation based on emotional data)

[1167] The emotion engine continuously collects user emotional data and stores it in a database. The server analyzes this data to recommend personalized prompts based on the user's interests and emotions. For example, if a user is feeling stressed, the server can recommend prompts with a relaxing effect.

[1168] (Return of profits)

[1169] The server returns a portion of the obtained usage fee to the creator of the prompt. The amount of the refund based on the usage fee is also recorded in the database using the user's usage emotion data generated by the emotion engine.

[1170] Specific examples

[1171] As a concrete example, user A creates a "prompt for generating a cat image" and uploads it to the system. The emotion engine recognizes the user's emotion at the time of uploading as "excitement," and this is added to the prompt information. The server receives the prompt, evaluates its quality, and assigns a value of 100 yen, taking the emotion information into consideration. When this prompt is made public and user B wishes to use it and sends a usage request to the server, the emotion engine recognizes the user's current emotion as "excitement." The server presents a usage fee of 100 yen, and user B pays. After confirming the payment, the server releases the encrypted prompt and sends it to user B's device. Finally, the server returns 50 yen of the 100 yen revenue to user A, the prompt creator.

[1172] In this way, the "Prompt Bank" system, which combines an emotion engine, utilizes users' emotional data to value and recommend prompts, thereby promoting the spread of high-quality prompts and providing appropriate rewards to their creators.

[1173] The processing flow will be explained below.

[1174] Step 1:

[1175] A user creates a prompt and uploads it to the system.

[1176] Specifically, the user inputs the required prompt content on the device's input screen, and the emotion engine recognizes the user's emotional state in real time. When the user presses the "upload" button, the prompt data and emotion data are sent to the server.

[1177] Step 2:

[1178] The server receives the uploaded prompts from the user.

[1179] The server receives the HTTP POST request and stores the prompt data and emotion data in a temporary directory.

[1180] Step 3:

[1181] The server checks the uploaded prompt.

[1182] Specifically, the server checks the format of the prompt, parses the content for correctness, and notifies the user of formatting errors or incomplete content if necessary.

[1183] Step 4:

[1184] The server hashes the prompt to generate a unique identifier.

[1185] The server generates a hash code of the prompt using the SHA-256 algorithm and retrieves the result.

[1186] Step 5:

[1187] The server stores the hashed prompts in a database.

[1188] The server records the prompt's hash value, original content, emotion data, and creation time in a database.

[1189] Step 6:

[1190] The server evaluates the prompt and assigns a value.

[1191] The server uses an emotion engine to analyze the user's emotion data, evaluates the quality of the prompt based on the results, and assigns an economic value to the prompt (e.g., 100 yen).

[1192] Step 7:

[1193] The server publishes the valued prompts to the public.

[1194] Specifically, the server generates a list of valued prompts as an HTML page or API response and makes it publicly available.

[1195] Step 8:

[1196] The user selects the prompt they want to use from the publicly available prompts.

[1197] The user selects a specific prompt (e.g., hash code abc123) from the list of published prompts and presses the "Use" button.

[1198] Step 9:

[1199] The user's terminal transmits the hash code and emotion data of the selected prompt to the server.

[1200] Specifically, the latest emotion data is sent to the server along with the hash code of the prompt using an HTTP POST request from the user's device.

[1201] Step 10:

[1202] The server receives the usage request and checks the usage fee.

[1203] The server retrieves the value information of the prompt from the database, extracts the usage fee (e.g., 100 yen), and presents it to the user.

[1204] Step 11:

[1205] The user pays a usage fee.

[1206] Specifically, the user enters their credit card information to complete the payment process, and the payment information is encrypted and sent to the server.

[1207] Step 12:

[1208] The server verifies the user's payment.

[1209] The server receives the response from the payment service, verifies whether the payment was successful, and records the payment information in a database.

[1210] Step 13:

[1211] The server releases the encrypted prompt and provides it to the user.

[1212] The server decodes the prompt and sends it to the user's device, possibly along with associated emotional data.

[1213] Step 14:

[1214] The server returns a portion of the usage fee earned to the creator.

[1215] The server will then credit a portion of the revenue earned based on a revenue sharing algorithm to the creator's account and record the amount in a database. For example, 50 yen out of a 100 yen usage fee will be returned to the creator.

[1216] Step 15:

[1217] The server recommends prompts based on the emotion data.

[1218] Specifically, the server analyzes the user's emotional data collected from the emotion engine and recommends personalized prompts to the user. For example, if the user is feeling stressed, it will recommend prompts that have a relaxing effect.

[1219] Example 2

[1220] 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."

[1221] Conventional prompt management systems evaluate and value prompts without considering the user's emotions, which makes it difficult to value and recommend prompts that are in line with the user's needs and emotions. It is also difficult to provide appropriate rewards to prompt creators.

[1222] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1223] In this invention, the server includes means for acquiring user emotion data using an emotion engine and adding it to prompt information, means for the server to evaluate prompts and assign values ​​based on the emotion data, and means for the emotion engine to collect, save, and analyze user emotion data to make personalized recommendations. This makes it possible to evaluate and assign values ​​to prompts based on user emotions, thereby enabling the spread of high-quality prompts and the provision of appropriate rewards to their creators.

[1224] "User" means an entity that uses the system to create, upload, or use prompts.

[1225] A "prompt" refers to text data that expresses instructions or requests to a generative AI model.

[1226] "Terminal" refers to a digital device used by a user, such as a computer, smartphone, or tablet.

[1227] "Server" refers to a central digital computer system that receives, evaluates, hashs, stores, publishes, etc., prompts.

[1228] An "emotion engine" refers to software or hardware that recognizes a user's emotional state and processes it as data.

[1229] "Hashing" refers to a cryptographic technique for converting a prompt into a unique identifier.

[1230] "Database" means a digital collection of information for managing and storing prompts and related data.

[1231] "Assigning a value" refers to the process of assigning an economic value to a prompt.

[1232] "Public" refers to making a valued prompt available for other users to view.

[1233] "Usage Request" refers to a request sent by a user to use a published prompt.

[1234] "Usage Fee" refers to the cost incurred when using Prompt.

[1235] "Rebate" refers to returning a portion of the usage fee to the prompt creator as compensation.

[1236] "Personalized recommendations" refers to suggesting prompts that are individually optimized based on the user's emotional data.

[1237] A "machine learning model" refers to an algorithmic method that learns from data and evaluates prompts based on the analysis results.

[1238] The "Prompt Bank" system of this invention is a platform for assigning value to, managing, and distributing prompts created by users. In addition to the main components of the system, which are a server, terminals, and users, it also combines an emotion engine to enable prompt evaluation and recommendations based on the user's emotions.

[1239] Hardware and software configuration

[1240] server

[1241] The server functions as a central processing unit and performs the following processes:

[1242] Receiving and hashing prompts

[1243] Save prompts to the database

[1244] Data analysis from the emotion engine

[1245] Valuing and Evaluating Prompts

[1246] Processing public availability and usage requests

[1247] Checking usage fees and processing payments

[1248] Fee rebates and management

[1249] Terminal

[1250] The devices used by users include computers, smartphones, tablets, etc. These devices perform the following functions:

[1251] Prompt creation and upload

[1252] Select a prompt and submit a request

[1253] Collecting and transmitting emotional data

[1254] Emotion Engine

[1255] The emotion engine has the following functions:

[1256] Recognizing the user's emotional state in real time

[1257] Collecting user emotion data

[1258] Adding emotional data to prompt information

[1259] Recommending prompts based on emotion data

[1260] Data processing and calculation

[1261] When a user creates a prompt and uploads it to the system from their device, the emotion engine collects the user's emotional state and sends it to the server as prompt information. The server receives the prompt, checks its content, and checks whether it is in the correct format. The server then hashes the prompt to generate a unique identifier and stores it in a database.

[1262] The server analyzes the data from the emotion engine and evaluates the quality of the prompts. Based on the evaluation results, the server assigns economic values ​​to the prompts. The server then makes the valued prompts public, allowing users to select prompts.

[1263] When a user requests to use a published prompt, the device sends a usage request including emotion data to the server. The server receives the usage request, checks and adjusts the usage fee based on the emotion data, and completes the payment once the user pays the fee. After the server confirms the payment, it releases the encrypted prompt and sends it to the device.

[1264] The emotion engine continuously collects user emotion data, and the server analyzes the data to recommend personalized prompts.

[1265] Specific examples

[1266] For example, user A creates a "prompt for generating a cat image" and uploads it to the system. The emotion at the time of uploading is recognized as "excitement," and this is added to the prompt information. The server receives the prompt, evaluates its quality, and assigns a value of 100 yen, taking into account the emotional information. This prompt is made public, and user B wants to use it. When a usage request is sent to the server, the emotion engine recognizes the user's current emotion as "excitement." The server presents a usage fee of 100 yen, and user B pays. After confirming the payment, the server releases the encrypted prompt and sends it to user B's device. Finally, the server returns 50 yen of the 100 yen revenue to user A.

[1267] By combining this system with an emotion engine, it is possible to value and recommend prompts based on the user's emotions, thereby promoting the spread of high-quality prompts and providing appropriate rewards to their creators.

[1268] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1269] Step 1: User creates and uploads prompt

[1270] The user opens the prompt creation screen on their device and enters a prompt for the generative AI model. When the user presses the upload button, the device sends the prompt to the server. At this time, the emotion engine recognizes the user's emotional state in real time and sends the emotional data along with it. The input is the prompt and emotional data, and the output is uploaded to the server.

[1271] Step 2: Receive and confirm the prompt

[1272] The server receives prompts uploaded by users. At this time, it checks whether the prompts are in the correct format. Specifically, it checks the text length of the prompt and whether it contains specific keywords. The input is the uploaded prompt and emotion data, and the output is the prompt format check result.

[1273] Step 3: Hash and save the prompt

[1274] The server hashes the prompt sentence and generates a unique identifier. The server then stores the prompt sentence, emotion data, and unique identifier in a database. The input is the confirmed prompt sentence and emotion data, and the output is storage in the database.

[1275] Step 4: Evaluate and value the prompt

[1276] The server uses an emotion engine to analyze the user's emotional data. Based on the results of this analysis, the server evaluates the quality of the prompt and assigns an economic value (e.g., 100 yen). The input is the emotional data and the prompt, and the output is the assigned value.

[1277] Step 5: Make the prompt public

[1278] The server compiles a list of valued prompts and makes it publicly available for users to view. The input is the valued prompt text, and the output is the published list of prompts.

[1279] Step 6: User requests prompt usage

[1280] The user browses a list of publicly available prompts on their device and selects the prompt they want to use. Then, they send a usage request from their device to the server. At this time, the emotion engine recognizes the user's latest emotion data and sends it along with the request to the server. The input is the usage request and emotion data, and the output is the request sent to the server.

[1281] Step 7: Check and settle usage fees

[1282] The server receives the usage request and analyzes the emotional data to assess the user's interest level. Based on this, it checks and possibly fine-tunes the usage fee. The user pays the fee, and the server confirms the payment. The input is the usage request and emotional data, and the output is the adjusted usage fee and its payment confirmation.

[1283] Step 8: Sending the Encrypted Prompt

[1284] After the server confirms the payment, it releases the encrypted prompt and sends it to the user's terminal. The input is the payment confirmation and the prompt text, and the output is the prompt sent to the terminal.

[1285] Step 9: Recommendation based on emotion data

[1286] The emotion engine continuously collects user emotion data, and the server analyzes the data to generate personalized recommendations. The input is the collected emotion data, and the output is personalized prompt recommendations.

[1287] Step 10: Returning profits

[1288] The server returns a portion of the revenue based on the prompt usage by the user to the prompt creator. The server also references the emotion data collected by the emotion engine to calculate the amount of return. The input is the usage fee and emotion data, and the output is the calculation and reflection of the return amount.

[1289] (Application example 2)

[1290] 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."

[1291] Conventional prompt management systems do not evaluate or recommend prompts based on the user's emotions, making it difficult to accurately evaluate the quality of prompts or to provide customized recommendations for individual users. Furthermore, it is difficult to provide content that matches the user's current emotional state, resulting in a decrease in user satisfaction. The present invention aims to solve these problems by enabling prompt evaluation and recommendation based on the user's emotions and providing content in accordance with emotional data.

[1292] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1293] In this invention, the server includes means for a user to create and upload prompts, means for the server to receive the uploaded prompts and check the contents of the prompts, means for the server to hash the prompts and store the hashed results in a database, means for the server to rate and assign values ​​to the prompts, means for the server to publicly publish the valued prompts, means for a user to select a published prompt and send a usage request, means for the server to receive the usage request and check a usage fee, means for the user to pay the usage fee, means for the server to confirm the payment and release and provide the encrypted prompts, and means for the server to return a portion of the usage fee to the creator, as well as means for rating and recommending prompts based on the user's emotions using an emotion engine, and means for recommending content according to the user's emotion data. This not only enables proper evaluation of the quality of prompts and recommendation of customized prompts to individual users, but also makes it possible to provide appropriate content according to the user's current emotional state.

[1294] A "prompt" is a statement written in the form of an instruction, question, or command given to a generative AI model.

[1295] "Uploading" is the act of a user sending data or files from their device to a server.

[1296] A "server" is a computer system that provides services to other computers (clients) on a network.

[1297] "Hashing" is a cryptographic process that converts original data into a fixed-length string of characters that can be used as a unique identifier.

[1298] A "database" is a collection of structured data that allows for efficient management and retrieval of large amounts of data.

[1299] An "emotion engine" is a software technology for analyzing a user's emotional state and collecting and utilizing that data.

[1300] "Valuing" is the act of assigning economic value or valuation to specific data or items.

[1301] "Publishing" means making certain data or information accessible to other users within the system.

[1302] A "use request" is a request that a user sends to the effect that he or she wishes to use a published prompt or service.

[1303] "Usage Fee" means money paid for the use of a particular service or item.

[1304] "Encryption" is a technology that codes data using a specific algorithm to protect it from easy access by third parties.

[1305] "Return" is the act of giving back a portion of the revenue or profits earned to a specific cause or person.

[1306] "Emotional Data" means information about the user's emotional state that is analyzed and collected by the Emotion Engine.

[1307] "Recommendation" is the act of a system suggesting optimal content or services based on a user's behavior and emotions.

[1308] "Content" refers to digital data and information such as music, video, text, and images provided through systems and services.

[1309] This invention relates to a prompt bank system incorporating an emotion engine. Specifically, it provides a method for uploading prompts created by users and analyzing and evaluating them using the emotion engine. The server assigns an appropriate value based on the prompt evaluation results and publishes them. Furthermore, the system provides recommended content based on the user's latest emotion data.

[1310] Hardware and Software Configuration

[1311] 1. The server is the central processing unit for managing, evaluating, storing, and publishing prompts. It includes hashing technology, a database management system, and machine learning models (e.g., TensorFlow).

[1312] 2. An emotion engine is a software technology that analyzes a user's emotional data, recognizes their emotional state, and generates corresponding data. A typical emotion analysis module is the sentiment_analysis library.

[1313] 3. User terminals are devices used to create, upload, view, and process payments for prompts. These include smartphones, tablets, and PCs.

[1314] 4. The payment processing module is a system that allows users to make payments and uses the APIs of Stripe and PayPal.

[1315] System details

[1316] 1. Create and upload a prompt:

[1317] Users create prompts and upload them to the system from their own devices. For example, if a user creates a prompt called "Relaxing music for stress relief," the system will recognize the user's current emotional state as "Relaxed" using the emotion engine.

[1318] 2. Receiving and Evaluating Prompts:

[1319] The server receives the uploaded prompts, hashes them, and stores them in a database. It then uses an emotion engine to analyze the user's emotional data and evaluate the quality of the prompts. Based on the evaluation results, economic values ​​are assigned to the prompts.

[1320] 3. Publishing and Recommending Prompts:

[1321] The server publishes the valued prompts to the public. Other users can browse the published prompts and select the prompts they want to use. The emotion engine then recommends the most appropriate prompts to the user based on the latest emotional data analyzed.

[1322] 4. Payment Processing and Prompts:

[1323] The user selects a published prompt and sends a usage request to the server. The server checks the usage fee, and the user pays. Once the payment is confirmed, the server releases the encrypted prompt and sends it to the user's device.

[1324] 5. Return of profits:

[1325] The server returns a portion of the usage fee to the prompt creator. Using usage emotion data from the emotion engine, the server accurately calculates the monetary amount of the return and records it in a database.

[1326] Example prompt

[1327] For example, if User A wants to recommend "relaxing music to relieve stress," he or she can create a prompt like this:

[1328] "Recommend relaxing music for stress relief."

[1329] This system improves the user experience by enabling the user to value prompts based on their emotional state and recommend content that is best suited to each individual user.

[1330] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1331] Step 1:

[1332] The user creates a prompt and uploads it from the device to the server. The input includes the prompt text "Please recommend some relaxing music to relieve stress." and the user's current emotional data. The device creates the prompt, recognizes the user's emotional state using an emotion engine, and sends the data including the prompt to the server. The server then receives this data.

[1333] Step 2:

[1334] The server verifies the received prompt, hashes it, and stores it in a database. The input includes the uploaded prompt data. The server verifies the prompt content, checks that it is in the correct format, and then uses hashing techniques to generate a unique identifier. The server then stores the hashed prompt in a database. The output is the hashed data.

[1335] Step 3:

[1336] The server evaluates the prompt content using an emotion engine and assigns a value. The input includes the prompt content and the user's emotion data. The server uses the emotion engine to analyze the user's emotion data and evaluates the quality of the prompt based on this. Based on the evaluation result, an economic value is assigned to the prompt. For example, a value of 100 yen is assigned. The output is the evaluation result and the prompt with the assigned value.

[1337] Step 4:

[1338] The server publishes valued prompts to the public. The input includes the valued prompt data. The server publishes the prompts to the public in a list format that can be accessed by other users. The output is a list of published prompts.

[1339] Step 5:

[1340] The user selects a published prompt and sends a usage request from the device to the server. The input includes a list of published prompts and the user's selection. The user browses the published prompts on the device and selects the prompt they want to use. The latest emotion data is also sent along with the usage request. The output is the selected prompt and the associated emotion data.

[1341] Step 6:

[1342] The server receives the usage request and checks the usage fee. The input includes the user's usage request and associated emotion data. The server checks the usage fee and possibly fine-tunes the fee based on the analysis results of the emotion engine. The output is the proposed usage fee.

[1343] Step 7:

[1344] The user pays the usage fee. The input includes the proposed usage fee and the user's payment information. The terminal uses the payment processing module to pay the usage fee. The server confirms the payment. The output is payment confirmation information.

[1345] Step 8:

[1346] The server verifies the payment, releases and provides an encrypted prompt. The input includes the payment confirmation information and the encrypted prompt. The server reverses the encryption process and sends the prompt to the user's terminal. The output is the released prompt.

[1347] Step 9:

[1348] The server returns a portion of the earned usage fee to the prompt creator. The input includes the usage fee and related prompt information. The server uses data from the emotion engine to calculate the refund amount and send it to the creator. The output is information indicating that the refund process has been completed.

[1349] Step 10:

[1350] The server continuously collects user emotion data and stores it in a database. The input includes the user emotion data. The server uses an emotion engine to retrieve the emotion data and stores it in a database. The output is an updated database.

[1351] Step 11:

[1352] The server analyzes the collected emotional data and recommends appropriate content to the user. The input includes the emotional data stored in the database. The server analyzes the emotional data using a machine learning model and recommends the most suitable content to the user. The output is the recommended content.

[1353] 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.

[1354] 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.

[1355] 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.

[1356] [Fourth embodiment]

[1357] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1358] 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.

[1359] 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).

[1360] 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.

[1361] 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.

[1362] 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).

[1363] 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.

[1364] 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.

[1365] 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.

[1366] 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.

[1367] 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.

[1368] 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.

[1369] 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."

[1370] The "Prompt Bank" system of this invention is a platform that values, manages, and distributes prompts created by users. This system consists of three main components: a server, terminals, and users.

[1371] System Overview

[1372] (User prompt registration)

[1373] The user creates a prompt and uploads it to the system. The prompt is uploaded by the user, who sets the input data for the prompt on the input screen. When the user uploads a new prompt to the system, the server receives the prompt.

[1374] (receive and acknowledge prompts)

[1375] The server receives the uploaded prompt and checks its content. Specifically, the server analyzes the prompt to ensure it is formatted and properly formatted, and performs format and content checks as necessary. Based on the results of this analysis, the server proceeds to the next step.

[1376] (prompt hashing and saving)

[1377] The server hashes the prompt content and stores the result in a database using an algorithm such as SHA-256 to generate a unique identifier for the prompt, which uniquely identifies the prompt within the database.

[1378] (Evaluating and Valuing Prompts)

[1379] The server evaluates the prompt and assigns a value to it. This evaluation is based on the judgment of machine learning models and evaluators, and an economic value is assigned according to the quality and usefulness of the prompt. For example, the server evaluates the prompt and assigns a value of 100 yen as a result.

[1380] (Public release of prompts)

[1381] The server publishes the valued prompts to the public, either as a web page or an API response that can be accessed by users. The prompts are displayed in an appropriate format upon publication, and users can choose the prompts they want to use.

[1382] (Using user prompts)

[1383] The user selects the prompt they want to use from the published prompts and sends a usage request from the terminal to the server. The terminal then sends the hash code of the selected prompt to the server and makes a usage request.

[1384] (Payment and confirmation of usage fees)

[1385] The server receives the usage request and checks the usage fee. The user pays the requested fee. Based on the analysis results, the server returns fee information to the user, who then completes the payment. Payment is made by credit card, electronic money, or other means, and the server confirms the payment.

[1386] (Release encrypted prompt)

[1387] Once the server confirms the payment, it releases the encrypted prompt and provides it to the user. At this time, the server decrypts the prompt and sends it to the user's device. Once this transmission is complete, the user can use the prompt they specified.

[1388] (Return of profits)

[1389] The server returns a portion of the usage fee to the prompt creator. This return is based on a revenue sharing algorithm, and the server reflects the return amount in the creator's account. For example, if the prompt usage fee is 100 yen, the server can return 50 yen to the creator.

[1390] Specific examples

[1391] As a specific example of use, user A creates a "prompt for generating cat images" and uploads it to the system. The server receives the prompt, hashes it, rates it, and publishes it with a value of 100 yen. User B selects the published prompt and wishes to use it, sending a usage request to the server. User B pays the 100 yen usage fee, and after the server confirms the payment, it releases the encrypted prompt and provides it to user B. Finally, the server returns 50 yen of the 100 yen obtained to user A.

[1392] In this way, the Prompt Bank system values ​​and distributes prompts created by users, thereby promoting the spread of high-quality prompts and providing appropriate compensation to their creators.

[1393] The processing flow will be explained below.

[1394] Step 1:

[1395] A user creates a prompt and uploads it to the system.

[1396] Specifically, the user enters the required data on the prompt input screen and presses the "upload" button.

[1397] Step 2:

[1398] The server receives the uploaded prompts from the user.

[1399] Specifically, the server receives the HTTP POST request and stores the prompt data in a temporary storage directory.

[1400] Step 3:

[1401] The server checks the uploaded prompt.

[1402] Specifically, the server checks the file format, analyzes some of the content, and verifies whether it is in the correct format.

[1403] Step 4:

[1404] The server hashes the prompt to generate a unique identifier.

[1405] Specifically, the hash value of the prompt is calculated using the SHA-256 algorithm and the result is obtained.

[1406] Step 5:

[1407] The server stores the hashed prompts in a database.

[1408] Specifically, relevant information such as the prompt's hash value, original content, and creation time is recorded in a database.

[1409] Step 6:

[1410] The server evaluates the prompt and assigns a value.

[1411] Specifically, the quality is evaluated using machine learning models and human evaluators, and an appropriate monetary value (e.g., 100 yen) is set.

[1412] Step 7:

[1413] The server lists the valued prompts and makes them publicly available.

[1414] Specifically, a prompt list is generated as a public HTML page or API response, making it accessible to users.

[1415] Step 8:

[1416] The user selects the prompt they want to use from the publicly available prompts.

[1417] Specifically, the user selects a specific prompt (e.g., hash code abc123) from a list of published prompts.

[1418] Step 9:

[1419] The user's terminal transmits the hash code of the selected prompt to the server and makes a usage request.

[1420] As a specific example, an HTTP POST request is used to send a hash code of the prompt to communicate intent to the server.

[1421] Step 10:

[1422] The server receives the usage request and checks the usage fee.

[1423] Specifically, the value information of the prompt is obtained from the database, and the usage fee (e.g., 100 yen) is extracted and communicated to the user.

[1424] Step 11:

[1425] The user pays a usage fee.

[1426] Specifically, the payment procedure is completed using a payment method such as a credit card or electronic money.

[1427] Step 12:

[1428] The server verifies the user's payment.

[1429] Specifically, it receives a response from the payment service and records in a database whether the payment was successful.

[1430] Step 13:

[1431] The server releases the encrypted prompt and provides it to the user.

[1432] Specifically, the prompt is decrypted and the prompt content is sent to the user's terminal.

[1433] Step 14:

[1434] The server returns a portion of the usage fee earned to the creator of the prompt.

[1435] Specifically, the amount is calculated based on a revenue distribution algorithm and reflected in the creator's account.

[1436] Example 1

[1437] 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."

[1438] There is a lack of a platform for properly evaluating, managing, and distributing prompts for generative AI models. It is necessary to guarantee the quality of user-created prompts and assign economic value to them, thereby providing appropriate rewards to prompt creators and promoting the spread of high-quality prompts. Furthermore, there is no system for efficiently publishing prompts and making them available to other users.

[1439] 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.

[1440] In this invention, the server includes: a means for a user to create and upload prompts for a generative AI model; a means for the server to receive the uploaded prompts and verify their format and content; a means for the server to hash the prompts using the SHA-256 algorithm and store the results in a database; a means for the server to evaluate the prompts using a machine learning model or an evaluator and assign values ​​to them; a means for the server to publicly publish the valued prompts via a webpage or API response; a means for a user to select a published prompt and send a usage request; a means for receiving a usage request and confirming the proposed usage fee; a means for a user to pay the usage fee by credit card or electronic money; a means for confirming the payment, releasing the encrypted prompt, and providing it to the user's device; and a means for returning a portion of the obtained usage fee to the prompt creator based on a revenue sharing algorithm. This allows for efficient management of the entire process from prompt creation to evaluation, publication, usage, and reward distribution, enabling the spread of high-quality prompts and appropriate rewards to creators.

[1441] "User" refers to a person or organization that creates prompts for generative AI models and registers and uses them in the system.

[1442] "Prompts for a Generative AI Model" refers to instructions or datasets created to be input to a Generative AI Model.

[1443] "Uploading a prompt" refers to the act of sending a prompt created by a user to the server and registering it.

[1444] "Server" refers to a computer system that receives, validates, hashes, evaluates, stores, and publishes prompts, processes redemption requests, verifies fees, releases prompts, and redeems them.

[1445] The "SHA-256 algorithm" is a hash function used to uniquely identify the contents of a prompt.

[1446] "Hashing" refers to the process of converting the contents of the prompt into a fixed-length string and generating a unique identifier.

[1447] A "machine learning model" is a type of artificial intelligence used to evaluate prompts.

[1448] "Evaluator" refers to an entity responsible for judging the quality of prompts using machine learning models or manually.

[1449] "Assigning a value" refers to the process of determining an economic value for a prompt based on the results of the prompt evaluation.

[1450] "Web Page" refers to the interface that a user accesses to review prompts, make selections, and make utilization requests.

[1451] "API response" refers to the response data returned by a server through an application program interface.

[1452] "Usage Request" refers to a request sent by a user to use a published prompt.

[1453] "Usage Fee" refers to the amount paid by a user to use a prompt.

[1454] "Credit cards and electronic money" refers to electronic payment methods used by users to pay usage fees.

[1455] "Encryption" refers to the process of converting the contents of a prompt into an unreadable form for security purposes.

[1456] "Releasing" refers to decrypting the encrypted prompt and making it available for use after the user pays the usage fee.

[1457] "Revenue Share Algorithm" refers to the calculation method used to appropriately return earned royalties to prompt creators.

[1458] This invention relates to a system called "Prompt Bank" for valuing, managing, and distributing prompts for generative AI models. This system is mainly composed of three elements: a server, a terminal, and a user.

[1459] System components and specific operations

[1460] Prompt registration for users

[1461] A user creates a prompt for a generative AI model and enters the prompt content into the device's input screen. The user then presses the "Register" button to send the prompt to the server. This operation is the first step for the user to widely publish their prompt and earn revenue by having other users use it. A specific example is when a user creates a "prompt for drawing a cat."

[1462] Receiving and acknowledging prompts

[1463] The server receives the prompt sent by the user and checks its format and content. During this check, the server analyzes the prompt to determine whether it is in the correct format and whether the content is inappropriate. This analysis process can be performed using commonly known software tools or custom-developed scripts.

[1464] Hashing and saving prompts

[1465] The server hashes the prompt using the SHA-256 algorithm. This hashing process generates a unique identifier. The generated hash value is stored in a database, ensuring the uniqueness of the prompt. A server computer is used as the hardware for high-speed calculations.

[1466] Evaluating and valuing prompts

[1467] The server evaluates the prompt using a machine learning model or evaluators. This evaluation determines the quality of the prompt and assigns an economic value to it. For example, a text analysis algorithm or a natural language processing model is used as the evaluation model. Based on the evaluation result of the prompt, a value of, for example, 100 yen is assigned.

[1468] Publicly available prompts

[1469] The server exposes the valued prompts to the public through web pages or API responses, where they are listed and categorized for easy user access, and a search function is provided to help users efficiently find the prompts they need.

[1470] User prompt usage request

[1471] The user selects a prompt from the published prompts and sends a usage request to the server from the device, requesting a specific prompt using the prompt's hash code.

[1472] Payment and confirmation of usage fees

[1473] The server receives the usage request and checks the proposed usage fee. The user pays the specified usage fee using a credit card or electronic money. The server verifies and confirms the completion of the payment.

[1474] Releasing the encrypted prompt

[1475] Once payment is confirmed, the server releases the encrypted prompts and provides them to the user's device, where they are decrypted and the user can use the purchased prompts.

[1476] Return of profits

[1477] The server returns a portion of the usage fee to the prompt creator based on a revenue sharing algorithm. For example, if the usage fee is 100 yen, 50 yen of that will be returned to the creator. This return will serve as an incentive for prompt creators to continue providing high-quality prompts.

[1478] Specific examples

[1479] For example, User A creates a "prompt to generate a picture of a cat" and uploads it to the "Prompt Bank" system. The server receives the prompt, hashes it using the SHA-256 algorithm, assigns a value of 100 yen, and publishes it. User B selects that prompt, sends a usage request, and makes payment. After the server confirms the payment, it releases the prompt and provides it to User B, and User A receives 50 yen in revenue. This process allows users to receive compensation for the valuable prompts they send out.

[1480] This allows the Prompt Bank system to seamlessly implement the entire process of registering, evaluating, publishing, using, and giving back prompts, efficiently promoting the dissemination of prompts and providing fair rewards to creators.

[1481] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1482] Processing flow and specific explanation

[1483] Step 1:

[1484] User creates and uploads prompts

[1485] Input: Prompt "Prompt to generate a picture of a cat"

[1486] Output: Sending a prompt to the server

[1487] Specific actions

[1488] The user creates a prompt for the generative AI model and enters it into the device's input screen. When the user presses the "Register" button, the prompt is sent to the server.

[1489] Step 2:

[1490] The server receives the prompt and confirms it.

[1491] Input: User uploaded prompt text

[1492] Output: Check the format and content of the prompt statement

[1493] Specific actions

[1494] The server analyzes and checks the format (e.g., text format) and content (e.g., whether it contains useful information) of the received prompt. The server uses a specific algorithm to evaluate the appropriateness of the content and filter out inappropriate content.

[1495] Step 3:

[1496] The server hashes and stores the prompt

[1497] Input: Confirmed prompt text

[1498] Output: Hash value of the prompt statement and the record stored in the database

[1499] Specific actions

[1500] The server hashes the prompt using the SHA-256 algorithm to generate a unique identifier, and stores the hash value and the original prompt in an internal database.

[1501] Step 4:

[1502] Server prompt evaluation and rating

[1503] Input: hashed prompt text

[1504] Output: Valued prompt sentences and their evaluation results

[1505] Specific actions

[1506] The server evaluates the prompt using machine learning models and evaluators. Based on the evaluation results, the server assigns an economic value (e.g., 100 yen) to the prompt. This evaluation is performed using text analysis and natural language processing models.

[1507] Step 5:

[1508] Server prompt public

[1509] Input: Valued prompt sentence

[1510] Output: List of published prompt statements

[1511] Specific actions

[1512] The server exposes the valued prompts as publicly accessible web pages or API responses, including appropriate formatting and search functionality.

[1513] Step 6:

[1514] The user selects the prompt and submits a request for use.

[1515] Input:Select the published prompt sentence

[1516] Output: Usage request to the server

[1517] Specific actions

[1518] The user selects a prompt from the list of available prompts and sends a usage request to the server from their device. The request includes the hash code of the prompt.

[1519] Step 7:

[1520] The server checks the usage fee

[1521] Input: User request

[1522] Output: Usage fee and payment confirmation

[1523] Specific actions

[1524] The server receives the usage request and checks the proposed usage fee. The user pays using a credit card or electronic money, and the server verifies and confirms the payment.

[1525] Step 8:

[1526] Server releases encrypted prompt

[1527] Input: Payment confirmed request

[1528] Output: Decoded prompt sentence

[1529] Specific actions

[1530] Once the payment is confirmed, the server decrypts the original encrypted prompt text and provides it to the user's terminal, where the user can use the specified prompt text.

[1531] Step 9:

[1532] Server returns profits

[1533] Input: Usage Fee Revenue

[1534] Output: Reward amount to prompt creator

[1535] Specific actions

[1536] The server will then return a portion of the fee to the prompt creator based on a revenue sharing algorithm. For example, if the fee is 100 yen, 50 yen will be returned to the creator. The refund amount will be reflected in the creator's account.

[1537] (Application example 1)

[1538] 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."

[1539] In conventional prompt management systems, the value of prompts created by users is evaluated centrally, which hinders the smooth distribution of prompts among users. Furthermore, the quality and usefulness of prompts are not adequately evaluated, which means that high-quality prompts are sometimes not properly evaluated. Furthermore, it is difficult for users to efficiently find prompts, which hinders the promotion of prompt usage.

[1540] 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.

[1541] In this invention, the server includes means for rating and assigning values ​​to prompts based on rating information from other users, means for prioritizing prompts based on the rating information and recommending them to other users, and means for analyzing the content of prompts and checking whether they are in an appropriate format. This facilitates the smooth distribution of prompts among users, ensures that high-quality prompts are appropriately rated, and enables users to efficiently find the prompts they need.

[1542] A "User" is an individual or organization that uses the system to create, upload, rate, select, pay for, or otherwise interact with prompts.

[1543] A "prompt" is text data that includes input instructions, guidelines, scripts, commands, etc. for a generative AI model.

[1544] "Server" means a computer system that receives, analyzes, hashes, stores, evaluates, and publishes prompts, and releases and provides encrypted prompts.

[1545] "Hashing" is the process of converting the contents of the prompt into a unique identifier using an algorithm such as SHA-256.

[1546] The "database" is a collection of information for managing hashed prompts, their evaluation information, and usage history.

[1547] "Valuing" is the process of calculating and assigning an economic value to a prompt based on its quality and usefulness.

[1548] "Publicly available" means making the valued prompt accessible to multiple users.

[1549] A "use request" is a request that a user sends to a server to use a particular prompt.

[1550] A "usage fee" is a fee paid by a user to use a published prompt.

[1551] "Rating information" is information about ratings and feedback given by other users to a particular prompt.

[1552] "Priority" refers to the display order when recommending a prompt to other users based on the prompt's evaluation information.

[1553] "Recommending" means preferentially displaying a particular prompt to other users and promoting its use.

[1554] The system for implementing this invention allows users to create and upload prompts, and manages their value assessment, publication, use, payment, and redemption. The main components of the system are a user interface for uploading prompts, a server, and a user interface for using prompts.

[1555] 1. Prompt registration of users

[1556] Users create prompts and upload them to the system from their smartphones or other devices. The uploaded prompts are received by the server. Specifically, users enter text data, such as a "prompt to generate a cat image," and send it to the system.

[1557] 2. Receiving and confirming the prompt on the server

[1558] The server checks the content of the received prompt and parses it to ensure it is in the correct format. Improperly formatted prompts are filtered out at this stage.

[1559] 3. Hashing and storing prompts

[1560] The server hashes the prompt using the SHA-256 algorithm and stores the result in a database, which uniquely identifies the prompt.

[1561] 4. Evaluating and Valuing Prompts

[1562] The server determines the value of prompts based on the rating information received from other users, and also prioritizes and recommends prompts to other users.

[1563] 5. Publicly displaying prompts

[1564] The valued prompts are then published as user-accessible web pages or API responses, allowing users to easily view and select from them.

[1565] 6. User Prompts

[1566] The user selects a published prompt and sends a request to the server to use it, along with the hash code of the prompt they want to use.

[1567] 7. Payment and Confirmation of Usage Fees

[1568] The server receives the usage request and checks the usage fee. The user pays using a credit card or electronic money. The server checks the payment and updates the information.

[1569] 8. Releasing the Encrypted Prompt

[1570] After the server verifies the payment, it releases and provides the encrypted prompt to the user, allowing them to use the prompt they specified.

[1571] 9. Return of profits

[1572] The server returns a portion of the usage fee to the prompt creator, the user, so that the user can receive appropriate compensation for the high-quality prompts they have created.

[1573] As a concrete example, consider a "prompt for generating cat images." A user uploads this prompt to the system, and other users rate it, assigning it a value. After that, another user selects a published prompt, confirms its value, and pays a fee to use it. After the server confirms the payment, it releases the encrypted prompt and provides it to the user. This entire process is performed automatically by the system.

[1574] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1575] Step 1:

[1576] A user creates a prompt and uploads it to the system using a terminal. To do this, the user enters text data, such as "a prompt to generate a cat image," and clicks the upload button. The input is the text data, and the output is the prompt sent to the server.

[1577] Step 2:

[1578] The server receives the uploaded prompt and checks its content. Specifically, the server parses the prompt to see if it is valid and checks its format and content. The input is the uploaded prompt, and the output is the parsing result (valid or invalid).

[1579] Step 3:

[1580] The server hashes the prompt using the SHA-256 algorithm and stores the result in a database. The input is the prompt text data, and the output is the hashed data.

[1581] Step 4:

[1582] The server evaluates the value of the prompt based on the rating information received from other users. This evaluation is performed using a machine learning model, which assigns an economic value to the prompt. The input is the rating information and the prompt, and the output is the valued prompt.

[1583] Step 5:

[1584] The server publishes the valued prompts to the public, where they are displayed as user-accessible web pages or API responses. The input is the valued prompt, and the output is the published prompt.

[1585] Step 6:

[1586] The user selects a published prompt and sends a usage request from the terminal to the server. The input is the published prompt and its hash code, and the output is the usage request sent to the server.

[1587] Step 7:

[1588] The server receives the usage request and checks the usage fee. At this time, the server retrieves the fee information from the database and presents it to the user. The input is the usage request, and the output is the fee information.

[1589] Step 8:

[1590] The user pays the displayed usage fee. This payment is made by means of a credit card, electronic money, etc. The input is fee information and payment information, and the output is confirmation of payment completion.

[1591] Step 9:

[1592] After the server confirms the payment, it releases the encrypted prompt and provides it to the user. Specifically, the server decrypts the prompt and sends it to the user's device. The input is the payment confirmation and the encrypted prompt, and the output is the decrypted prompt.

[1593] Step 10:

[1594] The server returns a portion of the earned usage fees to the prompt creator. The server calculates the amount of the return based on a revenue sharing algorithm and reflects it in the creator's account. The input is the usage fee and creator information, and the output is a reflection of the return amount.

[1595] 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.

[1596] The "Prompt Bank" system of this invention is a platform for assigning value to, managing, and distributing prompts created by users. The system includes the main components of a server, terminals, and users, and by combining it with an emotion engine, it has the ability to evaluate prompts and make recommendations based on the user's emotions.

[1597] System Overview

[1598] (User prompt registration)

[1599] The user creates a prompt and uploads it to the system. The prompt is uploaded from the user's terminal. At this time, the emotion engine recognizes the user's emotional state and sends data including the user's current emotion to the server as prompt information.

[1600] (receive and acknowledge prompts)

[1601] The server receives the prompt uploaded by the user, validates it, including checking that it is in the correct format, hashes it, generates a unique identifier, and stores it in a database.

[1602] (Evaluating and Valuing Prompts)

[1603] The server evaluates prompts by using an emotion engine to modify their value based on the user's emotion. Specifically, the emotion engine analyzes the user's emotion data and evaluates the quality of the prompt according to the emotion. Based on this evaluation result, the server assigns an economic value (e.g., 100 yen) to the prompt.

[1604] (Public release of prompts)

[1605] The server lists the valued prompts and makes them publicly available, allowing users to select from the list.

[1606] (Using user prompts and emotion recognition)

[1607] The user selects a prompt from the published prompts and sends a request to use it from the device to the server. The device then sends the hash code of the selected prompt along with the latest emotion data recognized by the emotion engine to the server.

[1608] (Payment and confirmation of usage fees)

[1609] The server receives the usage request and checks the usage fee. It analyzes the user's level of interest based on emotional data from the emotion engine and fine-tunes the fee if necessary. The user pays the proposed usage fee and the payment is completed. After the server confirms the payment, it releases an encrypted prompt and sends it to the user's device.

[1610] (Recommendation based on emotional data)

[1611] The emotion engine continuously collects user emotional data and stores it in a database. The server analyzes this data to recommend personalized prompts based on the user's interests and emotions. For example, if a user is feeling stressed, the server can recommend prompts with a relaxing effect.

[1612] (Return of profits)

[1613] The server returns a portion of the obtained usage fee to the creator of the prompt. The amount of the refund based on the usage fee is also recorded in the database using the user's usage emotion data generated by the emotion engine.

[1614] Specific examples

[1615] As a concrete example, user A creates a "prompt for generating a cat image" and uploads it to the system. The emotion engine recognizes the user's emotion at the time of uploading as "excitement," and this is added to the prompt information. The server receives the prompt, evaluates its quality, and assigns a value of 100 yen, taking the emotion information into consideration. When this prompt is made public and user B wishes to use it and sends a usage request to the server, the emotion engine recognizes the user's current emotion as "excitement." The server presents a usage fee of 100 yen, and user B pays. After confirming the payment, the server releases the encrypted prompt and sends it to user B's device. Finally, the server returns 50 yen of the 100 yen revenue to user A, the prompt creator.

[1616] In this way, the "Prompt Bank" system, which combines an emotion engine, utilizes users' emotional data to value and recommend prompts, thereby promoting the spread of high-quality prompts and providing appropriate rewards to their creators.

[1617] The processing flow will be explained below.

[1618] Step 1:

[1619] A user creates a prompt and uploads it to the system.

[1620] Specifically, the user inputs the required prompt content on the device's input screen, and the emotion engine recognizes the user's emotional state in real time. When the user presses the "upload" button, the prompt data and emotion data are sent to the server.

[1621] Step 2:

[1622] The server receives the uploaded prompts from the user.

[1623] The server receives the HTTP POST request and stores the prompt data and emotion data in a temporary directory.

[1624] Step 3:

[1625] The server checks the uploaded prompt.

[1626] Specifically, the server checks the format of the prompt, parses the content for correctness, and notifies the user of formatting errors or incomplete content if necessary.

[1627] Step 4:

[1628] The server hashes the prompt to generate a unique identifier.

[1629] The server generates a hash code of the prompt using the SHA-256 algorithm and retrieves the result.

[1630] Step 5:

[1631] The server stores the hashed prompts in a database.

[1632] The server records the prompt's hash value, original content, emotion data, and creation time in a database.

[1633] Step 6:

[1634] The server evaluates the prompt and assigns a value.

[1635] The server uses an emotion engine to analyze the user's emotion data, evaluates the quality of the prompt based on the results, and assigns an economic value to the prompt (e.g., 100 yen).

[1636] Step 7:

[1637] The server publishes the valued prompts to the public.

[1638] Specifically, the server generates a list of valued prompts as an HTML page or API response and makes it publicly available.

[1639] Step 8:

[1640] The user selects the prompt they want to use from the publicly available prompts.

[1641] The user selects a specific prompt (e.g., hash code abc123) from the list of published prompts and presses the "Use" button.

[1642] Step 9:

[1643] The user's terminal transmits the hash code and emotion data of the selected prompt to the server.

[1644] Specifically, the latest emotion data is sent to the server along with the hash code of the prompt using an HTTP POST request from the user's device.

[1645] Step 10:

[1646] The server receives the usage request and checks the usage fee.

[1647] The server retrieves the value information of the prompt from the database, extracts the usage fee (e.g., 100 yen), and presents it to the user.

[1648] Step 11:

[1649] The user pays a usage fee.

[1650] Specifically, the user enters their credit card information to complete the payment process, and the payment information is encrypted and sent to the server.

[1651] Step 12:

[1652] The server verifies the user's payment.

[1653] The server receives the response from the payment service, verifies whether the payment was successful, and records the payment information in a database.

[1654] Step 13:

[1655] The server releases the encrypted prompt and provides it to the user.

[1656] The server decodes the prompt and sends it to the user's device, possibly along with associated emotional data.

[1657] Step 14:

[1658] The server returns a portion of the usage fee earned to the creator.

[1659] The server will then credit a portion of the revenue earned based on a revenue sharing algorithm to the creator's account and record the amount in a database. For example, 50 yen out of a 100 yen usage fee will be returned to the creator.

[1660] Step 15:

[1661] The server recommends prompts based on the emotion data.

[1662] Specifically, the server analyzes the user's emotional data collected from the emotion engine and recommends personalized prompts to the user. For example, if the user is feeling stressed, it will recommend prompts that have a relaxing effect.

[1663] Example 2

[1664] 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."

[1665] Conventional prompt management systems evaluate and value prompts without considering the user's emotions, which makes it difficult to value and recommend prompts that are in line with the user's needs and emotions. It is also difficult to provide appropriate rewards to prompt creators.

[1666] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1667] In this invention, the server includes means for acquiring user emotion data using an emotion engine and adding it to prompt information, means for the server to evaluate prompts and assign values ​​based on the emotion data, and means for the emotion engine to collect, save, and analyze user emotion data to make personalized recommendations. This makes it possible to evaluate and assign values ​​to prompts based on user emotions, thereby enabling the spread of high-quality prompts and the provision of appropriate rewards to their creators.

[1668] "User" means an entity that uses the system to create, upload, or use prompts.

[1669] A "prompt" refers to text data that expresses instructions or requests to a generative AI model.

[1670] "Terminal" refers to a digital device used by a user, such as a computer, smartphone, or tablet.

[1671] "Server" refers to a central digital computer system that receives, evaluates, hashs, stores, publishes, etc., prompts.

[1672] An "emotion engine" refers to software or hardware that recognizes a user's emotional state and processes it as data.

[1673] "Hashing" refers to a cryptographic technique for converting a prompt into a unique identifier.

[1674] "Database" means a digital collection of information for managing and storing prompts and related data.

[1675] "Assigning a value" refers to the process of assigning an economic value to a prompt.

[1676] "Public" refers to making a valued prompt available for other users to view.

[1677] "Usage Request" refers to a request sent by a user to use a published prompt.

[1678] "Usage Fee" refers to the cost incurred when using Prompt.

[1679] "Rebate" refers to returning a portion of the usage fee to the prompt creator as compensation.

[1680] "Personalized recommendations" refers to suggesting prompts that are individually optimized based on the user's emotional data.

[1681] A "machine learning model" refers to an algorithmic method that learns from data and evaluates prompts based on the analysis results.

[1682] The "Prompt Bank" system of this invention is a platform for assigning value to, managing, and distributing prompts created by users. In addition to the main components of the system, which are a server, terminals, and users, it also combines an emotion engine to enable prompt evaluation and recommendations based on the user's emotions.

[1683] Hardware and software configuration

[1684] server

[1685] The server functions as a central processing unit and performs the following processes:

[1686] Receiving and hashing prompts

[1687] Save prompts to the database

[1688] Data analysis from the emotion engine

[1689] Valuing and Evaluating Prompts

[1690] Processing public availability and usage requests

[1691] Checking usage fees and processing payments

[1692] Fee rebates and management

[1693] Terminal

[1694] The devices used by users include computers, smartphones, tablets, etc. These devices perform the following functions:

[1695] Prompt creation and upload

[1696] Select a prompt and submit a request

[1697] Collecting and transmitting emotional data

[1698] Emotion Engine

[1699] The emotion engine has the following functions:

[1700] Recognizing the user's emotional state in real time

[1701] Collecting user emotion data

[1702] Adding emotional data to prompt information

[1703] Recommending prompts based on emotion data

[1704] Data processing and calculation

[1705] When a user creates a prompt and uploads it to the system from their device, the emotion engine collects the user's emotional state and sends it to the server as prompt information. The server receives the prompt, checks its content, and checks whether it is in the correct format. The server then hashes the prompt to generate a unique identifier and stores it in a database.

[1706] The server analyzes the data from the emotion engine and evaluates the quality of the prompts. Based on the evaluation results, the server assigns economic values ​​to the prompts. The server then makes the valued prompts public, allowing users to select prompts.

[1707] When a user requests to use a published prompt, the device sends a usage request including emotion data to the server. The server receives the usage request, checks and adjusts the usage fee based on the emotion data, and completes the payment once the user pays the fee. After the server confirms the payment, it releases the encrypted prompt and sends it to the device.

[1708] The emotion engine continuously collects user emotion data, and the server analyzes the data to recommend personalized prompts.

[1709] Specific examples

[1710] For example, user A creates a "prompt for generating a cat image" and uploads it to the system. The emotion at the time of uploading is recognized as "excitement," and this is added to the prompt information. The server receives the prompt, evaluates its quality, and assigns a value of 100 yen, taking into account the emotional information. This prompt is made public, and user B wants to use it. When a usage request is sent to the server, the emotion engine recognizes the user's current emotion as "excitement." The server presents a usage fee of 100 yen, and user B pays. After confirming the payment, the server releases the encrypted prompt and sends it to user B's device. Finally, the server returns 50 yen of the 100 yen revenue to user A.

[1711] By combining this system with an emotion engine, it is possible to value and recommend prompts based on the user's emotions, thereby promoting the spread of high-quality prompts and providing appropriate rewards to their creators.

[1712] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1713] Step 1: User creates and uploads prompt

[1714] The user opens the prompt creation screen on their device and enters a prompt for the generative AI model. When the user presses the upload button, the device sends the prompt to the server. At this time, the emotion engine recognizes the user's emotional state in real time and sends the emotional data along with it. The input is the prompt and emotional data, and the output is uploaded to the server.

[1715] Step 2: Receive and confirm the prompt

[1716] The server receives prompts uploaded by users. At this time, it checks whether the prompts are in the correct format. Specifically, it checks the text length of the prompt and whether it contains specific keywords. The input is the uploaded prompt and emotion data, and the output is the prompt format check result.

[1717] Step 3: Hash and save the prompt

[1718] The server hashes the prompt sentence and generates a unique identifier. The server then stores the prompt sentence, emotion data, and unique identifier in a database. The input is the confirmed prompt sentence and emotion data, and the output is storage in the database.

[1719] Step 4: Evaluate and value the prompt

[1720] The server uses an emotion engine to analyze the user's emotional data. Based on the results of this analysis, the server evaluates the quality of the prompt and assigns an economic value (e.g., 100 yen). The input is the emotional data and the prompt, and the output is the assigned value.

[1721] Step 5: Make the prompt public

[1722] The server compiles a list of valued prompts and makes it publicly available for users to view. The input is the valued prompt text, and the output is the published list of prompts.

[1723] Step 6: User requests prompt usage

[1724] The user browses a list of publicly available prompts on their device and selects the prompt they want to use. Then, they send a usage request from their device to the server. At this time, the emotion engine recognizes the user's latest emotion data and sends it along with the request to the server. The input is the usage request and emotion data, and the output is the request sent to the server.

[1725] Step 7: Check and settle usage fees

[1726] The server receives the usage request and analyzes the emotional data to assess the user's interest level. Based on this, it checks and possibly fine-tunes the usage fee. The user pays the fee, and the server confirms the payment. The input is the usage request and emotional data, and the output is the adjusted usage fee and its payment confirmation.

[1727] Step 8: Sending the Encrypted Prompt

[1728] After the server confirms the payment, it releases the encrypted prompt and sends it to the user's terminal. The input is the payment confirmation and the prompt text, and the output is the prompt sent to the terminal.

[1729] Step 9: Recommendation based on emotion data

[1730] The emotion engine continuously collects user emotion data, and the server analyzes the data to generate personalized recommendations. The input is the collected emotion data, and the output is personalized prompt recommendations.

[1731] Step 10: Returning profits

[1732] The server returns a portion of the revenue based on the prompt usage by the user to the prompt creator. The server also references the emotion data collected by the emotion engine to calculate the amount of return. The input is the usage fee and emotion data, and the output is the calculation and reflection of the return amount.

[1733] (Application example 2)

[1734] 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."

[1735] Conventional prompt management systems do not evaluate or recommend prompts based on the user's emotions, making it difficult to accurately evaluate the quality of prompts or to provide customized recommendations for individual users. Furthermore, it is difficult to provide content that matches the user's current emotional state, resulting in a decrease in user satisfaction. The present invention aims to solve these problems by enabling prompt evaluation and recommendation based on the user's emotions and providing content in accordance with emotional data.

[1736] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1737] In this invention, the server includes means for a user to create and upload prompts, means for the server to receive the uploaded prompts and check the contents of the prompts, means for the server to hash the prompts and store the hashed results in a database, means for the server to rate and assign values ​​to the prompts, means for the server to publicly publish the valued prompts, means for a user to select a published prompt and send a usage request, means for the server to receive the usage request and check a usage fee, means for the user to pay the usage fee, means for the server to confirm the payment and release and provide the encrypted prompts, and means for the server to return a portion of the usage fee to the creator, as well as means for rating and recommending prompts based on the user's emotions using an emotion engine, and means for recommending content according to the user's emotion data. This not only enables proper evaluation of the quality of prompts and recommendation of customized prompts to individual users, but also makes it possible to provide appropriate content according to the user's current emotional state.

[1738] A "prompt" is a statement written in the form of an instruction, question, or command given to a generative AI model.

[1739] "Uploading" is the act of a user sending data or files from their device to a server.

[1740] A "server" is a computer system that provides services to other computers (clients) on a network.

[1741] "Hashing" is a cryptographic process that converts original data into a fixed-length string of characters that can be used as a unique identifier.

[1742] A "database" is a collection of structured data that allows for efficient management and retrieval of large amounts of data.

[1743] An "emotion engine" is a software technology for analyzing a user's emotional state and collecting and utilizing that data.

[1744] "Valuing" is the act of assigning economic value or valuation to specific data or items.

[1745] "Publishing" means making certain data or information accessible to other users within the system.

[1746] A "use request" is a request that a user sends to the effect that he or she wishes to use a published prompt or service.

[1747] "Usage Fee" means money paid for the use of a particular service or item.

[1748] "Encryption" is a technology that codes data using a specific algorithm to protect it from easy access by third parties.

[1749] "Return" is the act of giving back a portion of the revenue or profits earned to a specific cause or person.

[1750] "Emotional Data" means information about the user's emotional state that is analyzed and collected by the Emotion Engine.

[1751] "Recommendation" is the act of a system suggesting optimal content or services based on a user's behavior and emotions.

[1752] "Content" refers to digital data and information such as music, video, text, and images provided through systems and services.

[1753] This invention relates to a prompt bank system incorporating an emotion engine. Specifically, it provides a method for uploading prompts created by users and analyzing and evaluating them using the emotion engine. The server assigns an appropriate value based on the prompt evaluation results and publishes them. Furthermore, the system provides recommended content based on the user's latest emotion data.

[1754] Hardware and Software Configuration

[1755] 1. The server is the central processing unit for managing, evaluating, storing, and publishing prompts. It includes hashing technology, a database management system, and machine learning models (e.g., TensorFlow).

[1756] 2. An emotion engine is a software technology that analyzes a user's emotional data, recognizes their emotional state, and generates corresponding data. A typical emotion analysis module is the sentiment_analysis library.

[1757] 3. User terminals are devices used to create, upload, view, and process payments for prompts. These include smartphones, tablets, and PCs.

[1758] 4. The payment processing module is a system that allows users to make payments and uses the APIs of Stripe and PayPal.

[1759] System details

[1760] 1. Create and upload a prompt:

[1761] Users create prompts and upload them to the system from their own devices. For example, if a user creates a prompt called "Relaxing music for stress relief," the system will recognize the user's current emotional state as "Relaxed" using the emotion engine.

[1762] 2. Receiving and Evaluating Prompts:

[1763] The server receives the uploaded prompts, hashes them, and stores them in a database. It then uses an emotion engine to analyze the user's emotional data and evaluate the quality of the prompts. Based on the evaluation results, economic values ​​are assigned to the prompts.

[1764] 3. Publishing and Recommending Prompts:

[1765] The server publishes the valued prompts to the public. Other users can browse the published prompts and select the prompts they want to use. The emotion engine then recommends the most appropriate prompts to the user based on the latest emotional data analyzed.

[1766] 4. Payment Processing and Prompts:

[1767] The user selects a published prompt and sends a usage request to the server. The server checks the usage fee, and the user pays. Once the payment is confirmed, the server releases the encrypted prompt and sends it to the user's device.

[1768] 5. Return of profits:

[1769] The server returns a portion of the usage fee to the prompt creator. Using usage emotion data from the emotion engine, the server accurately calculates the monetary amount of the return and records it in a database.

[1770] Example prompt

[1771] For example, if User A wants to recommend "relaxing music to relieve stress," he or she can create a prompt like this:

[1772] "Recommend relaxing music for stress relief."

[1773] This system improves the user experience by enabling the user to value prompts based on their emotional state and recommend content that is best suited to each individual user.

[1774] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1775] Step 1:

[1776] The user creates a prompt and uploads it from the device to the server. The input includes the prompt text "Please recommend some relaxing music to relieve stress." and the user's current emotional data. The device creates the prompt, recognizes the user's emotional state using an emotion engine, and sends the data including the prompt to the server. The server then receives this data.

[1777] Step 2:

[1778] The server verifies the received prompt, hashes it, and stores it in a database. The input includes the uploaded prompt data. The server verifies the prompt content, checks that it is in the correct format, and then uses hashing techniques to generate a unique identifier. The server then stores the hashed prompt in a database. The output is the hashed data.

[1779] Step 3:

[1780] The server evaluates the prompt content using an emotion engine and assigns a value. The input includes the prompt content and the user's emotion data. The server uses the emotion engine to analyze the user's emotion data and evaluates the quality of the prompt based on this. Based on the evaluation result, an economic value is assigned to the prompt. For example, a value of 100 yen is assigned. The output is the evaluation result and the prompt with the assigned value.

[1781] Step 4:

[1782] The server publishes valued prompts to the public. The input includes the valued prompt data. The server publishes the prompts to the public in a list format that can be accessed by other users. The output is a list of published prompts.

[1783] Step 5:

[1784] The user selects a published prompt and sends a usage request from the device to the server. The input includes a list of published prompts and the user's selection. The user browses the published prompts on the device and selects the prompt they want to use. The latest emotion data is also sent along with the usage request. The output is the selected prompt and the associated emotion data.

[1785] Step 6:

[1786] The server receives the usage request and checks the usage fee. The input includes the user's usage request and associated emotion data. The server checks the usage fee and possibly fine-tunes the fee based on the analysis results of the emotion engine. The output is the proposed usage fee.

[1787] Step 7:

[1788] The user pays the usage fee. The input includes the proposed usage fee and the user's payment information. The terminal uses the payment processing module to pay the usage fee. The server confirms the payment. The output is payment confirmation information.

[1789] Step 8:

[1790] The server verifies the payment, releases and provides an encrypted prompt. The input includes the payment confirmation information and the encrypted prompt. The server reverses the encryption process and sends the prompt to the user's terminal. The output is the released prompt.

[1791] Step 9:

[1792] The server returns a portion of the earned usage fee to the prompt creator. The input includes the usage fee and related prompt information. The server uses data from the emotion engine to calculate the refund amount and send it to the creator. The output is information indicating that the refund process has been completed.

[1793] Step 10:

[1794] The server continuously collects user emotion data and stores it in a database. The input includes the user emotion data. The server uses an emotion engine to retrieve the emotion data and stores it in a database. The output is an updated database.

[1795] Step 11:

[1796] The server analyzes the collected emotional data and recommends appropriate content to the user. The input includes the emotional data stored in the database. The server analyzes the emotional data using a machine learning model and recommends the most suitable content to the user. The output is the recommended content.

[1797] 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.

[1798] 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.

[1799] 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.

[1800] 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.

[1801] 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.

[1802] 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.

[1803] 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).

[1804] 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.

[1805] 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."

[1806] 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.

[1807] 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).

[1808] 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.

[1809] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1810] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1811] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1812] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1813] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1814] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1815] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1816] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1817] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1818] The following is further disclosed regarding the above embodiment.

[1819] (Claim 1)

[1820] a means for users to create and upload prompts;

[1821] a means for the server to receive the uploaded prompt and verify the prompt content;

[1822] A means for the server to hash the prompt and store the result in a database;

[1823] a means for the server to evaluate and assign a value to the prompt;

[1824] a means for the server to publicly publish the valued prompts;

[1825] A means for a user to select a published prompt and submit a request to use it;

[1826] A means for the server to receive a usage request and check the usage fee;

[1827] a means for users to pay usage fees;

[1828] a means for the server to verify the payment, release and provide an encrypted prompt;

[1829] A means for returning a portion of the usage fee obtained by the server to the creator;

[1830] A system including:

[1831] (Claim 2)

[1832] 10. The system of claim 1, further comprising means for the server to parse the content of the prompt to verify that it is in the correct format.

[1833] (Claim 3)

[1834] 10. The system of claim 1, wherein the server further comprises means for using a machine learning model to evaluate the prompt.

[1835] "Example 1"

[1836] (Claim 1)

[1837] A means for users to create and upload prompts for the generative AI model;

[1838] a means for the server to receive the uploaded prompt and validate its format and content;

[1839] A means for the server to hash the prompt using the SHA-256 algorithm and store the result in a database;

[1840] a means for the server to rate and assign values ​​to prompts using a machine learning model or raters;

[1841] A means for the server to publicly expose the valued prompts via a web page or API response; and

[1842] A means for a user to select a published prompt and submit a request to use it;

[1843] A means for the server to receive the usage request and confirm the proposed usage fee;

[1844] A means for users to pay usage fees by credit card or electronic money,

[1845] a means for the server to verify the payment and release an encrypted prompt to provide to the user's terminal;

[1846] A means for the server to return a portion of the usage fee earned to the prompt creator based on a revenue sharing algorithm;

[1847] A system including:

[1848] (Claim 2)

[1849] 10. The system of claim 1, further comprising means for the server to parse the content of the prompt to verify that it is in the correct format.

[1850] (Claim 3)

[1851] 10. The system of claim 1, wherein the server further comprises means for using a machine learning model to evaluate the prompt.

[1852] "Application Example 1"

[1853] (Claim 1)

[1854] a means for users to create and upload prompts;

[1855] a means for the server to receive the uploaded prompt and verify the prompt content;

[1856] A means for the server to hash the prompt and store the result in a database;

[1857] a means for the server to evaluate and assign a value to the prompt;

[1858] a means for the server to publicly publish the valued prompts;

[1859] A means for a user to select a published prompt and submit a request to use it;

[1860] A means for the server to receive a usage request and check the usage fee;

[1861] a means for users to pay usage fees;

[1862] a means for the server to verify the payment, release and provide an encrypted prompt;

[1863] A means for returning a portion of the usage fee obtained by the server to the creator;

[1864] A means for rating and assigning a value to the prompt based on rating information of other users;

[1865] a means for prioritizing and recommending prompts to other users based on the rating information;

[1866] A system including:

[1867] (Claim 2)

[1868] 10. The system of claim 1, further comprising means for the server to parse the content of the prompt to verify that it is in the correct format.

[1869] (Claim 3)

[1870] 10. The system of claim 1, wherein the server further comprises means for using a machine learning model to evaluate the prompt.

[1871] "Example 2: Combining Emotion Engines"

[1872] (Claim 1)

[1873] a means for users to create and upload prompts;

[1874] a means for the server to receive the uploaded prompt and verify the prompt content;

[1875] A means for the server to hash the prompt and store the result in a database;

[1876] a means for acquiring user emotion data from an emotion engine and adding the data to prompt information;

[1877] a means for the server to evaluate the prompt and assign a value based on the emotion data;

[1878] a means for the server to publicly publish the valued prompts;

[1879] A means for a user to select a published prompt and submit a request to use it;

[1880] The server receives the usage request and checks and adjusts the usage fee based on the user's emotional data.

[1881] a means for users to pay usage fees;

[1882] a means for the server to verify the payment, release and provide an encrypted prompt;

[1883] A means for returning a portion of the usage fee obtained by the server to the creator;

[1884] A means to collect, store, and analyze user emotional data using an emotion engine to make personalized recommendations;

[1885] A system including:

[1886] (Claim 2)

[1887] 10. The system of claim 1, further comprising means for the server to parse the content of the prompt to verify that it is in the correct format.

[1888] (Claim 3)

[1889] 10. The system of claim 1, wherein the server further comprises means for using a machine learning model to evaluate the prompt.

[1890] "Application example 2 when combining emotion engines"

[1891] (Claim 1)

[1892] a means for users to create and upload prompts;

[1893] a means for the server to receive the uploaded prompt and verify the prompt content;

[1894] A means for the server to hash the prompt and store the result in a database;

[1895] a means for the server to evaluate and assign a value to the prompt;

[1896] a means for the server to publicly publish the valued prompts;

[1897] A means for a user to select a published prompt and submit a request to use it;

[1898] A means for the server to receive a usage request and check the usage fee;

[1899] a means for users to pay usage fees;

[1900] a means for the server to verify the payment, release and provide an encrypted prompt;

[1901] In addition to the means by which the server returns a portion of the usage fees earned to the creator,

[1902] a means for rating and recommending prompts based on the user's emotions using an emotion engine;

[1903] A means for recommending content according to the user's emotional data;

[1904] A system including:

[1905] (Claim 2)

[1906] 10. The system of claim 1, further comprising means for the server to parse the content of the prompt to verify that it is in the correct format.

[1907] (Claim 3)

[1908] 10. The system of claim 1, wherein the server further comprises means for analyzing the emotion data using an emotion engine in addition to means for using a machine learning model to evaluate the prompt. [Explanation of symbols]

[1909] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for users to create and upload prompts; a means for the server to receive the uploaded prompt and verify the prompt content; A means for the server to hash the prompt and store the result in a database; a means for the server to evaluate and assign a value to the prompt; a means for the server to publicly publish the valued prompts; A means for a user to select a published prompt and submit a request to use it; A means for the server to receive a usage request and check the usage fee; a means for users to pay usage fees; a means for the server to verify the payment, release and provide an encrypted prompt; A means for returning a portion of the usage fee obtained by the server to the creator; A system including:

2. 2. The system of claim 1, further comprising means for the server to parse the content of the prompt to verify that it is in the correct format.

3. The system of claim 1 , wherein the server further comprises means for using a machine learning model to evaluate the prompt.

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