system

Abstract

Provide a system. A means for a user to input a log generated using an information generating device; means for transmitting the log to a server; A server receives the log and stores it in a database; A means for other users to give reactions to the log; A means for a server to receive the reactions and store them in a database; A means for users to share logs to social networking services; A system including:

Description

[Technical Field]

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

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

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

[0004] In recent years, the use of information generating devices has rapidly spread, but the know-how regarding optimal usage and prompting methods has not been sufficiently shared, posing a challenge for raising the level of knowledge and skills of users. Furthermore, the lack of a platform for efficiently sharing the logs acquired by users means that individual know-how is not circulated, preventing efficient utilization. Furthermore, the lack of a mechanism for exchanging reactions with other users or sharing high-quality logs on social media has hindered the growth of the community and the spread of information. [Means for solving the problem]

[0005] The present invention provides a means for a user to input a log generated using an information generating device, transmit the log to a server, and have the server receive and store the log in a database. It also provides a means for other users to provide reactions to the log, and a means for the server to receive the reactions and store them in a database. The system also includes a means for users to share the log on a social networking service, promoting the sharing of logs and the exchange of reactions, and enabling the spread of high-quality logs. In particular, the logs generated by users include prompts and their results, enabling the sharing of know-how. The system also provides a means for preferentially displaying logs that have received a certain number of reactions, thereby revitalizing the user community.

[0006] "User" refers to an individual or entity that uses an information generating device to generate logs and inputs and shares such logs on the Platform.

[0007] "Information generating device" refers to a system, software, or hardware that generates information based on prompts entered by a user.

[0008] "Log" refers to a record of data consisting of the results generated by an information generating device and the prompts used to generate them.

[0009] "Server" refers to a computer system that receives logs sent by users, stores them in a database, and manages reaction data.

[0010] "Database" means a system for storing, managing, searching, and displaying log and reaction data.

[0011] "Reaction" refers to the act of other users expressing their evaluation or feedback on an uploaded log.

[0012] "Social Networking Service (SNS)" refers to an online platform that enables users to share information and communicate with other users.

[0013] A "prompt" refers to the text of an instruction or question that a user enters into an information generating device. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0022] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0035] The present invention provides a system that allows users to efficiently share logs generated using information generation devices and improve the knowledge of the entire community through reactions. This system operates in cooperation with the elements of users, terminals, and servers.

[0036] Uploading logs

[0037] User: First, the user uses the information generator to generate a prompt and the corresponding result. Then, the user enters the generated prompt and result into an input form on the terminal. This input form has fields where the prompt and result can be entered separately. The user clicks the "Upload" button.

[0038] Terminal: The input prompts and results are compiled in JSON format and sent to the server, along with identifying information such as the user ID.

[0039] Server: Parses the received data, generates a log ID, and saves the log ID, user ID, prompt, result, timestamp, etc. in the database.

[0040] Adding a reaction

[0041] User: Next, other users can view the uploaded logs. A user interface is provided that displays a list of logs and a detailed page for each log. Useful logs have reaction buttons such as "Like" and "Helpful."

[0042] On the device: When a reaction button is clicked, the log ID and reaction type (e.g., "Like") are sent to the server.

[0043] Server: Receives reaction data and stores the user ID, reaction type, log ID, timestamp, etc. in the database. Also, increases or decreases the number of reactions as needed.

[0044] Sharing to social media

[0045] User: If the user finds the log useful, they can click the SNS share button to post the generated log and its results to SNS.

[0046] Device: When you click the share button, the log contents will be embedded in text format into a URL for sharing on social media, and the social media posting screen will open in a new window.

[0047] Specific examples

[0048] 1. Generate and upload logs:

[0049] Prompt: "Make a poem with AI."

[0050] Result: "A quiet night, the stars shine brightly."

[0051] The user fills in the prompts and results and clicks the upload button.

[0052] 2. Reaction to the log:

[0053] Another user views this log and clicks the "Like" button.

[0054] The number of "likes" increases and reaction information is recorded in the database.

[0055] 3. Sharing to social media:

[0056] The user clicks a button to share this log on Twitter.

[0057] A URL for sharing on social media will be generated, a new window will open, and the log content will be posted to the social media platform.

[0058] This allows other users to access the logs and easily obtain useful information. Furthermore, information can be spread through social media, making the convenience of generative AI known to many people.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] User: Uses the information generator to input a prompt and receive a result. For example, the user inputs "Please write a poem using AI" as a prompt and receives the text "A quiet night, the stars shine brightly" as a result.

[0062] Step 2:

[0063] User: Enters the generated prompt and results into an input form on the device. For example, the input form has a field for the prompt and a field for the result, and the user enters text into each field.

[0064] Step 3:

[0065] User: Once the input is complete, click the "Upload" button on the device. This action sends the input data to the server.

[0066] Step 4:

[0067] Terminal: The input prompt and result are converted into JSON format and sent to the server along with necessary identification information such as the user ID. Specifically, the data is sent using an HTTP POST request.

[0068] Step 5:

[0069] Server: Parses the received JSON data and generates a new log entry based on it. It generates a log ID and saves data such as the user ID, prompt, result, and timestamp in the database.

[0070] Step 6:

[0071] Users: View logs uploaded by other users and give reactions to logs they like. For example, select a specific log from the log list, go to the details page, and click the "Like" button.

[0072] Step 7:

[0073] Terminal: When the reaction button is clicked, data including the log ID and reaction type is sent to the server. As with the server, an HTTP POST request is used.

[0074] Step 8:

[0075] Server: Analyzes the received reaction data and records it in a database based on the user ID, reaction type, log ID, timestamp, etc. Also, if it is necessary to increase or decrease the number of reactions, it handles that process.

[0076] Step 9:

[0077] User: If you want to share a log you like on a social networking service (SNS), click the share button. For example, you can click the "Share" button to post the log on Twitter.

[0078] Step 10:

[0079] On the device: When the share button is clicked, a new window is opened by embedding the text containing the log contents into the URL for sharing on social media. Specifically, the text containing the log prompt and result is encoded, a URL containing that text is generated, and the URL is opened in a new window.

[0080] The above are the specific processing steps when a user shares a log generated using AI, receives reactions, or shares it on social media.

[0081] Example 1

[0082] 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."

[0083] Conventional information sharing systems have faced challenges in efficiently sharing user-generated logs and promoting knowledge sharing within the community. Furthermore, they lacked the functionality to allow other users to add reactions to logs, limiting the collection and analysis of the resulting data. Furthermore, there was a lack of an easy way to share generated logs on social networking services. A system that could solve these challenges, efficiently share user-generated information, and improve the knowledge of the entire community was needed.

[0084] 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.

[0085] In this invention, the server includes means for converting the prompt and results generated by the user using the information generation device into JSON format and transmitting them to the server together with user identification information, means for receiving the prompt and results, generating a log ID, and storing it in a database, means for other users to give reactions to the prompt and results, means for receiving the reactions, storing them in a database, and updating the number of reactions, and means for users to share the prompt and results on a social networking service, thereby enabling users to efficiently share the information they generate and improve the knowledge of the entire community through reactions.

[0086] A "user" is an individual or entity that utilizes the system to input prompts into an information generator and receive the results.

[0087] An "information generating device" is a device that generates results in response to prompts entered by a user, such as a generative AI model.

[0088] A "prompt" refers to a question or instruction that a user inputs into an information generating device.

[0089] "Results" refers to the output generated by an information generating device based on a prompt.

[0090] "Input Form" refers to the interface on a web page through which a user enters prompts and results.

[0091] The "JSON format" is a lightweight data exchange format that represents data as key-value pairs.

[0092] "User Identification Information" means an ID or other identifying data that uniquely identifies a user.

[0093] A "server" is a computer system for receiving and processing data sent by users and terminals.

[0094] A "Log ID" is a unique server-generated identifier used to identify a particular set of prompts and results.

[0095] A "database" is a system for efficiently storing, managing, and retrieving data in digital form.

[0096] "Reactions" refer to feedback other users give to a particular prompt and result, expressed in the form of "likes" or "helpful."

[0097] "Social networking service" refers to an online platform that users use to share information, such as a social networking site.

[0098] This invention is a system that allows users to efficiently share prompts generated using generative AI models and the results, thereby improving the knowledge of the entire community. This system works in cooperation with the user, terminal, and server elements.

[0099] 1. User Actions

[0100] First, the user uses a generative AI model to generate a prompt and its results. An example of a generative AI model is ChatGPT (registered trademark). The user then enters the generated prompt and results into an input form on their device. This input form provides fields for entering the prompt and results separately, and the user clicks the "Upload" button after entering the information.

[0101] (Example)

[0102] Prompt: "Make a poem with AI."

[0103] Result: "A quiet night, the stars shine brightly."

[0104] 2. Device Operation

[0105] The terminal converts the prompts and results entered in the input form into JSON format. It also includes the user's identity information in the JSON data. The converted JSON data is sent to a specific API endpoint. For example, the terminal generates the following data:

[0106] json

[0107] {

[0108] "userID": "12345",

[0109] "prompt": "Create a poem with AI",

[0110] "result": "A quiet night, the stars shine brightly"

[0111] }

[0112] This data is sent as a POST request to the URL 'http: / / example.com / upload'.

[0113] 3. Server Processing

[0114] The server analyzes the received JSON data and generates a new log ID. The server saves the data (user ID, prompt, result, timestamp) including the generated log ID in a database. The database is operated using, for example, an RDBMS (Relational Database Management System).

[0115] (example)

[0116] Store the received data as follows:

[0117] Log ID: "67890"

[0118] User ID: "12345"

[0119] Prompt: "Make a poem with AI."

[0120] Result: "A quiet night, the stars shine brightly."

[0121] Timestamp: "2023-10-05T12:34:56Z"

[0122] 4. Viewing logs and adding reactions

[0123] Next, other users can browse the list of uploaded logs using a user interface provided in a web browser, select a log of interest, go to the details page, and click reaction buttons such as "Like" or "Helpful."

[0124] 5. Handling Reactions

[0125] When the reaction button is clicked, the device detects the click event and sends data including the log ID and reaction type (e.g., "Like") to the server. The server processes the received reaction data, saves it in the database, and updates the reaction count. For example, the data is saved in the following format:

[0126] User ID: "54321"

[0127] Log ID: "67890"

[0128] Reaction type: Like

[0129] Timestamp: "2023-10-05T12:35:00Z"

[0130] 6. Sharing on social media

[0131] Finally, if a user wants to share a specific log on a social networking service (SNS), they can click the SNS share button. The device will generate data containing the log content and a sharing URL, and open the SNS posting screen in a new window. For example, the following URL may be generated:

[0132] 'https: / / twitter.com / intent / tweet?text=Check out this log!%20prompt:%20Make a poem with AI%20result:%20A quiet night, the stars shine brightly'

[0133] This system allows users to efficiently share the generated information and improve the knowledge of the entire community through reactions. Information can also be easily spread through social media, widely communicating the convenience of generative AI.

[0134] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0135] Step 1:

[0136] User: Inputs a prompt to the generative AI model. As input, the user provides the generative AI model with the prompt "Please write a poem using AI." As a result, the generative AI model generates the output "A quiet night, the stars shine brightly." The user enters this result into an input form on their device.

[0137] Step 2:

[0138] Terminal: The prompt and result entered in the input form are converted into JSON format. As input, the prompt entered by the user, "Please write a poem using AI," and the result, "A quiet night, the stars shine brightly," are received. These data, along with the user ID, are converted into JSON format like {'userID': '12345', 'prompt': 'Please write a poem using AI', 'result': 'A quiet night, the stars shine brightly'}.

[0139] Step 3:

[0140] Terminal: Sends data converted to JSON format to an API endpoint. As input, it takes JSON formatted data and creates an HTTP POST request. It sends this to a specific URL (e.g. http: / / example.com / upload). The output is a status code of 200 if the request is successful.

[0141] Step 4:

[0142] Server: Parses the data received at the API endpoint and generates a log ID. As input, it receives the received JSON data and parses the user ID, prompt, and result. Based on this, it generates a new log ID "67890". As output, it obtains the data {'logID': '67890', 'userID': '12345', 'prompt': 'Create a poem with AI', 'result': 'A quiet night, the stars shine', 'timestamp': '2023-10-05T12:34:56Z'} containing the generated log ID.

[0143] Step 5:

[0144] Server: Saves the data including the generated log ID to the database. As input, it receives the data generated in the previous step and saves it to the database. The output is a notification that saving to the database is complete.

[0145] Step 6:

[0146] User: Another user views the log list in a web browser and navigates to the individual log details page. As input, the user enters the URL to access the log list page in the web browser. The output is a display of the viewable log list.

[0147] Step 7:

[0148] User: Clicks the "Like" button for a log they are interested in. The input is clicking the "Like" button after viewing a specific log detail page. The output is the occurrence of a "Like" event.

[0149] Step 8:

[0150] Terminal: Detects the click event of the reaction button and sends the log ID and reaction type to the server. Receives the click event of the "Like" button as input and converts the log ID "67890" and reaction type "Like" into JSON format. The output is a request to send to the API endpoint based on this data.

[0151] Step 9:

[0152] Server: Processes the received reaction data, saves it in the database, and updates the number of reactions. As input, it receives JSON-formatted reaction data and analyzes it for the user ID, log ID, and reaction type. Based on this, it saves it in the database and updates the number of reactions. The output is a notification that the database has been updated.

[0153] Step 10:

[0154] User: Clicks the SNS share button to share the log on a social networking service (SNS). The input is clicking the share button. The output is that a URL for posting to the SNS is generated and the SNS posting screen is opened in a new window.

[0155] (Application example 1)

[0156] 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."

[0157] Modern advertising strategies require measuring advertising effectiveness in real time and optimizing advertising content based on user feedback. However, conventional systems lacked mechanisms for efficiently collecting and analyzing the quality of ad copy generated by advertisers and user reactions, making it difficult to develop effective advertising strategies. Furthermore, the lack of an integrated function for sharing ad logs with social networking services made it difficult to expand the user base.

[0158] 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.

[0159] In this invention, the server includes: a means for inputting a log generated by a user using an information generating device; a means for transmitting the log to the server; a means for the server to receive the log and store it in a database; a means for other users to provide reactions to the log; a means for the server to receive the reactions and store them in a database; a means for the user to share the log on a social networking service; a means for an advertiser to generate advertising copy using a generative AI model and upload it as a log; a means for users to provide reactions to the displayed advertising log; and a means for analyzing the reaction data and measuring the effectiveness of the advertisement. This enables the quality and effectiveness of the advertising copy generated by the advertiser to be evaluated and optimized in real time. In addition, a social networking service sharing function is integrated to expand the user base, allowing the system to reach more users.

[0160] A "user" refers to an entity that uses an information generating device to generate a log and provides the log to the system.

[0161] "Information generating device" refers to a device through which a user inputs a prompt and generates a result in response to the prompt.

[0162] "Log" refers to data including prompts generated by a user using an information generating device and the results thereof.

[0163] "Server" refers to a computer system that receives logs and reaction data sent by users and stores and manages them in a database.

[0164] "Reaction" refers to the rating or feedback that other users give to a particular log.

[0165] A "database" refers to a system that systematically stores logs and reaction data and manages them in a manner that allows for search and analysis.

[0166] "Social Networking Service" means an online platform that enables users to share information and communicate with other users.

[0167] "Advertiser" refers to the entity that uses a generative AI model to create advertising copy and uploads that advertising copy to the system as a log.

[0168] "Generative AI model" refers to an artificial intelligence model that automatically generates ad copy and other information based on prompts entered by a user.

[0169] "Ad copy" refers to the advertising content generated by a generative AI model and served to users.

[0170] "Advertising Log" refers to a log containing advertising copy generated by an advertiser using a generative AI model and uploaded to the system.

[0171] "Measuring the effectiveness of advertising" refers to analyzing user reaction data and evaluating how much evaluation and interest a particular ad copy has generated.

[0172] This invention is a system that allows users to efficiently share logs generated using an information generation device and optimize the effectiveness of advertising through reactions. This system operates in cooperation with each element of the user, terminal, and server.

[0173] Generating and uploading logs

[0174] User: First, the advertiser user generates ad copy using the generative AI model. For example, they input a prompt such as "Generate an ad for a new drinking water product" and get the generated result. Then, they input this ad copy into the input form on their device and click the upload button.

[0175] Device: The entered ad copy and the corresponding results are compiled in JSON format and sent to the server, along with identifying information such as the user ID and campaign ID.

[0176] Server: Parse the received data, generate a log_id, and save the log_id, user ID, campaign ID, ad copy, results, timestamp, etc. in the database.

[0177] Adding a reaction

[0178] Users: Other users can view the uploaded ad logs and click reaction buttons such as "Like" or "Interested" on the ad logs they find useful.

[0179] Device: When the reaction button is clicked, the ad log ID and reaction type (e.g., "Like") are sent to the server.

[0180] Server: Receives reaction data and stores the user ID, reaction type, ad log ID, timestamp, etc. in a database. Also manages the increase / decrease in the number of reactions.

[0181] Sharing to social media

[0182] User: Clicks a button to share the ad log they found useful on social media.

[0183] Device: When you click the share button, the contents of the ad log will be embedded in text format into a URL for sharing on social media, and the social media posting screen will open in a new window.

[0184] Specific examples

[0185] 1. Generate and upload your ad:

[0186] Prompt: "Generate a new drinking water ad"

[0187] Result: "Try Sparkling Water, a refreshing new experience."

[0188] The advertiser enters this advertisement text and clicks the upload button.

[0189] 2. Adding a reaction:

[0190] Another user views this ad log and clicks the "Like" button.

[0191] The number of "likes" increases and reaction information is recorded in the database.

[0192] 3. Sharing to social media:

[0193] The user clicks a button to share this ad log on Twitter.

[0194] An advertising caption such as "Try a new refreshing sparkling water experience" is automatically embedded in the Twitter post screen, and a new window opens.

[0195] This system allows advertisers to measure the effectiveness of their ads in real time, providing them with a powerful tool for developing optimal advertising strategies. Furthermore, the social media sharing feature helps expand the user base and reach more users, which is expected to maximize the effectiveness of advertising.

[0196] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0197] Step 1:

[0198] The user generates ad copy using the generative AI model, and then inputs the prompts and results into the device's input form. At this time, the user enters the ad copy and related information (user ID, campaign ID, etc.) and clicks the upload button.

[0199] Input: prompt text, ad copy, user ID, campaign ID

[0200] Output: JSON format data

[0201] Step 2:

[0202] The device compiles the input data into JSON format and sends it to the server. Specifically, JSON data is created that includes the user ID, campaign ID, ad copy, etc.

[0203] Input: Data entered by the user (prompt text, ad copy, user ID, campaign ID)

[0204] Output: JSON data (prompt text, ad copy, user ID, campaign ID)

[0205] Step 3:

[0206] The server parses the received JSON data and generates a log_id. The generated log_id, user ID, campaign ID, ad copy, and timestamp are saved in the database. The database stores this information in an organized manner for future searches and analysis.

[0207] Input: JSON data (prompt text, ad copy, user ID, campaign ID)

[0208] Output: Save to database (log_id, user ID, campaign ID, ad copy, timestamp)

[0209] Step 4:

[0210] Other users can view the ad logs uploaded through their devices and click reaction buttons such as "Like" or "Interested" on the ad logs that interest them.

[0211] Input: Ad logs viewed by the user

[0212] Output: Reaction data (log ID, reaction type)

[0213] Step 5:

[0214] The device receives the user's reaction and sends the reaction data (log ID, user ID, reaction type) to the server.

[0215] Input: User's reaction (log ID, reaction type)

[0216] Output: JSON data (log ID, user ID, reaction type)

[0217] Step 6:

[0218] The server analyzes the reaction data it receives and stores it in a database. Specifically, it registers the log ID, user ID, reaction type, timestamp, etc. in the database and manages the increase or decrease in the number of reactions.

[0219] Input: JSON data (log ID, user ID, reaction type)

[0220] Output: Save to database (log ID, user ID, reaction type, timestamp)

[0221] Step 7:

[0222] If a user finds an ad log useful, they click a button to share it on social media. This action embeds the ad copy into the URL for sharing on social media.

[0223] Input: Ad logs shared by users

[0224] Output: URL for SNS sharing

[0225] Step 8:

[0226] The device opens the generated SNS sharing URL in a new window and displays the SNS posting screen. The user can then confirm the content to be shared and complete the post.

[0227] Input: URL for SNS sharing

[0228] Output: SNS post screen

[0229] This completes the entire process, from generating ad logs to adding reactions and sharing on social media, creating a system that can measure advertising effectiveness based on user feedback and optimize advertising strategies.

[0230] 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.

[0231] This invention is a system that allows users to efficiently share logs generated using information generation devices and improve the knowledge of the entire community through reactions, and also combines an emotion engine that recognizes user emotions. In this system, each element of the user, terminal, and server works in cooperation with the emotion engine.

[0232] Uploading logs

[0233] User: First, the user uses the information generation device to input a prompt and obtain the result. For example, the user inputs "Please write a poem using AI" as the prompt and receives text such as "A quiet night, the stars shine brightly" as the result. Next, the user enters the generated prompt and result into the input form on the device and clicks the "Upload" button. This operation sends the prompt and result to the server in JSON format.

[0234] Terminal: Generates JSON data containing the input prompts and results and sends it to the server. The emotion engine also recognizes the user's emotions and sends that information to the server.

[0235] Server: The server parses the received JSON data and emotion data, generates a new log entry based on it, generates a log ID, and saves data such as the user ID, prompt, result, emotion information, and timestamp in the database.

[0236] Adding a reaction

[0237] Users: Other users can view the uploaded logs and react to the logs they find useful, for example, by selecting a specific log from the log list and clicking the "Like" button.

[0238] Terminal: When the reaction button is clicked, the log ID and reaction type, as well as the user's emotion information recognized by the emotion engine, are sent to the server.

[0239] Server: Receives reaction data and emotion information, and stores data such as user ID, reaction type, log ID, emotion information, and timestamp in a database. Also, adjusts the display order of logs based on the number of reactions and emotion information.

[0240] Sharing to social media

[0241] User: If you want to share a log you like on a social networking service (SNS), click the share button. For example, you can click the "Share" button to post the log on Twitter.

[0242] On the device: When the share button is clicked, a new window will open with the log contents (prompt and result) and related emotional information embedded in the URL for sharing on social media.

[0243] Specific examples

[0244] 1. Generate and upload logs:

[0245] Prompt: "Make a poem with AI."

[0246] Result: "A quiet night, the stars shine brightly."

[0247] The user fills in this prompt and the results and clicks the upload button.

[0248] The emotion engine recognizes the user's emotion as "satisfied" and also sends this information to the server.

[0249] The server stores the logs and emotional information in a database.

[0250] 2. Reaction to the log:

[0251] Another user views this log and clicks the "Like" button.

[0252] The emotion engine recognizes the user's emotion as "happy" and sends it along with the reaction data.

[0253] The server records reaction data and emotional information and reflects this in the display order of the logs.

[0254] 3. Sharing to social media:

[0255] The user clicks a button to share this log on Twitter.

[0256] The log content and the emotional information of "satisfaction" are embedded in a URL for sharing on social media, and a new window is opened and posted to the social media site.

[0257] The system allows users to efficiently share their AI-generated experiences and emotional data, facilitating greater knowledge and emotion-based interactions across the community.

[0258] The processing flow will be explained below.

[0259] Step 1:

[0260] User: Inputs a prompt into the information generator and generates a result for that prompt. For example, the user inputs the prompt "Please write a poem using AI" and receives the generated result "A quiet night, the stars shine brightly."

[0261] Step 2:

[0262] User: Enters the generated prompt and results into the input form on the device, and the emotion engine recognizes the emotion. The emotion engine obtains emotional information (e.g., satisfaction) from the user's facial expressions and voice.

[0263] Step 3:

[0264] Terminal: The input prompt, result, and emotion information are sent to the server in JSON format. The data is sent to the server using an HTTP POST request.

[0265] Step 4:

[0266] Server: Parses the received JSON data and generates a new log entry. Creates a log ID and saves information such as the user ID, prompt, result, emotion information, and timestamp in the database.

[0267] Step 5:

[0268] Users: View logs uploaded by other users. Logs are displayed in a list format, with a link to each log's details page.

[0269] Step 6:

[0270] User: Add a reaction to a specific log. For example, when clicking the "Like" button, the emotion engine will recognize the emotion again and process that information along with the reaction.

[0271] Step 7:

[0272] On the device: When a reaction button is clicked, data including the log ID, reaction type, and emotion information is sent to the server in JSON format using an HTTP POST request.

[0273] Step 8:

[0274] Server: Analyzes the received reaction data and stores the reaction and emotional information in a database. It also adjusts the display order based on the number of reactions and emotional information in the log.

[0275] Step 9:

[0276] User: If you want to share a specific log on a social networking service (SNS), click the SNS share button.

[0277] Step 10:

[0278] On the device, when the social media share button is clicked, a new window is opened with the log content (prompt and result) and related emotional information embedded in the social media share URL. The URL contains encoded text and displays the social media share screen.

[0279] The above is the specific processing flow of the system that combines the emotion engine of this invention. This system efficiently shares users' experiences with using generated AI and their emotion data, improving knowledge across the entire community and promoting emotion-based interactions.

[0280] Example 2

[0281] 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."

[0282] In conventional information sharing systems, when users share data or logs they generate with other users, they do not take into account the user's emotional information, and reactions to the shared data are based solely on numerical values, which means that they are unable to fully realize interactions based on user emotions or improve knowledge across the entire community.Furthermore, sharing to external platforms such as social media can sometimes be difficult.

[0283] 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.

[0284] In this invention, the server includes a means for transmitting data and emotional information generated by users to the server, a means for the server to receive, analyze, and store the data and emotional information in a database, and a means for adjusting the display order of data based on the number of reactions and the emotional information, thereby promoting interaction based on user emotions and improving knowledge throughout the community.

[0285] A "user" is a person or entity that uses the system, generates data using an information generating device, and shares or reacts to this data.

[0286] An "information generating device" is a device or software that generates information or data using a generative AI model or the like based on prompts entered by a user.

[0287] "Data" means text or other information generated by a user using an information generating device, including prompts and their results.

[0288] "Emotion information" is information that is recognized using an emotion engine to recognize the user's emotional state (e.g., "satisfied," "happy," etc.) and sent to the server as part of the data.

[0289] A "server" is a computer system on a network that receives, analyzes, and stores data and emotional information sent by users and provides this data to other users.

[0290] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation, and is a lightweight data exchange format for structuring data and storing and communicating it.

[0291] "Reactions" refer to actions other users take on shared data, and are expressed in the form of "likes" or comments.

[0292] A "database" is a collection of data built on a server, and is a system that stores and manages user-generated data, emotional information, and reactions.

[0293] "Display order" refers to the order in which the server displays data to other users, and is adjusted based on the number of reactions and emotional information.

[0294] "Social Networking Service" means an online service that enables users to share data with external social networking platforms.

[0295] This invention is a system that allows users to efficiently share data generated using information generation devices and improve the knowledge of the entire community through reactions, and also combines it with an emotion engine that recognizes the emotions of users. In this system, each element of the user, terminal, and server works in cooperation with the emotion engine.

[0296] Uploading logs

[0297] user

[0298] First, the user inputs a specific prompt sentence (e.g., "Please write a poem using AI") using the information generator. This information generator uses a generative AI model to generate data based on the input prompt. After receiving the generated result (e.g., "A quiet night, the stars shine"), the user enters the prompt and the result into the input form on their device and clicks the "Upload" button. This operation sends the prompt and the result to the server as JSON-formatted data. The emotion engine also recognizes the user's emotion (e.g., "Satisfied"), and this information is also sent.

[0299] Terminal

[0300] The device converts the input prompts and results into JSON format data and sends it to the server. In addition, an emotion engine (e.g., emotion recognition software) recognizes the user's emotions and sends that emotion information to the server. Examples of hardware used include PCs and smartphones. Software used includes Android (registered trademark) and iOS applications.

[0301] server

[0302] The server analyzes the received JSON data and emotion information and generates a new log entry. It stores data such as the log ID, user ID, prompt, result, emotion information, and timestamp in a database. To perform this processing, the server uses Python and a database management system (e.g., MySQL (registered trademark)).

[0303] Adding a reaction

[0304] user

[0305] Other users can view the log list provided by the server through a web browser or app and react to logs they like, for example, by selecting a specific log from the log list and clicking the "Like" button.

[0306] Terminal

[0307] When the reaction button is clicked, the device generates data including the target log ID and reaction type (e.g., "Like"), and recognizes the user's emotion (e.g., "Happy") using the emotion engine.The device then sends the reaction information and emotion information to the server.

[0308] server

[0309] The server analyzes the received reaction data and emotional information and adds a new entry to the database. Data such as user ID, reaction type, log ID, emotional information, and timestamp are saved. Furthermore, the server adjusts the display order of the data based on the number of reactions and emotional information, and displays the logs in the appropriate order for the user.

[0310] Sharing to social media

[0311] user

[0312] If a user wants to share a particular log on a social networking site, they can click the "Share" button. For example, they can click the "Share" button to post the log on Twitter.

[0313] Terminal

[0314] When the share button is clicked, the device opens a new window with the log contents (prompt and result) and emotional information embedded in the URL for sharing on social media, allowing the user to post directly to social media.

[0315] Specific examples

[0316] 1. Prompt: "Create a poem using AI."

[0317] 2. Result: "The stars shine brightly on a quiet night."

[0318] The user enters these prompts and results and clicks the upload button. The emotion engine recognizes the user's emotion as "satisfied," and this information is sent to the server and stored in the database. When another user views this log and clicks the "Like" button, the reaction data and the emotion information of "happy" are sent to the server and recorded in the database.

[0319] This provides a system that efficiently shares users' generated AI usage experiences and emotional data, improving knowledge across the community and promoting emotion-based interactions.

[0320] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0321] Step 1:

[0322] user

[0323] A user inputs a prompt (e.g., "Please write a poem using AI") into the information generator and receives the generated result (e.g., "The stars shine brightly on a quiet night"). The input is the prompt, and the output is the generated text. This data is used in subsequent processing.

[0324] Step 2:

[0325] user

[0326] Enter the generated prompt sentence and result into the input form on the terminal and click the "Upload" button. The input is the prompt sentence and its result, and the click operation triggers the next process.

[0327] Step 3:

[0328] Terminal

[0329] The terminal receives user input and converts it into JSON format data. The input is the prompt and its result, and the output is JSON format data. This data includes the prompt, the result, and a timestamp.

[0330] Step 4:

[0331] Terminal

[0332] The emotion engine recognizes the user's emotional information. The input is the user's emotional state, and the output is the emotional information (e.g., "Satisfied"). This information is also integrated into the JSON data.

[0333] Step 5:

[0334] Terminal

[0335] Send JSON data and emotion information to the server. The input is the generated JSON data, and the output is the data sent to the server.

[0336] Step 6:

[0337] server

[0338] The server receives and parses the JSON data. The input is the JSON data sent from the terminal, and the output is the parsed prompt, result, and emotion information.

[0339] Step 7:

[0340] server

[0341] Generates a new log entry and saves it to the database. The input is the parsed data, and the output is a new log entry inserted into the database. This entry contains the log ID, user ID, prompt, result, emotion information, and timestamp.

[0342] Step 8:

[0343] user

[0344] Other users view the log list from the database in a web browser or app. The input is a request to display the log list, and the output is the log data returned from the server.

[0345] Step 9:

[0346] user

[0347] Click the "Like" button for the log you like. The input is the log ID to react to, and the output is the trigger for the reaction operation.

[0348] Step 10:

[0349] Terminal

[0350] It generates reaction data (log ID, reaction type) and user emotion information. The input is the user's reaction operation and emotional state, and the output is reaction data and emotion information.

[0351] Step 11:

[0352] Terminal

[0353] The generated reaction data and emotion information are sent to the server. The input is the reaction data and emotion information, and the output is the data sent to the server.

[0354] Step 12:

[0355] server

[0356] The server receives the reaction data and emotion information, analyzes them, and stores them in a database. The input is the reaction data and emotion information from the device, and the output is the recorded entry in the database.

[0357] Step 13:

[0358] server

[0359] The display order of data is adjusted based on the number of reactions and emotional information. The input is the number of reactions and emotional information in the database, and the output is the log data to be displayed with priority.

[0360] Step 14:

[0361] user

[0362] To share a log you like on a social networking site, click the "Share" button. The input is the log ID to be shared, and the output is the trigger for the sharing operation.

[0363] Step 15:

[0364] Terminal

[0365] It detects when the share button is clicked and opens a new window with the log content and emotion information embedded in the URL for sharing on social media. The input is the log content and emotion information, and the output is a window for posting to social media.

[0366] This series of processing steps efficiently shares user-generated data and emotional information, and accumulates reactions from other users, facilitating improved knowledge and emotion-based interactions across the community.

[0367] (Application example 2)

[0368] 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."

[0369] Conventional information sharing systems provide functions for sharing logs generated by users and receiving reactions from other users, but because they do not take into account users' emotional information, it is difficult to properly evaluate the usefulness and relevance of logs across the community. In addition, they lack functions for prioritizing display of logs based on emotions and sharing to social media, so there is a need to improve user engagement.

[0370] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing the user's emotion and transmitting the emotion information to the server together with the log, means for analyzing the emotion information and storing it in association with the log, and means for adjusting the display order of logs that have gathered a certain number of reactions or more based on the reactions and emotion information. This makes it possible to share and prioritize the display of logs that take into account the user's emotion information.

[0371] An "information generating device" is a machine or software that receives a prompt from a user and generates information based on that prompt.

[0372] A "log" is a collection of prompts generated by a user using an information generating device, the results of those prompts, and related data.

[0373] A "server" is a computer system that receives data sent by users and stores it in a database.

[0374] An "emotion engine" is a machine learning model or algorithm for recognizing emotions from user input and analyzing that information.

[0375] A "prompt" is a request or instruction sentence that a user inputs to an information generating device.

[0376] A "reaction" is an evaluation or response that other users make to a log, and includes, for example, "likes" and comments.

[0377] A "database" is a data management system that stores structured data within a server and allows for easy search and retrieval.

[0378] A "social networking service" is a platform where different users can share information and communicate with each other.

[0379] "Emotion information" is data that indicates the user's emotional state as recognized by the emotion engine.

[0380] A system for implementing this invention allows users to efficiently share logs generated using information generation devices and combines emotion engines to improve the knowledge of the entire community. This system includes the following specific configuration and processing.

[0381] The user first inputs a prompt to the information generator. For example, the prompt is "Please write a poem using AI." Based on this prompt, the information generator generates a poem and returns a result such as "On a quiet night, the stars shine brightly."

[0382] The user then enters the generated log (prompt and result) into an input form on a device such as a smartphone and clicks the "Upload" button. This operation causes the device to send JSON data containing the prompt, result, and the user's emotional information recognized by the emotion engine to the server.

[0383] The server parses the received JSON data and saves data such as the user ID, prompt, result, emotion information, and timestamp as a new log entry in the database. For example, if the emotion information is "Satisfied," that information is also associated with the log and saved.

[0384] Other users can view the logs and react to the logs they find useful, for example by clicking the "Like" button. The device sends the log ID, reaction type, and the user's emotion information recognized by the emotion engine to the server.

[0385] The server receives the reaction data and emotional information, stores it in a database, and adjusts the display order of logs based on the number of reactions and emotional information. For example, logs that have received a certain number of "likes" will be displayed with priority over other logs.

[0386] Furthermore, if a user wants to share a log they like on a social networking service (SNS), they can click the "Share" button. This action causes the device to open a new window and post the log content and emotional information to the SNS sharing URL, embedding it in the URL.

[0387] A concrete example would be the following:

[0388] 1. User enters a prompt. Example: "Please write a poem using AI."

[0389] 2. As a result: "Quiet Night, Stars Shine" is obtained and uploaded

[0390] 3. The emotion engine recognizes the user's emotion as "satisfied"

[0391] 4. The server stores the logs and emotional information in a database

[0392] 5. Another user clicks "like" on the log and recognizes the emotion as "happy."

[0393] 6. The display order of logs will be adjusted and displayed with priority.

[0394] This system configuration enables sharing of logs and adjustment of display order taking into account users' emotional information, thereby improving engagement and knowledge across the entire community.

[0395] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0396] Step 1:

[0397] A user opens a smartphone application and inputs a prompt into the information generator, for example, "Please write a poem using AI." This input is sent to the generative AI model, and the resulting poem is "A quiet night, the stars shine brightly."

[0398] Step 2:

[0399] The user checks the generated log (prompt sentences and results), and the emotion engine recognizes the user's emotion from their facial expressions and voice. For example, the emotion engine recognizes the user's emotion as "satisfied."

[0400] Step 3:

[0401] The user clicks the "Upload" button to send the log and the recognized emotion information to the server. The device then packages the prompt, result, user ID, and emotion information into JSON format data and sends it to the server.

[0402] Step 4:

[0403] The server parses the received JSON data, which contains the user ID, prompt, result, emotion, and timestamp. The server parses this data and generates a new log entry.

[0404] Step 5:

[0405] The server stores the generated log entries in a database, which includes the user ID, prompt, result, emotion information, and a timestamp, allowing the logs to be searched and viewed later.

[0406] Step 6:

[0407] Other users can view the log and react to it by clicking "like" or commenting. For example, a user can click the "like" button. This action sends the reaction information (log ID, reaction type, user ID, and emotion information) from the device to the server.

[0408] Step 7:

[0409] The server analyzes the received reaction data and emotional information and stores it in a database. The server updates the engagement index in the log based on the type of reaction and the user's emotional information.

[0410] Step 8:

[0411] Based on the reaction and emotion information, the server adjusts the display order of the logs. For example, if a particular log receives a certain number of "likes," it will be displayed with priority over other logs.

[0412] Step 9:

[0413] To share the log on a social networking service, the user clicks the "Share" button. This action causes the device to embed the log content (prompt and result) and emotional information into a URL for sharing on the social networking service, and opens a new window to prepare for posting.

[0414] Step 10:

[0415] Once sharing to the SNS is complete, the log is posted on the SNS. This post contains the log content and emotional information, such as "satisfied," and can be viewed by other users on the SNS.

[0416] 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.

[0417] 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 (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.

[0418] 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.

[0419] [Second embodiment]

[0420] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0421] 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.

[0422] 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).

[0423] 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.

[0424] 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.

[0425] 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).

[0426] 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.

[0427] 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.

[0428] 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.

[0429] 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.

[0430] In the smart glasses 214, 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.

[0431] 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."

[0432] The present invention provides a system that allows users to efficiently share logs generated using information generation devices and improve the knowledge of the entire community through reactions. This system operates in cooperation with the elements of users, terminals, and servers.

[0433] Uploading logs

[0434] User: First, the user uses the information generator to generate a prompt and the corresponding result. Then, the user enters the generated prompt and result into an input form on the terminal. This input form has fields where the prompt and result can be entered separately. The user clicks the "Upload" button.

[0435] Terminal: The input prompts and results are compiled in JSON format and sent to the server, along with identifying information such as the user ID.

[0436] Server: Parses the received data, generates a log ID, and saves the log ID, user ID, prompt, result, timestamp, etc. in the database.

[0437] Adding a reaction

[0438] User: Next, other users can view the uploaded logs. A user interface is provided that displays a list of logs and a detailed page for each log. Useful logs have reaction buttons such as "Like" and "Helpful."

[0439] On the device: When a reaction button is clicked, the log ID and reaction type (e.g., "Like") are sent to the server.

[0440] Server: Receives reaction data and stores the user ID, reaction type, log ID, timestamp, etc. in the database. Also, increases or decreases the number of reactions as needed.

[0441] Sharing to social media

[0442] User: If the user finds the log useful, they can click the SNS share button to post the generated log and its results to SNS.

[0443] Device: When you click the share button, the log contents will be embedded in text format into a URL for sharing on social media, and the social media posting screen will open in a new window.

[0444] Specific examples

[0445] 1. Generate and upload logs:

[0446] Prompt: "Make a poem with AI."

[0447] Result: "A quiet night, the stars shine brightly."

[0448] The user fills in the prompts and results and clicks the upload button.

[0449] 2. Reaction to the log:

[0450] Another user views this log and clicks the "Like" button.

[0451] The number of "likes" increases and reaction information is recorded in the database.

[0452] 3. Sharing to social media:

[0453] The user clicks a button to share this log on Twitter.

[0454] A URL for sharing on social media will be generated, a new window will open, and the log content will be posted to the social media platform.

[0455] This allows other users to access the logs and easily obtain useful information. Furthermore, information can be spread through social media, making the convenience of generative AI known to many people.

[0456] The processing flow will be explained below.

[0457] Step 1:

[0458] User: Uses the information generator to input a prompt and receive a result. For example, the user inputs "Please write a poem using AI" as a prompt and receives the text "A quiet night, the stars shine brightly" as a result.

[0459] Step 2:

[0460] User: Enters the generated prompt and results into an input form on the device. For example, the input form has a field for the prompt and a field for the result, and the user enters text into each field.

[0461] Step 3:

[0462] User: Once the input is complete, click the "Upload" button on the device. This action sends the input data to the server.

[0463] Step 4:

[0464] Terminal: The input prompt and result are converted into JSON format and sent to the server along with necessary identification information such as the user ID. Specifically, the data is sent using an HTTP POST request.

[0465] Step 5:

[0466] Server: Parses the received JSON data and generates a new log entry based on it. It generates a log ID and saves data such as the user ID, prompt, result, and timestamp in the database.

[0467] Step 6:

[0468] Users: View logs uploaded by other users and give reactions to logs they like. For example, select a specific log from the log list, go to the details page, and click the "Like" button.

[0469] Step 7:

[0470] Terminal: When the reaction button is clicked, data including the log ID and reaction type is sent to the server. As with the server, an HTTP POST request is used.

[0471] Step 8:

[0472] Server: Analyzes the received reaction data and records it in a database based on the user ID, reaction type, log ID, timestamp, etc. Also, if it is necessary to increase or decrease the number of reactions, it handles that process.

[0473] Step 9:

[0474] User: If you want to share a log you like on a social networking service (SNS), click the share button. For example, you can click the "Share" button to post the log on Twitter.

[0475] Step 10:

[0476] On the device: When the share button is clicked, a new window is opened by embedding the text containing the log contents into the URL for sharing on social media. Specifically, the text containing the log prompt and result is encoded, a URL containing that text is generated, and the URL is opened in a new window.

[0477] The above are the specific processing steps when a user shares a log generated using AI, receives reactions, or shares it on social media.

[0478] Example 1

[0479] 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."

[0480] Conventional information sharing systems have faced challenges in efficiently sharing user-generated logs and promoting knowledge sharing within the community. Furthermore, they lacked the functionality to allow other users to add reactions to logs, limiting the collection and analysis of the resulting data. Furthermore, there was a lack of an easy way to share generated logs on social networking services. A system that could solve these challenges, efficiently share user-generated information, and improve the knowledge of the entire community was needed.

[0481] 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.

[0482] In this invention, the server includes means for converting the prompt and results generated by the user using the information generation device into JSON format and transmitting them to the server together with user identification information, means for receiving the prompt and results, generating a log ID, and storing it in a database, means for other users to give reactions to the prompt and results, means for receiving the reactions, storing them in a database, and updating the number of reactions, and means for users to share the prompt and results on a social networking service, thereby enabling users to efficiently share the information they generate and improve the knowledge of the entire community through reactions.

[0483] A "user" is an individual or entity that utilizes the system to input prompts into an information generator and receive the results.

[0484] An "information generating device" is a device that generates results in response to prompts entered by a user, such as a generative AI model.

[0485] A "prompt" refers to a question or instruction that a user inputs into an information generating device.

[0486] "Results" refers to the output generated by an information generating device based on a prompt.

[0487] "Input Form" refers to the interface on a web page through which a user enters prompts and results.

[0488] The "JSON format" is a lightweight data exchange format that represents data as key-value pairs.

[0489] "User Identification Information" means an ID or other identifying data that uniquely identifies a user.

[0490] A "server" is a computer system for receiving and processing data sent by users and terminals.

[0491] A "Log ID" is a unique server-generated identifier used to identify a particular set of prompts and results.

[0492] A "database" is a system for efficiently storing, managing, and retrieving data in digital form.

[0493] "Reactions" refer to feedback other users give to a particular prompt and result, expressed in the form of "likes" or "helpful."

[0494] "Social networking service" refers to an online platform that users use to share information, such as a social networking site.

[0495] This invention is a system that allows users to efficiently share prompts generated using generative AI models and the results, thereby improving the knowledge of the entire community. This system works in cooperation with the user, terminal, and server elements.

[0496] 1. User Actions

[0497] First, the user uses a generative AI model to generate a prompt and its results. An example of a generative AI model is ChatGPT. The user then enters the generated prompt and results into an input form on their device. This input form provides fields for entering the prompt and results separately, and the user clicks the "Upload" button after entering the information.

[0498] (Example)

[0499] Prompt: "Make a poem with AI."

[0500] Result: "A quiet night, the stars shine brightly."

[0501] 2. Device Operation

[0502] The terminal converts the prompts and results entered in the input form into JSON format. It also includes the user's identity information in the JSON data. The converted JSON data is sent to a specific API endpoint. For example, the terminal generates the following data:

[0503] json

[0504] {

[0505] "userID": "12345",

[0506] "prompt": "Create a poem with AI",

[0507] "result": "A quiet night, the stars shine brightly"

[0508] }

[0509] This data is sent as a POST request to the URL 'http: / / example.com / upload'.

[0510] 3. Server Processing

[0511] The server analyzes the received JSON data and generates a new log ID. The server saves the data (user ID, prompt, result, timestamp) including the generated log ID in a database. The database is operated using, for example, an RDBMS (Relational Database Management System).

[0512] (example)

[0513] Store the received data as follows:

[0514] Log ID: "67890"

[0515] User ID: "12345"

[0516] Prompt: "Make a poem with AI."

[0517] Result: "A quiet night, the stars shine brightly."

[0518] Timestamp: "2023-10-05T12:34:56Z"

[0519] 4. Viewing logs and adding reactions

[0520] Next, other users can browse the list of uploaded logs using a user interface provided in a web browser, select a log of interest, go to the details page, and click reaction buttons such as "Like" or "Helpful."

[0521] 5. Handling Reactions

[0522] When the reaction button is clicked, the device detects the click event and sends data including the log ID and reaction type (e.g., "Like") to the server. The server processes the received reaction data, saves it in the database, and updates the reaction count. For example, the data is saved in the following format:

[0523] User ID: "54321"

[0524] Log ID: "67890"

[0525] Reaction type: Like

[0526] Timestamp: "2023-10-05T12:35:00Z"

[0527] 6. Sharing on social media

[0528] Finally, if a user wants to share a specific log on a social networking service (SNS), they can click the SNS share button. The device will generate data containing the log content and a sharing URL, and open the SNS posting screen in a new window. For example, the following URL may be generated:

[0529] 'https: / / twitter.com / intent / tweet?text=Check out this log!%20prompt:%20Make a poem with AI%20result:%20A quiet night, the stars shine brightly'

[0530] This system allows users to efficiently share the generated information and improve the knowledge of the entire community through reactions. Information can also be easily spread through social media, widely communicating the convenience of generative AI.

[0531] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0532] Step 1:

[0533] User: Inputs a prompt to the generative AI model. As input, the user provides the generative AI model with the prompt "Please write a poem using AI." As a result, the generative AI model generates the output "A quiet night, the stars shine brightly." The user enters this result into an input form on their device.

[0534] Step 2:

[0535] Terminal: The prompt and result entered in the input form are converted into JSON format. As input, the prompt entered by the user, "Please write a poem using AI," and the result, "A quiet night, the stars shine brightly," are received. These data, along with the user ID, are converted into JSON format like {'userID': '12345', 'prompt': 'Please write a poem using AI', 'result': 'A quiet night, the stars shine brightly'}.

[0536] Step 3:

[0537] Terminal: Sends data converted to JSON format to an API endpoint. As input, it takes JSON formatted data and creates an HTTP POST request. It sends this to a specific URL (e.g. http: / / example.com / upload). The output is a status code of 200 if the request is successful.

[0538] Step 4:

[0539] Server: Parses the data received at the API endpoint and generates a log ID. As input, it receives the received JSON data and parses the user ID, prompt, and result. Based on this, it generates a new log ID "67890". As output, it obtains the data {'logID': '67890', 'userID': '12345', 'prompt': 'Create a poem with AI', 'result': 'A quiet night, the stars shine', 'timestamp': '2023-10-05T12:34:56Z'} containing the generated log ID.

[0540] Step 5:

[0541] Server: Saves the data including the generated log ID to the database. As input, it receives the data generated in the previous step and saves it to the database. The output is a notification that saving to the database is complete.

[0542] Step 6:

[0543] User: Another user views the log list in a web browser and navigates to the individual log details page. As input, the user enters the URL to access the log list page in the web browser. The output is a display of the viewable log list.

[0544] Step 7:

[0545] User: Clicks the "Like" button for a log they are interested in. The input is clicking the "Like" button after viewing a specific log detail page. The output is the occurrence of a "Like" event.

[0546] Step 8:

[0547] Terminal: Detects the click event of the reaction button and sends the log ID and reaction type to the server. Receives the click event of the "Like" button as input and converts the log ID "67890" and reaction type "Like" into JSON format. The output is a request to send to the API endpoint based on this data.

[0548] Step 9:

[0549] Server: Processes the received reaction data, saves it in the database, and updates the number of reactions. As input, it receives JSON-formatted reaction data and analyzes it for the user ID, log ID, and reaction type. Based on this, it saves it in the database and updates the number of reactions. The output is a notification that the database has been updated.

[0550] Step 10:

[0551] User: Clicks the SNS share button to share the log on a social networking service (SNS). The input is clicking the share button. The output is that a URL for posting to the SNS is generated and the SNS posting screen is opened in a new window.

[0552] (Application example 1)

[0553] 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."

[0554] Modern advertising strategies require measuring advertising effectiveness in real time and optimizing advertising content based on user feedback. However, conventional systems lacked mechanisms for efficiently collecting and analyzing the quality of ad copy generated by advertisers and user reactions, making it difficult to develop effective advertising strategies. Furthermore, the lack of an integrated function for sharing ad logs with social networking services made it difficult to expand the user base.

[0555] 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.

[0556] In this invention, the server includes: a means for inputting a log generated by a user using an information generating device; a means for transmitting the log to the server; a means for the server to receive the log and store it in a database; a means for other users to provide reactions to the log; a means for the server to receive the reactions and store them in a database; a means for the user to share the log on a social networking service; a means for an advertiser to generate advertising copy using a generative AI model and upload it as a log; a means for users to provide reactions to the displayed advertising log; and a means for analyzing the reaction data and measuring the effectiveness of the advertisement. This enables the quality and effectiveness of the advertising copy generated by the advertiser to be evaluated and optimized in real time. In addition, a social networking service sharing function is integrated to expand the user base, allowing the system to reach more users.

[0557] A "user" refers to an entity that uses an information generating device to generate a log and provides the log to the system.

[0558] "Information generating device" refers to a device through which a user inputs a prompt and generates a result in response to the prompt.

[0559] "Log" refers to data including prompts generated by a user using an information generating device and the results thereof.

[0560] "Server" refers to a computer system that receives logs and reaction data sent by users and stores and manages them in a database.

[0561] "Reaction" refers to the rating or feedback that other users give to a particular log.

[0562] A "database" refers to a system that systematically stores logs and reaction data and manages them in a manner that allows for search and analysis.

[0563] "Social Networking Service" means an online platform that enables users to share information and communicate with other users.

[0564] "Advertiser" refers to the entity that uses a generative AI model to create advertising copy and uploads that advertising copy to the system as a log.

[0565] "Generative AI model" refers to an artificial intelligence model that automatically generates ad copy and other information based on prompts entered by a user.

[0566] "Ad copy" refers to the advertising content generated by a generative AI model and served to users.

[0567] "Advertising Log" refers to a log containing advertising copy generated by an advertiser using a generative AI model and uploaded to the system.

[0568] "Measuring the effectiveness of advertising" refers to analyzing user reaction data and evaluating how much evaluation and interest a particular ad copy has generated.

[0569] This invention is a system that allows users to efficiently share logs generated using an information generation device and optimize the effectiveness of advertising through reactions. This system operates in cooperation with each element of the user, terminal, and server.

[0570] Generating and uploading logs

[0571] User: First, the advertiser user generates ad copy using the generative AI model. For example, they input a prompt such as "Generate an ad for a new drinking water product" and get the generated result. Then, they input this ad copy into the input form on their device and click the upload button.

[0572] Device: The entered ad copy and the corresponding results are compiled in JSON format and sent to the server, along with identifying information such as the user ID and campaign ID.

[0573] Server: Parse the received data, generate a log_id, and save the log_id, user ID, campaign ID, ad copy, results, timestamp, etc. in the database.

[0574] Adding a reaction

[0575] Users: Other users can view the uploaded ad logs and click reaction buttons such as "Like" or "Interested" on the ad logs they find useful.

[0576] Device: When the reaction button is clicked, the ad log ID and reaction type (e.g., "Like") are sent to the server.

[0577] Server: Receives reaction data and stores the user ID, reaction type, ad log ID, timestamp, etc. in a database. Also manages the increase / decrease in the number of reactions.

[0578] Sharing to social media

[0579] User: Clicks a button to share the ad log they found useful on social media.

[0580] Device: When you click the share button, the contents of the ad log will be embedded in text format into a URL for sharing on social media, and the social media posting screen will open in a new window.

[0581] Specific examples

[0582] 1. Generate and upload your ad:

[0583] Prompt: "Generate a new drinking water ad"

[0584] Result: "Try Sparkling Water, a refreshing new experience."

[0585] The advertiser enters this advertisement text and clicks the upload button.

[0586] 2. Adding a reaction:

[0587] Another user views this ad log and clicks the "Like" button.

[0588] The number of "likes" increases and reaction information is recorded in the database.

[0589] 3. Sharing to social media:

[0590] The user clicks a button to share this ad log on Twitter.

[0591] An advertising caption such as "Try a new refreshing sparkling water experience" is automatically embedded in the Twitter post screen, and a new window opens.

[0592] This system allows advertisers to measure the effectiveness of their ads in real time, providing them with a powerful tool for developing optimal advertising strategies. Furthermore, the social media sharing feature helps expand the user base and reach more users, which is expected to maximize the effectiveness of advertising.

[0593] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0594] Step 1:

[0595] The user generates ad copy using the generative AI model, and then inputs the prompts and results into the device's input form. At this time, the user enters the ad copy and related information (user ID, campaign ID, etc.) and clicks the upload button.

[0596] Input: prompt text, ad copy, user ID, campaign ID

[0597] Output: JSON format data

[0598] Step 2:

[0599] The device compiles the input data into JSON format and sends it to the server. Specifically, JSON data is created that includes the user ID, campaign ID, ad copy, etc.

[0600] Input: Data entered by the user (prompt text, ad copy, user ID, campaign ID)

[0601] Output: JSON data (prompt text, ad copy, user ID, campaign ID)

[0602] Step 3:

[0603] The server parses the received JSON data and generates a log_id. The generated log_id, user ID, campaign ID, ad copy, and timestamp are saved in the database. The database stores this information in an organized manner for future searches and analysis.

[0604] Input: JSON data (prompt text, ad copy, user ID, campaign ID)

[0605] Output: Save to database (log_id, user ID, campaign ID, ad copy, timestamp)

[0606] Step 4:

[0607] Other users can view the ad logs uploaded through their devices and click reaction buttons such as "Like" or "Interested" on the ad logs that interest them.

[0608] Input: Ad logs viewed by the user

[0609] Output: Reaction data (log ID, reaction type)

[0610] Step 5:

[0611] The device receives the user's reaction and sends the reaction data (log ID, user ID, reaction type) to the server.

[0612] Input: User's reaction (log ID, reaction type)

[0613] Output: JSON data (log ID, user ID, reaction type)

[0614] Step 6:

[0615] The server analyzes the reaction data it receives and stores it in a database. Specifically, it registers the log ID, user ID, reaction type, timestamp, etc. in the database and manages the increase or decrease in the number of reactions.

[0616] Input: JSON data (log ID, user ID, reaction type)

[0617] Output: Save to database (log ID, user ID, reaction type, timestamp)

[0618] Step 7:

[0619] If a user finds an ad log useful, they click a button to share it on social media. This action embeds the ad copy into the URL for sharing on social media.

[0620] Input: Ad logs shared by users

[0621] Output: URL for SNS sharing

[0622] Step 8:

[0623] The device opens the generated SNS sharing URL in a new window and displays the SNS posting screen. The user can then confirm the content to be shared and complete the post.

[0624] Input: URL for SNS sharing

[0625] Output: SNS post screen

[0626] This completes the entire process, from generating ad logs to adding reactions and sharing on social media, creating a system that can measure advertising effectiveness based on user feedback and optimize advertising strategies.

[0627] 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.

[0628] This invention is a system that allows users to efficiently share logs generated using information generation devices and improve the knowledge of the entire community through reactions, and also combines an emotion engine that recognizes user emotions. In this system, each element of the user, terminal, and server works in cooperation with the emotion engine.

[0629] Uploading logs

[0630] User: First, the user uses the information generation device to input a prompt and obtain the result. For example, the user inputs "Please write a poem using AI" as the prompt and receives text such as "A quiet night, the stars shine brightly" as the result. Next, the user enters the generated prompt and result into the input form on the device and clicks the "Upload" button. This operation sends the prompt and result to the server in JSON format.

[0631] Terminal: Generates JSON data containing the input prompts and results and sends it to the server. The emotion engine also recognizes the user's emotions and sends that information to the server.

[0632] Server: The server parses the received JSON data and emotion data, generates a new log entry based on it, generates a log ID, and saves data such as the user ID, prompt, result, emotion information, and timestamp in the database.

[0633] Adding a reaction

[0634] Users: Other users can view the uploaded logs and react to the logs they find useful, for example, by selecting a specific log from the log list and clicking the "Like" button.

[0635] Terminal: When the reaction button is clicked, the log ID and reaction type, as well as the user's emotion information recognized by the emotion engine, are sent to the server.

[0636] Server: Receives reaction data and emotion information, and stores data such as user ID, reaction type, log ID, emotion information, and timestamp in a database. Also, adjusts the display order of logs based on the number of reactions and emotion information.

[0637] Sharing to social media

[0638] User: If you want to share a log you like on a social networking service (SNS), click the share button. For example, you can click the "Share" button to post the log on Twitter.

[0639] On the device: When the share button is clicked, a new window will open with the log contents (prompt and result) and related emotional information embedded in the URL for sharing on social media.

[0640] Specific examples

[0641] 1. Generate and upload logs:

[0642] Prompt: "Make a poem with AI."

[0643] Result: "A quiet night, the stars shine brightly."

[0644] The user fills in this prompt and the results and clicks the upload button.

[0645] The emotion engine recognizes the user's emotion as "satisfied" and also sends this information to the server.

[0646] The server stores the logs and emotional information in a database.

[0647] 2. Reaction to the log:

[0648] Another user views this log and clicks the "Like" button.

[0649] The emotion engine recognizes the user's emotion as "happy" and sends it along with the reaction data.

[0650] The server records reaction data and emotional information and reflects this in the display order of the logs.

[0651] 3. Sharing to social media:

[0652] The user clicks a button to share this log on Twitter.

[0653] The log content and the emotional information of "satisfaction" are embedded in a URL for sharing on social media, and a new window is opened and posted to the social media site.

[0654] The system allows users to efficiently share their AI-generated experiences and emotional data, facilitating greater knowledge and emotion-based interactions across the community.

[0655] The processing flow will be explained below.

[0656] Step 1:

[0657] User: Inputs a prompt into the information generator and generates a result for that prompt. For example, the user inputs the prompt "Please write a poem using AI" and receives the generated result "A quiet night, the stars shine brightly."

[0658] Step 2:

[0659] User: Enters the generated prompt and results into the input form on the device, and the emotion engine recognizes the emotion. The emotion engine obtains emotional information (e.g., satisfaction) from the user's facial expressions and voice.

[0660] Step 3:

[0661] Terminal: The input prompt, result, and emotion information are sent to the server in JSON format. The data is sent to the server using an HTTP POST request.

[0662] Step 4:

[0663] Server: Parses the received JSON data and generates a new log entry. Creates a log ID and saves information such as the user ID, prompt, result, emotion information, and timestamp in the database.

[0664] Step 5:

[0665] Users: View logs uploaded by other users. Logs are displayed in a list format, with a link to each log's details page.

[0666] Step 6:

[0667] User: Add a reaction to a specific log. For example, when clicking the "Like" button, the emotion engine will recognize the emotion again and process that information along with the reaction.

[0668] Step 7:

[0669] On the device: When a reaction button is clicked, data including the log ID, reaction type, and emotion information is sent to the server in JSON format using an HTTP POST request.

[0670] Step 8:

[0671] Server: Analyzes the received reaction data and stores the reaction and emotional information in a database. It also adjusts the display order based on the number of reactions and emotional information in the log.

[0672] Step 9:

[0673] User: If you want to share a specific log on a social networking service (SNS), click the SNS share button.

[0674] Step 10:

[0675] On the device, when the social media share button is clicked, a new window is opened with the log content (prompt and result) and related emotional information embedded in the social media share URL. The URL contains encoded text and displays the social media share screen.

[0676] The above is the specific processing flow of the system that combines the emotion engine of this invention. This system efficiently shares users' experiences with using generated AI and their emotion data, improving knowledge across the entire community and promoting emotion-based interactions.

[0677] Example 2

[0678] 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."

[0679] In conventional information sharing systems, when users share data or logs they generate with other users, they do not take into account the user's emotional information, and reactions to the shared data are based solely on numerical values, which means that they are unable to fully realize interactions based on user emotions or improve knowledge across the entire community.Furthermore, sharing to external platforms such as social media can sometimes be difficult.

[0680] 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.

[0681] In this invention, the server includes a means for transmitting data and emotional information generated by users to the server, a means for the server to receive, analyze, and store the data and emotional information in a database, and a means for adjusting the display order of data based on the number of reactions and the emotional information, thereby promoting interaction based on user emotions and improving knowledge throughout the community.

[0682] A "user" is a person or entity that uses the system, generates data using an information generating device, and shares or reacts to this data.

[0683] An "information generating device" is a device or software that generates information or data using a generative AI model or the like based on prompts entered by a user.

[0684] "Data" means text or other information generated by a user using an information generating device, including prompts and their results.

[0685] "Emotion information" is information that is recognized using an emotion engine to recognize the user's emotional state (e.g., "satisfied," "happy," etc.) and sent to the server as part of the data.

[0686] A "server" is a computer system on a network that receives, analyzes, and stores data and emotional information sent by users and provides this data to other users.

[0687] "JSON format" is an abbreviation for JavaScript Object Notation, a lightweight data exchange format for storing and communicating structured data.

[0688] "Reactions" refer to actions other users take on shared data, and are expressed in the form of "likes" or comments.

[0689] A "database" is a collection of data built on a server, and is a system that stores and manages user-generated data, emotional information, and reactions.

[0690] "Display order" refers to the order in which the server displays data to other users, and is adjusted based on the number of reactions and emotional information.

[0691] "Social Networking Service" means an online service that enables users to share data with external social networking platforms.

[0692] This invention is a system that allows users to efficiently share data generated using information generation devices and improve the knowledge of the entire community through reactions, and also combines it with an emotion engine that recognizes the emotions of users. In this system, each element of the user, terminal, and server works in cooperation with the emotion engine.

[0693] Uploading logs

[0694] user

[0695] First, the user inputs a specific prompt sentence (e.g., "Please write a poem using AI") using the information generator. This information generator uses a generative AI model to generate data based on the input prompt. After receiving the generated result (e.g., "A quiet night, the stars shine"), the user enters the prompt and the result into the input form on their device and clicks the "Upload" button. This operation sends the prompt and the result to the server as JSON-formatted data. The emotion engine also recognizes the user's emotion (e.g., "Satisfied"), and this information is also sent.

[0696] Terminal

[0697] The device converts the input prompts and results into JSON format data and sends it to the server. In addition, an emotion engine (e.g., emotion recognition software) recognizes the user's emotions and sends that emotion information to the server. Examples of hardware used include PCs and smartphones, and software such as Android or iOS applications.

[0698] server

[0699] The server analyzes the received JSON data and emotion information and generates a new log entry. It stores data such as the log ID, user ID, prompt, result, emotion information, and timestamp in a database. The server uses Python and a database management system (e.g., MySQL) to perform this processing.

[0700] Adding a reaction

[0701] user

[0702] Other users can view the log list provided by the server through a web browser or app and react to logs they like, for example, by selecting a specific log from the log list and clicking the "Like" button.

[0703] Terminal

[0704] When the reaction button is clicked, the device generates data including the target log ID and reaction type (e.g., "Like"), and recognizes the user's emotion (e.g., "Happy") using the emotion engine.The device then sends the reaction information and emotion information to the server.

[0705] server

[0706] The server analyzes the received reaction data and emotional information and adds a new entry to the database. Data such as user ID, reaction type, log ID, emotional information, and timestamp are saved. Furthermore, the server adjusts the display order of the data based on the number of reactions and emotional information, and displays the logs in the appropriate order for the user.

[0707] Sharing to social media

[0708] user

[0709] If a user wants to share a particular log on a social networking site, they can click the "Share" button. For example, they can click the "Share" button to post the log on Twitter.

[0710] Terminal

[0711] When the share button is clicked, the device opens a new window with the log contents (prompt and result) and emotional information embedded in the URL for sharing on social media, allowing the user to post directly to social media.

[0712] Specific examples

[0713] 1. Prompt: "Create a poem using AI."

[0714] 2. Result: "The stars shine brightly on a quiet night."

[0715] The user enters these prompts and results and clicks the upload button. The emotion engine recognizes the user's emotion as "satisfied," and this information is sent to the server and stored in the database. When another user views this log and clicks the "Like" button, the reaction data and the emotion information of "happy" are sent to the server and recorded in the database.

[0716] This provides a system that efficiently shares users' generated AI usage experiences and emotional data, improving knowledge across the community and promoting emotion-based interactions.

[0717] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0718] Step 1:

[0719] user

[0720] A user inputs a prompt (e.g., "Please write a poem using AI") into the information generator and receives the generated result (e.g., "The stars shine brightly on a quiet night"). The input is the prompt, and the output is the generated text. This data is used in subsequent processing.

[0721] Step 2:

[0722] user

[0723] Enter the generated prompt sentence and result into the input form on the terminal and click the "Upload" button. The input is the prompt sentence and its result, and the click operation triggers the next process.

[0724] Step 3:

[0725] Terminal

[0726] The terminal receives user input and converts it into JSON format data. The input is the prompt and its result, and the output is JSON format data. This data includes the prompt, the result, and a timestamp.

[0727] Step 4:

[0728] Terminal

[0729] The emotion engine recognizes the user's emotional information. The input is the user's emotional state, and the output is the emotional information (e.g., "Satisfied"). This information is also integrated into the JSON data.

[0730] Step 5:

[0731] Terminal

[0732] Send JSON data and emotion information to the server. The input is the generated JSON data, and the output is the data sent to the server.

[0733] Step 6:

[0734] server

[0735] The server receives and parses the JSON data. The input is the JSON data sent from the terminal, and the output is the parsed prompt, result, and emotion information.

[0736] Step 7:

[0737] server

[0738] Generates a new log entry and saves it to the database. The input is the parsed data, and the output is a new log entry inserted into the database. This entry contains the log ID, user ID, prompt, result, emotion information, and timestamp.

[0739] Step 8:

[0740] user

[0741] Other users view the log list from the database in a web browser or app. The input is a request to display the log list, and the output is the log data returned from the server.

[0742] Step 9:

[0743] user

[0744] Click the "Like" button for the log you like. The input is the log ID to react to, and the output is the trigger for the reaction operation.

[0745] Step 10:

[0746] Terminal

[0747] It generates reaction data (log ID, reaction type) and user emotion information. The input is the user's reaction operation and emotional state, and the output is reaction data and emotion information.

[0748] Step 11:

[0749] Terminal

[0750] The generated reaction data and emotion information are sent to the server. The input is the reaction data and emotion information, and the output is the data sent to the server.

[0751] Step 12:

[0752] server

[0753] The server receives the reaction data and emotion information, analyzes them, and stores them in a database. The input is the reaction data and emotion information from the device, and the output is the recorded entry in the database.

[0754] Step 13:

[0755] server

[0756] The display order of data is adjusted based on the number of reactions and emotional information. The input is the number of reactions and emotional information in the database, and the output is the log data to be displayed with priority.

[0757] Step 14:

[0758] user

[0759] To share a log you like on a social networking site, click the "Share" button. The input is the log ID to be shared, and the output is the trigger for the sharing operation.

[0760] Step 15:

[0761] Terminal

[0762] It detects when the share button is clicked and opens a new window with the log content and emotion information embedded in the URL for sharing on social media. The input is the log content and emotion information, and the output is a window for posting to social media.

[0763] This series of processing steps efficiently shares user-generated data and emotional information, and accumulates reactions from other users, facilitating improved knowledge and emotion-based interactions across the community.

[0764] (Application example 2)

[0765] 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."

[0766] Conventional information sharing systems provide functions for sharing logs generated by users and receiving reactions from other users, but because they do not take into account users' emotional information, it is difficult to properly evaluate the usefulness and relevance of logs across the community. In addition, they lack functions for prioritizing display of logs based on emotions and sharing to social media, so there is a need to improve user engagement.

[0767] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing the user's emotion and transmitting the emotion information to the server together with the log, means for analyzing the emotion information and storing it in association with the log, and means for adjusting the display order of logs that have gathered a certain number of reactions or more based on the reactions and emotion information. This makes it possible to share and prioritize the display of logs that take into account the user's emotion information.

[0768] An "information generating device" is a machine or software that receives a prompt from a user and generates information based on that prompt.

[0769] A "log" is a collection of prompts generated by a user using an information generating device, the results of those prompts, and related data.

[0770] A "server" is a computer system that receives data sent by users and stores it in a database.

[0771] An "emotion engine" is a machine learning model or algorithm for recognizing emotions from user input and analyzing that information.

[0772] A "prompt" is a request or instruction sentence that a user inputs to an information generating device.

[0773] A "reaction" is an evaluation or response that other users make to a log, and includes, for example, "likes" and comments.

[0774] A "database" is a data management system that stores structured data within a server and allows for easy search and retrieval.

[0775] A "social networking service" is a platform where different users can share information and communicate with each other.

[0776] "Emotion information" is data that indicates the user's emotional state as recognized by the emotion engine.

[0777] A system for implementing this invention allows users to efficiently share logs generated using information generation devices and combines emotion engines to improve the knowledge of the entire community. This system includes the following specific configuration and processing.

[0778] The user first inputs a prompt to the information generator. For example, the prompt is "Please write a poem using AI." Based on this prompt, the information generator generates a poem and returns a result such as "On a quiet night, the stars shine brightly."

[0779] The user then enters the generated log (prompt and result) into an input form on a device such as a smartphone and clicks the "Upload" button. This operation causes the device to send JSON data containing the prompt, result, and the user's emotional information recognized by the emotion engine to the server.

[0780] The server parses the received JSON data and saves data such as the user ID, prompt, result, emotion information, and timestamp as a new log entry in the database. For example, if the emotion information is "Satisfied," that information is also associated with the log and saved.

[0781] Other users can view the logs and react to the logs they find useful, for example by clicking the "Like" button. The device sends the log ID, reaction type, and the user's emotion information recognized by the emotion engine to the server.

[0782] The server receives the reaction data and emotional information, stores it in a database, and adjusts the display order of logs based on the number of reactions and emotional information. For example, logs that have received a certain number of "likes" will be displayed with priority over other logs.

[0783] Furthermore, if a user wants to share a log they like on a social networking service (SNS), they can click the "Share" button. This action causes the device to open a new window and post the log content and emotional information to the SNS sharing URL, embedding it in the URL.

[0784] A concrete example would be the following:

[0785] 1. User enters a prompt. Example: "Please write a poem using AI."

[0786] 2. As a result: "Quiet Night, Stars Shine" is obtained and uploaded

[0787] 3. The emotion engine recognizes the user's emotion as "satisfied"

[0788] 4. The server stores the logs and emotional information in a database

[0789] 5. Another user clicks "like" on the log and recognizes the emotion as "happy."

[0790] 6. The display order of logs will be adjusted and displayed with priority.

[0791] This system configuration enables sharing of logs and adjustment of display order taking into account users' emotional information, thereby improving engagement and knowledge across the entire community.

[0792] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0793] Step 1:

[0794] A user opens a smartphone application and inputs a prompt into the information generator, for example, "Please write a poem using AI." This input is sent to the generative AI model, and the resulting poem is "A quiet night, the stars shine brightly."

[0795] Step 2:

[0796] The user checks the generated log (prompt sentences and results), and the emotion engine recognizes the user's emotion from their facial expressions and voice. For example, the emotion engine recognizes the user's emotion as "satisfied."

[0797] Step 3:

[0798] The user clicks the "Upload" button to send the log and the recognized emotion information to the server. The device then packages the prompt, result, user ID, and emotion information into JSON format data and sends it to the server.

[0799] Step 4:

[0800] The server parses the received JSON data, which contains the user ID, prompt, result, emotion, and timestamp. The server parses this data and generates a new log entry.

[0801] Step 5:

[0802] The server stores the generated log entries in a database, which includes the user ID, prompt, result, emotion information, and a timestamp, allowing the logs to be searched and viewed later.

[0803] Step 6:

[0804] Other users can view the log and react to it by clicking "like" or commenting. For example, a user can click the "like" button. This action sends the reaction information (log ID, reaction type, user ID, and emotion information) from the device to the server.

[0805] Step 7:

[0806] The server analyzes the received reaction data and emotional information and stores it in a database. The server updates the engagement index in the log based on the type of reaction and the user's emotional information.

[0807] Step 8:

[0808] Based on the reaction and emotion information, the server adjusts the display order of the logs. For example, if a particular log receives a certain number of "likes," it will be displayed with priority over other logs.

[0809] Step 9:

[0810] To share the log on a social networking service, the user clicks the "Share" button. This action causes the device to embed the log content (prompt and result) and emotional information into a URL for sharing on the social networking service, and opens a new window to prepare for posting.

[0811] Step 10:

[0812] Once sharing to the SNS is complete, the log is posted on the SNS. This post contains the log content and emotional information, such as "satisfied," and can be viewed by other users on the SNS.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] [Third embodiment]

[0817] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0818] 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.

[0819] 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).

[0820] 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.

[0821] 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.

[0822] 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).

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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."

[0829] The present invention provides a system that allows users to efficiently share logs generated using information generation devices and improve the knowledge of the entire community through reactions. This system operates in cooperation with the elements of users, terminals, and servers.

[0830] Uploading logs

[0831] User: First, the user uses the information generator to generate a prompt and the corresponding result. Then, the user enters the generated prompt and result into an input form on the terminal. This input form has fields where the prompt and result can be entered separately. The user clicks the "Upload" button.

[0832] Terminal: The input prompts and results are compiled in JSON format and sent to the server, along with identifying information such as the user ID.

[0833] Server: Parses the received data, generates a log ID, and saves the log ID, user ID, prompt, result, timestamp, etc. in the database.

[0834] Adding a reaction

[0835] User: Next, other users can view the uploaded logs. A user interface is provided that displays a list of logs and a detailed page for each log. Useful logs have reaction buttons such as "Like" and "Helpful."

[0836] On the device: When a reaction button is clicked, the log ID and reaction type (e.g., "Like") are sent to the server.

[0837] Server: Receives reaction data and stores the user ID, reaction type, log ID, timestamp, etc. in the database. Also, increases or decreases the number of reactions as needed.

[0838] Sharing to social media

[0839] User: If the user finds the log useful, they can click the SNS share button to post the generated log and its results to SNS.

[0840] Device: When you click the share button, the log contents will be embedded in text format into a URL for sharing on social media, and the social media posting screen will open in a new window.

[0841] Specific examples

[0842] 1. Generate and upload logs:

[0843] Prompt: "Make a poem with AI."

[0844] Result: "A quiet night, the stars shine brightly."

[0845] The user fills in the prompts and results and clicks the upload button.

[0846] 2. Reaction to the log:

[0847] Another user views this log and clicks the "Like" button.

[0848] The number of "likes" increases and reaction information is recorded in the database.

[0849] 3. Sharing to social media:

[0850] The user clicks a button to share this log on Twitter.

[0851] A URL for sharing on social media will be generated, a new window will open, and the log content will be posted to the social media platform.

[0852] This allows other users to access the logs and easily obtain useful information. Furthermore, information can be spread through social media, making the convenience of generative AI known to many people.

[0853] The processing flow will be explained below.

[0854] Step 1:

[0855] User: Uses the information generator to input a prompt and receive a result. For example, the user inputs "Please write a poem using AI" as a prompt and receives the text "A quiet night, the stars shine brightly" as a result.

[0856] Step 2:

[0857] User: Enters the generated prompt and results into an input form on the device. For example, the input form has a field for the prompt and a field for the result, and the user enters text into each field.

[0858] Step 3:

[0859] User: Once the input is complete, click the "Upload" button on the device. This action sends the input data to the server.

[0860] Step 4:

[0861] Terminal: The input prompt and result are converted into JSON format and sent to the server along with necessary identification information such as the user ID. Specifically, the data is sent using an HTTP POST request.

[0862] Step 5:

[0863] Server: Parses the received JSON data and generates a new log entry based on it. It generates a log ID and saves data such as the user ID, prompt, result, and timestamp in the database.

[0864] Step 6:

[0865] Users: View logs uploaded by other users and give reactions to logs they like. For example, select a specific log from the log list, go to the details page, and click the "Like" button.

[0866] Step 7:

[0867] Terminal: When the reaction button is clicked, data including the log ID and reaction type is sent to the server. As with the server, an HTTP POST request is used.

[0868] Step 8:

[0869] Server: Analyzes the received reaction data and records it in a database based on the user ID, reaction type, log ID, timestamp, etc. Also, if it is necessary to increase or decrease the number of reactions, it handles that process.

[0870] Step 9:

[0871] User: If you want to share a log you like on a social networking service (SNS), click the share button. For example, you can click the "Share" button to post the log on Twitter.

[0872] Step 10:

[0873] On the device: When the share button is clicked, a new window is opened by embedding the text containing the log contents into the URL for sharing on social media. Specifically, the text containing the log prompt and result is encoded, a URL containing that text is generated, and the URL is opened in a new window.

[0874] The above are the specific processing steps when a user shares a log generated using AI, receives reactions, or shares it on social media.

[0875] Example 1

[0876] 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."

[0877] Conventional information sharing systems have faced challenges in efficiently sharing user-generated logs and promoting knowledge sharing within the community. Furthermore, they lacked the functionality to allow other users to add reactions to logs, limiting the collection and analysis of the resulting data. Furthermore, there was a lack of an easy way to share generated logs on social networking services. A system that could solve these challenges, efficiently share user-generated information, and improve the knowledge of the entire community was needed.

[0878] 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.

[0879] In this invention, the server includes means for converting the prompt and results generated by the user using the information generation device into JSON format and transmitting them to the server together with user identification information, means for receiving the prompt and results, generating a log ID, and storing it in a database, means for other users to give reactions to the prompt and results, means for receiving the reactions, storing them in a database, and updating the number of reactions, and means for users to share the prompt and results on a social networking service, thereby enabling users to efficiently share the information they generate and improve the knowledge of the entire community through reactions.

[0880] A "user" is an individual or entity that utilizes the system to input prompts into an information generator and receive the results.

[0881] An "information generating device" is a device that generates results in response to prompts entered by a user, such as a generative AI model.

[0882] A "prompt" refers to a question or instruction that a user inputs into an information generating device.

[0883] "Results" refers to the output generated by an information generating device based on a prompt.

[0884] "Input Form" refers to the interface on a web page through which a user enters prompts and results.

[0885] The "JSON format" is a lightweight data exchange format that represents data as key-value pairs.

[0886] "User Identification Information" means an ID or other identifying data that uniquely identifies a user.

[0887] A "server" is a computer system for receiving and processing data sent by users and terminals.

[0888] A "Log ID" is a unique server-generated identifier used to identify a particular set of prompts and results.

[0889] A "database" is a system for efficiently storing, managing, and retrieving data in digital form.

[0890] "Reactions" refer to feedback other users give to a particular prompt and result, expressed in the form of "likes" or "helpful."

[0891] "Social networking service" refers to an online platform that users use to share information, such as a social networking site.

[0892] This invention is a system that allows users to efficiently share prompts generated using generative AI models and the results, thereby improving the knowledge of the entire community. This system works in cooperation with the user, terminal, and server elements.

[0893] 1. User Actions

[0894] First, the user uses a generative AI model to generate a prompt and its results. An example of a generative AI model is ChatGPT. The user then enters the generated prompt and results into an input form on their device. This input form provides fields for entering the prompt and results separately, and the user clicks the "Upload" button after entering the information.

[0895] (Example)

[0896] Prompt: "Make a poem with AI."

[0897] Result: "A quiet night, the stars shine brightly."

[0898] 2. Device Operation

[0899] The terminal converts the prompts and results entered in the input form into JSON format. It also includes the user's identity information in the JSON data. The converted JSON data is sent to a specific API endpoint. For example, the terminal generates the following data:

[0900] json

[0901] {

[0902] "userID": "12345",

[0903] "prompt": "Create a poem with AI",

[0904] "result": "A quiet night, the stars shine brightly"

[0905] }

[0906] This data is sent as a POST request to the URL 'http: / / example.com / upload'.

[0907] 3. Server Processing

[0908] The server analyzes the received JSON data and generates a new log ID. The server saves the data (user ID, prompt, result, timestamp) including the generated log ID in a database. The database is operated using, for example, an RDBMS (Relational Database Management System).

[0909] (example)

[0910] Store the received data as follows:

[0911] Log ID: "67890"

[0912] User ID: "12345"

[0913] Prompt: "Make a poem with AI."

[0914] Result: "A quiet night, the stars shine brightly."

[0915] Timestamp: "2023-10-05T12:34:56Z"

[0916] 4. Viewing logs and adding reactions

[0917] Next, other users can browse the list of uploaded logs using a user interface provided in a web browser, select a log of interest, go to the details page, and click reaction buttons such as "Like" or "Helpful."

[0918] 5. Handling Reactions

[0919] When the reaction button is clicked, the device detects the click event and sends data including the log ID and reaction type (e.g., "Like") to the server. The server processes the received reaction data, saves it in the database, and updates the reaction count. For example, the data is saved in the following format:

[0920] User ID: "54321"

[0921] Log ID: "67890"

[0922] Reaction type: Like

[0923] Timestamp: "2023-10-05T12:35:00Z"

[0924] 6. Sharing on social media

[0925] Finally, if a user wants to share a specific log on a social networking service (SNS), they can click the SNS share button. The device will generate data containing the log content and a sharing URL, and open the SNS posting screen in a new window. For example, the following URL may be generated:

[0926] 'https: / / twitter.com / intent / tweet?text=Check out this log!%20prompt:%20Make a poem with AI%20result:%20A quiet night, the stars shine brightly'

[0927] This system allows users to efficiently share the generated information and improve the knowledge of the entire community through reactions. Information can also be easily spread through social media, widely communicating the convenience of generative AI.

[0928] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0929] Step 1:

[0930] User: Inputs a prompt to the generative AI model. As input, the user provides the generative AI model with the prompt "Please write a poem using AI." As a result, the generative AI model generates the output "A quiet night, the stars shine brightly." The user enters this result into an input form on their device.

[0931] Step 2:

[0932] Terminal: The prompt and result entered in the input form are converted into JSON format. As input, the prompt entered by the user, "Please write a poem using AI," and the result, "A quiet night, the stars shine brightly," are received. These data, along with the user ID, are converted into JSON format like {'userID': '12345', 'prompt': 'Please write a poem using AI', 'result': 'A quiet night, the stars shine brightly'}.

[0933] Step 3:

[0934] Terminal: Sends data converted to JSON format to an API endpoint. As input, it takes JSON formatted data and creates an HTTP POST request. It sends this to a specific URL (e.g. http: / / example.com / upload). The output is a status code of 200 if the request is successful.

[0935] Step 4:

[0936] Server: Parses the data received at the API endpoint and generates a log ID. As input, it receives the received JSON data and parses the user ID, prompt, and result. Based on this, it generates a new log ID "67890". As output, it obtains the data {'logID': '67890', 'userID': '12345', 'prompt': 'Create a poem with AI', 'result': 'A quiet night, the stars shine', 'timestamp': '2023-10-05T12:34:56Z'} containing the generated log ID.

[0937] Step 5:

[0938] Server: Saves the data including the generated log ID to the database. As input, it receives the data generated in the previous step and saves it to the database. The output is a notification that saving to the database is complete.

[0939] Step 6:

[0940] User: Another user views the log list in a web browser and navigates to the individual log details page. As input, the user enters the URL to access the log list page in the web browser. The output is a display of the viewable log list.

[0941] Step 7:

[0942] User: Clicks the "Like" button for a log they are interested in. The input is clicking the "Like" button after viewing a specific log detail page. The output is the occurrence of a "Like" event.

[0943] Step 8:

[0944] Terminal: Detects the click event of the reaction button and sends the log ID and reaction type to the server. Receives the click event of the "Like" button as input and converts the log ID "67890" and reaction type "Like" into JSON format. The output is a request to send to the API endpoint based on this data.

[0945] Step 9:

[0946] Server: Processes the received reaction data, saves it in the database, and updates the number of reactions. As input, it receives JSON-formatted reaction data and analyzes it for the user ID, log ID, and reaction type. Based on this, it saves it in the database and updates the number of reactions. The output is a notification that the database has been updated.

[0947] Step 10:

[0948] User: Clicks the SNS share button to share the log on a social networking service (SNS). The input is clicking the share button. The output is that a URL for posting to the SNS is generated and the SNS posting screen is opened in a new window.

[0949] (Application example 1)

[0950] 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."

[0951] Modern advertising strategies require measuring advertising effectiveness in real time and optimizing advertising content based on user feedback. However, conventional systems lacked mechanisms for efficiently collecting and analyzing the quality of ad copy generated by advertisers and user reactions, making it difficult to develop effective advertising strategies. Furthermore, the lack of an integrated function for sharing ad logs with social networking services made it difficult to expand the user base.

[0952] 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.

[0953] In this invention, the server includes: a means for inputting a log generated by a user using an information generating device; a means for transmitting the log to the server; a means for the server to receive the log and store it in a database; a means for other users to provide reactions to the log; a means for the server to receive the reactions and store them in a database; a means for the user to share the log on a social networking service; a means for an advertiser to generate advertising copy using a generative AI model and upload it as a log; a means for users to provide reactions to the displayed advertising log; and a means for analyzing the reaction data and measuring the effectiveness of the advertisement. This enables the quality and effectiveness of the advertising copy generated by the advertiser to be evaluated and optimized in real time. In addition, a social networking service sharing function is integrated to expand the user base, allowing the system to reach more users.

[0954] A "user" refers to an entity that uses an information generating device to generate a log and provides the log to the system.

[0955] "Information generating device" refers to a device through which a user inputs a prompt and generates a result in response to the prompt.

[0956] "Log" refers to data including prompts generated by a user using an information generating device and the results thereof.

[0957] "Server" refers to a computer system that receives logs and reaction data sent by users and stores and manages them in a database.

[0958] "Reaction" refers to the rating or feedback that other users give to a particular log.

[0959] A "database" refers to a system that systematically stores logs and reaction data and manages them in a manner that allows for search and analysis.

[0960] "Social Networking Service" means an online platform that enables users to share information and communicate with other users.

[0961] "Advertiser" refers to the entity that uses a generative AI model to create advertising copy and uploads that advertising copy to the system as a log.

[0962] "Generative AI model" refers to an artificial intelligence model that automatically generates ad copy and other information based on prompts entered by a user.

[0963] "Ad copy" refers to the advertising content generated by a generative AI model and served to users.

[0964] "Advertising Log" refers to a log containing advertising copy generated by an advertiser using a generative AI model and uploaded to the system.

[0965] "Measuring the effectiveness of advertising" refers to analyzing user reaction data and evaluating how much evaluation and interest a particular ad copy has generated.

[0966] This invention is a system that allows users to efficiently share logs generated using an information generation device and optimize the effectiveness of advertising through reactions. This system operates in cooperation with each element of the user, terminal, and server.

[0967] Generating and uploading logs

[0968] User: First, the advertiser user generates ad copy using the generative AI model. For example, they input a prompt such as "Generate an ad for a new drinking water product" and get the generated result. Then, they input this ad copy into the input form on their device and click the upload button.

[0969] Device: The entered ad copy and the corresponding results are compiled in JSON format and sent to the server, along with identifying information such as the user ID and campaign ID.

[0970] Server: Parse the received data, generate a log_id, and save the log_id, user ID, campaign ID, ad copy, results, timestamp, etc. in the database.

[0971] Adding a reaction

[0972] Users: Other users can view the uploaded ad logs and click reaction buttons such as "Like" or "Interested" on the ad logs they find useful.

[0973] Device: When the reaction button is clicked, the ad log ID and reaction type (e.g., "Like") are sent to the server.

[0974] Server: Receives reaction data and stores the user ID, reaction type, ad log ID, timestamp, etc. in a database. Also manages the increase / decrease in the number of reactions.

[0975] Sharing to social media

[0976] User: Clicks a button to share the ad log they found useful on social media.

[0977] Device: When you click the share button, the contents of the ad log will be embedded in text format into a URL for sharing on social media, and the social media posting screen will open in a new window.

[0978] Specific examples

[0979] 1. Generate and upload your ad:

[0980] Prompt: "Generate a new drinking water ad"

[0981] Result: "Try Sparkling Water, a refreshing new experience."

[0982] The advertiser enters this advertisement text and clicks the upload button.

[0983] 2. Adding a reaction:

[0984] Another user views this ad log and clicks the "Like" button.

[0985] The number of "likes" increases and reaction information is recorded in the database.

[0986] 3. Sharing to social media:

[0987] The user clicks a button to share this ad log on Twitter.

[0988] An advertising caption such as "Try a new refreshing sparkling water experience" is automatically embedded in the Twitter post screen, and a new window opens.

[0989] This system allows advertisers to measure the effectiveness of their ads in real time, providing them with a powerful tool for developing optimal advertising strategies. Furthermore, the social media sharing feature helps expand the user base and reach more users, which is expected to maximize the effectiveness of advertising.

[0990] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0991] Step 1:

[0992] The user generates ad copy using the generative AI model, and then inputs the prompts and results into the device's input form. At this time, the user enters the ad copy and related information (user ID, campaign ID, etc.) and clicks the upload button.

[0993] Input: prompt text, ad copy, user ID, campaign ID

[0994] Output: JSON format data

[0995] Step 2:

[0996] The device compiles the input data into JSON format and sends it to the server. Specifically, JSON data is created that includes the user ID, campaign ID, ad copy, etc.

[0997] Input: Data entered by the user (prompt text, ad copy, user ID, campaign ID)

[0998] Output: JSON data (prompt text, ad copy, user ID, campaign ID)

[0999] Step 3:

[1000] The server parses the received JSON data and generates a log_id. The generated log_id, user ID, campaign ID, ad copy, and timestamp are saved in the database. The database stores this information in an organized manner for future searches and analysis.

[1001] Input: JSON data (prompt text, ad copy, user ID, campaign ID)

[1002] Output: Save to database (log_id, user ID, campaign ID, ad copy, timestamp)

[1003] Step 4:

[1004] Other users can view the ad logs uploaded through their devices and click reaction buttons such as "Like" or "Interested" on the ad logs that interest them.

[1005] Input: Ad logs viewed by the user

[1006] Output: Reaction data (log ID, reaction type)

[1007] Step 5:

[1008] The device receives the user's reaction and sends the reaction data (log ID, user ID, reaction type) to the server.

[1009] Input: User's reaction (log ID, reaction type)

[1010] Output: JSON data (log ID, user ID, reaction type)

[1011] Step 6:

[1012] The server analyzes the reaction data it receives and stores it in a database. Specifically, it registers the log ID, user ID, reaction type, timestamp, etc. in the database and manages the increase or decrease in the number of reactions.

[1013] Input: JSON data (log ID, user ID, reaction type)

[1014] Output: Save to database (log ID, user ID, reaction type, timestamp)

[1015] Step 7:

[1016] If a user finds an ad log useful, they click a button to share it on social media. This action embeds the ad copy into the URL for sharing on social media.

[1017] Input: Ad logs shared by users

[1018] Output: URL for SNS sharing

[1019] Step 8:

[1020] The device opens the generated SNS sharing URL in a new window and displays the SNS posting screen. The user can then confirm the content to be shared and complete the post.

[1021] Input: URL for SNS sharing

[1022] Output: SNS post screen

[1023] This completes the entire process, from generating ad logs to adding reactions and sharing on social media, creating a system that can measure advertising effectiveness based on user feedback and optimize advertising strategies.

[1024] 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.

[1025] This invention is a system that allows users to efficiently share logs generated using information generation devices and improve the knowledge of the entire community through reactions, and also combines an emotion engine that recognizes user emotions. In this system, each element of the user, terminal, and server works in cooperation with the emotion engine.

[1026] Uploading logs

[1027] User: First, the user uses the information generation device to input a prompt and obtain the result. For example, the user inputs "Please write a poem using AI" as the prompt and receives text such as "A quiet night, the stars shine brightly" as the result. Next, the user enters the generated prompt and result into the input form on the device and clicks the "Upload" button. This operation sends the prompt and result to the server in JSON format.

[1028] Terminal: Generates JSON data containing the input prompts and results and sends it to the server. The emotion engine also recognizes the user's emotions and sends that information to the server.

[1029] Server: The server parses the received JSON data and emotion data, generates a new log entry based on it, generates a log ID, and saves data such as the user ID, prompt, result, emotion information, and timestamp in the database.

[1030] Adding a reaction

[1031] Users: Other users can view the uploaded logs and react to the logs they find useful, for example, by selecting a specific log from the log list and clicking the "Like" button.

[1032] Terminal: When the reaction button is clicked, the log ID and reaction type, as well as the user's emotion information recognized by the emotion engine, are sent to the server.

[1033] Server: Receives reaction data and emotion information, and stores data such as user ID, reaction type, log ID, emotion information, and timestamp in a database. Also, adjusts the display order of logs based on the number of reactions and emotion information.

[1034] Sharing to social media

[1035] User: If you want to share a log you like on a social networking service (SNS), click the share button. For example, you can click the "Share" button to post the log on Twitter.

[1036] On the device: When the share button is clicked, a new window will open with the log contents (prompt and result) and related emotional information embedded in the URL for sharing on social media.

[1037] Specific examples

[1038] 1. Generate and upload logs:

[1039] Prompt: "Make a poem with AI."

[1040] Result: "A quiet night, the stars shine brightly."

[1041] The user fills in this prompt and the results and clicks the upload button.

[1042] The emotion engine recognizes the user's emotion as "satisfied" and also sends this information to the server.

[1043] The server stores the logs and emotional information in a database.

[1044] 2. Reaction to the log:

[1045] Another user views this log and clicks the "Like" button.

[1046] The emotion engine recognizes the user's emotion as "happy" and sends it along with the reaction data.

[1047] The server records reaction data and emotional information and reflects this in the display order of the logs.

[1048] 3. Sharing to social media:

[1049] The user clicks a button to share this log on Twitter.

[1050] The log content and the emotional information of "satisfaction" are embedded in a URL for sharing on social media, and a new window is opened and posted to the social media site.

[1051] The system allows users to efficiently share their AI-generated experiences and emotional data, facilitating greater knowledge and emotion-based interactions across the community.

[1052] The processing flow will be explained below.

[1053] Step 1:

[1054] User: Inputs a prompt into the information generator and generates a result for that prompt. For example, the user inputs the prompt "Please write a poem using AI" and receives the generated result "A quiet night, the stars shine brightly."

[1055] Step 2:

[1056] User: Enters the generated prompt and results into the input form on the device, and the emotion engine recognizes the emotion. The emotion engine obtains emotional information (e.g., satisfaction) from the user's facial expressions and voice.

[1057] Step 3:

[1058] Terminal: The input prompt, result, and emotion information are sent to the server in JSON format. The data is sent to the server using an HTTP POST request.

[1059] Step 4:

[1060] Server: Parses the received JSON data and generates a new log entry. Creates a log ID and saves information such as the user ID, prompt, result, emotion information, and timestamp in the database.

[1061] Step 5:

[1062] Users: View logs uploaded by other users. Logs are displayed in a list format, with a link to each log's details page.

[1063] Step 6:

[1064] User: Add a reaction to a specific log. For example, when clicking the "Like" button, the emotion engine will recognize the emotion again and process that information along with the reaction.

[1065] Step 7:

[1066] On the device: When a reaction button is clicked, data including the log ID, reaction type, and emotion information is sent to the server in JSON format using an HTTP POST request.

[1067] Step 8:

[1068] Server: Analyzes the received reaction data and stores the reaction and emotional information in a database. It also adjusts the display order based on the number of reactions and emotional information in the log.

[1069] Step 9:

[1070] User: If you want to share a specific log on a social networking service (SNS), click the SNS share button.

[1071] Step 10:

[1072] On the device, when the social media share button is clicked, a new window is opened with the log content (prompt and result) and related emotional information embedded in the social media share URL. The URL contains encoded text and displays the social media share screen.

[1073] The above is the specific processing flow of the system that combines the emotion engine of this invention. This system efficiently shares users' experiences with using generated AI and their emotion data, improving knowledge across the entire community and promoting emotion-based interactions.

[1074] Example 2

[1075] 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."

[1076] In conventional information sharing systems, when users share data or logs they generate with other users, they do not take into account the user's emotional information, and reactions to the shared data are based solely on numerical values, which means that they are unable to fully realize interactions based on user emotions or improve knowledge across the entire community.Furthermore, sharing to external platforms such as social media can sometimes be difficult.

[1077] 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.

[1078] In this invention, the server includes a means for transmitting data and emotional information generated by users to the server, a means for the server to receive, analyze, and store the data and emotional information in a database, and a means for adjusting the display order of data based on the number of reactions and the emotional information, thereby promoting interaction based on user emotions and improving knowledge throughout the community.

[1079] A "user" is a person or entity that uses the system, generates data using an information generating device, and shares or reacts to this data.

[1080] An "information generating device" is a device or software that generates information or data using a generative AI model or the like based on prompts entered by a user.

[1081] "Data" means text or other information generated by a user using an information generating device, including prompts and their results.

[1082] "Emotion information" is information that is recognized using an emotion engine to recognize the user's emotional state (e.g., "satisfied," "happy," etc.) and sent to the server as part of the data.

[1083] A "server" is a computer system on a network that receives, analyzes, and stores data and emotional information sent by users and provides this data to other users.

[1084] "JSON format" is an abbreviation for JavaScript Object Notation, a lightweight data exchange format for storing and communicating structured data.

[1085] "Reactions" refer to actions other users take on shared data, and are expressed in the form of "likes" or comments.

[1086] A "database" is a collection of data built on a server, and is a system that stores and manages user-generated data, emotional information, and reactions.

[1087] "Display order" refers to the order in which the server displays data to other users, and is adjusted based on the number of reactions and emotional information.

[1088] "Social Networking Service" means an online service that enables users to share data with external social networking platforms.

[1089] This invention is a system that allows users to efficiently share data generated using information generation devices and improve the knowledge of the entire community through reactions, and also combines it with an emotion engine that recognizes the emotions of users. In this system, each element of the user, terminal, and server works in cooperation with the emotion engine.

[1090] Uploading logs

[1091] user

[1092] First, the user inputs a specific prompt sentence (e.g., "Please write a poem using AI") using the information generator. This information generator uses a generative AI model to generate data based on the input prompt. After receiving the generated result (e.g., "A quiet night, the stars shine"), the user enters the prompt and the result into the input form on their device and clicks the "Upload" button. This operation sends the prompt and the result to the server as JSON-formatted data. The emotion engine also recognizes the user's emotion (e.g., "Satisfied"), and this information is also sent.

[1093] Terminal

[1094] The device converts the input prompts and results into JSON format data and sends it to the server. In addition, an emotion engine (e.g., emotion recognition software) recognizes the user's emotions and sends that emotion information to the server. Examples of hardware used include PCs and smartphones, and software such as Android or iOS applications.

[1095] server

[1096] The server analyzes the received JSON data and emotion information and generates a new log entry. It stores data such as the log ID, user ID, prompt, result, emotion information, and timestamp in a database. The server uses Python and a database management system (e.g., MySQL) to perform this processing.

[1097] Adding a reaction

[1098] user

[1099] Other users can view the log list provided by the server through a web browser or app and react to logs they like, for example, by selecting a specific log from the log list and clicking the "Like" button.

[1100] Terminal

[1101] When the reaction button is clicked, the device generates data including the target log ID and reaction type (e.g., "Like"), and recognizes the user's emotion (e.g., "Happy") using the emotion engine.The device then sends the reaction information and emotion information to the server.

[1102] server

[1103] The server analyzes the received reaction data and emotional information and adds a new entry to the database. Data such as user ID, reaction type, log ID, emotional information, and timestamp are saved. Furthermore, the server adjusts the display order of the data based on the number of reactions and emotional information, and displays the logs in the appropriate order for the user.

[1104] Sharing to social media

[1105] user

[1106] If a user wants to share a particular log on a social networking site, they can click the "Share" button. For example, they can click the "Share" button to post the log on Twitter.

[1107] Terminal

[1108] When the share button is clicked, the device opens a new window with the log contents (prompt and result) and emotional information embedded in the URL for sharing on social media, allowing the user to post directly to social media.

[1109] Specific examples

[1110] 1. Prompt: "Create a poem using AI."

[1111] 2. Result: "The stars shine brightly on a quiet night."

[1112] The user enters these prompts and results and clicks the upload button. The emotion engine recognizes the user's emotion as "satisfied," and this information is sent to the server and stored in the database. When another user views this log and clicks the "Like" button, the reaction data and the emotion information of "happy" are sent to the server and recorded in the database.

[1113] This provides a system that efficiently shares users' generated AI usage experiences and emotional data, improving knowledge across the community and promoting emotion-based interactions.

[1114] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1115] Step 1:

[1116] user

[1117] A user inputs a prompt (e.g., "Please write a poem using AI") into the information generator and receives the generated result (e.g., "The stars shine brightly on a quiet night"). The input is the prompt, and the output is the generated text. This data is used in subsequent processing.

[1118] Step 2:

[1119] user

[1120] Enter the generated prompt sentence and result into the input form on the terminal and click the "Upload" button. The input is the prompt sentence and its result, and the click operation triggers the next process.

[1121] Step 3:

[1122] Terminal

[1123] The terminal receives user input and converts it into JSON format data. The input is the prompt and its result, and the output is JSON format data. This data includes the prompt, the result, and a timestamp.

[1124] Step 4:

[1125] Terminal

[1126] The emotion engine recognizes the user's emotional information. The input is the user's emotional state, and the output is the emotional information (e.g., "Satisfied"). This information is also integrated into the JSON data.

[1127] Step 5:

[1128] Terminal

[1129] Send JSON data and emotion information to the server. The input is the generated JSON data, and the output is the data sent to the server.

[1130] Step 6:

[1131] server

[1132] The server receives and parses the JSON data. The input is the JSON data sent from the terminal, and the output is the parsed prompt, result, and emotion information.

[1133] Step 7:

[1134] server

[1135] Generates a new log entry and saves it to the database. The input is the parsed data, and the output is a new log entry inserted into the database. This entry contains the log ID, user ID, prompt, result, emotion information, and timestamp.

[1136] Step 8:

[1137] user

[1138] Other users view the log list from the database in a web browser or app. The input is a request to display the log list, and the output is the log data returned from the server.

[1139] Step 9:

[1140] user

[1141] Click the "Like" button for the log you like. The input is the log ID to react to, and the output is the trigger for the reaction operation.

[1142] Step 10:

[1143] Terminal

[1144] It generates reaction data (log ID, reaction type) and user emotion information. The input is the user's reaction operation and emotional state, and the output is reaction data and emotion information.

[1145] Step 11:

[1146] Terminal

[1147] The generated reaction data and emotion information are sent to the server. The input is the reaction data and emotion information, and the output is the data sent to the server.

[1148] Step 12:

[1149] server

[1150] The server receives the reaction data and emotion information, analyzes them, and stores them in a database. The input is the reaction data and emotion information from the device, and the output is the recorded entry in the database.

[1151] Step 13:

[1152] server

[1153] The display order of data is adjusted based on the number of reactions and emotional information. The input is the number of reactions and emotional information in the database, and the output is the log data to be displayed with priority.

[1154] Step 14:

[1155] user

[1156] To share a log you like on a social networking site, click the "Share" button. The input is the log ID to be shared, and the output is the trigger for the sharing operation.

[1157] Step 15:

[1158] Terminal

[1159] It detects when the share button is clicked and opens a new window with the log content and emotion information embedded in the URL for sharing on social media. The input is the log content and emotion information, and the output is a window for posting to social media.

[1160] This series of processing steps efficiently shares user-generated data and emotional information, and accumulates reactions from other users, facilitating improved knowledge and emotion-based interactions across the community.

[1161] (Application example 2)

[1162] 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."

[1163] Conventional information sharing systems provide functions for sharing logs generated by users and receiving reactions from other users, but because they do not take into account users' emotional information, it is difficult to properly evaluate the usefulness and relevance of logs across the community. In addition, they lack functions for prioritizing display of logs based on emotions and sharing to social media, so there is a need to improve user engagement.

[1164] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing the user's emotion and transmitting the emotion information to the server together with the log, means for analyzing the emotion information and storing it in association with the log, and means for adjusting the display order of logs that have gathered a certain number of reactions or more based on the reactions and emotion information. This makes it possible to share and prioritize the display of logs that take into account the user's emotion information.

[1165] An "information generating device" is a machine or software that receives a prompt from a user and generates information based on that prompt.

[1166] A "log" is a collection of prompts generated by a user using an information generating device, the results of those prompts, and related data.

[1167] A "server" is a computer system that receives data sent by users and stores it in a database.

[1168] An "emotion engine" is a machine learning model or algorithm for recognizing emotions from user input and analyzing that information.

[1169] A "prompt" is a request or instruction sentence that a user inputs to an information generating device.

[1170] A "reaction" is an evaluation or response that other users make to a log, and includes, for example, "likes" and comments.

[1171] A "database" is a data management system that stores structured data within a server and allows for easy search and retrieval.

[1172] A "social networking service" is a platform where different users can share information and communicate with each other.

[1173] "Emotion information" is data that indicates the user's emotional state as recognized by the emotion engine.

[1174] A system for implementing this invention allows users to efficiently share logs generated using information generation devices and combines emotion engines to improve the knowledge of the entire community. This system includes the following specific configuration and processing.

[1175] The user first inputs a prompt to the information generator. For example, the prompt is "Please write a poem using AI." Based on this prompt, the information generator generates a poem and returns a result such as "On a quiet night, the stars shine brightly."

[1176] The user then enters the generated log (prompt and result) into an input form on a device such as a smartphone and clicks the "Upload" button. This operation causes the device to send JSON data containing the prompt, result, and the user's emotional information recognized by the emotion engine to the server.

[1177] The server parses the received JSON data and saves data such as the user ID, prompt, result, emotion information, and timestamp as a new log entry in the database. For example, if the emotion information is "Satisfied," that information is also associated with the log and saved.

[1178] Other users can view the logs and react to the logs they find useful, for example by clicking the "Like" button. The device sends the log ID, reaction type, and the user's emotion information recognized by the emotion engine to the server.

[1179] The server receives the reaction data and emotional information, stores it in a database, and adjusts the display order of logs based on the number of reactions and emotional information. For example, logs that have received a certain number of "likes" will be displayed with priority over other logs.

[1180] Furthermore, if a user wants to share a log they like on a social networking service (SNS), they can click the "Share" button. This action causes the device to open a new window and post the log content and emotional information to the SNS sharing URL, embedding it in the URL.

[1181] A concrete example would be the following:

[1182] 1. User enters a prompt. Example: "Please write a poem using AI."

[1183] 2. As a result: "Quiet Night, Stars Shine" is obtained and uploaded

[1184] 3. The emotion engine recognizes the user's emotion as "satisfied"

[1185] 4. The server stores the logs and emotional information in a database

[1186] 5. Another user clicks "like" on the log and recognizes the emotion as "happy."

[1187] 6. The display order of logs will be adjusted and displayed with priority.

[1188] This system configuration enables sharing of logs and adjustment of display order taking into account users' emotional information, thereby improving engagement and knowledge across the entire community.

[1189] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1190] Step 1:

[1191] A user opens a smartphone application and inputs a prompt into the information generator, for example, "Please write a poem using AI." This input is sent to the generative AI model, and the resulting poem is "A quiet night, the stars shine brightly."

[1192] Step 2:

[1193] The user checks the generated log (prompt sentences and results), and the emotion engine recognizes the user's emotion from their facial expressions and voice. For example, the emotion engine recognizes the user's emotion as "satisfied."

[1194] Step 3:

[1195] The user clicks the "Upload" button to send the log and the recognized emotion information to the server. The device then packages the prompt, result, user ID, and emotion information into JSON format data and sends it to the server.

[1196] Step 4:

[1197] The server parses the received JSON data, which contains the user ID, prompt, result, emotion, and timestamp. The server parses this data and generates a new log entry.

[1198] Step 5:

[1199] The server stores the generated log entries in a database, which includes the user ID, prompt, result, emotion information, and a timestamp, allowing the logs to be searched and viewed later.

[1200] Step 6:

[1201] Other users can view the log and react to it by clicking "like" or commenting. For example, a user can click the "like" button. This action sends the reaction information (log ID, reaction type, user ID, and emotion information) from the device to the server.

[1202] Step 7:

[1203] The server analyzes the received reaction data and emotional information and stores it in a database. The server updates the engagement index in the log based on the type of reaction and the user's emotional information.

[1204] Step 8:

[1205] Based on the reaction and emotion information, the server adjusts the display order of the logs. For example, if a particular log receives a certain number of "likes," it will be displayed with priority over other logs.

[1206] Step 9:

[1207] To share the log on a social networking service, the user clicks the "Share" button. This action causes the device to embed the log content (prompt and result) and emotional information into a URL for sharing on the social networking service, and opens a new window to prepare for posting.

[1208] Step 10:

[1209] Once sharing to the SNS is complete, the log is posted on the SNS. This post contains the log content and emotional information, such as "satisfied," and can be viewed by other users on the SNS.

[1210] 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.

[1211] 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.

[1212] 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.

[1213] [Fourth embodiment]

[1214] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1215] 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.

[1216] 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).

[1217] 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.

[1218] 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.

[1219] 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).

[1220] 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.

[1221] 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.

[1222] 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.

[1223] 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.

[1224] 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.

[1225] 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.

[1226] 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."

[1227] The present invention provides a system that allows users to efficiently share logs generated using information generation devices and improve the knowledge of the entire community through reactions. This system operates in cooperation with the elements of users, terminals, and servers.

[1228] Uploading logs

[1229] User: First, the user uses the information generator to generate a prompt and the corresponding result. Then, the user enters the generated prompt and result into an input form on the terminal. This input form has fields where the prompt and result can be entered separately. The user clicks the "Upload" button.

[1230] Terminal: The input prompts and results are compiled in JSON format and sent to the server, along with identifying information such as the user ID.

[1231] Server: Parses the received data, generates a log ID, and saves the log ID, user ID, prompt, result, timestamp, etc. in the database.

[1232] Adding a reaction

[1233] User: Next, other users can view the uploaded logs. A user interface is provided that displays a list of logs and a detailed page for each log. Useful logs have reaction buttons such as "Like" and "Helpful."

[1234] On the device: When a reaction button is clicked, the log ID and reaction type (e.g., "Like") are sent to the server.

[1235] Server: Receives reaction data and stores the user ID, reaction type, log ID, timestamp, etc. in the database. Also, increases or decreases the number of reactions as needed.

[1236] Sharing to social media

[1237] User: If the user finds the log useful, they can click the SNS share button to post the generated log and its results to SNS.

[1238] Device: When you click the share button, the log contents will be embedded in text format into a URL for sharing on social media, and the social media posting screen will open in a new window.

[1239] Specific examples

[1240] 1. Generate and upload logs:

[1241] Prompt: "Make a poem with AI."

[1242] Result: "A quiet night, the stars shine brightly."

[1243] The user fills in the prompts and results and clicks the upload button.

[1244] 2. Reaction to the log:

[1245] Another user views this log and clicks the "Like" button.

[1246] The number of "likes" increases and reaction information is recorded in the database.

[1247] 3. Sharing to social media:

[1248] The user clicks a button to share this log on Twitter.

[1249] A URL for sharing on social media will be generated, a new window will open, and the log content will be posted to the social media platform.

[1250] This allows other users to access the logs and easily obtain useful information. Furthermore, information can be spread through social media, making the convenience of generative AI known to many people.

[1251] The processing flow will be explained below.

[1252] Step 1:

[1253] User: Uses the information generator to input a prompt and receive a result. For example, the user inputs "Please write a poem using AI" as a prompt and receives the text "A quiet night, the stars shine brightly" as a result.

[1254] Step 2:

[1255] User: Enters the generated prompt and results into an input form on the device. For example, the input form has a field for the prompt and a field for the result, and the user enters text into each field.

[1256] Step 3:

[1257] User: Once the input is complete, click the "Upload" button on the device. This action sends the input data to the server.

[1258] Step 4:

[1259] Terminal: The input prompt and result are converted into JSON format and sent to the server along with necessary identification information such as the user ID. Specifically, the data is sent using an HTTP POST request.

[1260] Step 5:

[1261] Server: Parses the received JSON data and generates a new log entry based on it. It generates a log ID and saves data such as the user ID, prompt, result, and timestamp in the database.

[1262] Step 6:

[1263] Users: View logs uploaded by other users and give reactions to logs they like. For example, select a specific log from the log list, go to the details page, and click the "Like" button.

[1264] Step 7:

[1265] Terminal: When the reaction button is clicked, data including the log ID and reaction type is sent to the server. As with the server, an HTTP POST request is used.

[1266] Step 8:

[1267] Server: Analyzes the received reaction data and records it in a database based on the user ID, reaction type, log ID, timestamp, etc. Also, if it is necessary to increase or decrease the number of reactions, it handles that process.

[1268] Step 9:

[1269] User: If you want to share a log you like on a social networking service (SNS), click the share button. For example, you can click the "Share" button to post the log on Twitter.

[1270] Step 10:

[1271] On the device: When the share button is clicked, a new window is opened by embedding the text containing the log contents into the URL for sharing on social media. Specifically, the text containing the log prompt and result is encoded, a URL containing that text is generated, and the URL is opened in a new window.

[1272] The above are the specific processing steps when a user shares a log generated using AI, receives reactions, or shares it on social media.

[1273] Example 1

[1274] 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."

[1275] Conventional information sharing systems have faced challenges in efficiently sharing user-generated logs and promoting knowledge sharing within the community. Furthermore, they lacked the functionality to allow other users to add reactions to logs, limiting the collection and analysis of the resulting data. Furthermore, there was a lack of an easy way to share generated logs on social networking services. A system that could solve these challenges, efficiently share user-generated information, and improve the knowledge of the entire community was needed.

[1276] 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.

[1277] In this invention, the server includes means for converting the prompt and results generated by the user using the information generation device into JSON format and transmitting them to the server together with user identification information, means for receiving the prompt and results, generating a log ID, and storing it in a database, means for other users to give reactions to the prompt and results, means for receiving the reactions, storing them in a database, and updating the number of reactions, and means for users to share the prompt and results on a social networking service, thereby enabling users to efficiently share the information they generate and improve the knowledge of the entire community through reactions.

[1278] A "user" is an individual or entity that utilizes the system to input prompts into an information generator and receive the results.

[1279] An "information generating device" is a device that generates results in response to prompts entered by a user, such as a generative AI model.

[1280] A "prompt" refers to a question or instruction that a user inputs into an information generating device.

[1281] "Results" refers to the output generated by an information generating device based on a prompt.

[1282] "Input Form" refers to the interface on a web page through which a user enters prompts and results.

[1283] The "JSON format" is a lightweight data exchange format that represents data as key-value pairs.

[1284] "User Identification Information" means an ID or other identifying data that uniquely identifies a user.

[1285] A "server" is a computer system for receiving and processing data sent by users and terminals.

[1286] A "Log ID" is a unique server-generated identifier used to identify a particular set of prompts and results.

[1287] A "database" is a system for efficiently storing, managing, and retrieving data in digital form.

[1288] "Reactions" refer to feedback other users give to a particular prompt and result, expressed in the form of "likes" or "helpful."

[1289] "Social networking service" refers to an online platform that users use to share information, such as a social networking site.

[1290] This invention is a system that allows users to efficiently share prompts generated using generative AI models and the results, thereby improving the knowledge of the entire community. This system works in cooperation with the user, terminal, and server elements.

[1291] 1. User Actions

[1292] First, the user uses a generative AI model to generate a prompt and its results. An example of a generative AI model is ChatGPT. The user then enters the generated prompt and results into an input form on their device. This input form provides fields for entering the prompt and results separately, and the user clicks the "Upload" button after entering the information.

[1293] (Example)

[1294] Prompt: "Make a poem with AI."

[1295] Result: "A quiet night, the stars shine brightly."

[1296] 2. Device Operation

[1297] The terminal converts the prompts and results entered in the input form into JSON format. It also includes the user's identity information in the JSON data. The converted JSON data is sent to a specific API endpoint. For example, the terminal generates the following data:

[1298] json

[1299] {

[1300] "userID": "12345",

[1301] "prompt": "Create a poem with AI",

[1302] "result": "A quiet night, the stars shine brightly"

[1303] }

[1304] This data is sent as a POST request to the URL 'http: / / example.com / upload'.

[1305] 3. Server Processing

[1306] The server analyzes the received JSON data and generates a new log ID. The server saves the data (user ID, prompt, result, timestamp) including the generated log ID in a database. The database is operated using, for example, an RDBMS (Relational Database Management System).

[1307] (example)

[1308] Store the received data as follows:

[1309] Log ID: "67890"

[1310] User ID: "12345"

[1311] Prompt: "Make a poem with AI."

[1312] Result: "A quiet night, the stars shine brightly."

[1313] Timestamp: "2023-10-05T12:34:56Z"

[1314] 4. Viewing logs and adding reactions

[1315] Next, other users can browse the list of uploaded logs using a user interface provided in a web browser, select a log of interest, go to the details page, and click reaction buttons such as "Like" or "Helpful."

[1316] 5. Handling Reactions

[1317] When the reaction button is clicked, the device detects the click event and sends data including the log ID and reaction type (e.g., "Like") to the server. The server processes the received reaction data, saves it in the database, and updates the reaction count. For example, the data is saved in the following format:

[1318] User ID: "54321"

[1319] Log ID: "67890"

[1320] Reaction type: Like

[1321] Timestamp: "2023-10-05T12:35:00Z"

[1322] 6. Sharing on social media

[1323] Finally, if a user wants to share a specific log on a social networking service (SNS), they can click the SNS share button. The device will generate data containing the log content and a sharing URL, and open the SNS posting screen in a new window. For example, the following URL may be generated:

[1324] 'https: / / twitter.com / intent / tweet?text=Check out this log!%20prompt:%20Make a poem with AI%20result:%20A quiet night, the stars shine brightly'

[1325] This system allows users to efficiently share the generated information and improve the knowledge of the entire community through reactions. Information can also be easily spread through social media, widely communicating the convenience of generative AI.

[1326] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1327] Step 1:

[1328] User: Inputs a prompt to the generative AI model. As input, the user provides the generative AI model with the prompt "Please write a poem using AI." As a result, the generative AI model generates the output "A quiet night, the stars shine brightly." The user enters this result into an input form on their device.

[1329] Step 2:

[1330] Terminal: The prompt and result entered in the input form are converted into JSON format. As input, the prompt entered by the user, "Please write a poem using AI," and the result, "A quiet night, the stars shine brightly," are received. These data, along with the user ID, are converted into JSON format like {'userID': '12345', 'prompt': 'Please write a poem using AI', 'result': 'A quiet night, the stars shine brightly'}.

[1331] Step 3:

[1332] Terminal: Sends data converted to JSON format to an API endpoint. As input, it takes JSON formatted data and creates an HTTP POST request. It sends this to a specific URL (e.g. http: / / example.com / upload). The output is a status code of 200 if the request is successful.

[1333] Step 4:

[1334] Server: Parses the data received at the API endpoint and generates a log ID. As input, it receives the received JSON data and parses the user ID, prompt, and result. Based on this, it generates a new log ID "67890". As output, it obtains the data {'logID': '67890', 'userID': '12345', 'prompt': 'Create a poem with AI', 'result': 'A quiet night, the stars shine', 'timestamp': '2023-10-05T12:34:56Z'} containing the generated log ID.

[1335] Step 5:

[1336] Server: Saves the data including the generated log ID to the database. As input, it receives the data generated in the previous step and saves it to the database. The output is a notification that saving to the database is complete.

[1337] Step 6:

[1338] User: Another user views the log list in a web browser and navigates to the individual log details page. As input, the user enters the URL to access the log list page in the web browser. The output is a display of the viewable log list.

[1339] Step 7:

[1340] User: Clicks the "Like" button for a log they are interested in. The input is clicking the "Like" button after viewing a specific log detail page. The output is the occurrence of a "Like" event.

[1341] Step 8:

[1342] Terminal: Detects the click event of the reaction button and sends the log ID and reaction type to the server. Receives the click event of the "Like" button as input and converts the log ID "67890" and reaction type "Like" into JSON format. The output is a request to send to the API endpoint based on this data.

[1343] Step 9:

[1344] Server: Processes the received reaction data, saves it in the database, and updates the number of reactions. As input, it receives JSON-formatted reaction data and analyzes it for the user ID, log ID, and reaction type. Based on this, it saves it in the database and updates the number of reactions. The output is a notification that the database has been updated.

[1345] Step 10:

[1346] User: Clicks the SNS share button to share the log on a social networking service (SNS). The input is clicking the share button. The output is that a URL for posting to the SNS is generated and the SNS posting screen is opened in a new window.

[1347] (Application example 1)

[1348] 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."

[1349] Modern advertising strategies require measuring advertising effectiveness in real time and optimizing advertising content based on user feedback. However, conventional systems lacked mechanisms for efficiently collecting and analyzing the quality of ad copy generated by advertisers and user reactions, making it difficult to develop effective advertising strategies. Furthermore, the lack of an integrated function for sharing ad logs with social networking services made it difficult to expand the user base.

[1350] 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.

[1351] In this invention, the server includes: a means for inputting a log generated by a user using an information generating device; a means for transmitting the log to the server; a means for the server to receive the log and store it in a database; a means for other users to provide reactions to the log; a means for the server to receive the reactions and store them in a database; a means for the user to share the log on a social networking service; a means for an advertiser to generate advertising copy using a generative AI model and upload it as a log; a means for users to provide reactions to the displayed advertising log; and a means for analyzing the reaction data and measuring the effectiveness of the advertisement. This enables the quality and effectiveness of the advertising copy generated by the advertiser to be evaluated and optimized in real time. In addition, a social networking service sharing function is integrated to expand the user base, allowing the system to reach more users.

[1352] A "user" refers to an entity that uses an information generating device to generate a log and provides the log to the system.

[1353] "Information generating device" refers to a device through which a user inputs a prompt and generates a result in response to the prompt.

[1354] "Log" refers to data including prompts generated by a user using an information generating device and the results thereof.

[1355] "Server" refers to a computer system that receives logs and reaction data sent by users and stores and manages them in a database.

[1356] "Reaction" refers to the rating or feedback that other users give to a particular log.

[1357] A "database" refers to a system that systematically stores logs and reaction data and manages them in a manner that allows for search and analysis.

[1358] "Social Networking Service" means an online platform that enables users to share information and communicate with other users.

[1359] "Advertiser" refers to the entity that uses a generative AI model to create advertising copy and uploads that advertising copy to the system as a log.

[1360] "Generative AI model" refers to an artificial intelligence model that automatically generates ad copy and other information based on prompts entered by a user.

[1361] "Ad copy" refers to the advertising content generated by a generative AI model and served to users.

[1362] "Advertising Log" refers to a log containing advertising copy generated by an advertiser using a generative AI model and uploaded to the system.

[1363] "Measuring the effectiveness of advertising" refers to analyzing user reaction data and evaluating how much evaluation and interest a particular ad copy has generated.

[1364] This invention is a system that allows users to efficiently share logs generated using an information generation device and optimize the effectiveness of advertising through reactions. This system operates in cooperation with each element of the user, terminal, and server.

[1365] Generating and uploading logs

[1366] User: First, the advertiser user generates ad copy using the generative AI model. For example, they input a prompt such as "Generate an ad for a new drinking water product" and get the generated result. Then, they input this ad copy into the input form on their device and click the upload button.

[1367] Device: The entered ad copy and the corresponding results are compiled in JSON format and sent to the server, along with identifying information such as the user ID and campaign ID.

[1368] Server: Parse the received data, generate a log_id, and save the log_id, user ID, campaign ID, ad copy, results, timestamp, etc. in the database.

[1369] Adding a reaction

[1370] Users: Other users can view the uploaded ad logs and click reaction buttons such as "Like" or "Interested" on the ad logs they find useful.

[1371] Device: When the reaction button is clicked, the ad log ID and reaction type (e.g., "Like") are sent to the server.

[1372] Server: Receives reaction data and stores the user ID, reaction type, ad log ID, timestamp, etc. in a database. Also manages the increase / decrease in the number of reactions.

[1373] Sharing to social media

[1374] User: Clicks a button to share the ad log they found useful on social media.

[1375] Device: When you click the share button, the contents of the ad log will be embedded in text format into a URL for sharing on social media, and the social media posting screen will open in a new window.

[1376] Specific examples

[1377] 1. Generate and upload your ad:

[1378] Prompt: "Generate a new drinking water ad"

[1379] Result: "Try Sparkling Water, a refreshing new experience."

[1380] The advertiser enters this advertisement text and clicks the upload button.

[1381] 2. Adding a reaction:

[1382] Another user views this ad log and clicks the "Like" button.

[1383] The number of "likes" increases and reaction information is recorded in the database.

[1384] 3. Sharing to social media:

[1385] The user clicks a button to share this ad log on Twitter.

[1386] An advertising caption such as "Try a new refreshing sparkling water experience" is automatically embedded in the Twitter post screen, and a new window opens.

[1387] This system allows advertisers to measure the effectiveness of their ads in real time, providing them with a powerful tool for developing optimal advertising strategies. Furthermore, the social media sharing feature helps expand the user base and reach more users, which is expected to maximize the effectiveness of advertising.

[1388] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1389] Step 1:

[1390] The user generates ad copy using the generative AI model, and then inputs the prompts and results into the device's input form. At this time, the user enters the ad copy and related information (user ID, campaign ID, etc.) and clicks the upload button.

[1391] Input: prompt text, ad copy, user ID, campaign ID

[1392] Output: JSON format data

[1393] Step 2:

[1394] The device compiles the input data into JSON format and sends it to the server. Specifically, JSON data is created that includes the user ID, campaign ID, ad copy, etc.

[1395] Input: Data entered by the user (prompt text, ad copy, user ID, campaign ID)

[1396] Output: JSON data (prompt text, ad copy, user ID, campaign ID)

[1397] Step 3:

[1398] The server parses the received JSON data and generates a log_id. The generated log_id, user ID, campaign ID, ad copy, and timestamp are saved in the database. The database stores this information in an organized manner for future searches and analysis.

[1399] Input: JSON data (prompt text, ad copy, user ID, campaign ID)

[1400] Output: Save to database (log_id, user ID, campaign ID, ad copy, timestamp)

[1401] Step 4:

[1402] Other users can view the ad logs uploaded through their devices and click reaction buttons such as "Like" or "Interested" on the ad logs that interest them.

[1403] Input: Ad logs viewed by the user

[1404] Output: Reaction data (log ID, reaction type)

[1405] Step 5:

[1406] The device receives the user's reaction and sends the reaction data (log ID, user ID, reaction type) to the server.

[1407] Input: User's reaction (log ID, reaction type)

[1408] Output: JSON data (log ID, user ID, reaction type)

[1409] Step 6:

[1410] The server analyzes the reaction data it receives and stores it in a database. Specifically, it registers the log ID, user ID, reaction type, timestamp, etc. in the database and manages the increase or decrease in the number of reactions.

[1411] Input: JSON data (log ID, user ID, reaction type)

[1412] Output: Save to database (log ID, user ID, reaction type, timestamp)

[1413] Step 7:

[1414] If a user finds an ad log useful, they click a button to share it on social media. This action embeds the ad copy into the URL for sharing on social media.

[1415] Input: Ad logs shared by users

[1416] Output: URL for SNS sharing

[1417] Step 8:

[1418] The device opens the generated SNS sharing URL in a new window and displays the SNS posting screen. The user can then confirm the content to be shared and complete the post.

[1419] Input: URL for SNS sharing

[1420] Output: SNS post screen

[1421] This completes the entire process, from generating ad logs to adding reactions and sharing on social media, creating a system that can measure advertising effectiveness based on user feedback and optimize advertising strategies.

[1422] 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.

[1423] This invention is a system that allows users to efficiently share logs generated using information generation devices and improve the knowledge of the entire community through reactions, and also combines an emotion engine that recognizes user emotions. In this system, each element of the user, terminal, and server works in cooperation with the emotion engine.

[1424] Uploading logs

[1425] User: First, the user uses the information generation device to input a prompt and obtain the result. For example, the user inputs "Please write a poem using AI" as the prompt and receives text such as "A quiet night, the stars shine brightly" as the result. Next, the user enters the generated prompt and result into the input form on the device and clicks the "Upload" button. This operation sends the prompt and result to the server in JSON format.

[1426] Terminal: Generates JSON data containing the input prompts and results and sends it to the server. The emotion engine also recognizes the user's emotions and sends that information to the server.

[1427] Server: The server parses the received JSON data and emotion data, generates a new log entry based on it, generates a log ID, and saves data such as the user ID, prompt, result, emotion information, and timestamp in the database.

[1428] Adding a reaction

[1429] Users: Other users can view the uploaded logs and react to the logs they find useful, for example, by selecting a specific log from the log list and clicking the "Like" button.

[1430] Terminal: When the reaction button is clicked, the log ID and reaction type, as well as the user's emotion information recognized by the emotion engine, are sent to the server.

[1431] Server: Receives reaction data and emotion information, and stores data such as user ID, reaction type, log ID, emotion information, and timestamp in a database. Also, adjusts the display order of logs based on the number of reactions and emotion information.

[1432] Sharing to social media

[1433] User: If you want to share a log you like on a social networking service (SNS), click the share button. For example, you can click the "Share" button to post the log on Twitter.

[1434] On the device: When the share button is clicked, a new window will open with the log contents (prompt and result) and related emotional information embedded in the URL for sharing on social media.

[1435] Specific examples

[1436] 1. Generate and upload logs:

[1437] Prompt: "Make a poem with AI."

[1438] Result: "A quiet night, the stars shine brightly."

[1439] The user fills in this prompt and the results and clicks the upload button.

[1440] The emotion engine recognizes the user's emotion as "satisfied" and also sends this information to the server.

[1441] The server stores the logs and emotional information in a database.

[1442] 2. Reaction to the log:

[1443] Another user views this log and clicks the "Like" button.

[1444] The emotion engine recognizes the user's emotion as "happy" and sends it along with the reaction data.

[1445] The server records reaction data and emotional information and reflects this in the display order of the logs.

[1446] 3. Sharing to social media:

[1447] The user clicks a button to share this log on Twitter.

[1448] The log content and the emotional information of "satisfaction" are embedded in a URL for sharing on social media, and a new window is opened and posted to the social media site.

[1449] The system allows users to efficiently share their AI-generated experiences and emotional data, facilitating greater knowledge and emotion-based interactions across the community.

[1450] The processing flow will be explained below.

[1451] Step 1:

[1452] User: Inputs a prompt into the information generator and generates a result for that prompt. For example, the user inputs the prompt "Please write a poem using AI" and receives the generated result "A quiet night, the stars shine brightly."

[1453] Step 2:

[1454] User: Enters the generated prompt and results into the input form on the device, and the emotion engine recognizes the emotion. The emotion engine obtains emotional information (e.g., satisfaction) from the user's facial expressions and voice.

[1455] Step 3:

[1456] Terminal: The input prompt, result, and emotion information are sent to the server in JSON format. The data is sent to the server using an HTTP POST request.

[1457] Step 4:

[1458] Server: Parses the received JSON data and generates a new log entry. Creates a log ID and saves information such as the user ID, prompt, result, emotion information, and timestamp in the database.

[1459] Step 5:

[1460] Users: View logs uploaded by other users. Logs are displayed in a list format, with a link to each log's details page.

[1461] Step 6:

[1462] User: Add a reaction to a specific log. For example, when clicking the "Like" button, the emotion engine will recognize the emotion again and process that information along with the reaction.

[1463] Step 7:

[1464] On the device: When a reaction button is clicked, data including the log ID, reaction type, and emotion information is sent to the server in JSON format using an HTTP POST request.

[1465] Step 8:

[1466] Server: Analyzes the received reaction data and stores the reaction and emotional information in a database. It also adjusts the display order based on the number of reactions and emotional information in the log.

[1467] Step 9:

[1468] User: If you want to share a specific log on a social networking service (SNS), click the SNS share button.

[1469] Step 10:

[1470] On the device, when the social media share button is clicked, a new window is opened with the log content (prompt and result) and related emotional information embedded in the social media share URL. The URL contains encoded text and displays the social media share screen.

[1471] The above is the specific processing flow of the system that combines the emotion engine of this invention. This system efficiently shares users' experiences with using generated AI and their emotion data, improving knowledge across the entire community and promoting emotion-based interactions.

[1472] Example 2

[1473] 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."

[1474] In conventional information sharing systems, when users share data or logs they generate with other users, they do not take into account the user's emotional information, and reactions to the shared data are based solely on numerical values, which means that they are unable to fully realize interactions based on user emotions or improve knowledge across the entire community.Furthermore, sharing to external platforms such as social media can sometimes be difficult.

[1475] 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.

[1476] In this invention, the server includes a means for transmitting data and emotional information generated by users to the server, a means for the server to receive, analyze, and store the data and emotional information in a database, and a means for adjusting the display order of data based on the number of reactions and the emotional information, thereby promoting interaction based on user emotions and improving knowledge throughout the community.

[1477] A "user" is a person or entity that uses the system, generates data using an information generating device, and shares or reacts to this data.

[1478] An "information generating device" is a device or software that generates information or data using a generative AI model or the like based on prompts entered by a user.

[1479] "Data" means text or other information generated by a user using an information generating device, including prompts and their results.

[1480] "Emotion information" is information that is recognized using an emotion engine to recognize the user's emotional state (e.g., "satisfied," "happy," etc.) and sent to the server as part of the data.

[1481] A "server" is a computer system on a network that receives, analyzes, and stores data and emotional information sent by users and provides this data to other users.

[1482] "JSON format" is an abbreviation for JavaScript Object Notation, a lightweight data exchange format for storing and communicating structured data.

[1483] "Reactions" refer to actions other users take on shared data, and are expressed in the form of "likes" or comments.

[1484] A "database" is a collection of data built on a server, and is a system that stores and manages user-generated data, emotional information, and reactions.

[1485] "Display order" refers to the order in which the server displays data to other users, and is adjusted based on the number of reactions and emotional information.

[1486] "Social Networking Service" means an online service that enables users to share data with external social networking platforms.

[1487] This invention is a system that allows users to efficiently share data generated using information generation devices and improve the knowledge of the entire community through reactions, and also combines it with an emotion engine that recognizes the emotions of users. In this system, each element of the user, terminal, and server works in cooperation with the emotion engine.

[1488] Uploading logs

[1489] user

[1490] First, the user inputs a specific prompt sentence (e.g., "Please write a poem using AI") using the information generator. This information generator uses a generative AI model to generate data based on the input prompt. After receiving the generated result (e.g., "A quiet night, the stars shine"), the user enters the prompt and the result into the input form on their device and clicks the "Upload" button. This operation sends the prompt and the result to the server as JSON-formatted data. The emotion engine also recognizes the user's emotion (e.g., "Satisfied"), and this information is also sent.

[1491] Terminal

[1492] The device converts the input prompts and results into JSON format data and sends it to the server. In addition, an emotion engine (e.g., emotion recognition software) recognizes the user's emotions and sends that emotion information to the server. Examples of hardware used include PCs and smartphones, and software such as Android or iOS applications.

[1493] server

[1494] The server analyzes the received JSON data and emotion information and generates a new log entry. It stores data such as the log ID, user ID, prompt, result, emotion information, and timestamp in a database. The server uses Python and a database management system (e.g., MySQL) to perform this processing.

[1495] Adding a reaction

[1496] user

[1497] Other users can view the log list provided by the server through a web browser or app and react to logs they like, for example, by selecting a specific log from the log list and clicking the "Like" button.

[1498] Terminal

[1499] When the reaction button is clicked, the device generates data including the target log ID and reaction type (e.g., "Like"), and recognizes the user's emotion (e.g., "Happy") using the emotion engine.The device then sends the reaction information and emotion information to the server.

[1500] server

[1501] The server analyzes the received reaction data and emotional information and adds a new entry to the database. Data such as user ID, reaction type, log ID, emotional information, and timestamp are saved. Furthermore, the server adjusts the display order of the data based on the number of reactions and emotional information, and displays the logs in the appropriate order for the user.

[1502] Sharing to social media

[1503] user

[1504] If a user wants to share a particular log on a social networking site, they can click the "Share" button. For example, they can click the "Share" button to post the log on Twitter.

[1505] Terminal

[1506] When the share button is clicked, the device opens a new window with the log contents (prompt and result) and emotional information embedded in the URL for sharing on social media, allowing the user to post directly to social media.

[1507] Specific examples

[1508] 1. Prompt: "Create a poem using AI."

[1509] 2. Result: "The stars shine brightly on a quiet night."

[1510] The user enters these prompts and results and clicks the upload button. The emotion engine recognizes the user's emotion as "satisfied," and this information is sent to the server and stored in the database. When another user views this log and clicks the "Like" button, the reaction data and the emotion information of "happy" are sent to the server and recorded in the database.

[1511] This provides a system that efficiently shares users' generated AI usage experiences and emotional data, improving knowledge across the community and promoting emotion-based interactions.

[1512] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1513] Step 1:

[1514] user

[1515] A user inputs a prompt (e.g., "Please write a poem using AI") into the information generator and receives the generated result (e.g., "The stars shine brightly on a quiet night"). The input is the prompt, and the output is the generated text. This data is used in subsequent processing.

[1516] Step 2:

[1517] user

[1518] Enter the generated prompt sentence and result into the input form on the terminal and click the "Upload" button. The input is the prompt sentence and its result, and the click operation triggers the next process.

[1519] Step 3:

[1520] Terminal

[1521] The terminal receives user input and converts it into JSON format data. The input is the prompt and its result, and the output is JSON format data. This data includes the prompt, the result, and a timestamp.

[1522] Step 4:

[1523] Terminal

[1524] The emotion engine recognizes the user's emotional information. The input is the user's emotional state, and the output is the emotional information (e.g., "Satisfied"). This information is also integrated into the JSON data.

[1525] Step 5:

[1526] Terminal

[1527] Send JSON data and emotion information to the server. The input is the generated JSON data, and the output is the data sent to the server.

[1528] Step 6:

[1529] server

[1530] The server receives and parses the JSON data. The input is the JSON data sent from the terminal, and the output is the parsed prompt, result, and emotion information.

[1531] Step 7:

[1532] server

[1533] Generates a new log entry and saves it to the database. The input is the parsed data, and the output is a new log entry inserted into the database. This entry contains the log ID, user ID, prompt, result, emotion information, and timestamp.

[1534] Step 8:

[1535] user

[1536] Other users view the log list from the database in a web browser or app. The input is a request to display the log list, and the output is the log data returned from the server.

[1537] Step 9:

[1538] user

[1539] Click the "Like" button for the log you like. The input is the log ID to react to, and the output is the trigger for the reaction operation.

[1540] Step 10:

[1541] Terminal

[1542] It generates reaction data (log ID, reaction type) and user emotion information. The input is the user's reaction operation and emotional state, and the output is reaction data and emotion information.

[1543] Step 11:

[1544] Terminal

[1545] The generated reaction data and emotion information are sent to the server. The input is the reaction data and emotion information, and the output is the data sent to the server.

[1546] Step 12:

[1547] server

[1548] The server receives the reaction data and emotion information, analyzes them, and stores them in a database. The input is the reaction data and emotion information from the device, and the output is the recorded entry in the database.

[1549] Step 13:

[1550] server

[1551] The display order of data is adjusted based on the number of reactions and emotional information. The input is the number of reactions and emotional information in the database, and the output is the log data to be displayed with priority.

[1552] Step 14:

[1553] user

[1554] To share a log you like on a social networking site, click the "Share" button. The input is the log ID to be shared, and the output is the trigger for the sharing operation.

[1555] Step 15:

[1556] Terminal

[1557] It detects when the share button is clicked and opens a new window with the log content and emotion information embedded in the URL for sharing on social media. The input is the log content and emotion information, and the output is a window for posting to social media.

[1558] This series of processing steps efficiently shares user-generated data and emotional information, and accumulates reactions from other users, facilitating improved knowledge and emotion-based interactions across the community.

[1559] (Application example 2)

[1560] 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."

[1561] Conventional information sharing systems provide functions for sharing logs generated by users and receiving reactions from other users, but because they do not take into account users' emotional information, it is difficult to properly evaluate the usefulness and relevance of logs across the community. In addition, they lack functions for prioritizing display of logs based on emotions and sharing to social media, so there is a need to improve user engagement.

[1562] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing the user's emotion and transmitting the emotion information to the server together with the log, means for analyzing the emotion information and storing it in association with the log, and means for adjusting the display order of logs that have gathered a certain number of reactions or more based on the reactions and emotion information. This makes it possible to share and prioritize the display of logs that take into account the user's emotion information.

[1563] An "information generating device" is a machine or software that receives a prompt from a user and generates information based on that prompt.

[1564] A "log" is a collection of prompts generated by a user using an information generating device, the results of those prompts, and related data.

[1565] A "server" is a computer system that receives data sent by users and stores it in a database.

[1566] An "emotion engine" is a machine learning model or algorithm for recognizing emotions from user input and analyzing that information.

[1567] A "prompt" is a request or instruction sentence that a user inputs to an information generating device.

[1568] A "reaction" is an evaluation or response that other users make to a log, and includes, for example, "likes" and comments.

[1569] A "database" is a data management system that stores structured data within a server and allows for easy search and retrieval.

[1570] A "social networking service" is a platform where different users can share information and communicate with each other.

[1571] "Emotion information" is data that indicates the user's emotional state as recognized by the emotion engine.

[1572] A system for implementing this invention allows users to efficiently share logs generated using information generation devices and combines emotion engines to improve the knowledge of the entire community. This system includes the following specific configuration and processing.

[1573] The user first inputs a prompt to the information generator. For example, the prompt is "Please write a poem using AI." Based on this prompt, the information generator generates a poem and returns a result such as "On a quiet night, the stars shine brightly."

[1574] The user then enters the generated log (prompt and result) into an input form on a device such as a smartphone and clicks the "Upload" button. This operation causes the device to send JSON data containing the prompt, result, and the user's emotional information recognized by the emotion engine to the server.

[1575] The server parses the received JSON data and saves data such as the user ID, prompt, result, emotion information, and timestamp as a new log entry in the database. For example, if the emotion information is "Satisfied," that information is also associated with the log and saved.

[1576] Other users can view the logs and react to the logs they find useful, for example by clicking the "Like" button. The device sends the log ID, reaction type, and the user's emotion information recognized by the emotion engine to the server.

[1577] The server receives the reaction data and emotional information, stores it in a database, and adjusts the display order of logs based on the number of reactions and emotional information. For example, logs that have received a certain number of "likes" will be displayed with priority over other logs.

[1578] Furthermore, if a user wants to share a log they like on a social networking service (SNS), they can click the "Share" button. This action causes the device to open a new window and post the log content and emotional information to the SNS sharing URL, embedding it in the URL.

[1579] A concrete example would be the following:

[1580] 1. User enters a prompt. Example: "Please write a poem using AI."

[1581] 2. As a result: "Quiet Night, Stars Shine" is obtained and uploaded

[1582] 3. The emotion engine recognizes the user's emotion as "satisfied"

[1583] 4. The server stores the logs and emotional information in a database

[1584] 5. Another user clicks "like" on the log and recognizes the emotion as "happy."

[1585] 6. The display order of logs will be adjusted and displayed with priority.

[1586] This system configuration enables sharing of logs and adjustment of display order taking into account users' emotional information, thereby improving engagement and knowledge across the entire community.

[1587] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1588] Step 1:

[1589] A user opens a smartphone application and inputs a prompt into the information generator, for example, "Please write a poem using AI." This input is sent to the generative AI model, and the resulting poem is "A quiet night, the stars shine brightly."

[1590] Step 2:

[1591] The user checks the generated log (prompt sentences and results), and the emotion engine recognizes the user's emotion from their facial expressions and voice. For example, the emotion engine recognizes the user's emotion as "satisfied."

[1592] Step 3:

[1593] The user clicks the "Upload" button to send the log and the recognized emotion information to the server. The device then packages the prompt, result, user ID, and emotion information into JSON format data and sends it to the server.

[1594] Step 4:

[1595] The server parses the received JSON data, which contains the user ID, prompt, result, emotion, and timestamp. The server parses this data and generates a new log entry.

[1596] Step 5:

[1597] The server stores the generated log entries in a database, which includes the user ID, prompt, result, emotion information, and a timestamp, allowing the logs to be searched and viewed later.

[1598] Step 6:

[1599] Other users can view the log and react to it by clicking "like" or commenting. For example, a user can click the "like" button. This action sends the reaction information (log ID, reaction type, user ID, and emotion information) from the device to the server.

[1600] Step 7:

[1601] The server analyzes the received reaction data and emotional information and stores it in a database. The server updates the engagement index in the log based on the type of reaction and the user's emotional information.

[1602] Step 8:

[1603] Based on the reaction and emotion information, the server adjusts the display order of the logs. For example, if a particular log receives a certain number of "likes," it will be displayed with priority over other logs.

[1604] Step 9:

[1605] To share the log on a social networking service, the user clicks the "Share" button. This action causes the device to embed the log content (prompt and result) and emotional information into a URL for sharing on the social networking service, and opens a new window to prepare for posting.

[1606] Step 10:

[1607] Once sharing to the SNS is complete, the log is posted on the SNS. This post contains the log content and emotional information, such as "satisfied," and can be viewed by other users on the SNS.

[1608] 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.

[1609] 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.

[1610] 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 robot 414.

[1611] 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.

[1612] FIG. 9 illustrates 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 behaviors 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.

[1613] 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.

[1614] 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).

[1615] 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.

[1616] 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."

[1617] 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.

[1618] 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).

[1619] 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.

[1620] 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.

[1621] 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.

[1622] 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.

[1623] 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.

[1624] 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.

[1625] 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.

[1626] 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.

[1627] 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.

[1628] 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.

[1629] The following is further disclosed regarding the above embodiment.

[1630] (Claim 1)

[1631] A means for a user to input a log generated using an information generating device;

[1632] means for transmitting the log to a server;

[1633] A server receives the log and stores it in a database;

[1634] A means for other users to give reactions to the log;

[1635] A means for a server to receive the reactions and store them in a database;

[1636] A means for users to share logs to social networking services;

[1637] A system including:

[1638] (Claim 2)

[1639] 10. The system of claim 1, wherein the user-generated log includes prompts and their results.

[1640] (Claim 3)

[1641] 2. The system according to claim 1, further comprising means for preferentially displaying logs that have collected a certain number of reactions or more.

[1642] "Example 1"

[1643] (Claim 1)

[1644] a means for a user to input the generated prompts and results using the information generating device;

[1645] means for converting the prompts and results into a JSON format and transmitting the JSON format along with user identification information to a server;

[1646] a server receiving the prompt and the result, generating a log ID, and storing the log ID in a database;

[1647] A means for other users to provide reactions to the prompts and results;

[1648] A means for a server to receive the reactions, store them in a database, and update the number of reactions;

[1649] a means for users to share prompts and results to social networking services;

[1650] A system including:

[1651] (Claim 2)

[1652] 10. The system of claim 1, wherein the user-generated log includes prompts and their results.

[1653] (Claim 3)

[1654] 2. The system according to claim 1, further comprising means for preferentially displaying logs that have collected a certain number of reactions or more.

[1655] "Application Example 1"

[1656] (Claim 1)

[1657] A means for a user to input a log generated using an information generating device;

[1658] means for transmitting the log to a server;

[1659] A server receives the log and stores it in a database;

[1660] A means for other users to give reactions to the log;

[1661] A means for a server to receive the reactions and store them in a database;

[1662] A means for users to share logs to social networking services;

[1663] Advertisers can use generative AI models to generate ad copy and upload it as a log.

[1664] A means for users to give reactions to the displayed ad logs;

[1665] means for analyzing the reaction data and measuring the effectiveness of the advertisement;

[1666] A system including:

[1667] (Claim 2)

[1668] 10. The system of claim 1, wherein the user-generated log includes prompts and their results.

[1669] (Claim 3)

[1670] 2. The system according to claim 1, further comprising means for preferentially displaying logs that have collected a certain number of reactions or more.

[1671] "Example 2: Combining Emotion Engines"

[1672] (Claim 1)

[1673] A means for a user to input data generated using an information generating device;

[1674] means for transmitting the data and JSON format data including the user's emotion information to a server;

[1675] A server receives the data and emotion information, analyzes them, and stores them in a database;

[1676] A means for other users to give reactions to the data;

[1677] A server receives the reactions and emotional information of the users who make the reactions and stores them in a database;

[1678] a means for adjusting the display order of data based on the number of reactions and emotion information;

[1679] How users can share data with social networking services;

[1680] A system including:

[1681] (Claim 2)

[1682] 10. The system of claim 1, wherein the user-generated data includes a prompt statement and its result.

[1683] (Claim 3)

[1684] 2. The system according to claim 1, further comprising means for preferentially displaying data for which a certain number of reactions have been collected.

[1685] "Application example 2 when combining emotion engines"

[1686] (Claim 1)

[1687] A means for a user to input a log generated using an information generating device;

[1688] means for transmitting the log to a server;

[1689] A server receives the log and stores it in a database;

[1690] A means for other users to give reactions to the log;

[1691] A means for a server to receive the reactions and store them in a database;

[1692] A means for users to share logs to social networking services;

[1693] means for recognizing the user's emotion by an emotion engine and transmitting the emotion information together with the log to a server;

[1694] means for analyzing the emotion information and storing the information in association with a log;

[1695] A system including:

[1696] (Claim 2)

[1697] 10. The system of claim 1, wherein the user-generated log includes prompts and their outcomes, and recognized emotion information.

[1698] (Claim 3)

[1699] The system according to claim 1, further comprising means for adjusting the display order of logs that have received a certain number of reactions or more, based on the reactions and emotional information. [Explanation of symbols]

[1700] 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 a user to input a log generated using an information generating device; means for transmitting the log to a server; A server receives the log and stores it in a database; A means for other users to give reactions to the log; A means for a server to receive the reactions and store them in a database; A means for users to share logs to social networking services; A system including:

2. 10. The system of claim 1, wherein the user-generated log includes prompts and their results.

3. The system according to claim 1, further comprising means for preferentially displaying logs that have collected a certain number of reactions or more.

Images