System

Abstract

To provide a system.SOLUTION: A system includes: first means for receiving an input by a user in a text form of at least either a private problem or security problem; second means for generating a prompt sentence for outputting a solution to the user's problem, based on text data indicated by the user's input; third means for inputting the generated prompt sentence to a generative AI model to generate the solution; and fourth means for transmitting the generated solution to a terminal of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] It is often difficult for people to find solutions to their personal problems on their own, and it is also difficult to consult with others. Problems in specific situations, such as weekend activities, are particularly difficult for people who are not familiar with the situation to understand. There are also limited means of receiving feedback on problem-solving. [Means for solving the problem]

[0005] The present invention provides a generative AI that receives a user's private problems as input and generates solutions to those problems. It also provides a means for presenting the solutions generated by the generative AI to the user and receiving feedback from the user. This allows the user to obtain a solution to their own problem and also receive feedback on the effectiveness of the solution. In particular, its ability to generate solutions to problems related to weekend activities assists with problem solving in specific situations. Furthermore, the accuracy of problem solving is improved by improving the solutions based on user feedback. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] In one embodiment of the present invention, a user provides a system with a personal problem as text input. This problem may be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend brass band activities." The system receives this input and uses generative AI to generate a solution. The generated solution may be specific advice, such as, "To improve communication with your section leader, it would be effective to clearly communicate the specific problem and work together to come up with a solution." This solution is presented to the user, who provides feedback on its effectiveness to the system. The system receives this feedback and improves the generative AI's ability to generate solutions.

[0029] "Example 2"

[0030] In one embodiment of the present invention, a user provides a system with a personal problem as text input. This problem may be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend brass band activities." The system receives this input and uses generative AI to generate a solution. The generated solution may be specific advice, such as, "To improve communication with your section leader, it would be effective to clearly communicate the specific problem and work together to come up with a solution." This solution is presented to the user, who provides feedback on its effectiveness to the system. The system receives this feedback and improves the generative AI's ability to generate solutions.

[0031] The processing flow of each embodiment will be described below.

[0032] "Example 1"

[0033] Step 1: The user provides the system with a text entry about their personal problem. This problem can be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend band activities."

[0034] Step 2: The system receives input from the user and uses generative AI to generate solutions. The generated solutions are specific advice such as, "To improve communication with the part-time leader, it is effective to clearly communicate the specific problems and work together to find solutions."

[0035] Step 3: The system presents the generated solution to the user, who then tries it out and provides feedback to the system on its effectiveness.

[0036] Step 4: The system receives feedback from the user and improves the generative AI's ability to generate solutions, thereby improving the accuracy of solutions to the same or similar problems.

[0037] "Example 2"

[0038] Step 1: The user provides the system with a text entry about their personal problem. This problem can be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend band activities."

[0039] Step 2: The system receives input from the user and uses generative AI to generate solutions. The generated solutions are specific advice such as, "To improve communication with the part-time leader, it is effective to clearly communicate the specific problems and work together to find solutions."

[0040] Step 3: The system presents the generated solution to the user, who then tries it out and provides feedback to the system on its effectiveness.

[0041] Step 4: The system receives feedback from the user and improves the generative AI's ability to generate solutions, thereby improving the accuracy of solutions to the same or similar problems.

[0042] Example 1

[0043] Next, a description will be given of Example 1 of Form 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."

[0044] Conventional systems have difficulty providing appropriate solutions to users' private problems. They also lack a mechanism for evaluating the effectiveness of the solutions provided and reflecting this in future solution generation. This has led to the issue of lowering users' satisfaction with the solutions they receive.

[0045] 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.

[0046] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for generating a prompt sentence suitable for the generative AI means, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, and means for reflecting the received feedback in the generative AI means. This makes it possible to provide an appropriate solution to the user's problem and improve the solution based on feedback on its effectiveness.

[0047] "User" means an individual who utilizes the System to enter their private problem and receive a solution.

[0048] "Private issues" refer to specific challenges or difficulties that users face personally.

[0049] "Generative AI means" refers to the function of artificial intelligence that generates appropriate solutions to private problems input by users.

[0050] A "prompt sentence" refers to an instruction sentence that conveys the content of the problem to a generative AI means.

[0051] "Solutions" refer to specific advice or suggestions that generative AI methods provide to users for their private problems.

[0052] "Presentation means" refers to the functionality for displaying the generated solution to the user.

[0053] "Feedback" refers to information provided by the user to the system regarding the effectiveness and impressions of the proposed solution.

[0054] "Means of reflection" refers to the function of incorporating feedback received from users into generative AI means and using them to generate solutions in the future.

[0055] This invention relates to a system that allows users to input their own private problems and generate solutions to those problems. The system receives the user's input, generates solutions using a generative AI model, and presents them to the user. It also receives feedback from the user and improves the performance of the generative AI model.

[0056] Hardware and software used

[0057] The system uses the following hardware and software:

[0058] Device: The device through which a user enters their private problem and receives a solution. Examples include computers, smartphones, and tablets.

[0059] Server: A computer system that receives user input, sends prompts to the generative AI model, and sends the generated solutions to the device.

[0060] Generative AI model: An artificial intelligence model that generates solutions to user problems. Examples include OpenAI's GPT-4.

[0061] Data processing and calculation

[0062] The user uses the device to input a private problem in text format. For example, they can input a specific problem such as, "I'm having trouble communicating with the section leader during my weekend brass band activities." The device then sends this input to the server.

[0063] The server generates a prompt to pass the received text input to the generative AI model. For example, it generates a prompt such as, "The user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to solve this problem."

[0064] The generative AI model generates solutions based on prompts, such as advice like, "To improve communication with the part-time leader, it would be effective to clearly communicate the specific problems and work together to find solutions."

[0065] The generated solution is sent from the server to the terminal and presented to the user. The user checks the presented solution and provides feedback on its effectiveness to the server via the terminal.

[0066] The server receives feedback from users and uses it to improve the generative AI model's ability to generate solutions, allowing the system to continuously learn and provide more effective solutions.

[0067] Specific examples

[0068] For example, a user enters the following problem:

[0069] "I'm having trouble communicating with the section leader during weekend band activities."

[0070] Example prompts for generative AI models:

[0071] "A user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to resolve this issue."

[0072] An example of a generated solution:

[0073] "In order to improve communication with section leaders, it is effective to clearly communicate specific problems and work together to find solutions. For example, you could set up regular meetings to provide an opportunity for frank discussion of each other's opinions."

[0074] In this way, the system provides solutions to users' problems and improves the performance of the generative AI model based on user feedback.

[0075] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0076] Step 1:

[0077] A user uses a terminal to enter a private problem.

[0078] Specifically, the user inputs a problem in text format into the terminal interface, such as "I'm having trouble communicating with the section leader during my weekend brass band activities."

[0079] Input: User's private information (text data)

[0080] Output: Text data entered into the terminal

[0081] Step 2:

[0082] The terminal transmits the input text data to the server.

[0083] Specifically, the terminal encrypts the text data entered by the user and transmits it to the server.

[0084] Input: Text data entered into the terminal

[0085] Output: Encrypted text data sent to the server

[0086] Step 3:

[0087] The server analyzes the text data it receives and generates a prompt sentence suitable for the generative AI model.

[0088] Specifically, the server analyzes the text data and generates a prompt that reads, "The user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to solve this problem."

[0089] Input: Encrypted text data sent to the server

[0090] Output: A prompt suitable for a generative AI model

[0091] Step 4:

[0092] The server sends a prompt to the generative AI model.

[0093] Specifically, the server sends the generated prompt sentence to the generative AI model.

[0094] Input: A prompt suitable for a generative AI model

[0095] Output: The prompt sent to the generative AI model

[0096] Step 5:

[0097] A generative AI model generates a solution based on the prompt.

[0098] Specifically, the generative AI model analyzes the prompt and generates a solution such as, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and think of solutions together."

[0099] Input: A prompt sent to the generative AI model

[0100] Output: Generated solution (text data)

[0101] Step 6:

[0102] The server sends the generated solution to the terminal.

[0103] Specifically, the server encrypts the solution received from the generative AI model and sends it to the device.

[0104] Input: Generated solution (text data)

[0105] Output: The encrypted solution sent to the terminal.

[0106] Step 7:

[0107] The terminal presents a solution to the user.

[0108] Specifically, the device decrypts the solution received from the server and displays it to the user, who then checks the solution on the screen.

[0109] Input: The encrypted solution sent to the terminal

[0110] Output: The solution presented to the user

[0111] Step 8:

[0112] The user provides feedback on the effectiveness of the proposed solution.

[0113] Specifically, the user checks the presented solution and inputs feedback such as "This advice was very helpful" into the terminal interface.

[0114] Input: User feedback (text data)

[0115] Output: Feedback typed into the terminal

[0116] Step 9:

[0117] The device sends the feedback to the server.

[0118] Specifically, the terminal encrypts the feedback input by the user and transmits it to the server.

[0119] Input: Feedback entered into the device

[0120] Output: Encrypted feedback sent to the server

[0121] Step 10:

[0122] The server reflects the feedback in the generative AI model.

[0123] Specifically, the server incorporates the received feedback into the generative AI model and uses it to generate solutions from the next time onwards.

[0124] Input: Encrypted feedback sent to the server

[0125] Output: Feedback reflected in the generative AI model

[0126] (Application example 1)

[0127] Next, a description will be given of Application Example 1 of Embodiment 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."

[0128] Conventional generative AI systems focused on providing solutions to users' private problems, but lacked the ability to provide solutions to specific security issues. Furthermore, they lacked mechanisms for improving solutions based on user feedback. This made it difficult for users to receive prompt and accurate advice on security issues.

[0129] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes generative AI means that receives a user's private problem as input and generates a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, means for receiving a security problem as input and generating a solution to the problem, and means for presenting the generated solution to the user. This enables the user to receive prompt and accurate advice on specific security problems.

[0130] "User" means any person or entity that uses the System to enter private or security-related issues.

[0131] "Private issues" are problems or challenges that users face personally, such as issues related to relationships or daily life.

[0132] "Generative AI" is an artificial intelligence system that generates solutions to problems input by users.

[0133] A "solution" is a specific piece of advice or suggestion that a generative AI provides to a user about a problem.

[0134] "Feedback" refers to the evaluation or opinion that a user gives of the solution provided by the generative AI.

[0135] "Security issues" are specific safety and security issues faced by users.

[0136] "Presentation means" refers to a method or device for displaying the solution generated by generative AI to the user.

[0137] "Means for receiving" refers to a method or device by which the system receives feedback from the user.

[0138] The system for implementing this invention is a system that uses generative AI to solve problems related to users' privacy and security. Specific embodiments of this system are described below.

[0139] System Configuration

[0140] The system mainly consists of the following components:

[0141] 1. User device: A device such as a smartphone or computer that users use to enter questions.

[0142] 2. Server: A central system for hosting the generative AI and processing input from users.

[0143] 3. Generative AI: An artificial intelligence model that generates solutions to user problems. Examples include OpenAI's GPT-3 (registered trademark).

[0144] 4. Database: A storage system for saving user input and feedback.

[0145] Program processing

[0146] The server processes the data as follows:

[0147] 1. Receiving user input: Receive private or security issues in text format sent from the user's device.

[0148] 2. Generating a solution using generative AI: The received problem is input into a generative AI, which generates a solution. OpenAI's GPT-3 is used as the generative AI.

[0149] 3. Presenting the solution: The generated solution is sent to the user's terminal and presented to the user.

[0150] 4. Receiving feedback: Receiving feedback from users and storing it in a database.

[0151] 5. Improve the AI ​​model: Use the feedback received to improve the generative AI's ability to generate solutions.

[0152] Hardware and software used

[0153] Hardware: smartphones, PCs, servers

[0154] Software: Python (registered trademark), OpenAI API, database management system (e.g., MySQL (registered trademark))

[0155] Specific examples

[0156] If a user types in "I've seen suspicious people around my house recently," the server sends this input to a generative AI, which then generates a solution, such as "Installing security cameras and sharing information with neighbors would be effective," and presents it to the user.

[0157] Prompt Sentence Examples

[0158] User security issue: I've recently seen some suspicious people around my house.

[0159] Please provide a solution.

[0160] In this way, users can get fast and accurate advice on specific security issues.

[0161] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0162] Step 1:

[0163] The user terminal receives input from the user. Specifically, the user inputs private and security-related issues in text format using a smartphone or PC. The input text data is sent to the server.

[0164] Input: Text data entered by the user (e.g., "I've been seeing some suspicious people around my house lately.")

[0165] Output: Text data sent to the server

[0166] Step 2:

[0167] The server receives the text data sent from the user's device and generates a prompt sentence to be input to the generative AI. The prompt sentence is a concrete description of the user's problem.

[0168] Input: Text data sent by the user

[0169] Output: A prompt to be input to the generative AI (e.g., "User's security problem: I've been seeing suspicious people around my house recently. Please provide a solution.")

[0170] Step 3:

[0171] The server sends a prompt to a generative AI (e.g., OpenAI's GPT-3) to generate a solution. The generative AI generates an appropriate solution in text format based on the prompt.

[0172] Input: Prompt sentence to input to the generative AI

[0173] Output: The solution generated by the generative AI (e.g., "Installing security cameras and sharing information with neighbors would be effective.")

[0174] Step 4:

[0175] The server sends the generated solution to the user's device and presents it to the user, who can then check the solution on their smartphone or computer screen.

[0176] Input: A solution generated by a generative AI

[0177] Output: The solution sent to the user's device

[0178] Step 5:

[0179] The user terminal receives feedback from the user, who inputs his / her evaluation and opinion on the provided solution in text format and sends it to the server.

[0180] Input: User-entered feedback (e.g., "I think installing security cameras is a good idea.")

[0181] Output: Feedback sent to the server

[0182] Step 6:

[0183] The server receives feedback from users and stores it in a database, which is used to improve the generative AI's ability to generate solutions.

[0184] Input: Feedback submitted by the user

[0185] Output: Feedback stored in a database

[0186] Step 7:

[0187] The server retrains the generative AI model based on the saved feedback, improving its ability to generate solutions, which will result in more accurate solutions in future.

[0188] Input: Feedback stored in the database

[0189] Output: Improved generative AI model

[0190] By following these steps, users can get fast and accurate advice on specific security issues.

[0191] Example 2

[0192] Next, a description will be given of Example 2 of Form 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."

[0193] Conventional systems have difficulty providing appropriate solutions to users' private problems. Furthermore, they lack a mechanism for evaluating the effectiveness of the solutions provided and reflecting this in future solution generation, making it difficult to increase user satisfaction. Furthermore, they lack the ability to generate appropriate prompts for the user's specific problem, which can result in a decline in the quality of the solutions generated.

[0194] 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.

[0195] In this invention, the server includes a generative artificial intelligence that receives a user's private problem as input and generates a solution to the problem, a means for generating a prompt sentence suitable for the generative artificial intelligence, a means for presenting the solution generated by the generative artificial intelligence to the user, a means for receiving feedback from the user, and a means for improving the solution generation ability of the generative artificial intelligence based on the user's feedback. This makes it possible to provide an appropriate solution to the user's specific problem, evaluate its effectiveness, and reflect it in future solution generation.

[0196] "User" means an individual who utilizes the System to enter their private problem and receive a solution.

[0197] "Private issues" refers to specific problems or concerns that the user has personally.

[0198] "Generative AI" refers to artificial intelligence techniques that generate solutions based on user input.

[0199] A "prompt sentence" refers to an instruction sentence that is input to a generative artificial intelligence to generate an appropriate solution.

[0200] "Solutions" refer to the specific advice or suggestions that generative artificial intelligence provides to users about their problems.

[0201] "Feedback" refers to information that a user reports to the system after trying out a proposed solution, including its effectiveness and impressions.

[0202] "Server" refers to a computer system that receives user input data, generates solutions using generative artificial intelligence, and presents them to the user.

[0203] "Device" refers to the device through which a User enters their problem, receives a solution, and provides feedback.

[0204] The present invention is a system in which a user provides a text input of their private problem to the system, and a solution to the problem is generated. A specific embodiment of this system will be described below.

[0205] Hardware and software used

[0206] Hardware

[0207] Server: A high-performance computer system that runs generative artificial intelligence and processes user input data.

[0208] Device: The device that a user uses to enter their problem, receive a solution, or provide feedback. This could be a smartphone, tablet, or computer.

[0209] software

[0210] Generative artificial intelligence: For example, using advanced natural language processing techniques such as OpenAI's GPT-4.

[0211] Encryption protocol: The SSL / TLS protocol is used to securely transmit user input data to the server.

[0212] Data processing and calculation

[0213] User problem input

[0214] Users enter their personal problems into a text box on the device, for example, "I'm having trouble communicating with my section leader during my weekend band activities."

[0215] Sending input data

[0216] The terminal encrypts the text data entered by the user using the SSL / TLS protocol and sends it to the server.

[0217] Problem analysis and prompt generation

[0218] The server analyzes the received text data using natural language processing (NLP) technology and generates a prompt suitable for generative artificial intelligence. For example, if the user input is "I'm having trouble communicating with the section leader during weekend band activities," the prompt would be "The user is having trouble communicating with the section leader during weekend band activities. Please clearly explain the specific problem and provide advice so we can work together to find a solution."

[0219] Solution Generation

[0220] The server inputs the prompt into the generative AI, which then generates a solution. The generative AI then generates appropriate advice based on the prompt. For example, the generated advice might be, "To improve communication with the part leader, it is effective to clearly communicate the specific problems and work together to come up with solutions. It would be a good idea to have a private discussion with the part leader before the next rehearsal, share the specific problems, and set aside time to think about solutions together."

[0221] Proposing a solution

[0222] The server sends the generated solution to the terminal, which displays it to the user, who can then check and try out the solution.

[0223] Collecting feedback

[0224] After trying out the proposed solutions, users can enter specific feedback into the device about their effectiveness, such as, "The discussion with the part leader went well, and communication has improved."

[0225] Model Improvements

[0226] The device sends user feedback to the server, which passes it on to the generative AI and uses it to improve the model's ability to generate solutions, resulting in more effective solutions in future.

[0227] Specific examples

[0228] Example user input

[0229] "I'm having trouble communicating with the section leader during weekend band activities."

[0230] Example prompts for generative AI models

[0231] "A user is having trouble communicating with the section leader during their weekend band activities. Please clearly explain the specific problem and provide advice on how we can work together to find a solution."

[0232] Example of a generated solution

[0233] "To improve communication with section leaders, it is effective to clearly communicate specific problems and work together to find solutions. It is a good idea to have a private discussion with section leaders before the next rehearsal, share specific problems, and set aside time to think about solutions together."

[0234] This way, users receive concrete advice and can try it out for themselves, and feedback helps the system improve and provide more effective solutions.

[0235] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0236] Step 1:

[0237] The user enters their personal problem into the text box on the device. For example, they might enter, "I'm having trouble communicating with my section leader during my weekend brass band activities." The input data is in text format, and the user can proceed to the next step by clicking the "Submit" button.

[0238] Step 2:

[0239] The terminal encrypts the text data entered by the user using the SSL / TLS protocol and sends it to the server. The input data is encrypted text data and sent securely to the server. The server decrypts the received data and proceeds to the next step.

[0240] Step 3:

[0241] The server analyzes the received text data using natural language processing (NLP) technology. The input data is text data containing the user's problem, and the content of the problem is extracted as a result of the analysis. Based on this analysis result, the server generates a prompt suitable for generative AI. For example, a generated prompt might read, "The user is having trouble communicating with the section leader during weekend brass band activities. Please clearly explain the specific problem and provide advice so we can work together to find a solution."

[0242] Step 4:

[0243] The server inputs a prompt into the generative AI and generates a solution. The input data is the prompt, and the generative AI generates appropriate advice based on this. For example, a solution might be generated that reads, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and work together to come up with solutions. It would be a good idea to have a private discussion with the part leader before the next rehearsal, share the specific problems, and set aside time to think about solutions together."

[0244] Step 5:

[0245] The server sends the generated solution to the terminal, and the input data is the generated solution, which the terminal displays to the user, who can then check the presented solution and try it out.

[0246] Step 6:

[0247] After trying out the proposed solution, the user enters feedback about its effectiveness into the device. For example, specific feedback such as "The discussion with the part leader went well, and communication has improved." The input data is feedback information, and the user can proceed to the next step by clicking the "Submit" button.

[0248] Step 7:

[0249] The device sends the user's feedback to the server. The input data is feedback information, which the server receives and analyzes. The server then passes the feedback information to the generative AI and uses it to improve the model's ability to generate solutions, making future solutions more effective.

[0250] (Application example 2)

[0251] Next, a description will be given of Application Example 2 of Form 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."

[0252] With conventional security services, it was difficult to quickly provide appropriate solutions to the specific security problems faced by users. Furthermore, there was a lack of a mechanism for evaluating the effectiveness of the solutions provided and for continuous improvement, making it difficult to improve users' security awareness and the quality of countermeasures. This led to the issue of users being unable to use the digital environment with peace of mind.

[0253] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0254] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving user feedback, means for receiving a security problem as input and generating a solution to the problem, means for presenting the generated solution to the user, and means for improving the solution generation ability of the generative AI based on user feedback. This makes it possible to provide quick and appropriate solutions to specific security problems faced by users and to evaluate their effectiveness and continuously improve them.

[0255] "User" means any person or entity that uses the System to enter private or security-related issues.

[0256] "Private issues" are specific problems or challenges that users face personally.

[0257] "Generative AI" is a type of artificial intelligence that generates solutions to problems input by the user.

[0258] A "solution" is a specific piece of advice or countermeasure that the generative AI provides to the user for their problem.

[0259] "Feedback" is information about the results and effectiveness of a user's attempt at a provided solution.

[0260] "Security issues" are specific issues users face regarding safety and protection in the digital environment.

[0261] "The solution generation ability of generative AI" refers to the ability of generative AI to generate appropriate solutions to users' problems.

[0262] "Presentation means" refers to a method or device for displaying or notifying the user of the solution generated by the generative AI.

[0263] "Means for receiving" refers to a method or device by which the system obtains feedback from the user.

[0264] "Means for improvement" are methods or devices for improving the solution-generating capabilities of generative AI based on user feedback.

[0265] As an embodiment of this invention, we will explain how to install a security advisor AI system on a smartphone. In this system, a user inputs a security problem, and a generative AI generates a solution and presents it to the user. Furthermore, feedback from the user is received, and the generative AI's ability to generate a solution is improved.

[0266] Hardware and software used

[0267] Hardware: Smartphone

[0268] Software: Python, OpenAI API

[0269] System configuration

[0270] 1. Obtaining user input: The user inputs text into a smartphone application. For example, they input a specific problem, such as, "My home Wi-Fi has been unstable recently, and I'm worried about security."

[0271] 2. Prompt generation: Based on the user's input, a prompt is generated to be passed to the generative AI. For example, it could be something like, "User's security problem: Recently, my home Wi-Fi (registered trademark) has been unstable and I'm worried about security. Please provide a solution."

[0272] 3. AI solution generation: Using OpenAI's API, a generative AI (e.g., GPT-3) generates a solution. The generated solution is specific advice such as, "We recommend updating your Wi-Fi router's firmware and setting a strong password."

[0273] 4. Present the solution: The generated solution is presented to the user and displayed on the smartphone application.

[0274] 5. Get feedback: Users try the solution and provide feedback on its effectiveness, such as, "My Wi-Fi is now more stable and secure."

[0275] 6. Improving the Generative AI: Based on user feedback, we will improve the generative AI's ability to generate solutions, which will result in better and more effective solutions in future.

[0276] Specific examples

[0277] User input: "My home Wi-Fi has been unstable lately and I'm worried about security."

[0278] Example prompt: "User security issue: My home Wi-Fi has been unstable lately and I'm worried about security. Please provide a solution."

[0279] AI advice: "We recommend updating your Wi-Fi router's firmware and setting a strong password."

[0280] User feedback: "Wi-Fi is now more stable and secure."

[0281] In this way, it is possible to provide quick and appropriate solutions to specific security problems faced by users, evaluate their effectiveness and continuously improve them.

[0282] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0283] Step 1:

[0284] The user launches an application on their smartphone and enters a security problem via text.

[0285] Input: A specific security issue entered by the user (e.g., "My home Wi-Fi has been unstable lately, and I'm worried about security.")

[0286] Output: The text entered by the user

[0287] Specific behavior: The user enters a problem into the application's text input field and presses the submit button.

[0288] Step 2:

[0289] The device receives user input and generates a prompt sentence to be passed to the generative AI.

[0290] Input: User-entered text

[0291] Output: Generated prompt (e.g. "User's security problem: My home Wi-Fi has been unstable recently and I'm worried about security. Please provide a solution.")

[0292] What it does: The application formats the user's input text and generates a prompt suitable for generative AI.

[0293] Step 3:

[0294] The server calls the generative AI and generates a solution using the generated prompt sentence as input.

[0295] Input: Generated prompt statement

[0296] Output: The solution generated by the generative AI (e.g., "It is recommended that you update your Wi-Fi router's firmware and set a strong password.")

[0297] Specific operation: The server uses the OpenAI API to send a prompt to a generative AI (e.g., GPT-3) and obtain a solution.

[0298] Step 4:

[0299] The terminal presents the generated solution to the user.

[0300] Input: A solution generated by a generative AI

[0301] Output: The solution presented to the user

[0302] What happens: The application displays the solution on the user's screen.

[0303] Step 5:

[0304] The user tries the proposed solution and inputs feedback on its effectiveness.

[0305] Input: Feedback about the effectiveness of the solution the user tried (e.g., "My Wi-Fi is now more stable and secure.")

[0306] Output: User feedback text

[0307] Specific behavior: The user enters the effect in the application's feedback input field and presses the submit button.

[0308] Step 6:

[0309] The server receives feedback from users and improves the generative AI's ability to generate solutions.

[0310] Input: User feedback text

[0311] Output: Improved solution generation capabilities of generative AI

[0312] Specific operation: The server analyzes the feedback data, incorporates it as learning data for the generative AI, and reflects it in generating solutions from the next time onwards.

[0313] 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.

[0314] "Example 1"

[0315] As one embodiment of the present invention, a system incorporating an emotion engine is provided. The system includes a generative AI that receives a user's private problem as input and generates a solution to the problem, a means for presenting the solution generated by the generative AI to the user, and a means for receiving feedback from the user. The system further includes an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's emotional state and provides the results to the generative AI. The generative AI uses this emotional information to generate a more appropriate solution. For example, if a user has a problem related to weekend band activities and feels strongly about the problem, the emotion engine recognizes the strong emotion, and the generative AI uses that information to generate a more specific and appropriate solution.

[0316] "Example 2"

[0317] As one embodiment of the present invention, a system incorporating an emotion engine is provided. The system includes a generative AI that receives a user's private problem as input and generates a solution to the problem, a means for presenting the solution generated by the generative AI to the user, and a means for receiving feedback from the user. The system further includes an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's emotional state and provides the results to the generative AI. The generative AI uses this emotional information to generate a more appropriate solution. For example, if a user has a problem related to weekend band activities and feels strongly about the problem, the emotion engine recognizes the strong emotion, and the generative AI uses that information to generate a more specific and appropriate solution.

[0318] The processing flow of each embodiment will be described below.

[0319] "Example 1"

[0320] Step 1: The user provides the system with a private concern as text input. Step 2: The emotion engine analyzes the user's emotional state based on information derived from the user's text input and, if possible, other inputs such as the user's voice and facial expressions.

[0321] Step 3: The emotion engine provides the analysis results to the generative AI, which uses this information as reference when generating solutions.

[0322] Step 4: The generative AI generates a solution to the user's problem. This solution is generated based on the problem information provided by the user and the emotional information provided by the emotion engine.

[0323] Step 5: The system presents the generated solution to the user.

[0324] Step 6: The user provides feedback regarding the usefulness and appropriateness of the proposed solution.

[0325] Step 7: The system receives user feedback and uses it to improve the generative AI's ability to generate solutions.

[0326] "Example 2"

[0327] Step 1: The user provides the system with a private concern as text input. Step 2: The emotion engine analyzes the user's emotional state based on information derived from the user's text input and, if possible, other inputs such as the user's voice and facial expressions.

[0328] Step 3: The emotion engine provides the analysis results to the generative AI, which uses this information as reference when generating solutions.

[0329] Step 4: The generative AI generates a solution to the user's problem. This solution is generated based on the problem information provided by the user and the emotional information provided by the emotion engine.

[0330] Step 5: The system presents the generated solution to the user.

[0331] Step 6: The user provides feedback regarding the usefulness and appropriateness of the proposed solution.

[0332] Step 7: The system receives user feedback and uses it to improve the generative AI's ability to generate solutions.

[0333] Example 1

[0334] Next, a description will be given of Example 1 of Form 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."

[0335] Conventional systems were unable to consider the user's emotional state when providing solutions to a user's private problems, making it difficult to provide appropriate solutions. Furthermore, there was a lack of a way to effectively utilize user feedback to improve the generative AI's ability to generate solutions. This resulted in problems such as a decrease in the accuracy and appropriateness of solutions for users.

[0336] 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.

[0337] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, emotion engine means for analyzing the user's emotional state, means for providing the emotion engine's analysis results to the generative AI, and means for analyzing the user's feedback and improving the generative AI's ability to generate solutions. This makes it possible to provide appropriate solutions that take the user's emotional state into consideration and to continuously improve the generative AI by utilizing the feedback.

[0338] "User" means an individual who utilizes the System to enter their private problems and obtain solutions.

[0339] "Private issues" refers to specific problems or concerns that the user has personally.

[0340] "Generative AI" refers to artificial intelligence models that generate solutions based on user input.

[0341] "Solutions" refer to the specific advice or suggestions that generative AI provides to users about their problems.

[0342] "Means for presentation" refers to the method or device for displaying the solution generated by generative AI to the user.

[0343] "Feedback" refers to information that users return to the system about the effectiveness and impressions of the proposed solutions.

[0344] An "emotion engine" refers to software or hardware that analyzes a user's emotional state and provides the results to generative AI.

[0345] "Analysis results" refers to the data obtained as a result of the emotion engine analyzing the user's emotional state.

[0346] "Means for improvement" refers to methods and devices for analyzing user feedback and improving the generative AI's ability to generate solutions.

[0347] This invention is a system that allows users to input their private problems in text format and generates solutions to those problems. The system uses a generative AI model to generate solutions and presents them to the user. It also receives feedback from the user to improve the generative AI model's ability to generate solutions. Furthermore, it uses an emotion engine to analyze the user's emotional state and provides the results to the generative AI model to generate more appropriate solutions.

[0348] Hardware and software used

[0349] Hardware

[0350] Device: The device through which a user enters their problem and receives a solution (e.g., smartphone, tablet, computer).

[0351] Server: A computer system for running generative AI models and emotion engines

[0352] software

[0353] Generative AI models: Artificial intelligence models that generate solutions to user problems (e.g., GPT-4)

[0354] Emotion Engine: Software for analyzing the user's emotional state

[0355] Feedback Analysis System: Software for analyzing user feedback and improving generative AI models

[0356] Data processing and calculation

[0357] User problem input

[0358] Users use the device to enter their personal problems in text format, for example, "I'm having trouble communicating with my section leader during my weekend band activities."

[0359] Receiving and analyzing the problem

[0360] The device sends input from the user to the server. The server receives this input and generates a prompt to pass to the generative AI model. For example, it generates a prompt such as, "The user is having trouble communicating with the section leader during weekend band activities. How can we improve this?"

[0361] Solution Generation

[0362] The server inputs the prompt into a generative AI model (e.g., GPT-4) and generates a solution. The generative AI model generates specific advice based on the prompt. For example, it generates a solution such as, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and work together to find a solution."

[0363] Proposing a solution

[0364] The server sends the generated solution to the terminal, which displays the received solution to the user, who then checks the presented solution and decides whether to execute it.

[0365] Receiving Feedback

[0366] The user inputs feedback into the device about the effectiveness of the proposed solution. For example, they can input something like, "As a result of implementing the advice, my communication with the part leader improved." The device then sends this feedback to the server.

[0367] Feedback analysis and learning

[0368] The server receives and analyzes feedback from users. The analysis results are used as learning data to improve the solution generation capabilities of the generative AI model. This will result in more accurate solutions being generated in the future.

[0369] Use of emotion engine

[0370] When a user inputs a problem, the emotion engine analyzes the user's emotional state. For example, if the user has strong emotions, it provides that information to the generative AI model, which then uses this emotional information to generate a more appropriate solution. For example, if the user is feeling very stressed, the emotion engine provides that information to the generative AI model, which then takes that information into account to generate a more empathetic solution.

[0371] Examples of specific examples and prompts

[0372] Specific examples

[0373] If a user enters, "I'm having trouble communicating with the section leader during my weekend band activities," the system will process the following:

[0374] 1. The user enters the problem.

[0375] 2. The device sends the input to the server.

[0376] 3. The server passes the problem to a generative AI model (e.g., GPT-4).

[0377] 4. The generative AI model generates a solution.

[0378] 5. The server sends the solution to the device.

[0379] 6. The device presents a solution to the user.

[0380] 7. The user enters feedback.

[0381] 8. The device sends the feedback to the server.

[0382] 9. The server analyzes the feedback and improves the generative AI model.

[0383] Prompt Sentence Examples

[0384] "During the weekend brass band activities, I'm having trouble communicating with the section leaders. How can I improve this?"

[0385] By inputting this prompt into a generative AI model, a specific solution is generated.

[0386] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0387] Step 1:

[0388] The user uses the device to input their personal problems in text format. For example, they might input, "I'm having trouble communicating with the section leader during my weekend brass band activities." The input text data is saved in an input field on the device.

[0389] Step 2:

[0390] The terminal sends user input to the server. Specifically, it sends text data to the server using an HTTP request. The server receives this request and prepares to parse the text data.

[0391] Step 3:

[0392] The server analyzes the received text data and generates a prompt to be passed to the generative AI model. For example, it generates a prompt such as, "The user is having trouble communicating with the section leader during weekend band activities. How can we improve this?" This prompt is then input into the generative AI model.

[0393] Step 4:

[0394] The server inputs the prompt into a generative AI model (e.g., GPT-4) and generates a solution. The generative AI model generates specific advice based on the prompt. For example, it generates a solution such as, "To improve communication with the part leader, it is effective to clearly communicate the specific problems and think about solutions together." This solution is stored on the server.

[0395] Step 5:

[0396] The server sends the generated solution to the terminal as an HTTP response. The terminal displays the received solution to the user. The user checks the presented solution and decides whether to execute it.

[0397] Step 6:

[0398] The user enters feedback into the device about the effectiveness of the proposed solution. For example, they might say, "After implementing the advice, my communication with the part leader improved." The entered feedback is saved in an input field on the device.

[0399] Step 7:

[0400] The device sends user feedback to the server. Specifically, it sends the feedback data to the server using an HTTP request. The server receives this request and prepares to analyze the feedback data.

[0401] Step 8:

[0402] The server analyzes user feedback and uses it as learning data to improve the generative AI model's ability to generate solutions. Based on the analysis results, the generative AI model is retrained to generate more accurate solutions in the future.

[0403] Step 9:

[0404] When a user inputs a problem, the emotion engine analyzes the user's emotional state. For example, if the user has strong emotions, it provides that information to the generative AI model, which then uses this emotional information to generate a more appropriate solution. For example, if the user is feeling very stressed, the emotion engine provides that information to the generative AI model, which then takes that information into account to generate a more empathetic solution.

[0405] (Application example 1)

[0406] Next, a description will be given of Application Example 1 of Embodiment 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."

[0407] Conventional security services have difficulty providing appropriate solutions to specific problems faced by users. Furthermore, they are unable to provide solutions that take into account the user's emotional state, which can lead to lower user satisfaction. Furthermore, they lack a mechanism for effectively utilizing user feedback to improve solutions.

[0408] 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.

[0409] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, emotion engine means for analyzing the user's emotional state, means for providing emotion information obtained by the emotion engine to the generative AI, and generative AI means for generating a solution based on the emotion information. This makes it possible to provide an appropriate solution that takes the user's emotional state into consideration and to improve the solution by utilizing feedback from the user.

[0410] "User's private issues" refer to the specific challenges and difficulties that individuals face in their daily lives and work.

[0411] "Generative AI" refers to artificial intelligence that generates solutions to problems provided by users.

[0412] "Generating a solution" means providing appropriate solutions or advice to the user's problem.

[0413] "User presentation" refers to the interface or method for displaying the generated solution to the user.

[0414] "Feedback methods" refers to the interface and methods for collecting user ratings and opinions.

[0415] An "emotion engine" is a system or software that analyzes a user's emotional state and provides the results.

[0416] "Emotional Information" means data regarding a user's emotional state analyzed by the Emotion Engine.

[0417] "Security issues" refer to specific security challenges faced by users, such as online fraud and personal information leaks.

[0418] "Improving the solution" means improving the quality of the solution provided by the generative AI based on feedback from users.

[0419] As an embodiment of the present invention, a security advisor system is constructed. The system includes a generative AI that receives a user's private problem as input and generates a solution to the problem, a means for presenting the solution generated by the generative AI to the user, a means for receiving feedback from the user, an emotion engine that analyzes the user's emotional state, a means for providing the generative AI with emotion information obtained by the emotion engine, and the generative AI that generates a solution based on the emotion information.

[0420] Hardware and software used

[0421] Hardware: Smartphone, PC

[0422] Software: Python, OpenAI API, EmotionEngine library

[0423] Data processing and calculation

[0424] 1. Getting user input:

[0425] The user provides a text input for a security problem, such as "I've been getting a lot of phishing emails lately."

[0426] 2. Emotional state analysis:

[0427] Analyze the emotional state of the user from their input using an emotion engine. Use the EmotionEngine library to detect the user's emotional state (e.g., "anxiety").

[0428] 3. Prompt generation:

[0429] Generate prompts that include emotional information and the user's problem. For example, generate prompts like the following:

[0430] User's emotional state: Anxiety

[0431] User Problem: I've been getting a lot of phishing emails lately.

[0432] Please provide a solution.

[0433] 4. Solution Generation:

[0434] Using the OpenAI API, generative AI generates solutions, such as "specific methods for identifying phishing emails."

[0435] 5. Propose a solution:

[0436] The generated solution is presented to the user, who can check it on their smartphone or PC screen.

[0437] 6. Getting feedback:

[0438] Get and store user feedback. Users rate whether the solution was helpful and provide that rating to the system.

[0439] Specific examples

[0440] If a user types, "I'm having trouble with the number of phishing emails I've received lately," the emotion engine will detect "anxiety," and the generative AI will provide "specific methods for identifying phishing emails." An example of a prompt sentence is as follows:

[0441] User's emotional state: Anxiety

[0442] User Problem: I've been getting a lot of phishing emails lately.

[0443] Please provide a solution.

[0444] In this way, it is possible to provide appropriate solutions that take into account the user's emotional state and to use user feedback to improve the solutions.

[0445] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0446] Step 1:

[0447] The user provides a security problem as text input using a terminal. For example, the user might type, "I've been getting a lot of phishing emails lately." This input is sent to the system.

[0448] Step 2:

[0449] The server receives input from the user and sends it to the emotion engine. The emotion engine uses the EmotionEngine library to analyze the emotional state from the user's input. For example, it detects the emotional state "anxiety." This emotional information is returned to the server.

[0450] Step 3:

[0451] The server generates a prompt based on the emotional information and the user's problem. For example, it generates the following prompt:

[0452] User's emotional state: Anxiety

[0453] User Problem: I've been getting a lot of phishing emails lately.

[0454] Please provide a solution.

[0455] This prompt is sent to the generative AI.

[0456] Step 4:

[0457] The server uses generative AI to generate a solution based on the prompt. Using the OpenAI API, the generative AI generates a solution. For example, a solution such as "specific methods for identifying phishing emails" is generated. This solution is then returned to the server.

[0458] Step 5:

[0459] The server presents the generated solution to the user, who can then check the solution on the device screen. For example, the solution may show "specific methods for identifying phishing emails."

[0460] Step 6:

[0461] The user enters feedback on the proposed solution, for example by answering "yes" or "no" to the question "Did this solution help you?" This feedback is sent to the server.

[0462] Step 7:

[0463] The server receives and stores feedback from users. The feedback is used to improve the generative AI. For example, it is stored in a feedback database and referenced the next time a solution is generated.

[0464] In this way, it is possible to provide an appropriate solution that takes into account the user's emotional state and to use feedback from the user to improve the solution.

[0465] Example 2

[0466] Next, a description will be given of Example 2 of Form 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."

[0467] Conventional systems were unable to take the user's emotional state into account when generating solutions to the user's private problems, making it difficult to provide appropriate solutions. Furthermore, there was a lack of a way to effectively utilize user feedback to improve the performance of generative AI. This resulted in a decrease in user satisfaction with the solution.

[0468] 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.

[0469] In this invention, the server includes a generative AI that receives a user's private problem as input and generates a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, an emotion engine that analyzes the user's emotional state, means for providing the emotion engine's analysis results to the generative AI, means for the generative AI to generate a solution using the user's emotional information, and means for improving the generative AI's algorithm based on user feedback. This makes it possible to provide appropriate solutions that take the user's emotional state into consideration and to improve the performance of the generative AI based on feedback.

[0470] "User" means an individual who utilizes the System to enter their private problems and obtain solutions.

[0471] "Private issues" refers to specific problems or concerns that the user has personally.

[0472] "Generative AI" refers to artificial intelligence models that generate solutions based on user input.

[0473] "Solutions" refer to the specific advice or suggestions that generative AI provides to users about their problems.

[0474] "Emotion engine" refers to a system component that analyzes the user's emotional state and provides the results to generative AI.

[0475] "Feedback" refers to information that a user provides to the system about the effectiveness and impressions of the proposed solution.

[0476] An "algorithm" refers to the set of computational steps or rules that generative AI uses to generate solutions.

[0477] The "server" refers to a central processing unit that receives user input, works with generative AI and emotion engines to generate solutions, and presents them to the user.

[0478] "Terminal" means the device through which a User enters a problem and receives a solution.

[0479] This invention is a system that allows users to provide their private problems as text input to the system, which then generates solutions to those problems. The system combines generative AI and an emotion engine to provide solutions that take into account the user's emotional state.

[0480] Users use devices such as smartphones or PCs to input personal problems in text format. For example, they can input a specific problem such as, "I'm having trouble communicating with my section leader during my weekend brass band activities."

[0481] The device sends the problem entered by the user to the server. The server passes the received text to a generative AI, which generates a solution. OpenAI's GPT-4 can be used as the generative AI. The generative AI generates a solution to the user's problem and provides specific advice, such as, "To improve communication with your part-time leader, it is effective to clearly communicate the specific problem and work together to find a solution."

[0482] The server sends the generated solution to the device, which then presents it to the user. The user reviews the presented solution and inputs its effectiveness as feedback into the device. The device then sends feedback from the user to the server. The server receives this feedback and uses it to improve the solution-generating ability of the generative AI.

[0483] Additionally, the emotion engine analyzes the user's emotional state. For example, if the user has strong emotions about a problem, the emotion engine provides that information to the generative AI, which then uses this emotional information to generate a more appropriate solution.

[0484] As a concrete example, if a user inputs the problem, "I'm having trouble communicating with the section leader during my weekend brass band activities," the following prompt sentence will be input to the generative AI.

[0485] Example prompt sentence:

[0486] A user is having trouble communicating with the section leader during weekend band activities. Please provide a concrete solution to this problem.

[0487] The generative AI generates a solution based on this prompt and provides advice such as the following:

[0488] To improve communication with your part-time leader, it is effective to clearly communicate specific problems and work together to find solutions. It is also recommended to hold regular meetings to create a forum for exchanging opinions with each other.

[0489] This solution is presented to the user, who then provides feedback on its effectiveness to the system, which then uses this feedback to improve the performance of the generative AI.

[0490] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0491] Step 1:

[0492] The user enters the problem.

[0493] Users enter their problem into a text input field displayed on the screen of their smartphone or computer. For example, they might enter, "I'm having trouble communicating with the section leader during my weekend brass band activities." The input data is in text format.

[0494] Step 2:

[0495] The device sends input to the server.

[0496] The terminal sends the text data entered by the user to the server as an HTTP request. When sending, the data is converted to JSON format. The input is the user's text data, and the output is the JSON data sent to the server.

[0497] Step 3:

[0498] The server sends a prompt to the generative AI.

[0499] The server analyzes the received JSON data and generates a prompt to send to the generative AI. The generated prompt is sent to the generative AI as an API request. The input is JSON data, and the output is the prompt.

[0500] Step 4:

[0501] Generative AI generates solutions.

[0502] Generative AI (for example, OpenAI's GPT-4) generates a solution based on the prompt received from the server. The generated solution is returned to the server as an API response. The input is the prompt, and the output is the solution text.

[0503] Step 5:

[0504] The server sends the solution to the device.

[0505] The server analyzes the solution received from the generative AI and converts it into a format for presentation to the user. The converted data is sent to the device as an HTTP response. The input is the text of the solution, and the output is the data sent to the device.

[0506] Step 6:

[0507] The terminal presents a solution to the user.

[0508] The terminal displays the solution received from the server on the screen. The user checks the solution displayed on the screen and decides whether to execute it. The input is the data from the server, and the output is the solution presented to the user.

[0509] Step 7:

[0510] The user enters feedback.

[0511] The user enters specific impressions and results in a field for entering feedback about the effectiveness of the solution. For example, the user might enter "Communication with the part leader has improved." The input is the feedback text, and the output is the data sent to the terminal.

[0512] Step 8:

[0513] The device sends the feedback to the server.

[0514] The terminal sends the feedback received from the user to the server again as an HTTP request. When sending, the data is converted to JSON format again. The input is the feedback text, and the output is the JSON data sent to the server.

[0515] Step 9:

[0516] The server improves the generative AI based on the feedback.

[0517] The server analyzes the received feedback and uses it as data to improve the generative AI algorithm, making future solution generation more appropriate and effective. The input is the feedback data, and the output is an improved generative AI algorithm.

[0518] (Application example 2)

[0519] Next, a description will be given of Application Example 2 of Form 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."

[0520] Conventional security services have difficulty providing appropriate solutions to specific problems users face. Furthermore, they lack a mechanism for providing solutions that take into account the user's emotional state, making it impossible to reduce user anxiety and stress. Furthermore, they lack a mechanism for effectively utilizing user feedback to improve solutions. To address these issues, a system is needed that provides appropriate solutions that take into account the user's specific problems and emotional state, and that continuously improves solutions based on feedback.

[0521] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0522] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, emotion engine means for analyzing the user's emotional state, means for providing the generative AI with emotion information obtained by the emotion engine, and means for the generative AI to generate a solution using the emotion information. This makes it possible to provide an appropriate solution that takes into account the user's specific problem and emotional state, and to continuously improve the solution based on feedback.

[0523] "User's private problems" refer to the specific troubles and concerns that individuals face in their daily lives or in specific situations.

[0524] "Generative AI" refers to artificial intelligence that generates solutions to problems provided by users.

[0525] "Means for presenting solutions to users" refers to methods or devices for communicating solutions generated by generative AI to users.

[0526] "Means for receiving user feedback" refers to a method or device for collecting user opinions and evaluations of the solution provided.

[0527] An "emotion engine" is a system or software that analyzes a user's emotional state and provides the results to generative AI.

[0528] "Emotional Information" means data regarding a user's emotional state analyzed by the Emotion Engine.

[0529] "Security-related issues" refer to specific problems or concerns users face regarding safety and crime prevention.

[0530] "Improving solutions based on feedback" means improving the quality of the solutions provided by generative AI by reflecting opinions and evaluations from users.

[0531] A system for implementing this invention includes a generative AI that receives a user's private problem as input and generates a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, an emotion engine that analyzes the user's emotional state, means for providing the generative AI with emotion information obtained by the emotion engine, and means for the generative AI to generate a solution using the emotion information.

[0532] Hardware and software used

[0533] Hardware: Smartphone

[0534] Software: Python, OpenAI API, EmotionEngine library

[0535] System processing overview

[0536] 1. Receiving user input: The user uses their smartphone to provide text input about a specific security issue, such as, "I've been seeing a lot of suspicious people around my house lately, and it's making me feel uneasy."

[0537] 2. Emotional state analysis: The emotion engine analyzes the user's input text and identifies the user's emotional state, for example recognizing emotions such as anxiety or fear.

[0538] 3. Sending a prompt to the generative AI: A prompt containing the emotional information obtained by the emotion engine and the user's problem is sent to the generative AI. An example of a prompt is as follows:

[0539] User's emotional state: Anxiety

[0540] User Problem: I've been seeing a lot of suspicious people around my house lately and it's making me feel uneasy.

[0541] Please provide a solution.

[0542] 4. Solution generation: Generative AI generates solutions based on the prompts, providing specific advice such as "Installing security cameras and sharing information with neighbors would be effective."

[0543] 5. Present the solution: The generated solution is presented to the user, who can check it on their smartphone screen.

[0544] 6. Receiving feedback: Users provide feedback on the solutions provided, including their opinions and ratings. This feedback is sent to the system and used to improve the generative AI's ability to generate solutions.

[0545] Specific examples

[0546] If a user inputs, "I've been seeing a lot of suspicious people around my house recently and I'm worried," the emotion engine will recognize the user's anxiety, and the generative AI will provide specific advice such as, "It would be effective to install security cameras and share information with neighbors." This solution is presented to the user, and the user provides feedback on its effectiveness to the system.

[0547] In this way, it is possible to provide appropriate solutions that take into account the user's specific problem and emotional state, and to continuously improve the solutions based on feedback.

[0548] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0549] Step 1:

[0550] The user uses their smartphone to provide a specific security problem as text input.

[0551] Input: User's problem text (e.g., "I've been seeing a lot of suspicious people around my house lately and it's making me feel uneasy.")

[0552] Output: The user's problem text is sent to the system.

[0553] Specific actions: The user opens the application on their smartphone, enters a problem into the text input field, and presses the submit button.

[0554] Step 2:

[0555] The server receives the user's input text and sends it to the emotion engine.

[0556] Input: User's problem text

[0557] Output: Text sent to the sentiment engine

[0558] Specific operation: The server receives the user's input text and sends the text to the emotion engine's API.

[0559] Step 3:

[0560] The emotion engine analyzes the user's input text and identifies their emotional state.

[0561] Input: User's problem text

[0562] Output: User's emotional state (e.g., "anxious")

[0563] What it does: The sentiment engine uses text analysis algorithms to identify sentiment in text and determine emotional states.

[0564] Step 4:

[0565] The server combines the emotional information obtained from the emotion engine with the user's question text and sends a prompt to the generative AI.

[0566] Input: User's problem text, sentiment information

[0567] Output: Prompt sent to the generative AI

[0568] Specific operation: The server combines the emotion information with the user's question text to generate a prompt sentence like the following:

[0569] User's emotional state: Anxiety

[0570] User Problem: I've been seeing a lot of suspicious people around my house lately and it's making me feel uneasy.

[0571] Please provide a solution.

[0572] This prompt text is sent to the generative AI API.

[0573] Step 5:

[0574] Generative AI generates solutions based on prompts.

[0575] Input: prompt statement

[0576] Output: Solution text (e.g., "Installing security cameras and sharing information with neighbors would be effective.")

[0577] What it does: The generative AI analyzes the prompt and uses its internal model to generate an appropriate solution.

[0578] Step 6:

[0579] The server presents the generated solution to the user.

[0580] Input: Solution text

[0581] Output: The solution displayed on the user's phone

[0582] Specific operation: The server sends the solution text received from the generative AI to the user's smartphone, and the application displays the solution on the screen.

[0583] Step 7:

[0584] Users can provide feedback on the solutions provided.

[0585] Input: User feedback text (e.g., "This solution was helpful")

[0586] Output: The feedback text is sent to the system.

[0587] Specific action: The user uses a smartphone application to enter feedback on the solution and presses the submit button.

[0588] Step 8:

[0589] The server receives feedback from users and uses it to improve the generative AI's ability to generate solutions.

[0590] Input: User feedback text

[0591] Output: An improved generative AI model

[0592] Specific operation: The server receives the feedback text, stores it as learning data for the generative AI, and uses it to retrain the model.

[0593] 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.

[0594] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) 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.

[0595] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0596] 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.

[0597] [Second embodiment]

[0598] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0599] 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.

[0600] 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).

[0601] 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.

[0602] 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.

[0603] 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).

[0604] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0605] 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.

[0606] 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.

[0607] 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.

[0608] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0609] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0610] "Example 1"

[0611] In one embodiment of the present invention, a user provides a system with a personal problem as text input. This problem may be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend brass band activities." The system receives this input and uses generative AI to generate a solution. The generated solution may be specific advice, such as, "To improve communication with your section leader, it would be effective to clearly communicate the specific problem and work together to come up with a solution." This solution is presented to the user, who provides feedback on its effectiveness to the system. The system receives this feedback and improves the generative AI's ability to generate solutions.

[0612] "Example 2"

[0613] In one embodiment of the present invention, a user provides a system with a personal problem as text input. This problem may be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend brass band activities." The system receives this input and uses generative AI to generate a solution. The generated solution may be specific advice, such as, "To improve communication with your section leader, it would be effective to clearly communicate the specific problem and work together to come up with a solution." This solution is presented to the user, who provides feedback on its effectiveness to the system. The system receives this feedback and improves the generative AI's ability to generate solutions.

[0614] The processing flow of each embodiment will be described below.

[0615] "Example 1"

[0616] Step 1: The user provides the system with a text entry about their personal problem. This problem can be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend band activities."

[0617] Step 2: The system receives input from the user and uses generative AI to generate solutions. The generated solutions are specific advice such as, "To improve communication with the part-time leader, it is effective to clearly communicate the specific problems and work together to find solutions."

[0618] Step 3: The system presents the generated solution to the user, who then tries it out and provides feedback to the system on its effectiveness.

[0619] Step 4: The system receives feedback from the user and improves the generative AI's ability to generate solutions, thereby improving the accuracy of solutions to the same or similar problems.

[0620] Example 1

[0621] Next, a description will be given of Example 1 of Form 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."

[0622] Conventional systems have difficulty providing appropriate solutions to users' private problems. They also lack a mechanism for evaluating the effectiveness of the solutions provided and reflecting this in future solution generation. This has led to the issue of lowering users' satisfaction with the solutions they receive.

[0623] 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.

[0624] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for generating a prompt sentence suitable for the generative AI means, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, and means for reflecting the received feedback in the generative AI means. This makes it possible to provide an appropriate solution to the user's problem and improve the solution based on feedback on its effectiveness.

[0625] "User" means an individual who utilizes the System to enter their private problem and receive a solution.

[0626] "Private issues" refer to specific challenges or difficulties that users face personally.

[0627] "Generative AI means" refers to the function of artificial intelligence that generates appropriate solutions to private problems input by users.

[0628] A "prompt sentence" refers to an instruction sentence that conveys the content of the problem to a generative AI means.

[0629] "Solutions" refer to specific advice or suggestions that generative AI methods provide to users for their private problems.

[0630] "Presentation means" refers to the functionality for displaying the generated solution to the user.

[0631] "Feedback" refers to information provided by the user to the system regarding the effectiveness and impressions of the proposed solution.

[0632] "Means of reflection" refers to the function of incorporating feedback received from users into generative AI means and using them to generate solutions in the future.

[0633] This invention relates to a system that allows users to input their own private problems and generate solutions to those problems. The system receives the user's input, generates solutions using a generative AI model, and presents them to the user. It also receives feedback from the user and improves the performance of the generative AI model.

[0634] Hardware and software used

[0635] The system uses the following hardware and software:

[0636] Device: The device through which a user enters their private problem and receives a solution. Examples include computers, smartphones, and tablets.

[0637] Server: A computer system that receives user input, sends prompts to the generative AI model, and sends the generated solutions to the device.

[0638] Generative AI model: An artificial intelligence model that generates solutions to user problems. Examples include OpenAI's GPT-4.

[0639] Data processing and calculation

[0640] The user uses the device to input a private problem in text format. For example, they can input a specific problem such as, "I'm having trouble communicating with the section leader during my weekend brass band activities." The device then sends this input to the server.

[0641] The server generates a prompt to pass the received text input to the generative AI model. For example, it generates a prompt such as, "The user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to solve this problem."

[0642] The generative AI model generates solutions based on prompts, such as advice like, "To improve communication with the part-time leader, it would be effective to clearly communicate the specific problems and work together to find solutions."

[0643] The generated solution is sent from the server to the terminal and presented to the user. The user checks the presented solution and provides feedback on its effectiveness to the server via the terminal.

[0644] The server receives feedback from users and uses it to improve the generative AI model's ability to generate solutions, allowing the system to continuously learn and provide more effective solutions.

[0645] Specific examples

[0646] For example, a user enters the following problem:

[0647] "I'm having trouble communicating with the section leader during weekend band activities."

[0648] Example prompts for generative AI models:

[0649] "A user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to resolve this issue."

[0650] An example of a generated solution:

[0651] "In order to improve communication with section leaders, it is effective to clearly communicate specific problems and work together to find solutions. For example, you could set up regular meetings to provide an opportunity for frank discussion of each other's opinions."

[0652] In this way, the system provides solutions to users' problems and improves the performance of the generative AI model based on user feedback.

[0653] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0654] Step 1:

[0655] A user uses a terminal to enter a private problem.

[0656] Specifically, the user inputs a problem in text format into the terminal interface, such as "I'm having trouble communicating with the section leader during my weekend brass band activities."

[0657] Input: User's private information (text data)

[0658] Output: Text data entered into the terminal

[0659] Step 2:

[0660] The terminal transmits the input text data to the server.

[0661] Specifically, the terminal encrypts the text data entered by the user and transmits it to the server.

[0662] Input: Text data entered into the terminal

[0663] Output: Encrypted text data sent to the server

[0664] Step 3:

[0665] The server analyzes the text data it receives and generates a prompt sentence suitable for the generative AI model.

[0666] Specifically, the server analyzes the text data and generates a prompt that reads, "The user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to solve this problem."

[0667] Input: Encrypted text data sent to the server

[0668] Output: A prompt suitable for a generative AI model

[0669] Step 4:

[0670] The server sends a prompt to the generative AI model.

[0671] Specifically, the server sends the generated prompt sentence to the generative AI model.

[0672] Input: A prompt suitable for a generative AI model

[0673] Output: The prompt sent to the generative AI model

[0674] Step 5:

[0675] A generative AI model generates a solution based on the prompt.

[0676] Specifically, the generative AI model analyzes the prompt and generates a solution such as, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and think of solutions together."

[0677] Input: A prompt sent to the generative AI model

[0678] Output: Generated solution (text data)

[0679] Step 6:

[0680] The server sends the generated solution to the terminal.

[0681] Specifically, the server encrypts the solution received from the generative AI model and sends it to the device.

[0682] Input: Generated solution (text data)

[0683] Output: The encrypted solution sent to the terminal.

[0684] Step 7:

[0685] The terminal presents a solution to the user.

[0686] Specifically, the device decrypts the solution received from the server and displays it to the user, who then checks the solution on the screen.

[0687] Input: The encrypted solution sent to the terminal

[0688] Output: The solution presented to the user

[0689] Step 8:

[0690] The user provides feedback on the effectiveness of the proposed solution.

[0691] Specifically, the user checks the presented solution and inputs feedback such as "This advice was very helpful" into the terminal interface.

[0692] Input: User feedback (text data)

[0693] Output: Feedback typed into the terminal

[0694] Step 9:

[0695] The device sends the feedback to the server.

[0696] Specifically, the terminal encrypts the feedback input by the user and transmits it to the server.

[0697] Input: Feedback entered into the device

[0698] Output: Encrypted feedback sent to the server

[0699] Step 10:

[0700] The server reflects the feedback in the generative AI model.

[0701] Specifically, the server incorporates the received feedback into the generative AI model and uses it to generate solutions from the next time onwards.

[0702] Input: Encrypted feedback sent to the server

[0703] Output: Feedback reflected in the generative AI model

[0704] (Application example 1)

[0705] Next, a description will be given of Application Example 1 of Form 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."

[0706] Conventional generative AI systems focused on providing solutions to users' private problems, but lacked the ability to provide solutions to specific security issues. Furthermore, they lacked mechanisms for improving solutions based on user feedback. This made it difficult for users to receive prompt and accurate advice on security issues.

[0707] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes generative AI means that receives a user's private problem as input and generates a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, means for receiving a security problem as input and generating a solution to the problem, and means for presenting the generated solution to the user. This enables the user to receive prompt and accurate advice on specific security problems.

[0708] "User" means any person or entity that uses the System to enter private or security-related issues.

[0709] "Private issues" are problems or challenges that users face personally, such as issues related to relationships or daily life.

[0710] "Generative AI" is an artificial intelligence system that generates solutions to problems input by users.

[0711] A "solution" is a specific piece of advice or suggestion that a generative AI provides to a user about a problem.

[0712] "Feedback" refers to the evaluation or opinion that a user gives of the solution provided by the generative AI.

[0713] "Security issues" are specific safety and security issues faced by users.

[0714] "Presentation means" refers to a method or device for displaying the solution generated by generative AI to the user.

[0715] "Means for receiving" refers to a method or device by which the system receives feedback from the user.

[0716] The system for implementing this invention is a system that uses generative AI to solve problems related to users' privacy and security. Specific embodiments of this system are described below.

[0717] System Configuration

[0718] The system mainly consists of the following components:

[0719] 1. User device: A device such as a smartphone or computer that users use to enter questions.

[0720] 2. Server: A central system for hosting the generative AI and processing input from users.

[0721] 3. Generative AI: An artificial intelligence model that generates solutions to user problems, such as OpenAI's GPT-3.

[0722] 4. Database: A storage system for saving user input and feedback.

[0723] Program processing

[0724] The server processes the data as follows:

[0725] 1. Receiving user input: Receive private or security issues in text format sent from the user's device.

[0726] 2. Generating a solution using generative AI: The received problem is input into a generative AI, which generates a solution. OpenAI's GPT-3 is used as the generative AI.

[0727] 3. Presenting the solution: The generated solution is sent to the user's terminal and presented to the user.

[0728] 4. Receiving feedback: Receiving feedback from users and storing it in a database.

[0729] 5. Improve the AI ​​model: Use the feedback received to improve the generative AI's ability to generate solutions.

[0730] Hardware and software used

[0731] Hardware: smartphones, PCs, servers

[0732] Software: Python, OpenAI API, database management system (e.g., MySQL)

[0733] Specific examples

[0734] If a user types in "I've seen suspicious people around my house recently," the server sends this input to a generative AI, which then generates a solution, such as "Installing security cameras and sharing information with neighbors would be effective," and presents it to the user.

[0735] Prompt Sentence Examples

[0736] User security issue: I've recently seen some suspicious people around my house.

[0737] Please provide a solution.

[0738] In this way, users can get fast and accurate advice on specific security issues.

[0739] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0740] Step 1:

[0741] The user terminal receives input from the user. Specifically, the user inputs private and security-related issues in text format using a smartphone or PC. The input text data is sent to the server.

[0742] Input: Text data entered by the user (e.g., "I've been seeing some suspicious people around my house lately.")

[0743] Output: Text data sent to the server

[0744] Step 2:

[0745] The server receives the text data sent from the user's device and generates a prompt sentence to be input to the generative AI. The prompt sentence is a concrete description of the user's problem.

[0746] Input: Text data sent by the user

[0747] Output: A prompt to be input to the generative AI (e.g., "User's security problem: I've been seeing suspicious people around my house recently. Please provide a solution.")

[0748] Step 3:

[0749] The server sends a prompt to a generative AI (e.g., OpenAI's GPT-3) to generate a solution. The generative AI generates an appropriate solution in text format based on the prompt.

[0750] Input: Prompt sentence to input to the generative AI

[0751] Output: The solution generated by the generative AI (e.g., "Installing security cameras and sharing information with neighbors would be effective.")

[0752] Step 4:

[0753] The server sends the generated solution to the user's device and presents it to the user, who can then check the solution on their smartphone or computer screen.

[0754] Input: A solution generated by a generative AI

[0755] Output: The solution sent to the user's device

[0756] Step 5:

[0757] The user terminal receives feedback from the user, who inputs his / her evaluation and opinion on the provided solution in text format and sends it to the server.

[0758] Input: User-entered feedback (e.g., "I think installing security cameras is a good idea.")

[0759] Output: Feedback sent to the server

[0760] Step 6:

[0761] The server receives feedback from users and stores it in a database, which is used to improve the generative AI's ability to generate solutions.

[0762] Input: Feedback submitted by the user

[0763] Output: Feedback stored in a database

[0764] Step 7:

[0765] The server retrains the generative AI model based on the saved feedback, improving its ability to generate solutions, which will result in more accurate solutions in future.

[0766] Input: Feedback stored in the database

[0767] Output: Improved generative AI model

[0768] By following these steps, users can get fast and accurate advice on specific security issues.

[0769] Example 2

[0770] Next, a description will be given of Example 2 of Form 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."

[0771] Conventional systems have difficulty providing appropriate solutions to users' private problems. Furthermore, they lack a mechanism for evaluating the effectiveness of the solutions provided and reflecting this in future solution generation, making it difficult to increase user satisfaction. Furthermore, they lack the ability to generate appropriate prompts for the user's specific problem, which can result in a decline in the quality of the solutions generated.

[0772] 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.

[0773] In this invention, the server includes a generative artificial intelligence that receives a user's private problem as input and generates a solution to the problem, a means for generating a prompt sentence suitable for the generative artificial intelligence, a means for presenting the solution generated by the generative artificial intelligence to the user, a means for receiving feedback from the user, and a means for improving the solution generation ability of the generative artificial intelligence based on the user's feedback. This makes it possible to provide an appropriate solution to the user's specific problem, evaluate its effectiveness, and reflect it in future solution generation.

[0774] "User" means an individual who utilizes the System to enter their private problem and receive a solution.

[0775] "Private issues" refers to specific problems or concerns that the user has personally.

[0776] "Generative AI" refers to artificial intelligence techniques that generate solutions based on user input.

[0777] A "prompt sentence" refers to an instruction sentence that is input to a generative artificial intelligence to generate an appropriate solution.

[0778] "Solutions" refer to the specific advice or suggestions that generative artificial intelligence provides to users about their problems.

[0779] "Feedback" refers to information that a user reports to the system after trying out a proposed solution, including its effectiveness and impressions.

[0780] "Server" refers to a computer system that receives user input data, generates solutions using generative artificial intelligence, and presents them to the user.

[0781] "Device" refers to the device through which a User enters their problem, receives a solution, and provides feedback.

[0782] The present invention is a system in which a user provides a text input of their private problem to the system, and a solution to the problem is generated. A specific embodiment of this system will be described below.

[0783] Hardware and software used

[0784] Hardware

[0785] Server: A high-performance computer system that runs generative artificial intelligence and processes user input data.

[0786] Device: The device that a user uses to enter their problem, receive a solution, or provide feedback. This could be a smartphone, tablet, or computer.

[0787] software

[0788] Generative artificial intelligence: For example, using advanced natural language processing techniques such as OpenAI's GPT-4.

[0789] Encryption protocol: The SSL / TLS protocol is used to securely transmit user input data to the server.

[0790] Data processing and calculation

[0791] User problem input

[0792] Users enter their personal problems into a text box on the device, for example, "I'm having trouble communicating with my section leader during my weekend band activities."

[0793] Sending input data

[0794] The terminal encrypts the text data entered by the user using the SSL / TLS protocol and sends it to the server.

[0795] Problem analysis and prompt generation

[0796] The server analyzes the received text data using natural language processing (NLP) technology and generates a prompt suitable for generative artificial intelligence. For example, if the user input is "I'm having trouble communicating with the section leader during weekend band activities," the prompt would be "The user is having trouble communicating with the section leader during weekend band activities. Please clearly explain the specific problem and provide advice so we can work together to find a solution."

[0797] Solution Generation

[0798] The server inputs the prompt into the generative AI, which then generates a solution. The generative AI then generates appropriate advice based on the prompt. For example, the generated advice might be, "To improve communication with the part leader, it is effective to clearly communicate the specific problems and work together to come up with solutions. It would be a good idea to have a private discussion with the part leader before the next rehearsal, share the specific problems, and set aside time to think about solutions together."

[0799] Proposing a solution

[0800] The server sends the generated solution to the terminal, which displays it to the user, who can then check and try out the solution.

[0801] Collecting feedback

[0802] After trying out the proposed solutions, users can enter specific feedback into the device about their effectiveness, such as, "The discussion with the part leader went well, and communication has improved."

[0803] Model Improvements

[0804] The device sends user feedback to the server, which passes it on to the generative AI and uses it to improve the model's ability to generate solutions, resulting in more effective solutions in future.

[0805] Specific examples

[0806] Example user input

[0807] "I'm having trouble communicating with the section leader during weekend band activities."

[0808] Example prompts for generative AI models

[0809] "A user is having trouble communicating with the section leader during their weekend band activities. Please clearly explain the specific problem and provide advice on how we can work together to find a solution."

[0810] Example of a generated solution

[0811] "To improve communication with section leaders, it is effective to clearly communicate specific problems and work together to find solutions. It is a good idea to have a private discussion with section leaders before the next rehearsal, share specific problems, and set aside time to think about solutions together."

[0812] This way, users receive concrete advice and can try it out for themselves, and feedback helps the system improve and provide more effective solutions.

[0813] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0814] Step 1:

[0815] The user enters their personal problem into the text box on the device. For example, they might enter, "I'm having trouble communicating with my section leader during my weekend brass band activities." The input data is in text format, and the user can proceed to the next step by clicking the "Submit" button.

[0816] Step 2:

[0817] The terminal encrypts the text data entered by the user using the SSL / TLS protocol and sends it to the server. The input data is encrypted text data and sent securely to the server. The server decrypts the received data and proceeds to the next step.

[0818] Step 3:

[0819] The server analyzes the received text data using natural language processing (NLP) technology. The input data is text data containing the user's problem, and the content of the problem is extracted as a result of the analysis. Based on this analysis result, the server generates a prompt suitable for generative AI. For example, a generated prompt might read, "The user is having trouble communicating with the section leader during weekend brass band activities. Please clearly explain the specific problem and provide advice so we can work together to find a solution."

[0820] Step 4:

[0821] The server inputs a prompt into the generative AI and generates a solution. The input data is the prompt, and the generative AI generates appropriate advice based on this. For example, a solution might be generated that reads, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and work together to come up with solutions. It would be a good idea to have a private discussion with the part leader before the next rehearsal, share the specific problems, and set aside time to think about solutions together."

[0822] Step 5:

[0823] The server sends the generated solution to the terminal, and the input data is the generated solution, which the terminal displays to the user, who can then check the presented solution and try it out.

[0824] Step 6:

[0825] After trying out the proposed solution, the user enters feedback about its effectiveness into the device. For example, specific feedback such as "The discussion with the part leader went well, and communication has improved." The input data is feedback information, and the user can proceed to the next step by clicking the "Submit" button.

[0826] Step 7:

[0827] The device sends the user's feedback to the server. The input data is feedback information, which the server receives and analyzes. The server then passes the feedback information to the generative AI and uses it to improve the model's ability to generate solutions, making future solutions more effective.

[0828] (Application example 2)

[0829] Next, a description will be given of Application Example 2 of Form 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."

[0830] With conventional security services, it was difficult to quickly provide appropriate solutions to the specific security problems faced by users. Furthermore, there was a lack of a mechanism for evaluating the effectiveness of the solutions provided and for continuous improvement, making it difficult to improve users' security awareness and the quality of countermeasures. This led to the issue of users being unable to use the digital environment with peace of mind.

[0831] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0832] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving user feedback, means for receiving a security problem as input and generating a solution to the problem, means for presenting the generated solution to the user, and means for improving the solution generation ability of the generative AI based on user feedback. This makes it possible to provide quick and appropriate solutions to specific security problems faced by users and to evaluate their effectiveness and continuously improve them.

[0833] "User" means any person or entity that uses the System to enter private or security-related issues.

[0834] "Private issues" are specific problems or challenges that users face personally.

[0835] "Generative AI" is a type of artificial intelligence that generates solutions to problems input by the user.

[0836] A "solution" is a specific piece of advice or countermeasure that the generative AI provides to the user for their problem.

[0837] "Feedback" is information about the results and effectiveness of a user's attempt at a provided solution.

[0838] "Security issues" are specific issues users face regarding safety and protection in the digital environment.

[0839] "The solution generation ability of generative AI" refers to the ability of generative AI to generate appropriate solutions to users' problems.

[0840] "Presentation means" refers to a method or device for displaying or notifying the user of the solution generated by the generative AI.

[0841] "Means for receiving" refers to a method or device by which the system obtains feedback from the user.

[0842] "Means for improvement" are methods or devices for improving the solution-generating capabilities of generative AI based on user feedback.

[0843] As an embodiment of this invention, we will explain how to install a security advisor AI system on a smartphone. In this system, a user inputs a security problem, and a generative AI generates a solution and presents it to the user. Furthermore, feedback from the user is received, and the generative AI's ability to generate a solution is improved.

[0844] Hardware and software used

[0845] Hardware: Smartphone

[0846] Software: Python, OpenAI API

[0847] System configuration

[0848] 1. Obtaining user input: The user inputs text into a smartphone application. For example, they input a specific problem, such as, "My home Wi-Fi has been unstable recently, and I'm worried about security."

[0849] 2. Prompt generation: Based on the user's input, a prompt is generated to be passed to the generative AI. For example, it could be something like, "User's security problem: My home Wi-Fi has been unstable recently, so I'm worried about security. Please provide a solution."

[0850] 3. AI solution generation: Using OpenAI's API, a generative AI (e.g., GPT-3) generates a solution. The generated solution is specific advice such as, "We recommend updating your Wi-Fi router's firmware and setting a strong password."

[0851] 4. Present the solution: The generated solution is presented to the user and displayed on the smartphone application.

[0852] 5. Get feedback: Users try the solution and provide feedback on its effectiveness, such as, "My Wi-Fi is now more stable and secure."

[0853] 6. Improving the Generative AI: Based on user feedback, we will improve the generative AI's ability to generate solutions, which will result in better and more effective solutions in future.

[0854] Specific examples

[0855] User input: "My home Wi-Fi has been unstable lately and I'm worried about security."

[0856] Example prompt: "User security issue: My home Wi-Fi has been unstable lately and I'm worried about security. Please provide a solution."

[0857] AI advice: "We recommend updating your Wi-Fi router's firmware and setting a strong password."

[0858] User feedback: "Wi-Fi is now more stable and secure."

[0859] In this way, it is possible to provide quick and appropriate solutions to specific security problems faced by users, evaluate their effectiveness and continuously improve them.

[0860] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0861] Step 1:

[0862] The user launches an application on their smartphone and enters a security problem via text.

[0863] Input: A specific security issue entered by the user (e.g., "My home Wi-Fi has been unstable lately, and I'm worried about security.")

[0864] Output: The text entered by the user

[0865] Specific behavior: The user enters a problem into the application's text input field and presses the submit button.

[0866] Step 2:

[0867] The device receives user input and generates a prompt sentence to be passed to the generative AI.

[0868] Input: User-entered text

[0869] Output: Generated prompt (e.g. "User's security problem: My home Wi-Fi has been unstable recently and I'm worried about security. Please provide a solution.")

[0870] What it does: The application formats the user's input text and generates a prompt suitable for generative AI.

[0871] Step 3:

[0872] The server calls the generative AI and generates a solution using the generated prompt sentence as input.

[0873] Input: Generated prompt statement

[0874] Output: The solution generated by the generative AI (e.g., "It is recommended that you update your Wi-Fi router's firmware and set a strong password.")

[0875] Specific operation: The server uses the OpenAI API to send a prompt to a generative AI (e.g., GPT-3) and obtain a solution.

[0876] Step 4:

[0877] The terminal presents the generated solution to the user.

[0878] Input: A solution generated by a generative AI

[0879] Output: The solution presented to the user

[0880] What happens: The application displays the solution on the user's screen.

[0881] Step 5:

[0882] The user tries the proposed solution and inputs feedback on its effectiveness.

[0883] Input: Feedback about the effectiveness of the solution the user tried (e.g., "My Wi-Fi is now more stable and secure.")

[0884] Output: User feedback text

[0885] Specific behavior: The user enters the effect in the application's feedback input field and presses the submit button.

[0886] Step 6:

[0887] The server receives feedback from users and improves the generative AI's ability to generate solutions.

[0888] Input: User feedback text

[0889] Output: Improved solution generation capabilities of generative AI

[0890] Specific operation: The server analyzes the feedback data, incorporates it as learning data for the generative AI, and reflects it in generating solutions from the next time onwards.

[0891] 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.

[0892] "Example 1"

[0893] As one embodiment of the present invention, a system incorporating an emotion engine is provided. The system includes a generative AI that receives a user's private problem as input and generates a solution to the problem, a means for presenting the solution generated by the generative AI to the user, and a means for receiving feedback from the user. The system further includes an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's emotional state and provides the results to the generative AI. The generative AI uses this emotional information to generate a more appropriate solution. For example, if a user has a problem related to weekend band activities and feels strongly about the problem, the emotion engine recognizes the strong emotion, and the generative AI uses that information to generate a more specific and appropriate solution.

[0894] "Example 2"

[0895] As one embodiment of the present invention, a system incorporating an emotion engine is provided. The system includes a generative AI that receives a user's private problem as input and generates a solution to the problem, a means for presenting the solution generated by the generative AI to the user, and a means for receiving feedback from the user. The system further includes an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's emotional state and provides the results to the generative AI. The generative AI uses this emotional information to generate a more appropriate solution. For example, if a user has a problem related to weekend band activities and feels strongly about the problem, the emotion engine recognizes the strong emotion, and the generative AI uses that information to generate a more specific and appropriate solution.

[0896] The processing flow of each embodiment will be described below.

[0897] "Example 1"

[0898] Step 1: The user provides the system with a private concern as text input. Step 2: The emotion engine analyzes the user's emotional state based on information derived from the user's text input and, if possible, other inputs such as the user's voice and facial expressions.

[0899] Step 3: The emotion engine provides the analysis results to the generative AI, which uses this information as reference when generating solutions.

[0900] Step 4: The generative AI generates a solution to the user's problem. This solution is generated based on the problem information provided by the user and the emotional information provided by the emotion engine.

[0901] Step 5: The system presents the generated solution to the user.

[0902] Step 6: The user provides feedback regarding the usefulness and appropriateness of the proposed solution.

[0903] Step 7: The system receives user feedback and uses it to improve the generative AI's ability to generate solutions.

[0904] Example 1

[0905] Next, a description will be given of Example 1 of Form 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."

[0906] Conventional systems were unable to consider the user's emotional state when providing solutions to a user's private problems, making it difficult to provide appropriate solutions. Furthermore, there was a lack of a way to effectively utilize user feedback to improve the generative AI's ability to generate solutions. This resulted in problems such as a decrease in the accuracy and appropriateness of solutions for users.

[0907] 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.

[0908] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, emotion engine means for analyzing the user's emotional state, means for providing the emotion engine's analysis results to the generative AI, and means for analyzing the user's feedback and improving the generative AI's ability to generate solutions. This makes it possible to provide appropriate solutions that take the user's emotional state into consideration and to continuously improve the generative AI by utilizing the feedback.

[0909] "User" means an individual who utilizes the System to enter their private problems and obtain solutions.

[0910] "Private issues" refers to specific problems or concerns that the user has personally.

[0911] "Generative AI" refers to artificial intelligence models that generate solutions based on user input.

[0912] "Solutions" refer to the specific advice or suggestions that generative AI provides to users about their problems.

[0913] "Means for presentation" refers to the method or device for displaying the solution generated by generative AI to the user.

[0914] "Feedback" refers to information that users return to the system about the effectiveness and impressions of the proposed solutions.

[0915] An "emotion engine" refers to software or hardware that analyzes a user's emotional state and provides the results to generative AI.

[0916] "Analysis results" refers to the data obtained as a result of the emotion engine analyzing the user's emotional state.

[0917] "Means for improvement" refers to methods and devices for analyzing user feedback and improving the generative AI's ability to generate solutions.

[0918] This invention is a system that allows users to input their private problems in text format and generates solutions to those problems. The system uses a generative AI model to generate solutions and presents them to the user. It also receives feedback from the user to improve the generative AI model's ability to generate solutions. Furthermore, it uses an emotion engine to analyze the user's emotional state and provides the results to the generative AI model to generate more appropriate solutions.

[0919] Hardware and software used

[0920] Hardware

[0921] Device: The device through which a user enters their problem and receives a solution (e.g., smartphone, tablet, computer).

[0922] Server: A computer system for running generative AI models and emotion engines

[0923] software

[0924] Generative AI models: Artificial intelligence models that generate solutions to user problems (e.g., GPT-4)

[0925] Emotion Engine: Software for analyzing the user's emotional state

[0926] Feedback Analysis System: Software for analyzing user feedback and improving generative AI models

[0927] Data processing and calculation

[0928] User problem input

[0929] Users use the device to enter their personal problems in text format, for example, "I'm having trouble communicating with my section leader during my weekend band activities."

[0930] Receiving and analyzing the problem

[0931] The device sends input from the user to the server. The server receives this input and generates a prompt to pass to the generative AI model. For example, it generates a prompt such as, "The user is having trouble communicating with the section leader during weekend band activities. How can we improve this?"

[0932] Solution Generation

[0933] The server inputs the prompt into a generative AI model (e.g., GPT-4) and generates a solution. The generative AI model generates specific advice based on the prompt. For example, it generates a solution such as, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and work together to find a solution."

[0934] Proposing a solution

[0935] The server sends the generated solution to the terminal, which displays the received solution to the user, who then checks the presented solution and decides whether to execute it.

[0936] Receiving Feedback

[0937] The user inputs feedback into the device about the effectiveness of the proposed solution. For example, they can input something like, "As a result of implementing the advice, my communication with the part leader improved." The device then sends this feedback to the server.

[0938] Feedback analysis and learning

[0939] The server receives and analyzes feedback from users. The analysis results are used as learning data to improve the solution generation capabilities of the generative AI model. This will result in more accurate solutions being generated in the future.

[0940] Use of emotion engine

[0941] When a user inputs a problem, the emotion engine analyzes the user's emotional state. For example, if the user has strong emotions, it provides that information to the generative AI model, which then uses this emotional information to generate a more appropriate solution. For example, if the user is feeling very stressed, the emotion engine provides that information to the generative AI model, which then takes that information into account to generate a more empathetic solution.

[0942] Examples of specific examples and prompts

[0943] Specific examples

[0944] If a user enters, "I'm having trouble communicating with the section leader during my weekend band activities," the system will process the following:

[0945] 1. The user enters the problem.

[0946] 2. The device sends the input to the server.

[0947] 3. The server passes the problem to a generative AI model (e.g., GPT-4).

[0948] 4. The generative AI model generates a solution.

[0949] 5. The server sends the solution to the device.

[0950] 6. The device presents a solution to the user.

[0951] 7. The user enters feedback.

[0952] 8. The device sends the feedback to the server.

[0953] 9. The server analyzes the feedback and improves the generative AI model.

[0954] Prompt Sentence Examples

[0955] "During the weekend brass band activities, I'm having trouble communicating with the section leaders. How can I improve this?"

[0956] By inputting this prompt into a generative AI model, a specific solution is generated.

[0957] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0958] Step 1:

[0959] The user uses the device to input their personal problems in text format. For example, they might input, "I'm having trouble communicating with the section leader during my weekend brass band activities." The input text data is saved in an input field on the device.

[0960] Step 2:

[0961] The terminal sends user input to the server. Specifically, it sends text data to the server using an HTTP request. The server receives this request and prepares to parse the text data.

[0962] Step 3:

[0963] The server analyzes the received text data and generates a prompt to be passed to the generative AI model. For example, it generates a prompt such as, "The user is having trouble communicating with the section leader during weekend band activities. How can we improve this?" This prompt is then input into the generative AI model.

[0964] Step 4:

[0965] The server inputs the prompt into a generative AI model (e.g., GPT-4) and generates a solution. The generative AI model generates specific advice based on the prompt. For example, it generates a solution such as, "To improve communication with the part leader, it is effective to clearly communicate the specific problems and think about solutions together." This solution is stored on the server.

[0966] Step 5:

[0967] The server sends the generated solution to the terminal as an HTTP response. The terminal displays the received solution to the user. The user checks the presented solution and decides whether to execute it.

[0968] Step 6:

[0969] The user enters feedback into the device about the effectiveness of the proposed solution. For example, they might say, "After implementing the advice, my communication with the part leader improved." The entered feedback is saved in an input field on the device.

[0970] Step 7:

[0971] The device sends user feedback to the server. Specifically, it sends the feedback data to the server using an HTTP request. The server receives this request and prepares to analyze the feedback data.

[0972] Step 8:

[0973] The server analyzes user feedback and uses it as learning data to improve the generative AI model's ability to generate solutions. Based on the analysis results, the generative AI model is retrained to generate more accurate solutions in the future.

[0974] Step 9:

[0975] When a user inputs a problem, the emotion engine analyzes the user's emotional state. For example, if the user has strong emotions, it provides that information to the generative AI model, which then uses this emotional information to generate a more appropriate solution. For example, if the user is feeling very stressed, the emotion engine provides that information to the generative AI model, which then takes that information into account to generate a more empathetic solution.

[0976] (Application example 1)

[0977] Next, a description will be given of Application Example 1 of Form 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."

[0978] Conventional security services have difficulty providing appropriate solutions to specific problems faced by users. Furthermore, they are unable to provide solutions that take into account the user's emotional state, which can lead to lower user satisfaction. Furthermore, they lack a mechanism for effectively utilizing user feedback to improve solutions.

[0979] 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.

[0980] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, emotion engine means for analyzing the user's emotional state, means for providing emotion information obtained by the emotion engine to the generative AI, and generative AI means for generating a solution based on the emotion information. This makes it possible to provide an appropriate solution that takes the user's emotional state into consideration and to improve the solution by utilizing feedback from the user.

[0981] "User's private issues" refer to the specific challenges and difficulties that individuals face in their daily lives and work.

[0982] "Generative AI" refers to artificial intelligence that generates solutions to problems provided by users.

[0983] "Generating a solution" means providing appropriate solutions or advice to the user's problem.

[0984] "User presentation" refers to the interface or method for displaying the generated solution to the user.

[0985] "Feedback methods" refers to the interface and methods for collecting user ratings and opinions.

[0986] An "emotion engine" is a system or software that analyzes a user's emotional state and provides the results.

[0987] "Emotional Information" means data regarding a user's emotional state analyzed by the Emotion Engine.

[0988] "Security issues" refer to specific security challenges faced by users, such as online fraud and personal information leaks.

[0989] "Improving the solution" means improving the quality of the solution provided by the generative AI based on feedback from users.

[0990] As an embodiment of the present invention, a security advisor system is constructed. The system includes a generative AI that receives a user's private problem as input and generates a solution to the problem, a means for presenting the solution generated by the generative AI to the user, a means for receiving feedback from the user, an emotion engine that analyzes the user's emotional state, a means for providing the generative AI with emotion information obtained by the emotion engine, and the generative AI that generates a solution based on the emotion information.

[0991] Hardware and software used

[0992] Hardware: Smartphone, PC

[0993] Software: Python, OpenAI API, EmotionEngine library

[0994] Data processing and calculation

[0995] 1. Getting user input:

[0996] The user provides a text input for a security problem, such as "I've been getting a lot of phishing emails lately."

[0997] 2. Emotional state analysis:

[0998] Analyze the emotional state of the user from their input using an emotion engine. Use the EmotionEngine library to detect the user's emotional state (e.g., "anxiety").

[0999] 3. Prompt generation:

[1000] Generate prompts that include emotional information and the user's problem. For example, generate prompts like the following:

[1001] User's emotional state: Anxiety

[1002] User Problem: I've been getting a lot of phishing emails lately.

[1003] Please provide a solution.

[1004] 4. Solution Generation:

[1005] Using the OpenAI API, generative AI generates solutions, such as "specific methods for identifying phishing emails."

[1006] 5. Propose a solution:

[1007] The generated solution is presented to the user, who can check it on their smartphone or PC screen.

[1008] 6. Getting feedback:

[1009] Get and store user feedback. Users rate whether the solution was helpful and provide that rating to the system.

[1010] Specific examples

[1011] If a user types, "I'm having trouble with the number of phishing emails I've received lately," the emotion engine will detect "anxiety," and the generative AI will provide "specific methods for identifying phishing emails." An example of a prompt sentence is as follows:

[1012] User's emotional state: Anxiety

[1013] User Problem: I've been getting a lot of phishing emails lately.

[1014] Please provide a solution.

[1015] In this way, it is possible to provide appropriate solutions that take into account the user's emotional state and to use user feedback to improve the solutions.

[1016] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1017] Step 1:

[1018] The user provides a security problem as text input using a terminal. For example, the user might type, "I've been getting a lot of phishing emails lately." This input is sent to the system.

[1019] Step 2:

[1020] The server receives input from the user and sends it to the emotion engine. The emotion engine uses the EmotionEngine library to analyze the emotional state from the user's input. For example, it detects the emotional state "anxiety." This emotional information is returned to the server.

[1021] Step 3:

[1022] The server generates a prompt based on the emotional information and the user's problem. For example, it generates the following prompt:

[1023] User's emotional state: Anxiety

[1024] User Problem: I've been getting a lot of phishing emails lately.

[1025] Please provide a solution.

[1026] This prompt is sent to the generative AI.

[1027] Step 4:

[1028] The server uses generative AI to generate a solution based on the prompt. Using the OpenAI API, the generative AI generates a solution. For example, a solution such as "specific methods for identifying phishing emails" is generated. This solution is then returned to the server.

[1029] Step 5:

[1030] The server presents the generated solution to the user, who can then check the solution on the device screen. For example, the solution may show "specific methods for identifying phishing emails."

[1031] Step 6:

[1032] The user enters feedback on the proposed solution, for example by answering "yes" or "no" to the question "Did this solution help you?" This feedback is sent to the server.

[1033] Step 7:

[1034] The server receives and stores feedback from users. The feedback is used to improve the generative AI. For example, it is stored in a feedback database and referenced the next time a solution is generated.

[1035] In this way, it is possible to provide an appropriate solution that takes into account the user's emotional state and to use feedback from the user to improve the solution.

[1036] Example 2

[1037] Next, a description will be given of Example 2 of Form 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."

[1038] Conventional systems were unable to take the user's emotional state into account when generating solutions to the user's private problems, making it difficult to provide appropriate solutions. Furthermore, there was a lack of a way to effectively utilize user feedback to improve the performance of generative AI. This resulted in a decrease in user satisfaction with the solution.

[1039] 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.

[1040] In this invention, the server includes a generative AI that receives a user's private problem as input and generates a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, an emotion engine that analyzes the user's emotional state, means for providing the emotion engine's analysis results to the generative AI, means for the generative AI to generate a solution using the user's emotional information, and means for improving the generative AI's algorithm based on user feedback. This makes it possible to provide appropriate solutions that take the user's emotional state into consideration and to improve the performance of the generative AI based on feedback.

[1041] "User" means an individual who utilizes the System to enter their private problems and obtain solutions.

[1042] "Private issues" refers to specific problems or concerns that the user has personally.

[1043] "Generative AI" refers to artificial intelligence models that generate solutions based on user input.

[1044] "Solutions" refer to the specific advice or suggestions that generative AI provides to users about their problems.

[1045] "Emotion engine" refers to a system component that analyzes the user's emotional state and provides the results to generative AI.

[1046] "Feedback" refers to information that a user provides to the system about the effectiveness and impressions of the proposed solution.

[1047] An "algorithm" refers to the set of computational steps or rules that generative AI uses to generate solutions.

[1048] The "server" refers to a central processing unit that receives user input, works with generative AI and emotion engines to generate solutions, and presents them to the user.

[1049] "Terminal" means the device through which a User enters a problem and receives a solution.

[1050] This invention is a system that allows users to provide their private problems as text input to the system, which then generates solutions to those problems. The system combines generative AI and an emotion engine to provide solutions that take into account the user's emotional state.

[1051] Users use devices such as smartphones or PCs to input personal problems in text format. For example, they can input a specific problem such as, "I'm having trouble communicating with my section leader during my weekend brass band activities."

[1052] The device sends the problem entered by the user to the server. The server passes the received text to a generative AI, which generates a solution. OpenAI's GPT-4 can be used as the generative AI. The generative AI generates a solution to the user's problem and provides specific advice, such as, "To improve communication with your part-time leader, it is effective to clearly communicate the specific problem and work together to find a solution."

[1053] The server sends the generated solution to the device, which then presents it to the user. The user reviews the presented solution and inputs its effectiveness as feedback into the device. The device then sends feedback from the user to the server. The server receives this feedback and uses it to improve the solution-generating ability of the generative AI.

[1054] Additionally, the emotion engine analyzes the user's emotional state. For example, if the user has strong emotions about a problem, the emotion engine provides that information to the generative AI, which then uses this emotional information to generate a more appropriate solution.

[1055] As a concrete example, if a user inputs the problem, "I'm having trouble communicating with the section leader during my weekend brass band activities," the following prompt sentence will be input to the generative AI.

[1056] Example prompt sentence:

[1057] A user is having trouble communicating with the section leader during weekend band activities. Please provide a concrete solution to this problem.

[1058] The generative AI generates a solution based on this prompt and provides advice such as the following:

[1059] To improve communication with your part-time leader, it is effective to clearly communicate specific problems and work together to find solutions. It is also recommended to hold regular meetings to create a forum for exchanging opinions with each other.

[1060] This solution is presented to the user, who then provides feedback on its effectiveness to the system, which then uses this feedback to improve the performance of the generative AI.

[1061] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1062] Step 1:

[1063] The user enters the problem.

[1064] Users enter their problem into a text input field displayed on the screen of their smartphone or computer. For example, they might enter, "I'm having trouble communicating with the section leader during my weekend brass band activities." The input data is in text format.

[1065] Step 2:

[1066] The device sends input to the server.

[1067] The terminal sends the text data entered by the user to the server as an HTTP request. When sending, the data is converted to JSON format. The input is the user's text data, and the output is the JSON data sent to the server.

[1068] Step 3:

[1069] The server sends a prompt to the generative AI.

[1070] The server analyzes the received JSON data and generates a prompt to send to the generative AI. The generated prompt is sent to the generative AI as an API request. The input is JSON data, and the output is the prompt.

[1071] Step 4:

[1072] Generative AI generates solutions.

[1073] Generative AI (for example, OpenAI's GPT-4) generates a solution based on the prompt received from the server. The generated solution is returned to the server as an API response. The input is the prompt, and the output is the solution text.

[1074] Step 5:

[1075] The server sends the solution to the device.

[1076] The server analyzes the solution received from the generative AI and converts it into a format for presentation to the user. The converted data is sent to the device as an HTTP response. The input is the text of the solution, and the output is the data sent to the device.

[1077] Step 6:

[1078] The terminal presents a solution to the user.

[1079] The terminal displays the solution received from the server on the screen. The user checks the solution displayed on the screen and decides whether to execute it. The input is the data from the server, and the output is the solution presented to the user.

[1080] Step 7:

[1081] The user enters feedback.

[1082] The user enters specific impressions and results in a field for entering feedback about the effectiveness of the solution. For example, the user might enter "Communication with the part leader has improved." The input is the feedback text, and the output is the data sent to the terminal.

[1083] Step 8:

[1084] The device sends the feedback to the server.

[1085] The terminal sends the feedback received from the user to the server again as an HTTP request. When sending, the data is converted to JSON format again. The input is the feedback text, and the output is the JSON data sent to the server.

[1086] Step 9:

[1087] The server improves the generative AI based on the feedback.

[1088] The server analyzes the received feedback and uses it as data to improve the generative AI algorithm, making future solution generation more appropriate and effective. The input is the feedback data, and the output is an improved generative AI algorithm.

[1089] (Application example 2)

[1090] Next, a description will be given of Application Example 2 of Form 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."

[1091] Conventional security services have difficulty providing appropriate solutions to specific problems users face. Furthermore, they lack a mechanism for providing solutions that take into account the user's emotional state, making it impossible to reduce user anxiety and stress. Furthermore, they lack a mechanism for effectively utilizing user feedback to improve solutions. To address these issues, a system is needed that provides appropriate solutions that take into account the user's specific problems and emotional state, and that continuously improves solutions based on feedback.

[1092] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1093] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, emotion engine means for analyzing the user's emotional state, means for providing the generative AI with emotion information obtained by the emotion engine, and means for the generative AI to generate a solution using the emotion information. This makes it possible to provide an appropriate solution that takes into account the user's specific problem and emotional state, and to continuously improve the solution based on feedback.

[1094] "User's private problems" refer to the specific troubles and concerns that individuals face in their daily lives or in specific situations.

[1095] "Generative AI" refers to artificial intelligence that generates solutions to problems provided by users.

[1096] "Means for presenting solutions to users" refers to methods or devices for communicating solutions generated by generative AI to users.

[1097] "Means for receiving user feedback" refers to a method or device for collecting user opinions and evaluations of the solution provided.

[1098] An "emotion engine" is a system or software that analyzes a user's emotional state and provides the results to generative AI.

[1099] "Emotional Information" means data regarding a user's emotional state analyzed by the Emotion Engine.

[1100] "Security-related issues" refer to specific problems or concerns users face regarding safety and crime prevention.

[1101] "Improving solutions based on feedback" means improving the quality of the solutions provided by generative AI by reflecting opinions and evaluations from users.

[1102] A system for implementing this invention includes a generative AI that receives a user's private problem as input and generates a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, an emotion engine that analyzes the user's emotional state, means for providing the generative AI with emotion information obtained by the emotion engine, and means for the generative AI to generate a solution using the emotion information.

[1103] Hardware and software used

[1104] Hardware: Smartphone

[1105] Software: Python, OpenAI API, EmotionEngine library

[1106] System processing overview

[1107] 1. Receiving user input: The user uses their smartphone to provide text input about a specific security issue, such as, "I've been seeing a lot of suspicious people around my house lately, and it's making me feel uneasy."

[1108] 2. Emotional state analysis: The emotion engine analyzes the user's input text and identifies the user's emotional state, for example recognizing emotions such as anxiety or fear.

[1109] 3. Sending a prompt to the generative AI: A prompt containing the emotional information obtained by the emotion engine and the user's problem is sent to the generative AI. An example of a prompt is as follows:

[1110] User's emotional state: Anxiety

[1111] User Problem: I've been seeing a lot of suspicious people around my house lately and it's making me feel uneasy.

[1112] Please provide a solution.

[1113] 4. Solution generation: Generative AI generates solutions based on the prompts, providing specific advice such as "Installing security cameras and sharing information with neighbors would be effective."

[1114] 5. Present the solution: The generated solution is presented to the user, who can check it on their smartphone screen.

[1115] 6. Receiving feedback: Users provide feedback on the solutions provided, including their opinions and ratings. This feedback is sent to the system and used to improve the generative AI's ability to generate solutions.

[1116] Specific examples

[1117] If a user inputs, "I've been seeing a lot of suspicious people around my house recently and I'm worried," the emotion engine will recognize the user's anxiety, and the generative AI will provide specific advice such as, "It would be effective to install security cameras and share information with neighbors." This solution is presented to the user, and the user provides feedback on its effectiveness to the system.

[1118] In this way, it is possible to provide appropriate solutions that take into account the user's specific problem and emotional state, and to continuously improve the solutions based on feedback.

[1119] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1120] Step 1:

[1121] The user uses their smartphone to provide a specific security problem as text input.

[1122] Input: User's problem text (e.g., "I've been seeing a lot of suspicious people around my house lately and it's making me feel uneasy.")

[1123] Output: The user's problem text is sent to the system.

[1124] Specific actions: The user opens the application on their smartphone, enters a problem into the text input field, and presses the submit button.

[1125] Step 2:

[1126] The server receives the user's input text and sends it to the emotion engine.

[1127] Input: User's problem text

[1128] Output: Text sent to the sentiment engine

[1129] Specific operation: The server receives the user's input text and sends the text to the emotion engine's API.

[1130] Step 3:

[1131] The emotion engine analyzes the user's input text and identifies their emotional state.

[1132] Input: User's problem text

[1133] Output: User's emotional state (e.g., "anxious")

[1134] What it does: The sentiment engine uses text analysis algorithms to identify sentiment in text and determine emotional states.

[1135] Step 4:

[1136] The server combines the emotional information obtained from the emotion engine with the user's question text and sends a prompt to the generative AI.

[1137] Input: User's problem text, sentiment information

[1138] Output: Prompt sent to the generative AI

[1139] Specific operation: The server combines the emotion information with the user's question text to generate a prompt sentence like the following:

[1140] User's emotional state: Anxiety

[1141] User Problem: I've been seeing a lot of suspicious people around my house lately and it's making me feel uneasy.

[1142] Please provide a solution.

[1143] This prompt text is sent to the generative AI API.

[1144] Step 5:

[1145] Generative AI generates solutions based on prompts.

[1146] Input: prompt statement

[1147] Output: Solution text (e.g., "Installing security cameras and sharing information with neighbors would be effective.")

[1148] What it does: The generative AI analyzes the prompt and uses its internal model to generate an appropriate solution.

[1149] Step 6:

[1150] The server presents the generated solution to the user.

[1151] Input: Solution text

[1152] Output: The solution displayed on the user's phone

[1153] Specific operation: The server sends the solution text received from the generative AI to the user's smartphone, and the application displays the solution on the screen.

[1154] Step 7:

[1155] Users can provide feedback on the solutions provided.

[1156] Input: User feedback text (e.g., "This solution was helpful")

[1157] Output: The feedback text is sent to the system.

[1158] Specific action: The user uses a smartphone application to enter feedback on the solution and presses the submit button.

[1159] Step 8:

[1160] The server receives feedback from users and uses it to improve the generative AI's ability to generate solutions.

[1161] Input: User feedback text

[1162] Output: An improved generative AI model

[1163] Specific operation: The server receives the feedback text, stores it as learning data for the generative AI, and uses it to retrain the model.

[1164] 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.

[1165] 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> ) 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.

[1166] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1167] 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.

[1168] [Third embodiment]

[1169] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1170] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1171] 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).

[1172] 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.

[1173] 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.

[1174] 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).

[1175] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1176] 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.

[1177] 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.

[1178] 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.

[1179] 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.

[1180] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1181] "Example 1"

[1182] In one embodiment of the present invention, a user provides a system with a personal problem as text input. This problem may be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend brass band activities." The system receives this input and uses generative AI to generate a solution. The generated solution may be specific advice, such as, "To improve communication with your section leader, it would be effective to clearly communicate the specific problem and work together to come up with a solution." This solution is presented to the user, who provides feedback on its effectiveness to the system. The system receives this feedback and improves the generative AI's ability to generate solutions.

[1183] "Example 2"

[1184] In one embodiment of the present invention, a user provides a system with a personal problem as text input. This problem may be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend brass band activities." The system receives this input and uses generative AI to generate a solution. The generated solution may be specific advice, such as, "To improve communication with your section leader, it would be effective to clearly communicate the specific problem and work together to come up with a solution." This solution is presented to the user, who provides feedback on its effectiveness to the system. The system receives this feedback and improves the generative AI's ability to generate solutions.

[1185] The processing flow of each embodiment will be described below.

[1186] "Example 1"

[1187] Step 1: The user provides the system with a text entry about their personal problem. This problem can be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend band activities."

[1188] Step 2: The system receives input from the user and uses generative AI to generate solutions. The generated solutions are specific advice such as, "To improve communication with the part-time leader, it is effective to clearly communicate the specific problems and work together to find solutions."

[1189] Step 3: The system presents the generated solution to the user, who then tries it out and provides feedback to the system on its effectiveness.

[1190] Step 4: The system receives feedback from the user and improves the generative AI's ability to generate solutions, thereby improving the accuracy of solutions to the same or similar problems.

[1191] Example 1

[1192] Next, a description will be given of Example 1 of Form 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."

[1193] Conventional systems have difficulty providing appropriate solutions to users' private problems. They also lack a mechanism for evaluating the effectiveness of the solutions provided and reflecting this in future solution generation. This has led to the issue of lowering users' satisfaction with the solutions they receive.

[1194] 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.

[1195] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for generating a prompt sentence suitable for the generative AI means, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, and means for reflecting the received feedback in the generative AI means. This makes it possible to provide an appropriate solution to the user's problem and improve the solution based on feedback on its effectiveness.

[1196] "User" means an individual who utilizes the System to enter their private problem and receive a solution.

[1197] "Private issues" refer to specific challenges or difficulties that users face personally.

[1198] "Generative AI means" refers to the function of artificial intelligence that generates appropriate solutions to private problems input by users.

[1199] A "prompt sentence" refers to an instruction sentence that conveys the content of the problem to a generative AI means.

[1200] "Solutions" refer to specific advice or suggestions that generative AI methods provide to users for their private problems.

[1201] "Presentation means" refers to the functionality for displaying the generated solution to the user.

[1202] "Feedback" refers to information provided by the user to the system regarding the effectiveness and impressions of the proposed solution.

[1203] "Means of reflection" refers to the function of incorporating feedback received from users into generative AI means and using them to generate solutions in the future.

[1204] This invention relates to a system that allows users to input their own private problems and generate solutions to those problems. The system receives the user's input, generates solutions using a generative AI model, and presents them to the user. It also receives feedback from the user and improves the performance of the generative AI model.

[1205] Hardware and software used

[1206] The system uses the following hardware and software:

[1207] Device: The device through which a user enters their private problem and receives a solution. Examples include computers, smartphones, and tablets.

[1208] Server: A computer system that receives user input, sends prompts to the generative AI model, and sends the generated solutions to the device.

[1209] Generative AI model: An artificial intelligence model that generates solutions to user problems. Examples include OpenAI's GPT-4.

[1210] Data processing and calculation

[1211] The user uses the device to input a private problem in text format. For example, they can input a specific problem such as, "I'm having trouble communicating with the section leader during my weekend brass band activities." The device then sends this input to the server.

[1212] The server generates a prompt to pass the received text input to the generative AI model. For example, it generates a prompt such as, "The user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to solve this problem."

[1213] The generative AI model generates solutions based on prompts, such as advice like, "To improve communication with the part-time leader, it would be effective to clearly communicate the specific problems and work together to find solutions."

[1214] The generated solution is sent from the server to the terminal and presented to the user. The user checks the presented solution and provides feedback on its effectiveness to the server via the terminal.

[1215] The server receives feedback from users and uses it to improve the generative AI model's ability to generate solutions, allowing the system to continuously learn and provide more effective solutions.

[1216] Specific examples

[1217] For example, a user enters the following problem:

[1218] "I'm having trouble communicating with the section leader during weekend band activities."

[1219] Example prompts for generative AI models:

[1220] "A user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to resolve this issue."

[1221] An example of a generated solution:

[1222] "In order to improve communication with section leaders, it is effective to clearly communicate specific problems and work together to find solutions. For example, you could set up regular meetings to provide an opportunity for frank discussion of each other's opinions."

[1223] In this way, the system provides solutions to users' problems and improves the performance of the generative AI model based on user feedback.

[1224] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1225] Step 1:

[1226] A user uses a terminal to enter a private problem.

[1227] Specifically, the user inputs a problem in text format into the terminal interface, such as "I'm having trouble communicating with the section leader during my weekend brass band activities."

[1228] Input: User's private information (text data)

[1229] Output: Text data entered into the terminal

[1230] Step 2:

[1231] The terminal transmits the input text data to the server.

[1232] Specifically, the terminal encrypts the text data entered by the user and transmits it to the server.

[1233] Input: Text data entered into the terminal

[1234] Output: Encrypted text data sent to the server

[1235] Step 3:

[1236] The server analyzes the text data it receives and generates a prompt sentence suitable for the generative AI model.

[1237] Specifically, the server analyzes the text data and generates a prompt that reads, "The user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to solve this problem."

[1238] Input: Encrypted text data sent to the server

[1239] Output: A prompt suitable for a generative AI model

[1240] Step 4:

[1241] The server sends a prompt to the generative AI model.

[1242] Specifically, the server sends the generated prompt sentence to the generative AI model.

[1243] Input: A prompt suitable for a generative AI model

[1244] Output: The prompt sent to the generative AI model

[1245] Step 5:

[1246] A generative AI model generates a solution based on the prompt.

[1247] Specifically, the generative AI model analyzes the prompt and generates a solution such as, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and think of solutions together."

[1248] Input: A prompt sent to the generative AI model

[1249] Output: Generated solution (text data)

[1250] Step 6:

[1251] The server sends the generated solution to the terminal.

[1252] Specifically, the server encrypts the solution received from the generative AI model and sends it to the device.

[1253] Input: Generated solution (text data)

[1254] Output: The encrypted solution sent to the terminal.

[1255] Step 7:

[1256] The terminal presents a solution to the user.

[1257] Specifically, the device decrypts the solution received from the server and displays it to the user, who then checks the solution on the screen.

[1258] Input: The encrypted solution sent to the terminal

[1259] Output: The solution presented to the user

[1260] Step 8:

[1261] The user provides feedback on the effectiveness of the proposed solution.

[1262] Specifically, the user checks the presented solution and inputs feedback such as "This advice was very helpful" into the terminal interface.

[1263] Input: User feedback (text data)

[1264] Output: Feedback typed into the terminal

[1265] Step 9:

[1266] The device sends the feedback to the server.

[1267] Specifically, the terminal encrypts the feedback input by the user and transmits it to the server.

[1268] Input: Feedback entered into the device

[1269] Output: Encrypted feedback sent to the server

[1270] Step 10:

[1271] The server reflects the feedback in the generative AI model.

[1272] Specifically, the server incorporates the received feedback into the generative AI model and uses it to generate solutions from the next time onwards.

[1273] Input: Encrypted feedback sent to the server

[1274] Output: Feedback reflected in the generative AI model

[1275] (Application example 1)

[1276] Next, a description will be given of Application Example 1 of Form 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."

[1277] Conventional generative AI systems focused on providing solutions to users' private problems, but lacked the ability to provide solutions to specific security issues. Furthermore, they lacked mechanisms for improving solutions based on user feedback. This made it difficult for users to receive prompt and accurate advice on security issues.

[1278] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes generative AI means that receives a user's private problem as input and generates a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, means for receiving a security problem as input and generating a solution to the problem, and means for presenting the generated solution to the user. This enables the user to receive prompt and accurate advice on specific security problems.

[1279] "User" means any person or entity that uses the System to enter private or security-related issues.

[1280] "Private issues" are problems or challenges that users face personally, such as issues related to relationships or daily life.

[1281] "Generative AI" is an artificial intelligence system that generates solutions to problems input by users.

[1282] A "solution" is a specific piece of advice or suggestion that a generative AI provides to a user about a problem.

[1283] "Feedback" refers to the evaluation or opinion that a user gives of the solution provided by the generative AI.

[1284] "Security issues" are specific safety and security issues faced by users.

[1285] "Presentation means" refers to a method or device for displaying the solution generated by generative AI to the user.

[1286] "Means for receiving" refers to a method or device by which the system receives feedback from the user.

[1287] The system for implementing this invention is a system that uses generative AI to solve problems related to users' privacy and security. Specific embodiments of this system are described below.

[1288] System Configuration

[1289] The system mainly consists of the following components:

[1290] 1. User device: A device such as a smartphone or computer that users use to enter questions.

[1291] 2. Server: A central system for hosting the generative AI and processing input from users.

[1292] 3. Generative AI: An artificial intelligence model that generates solutions to user problems, such as OpenAI's GPT-3.

[1293] 4. Database: A storage system for saving user input and feedback.

[1294] Program processing

[1295] The server processes the data as follows:

[1296] 1. Receiving user input: Receive private or security issues in text format sent from the user's device.

[1297] 2. Generating a solution using generative AI: The received problem is input into a generative AI, which generates a solution. OpenAI's GPT-3 is used as the generative AI.

[1298] 3. Presenting the solution: The generated solution is sent to the user's terminal and presented to the user.

[1299] 4. Receiving feedback: Receiving feedback from users and storing it in a database.

[1300] 5. Improve the AI ​​model: Use the feedback received to improve the generative AI's ability to generate solutions.

[1301] Hardware and software used

[1302] Hardware: smartphones, PCs, servers

[1303] Software: Python, OpenAI API, database management system (e.g., MySQL)

[1304] Specific examples

[1305] If a user types in "I've seen suspicious people around my house recently," the server sends this input to a generative AI, which then generates a solution, such as "Installing security cameras and sharing information with neighbors would be effective," and presents it to the user.

[1306] Prompt Sentence Examples

[1307] User security issue: I've recently seen some suspicious people around my house.

[1308] Please provide a solution.

[1309] In this way, users can get fast and accurate advice on specific security issues.

[1310] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1311] Step 1:

[1312] The user terminal receives input from the user. Specifically, the user inputs private and security-related issues in text format using a smartphone or PC. The input text data is sent to the server.

[1313] Input: Text data entered by the user (e.g., "I've been seeing some suspicious people around my house lately.")

[1314] Output: Text data sent to the server

[1315] Step 2:

[1316] The server receives the text data sent from the user's device and generates a prompt sentence to be input to the generative AI. The prompt sentence is a concrete description of the user's problem.

[1317] Input: Text data sent by the user

[1318] Output: A prompt to be input to the generative AI (e.g., "User's security problem: I've been seeing suspicious people around my house recently. Please provide a solution.")

[1319] Step 3:

[1320] The server sends a prompt to a generative AI (e.g., OpenAI's GPT-3) to generate a solution. The generative AI generates an appropriate solution in text format based on the prompt.

[1321] Input: Prompt sentence to input to the generative AI

[1322] Output: The solution generated by the generative AI (e.g., "Installing security cameras and sharing information with neighbors would be effective.")

[1323] Step 4:

[1324] The server sends the generated solution to the user's device and presents it to the user, who can then check the solution on their smartphone or computer screen.

[1325] Input: A solution generated by a generative AI

[1326] Output: The solution sent to the user's device

[1327] Step 5:

[1328] The user terminal receives feedback from the user, who inputs his / her evaluation and opinion on the provided solution in text format and sends it to the server.

[1329] Input: User-entered feedback (e.g., "I think installing security cameras is a good idea.")

[1330] Output: Feedback sent to the server

[1331] Step 6:

[1332] The server receives feedback from users and stores it in a database, which is used to improve the generative AI's ability to generate solutions.

[1333] Input: Feedback submitted by the user

[1334] Output: Feedback stored in a database

[1335] Step 7:

[1336] The server retrains the generative AI model based on the saved feedback, improving its ability to generate solutions, which will result in more accurate solutions in future.

[1337] Input: Feedback stored in the database

[1338] Output: Improved generative AI model

[1339] By following these steps, users can get fast and accurate advice on specific security issues.

[1340] Example 2

[1341] Next, a description will be given of Example 2 of Form 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."

[1342] Conventional systems have difficulty providing appropriate solutions to users' private problems. Furthermore, they lack a mechanism for evaluating the effectiveness of the solutions provided and reflecting this in future solution generation, making it difficult to increase user satisfaction. Furthermore, they lack the ability to generate appropriate prompts for the user's specific problem, which can result in a decline in the quality of the solutions generated.

[1343] 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.

[1344] In this invention, the server includes a generative artificial intelligence that receives a user's private problem as input and generates a solution to the problem, a means for generating a prompt sentence suitable for the generative artificial intelligence, a means for presenting the solution generated by the generative artificial intelligence to the user, a means for receiving feedback from the user, and a means for improving the solution generation ability of the generative artificial intelligence based on the user's feedback. This makes it possible to provide an appropriate solution to the user's specific problem, evaluate its effectiveness, and reflect it in future solution generation.

[1345] "User" means an individual who utilizes the System to enter their private problem and receive a solution.

[1346] "Private issues" refers to specific problems or concerns that the user has personally.

[1347] "Generative AI" refers to artificial intelligence techniques that generate solutions based on user input.

[1348] A "prompt sentence" refers to an instruction sentence that is input to a generative artificial intelligence to generate an appropriate solution.

[1349] "Solutions" refer to the specific advice or suggestions that generative artificial intelligence provides to users about their problems.

[1350] "Feedback" refers to information that a user reports to the system after trying out a proposed solution, including its effectiveness and impressions.

[1351] "Server" refers to a computer system that receives user input data, generates solutions using generative artificial intelligence, and presents them to the user.

[1352] "Device" refers to the device through which a User enters their problem, receives a solution, and provides feedback.

[1353] The present invention is a system in which a user provides a text input of their private problem to the system, and a solution to the problem is generated. A specific embodiment of this system will be described below.

[1354] Hardware and software used

[1355] Hardware

[1356] Server: A high-performance computer system that runs generative artificial intelligence and processes user input data.

[1357] Device: The device that a user uses to enter their problem, receive a solution, or provide feedback. This could be a smartphone, tablet, or computer.

[1358] software

[1359] Generative artificial intelligence: For example, using advanced natural language processing techniques such as OpenAI's GPT-4.

[1360] Encryption protocol: The SSL / TLS protocol is used to securely transmit user input data to the server.

[1361] Data processing and calculation

[1362] User problem input

[1363] Users enter their personal problems into a text box on the device, for example, "I'm having trouble communicating with my section leader during my weekend band activities."

[1364] Sending input data

[1365] The terminal encrypts the text data entered by the user using the SSL / TLS protocol and sends it to the server.

[1366] Problem analysis and prompt generation

[1367] The server analyzes the received text data using natural language processing (NLP) technology and generates a prompt suitable for generative artificial intelligence. For example, if the user input is "I'm having trouble communicating with the section leader during weekend band activities," the prompt would be "The user is having trouble communicating with the section leader during weekend band activities. Please clearly explain the specific problem and provide advice so we can work together to find a solution."

[1368] Solution Generation

[1369] The server inputs the prompt into the generative AI, which then generates a solution. The generative AI then generates appropriate advice based on the prompt. For example, the generated advice might be, "To improve communication with the part leader, it is effective to clearly communicate the specific problems and work together to come up with solutions. It would be a good idea to have a private discussion with the part leader before the next rehearsal, share the specific problems, and set aside time to think about solutions together."

[1370] Proposing a solution

[1371] The server sends the generated solution to the terminal, which displays it to the user, who can then check and try out the solution.

[1372] Collecting feedback

[1373] After trying out the proposed solutions, users can enter specific feedback into the device about their effectiveness, such as, "The discussion with the part leader went well, and communication has improved."

[1374] Model Improvements

[1375] The device sends user feedback to the server, which passes it on to the generative AI and uses it to improve the model's ability to generate solutions, resulting in more effective solutions in future.

[1376] Specific examples

[1377] Example user input

[1378] "I'm having trouble communicating with the section leader during weekend band activities."

[1379] Example prompts for generative AI models

[1380] "A user is having trouble communicating with the section leader during their weekend band activities. Please clearly explain the specific problem and provide advice on how we can work together to find a solution."

[1381] Example of a generated solution

[1382] "To improve communication with section leaders, it is effective to clearly communicate specific problems and work together to find solutions. It is a good idea to have a private discussion with section leaders before the next rehearsal, share specific problems, and set aside time to think about solutions together."

[1383] This way, users receive concrete advice and can try it out for themselves, and feedback helps the system improve and provide more effective solutions.

[1384] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1385] Step 1:

[1386] The user enters their personal problem into the text box on the device. For example, they might enter, "I'm having trouble communicating with my section leader during my weekend brass band activities." The input data is in text format, and the user can proceed to the next step by clicking the "Submit" button.

[1387] Step 2:

[1388] The terminal encrypts the text data entered by the user using the SSL / TLS protocol and sends it to the server. The input data is encrypted text data and sent securely to the server. The server decrypts the received data and proceeds to the next step.

[1389] Step 3:

[1390] The server analyzes the received text data using natural language processing (NLP) technology. The input data is text data containing the user's problem, and the content of the problem is extracted as a result of the analysis. Based on this analysis result, the server generates a prompt suitable for generative AI. For example, a generated prompt might read, "The user is having trouble communicating with the section leader during weekend brass band activities. Please clearly explain the specific problem and provide advice so we can work together to find a solution."

[1391] Step 4:

[1392] The server inputs a prompt into the generative AI and generates a solution. The input data is the prompt, and the generative AI generates appropriate advice based on this. For example, a solution might be generated that reads, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and work together to come up with solutions. It would be a good idea to have a private discussion with the part leader before the next rehearsal, share the specific problems, and set aside time to think about solutions together."

[1393] Step 5:

[1394] The server sends the generated solution to the terminal, and the input data is the generated solution, which the terminal displays to the user, who can then check the presented solution and try it out.

[1395] Step 6:

[1396] After trying out the proposed solution, the user enters feedback about its effectiveness into the device. For example, specific feedback such as "The discussion with the part leader went well, and communication has improved." The input data is feedback information, and the user can proceed to the next step by clicking the "Submit" button.

[1397] Step 7:

[1398] The device sends the user's feedback to the server. The input data is feedback information, which the server receives and analyzes. The server then passes the feedback information to the generative AI and uses it to improve the model's ability to generate solutions, making future solutions more effective.

[1399] (Application example 2)

[1400] Next, a description will be given of Application Example 2 of Form 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."

[1401] With conventional security services, it was difficult to quickly provide appropriate solutions to the specific security problems faced by users. Furthermore, there was a lack of a mechanism for evaluating the effectiveness of the solutions provided and for continuous improvement, making it difficult to improve users' security awareness and the quality of countermeasures. This led to the issue of users being unable to use the digital environment with peace of mind.

[1402] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1403] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving user feedback, means for receiving a security problem as input and generating a solution to the problem, means for presenting the generated solution to the user, and means for improving the solution generation ability of the generative AI based on user feedback. This makes it possible to provide quick and appropriate solutions to specific security problems faced by users and to evaluate their effectiveness and continuously improve them.

[1404] "User" means any person or entity that uses the System to enter private or security-related issues.

[1405] "Private issues" are specific problems or challenges that users face personally.

[1406] "Generative AI" is a type of artificial intelligence that generates solutions to problems input by the user.

[1407] A "solution" is a specific piece of advice or countermeasure that the generative AI provides to the user for their problem.

[1408] "Feedback" is information about the results and effectiveness of a user's attempt at a provided solution.

[1409] "Security issues" are specific issues users face regarding safety and protection in the digital environment.

[1410] "The solution generation ability of generative AI" refers to the ability of generative AI to generate appropriate solutions to users' problems.

[1411] "Presentation means" refers to a method or device for displaying or notifying the user of the solution generated by the generative AI.

[1412] "Means for receiving" refers to a method or device by which the system obtains feedback from the user.

[1413] "Means for improvement" are methods or devices for improving the solution-generating capabilities of generative AI based on user feedback.

[1414] As an embodiment of this invention, we will explain how to install a security advisor AI system on a smartphone. In this system, a user inputs a security problem, and a generative AI generates a solution and presents it to the user. Furthermore, feedback from the user is received, and the generative AI's ability to generate a solution is improved.

[1415] Hardware and software used

[1416] Hardware: Smartphone

[1417] Software: Python, OpenAI API

[1418] System configuration

[1419] 1. Obtaining user input: The user inputs text into a smartphone application. For example, they input a specific problem, such as, "My home Wi-Fi has been unstable recently, and I'm worried about security."

[1420] 2. Prompt generation: Based on the user's input, a prompt is generated to be passed to the generative AI. For example, it could be something like, "User's security problem: My home Wi-Fi has been unstable recently, so I'm worried about security. Please provide a solution."

[1421] 3. AI solution generation: Using OpenAI's API, a generative AI (e.g., GPT-3) generates a solution. The generated solution is specific advice such as, "We recommend updating your Wi-Fi router's firmware and setting a strong password."

[1422] 4. Present the solution: The generated solution is presented to the user and displayed on the smartphone application.

[1423] 5. Get feedback: Users try the solution and provide feedback on its effectiveness, such as, "My Wi-Fi is now more stable and secure."

[1424] 6. Improving the Generative AI: Based on user feedback, we will improve the generative AI's ability to generate solutions, which will result in better and more effective solutions in future.

[1425] Specific examples

[1426] User input: "My home Wi-Fi has been unstable lately and I'm worried about security."

[1427] Example prompt: "User security issue: My home Wi-Fi has been unstable lately and I'm worried about security. Please provide a solution."

[1428] AI advice: "We recommend updating your Wi-Fi router's firmware and setting a strong password."

[1429] User feedback: "Wi-Fi is now more stable and secure."

[1430] In this way, it is possible to provide quick and appropriate solutions to specific security problems faced by users, evaluate their effectiveness and continuously improve them.

[1431] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1432] Step 1:

[1433] The user launches an application on their smartphone and enters a security problem via text.

[1434] Input: A specific security issue entered by the user (e.g., "My home Wi-Fi has been unstable lately, and I'm worried about security.")

[1435] Output: The text entered by the user

[1436] Specific behavior: The user enters a problem into the application's text input field and presses the submit button.

[1437] Step 2:

[1438] The device receives user input and generates a prompt sentence to be passed to the generative AI.

[1439] Input: User-entered text

[1440] Output: Generated prompt (e.g. "User's security problem: My home Wi-Fi has been unstable recently and I'm worried about security. Please provide a solution.")

[1441] What it does: The application formats the user's input text and generates a prompt suitable for generative AI.

[1442] Step 3:

[1443] The server calls the generative AI and generates a solution using the generated prompt sentence as input.

[1444] Input: Generated prompt statement

[1445] Output: The solution generated by the generative AI (e.g., "It is recommended that you update your Wi-Fi router's firmware and set a strong password.")

[1446] Specific operation: The server uses the OpenAI API to send a prompt to a generative AI (e.g., GPT-3) and obtain a solution.

[1447] Step 4:

[1448] The terminal presents the generated solution to the user.

[1449] Input: A solution generated by a generative AI

[1450] Output: The solution presented to the user

[1451] What happens: The application displays the solution on the user's screen.

[1452] Step 5:

[1453] The user tries the proposed solution and inputs feedback on its effectiveness.

[1454] Input: Feedback about the effectiveness of the solution the user tried (e.g., "My Wi-Fi is now more stable and secure.")

[1455] Output: User feedback text

[1456] Specific behavior: The user enters the effect in the application's feedback input field and presses the submit button.

[1457] Step 6:

[1458] The server receives feedback from users and improves the generative AI's ability to generate solutions.

[1459] Input: User feedback text

[1460] Output: Improved solution generation capabilities of generative AI

[1461] Specific operation: The server analyzes the feedback data, incorporates it as learning data for the generative AI, and reflects it in generating solutions from the next time onwards.

[1462] 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.

[1463] "Example 1"

[1464] As one embodiment of the present invention, a system incorporating an emotion engine is provided. The system includes a generative AI that receives a user's private problem as input and generates a solution to the problem, a means for presenting the solution generated by the generative AI to the user, and a means for receiving feedback from the user. The system further includes an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's emotional state and provides the results to the generative AI. The generative AI uses this emotional information to generate a more appropriate solution. For example, if a user has a problem related to weekend band activities and feels strongly about the problem, the emotion engine recognizes the strong emotion, and the generative AI uses that information to generate a more specific and appropriate solution.

[1465] "Example 2"

[1466] As one embodiment of the present invention, a system incorporating an emotion engine is provided. The system includes a generative AI that receives a user's private problem as input and generates a solution to the problem, a means for presenting the solution generated by the generative AI to the user, and a means for receiving feedback from the user. The system further includes an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's emotional state and provides the results to the generative AI. The generative AI uses this emotional information to generate a more appropriate solution. For example, if a user has a problem related to weekend band activities and feels strongly about the problem, the emotion engine recognizes the strong emotion, and the generative AI uses that information to generate a more specific and appropriate solution.

[1467] The processing flow of each embodiment will be described below.

[1468] "Example 1"

[1469] Step 1: The user provides the system with a private concern as text input. Step 2: The emotion engine analyzes the user's emotional state based on information derived from the user's text input and, if possible, other inputs such as the user's voice and facial expressions.

[1470] Step 3: The emotion engine provides the analysis results to the generative AI, which uses this information as reference when generating solutions.

[1471] Step 4: The generative AI generates a solution to the user's problem. This solution is generated based on the problem information provided by the user and the emotional information provided by the emotion engine.

[1472] Step 5: The system presents the generated solution to the user.

[1473] Step 6: The user provides feedback regarding the usefulness and appropriateness of the proposed solution.

[1474] Step 7: The system receives user feedback and uses it to improve the generative AI's ability to generate solutions.

[1475] Example 1

[1476] Next, a description will be given of Example 1 of Form 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."

[1477] Conventional systems were unable to consider the user's emotional state when providing solutions to a user's private problems, making it difficult to provide appropriate solutions. Furthermore, there was a lack of a way to effectively utilize user feedback to improve the generative AI's ability to generate solutions. This resulted in problems such as a decrease in the accuracy and appropriateness of solutions for users.

[1478] 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.

[1479] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, emotion engine means for analyzing the user's emotional state, means for providing the emotion engine's analysis results to the generative AI, and means for analyzing the user's feedback and improving the generative AI's ability to generate solutions. This makes it possible to provide appropriate solutions that take the user's emotional state into consideration and to continuously improve the generative AI by utilizing the feedback.

[1480] "User" means an individual who utilizes the System to enter their private problems and obtain solutions.

[1481] "Private issues" refers to specific problems or concerns that the user has personally.

[1482] "Generative AI" refers to artificial intelligence models that generate solutions based on user input.

[1483] "Solutions" refer to the specific advice or suggestions that generative AI provides to users about their problems.

[1484] "Means for presentation" refers to the method or device for displaying the solution generated by generative AI to the user.

[1485] "Feedback" refers to information that users return to the system about the effectiveness and impressions of the proposed solutions.

[1486] An "emotion engine" refers to software or hardware that analyzes a user's emotional state and provides the results to generative AI.

[1487] "Analysis results" refers to the data obtained as a result of the emotion engine analyzing the user's emotional state.

[1488] "Means for improvement" refers to methods and devices for analyzing user feedback and improving the generative AI's ability to generate solutions.

[1489] This invention is a system that allows users to input their private problems in text format and generates solutions to those problems. The system uses a generative AI model to generate solutions and presents them to the user. It also receives feedback from the user to improve the generative AI model's ability to generate solutions. Furthermore, it uses an emotion engine to analyze the user's emotional state and provides the results to the generative AI model to generate more appropriate solutions.

[1490] Hardware and software used

[1491] Hardware

[1492] Device: The device through which a user enters their problem and receives a solution (e.g., smartphone, tablet, computer).

[1493] Server: A computer system for running generative AI models and emotion engines

[1494] software

[1495] Generative AI models: Artificial intelligence models that generate solutions to user problems (e.g., GPT-4)

[1496] Emotion Engine: Software for analyzing the user's emotional state

[1497] Feedback Analysis System: Software for analyzing user feedback and improving generative AI models

[1498] Data processing and calculation

[1499] User problem input

[1500] Users use the device to enter their personal problems in text format, for example, "I'm having trouble communicating with my section leader during my weekend band activities."

[1501] Receiving and analyzing the problem

[1502] The device sends input from the user to the server. The server receives this input and generates a prompt to pass to the generative AI model. For example, it generates a prompt such as, "The user is having trouble communicating with the section leader during weekend band activities. How can we improve this?"

[1503] Solution Generation

[1504] The server inputs the prompt into a generative AI model (e.g., GPT-4) and generates a solution. The generative AI model generates specific advice based on the prompt. For example, it generates a solution such as, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and work together to find a solution."

[1505] Proposing a solution

[1506] The server sends the generated solution to the terminal, which displays the received solution to the user, who then checks the presented solution and decides whether to execute it.

[1507] Receiving Feedback

[1508] The user inputs feedback into the device about the effectiveness of the proposed solution. For example, they can input something like, "As a result of implementing the advice, my communication with the part leader improved." The device then sends this feedback to the server.

[1509] Feedback analysis and learning

[1510] The server receives and analyzes feedback from users. The analysis results are used as learning data to improve the solution generation capabilities of the generative AI model. This will result in more accurate solutions being generated in the future.

[1511] Use of emotion engine

[1512] When a user inputs a problem, the emotion engine analyzes the user's emotional state. For example, if the user has strong emotions, it provides that information to the generative AI model, which then uses this emotional information to generate a more appropriate solution. For example, if the user is feeling very stressed, the emotion engine provides that information to the generative AI model, which then takes that information into account to generate a more empathetic solution.

[1513] Examples of specific examples and prompts

[1514] Specific examples

[1515] If a user enters, "I'm having trouble communicating with the section leader during my weekend band activities," the system will process the following:

[1516] 1. The user enters the problem.

[1517] 2. The device sends the input to the server.

[1518] 3. The server passes the problem to a generative AI model (e.g., GPT-4).

[1519] 4. The generative AI model generates a solution.

[1520] 5. The server sends the solution to the device.

[1521] 6. The device presents a solution to the user.

[1522] 7. The user enters feedback.

[1523] 8. The device sends the feedback to the server.

[1524] 9. The server analyzes the feedback and improves the generative AI model.

[1525] Prompt Sentence Examples

[1526] "During the weekend brass band activities, I'm having trouble communicating with the section leaders. How can I improve this?"

[1527] By inputting this prompt into a generative AI model, a specific solution is generated.

[1528] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1529] Step 1:

[1530] The user uses the device to input their personal problems in text format. For example, they might input, "I'm having trouble communicating with the section leader during my weekend brass band activities." The input text data is saved in an input field on the device.

[1531] Step 2:

[1532] The terminal sends user input to the server. Specifically, it sends text data to the server using an HTTP request. The server receives this request and prepares to parse the text data.

[1533] Step 3:

[1534] The server analyzes the received text data and generates a prompt to be passed to the generative AI model. For example, it generates a prompt such as, "The user is having trouble communicating with the section leader during weekend band activities. How can we improve this?" This prompt is then input into the generative AI model.

[1535] Step 4:

[1536] The server inputs the prompt into a generative AI model (e.g., GPT-4) and generates a solution. The generative AI model generates specific advice based on the prompt. For example, it generates a solution such as, "To improve communication with the part leader, it is effective to clearly communicate the specific problems and think about solutions together." This solution is stored on the server.

[1537] Step 5:

[1538] The server sends the generated solution to the terminal as an HTTP response. The terminal displays the received solution to the user. The user checks the presented solution and decides whether to execute it.

[1539] Step 6:

[1540] The user enters feedback into the device about the effectiveness of the proposed solution. For example, they might say, "After implementing the advice, my communication with the part leader improved." The entered feedback is saved in an input field on the device.

[1541] Step 7:

[1542] The device sends user feedback to the server. Specifically, it sends the feedback data to the server using an HTTP request. The server receives this request and prepares to analyze the feedback data.

[1543] Step 8:

[1544] The server analyzes user feedback and uses it as learning data to improve the generative AI model's ability to generate solutions. Based on the analysis results, the generative AI model is retrained to generate more accurate solutions in the future.

[1545] Step 9:

[1546] When a user inputs a problem, the emotion engine analyzes the user's emotional state. For example, if the user has strong emotions, it provides that information to the generative AI model, which then uses this emotional information to generate a more appropriate solution. For example, if the user is feeling very stressed, the emotion engine provides that information to the generative AI model, which then takes that information into account to generate a more empathetic solution.

[1547] (Application example 1)

[1548] Next, a description will be given of Application Example 1 of Form 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."

[1549] Conventional security services have difficulty providing appropriate solutions to specific problems faced by users. Furthermore, they are unable to provide solutions that take into account the user's emotional state, which can lead to lower user satisfaction. Furthermore, they lack a mechanism for effectively utilizing user feedback to improve solutions.

[1550] 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.

[1551] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, emotion engine means for analyzing the user's emotional state, means for providing emotion information obtained by the emotion engine to the generative AI, and generative AI means for generating a solution based on the emotion information. This makes it possible to provide an appropriate solution that takes the user's emotional state into consideration and to improve the solution by utilizing feedback from the user.

[1552] "User's private issues" refer to the specific challenges and difficulties that individuals face in their daily lives and work.

[1553] "Generative AI" refers to artificial intelligence that generates solutions to problems provided by users.

[1554] "Generating a solution" means providing appropriate solutions or advice to the user's problem.

[1555] "User presentation" refers to the interface or method for displaying the generated solution to the user.

[1556] "Feedback methods" refers to the interface and methods for collecting user ratings and opinions.

[1557] An "emotion engine" is a system or software that analyzes a user's emotional state and provides the results.

[1558] "Emotional Information" means data regarding a user's emotional state analyzed by the Emotion Engine.

[1559] "Security issues" refer to specific security challenges faced by users, such as online fraud and personal information leaks.

[1560] "Improving the solution" means improving the quality of the solution provided by the generative AI based on feedback from users.

[1561] As an embodiment of the present invention, a security advisor system is constructed. The system includes a generative AI that receives a user's private problem as input and generates a solution to the problem, a means for presenting the solution generated by the generative AI to the user, a means for receiving feedback from the user, an emotion engine that analyzes the user's emotional state, a means for providing the generative AI with emotion information obtained by the emotion engine, and the generative AI that generates a solution based on the emotion information.

[1562] Hardware and software used

[1563] Hardware: Smartphone, PC

[1564] Software: Python, OpenAI API, EmotionEngine library

[1565] Data processing and calculation

[1566] 1. Getting user input:

[1567] The user provides a text input for a security problem, such as "I've been getting a lot of phishing emails lately."

[1568] 2. Emotional state analysis:

[1569] Analyze the emotional state of the user from their input using an emotion engine. Use the EmotionEngine library to detect the user's emotional state (e.g., "anxiety").

[1570] 3. Prompt generation:

[1571] Generate prompts that include emotional information and the user's problem. For example, generate prompts like the following:

[1572] User's emotional state: Anxiety

[1573] User Problem: I've been getting a lot of phishing emails lately.

[1574] Please provide a solution.

[1575] 4. Solution Generation:

[1576] Using the OpenAI API, generative AI generates solutions, such as "specific methods for identifying phishing emails."

[1577] 5. Propose a solution:

[1578] The generated solution is presented to the user, who can check it on their smartphone or PC screen.

[1579] 6. Getting feedback:

[1580] Get and store user feedback. Users rate whether the solution was helpful and provide that rating to the system.

[1581] Specific examples

[1582] If a user types, "I'm having trouble with the number of phishing emails I've received lately," the emotion engine will detect "anxiety," and the generative AI will provide "specific methods for identifying phishing emails." An example of a prompt sentence is as follows:

[1583] User's emotional state: Anxiety

[1584] User Problem: I've been getting a lot of phishing emails lately.

[1585] Please provide a solution.

[1586] In this way, it is possible to provide appropriate solutions that take into account the user's emotional state and to use user feedback to improve the solutions.

[1587] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1588] Step 1:

[1589] The user provides a security problem as text input using a terminal. For example, the user might type, "I've been getting a lot of phishing emails lately." This input is sent to the system.

[1590] Step 2:

[1591] The server receives input from the user and sends it to the emotion engine. The emotion engine uses the EmotionEngine library to analyze the emotional state from the user's input. For example, it detects the emotional state "anxiety." This emotional information is returned to the server.

[1592] Step 3:

[1593] The server generates a prompt based on the emotional information and the user's problem. For example, it generates the following prompt:

[1594] User's emotional state: Anxiety

[1595] User Problem: I've been getting a lot of phishing emails lately.

[1596] Please provide a solution.

[1597] This prompt is sent to the generative AI.

[1598] Step 4:

[1599] The server uses generative AI to generate a solution based on the prompt. Using the OpenAI API, the generative AI generates a solution. For example, a solution such as "specific methods for identifying phishing emails" is generated. This solution is then returned to the server.

[1600] Step 5:

[1601] The server presents the generated solution to the user, who can then check the solution on the device screen. For example, the solution may show "specific methods for identifying phishing emails."

[1602] Step 6:

[1603] The user enters feedback on the proposed solution, for example by answering "yes" or "no" to the question "Did this solution help you?" This feedback is sent to the server.

[1604] Step 7:

[1605] The server receives and stores feedback from users. The feedback is used to improve the generative AI. For example, it is stored in a feedback database and referenced the next time a solution is generated.

[1606] In this way, it is possible to provide an appropriate solution that takes into account the user's emotional state and to use feedback from the user to improve the solution.

[1607] Example 2

[1608] Next, a description will be given of Example 2 of Form 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."

[1609] Conventional systems were unable to take the user's emotional state into account when generating solutions to the user's private problems, making it difficult to provide appropriate solutions. Furthermore, there was a lack of a way to effectively utilize user feedback to improve the performance of generative AI. This resulted in a decrease in user satisfaction with the solution.

[1610] 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.

[1611] In this invention, the server includes a generative AI that receives a user's private problem as input and generates a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, an emotion engine that analyzes the user's emotional state, means for providing the emotion engine's analysis results to the generative AI, means for the generative AI to generate a solution using the user's emotional information, and means for improving the generative AI's algorithm based on user feedback. This makes it possible to provide appropriate solutions that take the user's emotional state into consideration and to improve the performance of the generative AI based on feedback.

[1612] "User" means an individual who utilizes the System to enter their private problems and obtain solutions.

[1613] "Private issues" refers to specific problems or concerns that the user has personally.

[1614] "Generative AI" refers to artificial intelligence models that generate solutions based on user input.

[1615] "Solutions" refer to the specific advice or suggestions that generative AI provides to users about their problems.

[1616] "Emotion engine" refers to a system component that analyzes the user's emotional state and provides the results to generative AI.

[1617] "Feedback" refers to information that a user provides to the system about the effectiveness and impressions of the proposed solution.

[1618] An "algorithm" refers to the set of computational steps or rules that generative AI uses to generate solutions.

[1619] The "server" refers to a central processing unit that receives user input, works with generative AI and emotion engines to generate solutions, and presents them to the user.

[1620] "Terminal" means the device through which a User enters a problem and receives a solution.

[1621] This invention is a system that allows users to provide their private problems as text input to the system, which then generates solutions to those problems. The system combines generative AI and an emotion engine to provide solutions that take into account the user's emotional state.

[1622] Users use devices such as smartphones or PCs to input personal problems in text format. For example, they can input a specific problem such as, "I'm having trouble communicating with my section leader during my weekend brass band activities."

[1623] The device sends the problem entered by the user to the server. The server passes the received text to a generative AI, which generates a solution. OpenAI's GPT-4 can be used as the generative AI. The generative AI generates a solution to the user's problem and provides specific advice, such as, "To improve communication with your part-time leader, it is effective to clearly communicate the specific problem and work together to find a solution."

[1624] The server sends the generated solution to the device, which then presents it to the user. The user reviews the presented solution and inputs its effectiveness as feedback into the device. The device then sends feedback from the user to the server. The server receives this feedback and uses it to improve the solution-generating ability of the generative AI.

[1625] Additionally, the emotion engine analyzes the user's emotional state. For example, if the user has strong emotions about a problem, the emotion engine provides that information to the generative AI, which then uses this emotional information to generate a more appropriate solution.

[1626] As a concrete example, if a user inputs the problem, "I'm having trouble communicating with the section leader during my weekend brass band activities," the following prompt sentence will be input to the generative AI.

[1627] Example prompt sentence:

[1628] A user is having trouble communicating with the section leader during weekend band activities. Please provide a concrete solution to this problem.

[1629] The generative AI generates a solution based on this prompt and provides advice such as the following:

[1630] To improve communication with your part-time leader, it is effective to clearly communicate specific problems and work together to find solutions. It is also recommended to hold regular meetings to create a forum for exchanging opinions with each other.

[1631] This solution is presented to the user, who then provides feedback on its effectiveness to the system, which then uses this feedback to improve the performance of the generative AI.

[1632] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1633] Step 1:

[1634] The user enters the problem.

[1635] Users enter their problem into a text input field displayed on the screen of their smartphone or computer. For example, they might enter, "I'm having trouble communicating with the section leader during my weekend brass band activities." The input data is in text format.

[1636] Step 2:

[1637] The device sends input to the server.

[1638] The terminal sends the text data entered by the user to the server as an HTTP request. When sending, the data is converted to JSON format. The input is the user's text data, and the output is the JSON data sent to the server.

[1639] Step 3:

[1640] The server sends a prompt to the generative AI.

[1641] The server analyzes the received JSON data and generates a prompt to send to the generative AI. The generated prompt is sent to the generative AI as an API request. The input is JSON data, and the output is the prompt.

[1642] Step 4:

[1643] Generative AI generates solutions.

[1644] Generative AI (for example, OpenAI's GPT-4) generates a solution based on the prompt received from the server. The generated solution is returned to the server as an API response. The input is the prompt, and the output is the solution text.

[1645] Step 5:

[1646] The server sends the solution to the device.

[1647] The server analyzes the solution received from the generative AI and converts it into a format for presentation to the user. The converted data is sent to the device as an HTTP response. The input is the text of the solution, and the output is the data sent to the device.

[1648] Step 6:

[1649] The terminal presents a solution to the user.

[1650] The terminal displays the solution received from the server on the screen. The user checks the solution displayed on the screen and decides whether to execute it. The input is the data from the server, and the output is the solution presented to the user.

[1651] Step 7:

[1652] The user enters feedback.

[1653] The user enters specific impressions and results in a field for entering feedback about the effectiveness of the solution. For example, the user might enter "Communication with the part leader has improved." The input is the feedback text, and the output is the data sent to the terminal.

[1654] Step 8:

[1655] The device sends the feedback to the server.

[1656] The terminal sends the feedback received from the user to the server again as an HTTP request. When sending, the data is converted to JSON format again. The input is the feedback text, and the output is the JSON data sent to the server.

[1657] Step 9:

[1658] The server improves the generative AI based on the feedback.

[1659] The server analyzes the received feedback and uses it as data to improve the generative AI algorithm, making future solution generation more appropriate and effective. The input is the feedback data, and the output is an improved generative AI algorithm.

[1660] (Application example 2)

[1661] Next, a description will be given of Application Example 2 of Form 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."

[1662] Conventional security services have difficulty providing appropriate solutions to specific problems users face. Furthermore, they lack a mechanism for providing solutions that take into account the user's emotional state, making it impossible to reduce user anxiety and stress. Furthermore, they lack a mechanism for effectively utilizing user feedback to improve solutions. To address these issues, a system is needed that provides appropriate solutions that take into account the user's specific problems and emotional state, and that continuously improves solutions based on feedback.

[1663] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1664] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, emotion engine means for analyzing the user's emotional state, means for providing the generative AI with emotion information obtained by the emotion engine, and means for the generative AI to generate a solution using the emotion information. This makes it possible to provide an appropriate solution that takes into account the user's specific problem and emotional state, and to continuously improve the solution based on feedback.

[1665] "User's private problems" refer to the specific troubles and concerns that individuals face in their daily lives or in specific situations.

[1666] "Generative AI" refers to artificial intelligence that generates solutions to problems provided by users.

[1667] "Means for presenting solutions to users" refers to methods or devices for communicating solutions generated by generative AI to users.

[1668] "Means for receiving user feedback" refers to a method or device for collecting user opinions and evaluations of the solution provided.

[1669] An "emotion engine" is a system or software that analyzes a user's emotional state and provides the results to generative AI.

[1670] "Emotional Information" means data regarding a user's emotional state analyzed by the Emotion Engine.

[1671] "Security-related issues" refer to specific problems or concerns users face regarding safety and crime prevention.

[1672] "Improving solutions based on feedback" means improving the quality of the solutions provided by generative AI by reflecting opinions and evaluations from users.

[1673] A system for implementing this invention includes a generative AI that receives a user's private problem as input and generates a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, an emotion engine that analyzes the user's emotional state, means for providing the generative AI with emotion information obtained by the emotion engine, and means for the generative AI to generate a solution using the emotion information.

[1674] Hardware and software used

[1675] Hardware: Smartphone

[1676] Software: Python, OpenAI API, EmotionEngine library

[1677] System processing overview

[1678] 1. Receiving user input: The user uses their smartphone to provide text input about a specific security issue, such as, "I've been seeing a lot of suspicious people around my house lately, and it's making me feel uneasy."

[1679] 2. Emotional state analysis: The emotion engine analyzes the user's input text and identifies the user's emotional state, for example recognizing emotions such as anxiety or fear.

[1680] 3. Sending a prompt to the generative AI: A prompt containing the emotional information obtained by the emotion engine and the user's problem is sent to the generative AI. An example of a prompt is as follows:

[1681] User's emotional state: Anxiety

[1682] User Problem: I've been seeing a lot of suspicious people around my house lately and it's making me feel uneasy.

[1683] Please provide a solution.

[1684] 4. Solution generation: Generative AI generates solutions based on the prompts, providing specific advice such as "Installing security cameras and sharing information with neighbors would be effective."

[1685] 5. Present the solution: The generated solution is presented to the user, who can check it on their smartphone screen.

[1686] 6. Receiving feedback: Users provide feedback on the solutions provided, including their opinions and ratings. This feedback is sent to the system and used to improve the generative AI's ability to generate solutions.

[1687] Specific examples

[1688] If a user inputs, "I've been seeing a lot of suspicious people around my house recently and I'm worried," the emotion engine will recognize the user's anxiety, and the generative AI will provide specific advice such as, "It would be effective to install security cameras and share information with neighbors." This solution is presented to the user, and the user provides feedback on its effectiveness to the system.

[1689] In this way, it is possible to provide appropriate solutions that take into account the user's specific problem and emotional state, and to continuously improve the solutions based on feedback.

[1690] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1691] Step 1:

[1692] The user uses their smartphone to provide a specific security problem as text input.

[1693] Input: User's problem text (e.g., "I've been seeing a lot of suspicious people around my house lately and it's making me feel uneasy.")

[1694] Output: The user's problem text is sent to the system.

[1695] Specific actions: The user opens the application on their smartphone, enters a problem into the text input field, and presses the submit button.

[1696] Step 2:

[1697] The server receives the user's input text and sends it to the emotion engine.

[1698] Input: User's problem text

[1699] Output: Text sent to the sentiment engine

[1700] Specific operation: The server receives the user's input text and sends the text to the emotion engine's API.

[1701] Step 3:

[1702] The emotion engine analyzes the user's input text and identifies their emotional state.

[1703] Input: User's problem text

[1704] Output: User's emotional state (e.g., "anxious")

[1705] What it does: The sentiment engine uses text analysis algorithms to identify sentiment in text and determine emotional states.

[1706] Step 4:

[1707] The server combines the emotional information obtained from the emotion engine with the user's question text and sends a prompt to the generative AI.

[1708] Input: User's problem text, sentiment information

[1709] Output: Prompt sent to the generative AI

[1710] Specific operation: The server combines the emotion information with the user's question text to generate a prompt sentence like the following:

[1711] User's emotional state: Anxiety

[1712] User Problem: I've been seeing a lot of suspicious people around my house lately and it's making me feel uneasy.

[1713] Please provide a solution.

[1714] This prompt text is sent to the generative AI API.

[1715] Step 5:

[1716] Generative AI generates solutions based on prompts.

[1717] Input: prompt statement

[1718] Output: Solution text (e.g., "Installing security cameras and sharing information with neighbors would be effective.")

[1719] What it does: The generative AI analyzes the prompt and uses its internal model to generate an appropriate solution.

[1720] Step 6:

[1721] The server presents the generated solution to the user.

[1722] Input: Solution text

[1723] Output: The solution displayed on the user's phone

[1724] Specific operation: The server sends the solution text received from the generative AI to the user's smartphone, and the application displays the solution on the screen.

[1725] Step 7:

[1726] Users can provide feedback on the solutions provided.

[1727] Input: User feedback text (e.g., "This solution was helpful")

[1728] Output: The feedback text is sent to the system.

[1729] Specific action: The user uses a smartphone application to enter feedback on the solution and presses the submit button.

[1730] Step 8:

[1731] The server receives feedback from users and uses it to improve the generative AI's ability to generate solutions.

[1732] Input: User feedback text

[1733] Output: An improved generative AI model

[1734] Specific operation: The server receives the feedback text, stores it as learning data for the generative AI, and uses it to retrain the model.

[1735] 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.

[1736] 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> ) 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.

[1737] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1738] 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.

[1739] [Fourth embodiment]

[1740] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1741] 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.

[1742] 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).

[1743] 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.

[1744] 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.

[1745] 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).

[1746] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1747] 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.

[1748] 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.

[1749] 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.

[1750] 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.

[1751] 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.

[1752] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1753] "Example 1"

[1754] In one embodiment of the present invention, a user provides a system with a personal problem as text input. This problem may be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend brass band activities." The system receives this input and uses generative AI to generate a solution. The generated solution may be specific advice, such as, "To improve communication with your section leader, it would be effective to clearly communicate the specific problem and work together to come up with a solution." This solution is presented to the user, who provides feedback on its effectiveness to the system. The system receives this feedback and improves the generative AI's ability to generate solutions.

[1755] "Example 2"

[1756] In one embodiment of the present invention, a user provides a system with a personal problem as text input. This problem may be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend brass band activities." The system receives this input and uses generative AI to generate a solution. The generated solution may be specific advice, such as, "To improve communication with your section leader, it would be effective to clearly communicate the specific problem and work together to come up with a solution." This solution is presented to the user, who provides feedback on its effectiveness to the system. The system receives this feedback and improves the generative AI's ability to generate solutions.

[1757] The processing flow of each embodiment will be described below.

[1758] "Example 1"

[1759] Step 1: The user provides the system with a text entry about their personal problem. This problem can be a specific one, such as, "I'm having trouble communicating with my section leader during my weekend band activities."

[1760] Step 2: The system receives input from the user and uses generative AI to generate solutions. The generated solutions are specific advice such as, "To improve communication with the part-time leader, it is effective to clearly communicate the specific problems and work together to find solutions."

[1761] Step 3: The system presents the generated solution to the user, who then tries it out and provides feedback to the system on its effectiveness.

[1762] Step 4: The system receives feedback from the user and improves the generative AI's ability to generate solutions, thereby improving the accuracy of solutions to the same or similar problems.

[1763] Example 1

[1764] Next, a description will be given of Example 1 of Form 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."

[1765] Conventional systems have difficulty providing appropriate solutions to users' private problems. They also lack a mechanism for evaluating the effectiveness of the solutions provided and reflecting this in future solution generation. This has led to the issue of lowering users' satisfaction with the solutions they receive.

[1766] 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.

[1767] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for generating a prompt sentence suitable for the generative AI means, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, and means for reflecting the received feedback in the generative AI means. This makes it possible to provide an appropriate solution to the user's problem and improve the solution based on feedback on its effectiveness.

[1768] "User" means an individual who utilizes the System to enter their private problem and receive a solution.

[1769] "Private issues" refer to specific challenges or difficulties that users face personally.

[1770] "Generative AI means" refers to the function of artificial intelligence that generates appropriate solutions to private problems input by users.

[1771] A "prompt sentence" refers to an instruction sentence that conveys the content of the problem to a generative AI means.

[1772] "Solutions" refer to specific advice or suggestions that generative AI methods provide to users for their private problems.

[1773] "Presentation means" refers to the functionality for displaying the generated solution to the user.

[1774] "Feedback" refers to information provided by the user to the system regarding the effectiveness and impressions of the proposed solution.

[1775] "Means of reflection" refers to the function of incorporating feedback received from users into generative AI means and using them to generate solutions in the future.

[1776] This invention relates to a system that allows users to input their own private problems and generate solutions to those problems. The system receives the user's input, generates solutions using a generative AI model, and presents them to the user. It also receives feedback from the user and improves the performance of the generative AI model.

[1777] Hardware and software used

[1778] The system uses the following hardware and software:

[1779] Device: The device through which a user enters their private problem and receives a solution. Examples include computers, smartphones, and tablets.

[1780] Server: A computer system that receives user input, sends prompts to the generative AI model, and sends the generated solutions to the device.

[1781] Generative AI model: An artificial intelligence model that generates solutions to user problems. Examples include OpenAI's GPT-4.

[1782] Data processing and calculation

[1783] The user uses the device to input a private problem in text format. For example, they can input a specific problem such as, "I'm having trouble communicating with the section leader during my weekend brass band activities." The device then sends this input to the server.

[1784] The server generates a prompt to pass the received text input to the generative AI model. For example, it generates a prompt such as, "The user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to solve this problem."

[1785] The generative AI model generates solutions based on prompts, such as advice like, "To improve communication with the part-time leader, it would be effective to clearly communicate the specific problems and work together to find solutions."

[1786] The generated solution is sent from the server to the terminal and presented to the user. The user checks the presented solution and provides feedback on its effectiveness to the server via the terminal.

[1787] The server receives feedback from users and uses it to improve the generative AI model's ability to generate solutions, allowing the system to continuously learn and provide more effective solutions.

[1788] Specific examples

[1789] For example, a user enters the following problem:

[1790] "I'm having trouble communicating with the section leader during weekend band activities."

[1791] Example prompts for generative AI models:

[1792] "A user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to resolve this issue."

[1793] An example of a generated solution:

[1794] "In order to improve communication with section leaders, it is effective to clearly communicate specific problems and work together to find solutions. For example, you could set up regular meetings to provide an opportunity for frank discussion of each other's opinions."

[1795] In this way, the system provides solutions to users' problems and improves the performance of the generative AI model based on user feedback.

[1796] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1797] Step 1:

[1798] A user uses a terminal to enter a private problem.

[1799] Specifically, the user inputs a problem in text format into the terminal interface, such as "I'm having trouble communicating with the section leader during my weekend brass band activities."

[1800] Input: User's private information (text data)

[1801] Output: Text data entered into the terminal

[1802] Step 2:

[1803] The terminal transmits the input text data to the server.

[1804] Specifically, the terminal encrypts the text data entered by the user and transmits it to the server.

[1805] Input: Text data entered into the terminal

[1806] Output: Encrypted text data sent to the server

[1807] Step 3:

[1808] The server analyzes the text data it receives and generates a prompt sentence suitable for the generative AI model.

[1809] Specifically, the server analyzes the text data and generates a prompt that reads, "The user is having trouble communicating with the section leader during weekend band activities. Please provide specific advice on how to solve this problem."

[1810] Input: Encrypted text data sent to the server

[1811] Output: A prompt suitable for a generative AI model

[1812] Step 4:

[1813] The server sends a prompt to the generative AI model.

[1814] Specifically, the server sends the generated prompt sentence to the generative AI model.

[1815] Input: A prompt suitable for a generative AI model

[1816] Output: The prompt sent to the generative AI model

[1817] Step 5:

[1818] A generative AI model generates a solution based on the prompt.

[1819] Specifically, the generative AI model analyzes the prompt and generates a solution such as, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and think of solutions together."

[1820] Input: A prompt sent to the generative AI model

[1821] Output: Generated solution (text data)

[1822] Step 6:

[1823] The server sends the generated solution to the terminal.

[1824] Specifically, the server encrypts the solution received from the generative AI model and sends it to the device.

[1825] Input: Generated solution (text data)

[1826] Output: The encrypted solution sent to the terminal.

[1827] Step 7:

[1828] The terminal presents a solution to the user.

[1829] Specifically, the device decrypts the solution received from the server and displays it to the user, who then checks the solution on the screen.

[1830] Input: The encrypted solution sent to the terminal

[1831] Output: The solution presented to the user

[1832] Step 8:

[1833] The user provides feedback on the effectiveness of the proposed solution.

[1834] Specifically, the user checks the presented solution and inputs feedback such as "This advice was very helpful" into the terminal interface.

[1835] Input: User feedback (text data)

[1836] Output: Feedback typed into the terminal

[1837] Step 9:

[1838] The device sends the feedback to the server.

[1839] Specifically, the terminal encrypts the feedback input by the user and transmits it to the server.

[1840] Input: Feedback entered into the device

[1841] Output: Encrypted feedback sent to the server

[1842] Step 10:

[1843] The server reflects the feedback in the generative AI model.

[1844] Specifically, the server incorporates the received feedback into the generative AI model and uses it to generate solutions from the next time onwards.

[1845] Input: Encrypted feedback sent to the server

[1846] Output: Feedback reflected in the generative AI model

[1847] (Application example 1)

[1848] Next, a description will be given of Application Example 1 of Embodiment 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."

[1849] Conventional generative AI systems focused on providing solutions to users' private problems, but lacked the ability to provide solutions to specific security issues. Furthermore, they lacked mechanisms for improving solutions based on user feedback. This made it difficult for users to receive prompt and accurate advice on security issues.

[1850] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes generative AI means that receives a user's private problem as input and generates a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving feedback from the user, means for receiving a security problem as input and generating a solution to the problem, and means for presenting the generated solution to the user. This enables the user to receive prompt and accurate advice on specific security problems.

[1851] "User" means any person or entity that uses the System to enter private or security-related issues.

[1852] "Private issues" are problems or challenges that users face personally, such as issues related to relationships or daily life.

[1853] "Generative AI" is an artificial intelligence system that generates solutions to problems input by users.

[1854] A "solution" is a specific piece of advice or suggestion that a generative AI provides to a user about a problem.

[1855] "Feedback" refers to the evaluation or opinion that a user gives of the solution provided by the generative AI.

[1856] "Security issues" are specific safety and security issues faced by users.

[1857] "Presentation means" refers to a method or device for displaying the solution generated by generative AI to the user.

[1858] "Means for receiving" refers to a method or device by which the system receives feedback from the user.

[1859] The system for implementing this invention is a system that uses generative AI to solve problems related to users' privacy and security. Specific embodiments of this system are described below.

[1860] System Configuration

[1861] The system mainly consists of the following components:

[1862] 1. User device: A device such as a smartphone or computer that users use to enter questions.

[1863] 2. Server: A central system for hosting the generative AI and processing input from users.

[1864] 3. Generative AI: An artificial intelligence model that generates solutions to user problems, such as OpenAI's GPT-3.

[1865] 4. Database: A storage system for saving user input and feedback.

[1866] Program processing

[1867] The server processes the data as follows:

[1868] 1. Receiving user input: Receive private or security issues in text format sent from the user's device.

[1869] 2. Generating a solution using generative AI: The received problem is input into a generative AI, which generates a solution. OpenAI's GPT-3 is used as the generative AI.

[1870] 3. Presenting the solution: The generated solution is sent to the user's terminal and presented to the user.

[1871] 4. Receiving feedback: Receiving feedback from users and storing it in a database.

[1872] 5. Improve the AI ​​model: Use the feedback received to improve the generative AI's ability to generate solutions.

[1873] Hardware and software used

[1874] Hardware: smartphones, PCs, servers

[1875] Software: Python, OpenAI API, database management system (e.g., MySQL)

[1876] Specific examples

[1877] If a user types in "I've seen suspicious people around my house recently," the server sends this input to a generative AI, which then generates a solution, such as "Installing security cameras and sharing information with neighbors would be effective," and presents it to the user.

[1878] Prompt Sentence Examples

[1879] User security issue: I've recently seen some suspicious people around my house.

[1880] Please provide a solution.

[1881] In this way, users can get fast and accurate advice on specific security issues.

[1882] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1883] Step 1:

[1884] The user terminal receives input from the user. Specifically, the user inputs private and security-related issues in text format using a smartphone or PC. The input text data is sent to the server.

[1885] Input: Text data entered by the user (e.g., "I've been seeing some suspicious people around my house lately.")

[1886] Output: Text data sent to the server

[1887] Step 2:

[1888] The server receives the text data sent from the user's device and generates a prompt sentence to be input to the generative AI. The prompt sentence is a concrete description of the user's problem.

[1889] Input: Text data sent by the user

[1890] Output: A prompt to be input to the generative AI (e.g., "User's security problem: I've been seeing suspicious people around my house recently. Please provide a solution.")

[1891] Step 3:

[1892] The server sends a prompt to a generative AI (e.g., OpenAI's GPT-3) to generate a solution. The generative AI generates an appropriate solution in text format based on the prompt.

[1893] Input: Prompt sentence to input to the generative AI

[1894] Output: The solution generated by the generative AI (e.g., "Installing security cameras and sharing information with neighbors would be effective.")

[1895] Step 4:

[1896] The server sends the generated solution to the user's device and presents it to the user, who can then check the solution on their smartphone or computer screen.

[1897] Input: A solution generated by a generative AI

[1898] Output: The solution sent to the user's device

[1899] Step 5:

[1900] The user terminal receives feedback from the user, who inputs his / her evaluation and opinion on the provided solution in text format and sends it to the server.

[1901] Input: User-entered feedback (e.g., "I think installing security cameras is a good idea.")

[1902] Output: Feedback sent to the server

[1903] Step 6:

[1904] The server receives feedback from users and stores it in a database, which is used to improve the generative AI's ability to generate solutions.

[1905] Input: Feedback submitted by the user

[1906] Output: Feedback stored in a database

[1907] Step 7:

[1908] The server retrains the generative AI model based on the saved feedback, improving its ability to generate solutions, which will result in more accurate solutions in future.

[1909] Input: Feedback stored in the database

[1910] Output: Improved generative AI model

[1911] By following these steps, users can get fast and accurate advice on specific security issues.

[1912] Example 2

[1913] Next, a description will be given of Example 2 of Form 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."

[1914] Conventional systems have difficulty providing appropriate solutions to users' private problems. Furthermore, they lack a mechanism for evaluating the effectiveness of the solutions provided and reflecting this in future solution generation, making it difficult to increase user satisfaction. Furthermore, they lack the ability to generate appropriate prompts for the user's specific problem, which can result in a decline in the quality of the solutions generated.

[1915] 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.

[1916] In this invention, the server includes a generative artificial intelligence that receives a user's private problem as input and generates a solution to the problem, a means for generating a prompt sentence suitable for the generative artificial intelligence, a means for presenting the solution generated by the generative artificial intelligence to the user, a means for receiving feedback from the user, and a means for improving the solution generation ability of the generative artificial intelligence based on the user's feedback. This makes it possible to provide an appropriate solution to the user's specific problem, evaluate its effectiveness, and reflect it in future solution generation.

[1917] "User" means an individual who utilizes the System to enter their private problem and receive a solution.

[1918] "Private issues" refers to specific problems or concerns that the user has personally.

[1919] "Generative AI" refers to artificial intelligence techniques that generate solutions based on user input.

[1920] A "prompt sentence" refers to an instruction sentence that is input to a generative artificial intelligence to generate an appropriate solution.

[1921] "Solutions" refer to the specific advice or suggestions that generative artificial intelligence provides to users about their problems.

[1922] "Feedback" refers to information that a user reports to the system after trying out a proposed solution, including its effectiveness and impressions.

[1923] "Server" refers to a computer system that receives user input data, generates solutions using generative artificial intelligence, and presents them to the user.

[1924] "Device" refers to the device through which a User enters their problem, receives a solution, and provides feedback.

[1925] The present invention is a system in which a user provides a text input of their private problem to the system, and a solution to the problem is generated. A specific embodiment of this system will be described below.

[1926] Hardware and software used

[1927] Hardware

[1928] Server: A high-performance computer system that runs generative artificial intelligence and processes user input data.

[1929] Device: The device that a user uses to enter their problem, receive a solution, or provide feedback. This could be a smartphone, tablet, or computer.

[1930] software

[1931] Generative artificial intelligence: For example, using advanced natural language processing techniques such as OpenAI's GPT-4.

[1932] Encryption protocol: The SSL / TLS protocol is used to securely transmit user input data to the server.

[1933] Data processing and calculation

[1934] User problem input

[1935] Users enter their personal problems into a text box on the device, for example, "I'm having trouble communicating with my section leader during my weekend band activities."

[1936] Sending input data

[1937] The terminal encrypts the text data entered by the user using the SSL / TLS protocol and sends it to the server.

[1938] Problem analysis and prompt generation

[1939] The server analyzes the received text data using natural language processing (NLP) technology and generates a prompt suitable for generative artificial intelligence. For example, if the user input is "I'm having trouble communicating with the section leader during weekend band activities," the prompt would be "The user is having trouble communicating with the section leader during weekend band activities. Please clearly explain the specific problem and provide advice so we can work together to find a solution."

[1940] Solution Generation

[1941] The server inputs the prompt into the generative AI, which then generates a solution. The generative AI then generates appropriate advice based on the prompt. For example, the generated advice might be, "To improve communication with the part leader, it is effective to clearly communicate the specific problems and work together to come up with solutions. It would be a good idea to have a private discussion with the part leader before the next rehearsal, share the specific problems, and set aside time to think about solutions together."

[1942] Proposing a solution

[1943] The server sends the generated solution to the terminal, which displays it to the user, who can then check and try out the solution.

[1944] Collecting feedback

[1945] After trying out the proposed solutions, users can enter specific feedback into the device about their effectiveness, such as, "The discussion with the part leader went well, and communication has improved."

[1946] Model Improvements

[1947] The device sends user feedback to the server, which passes it on to the generative AI and uses it to improve the model's ability to generate solutions, resulting in more effective solutions in future.

[1948] Specific examples

[1949] Example user input

[1950] "I'm having trouble communicating with the section leader during weekend band activities."

[1951] Example prompts for generative AI models

[1952] "A user is having trouble communicating with the section leader during their weekend band activities. Please clearly explain the specific problem and provide advice on how we can work together to find a solution."

[1953] Example of a generated solution

[1954] "To improve communication with section leaders, it is effective to clearly communicate specific problems and work together to find solutions. It is a good idea to have a private discussion with section leaders before the next rehearsal, share specific problems, and set aside time to think about solutions together."

[1955] This way, users receive concrete advice and can try it out for themselves, and feedback helps the system improve and provide more effective solutions.

[1956] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1957] Step 1:

[1958] The user enters their personal problem into the text box on the device. For example, they might enter, "I'm having trouble communicating with my section leader during my weekend brass band activities." The input data is in text format, and the user can proceed to the next step by clicking the "Submit" button.

[1959] Step 2:

[1960] The terminal encrypts the text data entered by the user using the SSL / TLS protocol and sends it to the server. The input data is encrypted text data and sent securely to the server. The server decrypts the received data and proceeds to the next step.

[1961] Step 3:

[1962] The server analyzes the received text data using natural language processing (NLP) technology. The input data is text data containing the user's problem, and the content of the problem is extracted as a result of the analysis. Based on this analysis result, the server generates a prompt suitable for generative AI. For example, a generated prompt might read, "The user is having trouble communicating with the section leader during weekend brass band activities. Please clearly explain the specific problem and provide advice so we can work together to find a solution."

[1963] Step 4:

[1964] The server inputs a prompt into the generative AI and generates a solution. The input data is the prompt, and the generative AI generates appropriate advice based on this. For example, a solution might be generated that reads, "To improve communication with the part leader, it would be effective to clearly communicate the specific problems and work together to come up with solutions. It would be a good idea to have a private discussion with the part leader before the next rehearsal, share the specific problems, and set aside time to think about solutions together."

[1965] Step 5:

[1966] The server sends the generated solution to the terminal, and the input data is the generated solution, which the terminal displays to the user, who can then check the presented solution and try it out.

[1967] Step 6:

[1968] After trying out the proposed solution, the user enters feedback about its effectiveness into the device. For example, specific feedback such as "The discussion with the part leader went well, and communication has improved." The input data is feedback information, and the user can proceed to the next step by clicking the "Submit" button.

[1969] Step 7:

[1970] The device sends the user's feedback to the server. The input data is feedback information, which the server receives and analyzes. The server then passes the feedback information to the generative AI and uses it to improve the model's ability to generate solutions, making future solutions more effective.

[1971] (Application example 2)

[1972] Next, a description will be given of Application Example 2 of Form 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."

[1973] With conventional security services, it was difficult to quickly provide appropriate solutions to the specific security problems faced by users. Furthermore, there was a lack of a mechanism for evaluating the effectiveness of the solutions provided and for continuous improvement, making it difficult to improve users' security awareness and the quality of countermeasures. This led to the issue of users being unable to use the digital environment with peace of mind.

[1974] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1975] In this invention, the server includes generative AI means for receiving a user's private problem as input and generating a solution to the problem, means for presenting the solution generated by the generative AI to the user, means for receiving user feedback, means for receiving a security problem as input and generating a solution to the problem, means for presenting the generated solution to the user, and means for improving the solution generation ability of the generative AI based on user feedback. This makes it possible to provide quick and appropriate solutions to specific security problems faced by users and to evaluate their effectiveness and continuously improve them.

[1976] "User" means any person or entity that uses the System to enter private or security-related issues.

[1977] "Private issues" are specific problems or challenges that users face personally.

[1978] "Generative AI" is a type of artificial intelligence that generates solutions to problems input by the user.

[1979] A "solution" is a specific piece of advice or countermeasure that the generative AI provides to the user for their problem.

[1980] "Feedback" is information about the results and effectiveness of a user's attempt at a provided solution.

[1981] "Security issues" are specific issues users face regarding safety and protection in the digital environment.

[1982] "The solution generation ability of generative AI" refers to the ability of generative AI to generate appropriate solutions to users' problems.

[1983] "Presentation means" refers to a method or device for displaying or notifying the user of the solution generated by the generative AI.

[1984] "Means for receiving" refers to a method or device by which the system obtains feedback from the user.

[1985] "Means for improvement" are methods or devices for improving the solution-generating capabilities of generative AI based on user feedback.

[1986] As an embodiment of this invention, we will explain how to install a security advisor AI system on a smartphone. In this system, a user inputs a security problem, and a generative AI generates a solution and presents it to the user. Furthermore, feedback from the user is received, and the generative AI's ability to generate a solution is improved.

[1987] Hardware and software used

[1988] Hardware: Smartphone

[1989] Software: Python, OpenAI API

[1990] System configuration

[1991] 1. Obtaining user input: The user inputs text into a smartphone application. For example, they input a specific problem, such as, "My home Wi-Fi has been unstable recently, and I'm worried about security."

[1992] 2. Prompt generation: Based on the user's input, a prompt is generated to be passed to the generative AI. For example, it could be something like, "User's security problem: My home Wi-Fi has been unstable recently, so I'm worried about security. Please provide a solution."

[1993] 3. AI solution generation: Using OpenAI's API, a generative AI (e.g., GPT-3) generates a solution. The generated solution is specific advice such as, "We recommend updating your Wi-Fi router's firmware and setting a strong password."

[1994] 4. Present the solution: The generated solution is presented to the user and displayed on the smartphone application.

[1995] 5. Get feedback: Users try the solution and provide feedback on its effectiveness, such as, "My Wi-Fi is now more stable and secure."

[1996] 6. Improving the Generative AI: Based on user feedback, we will improve the generative AI's ability to generate solutions, which will result in better and more effective solutions in future.

[1997] Specific examples

[1998] User input: "My home Wi-Fi has been unstable lately and I'm worried about security."

[1999] Example prompt: "User security issue: My home Wi-Fi has been unstable lately and I'm worried about security. Please provide a solution."

[2000] AI advice: "We recommend updating your Wi-Fi router's firmware and setting a strong password."

[2001] User feedback: "Wi-Fi is now more stable and secure."

[2002] In this way, it is possible to provide quick and appropriate solutions to specific security problems faced by users, evaluate their effectiveness and continuously improve them.

[2003] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2004] Step 1:

[2005] The user launches an application on their smartphone and enters a security problem via text.

[2006] Input: A specific security issue entered by the user (e.g., "My home Wi-Fi has been unstable lately, and I'm worried about security.")

[2007] Output: The text entered by the user

[2008] Specific behavior: The user enters a problem into the application's text input field and presses the submit button.

[2009] Step 2:

[2010] The device receives user input and generates a prompt sentence to be passed to the generative AI.

[2011] Input: User-entered text

[2012] Output: Generated prompt (e.g. "User's security problem: My home Wi-Fi has been unstable recently and I'm worried about security. Please provide a solution.")

[2013] What it does: The application formats the user's input text and generates a prompt suitable for generative AI.

[2014] Step 3:

[2015] The server calls the generative AI and generates a solution using the generated prompt sentence as input.

[2016] Input: Generated prompt statement

[2017] Output: The solution generated by the generative AI (e.g., "It is recommended that you update your Wi-Fi router's firmware and set a strong password.")

[2018] Specific operation: The server uses the OpenAI API to send a prompt to a generative AI (e.g., GPT-3) and obtain a solution.

[2019] Step 4:

[2020] The terminal presents the generated solution to the user.

[2021] Input: A solution generated by a generative AI

[2022] Output: The solution presented to the user

[2023] What happens: The application displays the solution on the user's screen.

[2024] Step 5:

[2025] The user tries the proposed solution and inputs feedback on its effectiveness.

[2026] Input: Feedback about the effectiveness of the solution the user tried (e.g., "My Wi-Fi is now more stable and secure.")

[2027] Output: User feedback text

[2028] Specific behavior: The user enters the effect in the application's feedback input field and presses the submit button.

[2029] Step 6:

[2030] The server receives feedback from users and improves the generative AI's ability to generate solutions.

[2031] Input: User feedback text

[2032] Output: Improved solution generation capabilities of generative AI

[2033] Specific operation: The server analyzes the feedback data, incorporates it as learning data for the generative AI, and reflects it in generating solutions from the next time onwards.

[2034] 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.

[2035] "Example 1"

[2036] As one embodiment of the present invention, a system incorporating an emotion engine is provided. The system includes a generative AI th...

Claims

1. a first means for accepting input of at least one of a private concern and a security concern in text form by a user; second means for generating a prompt for outputting a solution to the user's problem based on text data indicated in the user's input; a third means for inputting the generated prompt sentence into a generative AI model to generate the solution; A fourth means for transmitting the generated solution to a terminal of the user; A system including:

2. The first means receives an input of feedback from the user regarding the generated solution; A fifth means for retraining the generative AI model based on the feedback to improve the ability of the generative AI model to generate the solution. The system of claim 1 .

3. a sixth means for analyzing an emotional state of the user from text data indicated in the input by the user using an emotion engine; The second means adjusts the prompt sentence based on an emotional state of the user; and The third means inputs the adjusted prompt sentence into the generative AI model to generate the solution suitable for the emotional state of the user.

3. A system according to claim 1 or 2.

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