System

Abstract

A system is provided.SOLUTION: A system comprising: means for users to input questions to terminals; means for terminals to send the questions to a server; means for the server to pass the questions to a generative AI model to generate answers; means for the server to send the generated answers to the terminals; and means for the terminals to display the answers received from the server to the users.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] As the elderly population grows, more and more people are facing issues related to end-of-life planning and inheritance, but the barrier to receiving professional support for these issues is high. Furthermore, many people do not know how to begin preparing, and as a result, they put off taking action. This situation exacerbates the problem and causes mental stress. The purpose of this invention is to provide an environment where people can easily consult about these issues and receive prompt, specific advice, thereby smoothly progressing with end-of-life planning and inheritance planning. [Means for solving the problem]

[0005] The present invention provides a system that solves the above-mentioned problems by combining the following means:

[0006] A means for a user to input a question into the terminal;

[0007] means for the terminal to send a query to the server;

[0008] A means for the server to pass questions to a generative AI model to generate answers;

[0009] means for the server to transmit the generated response to the terminal;

[0010] The system includes a means for displaying the answer received by the terminal from the server to the user.

[0011] This system allows users to input questions about end-of-life planning and inheritance into their device and receive quick answers using a generative AI model. This provides a significant boost in acquiring the necessary knowledge before consulting a specialist and taking appropriate measures. The user interface also makes it easy to input questions, and natural language processing technology is used to provide high-quality answers.

[0012] "User" refers to a person who uses the system to enter questions and receive answers.

[0013] A "terminal" refers to a device used by a user, and mainly refers to a smartphone or personal computer.

[0014] "Questions" refer to inquiries about end-of-life planning and inheritance entered by users.

[0015] "Server" refers to a device or system that receives a question sent from a terminal, generates an answer using a generative AI model, and then returns the answer to the terminal.

[0016] A "generative AI model" refers to a model that uses natural language processing to generate appropriate answers to input questions.

[0017] "Answer" refers to a response generated by the server to a question using a generative AI model.

[0018] "Sending" refers to the act of sending data from a terminal to a server, or from a server to a terminal, sending a question or answer.

[0019] "Receiving" refers to the act of the server taking in a question from a terminal, or the terminal taking in a response from a server.

[0020] "Display" refers to the act of making the response received by the terminal visible to the user in a viewable format.

[0021] "User interface" refers to the operation screen and input form that users use when operating a device.

[0022] "Natural language processing technology" refers to technology that enables computers to understand and process human language. [Brief explanation of the drawings]

[0023] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0024] 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.

[0025] First, the terms used in the following description will be explained.

[0026] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 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.

[0034] 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).

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0044] The present invention provides a system that allows users to easily consult with others and receive prompt answers regarding matters related to end-of-life planning and inheritance, in response to the growing elderly population. The following describes in detail the mode for implementing this system.

[0045] overview

[0046] In this system, users input questions via their devices, which are then sent to a server. The server then passes the received questions to a generative AI model, which generates an appropriate answer. The generated answer is then sent back to the device, which then displays it to the user, allowing them to receive appropriate support.

[0047] Embodiment

[0048] 1. The user enters a question

[0049] Users use devices such as smartphones or personal computers to input questions into a dedicated user interface. For example, a question might be, "Please tell me how I should start regarding the inheritance of my house."

[0050] 2. The device sends a question to the server

[0051] After entering a question, the user clicks the send button, which causes the device to send the question to the server via an Internet connection as an HTTP request from the device to the server.

[0052] 3. The server passes the question to the generative AI model to generate an answer.

[0053] The server analyzes the received question and passes it to a generative AI model. This generative AI model uses natural language processing technology, for example, and generates an appropriate answer for the question. The generative AI model has the ability to understand the content of the question and extract an appropriate answer from a huge database.

[0054] 4. The server generates a response and sends it to the device.

[0055] The generated answer is sent from the server to the device, again via the Internet, where the data is formatted in a way that the device can receive it.

[0056] 5. The device displays the answer received from the server to the user.

[0057] The device displays the received answer to the user in a text box, pop-up window, or other format. The user can then decide what to do next based on the displayed answer.

[0058] Specific examples

[0059] For example, if a user types, "Please tell me how to get started on inheriting a house," the following steps will be executed:

[0060] 1. The user enters a question and clicks the submit button.

[0061] 2. The device sends this question to the server.

[0062] 3. The server receives the question and passes it to the generative AI model.

[0063] 4. The generative AI model analyzes the question and generates the answer, "The first step in inheriting a house is to understand the current state of your assets."

[0064] 5. The server sends this response to the terminal.

[0065] 6. The terminal displays the received response to the user.

[0066] In this way, the system of the present invention allows users to easily and quickly obtain useful advice regarding end-of-life planning and inheritance, enabling them to acquire the necessary knowledge before consulting with a specialist, and providing support for taking appropriate measures while reducing psychological burden.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] The user inputs a question using the user interface of the terminal. Specifically, the user inputs the question "Please tell me how to get started regarding inheriting a house" into the input form and clicks the submit button.

[0070] Step 2:

[0071] The device detects the click event of the submit button, obtains the entered question as data, and converts this data into an appropriate format (for example, JSON format).

[0072] Step 3:

[0073] The device sends the question data to the server. Specifically, it uses an HTTP POST request to send the question data to the specified endpoint on the server.

[0074] Step 4:

[0075] The server receives the HTTP request, analyzes the question data, extracts the question content from the received data, and prepares it as input for the generative AI model.

[0076] Step 5:

[0077] The server passes the question to the generative AI model and instructs it to generate an answer. The generative AI model used here (for example, one that utilizes natural language processing technology) generates an appropriate answer based on the given question.

[0078] Step 6:

[0079] The generative AI model processes the question and generates an answer, such as, "The first step in inheriting a home is to understand the current state of your assets."

[0080] Step 7:

[0081] The server receives the generated response and formats it as data to be sent to the device, again in an appropriate format such as JSON.

[0082] Step 8:

[0083] The server sends the generated response data to the terminal. Specifically, it returns the response data as an HTTP response.

[0084] Step 9:

[0085] The device analyzes the response data received from the server and displays it in the user interface. For example, a text box might say, "The first step in inheriting a house is to understand the current state of your assets."

[0086] Step 10:

[0087] The user views the answers displayed on their device, decides their next action, and can repeat the process again, if desired, by entering a more specific question.

[0088] In this way, a system is provided that allows users to easily and quickly obtain useful advice regarding end-of-life planning and inheritance.

[0089] Example 1

[0090] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0091] As the elderly population increases, there is a growing need for consultations regarding end-of-life planning and inheritance. However, there are limited ways to acquire the necessary knowledge before consulting a specialist, making it difficult for users to obtain sufficient information. In particular, there is a need for a means to receive prompt and appropriate support.

[0092] 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.

[0093] In this invention, the server includes: [means for a user to input a question to an information processing device;] [means for the information processing device to send the question to an information processing system; and] [means for the information processing system to pass the question to a generative AI model and generate an answer.] This enables [users to receive prompt and appropriate advice and acquire the necessary knowledge before consulting an expert.]

[0094] "User" refers to a person who uses the system, and is a user who uses an information processing device to input a question and obtain an answer.

[0095] An "information processing device" is a terminal such as a smartphone or personal computer, which is a device through which a user inputs a question and communicates with an information processing system.

[0096] An "information processing system" refers to a central system such as a server that receives questions sent from an information processing device, generates answers using a generative AI model, and sends them back to the information processing device.

[0097] A "generative AI model" is an artificial intelligence model that analyzes questions and generates appropriate answers, and refers to a model that uses natural language processing technology.

[0098] "User interface" refers to a screen or application that runs on an information processing device and allows a user to input and send a question.

[0099] "Natural language processing technology" refers to the technology used by generative AI models to understand and analyze human language to generate appropriate answers.

[0100] This invention provides a system that allows users to easily ask questions and receive prompt answers in order to meet the needs for consultations regarding end-of-life planning and inheritance due to the increasing elderly population. The following describes in detail the mode for carrying out this invention.

[0101] System configuration

[0102] The system includes the following main components:

[0103] 1. Information processing device used by the user

[0104] 2. Central Processing Unit (Information Processing System)

[0105] 3. Generative AI Models

[0106] 4. Internet connection

[0107] Information processing device used by the user

[0108] Users use information processing devices such as smartphones and personal computers. These devices have a web browser and dedicated applications installed, and users can input questions through the user interface. For example, it is assumed that a user might input a question such as, "Please tell me how I should start regarding the inheritance of my house."

[0109] Data transmission from an information processing device to an information processing system

[0110] When a user inputs a question and clicks the send button, the information processing device sends the question to the information processing system in the form of an HTTP request. This transmission uses an Internet connection, and the question content is packaged in a format such as JSON.

[0111] Central Processing Unit (Information Processing System)

[0112] The information processing system analyzes the received question and sends it to a generative AI model. This generative AI model uses natural language processing technology to understand the question and generate the optimal answer. The generated answer is packaged in JSON format or similar and sent to the information processing device in HTTP response format.

[0113] Generative AI Models

[0114] A generative AI model uses natural language processing techniques trained from a large dataset. This model generates answers based on prompts received from the server. Below is an example of a prompt for a generative AI model:

[0115] A user has the following question: "How do I get started on inheriting a house?"

[0116] Generate a suitable answer based on this question.

[0117] The model analyzes this prompt sentence, generates an answer such as, "The first step in starting a home inheritance is to understand the current state of your assets," and sends it back to the information processing system.

[0118] Displaying answers on an information processing device

[0119] The information processing device analyzes the answers received from the information processing system and displays them on the user interface. The display format can be a text box or a pop-up window. For example, the user can check the answers on a web page as follows:

[0120] The first step in inheriting a home is to understand the current state of your assets.

[0121] In this way, the system of the present invention allows users to receive prompt and appropriate advice, enabling them to acquire the necessary knowledge before consulting a specialist, reducing the psychological burden and providing support for taking appropriate measures.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Step 1:

[0124] The user enters a question.

[0125] Users access the user interface of a web browser or dedicated application through a device such as a smartphone or personal computer. They enter a question in the input field on the screen and click the send button. For example, they write, "Please tell me how to get started regarding inheriting a house." The entered data is temporarily saved in text format in the internal storage.

[0126] Step 2:

[0127] The terminal sends a question to the server.

[0128] The device creates an HTTP POST request to send the entered question to the server over the Internet. This request contains the question in JSON format. For example, it might be sent in the following format:

[0129] json

[0130] {

[0131] "question": "How do I get started on inheriting a house?"

[0132] }

[0133] At this time, the terminal enters a state of waiting for a response after transmission.

[0134] Step 3:

[0135] The server passes the question to a generative AI model to generate an answer.

[0136] The server analyzes the received HTTP request and extracts the question. It then converts the extracted question into a prompt and sends the request to the generative AI model. An example of a prompt is:

[0137] A user has the following question: "How do I get started on inheriting a house?"

[0138] Generate an appropriate answer based on this question.

[0139] The generative AI model analyzes the prompt and uses natural language processing techniques to generate the optimal answer, which is then returned to the server in text format.

[0140] Step 4:

[0141] The server sends the generated response to the terminal.

[0142] The server converts the answer received from the generative AI model into JSON format and sends it to the device as an HTTP response. For example, the following HTTP response is created:

[0143] json

[0144] {

[0145] "answer": "The first step in inheriting a home is to understand the current state of your assets."

[0146] }

[0147] The server sends this data to the terminal and confirms that the response was sent successfully.

[0148] Step 5:

[0149] The terminal displays the response received from the server to the user.

[0150] The device analyzes the received HTTP response and extracts the answer from the JSON format data. The extracted answer is stored in the display area of ​​the user interface and displayed as text. For example, it is displayed on a web page as follows:

[0151] html

[0152]

[0153] The first step in inheriting a home is to understand the current state of your assets.

[0154]

[0155] This allows the user to view the answers provided and decide on their next action.

[0156] Through the above processing steps, this system is able to provide users with prompt and accurate advice.

[0157] (Application example 1)

[0158] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0159] In physical stores, it can be difficult for users to quickly obtain product information. This is especially true when staff are unavailable or when the store is busy, leaving users frustrated and unable to obtain the information they need. This can also increase the workload of store staff, making it difficult to provide efficient service. To solve these problems, a system is needed that allows users to easily obtain product information using their own devices.

[0160] 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.

[0161] In this invention, the server includes: [means for a user to input a question into a terminal;] [means for the terminal to send the question to the server;] [means for the server to pass the question to a generative AI model and generate an answer;] [means for the server to send the generated answer to the terminal;] [means for the terminal to display the answer received from the server to the user;] [means for a user to input information on a terminal installed in a physical store or the user's mobile terminal; and [means for communicating with the server using an internet connection.] This enables users to quickly obtain product information and answers to purchase-related questions in a physical store.

[0162] "User" means an individual or customer who uses the system to enter a question.

[0163] "Terminal" refers to the device used by the user to input questions and communicate with the server. This includes mobile devices and tablets.

[0164] A "server" is a device or system that receives a user's question, passes it to a generative AI model to generate an answer, and then sends the answer back to the terminal.

[0165] A "generative AI model" is an algorithm or system that uses natural language processing techniques to generate answers to user questions.

[0166] An "Internet connection" is a network that a terminal and a server use to communicate with each other.

[0167] "User interface" refers to interactive elements such as screens and input forms through which users can enter questions.

[0168] The present invention provides a system that allows users to input questions using a terminal in a physical store and quickly provides answers using a generative AI model. An embodiment of the present invention will be described in detail below.

[0169] Functions and Configuration

[0170] 1. The user enters a question

[0171] Customers can input questions into a dedicated user interface using a tablet device installed in the physical store or their own mobile device. For example, a question might be, "What is the most popular item in this store?"

[0172] 2. The device sends a question to the server

[0173] When a user types a question and clicks the submit button, the device sends the question to the server over its internet connection via an HTTP request.

[0174] 3. The server passes the question to the generative AI model to generate an answer.

[0175] The server analyzes the received question and passes it to a generative AI model, which uses natural language processing to understand the question and generate the best answer from a database that includes product information and FAQs.

[0176] 4. The server generates a response and sends it to the device.

[0177] The generated answer is sent from the server to the terminal again via the Internet. The sent data is reformatted as necessary and arranged in a format that can be displayed on the terminal.

[0178] 5. The device displays the answer received from the server to the user.

[0179] The terminal displays the response received from the server to the user using a text box or a pop-up window.

[0180] Hardware and software used

[0181] Hardware

[0182] Device: Tablet or mobile device

[0183] Server: A server with the computational resources to receive requests and generate answers using AI models.

[0184] software

[0185] Generative AI model: An AI model that utilizes natural language processing technology such as OpenAI GPT-3

[0186] Network: Communication over an internet connection

[0187] Database: A database that stores product information and FAQs (e.g., MySQL, ElasticSearch)

[0188] Specific examples

[0189] For example, a customer types a question into a tablet device in a store, such as "What is the most popular item in this store?" This question is answered through the following process:

[0190] 1. The customer types into the terminal, "What is the most popular item in this store?"

[0191] 2. The device sends a question to the server.

[0192] 3. The server receives the question and passes it to the generative AI model.

[0193] 4. The generative AI model analyzes the question and generates an answer such as, "Currently, our most popular item is XX."

[0194] 5. The server sends the generated response to the device.

[0195] 6. The terminal displays the received response to the user.

[0196] Example prompt sentence:

[0197] Type, "What is the most popular item in this store?"

[0198] In this way, the system of the present invention allows users to quickly and easily obtain product information even in physical stores, thereby reducing the workload of store staff and improving user satisfaction.

[0199] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0200] Step 1:

[0201] The customer enters their question into the terminal. Using a tablet device installed in the physical store or their own mobile device, the customer enters their question into a dedicated user interface. The entered data is stored in text format on the terminal.

[0202] Step 2:

[0203] The device sends the question to the server. When the user clicks the send button, the device sends the entered question to the server via an Internet connection. At this time, the device formats the question data in the form of an HTTP request and sends it.

[0204] Step 3:

[0205] The server passes the question to the generative AI model, which generates an answer. The server analyzes the received question data and passes it to the generative AI model. The generative AI model uses natural language processing technology to understand the question and generate the optimal answer from a database. The input to the generative AI model is the question data, and the output is the answer text.

[0206] Step 4:

[0207] The server sends the generated answer to the device. The answer text obtained from the generative AI model is then sent back to the device via the Internet. When sending, the answer data is again formatted in HTTP response format.

[0208] Step 5:

[0209] The terminal displays the answer received from the server to the user. The terminal analyzes the answer received from the server and displays it in the user interface. This can be displayed as a text box or a pop-up window, allowing the user to visually confirm it.

[0210] Step 6:

[0211] The user checks the displayed answer. The user looks at the answer displayed on the device and decides the next action to take. At this point, the user can decide whether the question has been resolved.

[0212] 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.

[0213] The present invention combines a system that allows users to easily consult about end-of-life planning and inheritance matters and quickly receive appropriate answers with an emotion engine that recognizes the user's emotions. The following describes in detail the embodiments of the present system.

[0214] overview

[0215] In this system, users input questions via their devices, and the questions and emotional information at the time of input are sent to a server. The server then passes the received questions and emotional information to a generative AI model and emotion engine, which generates an appropriate answer. The generated answer is then further adjusted by the emotion engine to use wording appropriate to the user's emotions, before being sent to the device and displayed to the user.

[0216] Embodiment

[0217] 1. Users enter questions and express their feelings

[0218] The user inputs a question using the device's user interface, and simultaneously, the user's emotions are recognized from the input text using an emotion engine that runs in the background and analyzes the input in real time.

[0219] 2. The device sends the question and emotion information to the server.

[0220] When the user has finished entering their question, they click the send button. The device then receives the question and the analyzed emotion information as data, converts it into an appropriate format (e.g., JSON), and sends it to the server.

[0221] 3. The server passes the question and emotion information to the generative AI model and emotion engine.

[0222] The server analyzes the received question and emotional information and passes them to the generative AI model and emotion engine. At this time, the generative AI model understands the question and generates an appropriate answer. Meanwhile, the emotion engine analyzes the user's emotional information and makes appropriate emotional adjustments to the generative AI model's output.

[0223] 4. The server adjusts the generated answers with an emotion engine

[0224] The response generated by the generative AI model is then translated by the emotion engine into language that matches the user's emotions. For example, if the user is feeling stressed, the response will be accompanied by kind and encouraging words.

[0225] 5. The server sends the adjusted answer to the device.

[0226] The adjusted response is then sent back from the server to the device, again over the Internet, where it is reformatted into a format that the device can receive.

[0227] 6. The device displays the response received from the server to the user.

[0228] The device displays the received answer to the user in a text box, pop-up window, or other format. The user can then decide what to do next based on the displayed answer.

[0229] Specific examples

[0230] For example, if a user types, "Please tell me how to get started on inheriting a house," the following steps will be performed:

[0231] 1. When a user enters a question, the system recognizes emotions such as "anxiety" or "tension."

[0232] 2. The device sends the question and emotion information to the server.

[0233] 3. The server passes the question content to the generative AI model and the emotion information to the emotion engine.

[0234] 4. The generative AI model generates the answer, "The first step when inheriting a house is to understand the current state of your assets."

[0235] 5. The emotion engine adjusts this response based on emotional information and translates it into a gentle statement: "Let's start by relaxing and understanding the current state of your assets."

[0236] 6. The server sends the adjusted response to the device.

[0237] 7. The terminal displays the response received from the server to the user.

[0238] This invention allows users to obtain not only specific answers according to the content of their questions, but also answers that take into consideration their emotions and reduce psychological burdens, which is a great help in obtaining the necessary knowledge before consulting a specialist and taking appropriate measures.

[0239] The processing flow will be explained below.

[0240] Step 1:

[0241] The user inputs a question using the device's user interface. At the same time, the input text is analyzed in real time by the emotion engine. For example, when typing "Please tell me how to start regarding inheriting a house," the user's emotion is recognized as "anxiety."

[0242] Step 2:

[0243] The device detects the click of the send button, obtains the entered question and analyzed emotion information, and converts this data into an appropriate format such as JSON.

[0244] Step 3:

[0245] The device sends the question and emotion information to the server as an HTTP POST request, sending the data to a specified endpoint on the server.

[0246] Step 4:

[0247] The server receives the HTTP request, analyzes the question data and emotion information, extracts the question content and emotion information from the received data, and prepares them as input to the generative AI model and emotion engine.

[0248] Step 5:

[0249] The server passes the question data to the generative AI model and instructs it to generate an answer. The generative AI model understands the question and generates an appropriate answer. For example, it might generate an answer such as, "The first step when inheriting a house is to understand the current state of the assets."

[0250] Step 6:

[0251] The server passes the generated answer to the emotion engine and instructs it to convert it into wording that is appropriate to the user's emotions. The emotion engine takes the user's emotional information into account and adjusts the answer. For example, it converts the answer into gentler language such as, "First, relax and let's start by understanding the current state of your assets."

[0252] Step 7:

[0253] The server receives the adjusted response and formats it as data to send to the device, which is again converted into a suitable format such as JSON.

[0254] Step 8:

[0255] The server sends the adjusted response data to the device as an HTTP response, formatted to be received by the device.

[0256] Step 9:

[0257] The device analyzes the response data received from the server and displays it in the user interface. For example, it might display "First, relax and start by understanding the current state of your assets" in a text box.

[0258] Step 10:

[0259] The user views the tailored answers displayed on their device and decides on their next action, and can repeat the process by entering more specific questions if desired.

[0260] In this way, a system is provided that allows users to not only obtain specific answers according to the content of their questions, but also quickly obtain answers that take into consideration their feelings and reduce psychological burden.

[0261] Example 2

[0262] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0263] Conventional question-and-answer systems often lack consideration for reducing the psychological burden on users when they casually seek advice about end-of-life planning or inheritance. Furthermore, answers provided without considering the user's emotional state may reduce the user's satisfaction. Therefore, there is a need for systems that provide answers that take into account the user's emotional information.

[0264] 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.

[0265] [Means for the user to input a question into the terminal;

[0266] [Means for the terminal to analyze the user's emotions and send questions and emotional information to the server;

[0267] [Means for the server to pass the question and emotion information to the generative AI model and emotion analyzer to generate and tailor an answer;

[0268] [means for the server to send the adjusted response to the terminal;

[0269] [Means for displaying the answer received by the terminal from the server to the user;

[0270] This allows for appropriate responses that take into account the user's emotional state and reduce the user's psychological burden.

[0271] "Means by which a user inputs a question into a terminal" refers to the interface used by a user to input a question as text and the operation thereof.

[0272] "Means for the terminal to analyze the user's emotions and send the question and emotional information to the server" refers to software for analyzing emotions from the user's input and a communication function for sending the analysis results and the question content to the server.

[0273] "Means for the server to pass the question and emotional information to the generative AI model and emotion analysis device to generate and adjust the answer" refers to the process in which the server inputs the question and emotional information it receives into the generative AI model and emotion analysis device to generate an answer to the question, and the process of adjusting the answer to suit the user's emotions.

[0274] "Means for the server to send adjusted answers to the terminal" refers to the function of the server to send answers adjusted by the generative AI model and the emotion analysis device to the terminal via communication means.

[0275] "Means for displaying to the user the answer received by the terminal from the server" refers to a display device and display software for visually presenting to the user the answer received by the terminal from the server.

[0276] This invention is a system that allows users to easily consult about end-of-life planning and inheritance matters and receive prompt and appropriate answers. This system is implemented by having the user input a question through a terminal, and the question and emotional information at the time of input are transmitted to a server.

[0277] Hardware and Software Configuration

[0278] Terminal

[0279] Users can use devices such as PCs and smartphones to input questions. The device is equipped with a user interface (e.g., a web browser or dedicated app). When a user inputs a question, an emotion engine (e.g., "IBM Watson Tone Analyzer") runs in the background and analyzes the emotion from the input in real time.

[0280] server

[0281] The server is the central device that processes questions and emotional information sent by users. Specific software includes a generative AI model (such as "OpenAI GPT-3") and an emotional analysis device. The server performs the following processes based on the received data:

[0282] The question is passed to a generative AI model to generate an answer.

[0283] The emotional information is passed to an emotion analyzer, which adjusts the response to suit the user's emotions.

[0284] Operation details and data processing

[0285] Sending questions and emotional information

[0286] Once the user has finished entering their question into the device, they press the send button. This action causes the device to send the question and analyzed emotion information in JSON format to the server. The transmission is performed using an HTTP POST request.

[0287] Generate and adjust answers

[0288] The server passes the received question and emotional information to the generative AI model and emotion analyzer. The generative AI model generates an appropriate answer, and the emotion analyzer adjusts the answer to match the user's emotions.

[0289] Submitting a tailored response

[0290] The adjusted answer is sent back from the server to the terminal, where it is displayed to the user.

[0291] Specific examples

[0292] For example, if a user types "How do I get started on inheriting a house?", the following steps are performed:

[0293] 1. When a user enters a question, the system recognizes emotions such as "anxiety" or "tension."

[0294] 2. The device sends the question and emotion information to the server.

[0295] 3. The server passes the question content to the generative AI model and the emotional information to the emotion analyzer.

[0296] 4. The generative AI model generates the answer, "The first step when inheriting a house is to understand the current state of your assets."

[0297] 5. The sentiment analyzer adjusts this response based on emotional information and translates it into a gentler response: "Let's start by relaxing and understanding the current state of your assets."

[0298] 6. The server sends the adjusted response to the device.

[0299] 7. The device displays the answer received from the server to the user.

[0300] Prompt Sentence Examples

[0301] It is possible to generate prompt sentences that include the question "How should I start regarding inheriting a house?" along with phrases that recognize emotions such as "anxiety" and "tension." Specifically, the following prompt sentences are possible:

[0302] Q: How do I get started on inheriting a house?

[0303] Emotional information: anxiety, tension

[0304] By passing this prompt to a generative AI model, a specific answer can be obtained, such as "Let's start by relaxing and understanding the current state of your assets."

[0305] The above configuration and processing not only allows users to receive specific answers based on their questions, but also answers that take into consideration their emotions and reduce their psychological burden. This is a great help in obtaining the necessary knowledge before consulting a specialist and taking appropriate measures.

[0306] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0307] System processing flow

[0308] Step 1:

[0309] The user enters a question into the terminal

[0310] Operation and Input

[0311] The user enters a question into the text box on the terminal. For example, the user might enter, "Please tell me how to get started regarding inheriting a house."

[0312] Data processing and output

[0313] The device receives this input, and an emotion engine (e.g., "IBM Watson Tone Analyzer") analyzes the input text in the background and detects the user's emotion (e.g., "anxiety" or "tension") in real time.

[0314] Step 2:

[0315] The device sends the question and emotion information to the server.

[0316] Operation and Input

[0317] When the user presses the send button, the terminal acquires the question entered by the user and the analysis results by the emotion engine.

[0318] Data processing and output

[0319] The device converts this data into JSON format and sends it to the server using an HTTP POST request. Specific data includes "Question: How should I start regarding inheriting a house?" and "Emotional information: Anxiety, tension."

[0320] Step 3:

[0321] The server receives the question and emotion information.

[0322] Operation and Input

[0323] The server receives the JSON data sent from the terminal.

[0324] Data processing and output

[0325] The server parses the received JSON data and extracts the question ("Please tell me how to start regarding inheritance of a house") and emotional information ("Anxiety, tension"), which is then passed to the next step.

[0326] Step 4:

[0327] The server sends the question content to the AI ​​model and the emotional information to the emotion analyzer.

[0328] Operation and Input

[0329] The server sends the question content to the generation AI model and the emotional information to the emotion analysis device.

[0330] Data processing and output

[0331] A generative AI model (e.g., "OpenAI GPT-3") analyzes the question and generates an appropriate answer ("The first step in inheriting a house is to understand the current state of your assets."). At the same time, an emotion analyzer analyzes emotional information and provides information to adjust the answer.

[0332] Step 5:

[0333] A generative AI model generates answers, and a sentiment analyzer adjusts them.

[0334] Operation and Input

[0335] Let's say the generative AI model's answer is, "The first step when starting to inherit a house is to understand the current state of the assets."

[0336] Data processing and output

[0337] The emotion analyzer adjusts this response based on the user's emotions ("anxiety, tension") to "Let's start by relaxing and understanding the current state of your assets." The adjusted response is sent to the next step.

[0338] Step 6:

[0339] The server sends the adjusted answer to the device.

[0340] Operation and Input

[0341] The server receives the response adjusted by the emotion analyzer.

[0342] Data processing and output

[0343] The server converts the tailored response ("Let's start by relaxing and understanding the current state of your assets") into JSON format and sends it to the device using an HTTP POST request.

[0344] Step 7:

[0345] Display the answer received by the device

[0346] Operation and Input

[0347] The terminal parses the JSON data received from the server.

[0348] Data processing and output

[0349] The device displays the adjusted response to the user, specifically displaying a message on the screen saying, "First, relax and let's start by understanding the current state of your assets."

[0350] The above steps complete the series of processes for the system to analyze the user's input and provide an appropriate answer.

[0351] (Application example 2)

[0352] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0353] In recent years, the number of users gathering information and seeking advice on inheritance and end-of-life planning has been increasing. However, many of these situations involve emotional burdens, and conventional systems are often unable to adequately address these. Furthermore, current systems have difficulty providing answers that take users' emotions into consideration, which is one of the factors that reduces user satisfaction. The purpose of this invention is to provide a consultation system for inheritance and end-of-life planning that adapts to users' emotions, thereby reducing psychological burdens and providing more appropriate answers more quickly.

[0354] 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.

[0355] In this invention, the server includes: a means for a user to input a question into a terminal and provide emotion information; a means for the terminal to transmit the question and emotion information to the server; a means for the server to pass the question to a generative AI model and the emotion information to an emotion engine; a means for the server to adjust the generated answer using the emotion engine to adjust the wording to match the emotion; a means for the server to transmit the adjusted answer to the terminal; and a means for the terminal to display the adjusted answer received from the server to the user. This makes it possible to quickly provide an appropriate answer that matches the user's emotion and reduce psychological burden.

[0356] A "terminal" is a device operated by a user, which inputs questions and emotional information and communicates with a server.

[0357] A "question" is text information entered by the user regarding inheritance or end-of-life planning.

[0358] "Emotional information" is data about the user's emotions that the system analyzes and recognizes in real time when the user enters a question.

[0359] The "server" is a computer system that receives questions and emotion information entered by users and generates appropriate answers using a generative AI model and emotion engine.

[0360] A "generative AI model" is an artificial intelligence model installed on a server, and is a technology for generating appropriate answers to users' questions.

[0361] An "emotion engine" is a technology installed on a server or terminal that analyzes the user's emotional information and adjusts the generated answers based on that information.

[0362] "User interface" refers to a function that allows users to input questions and provide emotional information through a terminal.

[0363] "Natural language processing technology" is a technology that allows a server to understand text data and generate an appropriate response when generating answers using a generative AI model.

[0364] "Adjustment" is a process in which the generated answer is changed to wording that is appropriate to the user's emotions using an emotion engine.

[0365] An "answer" is a response to a user's question generated by a generative AI model and adjusted by an emotion engine.

[0366] The following components are required to implement this invention: A user inputs a question through a terminal, and the question and emotional information are sent to a server. The server passes the received question and emotional information to a generative AI model and an emotional engine, which generates an appropriate answer. The generated answer is further adjusted by the emotional engine to use wording appropriate to the user's emotions, and then sent to the terminal and displayed to the user.

[0367] Program Description

[0368] 1. Enter a question and provide emotional information

[0369] The user inputs a question using the device's user interface. The device is equipped with an Emotion Engine, which analyzes and collects emotional information from the question in real time. The emotional information includes emotional states such as anxiety, tension, and joy.

[0370] 2. Sending questions and emotional information

[0371] Once the user has finished entering their question, the device converts the question and the analyzed emotional information into a data format (e.g., JSON format) and sends it to the server. At this time, the device uses the "requests" communication library to send the data to the server as an HTTP POST request.

[0372] 3. Questioning and emotional information processing

[0373] The server analyzes the received question and emotional information, and passes the question content to the generative AI model, while also passing the emotional information to the emotion engine. The generative AI model, "AIGeneratedResponse," is an artificial intelligence model that understands the question content and generates an appropriate answer.

[0374] 4. Emotionally appropriate adjustment of responses

[0375] The generated answers are adjusted by the emotion engine to use language that is appropriate to the user's emotions. This process adds additional consideration to the generated answers based on the user's emotional state. For example, if a user is feeling anxious, reassuring words such as "relax" will be added.

[0376] 5. Submitting and Viewing Tailored Answers

[0377] The answer, adjusted to suit the user's emotions, is then sent back to the device from the server. The device receives the answer and displays it on the user interface, allowing the user to receive an appropriate answer that takes their emotions into consideration.

[0378] Specific examples

[0379] For example, if a user types a question like "I'm worried about inheriting a house," the following steps will occur:

[0380] 1. The user types, "I'm worried about inheriting my house," and the system recognizes the emotion "anxiety."

[0381] 2. The question and emotion information are sent to the server.

[0382] 3. The server passes the question content to the generation AI model and the emotion information to the emotion engine.

[0383] 4. The generative AI model generates the answer, "Let's start by looking at basic information about your home's assets."

[0384] 5. The emotion engine refines this response to, "Relax, let's start by finding out some basic information about your home's assets."

[0385] 6. The adjusted answer is displayed to the user.

[0386] Prompt Sentence Examples

[0387] User Question: I'm worried about inheriting my house.

[0388] Recognized emotion: Anxiety

[0389] Prompt for generative AI model: Generate appropriate answers to user questions. Emotions considered: Anxiety

[0390] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0391] Step 1:

[0392] The user inputs a question using the device's user interface, and the device retrieves the question. At this time, EmotionEngine runs in the background and analyzes emotional information from the input question in real time. The input is the user's question (e.g., "I'm worried about inheriting my house"), and the output is the question and emotional information (e.g., "anxiety").

[0393] Step 2:

[0394] The device converts the question and emotion information into a data format (for example, JSON format) and sends it to the server. At this time, the communication library "requests" is used to send the data as an HTTP POST request. The input is the question and emotion information, which is converted into JSON format and output as a data packet to be sent.

[0395] Step 3:

[0396] The server analyzes the received question and emotional information, and passes the question content to the generative AI model "AIGeneratedResponse" and the emotional information to the emotion engine. The input is a JSON data packet, which is separated into the question content and emotional information as the analysis result. The output is input data to the generative AI model and the emotion engine.

[0397] Step 4:

[0398] The generative AI model understands the question and generates an appropriate answer. This process uses natural language processing techniques to process the question and generate the best answer. The input is the question, and the output is the generated answer (e.g., "Let's start by looking at basic information about your home's assets.").

[0399] Step 5:

[0400] The emotion engine adjusts the generated answer based on the user's emotional information. For example, if a user feels "anxious," the reassuring phrase "relax" is added. The input is the generated answer and emotional information, and the output is an answer that has been adjusted to suit the emotion (e.g., "Relax, let's start by looking up basic information about your home's assets.").

[0401] Step 6:

[0402] The server converts the adjusted response back into the appropriate data format and sends it to the device, again using the "requests" communication library. The input is the adjusted response, and the output is a data packet sent to the device.

[0403] Step 7:

[0404] The terminal displays the tailored response received from the server on the user interface, allowing the user to obtain an appropriate response that takes their emotions into consideration. The input is the data packet received from the server, and the output is the displayed text message.

[0405] 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.

[0406] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0407] 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.

[0408] [Second embodiment]

[0409] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0410] 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.

[0411] 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).

[0412] 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.

[0413] 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.

[0414] 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).

[0415] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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.

[0420] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0421] The present invention provides a system that allows users to easily consult with others and receive prompt answers regarding matters related to end-of-life planning and inheritance, in response to the growing elderly population. The following describes in detail the mode for implementing this system.

[0422] overview

[0423] In this system, users input questions via their devices, which are then sent to a server. The server then passes the received questions to a generative AI model, which generates an appropriate answer. The generated answer is then sent back to the device, which then displays it to the user, allowing them to receive appropriate support.

[0424] Embodiment

[0425] 1. The user enters a question

[0426] Users use devices such as smartphones or personal computers to input questions into a dedicated user interface. For example, a question might be, "Please tell me how I should start regarding the inheritance of my house."

[0427] 2. The device sends a question to the server

[0428] After entering a question, the user clicks the send button, which causes the device to send the question to the server via an Internet connection as an HTTP request from the device to the server.

[0429] 3. The server passes the question to the generative AI model to generate an answer.

[0430] The server analyzes the received question and passes it to a generative AI model. This generative AI model uses natural language processing technology, for example, and generates an appropriate answer for the question. The generative AI model has the ability to understand the content of the question and extract an appropriate answer from a huge database.

[0431] 4. The server generates a response and sends it to the device.

[0432] The generated answer is sent from the server to the device, again via the Internet, where the data is formatted in a way that the device can receive it.

[0433] 5. The device displays the answer received from the server to the user.

[0434] The device displays the received answer to the user in a text box, pop-up window, or other format. The user can then decide what to do next based on the displayed answer.

[0435] Specific examples

[0436] For example, if a user types, "Please tell me how to get started on inheriting a house," the following steps will be executed:

[0437] 1. The user enters a question and clicks the submit button.

[0438] 2. The device sends this question to the server.

[0439] 3. The server receives the question and passes it to the generative AI model.

[0440] 4. The generative AI model analyzes the question and generates the answer, "The first step in inheriting a house is to understand the current state of your assets."

[0441] 5. The server sends this response to the terminal.

[0442] 6. The terminal displays the received response to the user.

[0443] In this way, the system of the present invention allows users to easily and quickly obtain useful advice regarding end-of-life planning and inheritance, enabling them to acquire the necessary knowledge before consulting with a specialist, and providing support for taking appropriate measures while reducing psychological burden.

[0444] The processing flow will be explained below.

[0445] Step 1:

[0446] The user inputs a question using the user interface of the terminal. Specifically, the user inputs the question "Please tell me how to get started regarding inheriting a house" into the input form and clicks the submit button.

[0447] Step 2:

[0448] The device detects the click event of the submit button, obtains the entered question as data, and converts this data into an appropriate format (for example, JSON format).

[0449] Step 3:

[0450] The device sends the question data to the server. Specifically, it uses an HTTP POST request to send the question data to the specified endpoint on the server.

[0451] Step 4:

[0452] The server receives the HTTP request, analyzes the question data, extracts the question content from the received data, and prepares it as input for the generative AI model.

[0453] Step 5:

[0454] The server passes the question to the generative AI model and instructs it to generate an answer. The generative AI model used here (for example, one that utilizes natural language processing technology) generates an appropriate answer based on the given question.

[0455] Step 6:

[0456] The generative AI model processes the question and generates an answer, such as, "The first step in inheriting a home is to understand the current state of your assets."

[0457] Step 7:

[0458] The server receives the generated response and formats it as data to be sent to the device, again in an appropriate format such as JSON.

[0459] Step 8:

[0460] The server sends the generated response data to the terminal. Specifically, it returns the response data as an HTTP response.

[0461] Step 9:

[0462] The device analyzes the response data received from the server and displays it in the user interface. For example, a text box might say, "The first step in inheriting a house is to understand the current state of your assets."

[0463] Step 10:

[0464] The user views the answers displayed on their device, decides their next action, and can repeat the process again, if desired, by entering a more specific question.

[0465] In this way, a system is provided that allows users to easily and quickly obtain useful advice regarding end-of-life planning and inheritance.

[0466] Example 1

[0467] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0468] As the elderly population increases, there is a growing need for consultations regarding end-of-life planning and inheritance. However, there are limited ways to acquire the necessary knowledge before consulting a specialist, making it difficult for users to obtain sufficient information. In particular, there is a need for a means to receive prompt and appropriate support.

[0469] 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.

[0470] In this invention, the server includes: [means for a user to input a question to an information processing device;] [means for the information processing device to send the question to an information processing system; and] [means for the information processing system to pass the question to a generative AI model and generate an answer.] This enables [users to receive prompt and appropriate advice and acquire the necessary knowledge before consulting an expert.]

[0471] "User" refers to a person who uses the system, and is a user who uses an information processing device to input a question and obtain an answer.

[0472] An "information processing device" is a terminal such as a smartphone or personal computer, which is a device through which a user inputs a question and communicates with an information processing system.

[0473] An "information processing system" refers to a central system such as a server that receives questions sent from an information processing device, generates answers using a generative AI model, and sends them back to the information processing device.

[0474] A "generative AI model" is an artificial intelligence model that analyzes questions and generates appropriate answers, and refers to a model that uses natural language processing technology.

[0475] "User interface" refers to a screen or application that runs on an information processing device and allows a user to input and send a question.

[0476] "Natural language processing technology" refers to the technology used by generative AI models to understand and analyze human language to generate appropriate answers.

[0477] This invention provides a system that allows users to easily ask questions and receive prompt answers in order to meet the needs for consultations regarding end-of-life planning and inheritance due to the increasing elderly population. The following describes in detail the mode for carrying out this invention.

[0478] System configuration

[0479] The system includes the following main components:

[0480] 1. Information processing device used by the user

[0481] 2. Central Processing Unit (Information Processing System)

[0482] 3. Generative AI Models

[0483] 4. Internet connection

[0484] Information processing device used by the user

[0485] Users use information processing devices such as smartphones and personal computers. These devices have a web browser and dedicated applications installed, and users can input questions through the user interface. For example, it is assumed that a user might input a question such as, "Please tell me how I should start regarding the inheritance of my house."

[0486] Data transmission from an information processing device to an information processing system

[0487] When a user inputs a question and clicks the send button, the information processing device sends the question to the information processing system in the form of an HTTP request. This transmission uses an Internet connection, and the question content is packaged in a format such as JSON.

[0488] Central Processing Unit (Information Processing System)

[0489] The information processing system analyzes the received question and sends it to a generative AI model. This generative AI model uses natural language processing technology to understand the question and generate the optimal answer. The generated answer is packaged in JSON format or similar and sent to the information processing device in HTTP response format.

[0490] Generative AI Models

[0491] A generative AI model uses natural language processing techniques trained from a large dataset. This model generates answers based on prompts received from the server. Below is an example of a prompt for a generative AI model:

[0492] A user has the following question: "How do I get started on inheriting a house?"

[0493] Generate a suitable answer based on this question.

[0494] The model analyzes this prompt sentence, generates an answer such as, "The first step in starting a home inheritance is to understand the current state of your assets," and sends it back to the information processing system.

[0495] Displaying answers on an information processing device

[0496] The information processing device analyzes the answers received from the information processing system and displays them on the user interface. The display format can be a text box or a pop-up window. For example, the user can check the answers on a web page as follows:

[0497] The first step in inheriting a home is to understand the current state of your assets.

[0498] In this way, the system of the present invention allows users to receive prompt and appropriate advice, enabling them to acquire the necessary knowledge before consulting a specialist, reducing the psychological burden and providing support for taking appropriate measures.

[0499] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0500] Step 1:

[0501] The user enters a question.

[0502] Users access the user interface of a web browser or dedicated application through a device such as a smartphone or personal computer. They enter a question in the input field on the screen and click the send button. For example, they write, "Please tell me how to get started regarding inheriting a house." The entered data is temporarily saved in text format in the internal storage.

[0503] Step 2:

[0504] The terminal sends a question to the server.

[0505] The device creates an HTTP POST request to send the entered question to the server over the Internet. This request contains the question in JSON format. For example, it might be sent in the following format:

[0506] json

[0507] {

[0508] "question": "How do I get started on inheriting a house?"

[0509] }

[0510] At this time, the terminal enters a state of waiting for a response after transmission.

[0511] Step 3:

[0512] The server passes the question to a generative AI model to generate an answer.

[0513] The server analyzes the received HTTP request and extracts the question. It then converts the extracted question into a prompt and sends the request to the generative AI model. An example of a prompt is:

[0514] A user has the following question: "How do I get started on inheriting a house?"

[0515] Generate an appropriate answer based on this question.

[0516] The generative AI model analyzes the prompt and uses natural language processing techniques to generate the optimal answer, which is then returned to the server in text format.

[0517] Step 4:

[0518] The server sends the generated response to the terminal.

[0519] The server converts the answer received from the generative AI model into JSON format and sends it to the device as an HTTP response. For example, the following HTTP response is created:

[0520] json

[0521] {

[0522] "answer": "The first step in inheriting a home is to understand the current state of your assets."

[0523] }

[0524] The server sends this data to the terminal and confirms that the response was sent successfully.

[0525] Step 5:

[0526] The terminal displays the response received from the server to the user.

[0527] The device analyzes the received HTTP response and extracts the answer from the JSON format data. The extracted answer is stored in the display area of ​​the user interface and displayed as text. For example, it is displayed on a web page as follows:

[0528] html

[0529]

[0530] The first step in inheriting a home is to understand the current state of your assets.

[0531]

[0532] This allows the user to view the answers provided and decide on their next action.

[0533] Through the above processing steps, this system is able to provide users with prompt and accurate advice.

[0534] (Application example 1)

[0535] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0536] In physical stores, it can be difficult for users to quickly obtain product information. This is especially true when staff are unavailable or when the store is busy, leaving users frustrated and unable to obtain the information they need. This can also increase the workload of store staff, making it difficult to provide efficient service. To solve these problems, a system is needed that allows users to easily obtain product information using their own devices.

[0537] 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.

[0538] In this invention, the server includes: [means for a user to input a question into a terminal;] [means for the terminal to send the question to the server;] [means for the server to pass the question to a generative AI model and generate an answer;] [means for the server to send the generated answer to the terminal;] [means for the terminal to display the answer received from the server to the user;] [means for a user to input information on a terminal installed in a physical store or the user's mobile terminal; and [means for communicating with the server using an internet connection.] This enables users to quickly obtain product information and answers to purchase-related questions in a physical store.

[0539] "User" means an individual or customer who uses the system to enter a question.

[0540] "Terminal" refers to the device used by the user to input questions and communicate with the server. This includes mobile devices and tablets.

[0541] A "server" is a device or system that receives a user's question, passes it to a generative AI model to generate an answer, and then sends the answer back to the terminal.

[0542] A "generative AI model" is an algorithm or system that uses natural language processing techniques to generate answers to user questions.

[0543] An "Internet connection" is a network that a terminal and a server use to communicate with each other.

[0544] "User interface" refers to interactive elements such as screens and input forms through which users can enter questions.

[0545] The present invention provides a system that allows users to input questions using a terminal in a physical store and quickly provides answers using a generative AI model. An embodiment of the present invention will be described in detail below.

[0546] Functions and Configuration

[0547] 1. The user enters a question

[0548] Customers can input questions into a dedicated user interface using a tablet device installed in the physical store or their own mobile device. For example, a question might be, "What is the most popular item in this store?"

[0549] 2. The device sends a question to the server

[0550] When a user types a question and clicks the submit button, the device sends the question to the server over its internet connection via an HTTP request.

[0551] 3. The server passes the question to the generative AI model to generate an answer.

[0552] The server analyzes the received question and passes it to a generative AI model, which uses natural language processing to understand the question and generate the best answer from a database that includes product information and FAQs.

[0553] 4. The server generates a response and sends it to the device.

[0554] The generated answer is sent from the server to the terminal again via the Internet. The sent data is reformatted as necessary and arranged in a format that can be displayed on the terminal.

[0555] 5. The device displays the answer received from the server to the user.

[0556] The terminal displays the response received from the server to the user using a text box or a pop-up window.

[0557] Hardware and software used

[0558] Hardware

[0559] Device: Tablet or mobile device

[0560] Server: A server with the computational resources to receive requests and generate answers using AI models.

[0561] software

[0562] Generative AI model: An AI model that utilizes natural language processing technology such as OpenAI GPT-3

[0563] Network: Communication over an internet connection

[0564] Database: A database that stores product information and FAQs (e.g., MySQL, ElasticSearch)

[0565] Specific examples

[0566] For example, a customer types a question into a tablet device in a store, such as "What is the most popular item in this store?" This question is answered through the following process:

[0567] 1. The customer types into the terminal, "What is the most popular item in this store?"

[0568] 2. The device sends a question to the server.

[0569] 3. The server receives the question and passes it to the generative AI model.

[0570] 4. The generative AI model analyzes the question and generates an answer such as, "Currently, our most popular item is XX."

[0571] 5. The server sends the generated response to the device.

[0572] 6. The terminal displays the received response to the user.

[0573] Example prompt sentence:

[0574] Type, "What is the most popular item in this store?"

[0575] In this way, the system of the present invention allows users to quickly and easily obtain product information even in physical stores, thereby reducing the workload of store staff and improving user satisfaction.

[0576] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0577] Step 1:

[0578] The customer enters their question into the terminal. Using a tablet device installed in the physical store or their own mobile device, the customer enters their question into a dedicated user interface. The entered data is stored in text format on the terminal.

[0579] Step 2:

[0580] The device sends the question to the server. When the user clicks the send button, the device sends the entered question to the server via an Internet connection. At this time, the device formats the question data in the form of an HTTP request and sends it.

[0581] Step 3:

[0582] The server passes the question to the generative AI model, which generates an answer. The server analyzes the received question data and passes it to the generative AI model. The generative AI model uses natural language processing technology to understand the question and generate the optimal answer from a database. The input to the generative AI model is the question data, and the output is the answer text.

[0583] Step 4:

[0584] The server sends the generated answer to the device. The answer text obtained from the generative AI model is then sent back to the device via the Internet. When sending, the answer data is again formatted in HTTP response format.

[0585] Step 5:

[0586] The terminal displays the answer received from the server to the user. The terminal analyzes the answer received from the server and displays it in the user interface. This can be displayed as a text box or a pop-up window, allowing the user to visually confirm it.

[0587] Step 6:

[0588] The user checks the displayed answer. The user looks at the answer displayed on the device and decides the next action to take. At this point, the user can decide whether the question has been resolved.

[0589] 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.

[0590] The present invention combines a system that allows users to easily consult about end-of-life planning and inheritance matters and quickly receive appropriate answers with an emotion engine that recognizes the user's emotions. The following describes in detail the embodiments of the present system.

[0591] overview

[0592] In this system, users input questions via their devices, and the questions and emotional information at the time of input are sent to a server. The server then passes the received questions and emotional information to a generative AI model and emotion engine, which generates an appropriate answer. The generated answer is then further adjusted by the emotion engine to use wording appropriate to the user's emotions, before being sent to the device and displayed to the user.

[0593] Embodiment

[0594] 1. Users enter questions and express their feelings

[0595] The user inputs a question using the device's user interface, and simultaneously, the user's emotions are recognized from the input text using an emotion engine that runs in the background and analyzes the input in real time.

[0596] 2. The device sends the question and emotion information to the server.

[0597] When the user has finished entering their question, they click the send button. The device then receives the question and the analyzed emotion information as data, converts it into an appropriate format (e.g., JSON), and sends it to the server.

[0598] 3. The server passes the question and emotion information to the generative AI model and emotion engine.

[0599] The server analyzes the received question and emotional information and passes them to the generative AI model and emotion engine. At this time, the generative AI model understands the question and generates an appropriate answer. Meanwhile, the emotion engine analyzes the user's emotional information and makes appropriate emotional adjustments to the generative AI model's output.

[0600] 4. The server adjusts the generated answers with an emotion engine

[0601] The response generated by the generative AI model is then translated by the emotion engine into language that matches the user's emotions. For example, if the user is feeling stressed, the response will be accompanied by kind and encouraging words.

[0602] 5. The server sends the adjusted answer to the device.

[0603] The adjusted response is then sent back from the server to the device, again over the Internet, where it is reformatted into a format that the device can receive.

[0604] 6. The device displays the response received from the server to the user.

[0605] The device displays the received answer to the user in a text box, pop-up window, or other format. The user can then decide what to do next based on the displayed answer.

[0606] Specific examples

[0607] For example, if a user types, "Please tell me how to get started on inheriting a house," the following steps will be performed:

[0608] 1. When a user enters a question, the system recognizes emotions such as "anxiety" or "tension."

[0609] 2. The device sends the question and emotion information to the server.

[0610] 3. The server passes the question content to the generative AI model and the emotion information to the emotion engine.

[0611] 4. The generative AI model generates the answer, "The first step when inheriting a house is to understand the current state of your assets."

[0612] 5. The emotion engine adjusts this response based on emotional information and translates it into a gentle statement: "Let's start by relaxing and understanding the current state of your assets."

[0613] 6. The server sends the adjusted response to the device.

[0614] 7. The terminal displays the response received from the server to the user.

[0615] This invention allows users to obtain not only specific answers according to the content of their questions, but also answers that take into consideration their emotions and reduce psychological burdens, which is a great help in obtaining the necessary knowledge before consulting a specialist and taking appropriate measures.

[0616] The processing flow will be explained below.

[0617] Step 1:

[0618] The user inputs a question using the device's user interface. At the same time, the input text is analyzed in real time by the emotion engine. For example, when typing "Please tell me how to start regarding inheriting a house," the user's emotion is recognized as "anxiety."

[0619] Step 2:

[0620] The device detects the click of the send button, obtains the entered question and analyzed emotion information, and converts this data into an appropriate format such as JSON.

[0621] Step 3:

[0622] The device sends the question and emotion information to the server as an HTTP POST request, sending the data to a specified endpoint on the server.

[0623] Step 4:

[0624] The server receives the HTTP request, analyzes the question data and emotion information, extracts the question content and emotion information from the received data, and prepares them as input to the generative AI model and emotion engine.

[0625] Step 5:

[0626] The server passes the question data to the generative AI model and instructs it to generate an answer. The generative AI model understands the question and generates an appropriate answer. For example, it might generate an answer such as, "The first step when inheriting a house is to understand the current state of the assets."

[0627] Step 6:

[0628] The server passes the generated answer to the emotion engine and instructs it to convert it into wording that is appropriate to the user's emotions. The emotion engine takes the user's emotional information into account and adjusts the answer. For example, it converts the answer into gentler language such as, "First, relax and let's start by understanding the current state of your assets."

[0629] Step 7:

[0630] The server receives the adjusted response and formats it as data to send to the device, which is again converted into a suitable format such as JSON.

[0631] Step 8:

[0632] The server sends the adjusted response data to the device as an HTTP response, formatted to be received by the device.

[0633] Step 9:

[0634] The device analyzes the response data received from the server and displays it in the user interface. For example, it might display "First, relax and start by understanding the current state of your assets" in a text box.

[0635] Step 10:

[0636] The user views the tailored answers displayed on their device and decides on their next action, and can repeat the process by entering more specific questions if desired.

[0637] In this way, a system is provided that allows users to not only obtain specific answers according to the content of their questions, but also quickly obtain answers that take into consideration their feelings and reduce psychological burden.

[0638] Example 2

[0639] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0640] Conventional question-and-answer systems often lack consideration for reducing the psychological burden on users when they casually seek advice about end-of-life planning or inheritance. Furthermore, answers provided without considering the user's emotional state may reduce the user's satisfaction. Therefore, there is a need for systems that provide answers that take into account the user's emotional information.

[0641] 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.

[0642] [Means for the user to input a question into the terminal;

[0643] [Means for the terminal to analyze the user's emotions and send questions and emotional information to the server;

[0644] [Means for the server to pass the question and emotion information to the generative AI model and emotion analyzer to generate and tailor an answer;

[0645] [means for the server to send the adjusted response to the terminal;

[0646] [Means for displaying the answer received by the terminal from the server to the user;

[0647] This allows for appropriate responses that take into account the user's emotional state and reduce the user's psychological burden.

[0648] "Means by which a user inputs a question into a terminal" refers to the interface used by a user to input a question as text and the operation thereof.

[0649] "Means for the terminal to analyze the user's emotions and send the question and emotional information to the server" refers to software for analyzing emotions from the user's input and a communication function for sending the analysis results and the question content to the server.

[0650] "Means for the server to pass the question and emotional information to the generative AI model and emotion analysis device to generate and adjust the answer" refers to the process in which the server inputs the question and emotional information it receives into the generative AI model and emotion analysis device to generate an answer to the question, and the process of adjusting the answer to suit the user's emotions.

[0651] "Means for the server to send adjusted answers to the terminal" refers to the function of the server to send answers adjusted by the generative AI model and the emotion analysis device to the terminal via communication means.

[0652] "Means for displaying to the user the answer received by the terminal from the server" refers to a display device and display software for visually presenting to the user the answer received by the terminal from the server.

[0653] This invention is a system that allows users to easily consult about end-of-life planning and inheritance matters and receive prompt and appropriate answers. This system is implemented by having the user input a question through a terminal, and the question and emotional information at the time of input are transmitted to a server.

[0654] Hardware and Software Configuration

[0655] Terminal

[0656] Users can use devices such as PCs and smartphones to input questions. The device is equipped with a user interface (e.g., a web browser or dedicated app). When a user inputs a question, an emotion engine (e.g., "IBM Watson Tone Analyzer") runs in the background and analyzes the emotion from the input in real time.

[0657] server

[0658] The server is the central device that processes questions and emotional information sent by users. Specific software includes a generative AI model (such as "OpenAI GPT-3") and an emotional analysis device. The server performs the following processes based on the received data:

[0659] The question is passed to a generative AI model to generate an answer.

[0660] The emotional information is passed to an emotion analyzer, which adjusts the response to suit the user's emotions.

[0661] Operation details and data processing

[0662] Sending questions and emotional information

[0663] Once the user has finished entering their question into the device, they press the send button. This action causes the device to send the question and analyzed emotion information in JSON format to the server. The transmission is performed using an HTTP POST request.

[0664] Generate and adjust answers

[0665] The server passes the received question and emotional information to the generative AI model and emotion analyzer. The generative AI model generates an appropriate answer, and the emotion analyzer adjusts the answer to match the user's emotions.

[0666] Submitting a tailored response

[0667] The adjusted answer is sent back from the server to the terminal, where it is displayed to the user.

[0668] Specific examples

[0669] For example, if a user types "How do I get started on inheriting a house?", the following steps are performed:

[0670] 1. When a user enters a question, the system recognizes emotions such as "anxiety" or "tension."

[0671] 2. The device sends the question and emotion information to the server.

[0672] 3. The server passes the question content to the generative AI model and the emotional information to the emotion analyzer.

[0673] 4. The generative AI model generates the answer, "The first step when inheriting a house is to understand the current state of your assets."

[0674] 5. The sentiment analyzer adjusts this response based on emotional information and translates it into a gentler response: "Let's start by relaxing and understanding the current state of your assets."

[0675] 6. The server sends the adjusted response to the device.

[0676] 7. The device displays the answer received from the server to the user.

[0677] Prompt Sentence Examples

[0678] It is possible to generate prompt sentences that include the question "How should I start regarding inheriting a house?" along with phrases that recognize emotions such as "anxiety" and "tension." Specifically, the following prompt sentences are possible:

[0679] Q: How do I get started on inheriting a house?

[0680] Emotional information: anxiety, tension

[0681] By passing this prompt to a generative AI model, a specific answer can be obtained, such as "Let's start by relaxing and understanding the current state of your assets."

[0682] The above configuration and processing not only allows users to receive specific answers based on their questions, but also answers that take into consideration their emotions and reduce their psychological burden. This is a great help in obtaining the necessary knowledge before consulting a specialist and taking appropriate measures.

[0683] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0684] System processing flow

[0685] Step 1:

[0686] The user enters a question into the terminal

[0687] Operation and Input

[0688] The user enters a question into the text box on the terminal. For example, the user might enter, "Please tell me how to get started regarding inheriting a house."

[0689] Data processing and output

[0690] The device receives this input, and an emotion engine (e.g., "IBM Watson Tone Analyzer") analyzes the input text in the background and detects the user's emotion (e.g., "anxiety" or "tension") in real time.

[0691] Step 2:

[0692] The device sends the question and emotion information to the server.

[0693] Operation and Input

[0694] When the user presses the send button, the terminal acquires the question entered by the user and the analysis results by the emotion engine.

[0695] Data processing and output

[0696] The device converts this data into JSON format and sends it to the server using an HTTP POST request. Specific data includes "Question: How should I start regarding inheriting a house?" and "Emotional information: Anxiety, tension."

[0697] Step 3:

[0698] The server receives the question and emotion information.

[0699] Operation and Input

[0700] The server receives the JSON data sent from the terminal.

[0701] Data processing and output

[0702] The server parses the received JSON data and extracts the question ("Please tell me how to start regarding inheritance of a house") and emotional information ("Anxiety, tension"), which is then passed to the next step.

[0703] Step 4:

[0704] The server sends the question content to the AI ​​model and the emotional information to the emotion analyzer.

[0705] Operation and Input

[0706] The server sends the question content to the generation AI model and the emotional information to the emotion analysis device.

[0707] Data processing and output

[0708] A generative AI model (e.g., "OpenAI GPT-3") analyzes the question and generates an appropriate answer ("The first step in inheriting a house is to understand the current state of your assets."). At the same time, an emotion analyzer analyzes emotional information and provides information to adjust the answer.

[0709] Step 5:

[0710] A generative AI model generates answers, and a sentiment analyzer adjusts them.

[0711] Operation and Input

[0712] Let's say the generative AI model's answer is, "The first step when starting to inherit a house is to understand the current state of the assets."

[0713] Data processing and output

[0714] The emotion analyzer adjusts this response based on the user's emotions ("anxiety, tension") to "Let's start by relaxing and understanding the current state of your assets." The adjusted response is sent to the next step.

[0715] Step 6:

[0716] The server sends the adjusted answer to the device.

[0717] Operation and Input

[0718] The server receives the response adjusted by the emotion analyzer.

[0719] Data processing and output

[0720] The server converts the tailored response ("Let's start by relaxing and understanding the current state of your assets") into JSON format and sends it to the device using an HTTP POST request.

[0721] Step 7:

[0722] Display the answer received by the device

[0723] Operation and Input

[0724] The terminal parses the JSON data received from the server.

[0725] Data processing and output

[0726] The device displays the adjusted response to the user, specifically displaying a message on the screen saying, "First, relax and let's start by understanding the current state of your assets."

[0727] The above steps complete the series of processes for the system to analyze the user's input and provide an appropriate answer.

[0728] (Application example 2)

[0729] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0730] In recent years, the number of users gathering information and seeking advice on inheritance and end-of-life planning has been increasing. However, many of these situations involve emotional burdens, and conventional systems are often unable to adequately address these. Furthermore, current systems have difficulty providing answers that take users' emotions into consideration, which is one of the factors that reduces user satisfaction. The purpose of this invention is to provide a consultation system for inheritance and end-of-life planning that adapts to users' emotions, thereby reducing psychological burdens and providing more appropriate answers more quickly.

[0731] 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.

[0732] In this invention, the server includes: a means for a user to input a question into a terminal and provide emotion information; a means for the terminal to transmit the question and emotion information to the server; a means for the server to pass the question to a generative AI model and the emotion information to an emotion engine; a means for the server to adjust the generated answer using the emotion engine to adjust the wording to match the emotion; a means for the server to transmit the adjusted answer to the terminal; and a means for the terminal to display the adjusted answer received from the server to the user. This makes it possible to quickly provide an appropriate answer that matches the user's emotion and reduce psychological burden.

[0733] A "terminal" is a device operated by a user, which inputs questions and emotional information and communicates with a server.

[0734] A "question" is text information entered by the user regarding inheritance or end-of-life planning.

[0735] "Emotional information" is data about the user's emotions that the system analyzes and recognizes in real time when the user enters a question.

[0736] The "server" is a computer system that receives questions and emotion information entered by users and generates appropriate answers using a generative AI model and emotion engine.

[0737] A "generative AI model" is an artificial intelligence model installed on a server, and is a technology for generating appropriate answers to users' questions.

[0738] An "emotion engine" is a technology installed on a server or terminal that analyzes the user's emotional information and adjusts the generated answers based on that information.

[0739] "User interface" refers to a function that allows users to input questions and provide emotional information through a terminal.

[0740] "Natural language processing technology" is a technology that allows a server to understand text data and generate an appropriate response when generating answers using a generative AI model.

[0741] "Adjustment" is a process in which the generated answer is changed to wording that is appropriate to the user's emotions using an emotion engine.

[0742] An "answer" is a response to a user's question generated by a generative AI model and adjusted by an emotion engine.

[0743] The following components are required to implement this invention: A user inputs a question through a terminal, and the question and emotional information are sent to a server. The server passes the received question and emotional information to a generative AI model and an emotional engine, which generates an appropriate answer. The generated answer is further adjusted by the emotional engine to use wording appropriate to the user's emotions, and then sent to the terminal and displayed to the user.

[0744] Program Description

[0745] 1. Enter a question and provide emotional information

[0746] The user inputs a question using the device's user interface. The device is equipped with an Emotion Engine, which analyzes and collects emotional information from the question in real time. The emotional information includes emotional states such as anxiety, tension, and joy.

[0747] 2. Sending questions and emotional information

[0748] Once the user has finished entering their question, the device converts the question and the analyzed emotional information into a data format (e.g., JSON format) and sends it to the server. At this time, the device uses the "requests" communication library to send the data to the server as an HTTP POST request.

[0749] 3. Questioning and emotional information processing

[0750] The server analyzes the received question and emotional information, and passes the question content to the generative AI model, while also passing the emotional information to the emotion engine. The generative AI model, "AIGeneratedResponse," is an artificial intelligence model that understands the question content and generates an appropriate answer.

[0751] 4. Emotionally appropriate adjustment of responses

[0752] The generated answers are adjusted by the emotion engine to use language that is appropriate to the user's emotions. This process adds additional consideration to the generated answers based on the user's emotional state. For example, if a user is feeling anxious, reassuring words such as "relax" will be added.

[0753] 5. Submitting and Viewing Tailored Answers

[0754] The answer, adjusted to suit the user's emotions, is then sent back to the device from the server. The device receives the answer and displays it on the user interface, allowing the user to receive an appropriate answer that takes their emotions into consideration.

[0755] Specific examples

[0756] For example, if a user types a question like "I'm worried about inheriting a house," the following steps will occur:

[0757] 1. The user types, "I'm worried about inheriting my house," and the system recognizes the emotion "anxiety."

[0758] 2. The question and emotion information are sent to the server.

[0759] 3. The server passes the question content to the generation AI model and the emotion information to the emotion engine.

[0760] 4. The generative AI model generates the answer, "Let's start by looking at basic information about your home's assets."

[0761] 5. The emotion engine refines this response to, "Relax, let's start by finding out some basic information about your home's assets."

[0762] 6. The adjusted answer is displayed to the user.

[0763] Prompt Sentence Examples

[0764] User Question: I'm worried about inheriting my house.

[0765] Recognized emotion: Anxiety

[0766] Prompt for generative AI model: Generate appropriate answers to user questions. Emotions considered: Anxiety

[0767] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0768] Step 1:

[0769] The user inputs a question using the device's user interface, and the device retrieves the question. At this time, EmotionEngine runs in the background and analyzes emotional information from the input question in real time. The input is the user's question (e.g., "I'm worried about inheriting my house"), and the output is the question and emotional information (e.g., "anxiety").

[0770] Step 2:

[0771] The device converts the question and emotion information into a data format (for example, JSON format) and sends it to the server. At this time, the communication library "requests" is used to send the data as an HTTP POST request. The input is the question and emotion information, which is converted into JSON format and output as a data packet to be sent.

[0772] Step 3:

[0773] The server analyzes the received question and emotional information, and passes the question content to the generative AI model "AIGeneratedResponse" and the emotional information to the emotion engine. The input is a JSON data packet, which is separated into the question content and emotional information as the analysis result. The output is input data to the generative AI model and the emotion engine.

[0774] Step 4:

[0775] The generative AI model understands the question and generates an appropriate answer. This process uses natural language processing techniques to process the question and generate the best answer. The input is the question, and the output is the generated answer (e.g., "Let's start by looking at basic information about your home's assets.").

[0776] Step 5:

[0777] The emotion engine adjusts the generated answer based on the user's emotional information. For example, if a user feels "anxious," the reassuring phrase "relax" is added. The input is the generated answer and emotional information, and the output is an answer that has been adjusted to suit the emotion (e.g., "Relax, let's start by looking up basic information about your home's assets.").

[0778] Step 6:

[0779] The server converts the adjusted response back into the appropriate data format and sends it to the device, again using the "requests" communication library. The input is the adjusted response, and the output is a data packet sent to the device.

[0780] Step 7:

[0781] The terminal displays the tailored response received from the server on the user interface, allowing the user to obtain an appropriate response that takes their emotions into consideration. The input is the data packet received from the server, and the output is the displayed text message.

[0782] 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.

[0783] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0784] 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.

[0785] [Third embodiment]

[0786] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0787] 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.

[0788] 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).

[0789] 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.

[0790] 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.

[0791] 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).

[0792] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0793] 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.

[0794] 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.

[0795] 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.

[0796] 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.

[0797] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0798] The present invention provides a system that allows users to easily consult with others and receive prompt answers regarding matters related to end-of-life planning and inheritance, in response to the growing elderly population. The following describes in detail the mode for implementing this system.

[0799] overview

[0800] In this system, users input questions via their devices, which are then sent to a server. The server then passes the received questions to a generative AI model, which generates an appropriate answer. The generated answer is then sent back to the device, which then displays it to the user, allowing them to receive appropriate support.

[0801] Embodiment

[0802] 1. The user enters a question

[0803] Users use devices such as smartphones or personal computers to input questions into a dedicated user interface. For example, a question might be, "Please tell me how I should start regarding the inheritance of my house."

[0804] 2. The device sends a question to the server

[0805] After entering a question, the user clicks the send button, which causes the device to send the question to the server via an Internet connection as an HTTP request from the device to the server.

[0806] 3. The server passes the question to the generative AI model to generate an answer.

[0807] The server analyzes the received question and passes it to a generative AI model. This generative AI model uses natural language processing technology, for example, and generates an appropriate answer for the question. The generative AI model has the ability to understand the content of the question and extract an appropriate answer from a huge database.

[0808] 4. The server generates a response and sends it to the device.

[0809] The generated answer is sent from the server to the device, again via the Internet, where the data is formatted in a way that the device can receive it.

[0810] 5. The device displays the answer received from the server to the user.

[0811] The device displays the received answer to the user in a text box, pop-up window, or other format. The user can then decide what to do next based on the displayed answer.

[0812] Specific examples

[0813] For example, if a user types, "Please tell me how to get started on inheriting a house," the following steps will be executed:

[0814] 1. The user enters a question and clicks the submit button.

[0815] 2. The device sends this question to the server.

[0816] 3. The server receives the question and passes it to the generative AI model.

[0817] 4. The generative AI model analyzes the question and generates the answer, "The first step in inheriting a house is to understand the current state of your assets."

[0818] 5. The server sends this response to the terminal.

[0819] 6. The terminal displays the received response to the user.

[0820] In this way, the system of the present invention allows users to easily and quickly obtain useful advice regarding end-of-life planning and inheritance, enabling them to acquire the necessary knowledge before consulting with a specialist, and providing support for taking appropriate measures while reducing psychological burden.

[0821] The processing flow will be explained below.

[0822] Step 1:

[0823] The user inputs a question using the user interface of the terminal. Specifically, the user inputs the question "Please tell me how to get started regarding inheriting a house" into the input form and clicks the submit button.

[0824] Step 2:

[0825] The device detects the click event of the submit button, obtains the entered question as data, and converts this data into an appropriate format (for example, JSON format).

[0826] Step 3:

[0827] The device sends the question data to the server. Specifically, it uses an HTTP POST request to send the question data to the specified endpoint on the server.

[0828] Step 4:

[0829] The server receives the HTTP request, analyzes the question data, extracts the question content from the received data, and prepares it as input for the generative AI model.

[0830] Step 5:

[0831] The server passes the question to the generative AI model and instructs it to generate an answer. The generative AI model used here (for example, one that utilizes natural language processing technology) generates an appropriate answer based on the given question.

[0832] Step 6:

[0833] The generative AI model processes the question and generates an answer, such as, "The first step in inheriting a home is to understand the current state of your assets."

[0834] Step 7:

[0835] The server receives the generated response and formats it as data to be sent to the device, again in an appropriate format such as JSON.

[0836] Step 8:

[0837] The server sends the generated response data to the terminal. Specifically, it returns the response data as an HTTP response.

[0838] Step 9:

[0839] The device analyzes the response data received from the server and displays it in the user interface. For example, a text box might say, "The first step in inheriting a house is to understand the current state of your assets."

[0840] Step 10:

[0841] The user views the answers displayed on their device, decides their next action, and can repeat the process again, if desired, by entering a more specific question.

[0842] In this way, a system is provided that allows users to easily and quickly obtain useful advice regarding end-of-life planning and inheritance.

[0843] Example 1

[0844] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0845] As the elderly population increases, there is a growing need for consultations regarding end-of-life planning and inheritance. However, there are limited ways to acquire the necessary knowledge before consulting a specialist, making it difficult for users to obtain sufficient information. In particular, there is a need for a means to receive prompt and appropriate support.

[0846] 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.

[0847] In this invention, the server includes: [means for a user to input a question to an information processing device;] [means for the information processing device to send the question to an information processing system; and] [means for the information processing system to pass the question to a generative AI model and generate an answer.] This enables [users to receive prompt and appropriate advice and acquire the necessary knowledge before consulting an expert.]

[0848] "User" refers to a person who uses the system, and is a user who uses an information processing device to input a question and obtain an answer.

[0849] An "information processing device" is a terminal such as a smartphone or personal computer, which is a device through which a user inputs a question and communicates with an information processing system.

[0850] An "information processing system" refers to a central system such as a server that receives questions sent from an information processing device, generates answers using a generative AI model, and sends them back to the information processing device.

[0851] A "generative AI model" is an artificial intelligence model that analyzes questions and generates appropriate answers, and refers to a model that uses natural language processing technology.

[0852] "User interface" refers to a screen or application that runs on an information processing device and allows a user to input and send a question.

[0853] "Natural language processing technology" refers to the technology used by generative AI models to understand and analyze human language to generate appropriate answers.

[0854] This invention provides a system that allows users to easily ask questions and receive prompt answers in order to meet the needs for consultations regarding end-of-life planning and inheritance due to the increasing elderly population. The following describes in detail the mode for carrying out this invention.

[0855] System configuration

[0856] The system includes the following main components:

[0857] 1. Information processing device used by the user

[0858] 2. Central Processing Unit (Information Processing System)

[0859] 3. Generative AI Models

[0860] 4. Internet connection

[0861] Information processing device used by the user

[0862] Users use information processing devices such as smartphones and personal computers. These devices have a web browser and dedicated applications installed, and users can input questions through the user interface. For example, it is assumed that a user might input a question such as, "Please tell me how I should start regarding the inheritance of my house."

[0863] Data transmission from an information processing device to an information processing system

[0864] When a user inputs a question and clicks the send button, the information processing device sends the question to the information processing system in the form of an HTTP request. This transmission uses an Internet connection, and the question content is packaged in a format such as JSON.

[0865] Central Processing Unit (Information Processing System)

[0866] The information processing system analyzes the received question and sends it to a generative AI model. This generative AI model uses natural language processing technology to understand the question and generate the optimal answer. The generated answer is packaged in JSON format or similar and sent to the information processing device in HTTP response format.

[0867] Generative AI Models

[0868] A generative AI model uses natural language processing techniques trained from a large dataset. This model generates answers based on prompts received from the server. Below is an example of a prompt for a generative AI model:

[0869] A user has the following question: "How do I get started on inheriting a house?"

[0870] Generate a suitable answer based on this question.

[0871] The model analyzes this prompt sentence, generates an answer such as, "The first step in starting a home inheritance is to understand the current state of your assets," and sends it back to the information processing system.

[0872] Displaying answers on an information processing device

[0873] The information processing device analyzes the answers received from the information processing system and displays them on the user interface. The display format can be a text box or a pop-up window. For example, the user can check the answers on a web page as follows:

[0874] The first step in inheriting a home is to understand the current state of your assets.

[0875] In this way, the system of the present invention allows users to receive prompt and appropriate advice, enabling them to acquire the necessary knowledge before consulting a specialist, reducing the psychological burden and providing support for taking appropriate measures.

[0876] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0877] Step 1:

[0878] The user enters a question.

[0879] Users access the user interface of a web browser or dedicated application through a device such as a smartphone or personal computer. They enter a question in the input field on the screen and click the send button. For example, they write, "Please tell me how to get started regarding inheriting a house." The entered data is temporarily saved in text format in the internal storage.

[0880] Step 2:

[0881] The terminal sends a question to the server.

[0882] The device creates an HTTP POST request to send the entered question to the server over the Internet. This request contains the question in JSON format. For example, it might be sent in the following format:

[0883] json

[0884] {

[0885] "question": "How do I get started on inheriting a house?"

[0886] }

[0887] At this time, the terminal enters a state of waiting for a response after transmission.

[0888] Step 3:

[0889] The server passes the question to a generative AI model to generate an answer.

[0890] The server analyzes the received HTTP request and extracts the question. It then converts the extracted question into a prompt and sends the request to the generative AI model. An example of a prompt is:

[0891] A user has the following question: "How do I get started on inheriting a house?"

[0892] Generate an appropriate answer based on this question.

[0893] The generative AI model analyzes the prompt and uses natural language processing techniques to generate the optimal answer, which is then returned to the server in text format.

[0894] Step 4:

[0895] The server sends the generated response to the terminal.

[0896] The server converts the answer received from the generative AI model into JSON format and sends it to the device as an HTTP response. For example, the following HTTP response is created:

[0897] json

[0898] {

[0899] "answer": "The first step in inheriting a home is to understand the current state of your assets."

[0900] }

[0901] The server sends this data to the terminal and confirms that the response was sent successfully.

[0902] Step 5:

[0903] The terminal displays the response received from the server to the user.

[0904] The device analyzes the received HTTP response and extracts the answer from the JSON format data. The extracted answer is stored in the display area of ​​the user interface and displayed as text. For example, it is displayed on a web page as follows:

[0905] html

[0906]

[0907] The first step in inheriting a home is to understand the current state of your assets.

[0908]

[0909] This allows the user to view the answers provided and decide on their next action.

[0910] Through the above processing steps, this system is able to provide users with prompt and accurate advice.

[0911] (Application example 1)

[0912] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0913] In physical stores, it can be difficult for users to quickly obtain product information. This is especially true when staff are unavailable or when the store is busy, leaving users frustrated and unable to obtain the information they need. This can also increase the workload of store staff, making it difficult to provide efficient service. To solve these problems, a system is needed that allows users to easily obtain product information using their own devices.

[0914] 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.

[0915] In this invention, the server includes: [means for a user to input a question into a terminal;] [means for the terminal to send the question to the server;] [means for the server to pass the question to a generative AI model and generate an answer;] [means for the server to send the generated answer to the terminal;] [means for the terminal to display the answer received from the server to the user;] [means for a user to input information on a terminal installed in a physical store or the user's mobile terminal; and [means for communicating with the server using an internet connection.] This enables users to quickly obtain product information and answers to purchase-related questions in a physical store.

[0916] "User" means an individual or customer who uses the system to enter a question.

[0917] "Terminal" refers to the device used by the user to input questions and communicate with the server. This includes mobile devices and tablets.

[0918] A "server" is a device or system that receives a user's question, passes it to a generative AI model to generate an answer, and then sends the answer back to the terminal.

[0919] A "generative AI model" is an algorithm or system that uses natural language processing techniques to generate answers to user questions.

[0920] An "Internet connection" is a network that a terminal and a server use to communicate with each other.

[0921] "User interface" refers to interactive elements such as screens and input forms through which users can enter questions.

[0922] The present invention provides a system that allows users to input questions using a terminal in a physical store and quickly provides answers using a generative AI model. An embodiment of the present invention will be described in detail below.

[0923] Functions and Configuration

[0924] 1. The user enters a question

[0925] Customers can input questions into a dedicated user interface using a tablet device installed in the physical store or their own mobile device. For example, a question might be, "What is the most popular item in this store?"

[0926] 2. The device sends a question to the server

[0927] When a user types a question and clicks the submit button, the device sends the question to the server over its internet connection via an HTTP request.

[0928] 3. The server passes the question to the generative AI model to generate an answer.

[0929] The server analyzes the received question and passes it to a generative AI model, which uses natural language processing to understand the question and generate the best answer from a database that includes product information and FAQs.

[0930] 4. The server generates a response and sends it to the device.

[0931] The generated answer is sent from the server to the terminal again via the Internet. The sent data is reformatted as necessary and arranged in a format that can be displayed on the terminal.

[0932] 5. The device displays the answer received from the server to the user.

[0933] The terminal displays the response received from the server to the user using a text box or a pop-up window.

[0934] Hardware and software used

[0935] Hardware

[0936] Device: Tablet or mobile device

[0937] Server: A server with the computational resources to receive requests and generate answers using AI models.

[0938] software

[0939] Generative AI model: An AI model that utilizes natural language processing technology such as OpenAI GPT-3

[0940] Network: Communication over an internet connection

[0941] Database: A database that stores product information and FAQs (e.g., MySQL, ElasticSearch)

[0942] Specific examples

[0943] For example, a customer types a question into a tablet device in a store, such as "What is the most popular item in this store?" This question is answered through the following process:

[0944] 1. The customer types into the terminal, "What is the most popular item in this store?"

[0945] 2. The device sends a question to the server.

[0946] 3. The server receives the question and passes it to the generative AI model.

[0947] 4. The generative AI model analyzes the question and generates an answer such as, "Currently, our most popular item is XX."

[0948] 5. The server sends the generated response to the device.

[0949] 6. The terminal displays the received response to the user.

[0950] Example prompt sentence:

[0951] Type, "What is the most popular item in this store?"

[0952] In this way, the system of the present invention allows users to quickly and easily obtain product information even in physical stores, thereby reducing the workload of store staff and improving user satisfaction.

[0953] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0954] Step 1:

[0955] The customer enters their question into the terminal. Using a tablet device installed in the physical store or their own mobile device, the customer enters their question into a dedicated user interface. The entered data is stored in text format on the terminal.

[0956] Step 2:

[0957] The device sends the question to the server. When the user clicks the send button, the device sends the entered question to the server via an Internet connection. At this time, the device formats the question data in the form of an HTTP request and sends it.

[0958] Step 3:

[0959] The server passes the question to the generative AI model, which generates an answer. The server analyzes the received question data and passes it to the generative AI model. The generative AI model uses natural language processing technology to understand the question and generate the optimal answer from a database. The input to the generative AI model is the question data, and the output is the answer text.

[0960] Step 4:

[0961] The server sends the generated answer to the device. The answer text obtained from the generative AI model is then sent back to the device via the Internet. When sending, the answer data is again formatted in HTTP response format.

[0962] Step 5:

[0963] The terminal displays the answer received from the server to the user. The terminal analyzes the answer received from the server and displays it in the user interface. This can be displayed as a text box or a pop-up window, allowing the user to visually confirm it.

[0964] Step 6:

[0965] The user checks the displayed answer. The user looks at the answer displayed on the device and decides the next action to take. At this point, the user can decide whether the question has been resolved.

[0966] 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.

[0967] The present invention combines a system that allows users to easily consult about end-of-life planning and inheritance matters and quickly receive appropriate answers with an emotion engine that recognizes the user's emotions. The following describes in detail the embodiments of the present system.

[0968] overview

[0969] In this system, users input questions via their devices, and the questions and emotional information at the time of input are sent to a server. The server then passes the received questions and emotional information to a generative AI model and emotion engine, which generates an appropriate answer. The generated answer is then further adjusted by the emotion engine to use wording appropriate to the user's emotions, before being sent to the device and displayed to the user.

[0970] Embodiment

[0971] 1. Users enter questions and express their feelings

[0972] The user inputs a question using the device's user interface, and simultaneously, the user's emotions are recognized from the input text using an emotion engine that runs in the background and analyzes the input in real time.

[0973] 2. The device sends the question and emotion information to the server.

[0974] When the user has finished entering their question, they click the send button. The device then receives the question and the analyzed emotion information as data, converts it into an appropriate format (e.g., JSON), and sends it to the server.

[0975] 3. The server passes the question and emotion information to the generative AI model and emotion engine.

[0976] The server analyzes the received question and emotional information and passes them to the generative AI model and emotion engine. At this time, the generative AI model understands the question and generates an appropriate answer. Meanwhile, the emotion engine analyzes the user's emotional information and makes appropriate emotional adjustments to the generative AI model's output.

[0977] 4. The server adjusts the generated answers with an emotion engine

[0978] The response generated by the generative AI model is then translated by the emotion engine into language that matches the user's emotions. For example, if the user is feeling stressed, the response will be accompanied by kind and encouraging words.

[0979] 5. The server sends the adjusted answer to the device.

[0980] The adjusted response is then sent back from the server to the device, again over the Internet, where it is reformatted into a format that the device can receive.

[0981] 6. The device displays the response received from the server to the user.

[0982] The device displays the received answer to the user in a text box, pop-up window, or other format. The user can then decide what to do next based on the displayed answer.

[0983] Specific examples

[0984] For example, if a user types, "Please tell me how to get started on inheriting a house," the following steps will be performed:

[0985] 1. When a user enters a question, the system recognizes emotions such as "anxiety" or "tension."

[0986] 2. The device sends the question and emotion information to the server.

[0987] 3. The server passes the question content to the generative AI model and the emotion information to the emotion engine.

[0988] 4. The generative AI model generates the answer, "The first step when inheriting a house is to understand the current state of your assets."

[0989] 5. The emotion engine adjusts this response based on emotional information and translates it into a gentle statement: "Let's start by relaxing and understanding the current state of your assets."

[0990] 6. The server sends the adjusted response to the device.

[0991] 7. The terminal displays the response received from the server to the user.

[0992] This invention allows users to obtain not only specific answers according to the content of their questions, but also answers that take into consideration their emotions and reduce psychological burdens, which is a great help in obtaining the necessary knowledge before consulting a specialist and taking appropriate measures.

[0993] The processing flow will be explained below.

[0994] Step 1:

[0995] The user inputs a question using the device's user interface. At the same time, the input text is analyzed in real time by the emotion engine. For example, when typing "Please tell me how to start regarding inheriting a house," the user's emotion is recognized as "anxiety."

[0996] Step 2:

[0997] The device detects the click of the send button, obtains the entered question and analyzed emotion information, and converts this data into an appropriate format such as JSON.

[0998] Step 3:

[0999] The device sends the question and emotion information to the server as an HTTP POST request, sending the data to a specified endpoint on the server.

[1000] Step 4:

[1001] The server receives the HTTP request, analyzes the question data and emotion information, extracts the question content and emotion information from the received data, and prepares them as input to the generative AI model and emotion engine.

[1002] Step 5:

[1003] The server passes the question data to the generative AI model and instructs it to generate an answer. The generative AI model understands the question and generates an appropriate answer. For example, it might generate an answer such as, "The first step when inheriting a house is to understand the current state of the assets."

[1004] Step 6:

[1005] The server passes the generated answer to the emotion engine and instructs it to convert it into wording that is appropriate to the user's emotions. The emotion engine takes the user's emotional information into account and adjusts the answer. For example, it converts the answer into gentler language such as, "First, relax and let's start by understanding the current state of your assets."

[1006] Step 7:

[1007] The server receives the adjusted response and formats it as data to send to the device, which is again converted into a suitable format such as JSON.

[1008] Step 8:

[1009] The server sends the adjusted response data to the device as an HTTP response, formatted to be received by the device.

[1010] Step 9:

[1011] The device analyzes the response data received from the server and displays it in the user interface. For example, it might display "First, relax and start by understanding the current state of your assets" in a text box.

[1012] Step 10:

[1013] The user views the tailored answers displayed on their device and decides on their next action, and can repeat the process by entering more specific questions if desired.

[1014] In this way, a system is provided that allows users to not only obtain specific answers according to the content of their questions, but also quickly obtain answers that take into consideration their feelings and reduce psychological burden.

[1015] Example 2

[1016] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1017] Conventional question-and-answer systems often lack consideration for reducing the psychological burden on users when they casually seek advice about end-of-life planning or inheritance. Furthermore, answers provided without considering the user's emotional state may reduce the user's satisfaction. Therefore, there is a need for systems that provide answers that take into account the user's emotional information.

[1018] 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.

[1019] [Means for the user to input a question into the terminal;

[1020] [Means for the terminal to analyze the user's emotions and send questions and emotional information to the server;

[1021] [Means for the server to pass the question and emotion information to the generative AI model and emotion analyzer to generate and tailor an answer;

[1022] [means for the server to send the adjusted response to the terminal;

[1023] [Means for displaying the answer received by the terminal from the server to the user;

[1024] This allows for appropriate responses that take into account the user's emotional state and reduce the user's psychological burden.

[1025] "Means by which a user inputs a question into a terminal" refers to the interface used by a user to input a question as text and the operation thereof.

[1026] "Means for the terminal to analyze the user's emotions and send the question and emotional information to the server" refers to software for analyzing emotions from the user's input and a communication function for sending the analysis results and the question content to the server.

[1027] "Means for the server to pass the question and emotional information to the generative AI model and emotion analysis device to generate and adjust the answer" refers to the process in which the server inputs the question and emotional information it receives into the generative AI model and emotion analysis device to generate an answer to the question, and the process of adjusting the answer to suit the user's emotions.

[1028] "Means for the server to send adjusted answers to the terminal" refers to the function of the server to send answers adjusted by the generative AI model and the emotion analysis device to the terminal via communication means.

[1029] "Means for displaying to the user the answer received by the terminal from the server" refers to a display device and display software for visually presenting to the user the answer received by the terminal from the server.

[1030] This invention is a system that allows users to easily consult about end-of-life planning and inheritance matters and receive prompt and appropriate answers. This system is implemented by having the user input a question through a terminal, and the question and emotional information at the time of input are transmitted to a server.

[1031] Hardware and Software Configuration

[1032] Terminal

[1033] Users can use devices such as PCs and smartphones to input questions. The device is equipped with a user interface (e.g., a web browser or dedicated app). When a user inputs a question, an emotion engine (e.g., "IBM Watson Tone Analyzer") runs in the background and analyzes the emotion from the input in real time.

[1034] server

[1035] The server is the central device that processes questions and emotional information sent by users. Specific software includes a generative AI model (such as "OpenAI GPT-3") and an emotional analysis device. The server performs the following processes based on the received data:

[1036] The question is passed to a generative AI model to generate an answer.

[1037] The emotional information is passed to an emotion analyzer, which adjusts the response to suit the user's emotions.

[1038] Operation details and data processing

[1039] Sending questions and emotional information

[1040] Once the user has finished entering their question into the device, they press the send button. This action causes the device to send the question and analyzed emotion information in JSON format to the server. The transmission is performed using an HTTP POST request.

[1041] Generate and adjust answers

[1042] The server passes the received question and emotional information to the generative AI model and emotion analyzer. The generative AI model generates an appropriate answer, and the emotion analyzer adjusts the answer to match the user's emotions.

[1043] Submitting a tailored response

[1044] The adjusted answer is sent back from the server to the terminal, where it is displayed to the user.

[1045] Specific examples

[1046] For example, if a user types "How do I get started on inheriting a house?", the following steps are performed:

[1047] 1. When a user enters a question, the system recognizes emotions such as "anxiety" or "tension."

[1048] 2. The device sends the question and emotion information to the server.

[1049] 3. The server passes the question content to the generative AI model and the emotional information to the emotion analyzer.

[1050] 4. The generative AI model generates the answer, "The first step when inheriting a house is to understand the current state of your assets."

[1051] 5. The sentiment analyzer adjusts this response based on emotional information and translates it into a gentler response: "Let's start by relaxing and understanding the current state of your assets."

[1052] 6. The server sends the adjusted response to the device.

[1053] 7. The device displays the answer received from the server to the user.

[1054] Prompt Sentence Examples

[1055] It is possible to generate prompt sentences that include the question "How should I start regarding inheriting a house?" along with phrases that recognize emotions such as "anxiety" and "tension." Specifically, the following prompt sentences are possible:

[1056] Q: How do I get started on inheriting a house?

[1057] Emotional information: anxiety, tension

[1058] By passing this prompt to a generative AI model, a specific answer can be obtained, such as "Let's start by relaxing and understanding the current state of your assets."

[1059] The above configuration and processing not only allows users to receive specific answers based on their questions, but also answers that take into consideration their emotions and reduce their psychological burden. This is a great help in obtaining the necessary knowledge before consulting a specialist and taking appropriate measures.

[1060] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1061] System processing flow

[1062] Step 1:

[1063] The user enters a question into the terminal

[1064] Operation and Input

[1065] The user enters a question into the text box on the terminal. For example, the user might enter, "Please tell me how to get started regarding inheriting a house."

[1066] Data processing and output

[1067] The device receives this input, and an emotion engine (e.g., "IBM Watson Tone Analyzer") analyzes the input text in the background and detects the user's emotion (e.g., "anxiety" or "tension") in real time.

[1068] Step 2:

[1069] The device sends the question and emotion information to the server.

[1070] Operation and Input

[1071] When the user presses the send button, the terminal acquires the question entered by the user and the analysis results by the emotion engine.

[1072] Data processing and output

[1073] The device converts this data into JSON format and sends it to the server using an HTTP POST request. Specific data includes "Question: How should I start regarding inheriting a house?" and "Emotional information: Anxiety, tension."

[1074] Step 3:

[1075] The server receives the question and emotion information.

[1076] Operation and Input

[1077] The server receives the JSON data sent from the terminal.

[1078] Data processing and output

[1079] The server parses the received JSON data and extracts the question ("Please tell me how to start regarding inheritance of a house") and emotional information ("Anxiety, tension"), which is then passed to the next step.

[1080] Step 4:

[1081] The server sends the question content to the AI ​​model and the emotional information to the emotion analyzer.

[1082] Operation and Input

[1083] The server sends the question content to the generation AI model and the emotional information to the emotion analysis device.

[1084] Data processing and output

[1085] A generative AI model (e.g., "OpenAI GPT-3") analyzes the question and generates an appropriate answer ("The first step in inheriting a house is to understand the current state of your assets."). At the same time, an emotion analyzer analyzes emotional information and provides information to adjust the answer.

[1086] Step 5:

[1087] A generative AI model generates answers, and a sentiment analyzer adjusts them.

[1088] Operation and Input

[1089] Let's say the generative AI model's answer is, "The first step when starting to inherit a house is to understand the current state of the assets."

[1090] Data processing and output

[1091] The emotion analyzer adjusts this response based on the user's emotions ("anxiety, tension") to "Let's start by relaxing and understanding the current state of your assets." The adjusted response is sent to the next step.

[1092] Step 6:

[1093] The server sends the adjusted answer to the device.

[1094] Operation and Input

[1095] The server receives the response adjusted by the emotion analyzer.

[1096] Data processing and output

[1097] The server converts the tailored response ("Let's start by relaxing and understanding the current state of your assets") into JSON format and sends it to the device using an HTTP POST request.

[1098] Step 7:

[1099] Display the answer received by the device

[1100] Operation and Input

[1101] The terminal parses the JSON data received from the server.

[1102] Data processing and output

[1103] The device displays the adjusted response to the user, specifically displaying a message on the screen saying, "First, relax and let's start by understanding the current state of your assets."

[1104] The above steps complete the series of processes for the system to analyze the user's input and provide an appropriate answer.

[1105] (Application example 2)

[1106] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1107] In recent years, the number of users gathering information and seeking advice on inheritance and end-of-life planning has been increasing. However, many of these situations involve emotional burdens, and conventional systems are often unable to adequately address these. Furthermore, current systems have difficulty providing answers that take users' emotions into consideration, which is one of the factors that reduces user satisfaction. The purpose of this invention is to provide a consultation system for inheritance and end-of-life planning that adapts to users' emotions, thereby reducing psychological burdens and providing more appropriate answers more quickly.

[1108] 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.

[1109] In this invention, the server includes: a means for a user to input a question into a terminal and provide emotion information; a means for the terminal to transmit the question and emotion information to the server; a means for the server to pass the question to a generative AI model and the emotion information to an emotion engine; a means for the server to adjust the generated answer using the emotion engine to adjust the wording to match the emotion; a means for the server to transmit the adjusted answer to the terminal; and a means for the terminal to display the adjusted answer received from the server to the user. This makes it possible to quickly provide an appropriate answer that matches the user's emotion and reduce psychological burden.

[1110] A "terminal" is a device operated by a user, which inputs questions and emotional information and communicates with a server.

[1111] A "question" is text information entered by the user regarding inheritance or end-of-life planning.

[1112] "Emotional information" is data about the user's emotions that the system analyzes and recognizes in real time when the user enters a question.

[1113] The "server" is a computer system that receives questions and emotion information entered by users and generates appropriate answers using a generative AI model and emotion engine.

[1114] A "generative AI model" is an artificial intelligence model installed on a server, and is a technology for generating appropriate answers to users' questions.

[1115] An "emotion engine" is a technology installed on a server or terminal that analyzes the user's emotional information and adjusts the generated answers based on that information.

[1116] "User interface" refers to a function that allows users to input questions and provide emotional information through a terminal.

[1117] "Natural language processing technology" is a technology that allows a server to understand text data and generate an appropriate response when generating answers using a generative AI model.

[1118] "Adjustment" is a process in which the generated answer is changed to wording that is appropriate to the user's emotions using an emotion engine.

[1119] An "answer" is a response to a user's question generated by a generative AI model and adjusted by an emotion engine.

[1120] The following components are required to implement this invention: A user inputs a question through a terminal, and the question and emotional information are sent to a server. The server passes the received question and emotional information to a generative AI model and an emotional engine, which generates an appropriate answer. The generated answer is further adjusted by the emotional engine to use wording appropriate to the user's emotions, and then sent to the terminal and displayed to the user.

[1121] Program Description

[1122] 1. Enter a question and provide emotional information

[1123] The user inputs a question using the device's user interface. The device is equipped with an Emotion Engine, which analyzes and collects emotional information from the question in real time. The emotional information includes emotional states such as anxiety, tension, and joy.

[1124] 2. Sending questions and emotional information

[1125] Once the user has finished entering their question, the device converts the question and the analyzed emotional information into a data format (e.g., JSON format) and sends it to the server. At this time, the device uses the "requests" communication library to send the data to the server as an HTTP POST request.

[1126] 3. Questioning and emotional information processing

[1127] The server analyzes the received question and emotional information, and passes the question content to the generative AI model, while also passing the emotional information to the emotion engine. The generative AI model, "AIGeneratedResponse," is an artificial intelligence model that understands the question content and generates an appropriate answer.

[1128] 4. Emotionally appropriate adjustment of responses

[1129] The generated answers are adjusted by the emotion engine to use language that is appropriate to the user's emotions. This process adds additional consideration to the generated answers based on the user's emotional state. For example, if a user is feeling anxious, reassuring words such as "relax" will be added.

[1130] 5. Submitting and Viewing Tailored Answers

[1131] The answer, adjusted to suit the user's emotions, is then sent back to the device from the server. The device receives the answer and displays it on the user interface, allowing the user to receive an appropriate answer that takes their emotions into consideration.

[1132] Specific examples

[1133] For example, if a user types a question like "I'm worried about inheriting a house," the following steps will occur:

[1134] 1. The user types, "I'm worried about inheriting my house," and the system recognizes the emotion "anxiety."

[1135] 2. The question and emotion information are sent to the server.

[1136] 3. The server passes the question content to the generation AI model and the emotion information to the emotion engine.

[1137] 4. The generative AI model generates the answer, "Let's start by looking at basic information about your home's assets."

[1138] 5. The emotion engine refines this response to, "Relax, let's start by finding out some basic information about your home's assets."

[1139] 6. The adjusted answer is displayed to the user.

[1140] Prompt Sentence Examples

[1141] User Question: I'm worried about inheriting my house.

[1142] Recognized emotion: Anxiety

[1143] Prompt for generative AI model: Generate appropriate answers to user questions. Emotions considered: Anxiety

[1144] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1145] Step 1:

[1146] The user inputs a question using the device's user interface, and the device retrieves the question. At this time, EmotionEngine runs in the background and analyzes emotional information from the input question in real time. The input is the user's question (e.g., "I'm worried about inheriting my house"), and the output is the question and emotional information (e.g., "anxiety").

[1147] Step 2:

[1148] The device converts the question and emotion information into a data format (for example, JSON format) and sends it to the server. At this time, the communication library "requests" is used to send the data as an HTTP POST request. The input is the question and emotion information, which is converted into JSON format and output as a data packet to be sent.

[1149] Step 3:

[1150] The server analyzes the received question and emotional information, and passes the question content to the generative AI model "AIGeneratedResponse" and the emotional information to the emotion engine. The input is a JSON data packet, which is separated into the question content and emotional information as the analysis result. The output is input data to the generative AI model and the emotion engine.

[1151] Step 4:

[1152] The generative AI model understands the question and generates an appropriate answer. This process uses natural language processing techniques to process the question and generate the best answer. The input is the question, and the output is the generated answer (e.g., "Let's start by looking at basic information about your home's assets.").

[1153] Step 5:

[1154] The emotion engine adjusts the generated answer based on the user's emotional information. For example, if a user feels "anxious," the reassuring phrase "relax" is added. The input is the generated answer and emotional information, and the output is an answer that has been adjusted to suit the emotion (e.g., "Relax, let's start by looking up basic information about your home's assets.").

[1155] Step 6:

[1156] The server converts the adjusted response back into the appropriate data format and sends it to the device, again using the "requests" communication library. The input is the adjusted response, and the output is a data packet sent to the device.

[1157] Step 7:

[1158] The terminal displays the tailored response received from the server on the user interface, allowing the user to obtain an appropriate response that takes their emotions into consideration. The input is the data packet received from the server, and the output is the displayed text message.

[1159] 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.

[1160] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1161] 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.

[1162] [Fourth embodiment]

[1163] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1164] 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.

[1165] 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).

[1166] 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.

[1167] 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.

[1168] 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).

[1169] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1170] 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.

[1171] 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.

[1172] 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.

[1173] 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.

[1174] 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.

[1175] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1176] The present invention provides a system that allows users to easily consult with others and receive prompt answers regarding matters related to end-of-life planning and inheritance, in response to the growing elderly population. The following describes in detail the mode for implementing this system.

[1177] overview

[1178] In this system, users input questions via their devices, which are then sent to a server. The server then passes the received questions to a generative AI model, which generates an appropriate answer. The generated answer is then sent back to the device, which then displays it to the user, allowing them to receive appropriate support.

[1179] Embodiment

[1180] 1. The user enters a question

[1181] Users use devices such as smartphones or personal computers to input questions into a dedicated user interface. For example, a question might be, "Please tell me how I should start regarding the inheritance of my house."

[1182] 2. The device sends a question to the server

[1183] After entering a question, the user clicks the send button, which causes the device to send the question to the server via an Internet connection as an HTTP request from the device to the server.

[1184] 3. The server passes the question to the generative AI model to generate an answer.

[1185] The server analyzes the received question and passes it to a generative AI model. This generative AI model uses natural language processing technology, for example, and generates an appropriate answer for the question. The generative AI model has the ability to understand the content of the question and extract an appropriate answer from a huge database.

[1186] 4. The server generates a response and sends it to the device.

[1187] The generated answer is sent from the server to the device, again via the Internet, where the data is formatted in a way that the device can receive it.

[1188] 5. The device displays the answer received from the server to the user.

[1189] The device displays the received answer to the user in a text box, pop-up window, or other format. The user can then decide what to do next based on the displayed answer.

[1190] Specific examples

[1191] For example, if a user types, "Please tell me how to get started on inheriting a house," the following steps will be executed:

[1192] 1. The user enters a question and clicks the submit button.

[1193] 2. The device sends this question to the server.

[1194] 3. The server receives the question and passes it to the generative AI model.

[1195] 4. The generative AI model analyzes the question and generates the answer, "The first step in inheriting a house is to understand the current state of your assets."

[1196] 5. The server sends this response to the terminal.

[1197] 6. The terminal displays the received response to the user.

[1198] In this way, the system of the present invention allows users to easily and quickly obtain useful advice regarding end-of-life planning and inheritance, enabling them to acquire the necessary knowledge before consulting with a specialist, and providing support for taking appropriate measures while reducing psychological burden.

[1199] The processing flow will be explained below.

[1200] Step 1:

[1201] The user inputs a question using the user interface of the terminal. Specifically, the user inputs the question "Please tell me how to get started regarding inheriting a house" into the input form and clicks the submit button.

[1202] Step 2:

[1203] The device detects the click event of the submit button, obtains the entered question as data, and converts this data into an appropriate format (for example, JSON format).

[1204] Step 3:

[1205] The device sends the question data to the server. Specifically, it uses an HTTP POST request to send the question data to the specified endpoint on the server.

[1206] Step 4:

[1207] The server receives the HTTP request, analyzes the question data, extracts the question content from the received data, and prepares it as input for the generative AI model.

[1208] Step 5:

[1209] The server passes the question to the generative AI model and instructs it to generate an answer. The generative AI model used here (for example, one that utilizes natural language processing technology) generates an appropriate answer based on the given question.

[1210] Step 6:

[1211] The generative AI model processes the question and generates an answer, such as, "The first step in inheriting a home is to understand the current state of your assets."

[1212] Step 7:

[1213] The server receives the generated response and formats it as data to be sent to the device, again in an appropriate format such as JSON.

[1214] Step 8:

[1215] The server sends the generated response data to the terminal. Specifically, it returns the response data as an HTTP response.

[1216] Step 9:

[1217] The device analyzes the response data received from the server and displays it in the user interface. For example, a text box might say, "The first step in inheriting a house is to understand the current state of your assets."

[1218] Step 10:

[1219] The user views the answers displayed on their device, decides their next action, and can repeat the process again, if desired, by entering a more specific question.

[1220] In this way, a system is provided that allows users to easily and quickly obtain useful advice regarding end-of-life planning and inheritance.

[1221] Example 1

[1222] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1223] As the elderly population increases, there is a growing need for consultations regarding end-of-life planning and inheritance. However, there are limited ways to acquire the necessary knowledge before consulting a specialist, making it difficult for users to obtain sufficient information. In particular, there is a need for a means to receive prompt and appropriate support.

[1224] 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.

[1225] In this invention, the server includes: [means for a user to input a question to an information processing device;] [means for the information processing device to send the question to an information processing system; and] [means for the information processing system to pass the question to a generative AI model and generate an answer.] This enables [users to receive prompt and appropriate advice and acquire the necessary knowledge before consulting an expert.]

[1226] "User" refers to a person who uses the system, and is a user who uses an information processing device to input a question and obtain an answer.

[1227] An "information processing device" is a terminal such as a smartphone or personal computer, which is a device through which a user inputs a question and communicates with an information processing system.

[1228] An "information processing system" refers to a central system such as a server that receives questions sent from an information processing device, generates answers using a generative AI model, and sends them back to the information processing device.

[1229] A "generative AI model" is an artificial intelligence model that analyzes questions and generates appropriate answers, and refers to a model that uses natural language processing technology.

[1230] "User interface" refers to a screen or application that runs on an information processing device and allows a user to input and send a question.

[1231] "Natural language processing technology" refers to the technology used by generative AI models to understand and analyze human language to generate appropriate answers.

[1232] This invention provides a system that allows users to easily ask questions and receive prompt answers in order to meet the needs for consultations regarding end-of-life planning and inheritance due to the increasing elderly population. The following describes in detail the mode for carrying out this invention.

[1233] System configuration

[1234] The system includes the following main components:

[1235] 1. Information processing device used by the user

[1236] 2. Central Processing Unit (Information Processing System)

[1237] 3. Generative AI Models

[1238] 4. Internet connection

[1239] Information processing device used by the user

[1240] Users use information processing devices such as smartphones and personal computers. These devices have a web browser and dedicated applications installed, and users can input questions through the user interface. For example, it is assumed that a user might input a question such as, "Please tell me how I should start regarding the inheritance of my house."

[1241] Data transmission from an information processing device to an information processing system

[1242] When a user inputs a question and clicks the send button, the information processing device sends the question to the information processing system in the form of an HTTP request. This transmission uses an Internet connection, and the question content is packaged in a format such as JSON.

[1243] Central Processing Unit (Information Processing System)

[1244] The information processing system analyzes the received question and sends it to a generative AI model. This generative AI model uses natural language processing technology to understand the question and generate the optimal answer. The generated answer is packaged in JSON format or similar and sent to the information processing device in HTTP response format.

[1245] Generative AI Models

[1246] A generative AI model uses natural language processing techniques trained from a large dataset. This model generates answers based on prompts received from the server. Below is an example of a prompt for a generative AI model:

[1247] A user has the following question: "How do I get started on inheriting a house?"

[1248] Generate a suitable answer based on this question.

[1249] The model analyzes this prompt sentence, generates an answer such as, "The first step in starting a home inheritance is to understand the current state of your assets," and sends it back to the information processing system.

[1250] Displaying answers on an information processing device

[1251] The information processing device analyzes the answers received from the information processing system and displays them on the user interface. The display format can be a text box or a pop-up window. For example, the user can check the answers on a web page as follows:

[1252] The first step in inheriting a home is to understand the current state of your assets.

[1253] In this way, the system of the present invention allows users to receive prompt and appropriate advice, enabling them to acquire the necessary knowledge before consulting a specialist, reducing the psychological burden and providing support for taking appropriate measures.

[1254] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1255] Step 1:

[1256] The user enters a question.

[1257] Users access the user interface of a web browser or dedicated application through a device such as a smartphone or personal computer. They enter a question in the input field on the screen and click the send button. For example, they write, "Please tell me how to get started regarding inheriting a house." The entered data is temporarily saved in text format in the internal storage.

[1258] Step 2:

[1259] The terminal sends a question to the server.

[1260] The device creates an HTTP POST request to send the entered question to the server over the Internet. This request contains the question in JSON format. For example, it might be sent in the following format:

[1261] json

[1262] {

[1263] "question": "How do I get started on inheriting a house?"

[1264] }

[1265] At this time, the terminal enters a state of waiting for a response after transmission.

[1266] Step 3:

[1267] The server passes the question to a generative AI model to generate an answer.

[1268] The server analyzes the received HTTP request and extracts the question. It then converts the extracted question into a prompt and sends the request to the generative AI model. An example of a prompt is:

[1269] A user has the following question: "How do I get started on inheriting a house?"

[1270] Generate an appropriate answer based on this question.

[1271] The generative AI model analyzes the prompt and uses natural language processing techniques to generate the optimal answer, which is then returned to the server in text format.

[1272] Step 4:

[1273] The server sends the generated response to the terminal.

[1274] The server converts the answer received from the generative AI model into JSON format and sends it to the device as an HTTP response. For example, the following HTTP response is created:

[1275] json

[1276] {

[1277] "answer": "The first step in inheriting a home is to understand the current state of your assets."

[1278] }

[1279] The server sends this data to the terminal and confirms that the response was sent successfully.

[1280] Step 5:

[1281] The terminal displays the response received from the server to the user.

[1282] The device analyzes the received HTTP response and extracts the answer from the JSON format data. The extracted answer is stored in the display area of ​​the user interface and displayed as text. For example, it is displayed on a web page as follows:

[1283] html

[1284]

[1285] The first step in inheriting a home is to understand the current state of your assets.

[1286]

[1287] This allows the user to view the answers provided and decide on their next action.

[1288] Through the above processing steps, this system is able to provide users with prompt and accurate advice.

[1289] (Application example 1)

[1290] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1291] In physical stores, it can be difficult for users to quickly obtain product information. This is especially true when staff are unavailable or when the store is busy, leaving users frustrated and unable to obtain the information they need. This can also increase the workload of store staff, making it difficult to provide efficient service. To solve these problems, a system is needed that allows users to easily obtain product information using their own devices.

[1292] 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.

[1293] In this invention, the server includes: [means for a user to input a question into a terminal;] [means for the terminal to send the question to the server;] [means for the server to pass the question to a generative AI model and generate an answer;] [means for the server to send the generated answer to the terminal;] [means for the terminal to display the answer received from the server to the user;] [means for a user to input information on a terminal installed in a physical store or the user's mobile terminal; and [means for communicating with the server using an internet connection.] This enables users to quickly obtain product information and answers to purchase-related questions in a physical store.

[1294] "User" means an individual or customer who uses the system to enter a question.

[1295] "Terminal" refers to the device used by the user to input questions and communicate with the server. This includes mobile devices and tablets.

[1296] A "server" is a device or system that receives a user's question, passes it to a generative AI model to generate an answer, and then sends the answer back to the terminal.

[1297] A "generative AI model" is an algorithm or system that uses natural language processing techniques to generate answers to user questions.

[1298] An "Internet connection" is a network that a terminal and a server use to communicate with each other.

[1299] "User interface" refers to interactive elements such as screens and input forms through which users can enter questions.

[1300] The present invention provides a system that allows users to input questions using a terminal in a physical store and quickly provides answers using a generative AI model. An embodiment of the present invention will be described in detail below.

[1301] Functions and Configuration

[1302] 1. The user enters a question

[1303] Customers can input questions into a dedicated user interface using a tablet device installed in the physical store or their own mobile device. For example, a question might be, "What is the most popular item in this store?"

[1304] 2. The device sends a question to the server

[1305] When a user types a question and clicks the submit button, the device sends the question to the server over its internet connection via an HTTP request.

[1306] 3. The server passes the question to the generative AI model to generate an answer.

[1307] The server analyzes the received question and passes it to a generative AI model, which uses natural language processing to understand the question and generate the best answer from a database that includes product information and FAQs.

[1308] 4. The server generates a response and sends it to the device.

[1309] The generated answer is sent from the server to the terminal again via the Internet. The sent data is reformatted as necessary and arranged in a format that can be displayed on the terminal.

[1310] 5. The device displays the answer received from the server to the user.

[1311] The terminal displays the response received from the server to the user using a text box or a pop-up window.

[1312] Hardware and software used

[1313] Hardware

[1314] Device: Tablet or mobile device

[1315] Server: A server with the computational resources to receive requests and generate answers using AI models.

[1316] software

[1317] Generative AI model: An AI model that utilizes natural language processing technology such as OpenAI GPT-3

[1318] Network: Communication over an internet connection

[1319] Database: A database that stores product information and FAQs (e.g., MySQL, ElasticSearch)

[1320] Specific examples

[1321] For example, a customer types a question into a tablet device in a store, such as "What is the most popular item in this store?" This question is answered through the following process:

[1322] 1. The customer types into the terminal, "What is the most popular item in this store?"

[1323] 2. The device sends a question to the server.

[1324] 3. The server receives the question and passes it to the generative AI model.

[1325] 4. The generative AI model analyzes the question and generates an answer such as, "Currently, our most popular item is XX."

[1326] 5. The server sends the generated response to the device.

[1327] 6. The terminal displays the received response to the user.

[1328] Example prompt sentence:

[1329] Type, "What is the most popular item in this store?"

[1330] In this way, the system of the present invention allows users to quickly and easily obtain product information even in physical stores, thereby reducing the workload of store staff and improving user satisfaction.

[1331] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1332] Step 1:

[1333] The customer enters their question into the terminal. Using a tablet device installed in the physical store or their own mobile device, the customer enters their question into a dedicated user interface. The entered data is stored in text format on the terminal.

[1334] Step 2:

[1335] The device sends the question to the server. When the user clicks the send button, the device sends the entered question to the server via an Internet connection. At this time, the device formats the question data in the form of an HTTP request and sends it.

[1336] Step 3:

[1337] The server passes the question to the generative AI model, which generates an answer. The server analyzes the received question data and passes it to the generative AI model. The generative AI model uses natural language processing technology to understand the question and generate the optimal answer from a database. The input to the generative AI model is the question data, and the output is the answer text.

[1338] Step 4:

[1339] The server sends the generated answer to the device. The answer text obtained from the generative AI model is then sent back to the device via the Internet. When sending, the answer data is again formatted in HTTP response format.

[1340] Step 5:

[1341] The terminal displays the answer received from the server to the user. The terminal analyzes the answer received from the server and displays it in the user interface. This can be displayed as a text box or a pop-up window, allowing the user to visually confirm it.

[1342] Step 6:

[1343] The user checks the displayed answer. The user looks at the answer displayed on the device and decides the next action to take. At this point, the user can decide whether the question has been resolved.

[1344] 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.

[1345] The present invention combines a system that allows users to easily consult about end-of-life planning and inheritance matters and quickly receive appropriate answers with an emotion engine that recognizes the user's emotions. The following describes in detail the embodiments of the present system.

[1346] overview

[1347] In this system, users input questions via their devices, and the questions and emotional information at the time of input are sent to a server. The server then passes the received questions and emotional information to a generative AI model and emotion engine, which generates an appropriate answer. The generated answer is then further adjusted by the emotion engine to use wording appropriate to the user's emotions, before being sent to the device and displayed to the user.

[1348] Embodiment

[1349] 1. Users enter questions and express their feelings

[1350] The user inputs a question using the device's user interface, and simultaneously, the user's emotions are recognized from the input text using an emotion engine that runs in the background and analyzes the input in real time.

[1351] 2. The device sends the question and emotion information to the server.

[1352] When the user has finished entering their question, they click the send button. The device then receives the question and the analyzed emotion information as data, converts it into an appropriate format (e.g., JSON), and sends it to the server.

[1353] 3. The server passes the question and emotion information to the generative AI model and emotion engine.

[1354] The server analyzes the received question and emotional information and passes them to the generative AI model and emotion engine. At this time, the generative AI model understands the question and generates an appropriate answer. Meanwhile, the emotion engine analyzes the user's emotional information and makes appropriate emotional adjustments to the generative AI model's output.

[1355] 4. The server adjusts the generated answers with an emotion engine

[1356] The response generated by the generative AI model is then translated by the emotion engine into language that matches the user's emotions. For example, if the user is feeling stressed, the response will be accompanied by kind and encouraging words.

[1357] 5. The server sends the adjusted answer to the device.

[1358] The adjusted response is then sent back from the server to the device, again over the Internet, where it is reformatted into a format that the device can receive.

[1359] 6. The device displays the response received from the server to the user.

[1360] The device displays the received answer to the user in a text box, pop-up window, or other format. The user can then decide what to do next based on the displayed answer.

[1361] Specific examples

[1362] For example, if a user types, "Please tell me how to get started on inheriting a house," the following steps will be performed:

[1363] 1. When a user enters a question, the system recognizes emotions such as "anxiety" or "tension."

[1364] 2. The device sends the question and emotion information to the server.

[1365] 3. The server passes the question content to the generative AI model and the emotion information to the emotion engine.

[1366] 4. The generative AI model generates the answer, "The first step when inheriting a house is to understand the current state of your assets."

[1367] 5. The emotion engine adjusts this response based on emotional information and translates it into a gentle statement: "Let's start by relaxing and understanding the current state of your assets."

[1368] 6. The server sends the adjusted response to the device.

[1369] 7. The terminal displays the response received from the server to the user.

[1370] This invention allows users to obtain not only specific answers according to the content of their questions, but also answers that take into consideration their emotions and reduce psychological burdens, which is a great help in obtaining the necessary knowledge before consulting a specialist and taking appropriate measures.

[1371] The processing flow will be explained below.

[1372] Step 1:

[1373] The user inputs a question using the device's user interface. At the same time, the input text is analyzed in real time by the emotion engine. For example, when typing "Please tell me how to start regarding inheriting a house," the user's emotion is recognized as "anxiety."

[1374] Step 2:

[1375] The device detects the click of the send button, obtains the entered question and analyzed emotion information, and converts this data into an appropriate format such as JSON.

[1376] Step 3:

[1377] The device sends the question and emotion information to the server as an HTTP POST request, sending the data to a specified endpoint on the server.

[1378] Step 4:

[1379] The server receives the HTTP request, analyzes the question data and emotion information, extracts the question content and emotion information from the received data, and prepares them as input to the generative AI model and emotion engine.

[1380] Step 5:

[1381] The server passes the question data to the generative AI model and instructs it to generate an answer. The generative AI model understands the question and generates an appropriate answer. For example, it might generate an answer such as, "The first step when inheriting a house is to understand the current state of the assets."

[1382] Step 6:

[1383] The server passes the generated answer to the emotion engine and instructs it to convert it into wording that is appropriate to the user's emotions. The emotion engine takes the user's emotional information into account and adjusts the answer. For example, it converts the answer into gentler language such as, "First, relax and let's start by understanding the current state of your assets."

[1384] Step 7:

[1385] The server receives the adjusted response and formats it as data to send to the device, which is again converted into a suitable format such as JSON.

[1386] Step 8:

[1387] The server sends the adjusted response data to the device as an HTTP response, formatted to be received by the device.

[1388] Step 9:

[1389] The device analyzes the response data received from the server and displays it in the user interface. For example, it might display "First, relax and start by understanding the current state of your assets" in a text box.

[1390] Step 10:

[1391] The user views the tailored answers displayed on their device and decides on their next action, and can repeat the process by entering more specific questions if desired.

[1392] In this way, a system is provided that allows users to not only obtain specific answers according to the content of their questions, but also quickly obtain answers that take into consideration their feelings and reduce psychological burden.

[1393] Example 2

[1394] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1395] Conventional question-and-answer systems often lack consideration for reducing the psychological burden on users when they casually seek advice about end-of-life planning or inheritance. Furthermore, answers provided without considering the user's emotional state may reduce the user's satisfaction. Therefore, there is a need for systems that provide answers that take into account the user's emotional information.

[1396] 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.

[1397] [Means for the user to input a question into the terminal;

[1398] [Means for the terminal to analyze the user's emotions and send questions and emotional information to the server;

[1399] [Means for the server to pass the question and emotion information to the generative AI model and emotion analyzer to generate and tailor an answer;

[1400] [means for the server to send the adjusted response to the terminal;

[1401] [Means for displaying the answer received by the terminal from the server to the user;

[1402] This allows for appropriate responses that take into account the user's emotional state and reduce the user's psychological burden.

[1403] "Means by which a user inputs a question into a terminal" refers to the interface used by a user to input a question as text and the operation thereof.

[1404] "Means for the terminal to analyze the user's emotions and send the question and emotional information to the server" refers to software for analyzing emotions from the user's input and a communication function for sending the analysis results and the question content to the server.

[1405] "Means for the server to pass the question and emotional information to the generative AI model and emotion analysis device to generate and adjust the answer" refers to the process in which the server inputs the question and emotional information it receives into the generative AI model and emotion analysis device to generate an answer to the question, and the process of adjusting the answer to suit the user's emotions.

[1406] "Means for the server to send adjusted answers to the terminal" refers to the function of the server to send answers adjusted by the generative AI model and the emotion analysis device to the terminal via communication means.

[1407] "Means for displaying to the user the answer received by the terminal from the server" refers to a display device and display software for visually presenting to the user the answer received by the terminal from the server.

[1408] This invention is a system that allows users to easily consult about end-of-life planning and inheritance matters and receive prompt and appropriate answers. This system is implemented by having the user input a question through a terminal, and the question and emotional information at the time of input are transmitted to a server.

[1409] Hardware and Software Configuration

[1410] Terminal

[1411] Users can use devices such as PCs and smartphones to input questions. The device is equipped with a user interface (e.g., a web browser or dedicated app). When a user inputs a question, an emotion engine (e.g., "IBM Watson Tone Analyzer") runs in the background and analyzes the emotion from the input in real time.

[1412] server

[1413] The server is the central device that processes questions and emotional information sent by users. Specific software includes a generative AI model (such as "OpenAI GPT-3") and an emotional analysis device. The server performs the following processes based on the received data:

[1414] The question is passed to a generative AI model to generate an answer.

[1415] The emotional information is passed to an emotion analyzer, which adjusts the response to suit the user's emotions.

[1416] Operation details and data processing

[1417] Sending questions and emotional information

[1418] Once the user has finished entering their question into the device, they press the send button. This action causes the device to send the question and analyzed emotion information in JSON format to the server. The transmission is performed using an HTTP POST request.

[1419] Generate and adjust answers

[1420] The server passes the received question and emotional information to the generative AI model and emotion analyzer. The generative AI model generates an appropriate answer, and the emotion analyzer adjusts the answer to match the user's emotions.

[1421] Submitting a tailored response

[1422] The adjusted answer is sent back from the server to the terminal, where it is displayed to the user.

[1423] Specific examples

[1424] For example, if a user types "How do I get started on inheriting a house?", the following steps are performed:

[1425] 1. When a user enters a question, the system recognizes emotions such as "anxiety" or "tension."

[1426] 2. The device sends the question and emotion information to the server.

[1427] 3. The server passes the question content to the generative AI model and the emotional information to the emotion analyzer.

[1428] 4. The generative AI model generates the answer, "The first step when inheriting a house is to understand the current state of your assets."

[1429] 5. The sentiment analyzer adjusts this response based on emotional information and translates it into a gentler response: "Let's start by relaxing and understanding the current state of your assets."

[1430] 6. The server sends the adjusted response to the device.

[1431] 7. The device displays the answer received from the server to the user.

[1432] Prompt Sentence Examples

[1433] It is possible to generate prompt sentences that include the question "How should I start regarding inheriting a house?" along with phrases that recognize emotions such as "anxiety" and "tension." Specifically, the following prompt sentences are possible:

[1434] Q: How do I get started on inheriting a house?

[1435] Emotional information: anxiety, tension

[1436] By passing this prompt to a generative AI model, a specific answer can be obtained, such as "Let's start by relaxing and understanding the current state of your assets."

[1437] The above configuration and processing not only allows users to receive specific answers based on their questions, but also answers that take into consideration their emotions and reduce their psychological burden. This is a great help in obtaining the necessary knowledge before consulting a specialist and taking appropriate measures.

[1438] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1439] System processing flow

[1440] Step 1:

[1441] The user enters a question into the terminal

[1442] Operation and Input

[1443] The user enters a question into the text box on the terminal. For example, the user might enter, "Please tell me how to get started regarding inheriting a house."

[1444] Data processing and output

[1445] The device receives this input, and an emotion engine (e.g., "IBM Watson Tone Analyzer") analyzes the input text in the background and detects the user's emotion (e.g., "anxiety" or "tension") in real time.

[1446] Step 2:

[1447] The device sends the question and emotion information to the server.

[1448] Operation and Input

[1449] When the user presses the send button, the terminal acquires the question entered by the user and the analysis results by the emotion engine.

[1450] Data processing and output

[1451] The device converts this data into JSON format and sends it to the server using an HTTP POST request. Specific data includes "Question: How should I start regarding inheriting a house?" and "Emotional information: Anxiety, tension."

[1452] Step 3:

[1453] The server receives the question and emotion information.

[1454] Operation and Input

[1455] The server receives the JSON data sent from the terminal.

[1456] Data processing and output

[1457] The server parses the received JSON data and extracts the question ("Please tell me how to start regarding inheritance of a house") and emotional information ("Anxiety, tension"), which is then passed to the next step.

[1458] Step 4:

[1459] The server sends the question content to the AI ​​model and the emotional information to the emotion analyzer.

[1460] Operation and Input

[1461] The server sends the question content to the generation AI model and the emotional information to the emotion analysis device.

[1462] Data processing and output

[1463] A generative AI model (e.g., "OpenAI GPT-3") analyzes the question and generates an appropriate answer ("The first step in inheriting a house is to understand the current state of your assets."). At the same time, an emotion analyzer analyzes emotional information and provides information to adjust the answer.

[1464] Step 5:

[1465] A generative AI model generates answers, and a sentiment analyzer adjusts them.

[1466] Operation and Input

[1467] Let's say the generative AI model's answer is, "The first step when starting to inherit a house is to understand the current state of the assets."

[1468] Data processing and output

[1469] The emotion analyzer adjusts this response based on the user's emotions ("anxiety, tension") to "Let's start by relaxing and understanding the current state of your assets." The adjusted response is sent to the next step.

[1470] Step 6:

[1471] The server sends the adjusted answer to the device.

[1472] Operation and Input

[1473] The server receives the response adjusted by the emotion analyzer.

[1474] Data processing and output

[1475] The server converts the tailored response ("Let's start by relaxing and understanding the current state of your assets") into JSON format and sends it to the device using an HTTP POST request.

[1476] Step 7:

[1477] Display the answer received by the device

[1478] Operation and Input

[1479] The terminal parses the JSON data received from the server.

[1480] Data processing and output

[1481] The device displays the adjusted response to the user, specifically displaying a message on the screen saying, "First, relax and let's start by understanding the current state of your assets."

[1482] The above steps complete the series of processes for the system to analyze the user's input and provide an appropriate answer.

[1483] (Application example 2)

[1484] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1485] In recent years, the number of users gathering information and seeking advice on inheritance and end-of-life planning has been increasing. However, many of these situations involve emotional burdens, and conventional systems are often unable to adequately address these. Furthermore, current systems have difficulty providing answers that take users' emotions into consideration, which is one of the factors that reduces user satisfaction. The purpose of this invention is to provide a consultation system for inheritance and end-of-life planning that adapts to users' emotions, thereby reducing psychological burdens and providing more appropriate answers more quickly.

[1486] 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.

[1487] In this invention, the server includes: a means for a user to input a question into a terminal and provide emotion information; a means for the terminal to transmit the question and emotion information to the server; a means for the server to pass the question to a generative AI model and the emotion information to an emotion engine; a means for the server to adjust the generated answer using the emotion engine to adjust the wording to match the emotion; a means for the server to transmit the adjusted answer to the terminal; and a means for the terminal to display the adjusted answer received from the server to the user. This makes it possible to quickly provide an appropriate answer that matches the user's emotion and reduce psychological burden.

[1488] A "terminal" is a device operated by a user, which inputs questions and emotional information and communicates with a server.

[1489] A "question" is text information entered by the user regarding inheritance or end-of-life planning.

[1490] "Emotional information" is data about the user's emotions that the system analyzes and recognizes in real time when the user enters a question.

[1491] The "server" is a computer system that receives questions and emotion information entered by users and generates appropriate answers using a generative AI model and emotion engine.

[1492] A "generative AI model" is an artificial intelligence model installed on a server, and is a technology for generating appropriate answers to users' questions.

[1493] An "emotion engine" is a technology installed on a server or terminal that analyzes the user's emotional information and adjusts the generated answers based on that information.

[1494] "User interface" refers to a function that allows users to input questions and provide emotional information through a terminal.

[1495] "Natural language processing technology" is a technology that allows a server to understand text data and generate an appropriate response when generating answers using a generative AI model.

[1496] "Adjustment" is a process in which the generated answer is changed to wording that is appropriate to the user's emotions using an emotion engine.

[1497] An "answer" is a response to a user's question generated by a generative AI model and adjusted by an emotion engine.

[1498] The following components are required to implement this invention: A user inputs a question through a terminal, and the question and emotional information are sent to a server. The server passes the received question and emotional information to a generative AI model and an emotional engine, which generates an appropriate answer. The generated answer is further adjusted by the emotional engine to use wording appropriate to the user's emotions, and then sent to the terminal and displayed to the user.

[1499] Program Description

[1500] 1. Enter a question and provide emotional information

[1501] The user inputs a question using the device's user interface. The device is equipped with an Emotion Engine, which analyzes and collects emotional information from the question in real time. The emotional information includes emotional states such as anxiety, tension, and joy.

[1502] 2. Sending questions and emotional information

[1503] Once the user has finished entering their question, the device converts the question and the analyzed emotional information into a data format (e.g., JSON format) and sends it to the server. At this time, the device uses the "requests" communication library to send the data to the server as an HTTP POST request.

[1504] 3. Questioning and emotional information processing

[1505] The server analyzes the received question and emotional information, and passes the question content to the generative AI model, while also passing the emotional information to the emotion engine. The generative AI model, "AIGeneratedResponse," is an artificial intelligence model that understands the question content and generates an appropriate answer.

[1506] 4. Emotionally appropriate adjustment of responses

[1507] The generated answers are adjusted by the emotion engine to use language that is appropriate to the user's emotions. This process adds additional consideration to the generated answers based on the user's emotional state. For example, if a user is feeling anxious, reassuring words such as "relax" will be added.

[1508] 5. Submitting and Viewing Tailored Answers

[1509] The answer, adjusted to suit the user's emotions, is then sent back to the device from the server. The device receives the answer and displays it on the user interface, allowing the user to receive an appropriate answer that takes their emotions into consideration.

[1510] Specific examples

[1511] For example, if a user types a question like "I'm worried about inheriting a house," the following steps will occur:

[1512] 1. The user types, "I'm worried about inheriting my house," and the system recognizes the emotion "anxiety."

[1513] 2. The question and emotion information are sent to the server.

[1514] 3. The server passes the question content to the generation AI model and the emotion information to the emotion engine.

[1515] 4. The generative AI model generates the answer, "Let's start by looking at basic information about your home's assets."

[1516] 5. The emotion engine refines this response to, "Relax, let's start by finding out some basic information about your home's assets."

[1517] 6. The adjusted answer is displayed to the user.

[1518] Prompt Sentence Examples

[1519] User Question: I'm worried about inheriting my house.

[1520] Recognized emotion: Anxiety

[1521] Prompt for generative AI model: Generate appropriate answers to user questions. Emotions considered: Anxiety

[1522] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1523] Step 1:

[1524] The user inputs a question using the device's user interface, and the device retrieves the question. At this time, EmotionEngine runs in the background and analyzes emotional information from the input question in real time. The input is the user's question (e.g., "I'm worried about inheriting my house"), and the output is the question and emotional information (e.g., "anxiety").

[1525] Step 2:

[1526] The device converts the question and emotion information into a data format (for example, JSON format) and sends it to the server. At this time, the communication library "requests" is used to send the data as an HTTP POST request. The input is the question and emotion information, which is converted into JSON format and output as a data packet to be sent.

[1527] Step 3:

[1528] The server analyzes the received question and emotional information, and passes the question content to the generative AI model "AIGeneratedResponse" and the emotional information to the emotion engine. The input is a JSON data packet, which is separated into the question content and emotional information as the analysis result. The output is input data to the generative AI model and the emotion engine.

[1529] Step 4:

[1530] The generative AI model understands the question and generates an appropriate answer. This process uses natural language processing techniques to process the question and generate the best answer. The input is the question, and the output is the generated answer (e.g., "Let's start by looking at basic information about your home's assets.").

[1531] Step 5:

[1532] The emotion engine adjusts the generated answer based on the user's emotional information. For example, if a user feels "anxious," the reassuring phrase "relax" is added. The input is the generated answer and emotional information, and the output is an answer that has been adjusted to suit the emotion (e.g., "Relax, let's start by looking up basic information about your home's assets.").

[1533] Step 6:

[1534] The server converts the adjusted response back into the appropriate data format and sends it to the device, again using the "requests" communication library. The input is the adjusted response, and the output is a data packet sent to the device.

[1535] Step 7:

[1536] The terminal displays the tailored response received from the server on the user interface, allowing the user to obtain an appropriate response that takes their emotions into consideration. The input is the data packet received from the server, and the output is the displayed text message.

[1537] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1538] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1539] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1540] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1541] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1542] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1543] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1544] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1545] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1546] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1547] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1548] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1549] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1550] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1551] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1552] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1553] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1554] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1555] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1556] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1557] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1558] The following is further disclosed regarding the above embodiment.

[1559] (Claim 1)

[1560] [Means for the user to input a question into the terminal;

[1561] [Means for the terminal to send a query to the server;

[1562] [Means for the server to pass questions to a generative AI model to generate answers;

[1563] [means for the server to transmit the generated response to the terminal;

[1564] [Means for displaying the answer received by the terminal from the server to the user;

[1565] A system including:

[1566] (Claim 2)

[1567] The system of claim 1, further comprising means for allowing the terminal to input a question using a user interface when the terminal transmits the question to the server.

[1568] (Claim 3)

[1569] [The system of claim 1, further comprising means for the server to use natural language processing techniques when generating answers using a generative AI model.

[1570] "Example 1"

[1571] (Claim 1)

[1572] [Means for a user to input a question into an information processing device;

[1573] [Means for an information processing device to send a query to an information processing system;

[1574] [Means for an information processing system to pass a question to a generative AI model to generate an answer;

[1575] [Means for transmitting the generated answers to the information processing device by the information processing system;

[1576] [Means for displaying the answer received by the information processing device from the information processing system to the user;

[1577] A system including:

[1578] (Claim 2)

[1579] The system according to claim 1, further comprising means for allowing a user to input a question using a user interface when the information processing device transmits the question to the information processing system.

[1580] (Claim 3)

[1581] [The system of claim 1, wherein the information processing system includes means for using natural language processing techniques when generating answers using a generative AI model.

[1582] "Application Example 1"

[1583] (Claim 1)

[1584] [Means for the user to input a question into the terminal;

[1585] [Means for the terminal to send a query to the server;

[1586] [Means for the server to pass questions to a generative AI model to generate answers;

[1587] [means for the server to transmit the generated response to the terminal;

[1588] [Means for displaying the answer received by the terminal from the server to the user;

[1589] [Means for users to input information on a terminal installed in a physical store or on a user's mobile terminal;

[1590] [Means for communicating with the server using an Internet connection;

[1591] A system including:

[1592] (Claim 2)

[1593] The system of claim 1, further comprising means for allowing the terminal to input a question using a user interface when the terminal transmits the question to the server.

[1594] (Claim 3)

[1595] [The system of claim 1, further comprising means for the server to use natural language processing techniques when generating answers using a generative AI model.

[1596] "Example 2: Combining Emotion Engines"

[1597] (Claim 1)

[1598] [Means for the user to input a question into the terminal;

[1599] [Means for the terminal to analyze the user's emotions and send questions and emotional information to the server;

[1600] [Means for the server to pass the question and emotion information to the generative AI model and emotion analyzer to generate and tailor an answer;

[1601] [means for the server to send the adjusted response to the terminal;

[1602] [Means for displaying the answer received by the terminal from the server to the user;

[1603] A system including:

[1604] (Claim 2)

[1605] [The system according to claim 1, wherein the terminal allows the user to input a question using a user interface when sending the question to the server.

[1606] (Claim 3)

[1607] [The system of claim 1, wherein the server uses natural language processing technology when generating answers using a generative AI model.

[1608] "Application example 2 when combining emotion engines"

[1609] (Claim 1)

[1610] [Means for users to input questions into the terminal and provide emotion information;

[1611] [Means for the terminal to transmit questions and emotion information to the server;

[1612] [Means for the server to pass the question to the generative AI model and pass the emotion information to the emotion engine;

[1613] [means for the server to adjust the generated answer using an emotion engine to adjust the wording to suit the emotion;

[1614] [means for the server to send the adjusted response to the terminal;

[1615] [means for displaying to the user the adjusted answer received by the terminal from the server;

[1616] A system including:

[1617] (Claim 2)

[1618] The system of claim 1 further comprising means for allowing a user to input a question using a user interface and analyzing the user's emotions in real time when the terminal transmits the question and emotion information to the server.

[1619] (Claim 3)

[1620] [The system of claim 1, further comprising means for using natural language processing and sentiment analysis techniques when the server generates answers using a generative AI model and adjusts the generated answers using a sentiment engine.] [Explanation of symbols]

[1621] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for a user to input a question into the terminal; means for the terminal to send a query to the server; A means for the server to pass questions to a generative AI model to generate answers; means for the server to transmit the generated response to the terminal; a means for displaying to the user the response received by the terminal from the server; A system including:

2. 2. The system according to claim 1, further comprising means for allowing the terminal to input a question using a user interface when the terminal transmits the question to the server.

3. The system of claim 1 , further comprising means for using natural language processing techniques when generating answers using the generative AI model.

Images