system

Abstract

To provide a system that controls the Persona chatbot.SOLUTION: A system includes means for receiving a question from a user through a messenger application, means for analyzing the question and converting it into a prompt sentence suitable for a generative AI model that generates questions and answers about a specific product or theme, means for receiving an answer generated by the generative AI model on the basis of the prompt sentence, means for converting the answer into a predetermined format, and means for providing the answer whose format has been converted to the user through the messenger application.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] During business negotiations and meetings, people may want to ask questions but feel hesitant to do so, and in sales activities, they may be unable to respond quickly to customer questions, resulting in missed business opportunities. [Means for solving the problem]

[0005] By using a generative AI that generates detailed Q&As about specific products or themes and a messenger app that sends and receives the Q&As generated by the generative AI, the company provides a system that provides answers to user questions in real time. This system can be used in a variety of situations, such as business negotiations, meetings, education, and events. [Brief explanation of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0014] [First embodiment]

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

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0027] "Example 1"

[0028] One embodiment of the present invention is a system that uses a generative AI that generates detailed Q&As about specific products or themes, and a messenger app that sends and receives the Q&As generated by the generative AI. The generative AI generates answers to questions from users in real time. The messenger app sends the Q&As generated by the generative AI to users and sends questions from users to the generative AI.

[0029] "Example 2"

[0030] As a specific example, consider a sales negotiation scenario. Salespeople can receive answers to customer questions in real time through generative AI. This allows salespeople to respond to customer questions quickly, avoid missing sales opportunities, and improve customer satisfaction.

[0031] "Example 3"

[0032] The present invention is also useful in educational settings. Teachers can use generative AI to obtain detailed answers to questions from students, helping them improve their students' understanding. Furthermore, using the system of the present invention in Q&A sessions at events can also improve participant satisfaction.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: User types in a question through the messenger app.

[0036] Step 2: The messenger app sends the user's question to the generative AI.

[0037] Step 3: The generative AI generates answers to the user's questions in real time. Step 4: The messenger app sends the answers generated by the generative AI to the user.

[0038] "Example 2"

[0039] Step 1: A salesperson types a customer's question into a messenger app.

[0040] Step 2: The messenger app sends the salesperson's question to the generative AI.

[0041] Step 3: The generative AI generates answers to questions from sales representatives in real time.

[0042] Step 4: The messenger app sends the answer generated by the generative AI to the salesperson, who then responds to the customer based on the answer.

[0043] "Example 3"

[0044] Step 1: The teacher types the student's question into the messenger app.

[0045] Step 2: The messenger app sends the teacher's question to the generative AI.

[0046] Step 3: The generative AI generates answers to questions from the teacher in real time.

[0047] Step 4: The answer generated by the generative AI is sent to the teacher via a messaging app, who then responds to the student based on the answer.

[0048] Example 1

[0049] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0050] Previous Q&A systems often had delays in responding to user questions, making it difficult to respond in real time. Providing detailed information on specific products or topics also required building and maintaining a massive database, which was costly. Furthermore, the interface for users to enter questions could be difficult to use, resulting in a poor user experience.

[0051] 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.

[0052] In this invention, the server includes a generation AI means for generating detailed Q&As about specific products or themes, a messenger application means for transmitting and receiving the Q&As generated by the generation AI means, a means for sending questions from users to the generation AI means through the messenger application means, and a means for sending answers generated by the generation AI means to users, thereby enabling users to receive detailed Q&As in real time.

[0053] A "generative AI tool" is a system that uses artificial intelligence technology to generate detailed Q&A about a specific product or topic.

[0054] The "messenger app means" is a communication application for sending questions from users and receiving answers from the generative AI means.

[0055] The "means for sending questions from users to generative AI means" is a function for sending questions entered by users through messenger app means to generative AI means.

[0056] "Means for sending an answer generated by a generative AI means to a user" is a function for sending an answer generated by a generative AI means to a user through a messenger app means.

[0057] A "prompt" is text containing a question from a user that is input to a generative AI means.

[0058] This invention is a system for generating detailed Q&A about a specific product or theme. The system includes a generative AI means, a messenger application means, a means for sending a question from a user to the generative AI means, and a means for sending an answer generated by the generative AI means to the user.

[0059] The server uses server hardware equipped with a high-performance GPU (e.g., a high-performance graphics processor) to run the generative AI means. Furthermore, the generative AI model employs an advanced generative AI model (e.g., a large-scale language model) that uses natural language processing technology. The generative AI means receives questions from users and generates appropriate answers to those questions in real time.

[0060] The device is a smartphone or PC with a messenger app installed that the user uses. This messenger app (e.g., a general communication application) sends questions from the user to the generative AI means and displays the answers from the generative AI means to the user.

[0061] Specifically, the data processing involves sending a question from the user to the server via a messenger app, where the generative AI analyzes the question and generates an appropriate answer, which is then sent back to the user via the messenger app.

[0062] For example, if a user asks, "What is the battery life like on my new smartphone?" the following happens:

[0063] 1. The user types a question using a messenger app.

[0064] 2. The messenger app sends the question to the server.

[0065] 3. The server uses generative AI methods to analyze the question and generate an appropriate answer.

[0066] 4. The generated answer (e.g., "The battery life of a new smartphone is typically around 24 hours. However, this may vary depending on usage.") is sent from the server to the messenger app.

[0067] 5. The Messenger app will display the generated answer to the user.

[0068] Example prompt sentence:

[0069] "What's the battery life like on my new smartphone?"

[0070] In this way, users can receive detailed Q&A in real time.

[0071] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0072] Step 1:

[0073] The user types a question through a messenger app.

[0074] Specifically, a user opens a messaging app installed on their smartphone or PC and types a question, for example, "What is the battery life of my new smartphone?"

[0075] Input: User question text

[0076] Output: Question text entered into the messenger app

[0077] Step 2:

[0078] The terminal sends a question to the server.

[0079] Specifically, the device sends the user's question to the server via the messenger app's API. The question is sent to the server in an appropriate format (e.g., JSON format).

[0080] Input: Question text entered into the messenger app

[0081] Output: Question text sent to the server

[0082] Step 3:

[0083] The server receives the question and inputs it as a prompt into the generative AI model.

[0084] Specifically, the server analyzes the received question and inputs it into the generative AI model as a prompt sentence, which is the user's question as is.

[0085] Input: Question text sent to the server

[0086] Output: The prompt sentence that is input to the generative AI model

[0087] Step 4:

[0088] A generative AI model generates answers to questions.

[0089] Specifically, the generative AI model generates an appropriate answer to the question based on the prompt sentence, for example, "The battery life of a new smartphone is usually about 24 hours. However, this may vary depending on usage."

[0090] Input: A prompt sentence entered into the generative AI model

[0091] Output: Answer text generated by the generative AI model

[0092] Step 5:

[0093] The server receives the generated response and sends it to the terminal.

[0094] Specifically, the server converts the answer received from the generative AI model back into an appropriate format (e.g., JSON format) and sends it to the terminal.

[0095] Input: Answer text generated by the generative AI model

[0096] Output: Answer text sent to the terminal

[0097] Step 6:

[0098] The terminal displays the answer to the user.

[0099] Specifically, the device receives the response from the server and displays it to the user via the messenger app. The user can then check the response on the chat screen of the messenger app.

[0100] Input: Answer text sent to the terminal

[0101] Output: Reply text displayed in the messenger app

[0102] (Application example 1)

[0103] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0104] On traditional online shopping sites, users would have to visit FAQ pages or contact customer support to get detailed information about products, which made it difficult to get a quick response. Furthermore, if users were unable to resolve their questions about a product, their desire to purchase would decrease, which could result in a decrease in sales. Furthermore, the burden on customer support would increase, making it difficult to operate efficiently.

[0105] 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.

[0106] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the Q&As generated by the generative AI means, a means for providing answers to questions from users through the messenger app means, an application means installed on a smartphone, and a means for users to input product-related questions through the application means, the generative AI means for generating answers to those questions in real time, and the means for providing the answers to users through the messenger app means. This allows users to quickly obtain detailed product information, increasing their desire to purchase. It also reduces the burden on customer support and enables more efficient operations.

[0107] "Generative AI methods" refers to artificial intelligence techniques for generating detailed Q&A about specific products or topics.

[0108] "Messenger App Means" refers to an application for sending and receiving Q&As generated by Generative AI Means.

[0109] "Means for providing answers to questions from users" refers to a function for providing users with answers generated by generative AI means in response to questions entered by users.

[0110] "Application means installed on a smartphone" refers to an application that runs on a smartphone and allows a user to input questions about a product.

[0111] "Means for inputting a question about a product, for the generative AI means to generate an answer to the question in real time, and for providing the answer to the user through the messenger app means" refers to a series of functions for a user to input a question about a product, for the generative AI means to generate an answer to the question in real time, and for providing the answer to the user through the messenger app means.

[0112] The following system configuration is used as an embodiment of the present invention.

[0113] The server includes a generative AI means for generating detailed Q&A about a specific product or topic. The generative AI means uses a generative AI model, such as OpenAI's GPT-3™, to generate answers in real time to user questions.

[0114] The terminal includes an application means installed on the smartphone. The application means provides an interface for the user to input a question about the product. When the user inputs a question, the question is transmitted to the server via a messenger application means.

[0115] The messenger app means is an application for sending and receiving Q&As generated by the generative AI means. For example, it is implemented as a web application using Flask. This messenger app means plays a role in sending questions from users to the generative AI means and returning generated answers to users.

[0116] Specifically, the process involves a user entering a question through a smartphone app, which is then sent to the server through a messenger app. The server's AI generator generates an answer to the question in real time and returns the answer to the user through the messenger app.

[0117] For example, if a user asks, "What is the battery life of this smartphone?", the generative AI means generates the answer, "This smartphone's battery life is approximately 10 hours under normal use." This answer is provided to the user via a messenger app means.

[0118] An example prompt sentence would be of the following format:

[0119] Q: What is the battery life of this phone?

[0120] A: This smartphone's battery life is approximately 10 hours under normal use.

[0121] In this way, users can quickly obtain detailed information about products, which increases their willingness to purchase. It also reduces the burden on customer support and enables more efficient operations.

[0122] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0123] Step 1:

[0124] A user starts the smartphone app and inputs a question about a product. The input question is transmitted to the messenger app means via the application means. The input data is the user's question, and the output data is the question transmitted to the messenger app means.

[0125] Step 2:

[0126] The messenger application means transmits a question received from a user to a server. The input data is the user's question, and the output data is the question to be transmitted to the server. Specifically, the messenger application means transmits the question data to the server using an HTTP request.

[0127] Step 3:

[0128] The server passes the received question to the generative AI means. The input data is the question received from the messenger app means, and the output data is the question passed to the generative AI means. Specifically, the server inputs the question data into the generative AI model.

[0129] Step 4:

[0130] The generative AI means generates answers to received questions in real time. The input data is the user's question, and the output data is the generated answer. Specifically, it uses a generative AI model (e.g., GPT-3) to generate a prompt sentence and generate an answer.

[0131] Step 5:

[0132] The server transmits the answer received from the generative AI means to the messenger application means. The input data is the generated answer, and the output data is the answer to be transmitted to the messenger application means. Specifically, the server transmits the answer data to the messenger application means using an HTTP response.

[0133] Step 6:

[0134] The messenger application means transmits the response received from the server to the smartphone application. The input data is the response received from the server, and the output data is the response sent to the smartphone application. Specifically, the application performs processing to display the response data within the application.

[0135] Step 7:

[0136] The user checks the answer generated by the generative AI means through the smartphone app. The input data is the answer received from the messenger app means, and the output data is the answer checked by the user. Specifically, the answer is displayed on the smartphone screen and the user views it.

[0137] Example 2

[0138] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0139] In traditional business negotiations and meetings, it can be difficult for salespeople and other participants to quickly and accurately answer questions from customers and other participants. This can lead to missed business opportunities and reduced customer satisfaction. Another issue is the lack of a way to instantly obtain appropriate answers in situations where real-time information provision is required.

[0140] 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.

[0141] In this invention, the server includes a means for a user to input a question, a means for the terminal to transmit the input to the server, a means for the server to transmit a prompt sentence to the generative AI model, a means for the generative AI model to generate an answer, a means for the server to transmit the answer to the terminal, and a means for the terminal to display the answer to the user, thereby enabling the user to quickly and accurately obtain answers to questions from customers and other participants.

[0142] A "user" is an entity that uses the system to enter questions and receive answers.

[0143] A "terminal" is a device through which a user inputs questions and communicates with the server, and includes laptops, tablets, etc.

[0144] The "server" is a computer system that receives questions from users, sends prompts to the generative AI model, and sends the generated answers to the terminal.

[0145] A "generative AI model" is an artificial intelligence model that generates appropriate answers based on prompt sentences, and includes, for example, GPT-4 (registered trademark).

[0146] A "prompt sentence" is a textual sentence that is converted to help the generative AI model properly understand the question.

[0147] The "means for inputting a question" is an interface that allows a user to input a question using a terminal.

[0148] The "means for transmitting input to a server" is a communication means by which the terminal transmits a question input by a user to a server.

[0149] The "means for sending a prompt sentence" is the means by which the server converts the user's question into a prompt sentence and sends it to the generative AI model.

[0150] The "means for generating an answer" refers to the means by which the generative AI model generates an answer based on the prompt sentence.

[0151] "Means for sending an answer to a terminal" refers to the means by which the server sends the answer obtained from the generative AI model to the terminal.

[0152] The "means for displaying the answer to the user" is an interface for displaying the answer received by the terminal from the server to the user.

[0153] This invention is a system that allows users to quickly and accurately obtain answers to questions from customers and other participants in business negotiations and meetings. The system allows users to input questions, generates answers in real time using a generative AI model, and provides the answers to users.

[0154] Hardware and software used

[0155] 1. Terminal

[0156] Use devices such as laptops and tablets.

[0157] Using a dedicated application or web browser, users enter questions and communicate with the server.

[0158] 2. Server

[0159] It uses a high-performance computer system to receive questions from users, send prompts to a generative AI model, and send the generated answers to the device.

[0160] Python, Node.js, etc. are used as server-side scripts.

[0161] 3. Generative AI Models

[0162] For example, GPT-4 is used as a generative AI model.

[0163] Generate appropriate answers based on the prompt.

[0164] Data processing and calculation

[0165] 1. The user enters a question

[0166] Users enter questions using the keyboard or touchscreen of their laptop or tablet.

[0167] Example: A salesperson types, "How long is the warranty on this product?"

[0168] 2. The device sends the input to the server

[0169] The terminal sends the entered question to the server as an HTTP request.

[0170] Software required: Dedicated application and web browser

[0171] 3. The server sends a prompt to the generative AI model

[0172] The server converts the received question into a prompt sentence suitable for the generative AI model and sends it to the generative AI model.

[0173] Example: A server-side script converts a prompt into a statement of the form "Generate an answer to the customer question: 'What is the warranty period for this product?'"

[0174] 4. Generative AI models generate answers

[0175] The generative AI model generates appropriate answers based on the prompt text.

[0176] Example: Generate the answer "This product has a one-year warranty."

[0177] 5. The server sends the answer to the device

[0178] The server sends the answer obtained from the generative AI model to the terminal as an HTTP response.

[0179] 6. The device displays the answer to the user

[0180] The terminal displays the answer received from the server on the screen and the user confirms it.

[0181] Software required: Dedicated application and web browser

[0182] Examples of specific examples and prompts

[0183] Specific examples

[0184] A salesperson is asked by a customer, "How long is the warranty on this product?"

[0185] The salesperson types into the terminal, "How long is the warranty on this product?"

[0186] The device sends the question to the server, which then sends the prompt to the generative AI model.

[0187] The generative AI model generates the answer, "This product has a one-year warranty."

[0188] The server sends the answer to the terminal, which displays it to the salesperson.

[0189] Prompt Sentence Examples

[0190] "Generate an answer to the customer question: 'How long is the warranty on this product?'"

[0191] The system allows users to get quick and accurate answers to questions from customers and other participants, increasing the success of business negotiations and meetings.

[0192] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0193] Step 1:

[0194] The user enters a question.

[0195] A user inputs a question using the keyboard or touch screen of a laptop or tablet. For example, a salesperson might input, "How long is the warranty period for this product?" The input data is a text question.

[0196] Step 2:

[0197] The device sends input to the server.

[0198] The device sends the question entered by the user to the server as an HTTP request. Specifically, a dedicated application or web browser sends the entered question to the server. The input data is the text question entered by the user, and the output data is the HTTP request sent to the server.

[0199] Step 3:

[0200] The server sends a prompt to the generative AI model.

[0201] The server converts the received question into a prompt suitable for the generative AI model and sends it to the generative AI model. Specifically, a server-side script (e.g., Python, Node.js) converts the question into a prompt in the format "Please generate an answer to customer question: 'How long is the warranty period for this product?'" and sends an API request to the generative AI model. The input data is the HTTP request sent to the server, and the output data is the prompt sent to the generative AI model.

[0202] Step 4:

[0203] A generative AI model generates the answer.

[0204] The generative AI model generates an appropriate answer based on the prompt. Specifically, the generative AI model (e.g., GPT-4) analyzes the received prompt and generates the answer, "This product has a one-year warranty." The input data is the prompt sent to the generative AI model, and the output data is the generated answer.

[0205] Step 5:

[0206] The server sends the response to the terminal.

[0207] The server sends the answer obtained from the generative AI model to the terminal as an HTTP response. Specifically, the server-side script sends the generated answer to the terminal as an HTTP response. The input data is the answer obtained from the generative AI model, and the output data is the HTTP response sent to the terminal.

[0208] Step 6:

[0209] The terminal displays the answer to the user.

[0210] The terminal displays the response received from the server to the user. Specifically, a dedicated application or web browser displays the received response on the screen, which the sales representative can then confirm. The input data is the HTTP response received from the server, and the output data is the text-formatted response that is displayed to the user.

[0211] (Application example 2)

[0212] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0213] In traditional sales negotiations and customer service in brick-and-mortar stores, it can be difficult for salespeople or store clerks to quickly and accurately answer customer questions. This can lead to lower customer satisfaction and missed business opportunities. Another issue is that the time it takes to search for information and respond to questions can hinder efficient business operations.

[0214] 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.

[0215] In this invention, the server includes a generative AI means, a messenger application means for transmitting and receiving Q&As generated by the generative AI means, a means for providing answers to questions from users through the messenger application means, and a means for receiving voice input from users using smart glasses, generating answers through the generative AI means, and displaying the answers on a display of the smart glasses. This enables salespeople and store clerks to quickly and accurately answer questions from customers, thereby improving customer satisfaction and work efficiency.

[0216] "Generative AI methods" are methods that use artificial intelligence technology to generate appropriate answers to questions from users.

[0217] "Messenger app means" refers to an application means for sending and receiving Q&A generated by generative AI means.

[0218] "Means for providing answers to questions from users" refers to means for providing answers to questions from users through messenger app means.

[0219] "Smart glasses" are wearable devices worn by users that have voice input and display functions.

[0220] The "means for obtaining voice input" refers to a means for obtaining voice input from a user using the smart glasses.

[0221] "Means for displaying on a display" refers to means for displaying the answer generated through the generative AI means on the display of the smart glasses.

[0222] A system for implementing this invention includes generative AI means, messenger application means, means for providing answers to questions from users, means for acquiring voice input using smart glasses, and display means.

[0223] 1. System Program

[0224] The system program is configured as follows:

[0225] Generative AI method: Uses OpenAI's API to generate appropriate answers to user questions.

[0226] Messenger app means: an application for sending and receiving questions and answers, which works in conjunction with smart glasses.

[0227] Voice input acquisition means: The microphone in the smart glasses is used to acquire voice input from the user.

[0228] Display means: Display the generated answer on the display of the smart glasses.

[0229] 2. Program processing explanation

[0230] The server uses OpenAI's API as the generative AI means. When a user wears the smart glasses and makes a voice input, the microphone in the smart glasses picks up the voice. The picked up voice data is sent to the server via the messenger app means. The server uses the generative AI means to convert the voice data into text and generate an appropriate answer. The generated answer is then sent again to the smart glasses via the messenger app means and displayed on the display.

[0231] 3. Specific Examples

[0232] For example, if a customer asks "Do you have this item in stock?" in a physical store, the microphone in the smart glasses will pick up the voice. The voice data will be sent to the server, and the generative AI means will generate a response such as "Yes, this item is in stock." This response will be displayed on the smart glasses' display, allowing the store clerk to quickly respond to the customer.

[0233] Prompt Sentence Examples

[0234] Customer Question: Is this item in stock?

[0235] A: Yes, this item is in stock.

[0236] In this way, salespeople and store clerks can quickly and accurately answer customer questions through the smart glasses, improving customer satisfaction.

[0237] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0238] Step 1:

[0239] The user wears the smart glasses and performs voice input.

[0240] Input: User's voice question

[0241] Output: Audio data

[0242] Specific operation: The user speaks a question into the microphone of the smart glasses, which then picks up the voice data.

[0243] Step 2:

[0244] The terminal transmits the voice data to the server via the messenger application means.

[0245] Input: Audio data

[0246] Output: Audio data sent to the server

[0247] Specific operation: The smart glasses transmit the acquired voice data to the server through the messenger app.

[0248] Step 3:

[0249] The server converts the audio data into text.

[0250] Input: Audio data

[0251] Output: Text data

[0252] Specific operation: The server uses voice recognition technology to convert the voice data into text data.

[0253] Step 4:

[0254] The server uses generative AI tools to generate answers based on the text data.

[0255] Input: Text data

[0256] Output: Answer text

[0257] What happens: The server uses generative AI tools (e.g., OpenAI API) to generate appropriate answers based on the text data.

[0258] Step 5:

[0259] The server transmits the generated answer text to the terminal via the messenger application means.

[0260] Input: Answer text

[0261] Output: Answer text sent to the terminal

[0262] Specific operation: The server sends the generated answer text to the smart glasses through a messenger app.

[0263] Step 6:

[0264] The terminal displays the answer text on the display of the smart glasses.

[0265] Input: Answer text

[0266] Output: Answer displayed on the smart glasses display

[0267] Specific operation: The smart glasses display the received answer text on the display and the user confirms it.

[0268] In this way, users can quickly and accurately answer customer questions through the smart glasses.

[0269] Example 3

[0270] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0271] In traditional education and events, it has been difficult to get quick and accurate answers to questions. In particular, questions that require specialized knowledge often require a lot of time and effort to provide answers. Furthermore, in situations where real-time answers are required, it is difficult to provide appropriate answers immediately. This can lead to a decline in the quality of education and the satisfaction of event participants.

[0272] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0273] In this invention, the server includes means for generating answers to questions from users using a generative AI model, communication means for transmitting and receiving the answers generated by the generative AI model, and means for receiving questions from users via the communication means and displaying the generated answers, thereby enabling users to obtain quick and accurate answers in real time.

[0274] A "generative AI model" is an artificial intelligence model used to generate answers to user questions.

[0275] "Communication means" refers to the means for sending and receiving answers generated by the generative AI model.

[0276] The "display means" is a means for displaying to the user the answer received through the communication means.

[0277] A "user" is a person or entity that utilizes the system to enter questions and receive answers.

[0278] A "question" is information or a question that a user inputs into the system.

[0279] An "answer" is the information or answer that a generative AI model generates in response to a question.

[0280] "Real-time" refers to the extremely short time between when a user enters a question and when they receive a response.

[0281] "Education" is the activity or process of imparting knowledge or skills.

[0282] An "event" is a gathering or event held for a specific purpose or theme.

[0283] A "meeting" is a place where multiple people gather to discuss and make decisions.

[0284] A "business meeting" is a place where business negotiations and transactions are conducted.

[0285] This invention is a system that uses a generative AI model to generate answers to user questions and provide them quickly and accurately. This system can be used in a variety of situations, such as education, events, meetings, and business negotiations.

[0286] Hardware and software used

[0287] Hardware

[0288] Server: A server with high-performance computing power is required, including CPU, GPU, memory, and storage.

[0289] Device: The device through which a user enters a question and receives a response. This can include a tablet, PC, or smartphone.

[0290] software

[0291] Generative AI models: For example, using advanced natural language processing models such as OpenAI's GPT-4.

[0292] Communication method: Uses network protocols (such as HTTP / HTTPS) to send and receive data over an internet connection.

[0293] Display method: Use an application or web browser to display the answers on your device.

[0294] Data processing and calculation

[0295] Data Entry

[0296] Users use the device to type in a question, for example, a teacher uses the tablet keyboard to type, "What is the speed of light?"

[0297] Data transmission

[0298] The device sends the entered question to the server. An internet connection is required for sending. When the device presses the "Send" button, the question is sent to the server via the internet.

[0299] Data Processing

[0300] The server analyzes the received question and converts it into a format suitable for the generative AI model. This process includes text preprocessing and tokenization. The server breaks down the text "What is the speed of light?" into tokens and converts it into a format that can be input to the generative AI model.

[0301] Generate answers

[0302] The server uses a generative AI model to generate a detailed answer to the question. The server inputs the question "What is the speed of light?" into the generative AI model and gets the answer "The speed of light is approximately 299,792,458 meters per second."

[0303] Data transmission

[0304] The server then sends the generated answer to the device. This again requires an internet connection. The server then sends the answer "The speed of light is approximately 299,792,458 meters per second" to the device via the internet.

[0305] Data Display

[0306] The device displays the received answer to the user on the device's screen. The device displays the text "The speed of light is approximately 299,792,458 meters per second" on the screen, and the teacher confirms it.

[0307] Examples of specific examples and prompts

[0308] Specific examples

[0309] A teacher is asked by a student during class, "What is the speed of light?"

[0310] The teacher uses a tablet to type in a question and presses the send button.

[0311] The terminal sends a query to the server.

[0312] The server analyzes the question and inputs it into a generative AI model.

[0313] The generative AI model generates the answer, "The speed of light is approximately 299,792,458 meters per second."

[0314] The server sends the generated response to the terminal.

[0315] The device displays the answers on the screen, and the teacher checks them and passes them on to the students.

[0316] Prompt Sentence Examples

[0317] "What is the speed of light?"

[0318] "What caused World War II?"

[0319] "What is the chemical formula for oxygen?"

[0320] This system enables users to obtain prompt and accurate answers in real time, thereby improving the quality of education and events. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0321] Step 1:

[0322] A user uses a terminal to input a question. The input question is in text format, such as "What is the speed of light?" The terminal receives the question and prepares it for transmission.

[0323] Input: A question typed into the device by the user (e.g., "What is the speed of light?")

[0324] Output: Question data ready to be sent

[0325] Step 2:

[0326] The device sends the entered question to the server. An internet connection is required for transmission, and the HTTP / HTTPS protocol is used. When the device presses the "Send" button, the question is sent to the server via the internet.

[0327] Input: Question data ready to be sent

[0328] Output: Question data sent to the server

[0329] Step 3:

[0330] The server analyzes the received question and converts it into a format suitable for the generative AI model. This process includes text preprocessing and tokenization. The server breaks down the text "What is the speed of light?" into tokens and converts it into a format that can be input to the generative AI model.

[0331] Input: Question data sent to the server

[0332] Output: Data converted into a format that can be fed into a generative AI model

[0333] Step 4:

[0334] The server uses a generative AI model to generate a detailed answer to the question. The server inputs the question "What is the speed of light?" into the generative AI model and gets the answer "The speed of light is approximately 299,792,458 meters per second."

[0335] Input: Data converted into a format that can be fed into a generative AI model

[0336] Output: Answer data obtained from the generative AI model

[0337] Step 5:

[0338] The server then sends the generated answer to the device. This again requires an internet connection and uses the HTTP / HTTPS protocol. The server then sends the answer "The speed of light is approximately 299,792,458 meters per second" to the device via the internet.

[0339] Input: Answer data obtained from a generative AI model

[0340] Output: Answer data sent to the device

[0341] Step 6:

[0342] The device displays the received answer to the user on the device's screen. The device displays the text "The speed of light is approximately 299,792,458 meters per second" on the screen, and the user confirms it.

[0343] Input: Answer data sent to the terminal

[0344] Output: Answer data displayed on the screen

[0345] In this way, users can get fast and accurate answers in real time.

[0346] (Application example 3)

[0347] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0348] In traditional Q&A sessions at educational settings and events, it has been difficult for teachers and moderators to provide quick and detailed answers to questions from participants. Furthermore, when real-time answers are required, limitations on human resources have become an issue. This has led to a decline in participant satisfaction and understanding.

[0349] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0350] In this invention, the server includes generative AI means, communication application means, means for providing answers to questions from users, means for teachers to obtain detailed answers to questions from students in educational settings, and means for generating answers in real time to questions from participants in Q&A sessions at events. This makes it possible to provide quick and detailed answers in educational settings and events, thereby improving participant satisfaction and understanding.

[0351] "Generative AI methods" refers to artificial intelligence technology that automatically generates answers to questions posed by users.

[0352] "Communication application means" refers to software for sending and receiving Q&As generated by generative AI means.

[0353] "Means for providing answers to questions from users" refers to a function for providing answers to questions from users through a communication application means.

[0354] "A means for teachers to obtain detailed answers to questions from students in educational settings" refers to a function that allows teachers to input questions from students and obtain detailed answers using generative AI means.

[0355] "A means for generating answers in real time to questions from participants in Q&A sessions at events" refers to a function that receives questions from participants in real time at an event and instantly generates answers using generative AI means.

[0356] In order to practice this invention, it is necessary to build a system that includes generative AI means, communication application means, means for providing answers to questions from users, means for teachers to obtain detailed answers to questions from students in educational settings, and means for generating answers in real time to questions from participants in Q&A sessions at events.

[0357] System configuration

[0358] 1. Generative AI means

[0359] The server uses generative AI models such as OpenAI's GPT-3 as a generative AI method, which allows it to automatically generate detailed answers to user questions.

[0360] 2. Communication Application Means

[0361] The server uses a smartphone application as a communication application means, which provides an interface for sending and receiving the Q&A generated by the generative AI means.

[0362] 3. Means of providing answers to user questions

[0363] The server receives a question from a user through the communication application means, generates an answer using the generative AI means, and provides the answer to the user again through the communication application means.

[0364] 4. A way for teachers to get detailed answers to student questions in educational settings

[0365] Teachers can use a smartphone application to input questions from students and get detailed answers using generative AI methods, thereby improving the quality of education.

[0366] 5. A way to generate real-time answers to attendee questions during event Q&A sessions

[0367] Event hosts and organizers can use a smartphone application to receive questions from attendees in real time and use generative AI tools to instantly generate answers and provide them to attendees.

[0368] Program processing explanation

[0369] The server uses the OpenAI API to access a generative AI model (GPT-3). It works as follows:

[0370] 1. The server imports the openai library and sets the API key.

[0371] 2. The server receives the question from the user and generates an answer using generative AI means.

[0372] 3. The server provides the generated answer to the user through a communication application means.

[0373] Specific examples

[0374] For example, if a teacher receives a question from a student such as "Please explain the process of photosynthesis," the following prompt sentence can be input into the generative AI model:

[0375] Prompt Sentence Examples

[0376] Explain the process of photosynthesis

[0377] The generative AI model generates detailed answers such as, "Photosynthesis is the process by which plants use light energy to produce glucose and oxygen from carbon dioxide and water. Chlorophyll, primarily found in leaves, absorbs light and converts it into chemical energy." These answers are provided to teachers via communication applications.

[0378] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0379] Step 1:

[0380] The user inputs a question using a device (smartphone application).

[0381] Input: User question (e.g., "Please explain the process of photosynthesis.")

[0382] Output: User question data

[0383] Specific operation: The user enters a question into the application's input field and presses the submit button.

[0384] Step 2:

[0385] The terminal transmits the user's question data to the server.

[0386] Input: User question data

[0387] Output: The query data sent to the server

[0388] Specific operation: The terminal sends the query data to the server via the Internet.

[0389] Step 3:

[0390] The server receives the question data and passes it to the generative AI means.

[0391] Input: Query data sent to the server

[0392] Output: Question data passed to the generative AI method

[0393] Specific operation: The server analyzes the received question data and passes it to the generative AI means (OpenAI's API).

[0394] Step 4:

[0395] A generative AI tool generates answers based on the question data.

[0396] Input: Question data passed to the generative AI method

[0397] Output: Generated response data

[0398] Specific operation: The generative AI method uses the question data as a prompt and generates an answer using an AI model (GPT-3).

[0399] Step 5:

[0400] The server receives the generated response data and transmits it to the terminal.

[0401] Input: Generated response data

[0402] Output: Response data sent to the device

[0403] Specific operation: The server sends the answer data received from the generative AI means to the terminal.

[0404] Step 6:

[0405] The terminal displays the answer data received from the server to the user.

[0406] Input: Answer data sent to the terminal

[0407] Output: Answer data displayed to the user

[0408] Specific operation: The terminal displays the received response data on the screen and provides it to the user.

[0409] Through the above processing steps, a user can input a question and obtain a detailed answer using generative AI means.

[0410] 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.

[0411] "Example 1"

[0412] One embodiment of the present invention is a system that incorporates an emotion engine that recognizes user emotions. This system includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the Q&As generated by the generative AI means, and a means for providing answers to questions from users via the messenger app means. Furthermore, an emotion engine that recognizes user emotions is incorporated. This emotion engine recognizes emotions from the user's facial expressions, tone of voice, message context, etc., and provides this information to the generative AI means. The generative AI means generates answers to user questions based on this emotion information. For example, if the user feels angry, the generative AI means will generate more polite answers.

[0413] "Example 2"

[0414] Another embodiment of the present invention is a system in which an emotion engine tracks changes in a user's emotions and a generative AI means adjusts responses in response to those changes. In this system, the emotion engine tracks changes in a user's emotions in real time and provides that information to the generative AI means. The generative AI means adjusts responses based on this information about changes in emotion. For example, if a user is initially happy but gradually begins to show signs of dissatisfaction, the generative AI means captures that change and adjusts the tone and content of the responses.

[0415] "Example 3"

[0416] One embodiment of the present invention is a system that incorporates an emotion engine that recognizes user emotions. This system includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the Q&As generated by the generative AI means, and a means for providing answers to questions from users via the messenger app means. Furthermore, an emotion engine that recognizes user emotions is incorporated. This emotion engine recognizes emotions from the user's facial expressions, tone of voice, message context, etc., and provides this information to the generative AI means. The generative AI means generates answers to user questions based on this emotion information. For example, if the user feels angry, the generative AI means will generate more polite answers.

[0417] The processing flow of each embodiment will be described below.

[0418] "Example 1"

[0419] Step 1: The user sends a question via a messenger app.

[0420] Step 2: The emotion engine recognizes emotions from the user's facial expressions, tone of voice, and message context.

[0421] Step 3: The emotion engine provides the recognized emotion information to the generative AI means.

[0422] Step 4: The generative AI method generates an answer to the user's question based on the emotional information.

[0423] Step 5: The generative AI method sends the generated answer to the user via a messenger app method.

[0424] "Example 2"

[0425] Step 1: The user sends a question via a messenger app.

[0426] Step 2: The emotion engine tracks changes in the user's emotions in real time. Step 3: The emotion engine provides the tracked emotion change information to the generative AI means.

[0427] Step 4: The generative AI tool adjusts the response based on the emotional change information.

[0428] Step 5: The generative AI method sends the adjusted response to the user via the messenger app method.

[0429] Example 1

[0430] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0431] Conventional Q&A systems generate answers without considering the user's feelings, which can lead to low user satisfaction. They also face the problem of being unable to respond to user questions quickly due to the difficulty of generating answers in real time. Furthermore, they sometimes fail to provide detailed information about specific products or topics, which can make it difficult to meet user needs.

[0432] 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.

[0433] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger application means for sending and receiving the Q&As generated by the generative AI means, an emotion engine means for recognizing the user's emotions, and a generative AI means for adjusting answers based on the emotion information provided by the emotion engine means. This makes it possible to provide detailed Q&As in real time that take the user's emotions into consideration.

[0434] "Generative AI methods" refers to artificial intelligence techniques for generating detailed Q&A about specific products or topics.

[0435] "Messenger app means" refers to application software for sending and receiving Q&As generated by generative AI means and providing answers to questions from users.

[0436] "Emotion engine means" refers to technology that recognizes the user's emotions and provides that information to generative AI means.

[0437] "Emotional information" refers to data regarding emotions recognized by the emotion engine means from the user's facial expression, tone of voice, message context, etc.

[0438] "Real-time" refers to generating and providing answers to user questions instantly.

[0439] "In-depth Q&A" refers to in-depth questions and answers about a specific product or topic.

[0440] The present invention is a system that combines a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the generated Q&As, and an emotion engine means for recognizing the user's emotions.

[0441] The server hosts a generative AI model that generates answers to user questions in real time. The generative AI model uses natural language processing techniques to receive user questions and generate appropriate answers.

[0442] The device (user's smartphone or PC) sends the user's question to the server through a messenger app, such as WhatsApp or Slack, and receives the generated answer.

[0443] The emotion engine recognizes emotions from the user's facial expressions, tone of voice, and message context. For example, it can use the emotion recognition API from Microsoft's Azure Cognitive Services. The emotion engine provides the recognized emotion information to the generative AI model.

[0444] The generative AI model generates answers to user questions based on the emotional information provided by the emotion engine. For example, if the emotion engine recognizes that the user is angry, the generative AI model will generate a more polite answer.

[0445] As a concrete example, consider a case where a user asks, "How do I return this product?" If the emotion engine recognizes anger in the user's message, the generative AI model will generate a polite response such as, "We're sorry. We'll explain the return process in detail."

[0446] Example prompt sentence:

[0447] User: How do I return this product?

[0448] Generative AI model: If the emotion engine recognizes that the user is angry, generate a polite response.

[0449] This system makes it possible to provide detailed Q&A in real time, taking into account the user's emotions.

[0450] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0451] Step 1:

[0452] A user types a question into a messenger app.

[0453] Input: Users enter text questions about a particular product or topic.

[0454] What happens: A user types "How do I return this product?" into a messenger app.

[0455] Step 2:

[0456] The terminal sends a question to the server.

[0457] Input: The question text entered by the user.

[0458] Output: The question data sent to the server.

[0459] Specific operation: The device sends the user's question to the server via the messenger app.

[0460] Step 3:

[0461] The server passes the question to the generative AI model.

[0462] Input: Question data sent from the terminal.

[0463] Output: Question data passed to the generative AI model.

[0464] Specific operation: The server passes the received question to the generative AI model.

[0465] Step 4:

[0466] A generative AI model generates the answer.

[0467] Input: The query data passed by the server.

[0468] Output: The initial answer text.

[0469] How it works: The generative AI model generates an initial response such as, "We will provide detailed instructions on how to return the item."

[0470] Step 5:

[0471] The emotion engine recognizes the user's emotions.

[0472] Input: User messages, facial expressions, tone of voice, etc.

[0473] Output: User's emotional information.

[0474] Specific behavior: The emotion engine recognizes anger from the user's message.

[0475] Step 6:

[0476] A generative AI model takes emotional information into account and adjusts the answer.

[0477] Input: Initial answer text, user sentiment information.

[0478] Output: The adjusted answer text.

[0479] Specific operation: The generative AI model uses emotional information to generate a polite response such as, "We're sorry. We'll explain in detail how to return the product."

[0480] Step 7:

[0481] The server sends the final answer to the device.

[0482] Input: The adjusted answer text.

[0483] Output: The final answer data sent to the device.

[0484] Specific operation: The server sends the final answer from the generative AI model to the device.

[0485] Step 8:

[0486] The terminal displays the answer to the user.

[0487] Input: The final answer data sent from the server.

[0488] Output: The answer text that is displayed to the user.

[0489] Specific behavior: The device will display the final response to the user through the messenger app.

[0490] (Application example 1)

[0491] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0492] Conventional customer support systems provide uniform answers without considering the user's emotions, which leads to a decline in user satisfaction. It is also difficult to respond in real time, so users need to provide prompt answers to their questions. Furthermore, because they are unable to respond appropriately to the user's emotions, there is an issue of a decline in the quality of support, especially for users with negative emotions such as anger or confusion.

[0493] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes: generative AI means for generating detailed Q&As about specific products or themes; messenger application means for sending and receiving the Q&As generated by the generative AI means; means for providing answers to questions from users via the messenger application means; emotion engine means for recognizing the user's emotions; means for the emotion engine means to recognize the user's emotions from the user's facial expressions, tone of voice, and message context and provide this information to the generative AI means; and means for the generative AI means to generate answers to questions from users based on the emotion information. This makes it possible to provide appropriate answers in real time that correspond to the user's emotions.

[0494] "Generative AI methods" refers to artificial intelligence techniques that generate detailed Q&A about specific products or topics.

[0495] "Messenger App Means" refers to a communication application for sending and receiving Q&As generated by Generative AI Means.

[0496] "Emotion engine means" refers to technology for recognizing emotions from a user's facial expressions, tone of voice, and message context.

[0497] "Means for providing answers to user questions" refers to technology for providing answers to user questions through messenger app means.

[0498] "Emotion information" refers to data relating to the user's emotions recognized by the emotion engine means.

[0499] "Generating in real time" refers to generating answers instantly to questions from users.

[0500] "Customer support" refers to assistance activities to address user questions or issues regarding products or services.

[0501] A system for implementing this invention includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the generated Q&As, and an emotion engine means for recognizing user emotions. Specific embodiments of this system are described below.

[0502] System Configuration

[0503] 1. Hardware:

[0504] Device: Smartphone or tablet

[0505] Sensors: Camera and microphone (to recognize your facial expressions and tone of voice)

[0506] 2. Software:

[0507] Generative AI models: We will use OpenAI GPT-4 as an example.

[0508] Emotion recognition engine: As an example, we will use the Microsoft Azure Emotion API.

[0509] Messenger app: For example, using the Twilio API.

[0510] Data processing and calculation

[0511] 1. Get user's question:

[0512] The user's question is obtained as text data through the device's messenger app.

[0513] 2. Emotion recognition:

[0514] The user's facial expressions and tone of voice are transmitted to the emotion recognition engine means via the device's camera and microphone.

[0515] The emotion recognition engine means analyzes the user's emotions and provides the results to the generative AI means.

[0516] 3. Answer generation:

[0517] A generative AI tool takes emotional information into account and generates answers to user questions in real time.

[0518] 4. Submit your response:

[0519] The generated answer is sent to the user via a messenger app.

[0520] Specific examples

[0521] Example 1: When the user is angry

[0522] If a user asks, "My product hasn't arrived yet, what's going on?" and the emotion recognition engine means recognizes that the user is angry, the generative AI means will generate an answer like the following:

[0523] Example answer:

[0524] "We apologize for the inconvenience. We are currently checking the delivery status. Please wait a moment."

[0525] Example 2: When a user is having trouble

[0526] If a user asks, "I don't know how to use this product, what should I do?" and the emotion recognition engine means recognizes that the user is having trouble, the generative AI means will generate an answer like the following.

[0527] Example answer:

[0528] "Don't worry, here's a link to a video on how to use it. Let me know if you have any other questions."

[0529] Prompt Sentence Examples

[0530] An example of a prompt sentence to input to the generative AI model is as follows:

[0531] Prompt statement:

[0532] "If a user is upset, generate a polite response to the following question: Question: 'My item hasn't arrived, what's going on?'"

[0533] In this way, an emotion-responsive customer support system can provide a better customer experience by responding appropriately to the user's emotions.

[0534] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0535] Step 1:

[0536] A user inputs a question through a messenger app on the device. The input question is acquired as text data. The input data is the user's question text, and the output data is the question in text format.

[0537] Step 2:

[0538] The system captures the user's facial expressions and tone of voice in real time using the device's camera and microphone. The input data are the user's facial images and voice data, and the output data is multimedia information including these data.

[0539] Step 3:

[0540] The facial expression images and voice data captured by the terminal are sent to the emotion recognition engine means. The emotion recognition engine means analyzes these data and recognizes the user's emotion. The input data is multimedia information, and the output data is the user's emotion information.

[0541] Step 4:

[0542] The emotion recognition engine means provides the recognized emotion information to the generative AI means. The input data is the user's emotion information, and the output data is a prompt sentence containing the emotion information.

[0543] Step 5:

[0544] The generative AI method generates answers to user questions in real time, taking into account emotional information. The input data are a prompt containing emotional information and the user's question text, and the output data is the generated answer text.

[0545] Step 6:

[0546] The generated answer text is sent to the user through a messenger application means of the terminal, and the input data is the generated answer text, and the output data is the answer displayed to the user.

[0547] Step 7:

[0548] The user receives the answer and enters a follow-up question if necessary, and the process repeats again from step 1. The input data is the user's follow-up question text, and the output data is the new question text.

[0549] In this way, it is possible to provide an appropriate response in real time according to the user's feelings.

[0550] Example 2

[0551] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0552] In traditional business negotiations and meetings, it can be difficult for users to respond quickly and appropriately to customer questions. Furthermore, responses cannot be adjusted according to changes in the user's emotions, which can lead to lower customer satisfaction. This increases the risk of missed business opportunities.

[0553] 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.

[0554] In this invention, the server includes generative AI means, communication means, and emotion engine means, which allow users to receive appropriate answers to customer questions in real time and adjust the answers according to changes in the user's emotions.

[0555] "Generative AI methods" refers to artificial intelligence technology that generates appropriate answers to questions from users.

[0556] "Communication means" refers to the technology for sending and receiving data between the generative AI means and the user's device.

[0557] "Emotion engine means" refers to technology that tracks user emotions in real time and collects that data.

[0558] "Means for providing answers" refers to the technology for presenting the answers generated by the generative AI means to the user.

[0559] "Emotional Data" refers to information regarding a user's emotional state collected by emotion engine means.

[0560] "Means for adjusting responses" refers to technology that changes the tone and content of responses generated by generative AI means based on emotional data.

[0561] This invention is a system that enables a user to quickly and appropriately answer questions from customers in situations such as business negotiations and meetings. This system includes generative AI means, communication means, and emotion engine means.

[0562] Hardware and software used

[0563] Hardware: Servers, devices (PCs, tablets, smartphones)

[0564] Software: Generative AI models (e.g., general-purpose natural language processing models), emotion engines (e.g., emotion recognition software)

[0565] System configuration

[0566] 1. The server hosts the generative AI means and the emotion engine means. The server receives questions from users, passes them to the generative AI means to generate answers, and receives emotion data from the emotion engine means and provides it to the generative AI means.

[0567] 2. The terminal is a device used by the user to input questions in real time during a business meeting with a customer. The terminal sends the questions to the server, receives the answers from the server, and displays them to the user.

[0568] 3. The user inputs questions from customers into the device during business negotiations or meetings and receives answers from the generative AI means.

[0569] Details of data processing and calculation

[0570] The generative AI means generates appropriate answers to questions from users. For example, if a user asks, "How long is the warranty period for this product?", the generative AI means generates the answer, "The warranty period for this product is two years."

[0571] The communication means sends and receives data between the device and the server. Questions entered by the user into the device are sent to the server via the communication means. The server receives the answer from the generative AI means and sends it back to the device via the communication means.

[0572] The emotion engine means tracks the user's emotions in real time and collects the data, for example, when the user expresses dissatisfaction, the information is collected and sent to the server.

[0573] The response adjustment means changes the tone and content of the response generated by the generative AI means based on the emotional data. For example, if the user expresses dissatisfaction, the generative AI means may provide additional information such as, "Furthermore, if any problems occur during the warranty period, we will repair the product free of charge."

[0574] Specific examples

[0575] Sales scenario: A salesperson is explaining a new product when a customer asks, "How long is the warranty on this product?"

[0576] The user enters this question into the terminal.

[0577] The terminal sends a query to the server.

[0578] The server passes the question to a generative AI means to generate an answer.

[0579] The generative AI means generates an answer, "The warranty period for this product is two years," and returns it to the server.

[0580] The server sends the answer to the terminal, which displays it to the user.

[0581] The emotion engine means tracks changes in the user's emotions and collects information when the user is dissatisfied.

[0582] The server provides emotional data to the generative AI means to adjust the tone and content of the response.

[0583] The generative AI means provides the additional information, "Furthermore, if any problems arise during the warranty period, we will repair it free of charge."

[0584] The server sends the adjusted answer to the terminal, which displays it to the user.

[0585] Prompt Sentence Examples

[0586] Input prompt: "How long is the warranty on this product?"

[0587] Generated answer: "This product is covered by a two-year warranty. What's more, if a problem occurs during the warranty period, we'll repair it free of charge."

[0588] This system allows users to respond to customer questions quickly and appropriately, preventing missed business opportunities and improving customer satisfaction.

[0589] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0590] Step 1:

[0591] The user inputs a question into the terminal.

[0592] Input: A question the user receives from a customer (e.g., "How long is the warranty on this product?")

[0593] Specific actions: The user types a question into the input field on the terminal and presses the send button.

[0594] Output: Question data entered on the terminal

[0595] Step 2:

[0596] The terminal sends a question to the server.

[0597] Input: Question data entered into the terminal

[0598] Specific operation: The device generates an HTTP request and sends the query data to the server.

[0599] Output: Question data sent to the server

[0600] Step 3:

[0601] The server passes the question to the generative AI means.

[0602] Input: Question data sent to the server

[0603] Specific operation: The server analyzes the question data and makes an API call to pass it to the generative AI means.

[0604] Output: Question data passed to the generative AI method

[0605] Step 4:

[0606] A generative AI means generates answers to questions.

[0607] Input: Question data passed to the generative AI method

[0608] How it works: The generative AI means analyzes the question data and generates an appropriate answer (e.g., "This product has a two-year warranty").

[0609] Output: Generated response data

[0610] Step 5:

[0611] The server sends the generated response to the terminal.

[0612] Input: Generated response data

[0613] Specific operation: The server receives the generated response data and sends it to the terminal as an HTTP response.

[0614] Output: Answer data sent to the device

[0615] Step 6:

[0616] The terminal displays the answer to the user.

[0617] Input: Answer data sent to the terminal

[0618] Specific operation: The device displays the received answer data on the screen. The user can check the answer on the device screen.

[0619] Output: The answer displayed to the user

[0620] Step 7:

[0621] An emotion engine means tracks the emotions of the user.

[0622] Input: Emotional data such as the user's facial expressions and tone of voice

[0623] Specific operation: The emotion engine means analyzes the user's facial expressions and tone of voice in real time and tracks changes in emotions.

[0624] Output: Tracked emotion data

[0625] Step 8:

[0626] The server provides emotion data to the generative AI means.

[0627] Input: Tracked emotion data

[0628] Specific operation: The server makes an API call to provide the emotion data received from the emotion engine means to the generative AI means.

[0629] Output: Emotion data provided to the generative AI means

[0630] Step 9:

[0631] A generative AI tool adjusts the answer based on the emotional data.

[0632] Input: Emotion data provided to the generative AI method

[0633] What it does: The generative AI method analyzes the emotional data and adjusts the tone and content of the response (e.g., "What's more, if the issue occurs during the warranty period, we'll repair it free of charge").

[0634] Output: Adjusted response data

[0635] Step 10:

[0636] The server sends the adjusted response to the terminal.

[0637] Input: Adjusted response data

[0638] Specific operation: The server receives the adjusted response data and sends it to the terminal as an HTTP response.

[0639] Output: Adjusted response data sent to the device

[0640] Step 11:

[0641] The terminal displays the adjusted answer to the user.

[0642] Input: Adjusted response data sent to the device

[0643] Specific operation: The device displays the received adjusted answer data on the screen. The user checks the adjusted answer on the device screen.

[0644] Output: The adjusted answer displayed to the user

[0645] (Application example 2)

[0646] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0647] In traditional sales negotiations and customer service in brick-and-mortar stores, salespeople and store clerks are required to respond to customer questions quickly and accurately, but it is difficult to provide appropriate answers to all questions immediately. It is also difficult to adjust responses according to changes in the customer's emotions, making it difficult to improve customer satisfaction.

[0648] 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.

[0649] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger application means for sending and receiving the Q&As generated by the generative AI means, a means for providing answers to questions from users via the messenger application means, an emotion recognition means for tracking user emotions, a means for adjusting the answers of the generative AI means based on the emotion information tracked by the emotion recognition means, and a display means for displaying the answers. This makes it possible to provide quick and accurate answers to customer questions and to adjust responses according to changes in the customer's emotions.

[0650] "Generative AI methods" are artificial intelligence techniques that generate detailed Q&A about specific products or topics.

[0651] The "messenger app means" is an application for sending and receiving Q&A generated by the generative AI means.

[0652] "Means for providing answers to questions from users" refers to a function that provides answers generated by generative AI means to questions from users through messenger app means.

[0653] "Emotion recognition means" is a technology for tracking a user's emotions.

[0654] The "means for adjusting the response of the generative AI means based on emotional information" is a function for adjusting the response generated by the generative AI means based on emotional information tracked by the emotion recognition means.

[0655] "Display means" refers to devices or technologies used to display the answers generated by the generative AI means to the user.

[0656] As an embodiment of the present invention, a customer service system for a brick-and-mortar store will be described as an example. This system includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the generated Q&As, a means for providing answers to questions from users, an emotion recognition means for tracking user emotions, a means for adjusting the answers of the generative AI means based on the emotion information, and a display means for displaying the answers.

[0657] Hardware and software used

[0658] 1. Hardware:

[0659] Smart glasses (display means)

[0660] Camera (built into smart glasses, for emotion recognition)

[0661] Microphone (for voice input)

[0662] 2. Software:

[0663] OpenAI API (generating AI means)

[0664] EmotionRecognizer (emotion recognition means)

[0665] OpenCV (camera image processing)

[0666] Data processing and calculation

[0667] The server captures the customer's face from the camera footage and tracks their emotions using an emotion recognition model. The user's (customer's) question is obtained through voice input. The answer generated by the generative AI means is adjusted based on the emotional information tracked by the emotion recognition means. For example, the tone and content of the generated answer can be adjusted to be different depending on whether the customer is happy or angry. The generated answer is displayed on the smart glasses.

[0668] Specific examples

[0669] If a customer asks, "How do I use this product?" and the emotion recognition model determines that the customer is happy, the prompt might look like this:

[0670] Prompt Sentence Examples

[0671] Once the customer is happy, ask: How do I use this product?

[0672] This prompt is sent to a generative AI, and the resulting answer is displayed on the store associate's smart glasses, allowing them to quickly provide an appropriate response based on the customer's emotions.

[0673] This system will enable the company to provide quick and accurate answers to customer questions and adjust responses according to changes in customer emotions, which is expected to improve customer satisfaction.

[0674] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0675] Step 1:

[0676] The server captures the customer's face through a camera. The input is the camera image, and the output is the captured customer's face image. This face image is sent to the emotion recognition means.

[0677] Step 2:

[0678] The server tracks the customer's emotions from the captured facial images using an emotion recognition means. The input is the facial image obtained in step 1, and the output is the customer's emotional information (e.g., joy, anger, sadness, etc.). This emotional information is sent to the generative AI means.

[0679] Step 3:

[0680] The user (customer) speaks their question into the microphone. The input is the customer's voice, and the output is voice data. This voice data is sent to the voice recognition system.

[0681] Step 4:

[0682] The server converts the voice data into text using a speech recognition system. The input is the voice data obtained in step 3, and the output is a text question. This text is sent to the generative AI means.

[0683] Step 5:

[0684] The server generates a prompt sentence based on the emotional information and the text question. The input is the emotional information obtained in step 2 and the text question obtained in step 4, and the output is the prompt sentence. For example, the generated prompt sentence is, "Question when the customer is happy: How do you use this product?"

[0685] Step 6:

[0686] The server uses a generative AI means to generate an answer based on the prompt. The input is the prompt obtained in step 5, and the output is the generated answer. This answer is sent to the display means.

[0687] Step 7:

[0688] The terminal (smart glasses) displays the generated answer. The input is the answer obtained in step 6, and the output is the text displayed on the smart glasses display. This allows the user (store clerk) to provide an appropriate answer to the customer.

[0689] Example 3

[0690] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0691] Conventional generative AI systems generate answers without considering the user's emotions, which can lead to lower user satisfaction. It is also difficult to provide appropriate answers based on the user's emotions, making it necessary to provide effective responses, especially when used in educational and event settings. This has made it difficult to improve user understanding and satisfaction.

[0692] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0693] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger application means for sending and receiving the Q&As generated by the generative AI means, a means for providing answers to questions from users via the messenger application means, an emotion engine means for recognizing user emotions, and a means for generating answers based on emotion information obtained from the emotion engine means. This makes it possible to provide appropriate answers in real time according to the user's emotions.

[0694] "Generative AI methods" refers to artificial intelligence techniques for generating detailed Q&A about specific products or topics.

[0695] "Messenger app means" refers to application software for sending and receiving Q&As generated by generative AI means.

[0696] "Means for providing answers to questions from users" refers to the function for providing answers to questions from users through messenger app means.

[0697] "Emotion engine means" refers to technology for recognizing emotions from a user's facial expressions, tone of voice, message context, etc.

[0698] The "means for generating an answer based on emotional information" refers to a function for generating an appropriate answer to a question from a user based on emotional information obtained from the emotion engine means.

[0699] This invention relates to a system for generating detailed Q&A about a specific product or topic. This system is composed of a generative AI means, a messenger app means, and an emotion engine means for recognizing user emotions.

[0700] The server uses, as the generative AI means, for example, OpenAI's GPT-4 or a similar generative AI model. This generative AI means is designed to generate detailed answers to questions from users. The generated answers are sent to the users via a messenger app means. The messenger app means can be a common messaging platform such as Slack, MICROSOFT TEAMS (registered trademark), or WhatsApp.

[0701] Furthermore, the server uses, for example, Microsoft Azure's Emotion API or Google® Cloud's Natural Language API as an emotion engine means. This emotion engine means recognizes emotions from the user's facial expressions, tone of voice, message context, etc., and provides this information to the generative AI means. The generative AI means generates appropriate answers to questions from the user based on this emotion information. For example, if the emotion engine means recognizes that the user is angry, the generative AI means generates answers in a more polite and calm tone.

[0702] As a concrete example, consider the case where a teacher receives a question from a student, "I don't understand this math problem." The teacher opens the Slack app and types, "I don't understand this math problem." The teacher's device sends the typed question to a server via Slack's API. The server uses Microsoft Azure's Emotion API to recognize that the teacher is confused from the context of the question. The server uses OpenAI's GPT-4 to generate a careful and detailed solution to the math problem for the confused teacher. The server sends the generated answer to the teacher's device via Slack's API. The teacher's device displays an answer on the Slack app, such as, "Here's how to solve this math problem..."

[0703] An example of a prompt sentence is, "If a student is confused, please explain in an easy-to-understand way how to solve the math problem." In this way, the user can quickly obtain a detailed answer to their question. The flow of the specific process in Example 3 will be described with reference to FIG. 21.

[0704] Step 1:

[0705] The user enters a question.

[0706] The user uses the messenger app to input a question. For example, a teacher might type, "I don't understand this math problem." The input question is saved on the user's device.

[0707] Step 2:

[0708] The terminal sends a question to the server.

[0709] The device sends the entered question to the server through the API of the messenger app. For example, the Slack API is used to send the question to the server. The input is the user's question, and the output is the question sent to the server.

[0710] Step 3:

[0711] The server analyzes the user's emotions using an emotion engine.

[0712] The server passes the received question to the emotion engine, which analyzes the user's facial expression, tone of voice, and message context to recognize the user's emotion. For example, it uses Microsoft Azure's Emotion API to recognize that the user is confused. The input is the user's question, and the output is the user's emotional information.

[0713] Step 4:

[0714] The server generates answers using a generative AI model.

[0715] The server generates answers using a generative AI model based on the emotional information obtained from the emotion engine. For example, it uses OpenAI's GPT-4 to generate polite and detailed answers for confused users. The input is the user's question and emotional information, and the output is the generated answer.

[0716] Step 5:

[0717] The server sends the generated response to the terminal.

[0718] The server sends the generated answer to the device through the API of the messenger app. For example, it sends the answer using the Slack API. The input is the generated answer, and the output is sending the answer to the device.

[0719] Step 6:

[0720] The terminal displays the answer to the user.

[0721] The device displays the response received from the server to the user, who can then check the response on the messenger app. The input is the response from the server, and the output is the display of the response to the user.

[0722] (Application example 3)

[0723] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0724] Conventional customer support systems provide uniform answers without considering the user's feelings, resulting in low user satisfaction. Furthermore, in physical stores, it is difficult to provide quick and appropriate answers to customers' questions, and responses are often insufficient, especially in situations where an emotional response is required. This can sometimes ruin the customer experience.

[0725] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0726] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger application means for sending and receiving the Q&As generated by the generative AI means, a means for providing answers to questions from users via the messenger application means, an emotion engine means for recognizing user emotions, a means for generating answers based on emotion information recognized by the emotion engine means, and a means installed in a customer support robot located in a physical store. This makes it possible to provide appropriate answers in real time according to the user's emotions, thereby improving customer satisfaction.

[0727] "Generative AI methods" refers to artificial intelligence techniques that generate detailed Q&A about specific products or topics.

[0728] "Messenger App Means" refers to an application for sending and receiving Q&As generated by Generative AI Means.

[0729] "Means of providing answers to questions from users" refers to the function of providing appropriate answers to questions from users through messenger app means.

[0730] "Emotion engine means" refers to technology for recognizing emotions from a user's facial expressions, tone of voice, message context, etc.

[0731] "Means for generating answers based on emotional information" refers to a function that enables the generative AI means to generate appropriate answers for the user based on the emotional information recognized by the emotion engine means.

[0732] "Means to be installed in customer support robots installed in physical stores" refers to a function that is installed in a robot installed in a physical store and that uses generative AI means to provide answers to questions from customers.

[0733] A system for carrying out this invention includes generative AI means for generating detailed Q&As about specific products or themes, messenger application means for sending and receiving Q&As generated by the generative AI means, means for providing answers to questions from users through the messenger application means, emotion engine means for recognizing user emotions, means for generating answers based on emotion information recognized by the emotion engine means, and means installed in a customer support robot installed in a physical store.

[0734] The server uses, for example, the Transformers library as the generative AI means. The generative AI means generates detailed answers to questions from users. The messenger app means is an application for sending and receiving the generated Q&A, and receives questions from users and sends them to the generative AI means. The means for providing answers to questions from users returns answers to users through the messenger app means.

[0735] The emotion engine means is a technology for recognizing emotions from the user's facial expressions, tone of voice, message context, etc., and uses the EmotionRecognition library, for example. The emotion information recognized by the emotion engine means is provided to the generative AI means, which generates an appropriate response according to the user's emotions.

[0736] A customer support robot installed in a physical store uses a camera to capture the user's facial expressions and transmits them to an emotion engine means. The customer support robot then uses generative AI means to generate answers to the user's questions in real time and provides them to the user.

[0737] As a concrete example, consider the case where a customer asks, "Tell me about this product." If the customer appears to be troubled, the emotion engine means will recognize this as "trouble" and input the following prompt sentence to the generative AI means:

[0738] "If a user is having trouble, please politely answer the following question: Tell me about this product."

[0739] The generative AI means uses this prompt to generate a more helpful and polite response, such as, "This product uses the latest technology and is extremely high-performance. It is also designed to be easy to use, so even first-time users can use it with confidence."

[0740] In this way, it becomes possible to provide appropriate answers in real time according to the user's emotions, thereby improving customer satisfaction.

[0741] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0742] Step 1:

[0743] A user types a question into a customer support robot.

[0744] Input: User question (e.g. "Tell me about this product")

[0745] Output: The user's question is sent to the customer support robot.

[0746] Specific operation: The user enters a question through the robot's interface and presses the send button.

[0747] Step 2:

[0748] The customer support robot uses a camera to capture the user's facial expressions.

[0749] Input: User's facial expression video

[0750] Output: Captured facial expression data

[0751] Specific operation: The robot's camera captures the user's face and acquires video data.

[0752] Step 3:

[0753] The server recognizes the user's emotions using an emotion engine means.

[0754] Input: Captured facial expression data

[0755] Output: Recognized emotion information (e.g., "I'm in trouble")

[0756] Specific operation: The server uses the EmotionRecognition library to analyze facial expression data and identify the user's emotions.

[0757] Step 4:

[0758] The server generates a prompt using generative AI means.

[0759] Input: User question, recognized emotion information

[0760] Output: Generated prompt (e.g., "If the user is having trouble, please politely answer the following question: Tell me about this product.")

[0761] Specific operation: The server creates a prompt sentence based on the emotional information and inputs it into the generative AI model.

[0762] Step 5:

[0763] The server uses generative AI tools to generate answers to users' questions.

[0764] Input: Generated prompt text

[0765] Output: Generated answer (e.g., "This product uses the latest technology and is extremely high-performance. It is also designed to be easy to use, so even first-time users can use it with confidence.")

[0766] What happens: The server uses the Transformers library to generate an answer based on the prompt.

[0767] Step 6:

[0768] The customer support robot provides the generated answer to the user.

[0769] Input: Generated Answer

[0770] Output: The answer provided to the user

[0771] Specific behavior: The robot will respond to the user via voice or text.

[0772] 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.

[0773] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0774] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0775] 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.

[0776] [Second embodiment]

[0777] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0778] 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.

[0779] 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).

[0780] 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.

[0781] 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.

[0782] 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).

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0789] "Example 1"

[0790] One embodiment of the present invention is a system that uses a generative AI that generates detailed Q&As about specific products or themes, and a messenger app that sends and receives the Q&As generated by the generative AI. The generative AI generates answers to questions from users in real time. The messenger app sends the Q&As generated by the generative AI to users and sends questions from users to the generative AI.

[0791] "Example 2"

[0792] As a specific example, consider a sales negotiation scenario. Salespeople can receive answers to customer questions in real time through generative AI. This allows salespeople to respond to customer questions quickly, avoid missing sales opportunities, and improve customer satisfaction.

[0793] "Example 3"

[0794] The present invention is also useful in educational settings. Teachers can use generative AI to obtain detailed answers to questions from students, helping them improve their students' understanding. Furthermore, using the system of the present invention in Q&A sessions at events can also improve participant satisfaction.

[0795] The processing flow of each embodiment will be described below.

[0796] "Example 1"

[0797] Step 1: User types in a question through the messenger app.

[0798] Step 2: The messenger app sends the user's question to the generative AI.

[0799] Step 3: The generative AI generates answers to the user's questions in real time. Step 4: The messenger app sends the answers generated by the generative AI to the user.

[0800] "Example 2"

[0801] Step 1: A salesperson types a customer's question into a messenger app.

[0802] Step 2: The messenger app sends the salesperson's question to the generative AI.

[0803] Step 3: The generative AI generates answers to questions from sales representatives in real time.

[0804] Step 4: The messenger app sends the answer generated by the generative AI to the salesperson, who then responds to the customer based on the answer.

[0805] "Example 3"

[0806] Step 1: The teacher types the student's question into the messenger app.

[0807] Step 2: The messenger app sends the teacher's question to the generative AI.

[0808] Step 3: The generative AI generates answers to questions from the teacher in real time.

[0809] Step 4: The answer generated by the generative AI is sent to the teacher via a messaging app, who then responds to the student based on the answer.

[0810] Example 1

[0811] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0812] Previous Q&A systems often had delays in responding to user questions, making it difficult to respond in real time. Providing detailed information on specific products or topics also required building and maintaining a massive database, which was costly. Furthermore, the interface for users to enter questions could be difficult to use, resulting in a poor user experience.

[0813] 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.

[0814] In this invention, the server includes a generation AI means for generating detailed Q&As about specific products or themes, a messenger application means for transmitting and receiving the Q&As generated by the generation AI means, a means for sending questions from users to the generation AI means through the messenger application means, and a means for sending answers generated by the generation AI means to users, thereby enabling users to receive detailed Q&As in real time.

[0815] A "generative AI tool" is a system that uses artificial intelligence technology to generate detailed Q&A about a specific product or topic.

[0816] The "messenger app means" is a communication application for sending questions from users and receiving answers from the generative AI means.

[0817] The "means for sending questions from users to generative AI means" is a function for sending questions entered by users through messenger app means to generative AI means.

[0818] "Means for sending an answer generated by a generative AI means to a user" is a function for sending an answer generated by a generative AI means to a user through a messenger app means.

[0819] A "prompt" is text containing a question from a user that is input to a generative AI means.

[0820] This invention is a system for generating detailed Q&A about a specific product or theme. The system includes a generative AI means, a messenger application means, a means for sending a question from a user to the generative AI means, and a means for sending an answer generated by the generative AI means to the user.

[0821] The server uses server hardware equipped with a high-performance GPU (e.g., a high-performance graphics processor) to run the generative AI means. Furthermore, the generative AI model employs an advanced generative AI model (e.g., a large-scale language model) that uses natural language processing technology. The generative AI means receives questions from users and generates appropriate answers to those questions in real time.

[0822] The device is a smartphone or PC with a messenger app installed that the user uses. This messenger app (e.g., a general communication application) sends questions from the user to the generative AI means and displays the answers from the generative AI means to the user.

[0823] Specifically, the data processing involves sending a question from the user to the server via a messenger app, where the generative AI analyzes the question and generates an appropriate answer, which is then sent back to the user via the messenger app.

[0824] For example, if a user asks, "What is the battery life like on my new smartphone?" the following happens:

[0825] 1. The user types a question using a messenger app.

[0826] 2. The messenger app sends the question to the server.

[0827] 3. The server uses generative AI methods to analyze the question and generate an appropriate answer.

[0828] 4. The generated answer (e.g., "The battery life of a new smartphone is typically around 24 hours. However, this may vary depending on usage.") is sent from the server to the messenger app.

[0829] 5. The Messenger app will display the generated answer to the user.

[0830] Example prompt sentence:

[0831] "What's the battery life like on my new smartphone?"

[0832] In this way, users can receive detailed Q&A in real time.

[0833] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0834] Step 1:

[0835] The user types a question through a messenger app.

[0836] Specifically, a user opens a messaging app installed on their smartphone or PC and types a question, for example, "What is the battery life of my new smartphone?"

[0837] Input: User question text

[0838] Output: Question text entered into the messenger app

[0839] Step 2:

[0840] The terminal sends a question to the server.

[0841] Specifically, the device sends the user's question to the server via the messenger app's API. The question is sent to the server in an appropriate format (e.g., JSON format).

[0842] Input: Question text entered into the messenger app

[0843] Output: Question text sent to the server

[0844] Step 3:

[0845] The server receives the question and inputs it as a prompt into the generative AI model.

[0846] Specifically, the server analyzes the received question and inputs it into the generative AI model as a prompt sentence, which is the user's question as is.

[0847] Input: Question text sent to the server

[0848] Output: The prompt sentence that is input to the generative AI model

[0849] Step 4:

[0850] A generative AI model generates answers to questions.

[0851] Specifically, the generative AI model generates an appropriate answer to the question based on the prompt sentence, for example, "The battery life of a new smartphone is usually about 24 hours. However, this may vary depending on usage."

[0852] Input: A prompt sentence entered into the generative AI model

[0853] Output: Answer text generated by the generative AI model

[0854] Step 5:

[0855] The server receives the generated response and sends it to the terminal.

[0856] Specifically, the server converts the answer received from the generative AI model back into an appropriate format (e.g., JSON format) and sends it to the terminal.

[0857] Input: Answer text generated by the generative AI model

[0858] Output: Answer text sent to the terminal

[0859] Step 6:

[0860] The terminal displays the answer to the user.

[0861] Specifically, the device receives the response from the server and displays it to the user via the messenger app. The user can then check the response on the chat screen of the messenger app.

[0862] Input: Answer text sent to the terminal

[0863] Output: Reply text displayed in the messenger app

[0864] (Application example 1)

[0865] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0866] On traditional online shopping sites, users would have to visit FAQ pages or contact customer support to get detailed information about products, which made it difficult to get a quick response. Furthermore, if users were unable to resolve their questions about a product, their desire to purchase would decrease, which could result in a decrease in sales. Furthermore, the burden on customer support would increase, making it difficult to operate efficiently.

[0867] 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.

[0868] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the Q&As generated by the generative AI means, a means for providing answers to questions from users through the messenger app means, an application means installed on a smartphone, and a means for users to input product-related questions through the application means, the generative AI means for generating answers to those questions in real time, and the means for providing the answers to users through the messenger app means. This allows users to quickly obtain detailed product information, increasing their desire to purchase. It also reduces the burden on customer support and enables more efficient operations.

[0869] "Generative AI methods" refers to artificial intelligence techniques for generating detailed Q&A about specific products or topics.

[0870] "Messenger App Means" refers to an application for sending and receiving Q&As generated by Generative AI Means.

[0871] "Means for providing answers to questions from users" refers to a function for providing users with answers generated by generative AI means in response to questions entered by users.

[0872] "Application means installed on a smartphone" refers to an application that runs on a smartphone and allows a user to input questions about a product.

[0873] "Means for inputting a question about a product, for the generative AI means to generate an answer to the question in real time, and for providing the answer to the user through the messenger app means" refers to a series of functions for a user to input a question about a product, for the generative AI means to generate an answer to the question in real time, and for providing the answer to the user through the messenger app means.

[0874] The following system configuration is used as an embodiment of the present invention.

[0875] The server includes a generative AI means for generating detailed Q&A about a specific product or topic, using a generative AI model such as OpenAI's GPT-3, and capable of generating answers in real time to user questions.

[0876] The terminal includes an application means installed on the smartphone. The application means provides an interface for the user to input a question about the product. When the user inputs a question, the question is transmitted to the server via a messenger application means.

[0877] The messenger app means is an application for sending and receiving Q&As generated by the generative AI means. For example, it is implemented as a web application using Flask. This messenger app means plays a role in sending questions from users to the generative AI means and returning generated answers to users.

[0878] Specifically, the process involves a user entering a question through a smartphone app, which is then sent to the server through a messenger app. The server's AI generator generates an answer to the question in real time and returns the answer to the user through the messenger app.

[0879] For example, if a user asks, "What is the battery life of this smartphone?", the generative AI means generates the answer, "This smartphone's battery life is approximately 10 hours under normal use." This answer is provided to the user via a messenger app means.

[0880] An example prompt sentence would be of the following format:

[0881] Q: What is the battery life of this phone?

[0882] A: This smartphone's battery life is approximately 10 hours under normal use.

[0883] In this way, users can quickly obtain detailed information about products, which increases their willingness to purchase. It also reduces the burden on customer support and enables more efficient operations.

[0884] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0885] Step 1:

[0886] A user starts the smartphone app and inputs a question about a product. The input question is transmitted to the messenger app means via the application means. The input data is the user's question, and the output data is the question transmitted to the messenger app means.

[0887] Step 2:

[0888] The messenger application means transmits a question received from a user to a server. The input data is the user's question, and the output data is the question to be transmitted to the server. Specifically, the messenger application means transmits the question data to the server using an HTTP request.

[0889] Step 3:

[0890] The server passes the received question to the generative AI means. The input data is the question received from the messenger app means, and the output data is the question passed to the generative AI means. Specifically, the server inputs the question data into the generative AI model.

[0891] Step 4:

[0892] The generative AI means generates answers to received questions in real time. The input data is the user's question, and the output data is the generated answer. Specifically, it uses a generative AI model (e.g., GPT-3) to generate a prompt sentence and generate an answer.

[0893] Step 5:

[0894] The server transmits the answer received from the generative AI means to the messenger application means. The input data is the generated answer, and the output data is the answer to be transmitted to the messenger application means. Specifically, the server transmits the answer data to the messenger application means using an HTTP response.

[0895] Step 6:

[0896] The messenger application means transmits the response received from the server to the smartphone application. The input data is the response received from the server, and the output data is the response sent to the smartphone application. Specifically, the application performs processing to display the response data within the application.

[0897] Step 7:

[0898] The user checks the answer generated by the generative AI means through the smartphone app. The input data is the answer received from the messenger app means, and the output data is the answer checked by the user. Specifically, the answer is displayed on the smartphone screen and the user views it.

[0899] Example 2

[0900] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0901] In traditional business negotiations and meetings, it can be difficult for salespeople and other participants to quickly and accurately answer questions from customers and other participants. This can lead to missed business opportunities and reduced customer satisfaction. Another issue is the lack of a way to instantly obtain appropriate answers in situations where real-time information provision is required.

[0902] 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.

[0903] In this invention, the server includes a means for a user to input a question, a means for the terminal to transmit the input to the server, a means for the server to transmit a prompt sentence to the generative AI model, a means for the generative AI model to generate an answer, a means for the server to transmit the answer to the terminal, and a means for the terminal to display the answer to the user, thereby enabling the user to quickly and accurately obtain answers to questions from customers and other participants.

[0904] A "user" is an entity that uses the system to enter questions and receive answers.

[0905] A "terminal" is a device through which a user inputs questions and communicates with the server, and includes laptops, tablets, etc.

[0906] The "server" is a computer system that receives questions from users, sends prompts to the generative AI model, and sends the generated answers to the terminal.

[0907] A "generative AI model" is an artificial intelligence model that generates appropriate answers based on prompt text, and examples include GPT-4.

[0908] A "prompt sentence" is a textual sentence that is converted to help the generative AI model properly understand the question.

[0909] The "means for inputting a question" is an interface that allows a user to input a question using a terminal.

[0910] The "means for transmitting input to a server" is a communication means by which the terminal transmits a question input by a user to a server.

[0911] The "means for sending a prompt sentence" is the means by which the server converts the user's question into a prompt sentence and sends it to the generative AI model.

[0912] The "means for generating an answer" refers to the means by which the generative AI model generates an answer based on the prompt sentence.

[0913] "Means for sending an answer to a terminal" refers to the means by which the server sends the answer obtained from the generative AI model to the terminal.

[0914] The "means for displaying the answer to the user" is an interface for displaying the answer received by the terminal from the server to the user.

[0915] This invention is a system that allows users to quickly and accurately obtain answers to questions from customers and other participants in business negotiations and meetings. The system allows users to input questions, generates answers in real time using a generative AI model, and provides the answers to users.

[0916] Hardware and software used

[0917] 1. Terminal

[0918] Use devices such as laptops and tablets.

[0919] Using a dedicated application or web browser, users enter questions and communicate with the server.

[0920] 2. Server

[0921] It uses a high-performance computer system to receive questions from users, send prompts to a generative AI model, and send the generated answers to the device.

[0922] Python, Node.js, etc. are used as server-side scripts.

[0923] 3. Generative AI Models

[0924] For example, GPT-4 is used as a generative AI model.

[0925] Generate appropriate answers based on the prompt.

[0926] Data processing and calculation

[0927] 1. The user enters a question

[0928] Users enter questions using the keyboard or touchscreen of their laptop or tablet.

[0929] Example: A salesperson types, "How long is the warranty on this product?"

[0930] 2. The device sends the input to the server

[0931] The terminal sends the entered question to the server as an HTTP request.

[0932] Software required: Dedicated application and web browser

[0933] 3. The server sends a prompt to the generative AI model

[0934] The server converts the received question into a prompt sentence suitable for the generative AI model and sends it to the generative AI model.

[0935] Example: A server-side script converts a prompt into a statement of the form "Generate an answer to the customer question: 'What is the warranty period for this product?'"

[0936] 4. Generative AI models generate answers

[0937] The generative AI model generates appropriate answers based on the prompt text.

[0938] Example: Generate the answer "This product has a one-year warranty."

[0939] 5. The server sends the answer to the device

[0940] The server sends the answer obtained from the generative AI model to the terminal as an HTTP response.

[0941] 6. The device displays the answer to the user

[0942] The terminal displays the answer received from the server on the screen and the user confirms it.

[0943] Software required: Dedicated application and web browser

[0944] Examples of specific examples and prompts

[0945] Specific examples

[0946] A salesperson is asked by a customer, "How long is the warranty on this product?"

[0947] The salesperson types into the terminal, "How long is the warranty on this product?"

[0948] The device sends the question to the server, which then sends the prompt to the generative AI model.

[0949] The generative AI model generates the answer, "This product has a one-year warranty."

[0950] The server sends the answer to the terminal, which displays it to the salesperson.

[0951] Prompt Sentence Examples

[0952] "Generate an answer to the customer question: 'How long is the warranty on this product?'"

[0953] The system allows users to get quick and accurate answers to questions from customers and other participants, increasing the success of business negotiations and meetings.

[0954] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0955] Step 1:

[0956] The user enters a question.

[0957] A user inputs a question using the keyboard or touch screen of a laptop or tablet. For example, a salesperson might input, "How long is the warranty period for this product?" The input data is a text question.

[0958] Step 2:

[0959] The device sends input to the server.

[0960] The device sends the question entered by the user to the server as an HTTP request. Specifically, a dedicated application or web browser sends the entered question to the server. The input data is the text question entered by the user, and the output data is the HTTP request sent to the server.

[0961] Step 3:

[0962] The server sends a prompt to the generative AI model.

[0963] The server converts the received question into a prompt suitable for the generative AI model and sends it to the generative AI model. Specifically, a server-side script (e.g., Python, Node.js) converts the question into a prompt in the format "Please generate an answer to customer question: 'How long is the warranty period for this product?'" and sends an API request to the generative AI model. The input data is the HTTP request sent to the server, and the output data is the prompt sent to the generative AI model.

[0964] Step 4:

[0965] A generative AI model generates the answer.

[0966] The generative AI model generates an appropriate answer based on the prompt. Specifically, the generative AI model (e.g., GPT-4) analyzes the received prompt and generates the answer, "This product has a one-year warranty." The input data is the prompt sent to the generative AI model, and the output data is the generated answer.

[0967] Step 5:

[0968] The server sends the response to the terminal.

[0969] The server sends the answer obtained from the generative AI model to the terminal as an HTTP response. Specifically, the server-side script sends the generated answer to the terminal as an HTTP response. The input data is the answer obtained from the generative AI model, and the output data is the HTTP response sent to the terminal.

[0970] Step 6:

[0971] The terminal displays the answer to the user.

[0972] The terminal displays the response received from the server to the user. Specifically, a dedicated application or web browser displays the received response on the screen, which the sales representative can then confirm. The input data is the HTTP response received from the server, and the output data is the text-formatted response that is displayed to the user.

[0973] (Application example 2)

[0974] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0975] In traditional sales negotiations and customer service in brick-and-mortar stores, it can be difficult for salespeople or store clerks to quickly and accurately answer customer questions. This can lead to lower customer satisfaction and missed business opportunities. Another issue is that the time it takes to search for information and respond to questions can hinder efficient business operations.

[0976] 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.

[0977] In this invention, the server includes a generative AI means, a messenger application means for transmitting and receiving Q&As generated by the generative AI means, a means for providing answers to questions from users through the messenger application means, and a means for receiving voice input from users using smart glasses, generating answers through the generative AI means, and displaying the answers on a display of the smart glasses. This enables salespeople and store clerks to quickly and accurately answer questions from customers, thereby improving customer satisfaction and work efficiency.

[0978] "Generative AI methods" are methods that use artificial intelligence technology to generate appropriate answers to questions from users.

[0979] "Messenger app means" refers to an application means for sending and receiving Q&A generated by generative AI means.

[0980] "Means for providing answers to questions from users" refers to means for providing answers to questions from users through messenger app means.

[0981] "Smart glasses" are wearable devices worn by users that have voice input and display functions.

[0982] The "means for obtaining voice input" refers to a means for obtaining voice input from a user using the smart glasses.

[0983] "Means for displaying on a display" refers to means for displaying the answer generated through the generative AI means on the display of the smart glasses.

[0984] A system for implementing this invention includes generative AI means, messenger application means, means for providing answers to questions from users, means for acquiring voice input using smart glasses, and display means.

[0985] 1. System Program

[0986] The system program is configured as follows:

[0987] Generative AI method: Uses OpenAI's API to generate appropriate answers to user questions.

[0988] Messenger app means: an application for sending and receiving questions and answers, which works in conjunction with smart glasses.

[0989] Voice input acquisition means: The microphone in the smart glasses is used to acquire voice input from the user.

[0990] Display means: Display the generated answer on the display of the smart glasses.

[0991] 2. Program processing explanation

[0992] The server uses OpenAI's API as the generative AI means. When a user wears the smart glasses and makes a voice input, the microphone in the smart glasses picks up the voice. The picked up voice data is sent to the server via the messenger app means. The server uses the generative AI means to convert the voice data into text and generate an appropriate answer. The generated answer is then sent again to the smart glasses via the messenger app means and displayed on the display.

[0993] 3. Specific Examples

[0994] For example, if a customer asks "Do you have this item in stock?" in a physical store, the microphone in the smart glasses will pick up the voice. The voice data will be sent to the server, and the generative AI means will generate a response such as "Yes, this item is in stock." This response will be displayed on the smart glasses' display, allowing the store clerk to quickly respond to the customer.

[0995] Prompt Sentence Examples

[0996] Customer Question: Is this item in stock?

[0997] A: Yes, this item is in stock.

[0998] In this way, salespeople and store clerks can quickly and accurately answer customer questions through the smart glasses, improving customer satisfaction.

[0999] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1000] Step 1:

[1001] The user wears the smart glasses and performs voice input.

[1002] Input: User's voice question

[1003] Output: Audio data

[1004] Specific operation: The user speaks a question into the microphone of the smart glasses, which then picks up the voice data.

[1005] Step 2:

[1006] The terminal transmits the voice data to the server via the messenger application means.

[1007] Input: Audio data

[1008] Output: Audio data sent to the server

[1009] Specific operation: The smart glasses transmit the acquired voice data to the server through the messenger app.

[1010] Step 3:

[1011] The server converts the audio data into text.

[1012] Input: Audio data

[1013] Output: Text data

[1014] Specific operation: The server uses voice recognition technology to convert the voice data into text data.

[1015] Step 4:

[1016] The server uses generative AI tools to generate answers based on the text data.

[1017] Input: Text data

[1018] Output: Answer text

[1019] What happens: The server uses generative AI tools (e.g., OpenAI API) to generate appropriate answers based on the text data.

[1020] Step 5:

[1021] The server transmits the generated answer text to the terminal via the messenger application means.

[1022] Input: Answer text

[1023] Output: Answer text sent to the terminal

[1024] Specific operation: The server sends the generated answer text to the smart glasses through a messenger app.

[1025] Step 6:

[1026] The terminal displays the answer text on the display of the smart glasses.

[1027] Input: Answer text

[1028] Output: Answer displayed on the smart glasses display

[1029] Specific operation: The smart glasses display the received answer text on the display and the user confirms it.

[1030] In this way, users can quickly and accurately answer customer questions through the smart glasses.

[1031] Example 3

[1032] Next, a description will be given of Example 3 of Form Example 3. 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."

[1033] In traditional education and events, it has been difficult to get quick and accurate answers to questions. In particular, questions that require specialized knowledge often require a lot of time and effort to provide answers. Furthermore, in situations where real-time answers are required, it is difficult to provide appropriate answers immediately. This can lead to a decline in the quality of education and the satisfaction of event participants.

[1034] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1035] In this invention, the server includes means for generating answers to questions from users using a generative AI model, communication means for transmitting and receiving the answers generated by the generative AI model, and means for receiving questions from users via the communication means and displaying the generated answers, thereby enabling users to obtain quick and accurate answers in real time.

[1036] A "generative AI model" is an artificial intelligence model used to generate answers to user questions.

[1037] "Communication means" refers to the means for sending and receiving answers generated by the generative AI model.

[1038] The "display means" is a means for displaying to the user the answer received through the communication means.

[1039] A "user" is a person or entity that utilizes the system to enter questions and receive answers.

[1040] A "question" is information or a question that a user inputs into the system.

[1041] An "answer" is the information or answer that a generative AI model generates in response to a question.

[1042] "Real-time" refers to the extremely short time between when a user enters a question and when they receive a response.

[1043] "Education" is the activity or process of imparting knowledge or skills.

[1044] An "event" is a gathering or event held for a specific purpose or theme.

[1045] A "meeting" is a place where multiple people gather to discuss and make decisions.

[1046] A "business meeting" is a place where business negotiations and transactions are conducted.

[1047] This invention is a system that uses a generative AI model to generate answers to user questions and provide them quickly and accurately. This system can be used in a variety of situations, such as education, events, meetings, and business negotiations.

[1048] Hardware and software used

[1049] Hardware

[1050] Server: A server with high-performance computing power is required, including CPU, GPU, memory, and storage.

[1051] Device: The device through which a user enters a question and receives a response. This can include a tablet, PC, or smartphone.

[1052] software

[1053] Generative AI models: For example, using advanced natural language processing models such as OpenAI's GPT-4.

[1054] Communication method: Uses network protocols (such as HTTP / HTTPS) to send and receive data over an internet connection.

[1055] Display method: Use an application or web browser to display the answers on your device.

[1056] Data processing and calculation

[1057] Data Entry

[1058] Users use the device to type in a question, for example, a teacher uses the tablet keyboard to type, "What is the speed of light?"

[1059] Data transmission

[1060] The device sends the entered question to the server. An internet connection is required for sending. When the device presses the "Send" button, the question is sent to the server via the internet.

[1061] Data Processing

[1062] The server analyzes the received question and converts it into a format suitable for the generative AI model. This process includes text preprocessing and tokenization. The server breaks down the text "What is the speed of light?" into tokens and converts it into a format that can be input to the generative AI model.

[1063] Generate answers

[1064] The server uses a generative AI model to generate a detailed answer to the question. The server inputs the question "What is the speed of light?" into the generative AI model and gets the answer "The speed of light is approximately 299,792,458 meters per second."

[1065] Data transmission

[1066] The server then sends the generated answer to the device. This again requires an internet connection. The server then sends the answer "The speed of light is approximately 299,792,458 meters per second" to the device via the internet.

[1067] Data Display

[1068] The device displays the received answer to the user on the device's screen. The device displays the text "The speed of light is approximately 299,792,458 meters per second" on the screen, and the teacher confirms it.

[1069] Examples of specific examples and prompts

[1070] Specific examples

[1071] A teacher is asked by a student during class, "What is the speed of light?"

[1072] The teacher uses a tablet to type in a question and presses the send button.

[1073] The terminal sends a query to the server.

[1074] The server analyzes the question and inputs it into a generative AI model.

[1075] The generative AI model generates the answer, "The speed of light is approximately 299,792,458 meters per second."

[1076] The server sends the generated response to the terminal.

[1077] The device displays the answers on the screen, and the teacher checks them and passes them on to the students.

[1078] Prompt Sentence Examples

[1079] "What is the speed of light?"

[1080] "What caused World War II?"

[1081] "What is the chemical formula for oxygen?"

[1082] This system enables users to obtain prompt and accurate answers in real time, thereby improving the quality of education and events. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1083] Step 1:

[1084] A user uses a terminal to input a question. The input question is in text format, such as "What is the speed of light?" The terminal receives the question and prepares it for transmission.

[1085] Input: A question typed into the device by the user (e.g., "What is the speed of light?")

[1086] Output: Question data ready to be sent

[1087] Step 2:

[1088] The device sends the entered question to the server. An internet connection is required for transmission, and the HTTP / HTTPS protocol is used. When the device presses the "Send" button, the question is sent to the server via the internet.

[1089] Input: Question data ready to be sent

[1090] Output: Question data sent to the server

[1091] Step 3:

[1092] The server analyzes the received question and converts it into a format suitable for the generative AI model. This process includes text preprocessing and tokenization. The server breaks down the text "What is the speed of light?" into tokens and converts it into a format that can be input to the generative AI model.

[1093] Input: Question data sent to the server

[1094] Output: Data converted into a format that can be fed into a generative AI model

[1095] Step 4:

[1096] The server uses a generative AI model to generate a detailed answer to the question. The server inputs the question "What is the speed of light?" into the generative AI model and gets the answer "The speed of light is approximately 299,792,458 meters per second."

[1097] Input: Data converted into a format that can be fed into a generative AI model

[1098] Output: Answer data obtained from the generative AI model

[1099] Step 5:

[1100] The server then sends the generated answer to the device. This again requires an internet connection and uses the HTTP / HTTPS protocol. The server then sends the answer "The speed of light is approximately 299,792,458 meters per second" to the device via the internet.

[1101] Input: Answer data obtained from a generative AI model

[1102] Output: Answer data sent to the device

[1103] Step 6:

[1104] The device displays the received answer to the user on the device's screen. The device displays the text "The speed of light is approximately 299,792,458 meters per second" on the screen, and the user confirms it.

[1105] Input: Answer data sent to the terminal

[1106] Output: Answer data displayed on the screen

[1107] In this way, users can get fast and accurate answers in real time.

[1108] (Application example 3)

[1109] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1110] In traditional Q&A sessions at educational settings and events, it has been difficult for teachers and moderators to provide quick and detailed answers to questions from participants. Furthermore, when real-time answers are required, limitations on human resources have become an issue. This has led to a decline in participant satisfaction and understanding.

[1111] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1112] In this invention, the server includes generative AI means, communication application means, means for providing answers to questions from users, means for teachers to obtain detailed answers to questions from students in educational settings, and means for generating answers in real time to questions from participants in Q&A sessions at events. This makes it possible to provide quick and detailed answers in educational settings and events, thereby improving participant satisfaction and understanding.

[1113] "Generative AI methods" refers to artificial intelligence technology that automatically generates answers to questions posed by users.

[1114] "Communication application means" refers to software for sending and receiving Q&As generated by generative AI means.

[1115] "Means for providing answers to questions from users" refers to a function for providing answers to questions from users through a communication application means.

[1116] "A means for teachers to obtain detailed answers to questions from students in educational settings" refers to a function that allows teachers to input questions from students and obtain detailed answers using generative AI means.

[1117] "A means for generating answers in real time to questions from participants in Q&A sessions at events" refers to a function that receives questions from participants in real time at an event and instantly generates answers using generative AI means.

[1118] In order to practice this invention, it is necessary to build a system that includes generative AI means, communication application means, means for providing answers to questions from users, means for teachers to obtain detailed answers to questions from students in educational settings, and means for generating answers in real time to questions from participants in Q&A sessions at events.

[1119] System configuration

[1120] 1. Generative AI means

[1121] The server uses generative AI models such as OpenAI's GPT-3 as a generative AI method, which allows it to automatically generate detailed answers to user questions.

[1122] 2. Communication Application Means

[1123] The server uses a smartphone application as a communication application means, which provides an interface for sending and receiving the Q&A generated by the generative AI means.

[1124] 3. Means of providing answers to user questions

[1125] The server receives a question from a user through the communication application means, generates an answer using the generative AI means, and provides the answer to the user again through the communication application means.

[1126] 4. A way for teachers to get detailed answers to student questions in educational settings

[1127] Teachers can use a smartphone application to input questions from students and get detailed answers using generative AI methods, thereby improving the quality of education.

[1128] 5. A way to generate real-time answers to attendee questions during event Q&A sessions

[1129] Event hosts and organizers can use a smartphone application to receive questions from attendees in real time and use generative AI tools to instantly generate answers and provide them to attendees.

[1130] Program processing explanation

[1131] The server uses the OpenAI API to access a generative AI model (GPT-3). It works as follows:

[1132] 1. The server imports the openai library and sets the API key.

[1133] 2. The server receives the question from the user and generates an answer using generative AI means.

[1134] 3. The server provides the generated answer to the user through a communication application means.

[1135] Specific examples

[1136] For example, if a teacher receives a question from a student such as "Please explain the process of photosynthesis," the following prompt sentence can be input into the generative AI model:

[1137] Prompt Sentence Examples

[1138] Explain the process of photosynthesis

[1139] The generative AI model generates detailed answers such as, "Photosynthesis is the process by which plants use light energy to produce glucose and oxygen from carbon dioxide and water. Chlorophyll, primarily found in leaves, absorbs light and converts it into chemical energy." These answers are provided to teachers via communication applications.

[1140] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1141] Step 1:

[1142] The user inputs a question using a device (smartphone application).

[1143] Input: User question (e.g., "Please explain the process of photosynthesis.")

[1144] Output: User question data

[1145] Specific operation: The user enters a question into the application's input field and presses the submit button.

[1146] Step 2:

[1147] The terminal transmits the user's question data to the server.

[1148] Input: User question data

[1149] Output: The query data sent to the server

[1150] Specific operation: The terminal sends the query data to the server via the Internet.

[1151] Step 3:

[1152] The server receives the question data and passes it to the generative AI means.

[1153] Input: Query data sent to the server

[1154] Output: Question data passed to the generative AI method

[1155] Specific operation: The server analyzes the received question data and passes it to the generative AI means (OpenAI's API).

[1156] Step 4:

[1157] A generative AI tool generates answers based on the question data.

[1158] Input: Question data passed to the generative AI method

[1159] Output: Generated response data

[1160] Specific operation: The generative AI method uses the question data as a prompt and generates an answer using an AI model (GPT-3).

[1161] Step 5:

[1162] The server receives the generated response data and transmits it to the terminal.

[1163] Input: Generated response data

[1164] Output: Response data sent to the device

[1165] Specific operation: The server sends the answer data received from the generative AI means to the terminal.

[1166] Step 6:

[1167] The terminal displays the answer data received from the server to the user.

[1168] Input: Answer data sent to the terminal

[1169] Output: Answer data displayed to the user

[1170] Specific operation: The terminal displays the received response data on the screen and provides it to the user.

[1171] Through the above processing steps, a user can input a question and obtain a detailed answer using generative AI means.

[1172] 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.

[1173] "Example 1"

[1174] One embodiment of the present invention is a system that incorporates an emotion engine that recognizes user emotions. This system includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the Q&As generated by the generative AI means, and a means for providing answers to questions from users via the messenger app means. Furthermore, an emotion engine that recognizes user emotions is incorporated. This emotion engine recognizes emotions from the user's facial expressions, tone of voice, message context, etc., and provides this information to the generative AI means. The generative AI means generates answers to user questions based on this emotion information. For example, if the user feels angry, the generative AI means will generate more polite answers.

[1175] "Example 2"

[1176] Another embodiment of the present invention is a system in which an emotion engine tracks changes in a user's emotions and a generative AI means adjusts responses in response to those changes. In this system, the emotion engine tracks changes in a user's emotions in real time and provides that information to the generative AI means. The generative AI means adjusts responses based on this information about changes in emotion. For example, if a user is initially happy but gradually begins to show signs of dissatisfaction, the generative AI means captures that change and adjusts the tone and content of the responses.

[1177] "Example 3"

[1178] One embodiment of the present invention is a system that incorporates an emotion engine that recognizes user emotions. This system includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the Q&As generated by the generative AI means, and a means for providing answers to questions from users via the messenger app means. Furthermore, an emotion engine that recognizes user emotions is incorporated. This emotion engine recognizes emotions from the user's facial expressions, tone of voice, message context, etc., and provides this information to the generative AI means. The generative AI means generates answers to user questions based on this emotion information. For example, if the user feels angry, the generative AI means will generate more polite answers.

[1179] The processing flow of each embodiment will be described below.

[1180] "Example 1"

[1181] Step 1: The user sends a question via a messenger app.

[1182] Step 2: The emotion engine recognizes emotions from the user's facial expressions, tone of voice, and message context.

[1183] Step 3: The emotion engine provides the recognized emotion information to the generative AI means.

[1184] Step 4: The generative AI method generates an answer to the user's question based on the emotional information.

[1185] Step 5: The generative AI method sends the generated answer to the user via a messenger app method.

[1186] "Example 2"

[1187] Step 1: The user sends a question via a messenger app.

[1188] Step 2: The emotion engine tracks changes in the user's emotions in real time. Step 3: The emotion engine provides the tracked emotion change information to the generative AI means.

[1189] Step 4: The generative AI tool adjusts the response based on the emotional change information.

[1190] Step 5: The generative AI method sends the adjusted response to the user via the messenger app method.

[1191] Example 1

[1192] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1193] Conventional Q&A systems generate answers without considering the user's feelings, which can lead to low user satisfaction. They also face the problem of being unable to respond to user questions quickly due to the difficulty of generating answers in real time. Furthermore, they sometimes fail to provide detailed information about specific products or topics, which can make it difficult to meet user needs.

[1194] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1195] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger application means for sending and receiving the Q&As generated by the generative AI means, an emotion engine means for recognizing the user's emotions, and a generative AI means for adjusting answers based on the emotion information provided by the emotion engine means. This makes it possible to provide detailed Q&As in real time that take the user's emotions into consideration.

[1196] "Generative AI methods" refers to artificial intelligence techniques for generating detailed Q&A about specific products or topics.

[1197] "Messenger app means" refers to application software for sending and receiving Q&As generated by generative AI means and providing answers to questions from users.

[1198] "Emotion engine means" refers to technology that recognizes the user's emotions and provides that information to generative AI means.

[1199] "Emotional information" refers to data regarding emotions recognized by the emotion engine means from the user's facial expression, tone of voice, message context, etc.

[1200] "Real-time" refers to generating and providing answers to user questions instantly.

[1201] "In-depth Q&A" refers to in-depth questions and answers about a specific product or topic.

[1202] The present invention is a system that combines a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the generated Q&As, and an emotion engine means for recognizing the user's emotions.

[1203] The server hosts a generative AI model that generates answers to user questions in real time. The generative AI model uses natural language processing techniques to receive user questions and generate appropriate answers.

[1204] The device (user's smartphone or PC) sends the user's question to the server through a messenger app, such as WhatsApp or Slack, and receives the generated answer.

[1205] The emotion engine recognizes emotions from the user's facial expressions, tone of voice, and message context. For example, it can use the emotion recognition API from Microsoft's Azure Cognitive Services. The emotion engine provides the recognized emotion information to the generative AI model.

[1206] The generative AI model generates answers to user questions based on the emotional information provided by the emotion engine. For example, if the emotion engine recognizes that the user is angry, the generative AI model will generate a more polite answer.

[1207] As a concrete example, consider a case where a user asks, "How do I return this product?" If the emotion engine recognizes anger in the user's message, the generative AI model will generate a polite response such as, "We're sorry. We'll explain the return process in detail."

[1208] Example prompt sentence:

[1209] User: How do I return this product?

[1210] Generative AI model: If the emotion engine recognizes that the user is angry, generate a polite response.

[1211] This system makes it possible to provide detailed Q&A in real time, taking into account the user's emotions.

[1212] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1213] Step 1:

[1214] A user types a question into a messenger app.

[1215] Input: Users enter text questions about a particular product or topic.

[1216] What happens: A user types "How do I return this product?" into a messenger app.

[1217] Step 2:

[1218] The terminal sends a question to the server.

[1219] Input: The question text entered by the user.

[1220] Output: The question data sent to the server.

[1221] Specific operation: The device sends the user's question to the server via the messenger app.

[1222] Step 3:

[1223] The server passes the question to the generative AI model.

[1224] Input: Question data sent from the terminal.

[1225] Output: Question data passed to the generative AI model.

[1226] Specific operation: The server passes the received question to the generative AI model.

[1227] Step 4:

[1228] A generative AI model generates the answer.

[1229] Input: The query data passed by the server.

[1230] Output: The initial answer text.

[1231] How it works: The generative AI model generates an initial response such as, "We will provide detailed instructions on how to return the item."

[1232] Step 5:

[1233] The emotion engine recognizes the user's emotions.

[1234] Input: User messages, facial expressions, tone of voice, etc.

[1235] Output: User's emotional information.

[1236] Specific behavior: The emotion engine recognizes anger from the user's message.

[1237] Step 6:

[1238] A generative AI model takes emotional information into account and adjusts the answer.

[1239] Input: Initial answer text, user sentiment information.

[1240] Output: The adjusted answer text.

[1241] Specific operation: The generative AI model uses emotional information to generate a polite response such as, "We're sorry. We'll explain in detail how to return the product."

[1242] Step 7:

[1243] The server sends the final answer to the device.

[1244] Input: The adjusted answer text.

[1245] Output: The final answer data sent to the device.

[1246] Specific operation: The server sends the final answer from the generative AI model to the device.

[1247] Step 8:

[1248] The terminal displays the answer to the user.

[1249] Input: The final answer data sent from the server.

[1250] Output: The answer text that is displayed to the user.

[1251] Specific behavior: The device will display the final response to the user through the messenger app.

[1252] (Application example 1)

[1253] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1254] Conventional customer support systems provide uniform answers without considering the user's emotions, which leads to a decline in user satisfaction. It is also difficult to respond in real time, so users need to provide prompt answers to their questions. Furthermore, because they are unable to respond appropriately to the user's emotions, there is an issue of a decline in the quality of support, especially for users with negative emotions such as anger or confusion.

[1255] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes: generative AI means for generating detailed Q&As about specific products or themes; messenger application means for sending and receiving the Q&As generated by the generative AI means; means for providing answers to questions from users via the messenger application means; emotion engine means for recognizing the user's emotions; means for the emotion engine means to recognize the user's emotions from the user's facial expressions, tone of voice, and message context and provide this information to the generative AI means; and means for the generative AI means to generate answers to questions from users based on the emotion information. This makes it possible to provide appropriate answers in real time that correspond to the user's emotions.

[1256] "Generative AI methods" refers to artificial intelligence techniques that generate detailed Q&A about specific products or topics.

[1257] "Messenger App Means" refers to a communication application for sending and receiving Q&As generated by Generative AI Means.

[1258] "Emotion engine means" refers to technology for recognizing emotions from a user's facial expressions, tone of voice, and message context.

[1259] "Means for providing answers to user questions" refers to technology for providing answers to user questions through messenger app means.

[1260] "Emotion information" refers to data relating to the user's emotions recognized by the emotion engine means.

[1261] "Generating in real time" refers to generating answers instantly to questions from users.

[1262] "Customer support" refers to assistance activities to address user questions or issues regarding products or services.

[1263] A system for implementing this invention includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the generated Q&As, and an emotion engine means for recognizing user emotions. Specific embodiments of this system are described below.

[1264] System Configuration

[1265] 1. Hardware:

[1266] Device: Smartphone or tablet

[1267] Sensors: Camera and microphone (to recognize your facial expressions and tone of voice)

[1268] 2. Software:

[1269] Generative AI models: We will use OpenAI GPT-4 as an example.

[1270] Emotion recognition engine: As an example, we will use the Microsoft Azure Emotion API.

[1271] Messenger app: For example, using the Twilio API.

[1272] Data processing and calculation

[1273] 1. Get user's question:

[1274] The user's question is obtained as text data through the device's messenger app.

[1275] 2. Emotion recognition:

[1276] The user's facial expressions and tone of voice are transmitted to the emotion recognition engine means via the device's camera and microphone.

[1277] The emotion recognition engine means analyzes the user's emotions and provides the results to the generative AI means.

[1278] 3. Answer generation:

[1279] A generative AI tool takes emotional information into account and generates answers to user questions in real time.

[1280] 4. Submit your response:

[1281] The generated answer is sent to the user via a messenger app.

[1282] Specific examples

[1283] Example 1: When the user is angry

[1284] If a user asks, "My product hasn't arrived yet, what's going on?" and the emotion recognition engine means recognizes that the user is angry, the generative AI means will generate an answer like the following:

[1285] Example answer:

[1286] "We apologize for the inconvenience. We are currently checking the delivery status. Please wait a moment."

[1287] Example 2: When a user is having trouble

[1288] If a user asks, "I don't know how to use this product, what should I do?" and the emotion recognition engine means recognizes that the user is having trouble, the generative AI means will generate an answer like the following.

[1289] Example answer:

[1290] "Don't worry, here's a link to a video on how to use it. Let me know if you have any other questions."

[1291] Prompt Sentence Examples

[1292] An example of a prompt sentence to input to the generative AI model is as follows:

[1293] Prompt statement:

[1294] "If a user is upset, generate a polite response to the following question: Question: 'My item hasn't arrived, what's going on?'"

[1295] In this way, an emotion-responsive customer support system can provide a better customer experience by responding appropriately to the user's emotions.

[1296] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1297] Step 1:

[1298] A user inputs a question through a messenger app on the device. The input question is acquired as text data. The input data is the user's question text, and the output data is the question in text format.

[1299] Step 2:

[1300] The system captures the user's facial expressions and tone of voice in real time using the device's camera and microphone. The input data are the user's facial images and voice data, and the output data is multimedia information including these data.

[1301] Step 3:

[1302] The facial expression images and voice data captured by the terminal are sent to the emotion recognition engine means. The emotion recognition engine means analyzes these data and recognizes the user's emotion. The input data is multimedia information, and the output data is the user's emotion information.

[1303] Step 4:

[1304] The emotion recognition engine means provides the recognized emotion information to the generative AI means. The input data is the user's emotion information, and the output data is a prompt sentence containing the emotion information.

[1305] Step 5:

[1306] The generative AI method generates answers to user questions in real time, taking into account emotional information. The input data are a prompt containing emotional information and the user's question text, and the output data is the generated answer text.

[1307] Step 6:

[1308] The generated answer text is sent to the user through a messenger application means of the terminal, and the input data is the generated answer text, and the output data is the answer displayed to the user.

[1309] Step 7:

[1310] The user receives the answer and enters a follow-up question if necessary, and the process repeats again from step 1. The input data is the user's follow-up question text, and the output data is the new question text.

[1311] In this way, it is possible to provide an appropriate response in real time according to the user's feelings.

[1312] Example 2

[1313] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1314] In traditional business negotiations and meetings, it can be difficult for users to respond quickly and appropriately to customer questions. Furthermore, responses cannot be adjusted according to changes in the user's emotions, which can lead to lower customer satisfaction. This increases the risk of missed business opportunities.

[1315] 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.

[1316] In this invention, the server includes generative AI means, communication means, and emotion engine means, which allow users to receive appropriate answers to customer questions in real time and adjust the answers according to changes in the user's emotions.

[1317] "Generative AI methods" refers to artificial intelligence technology that generates appropriate answers to questions from users.

[1318] "Communication means" refers to the technology for sending and receiving data between the generative AI means and the user's device.

[1319] "Emotion engine means" refers to technology that tracks user emotions in real time and collects that data.

[1320] "Means for providing answers" refers to the technology for presenting the answers generated by the generative AI means to the user.

[1321] "Emotional Data" refers to information regarding a user's emotional state collected by emotion engine means.

[1322] "Means for adjusting responses" refers to technology that changes the tone and content of responses generated by generative AI means based on emotional data.

[1323] This invention is a system that enables a user to quickly and appropriately answer questions from customers in situations such as business negotiations and meetings. This system includes generative AI means, communication means, and emotion engine means.

[1324] Hardware and software used

[1325] Hardware: Servers, devices (PCs, tablets, smartphones)

[1326] Software: Generative AI models (e.g., general-purpose natural language processing models), emotion engines (e.g., emotion recognition software)

[1327] System configuration

[1328] 1. The server hosts the generative AI means and the emotion engine means. The server receives questions from users, passes them to the generative AI means to generate answers, and receives emotion data from the emotion engine means and provides it to the generative AI means.

[1329] 2. The terminal is a device used by the user to input questions in real time during a business meeting with a customer. The terminal sends the questions to the server, receives the answers from the server, and displays them to the user.

[1330] 3. The user inputs questions from customers into the device during business negotiations or meetings and receives answers from the generative AI means.

[1331] Details of data processing and calculation

[1332] The generative AI means generates appropriate answers to questions from users. For example, if a user asks, "How long is the warranty period for this product?", the generative AI means generates the answer, "The warranty period for this product is two years."

[1333] The communication means sends and receives data between the device and the server. Questions entered by the user into the device are sent to the server via the communication means. The server receives the answer from the generative AI means and sends it back to the device via the communication means.

[1334] The emotion engine means tracks the user's emotions in real time and collects the data, for example, when the user expresses dissatisfaction, the information is collected and sent to the server.

[1335] The response adjustment means changes the tone and content of the response generated by the generative AI means based on the emotional data. For example, if the user expresses dissatisfaction, the generative AI means may provide additional information such as, "Furthermore, if any problems occur during the warranty period, we will repair the product free of charge."

[1336] Specific examples

[1337] Sales scenario: A salesperson is explaining a new product when a customer asks, "How long is the warranty on this product?"

[1338] The user enters this question into the terminal.

[1339] The terminal sends a query to the server.

[1340] The server passes the question to a generative AI means to generate an answer.

[1341] The generative AI means generates an answer, "The warranty period for this product is two years," and returns it to the server.

[1342] The server sends the answer to the terminal, which displays it to the user.

[1343] The emotion engine means tracks changes in the user's emotions and collects information when the user is dissatisfied.

[1344] The server provides emotional data to the generative AI means to adjust the tone and content of the response.

[1345] The generative AI means provides the additional information, "Furthermore, if any problems arise during the warranty period, we will repair it free of charge."

[1346] The server sends the adjusted answer to the terminal, which displays it to the user.

[1347] Prompt Sentence Examples

[1348] Input prompt: "How long is the warranty on this product?"

[1349] Generated answer: "This product is covered by a two-year warranty. What's more, if a problem occurs during the warranty period, we'll repair it free of charge."

[1350] This system allows users to respond to customer questions quickly and appropriately, preventing missed business opportunities and improving customer satisfaction.

[1351] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1352] Step 1:

[1353] The user inputs a question into the terminal.

[1354] Input: A question the user receives from a customer (e.g., "How long is the warranty on this product?")

[1355] Specific actions: The user types a question into the input field on the terminal and presses the send button.

[1356] Output: Question data entered on the terminal

[1357] Step 2:

[1358] The terminal sends a question to the server.

[1359] Input: Question data entered into the terminal

[1360] Specific operation: The device generates an HTTP request and sends the query data to the server.

[1361] Output: Question data sent to the server

[1362] Step 3:

[1363] The server passes the question to the generative AI means.

[1364] Input: Question data sent to the server

[1365] Specific operation: The server analyzes the question data and makes an API call to pass it to the generative AI means.

[1366] Output: Question data passed to the generative AI method

[1367] Step 4:

[1368] A generative AI means generates answers to questions.

[1369] Input: Question data passed to the generative AI method

[1370] How it works: The generative AI means analyzes the question data and generates an appropriate answer (e.g., "This product has a two-year warranty").

[1371] Output: Generated response data

[1372] Step 5:

[1373] The server sends the generated response to the terminal.

[1374] Input: Generated response data

[1375] Specific operation: The server receives the generated response data and sends it to the terminal as an HTTP response.

[1376] Output: Answer data sent to the device

[1377] Step 6:

[1378] The terminal displays the answer to the user.

[1379] Input: Answer data sent to the terminal

[1380] Specific operation: The device displays the received answer data on the screen. The user can check the answer on the device screen.

[1381] Output: The answer displayed to the user

[1382] Step 7:

[1383] An emotion engine means tracks the emotions of the user.

[1384] Input: Emotional data such as the user's facial expressions and tone of voice

[1385] Specific operation: The emotion engine means analyzes the user's facial expressions and tone of voice in real time and tracks changes in emotions.

[1386] Output: Tracked emotion data

[1387] Step 8:

[1388] The server provides emotion data to the generative AI means.

[1389] Input: Tracked emotion data

[1390] Specific operation: The server makes an API call to provide the emotion data received from the emotion engine means to the generative AI means.

[1391] Output: Emotion data provided to the generative AI means

[1392] Step 9:

[1393] A generative AI tool adjusts the answer based on the emotional data.

[1394] Input: Emotion data provided to the generative AI method

[1395] What it does: The generative AI method analyzes the emotional data and adjusts the tone and content of the response (e.g., "What's more, if the issue occurs during the warranty period, we'll repair it free of charge").

[1396] Output: Adjusted response data

[1397] Step 10:

[1398] The server sends the adjusted response to the terminal.

[1399] Input: Adjusted response data

[1400] Specific operation: The server receives the adjusted response data and sends it to the terminal as an HTTP response.

[1401] Output: Adjusted response data sent to the device

[1402] Step 11:

[1403] The terminal displays the adjusted answer to the user.

[1404] Input: Adjusted response data sent to the device

[1405] Specific operation: The device displays the received adjusted answer data on the screen. The user checks the adjusted answer on the device screen.

[1406] Output: The adjusted answer displayed to the user

[1407] (Application example 2)

[1408] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1409] In traditional sales negotiations and customer service in brick-and-mortar stores, salespeople and store clerks are required to respond to customer questions quickly and accurately, but it is difficult to provide appropriate answers to all questions immediately. It is also difficult to adjust responses according to changes in the customer's emotions, making it difficult to improve customer satisfaction.

[1410] 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.

[1411] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger application means for sending and receiving the Q&As generated by the generative AI means, a means for providing answers to questions from users via the messenger application means, an emotion recognition means for tracking user emotions, a means for adjusting the answers of the generative AI means based on the emotion information tracked by the emotion recognition means, and a display means for displaying the answers. This makes it possible to provide quick and accurate answers to customer questions and to adjust responses according to changes in the customer's emotions.

[1412] "Generative AI methods" are artificial intelligence techniques that generate detailed Q&A about specific products or topics.

[1413] The "messenger app means" is an application for sending and receiving Q&A generated by the generative AI means.

[1414] "Means for providing answers to questions from users" refers to a function that provides answers generated by generative AI means to questions from users through messenger app means.

[1415] "Emotion recognition means" is a technology for tracking a user's emotions.

[1416] The "means for adjusting the response of the generative AI means based on emotional information" is a function for adjusting the response generated by the generative AI means based on emotional information tracked by the emotion recognition means.

[1417] "Display means" refers to devices or technologies used to display the answers generated by the generative AI means to the user.

[1418] As an embodiment of the present invention, a customer service system for a brick-and-mortar store will be described as an example. This system includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the generated Q&As, a means for providing answers to questions from users, an emotion recognition means for tracking user emotions, a means for adjusting the answers of the generative AI means based on the emotion information, and a display means for displaying the answers.

[1419] Hardware and software used

[1420] 1. Hardware:

[1421] Smart glasses (display means)

[1422] Camera (built into smart glasses, for emotion recognition)

[1423] Microphone (for voice input)

[1424] 2. Software:

[1425] OpenAI API (generating AI means)

[1426] EmotionRecognizer (emotion recognition means)

[1427] OpenCV (camera image processing)

[1428] Data processing and calculation

[1429] The server captures the customer's face from the camera footage and tracks their emotions using an emotion recognition model. The user's (customer's) question is obtained through voice input. The answer generated by the generative AI means is adjusted based on the emotional information tracked by the emotion recognition means. For example, the tone and content of the generated answer can be adjusted to be different depending on whether the customer is happy or angry. The generated answer is displayed on the smart glasses.

[1430] Specific examples

[1431] If a customer asks, "How do I use this product?" and the emotion recognition model determines that the customer is happy, the prompt might look like this:

[1432] Prompt Sentence Examples

[1433] Once the customer is happy, ask: How do I use this product?

[1434] This prompt is sent to a generative AI, and the resulting answer is displayed on the store associate's smart glasses, allowing them to quickly provide an appropriate response based on the customer's emotions.

[1435] This system will enable the company to provide quick and accurate answers to customer questions and adjust responses according to changes in customer emotions, which is expected to improve customer satisfaction.

[1436] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1437] Step 1:

[1438] The server captures the customer's face through a camera. The input is the camera image, and the output is the captured customer's face image. This face image is sent to the emotion recognition means.

[1439] Step 2:

[1440] The server tracks the customer's emotions from the captured facial images using an emotion recognition means. The input is the facial image obtained in step 1, and the output is the customer's emotional information (e.g., joy, anger, sadness, etc.). This emotional information is sent to the generative AI means.

[1441] Step 3:

[1442] The user (customer) speaks their question into the microphone. The input is the customer's voice, and the output is voice data. This voice data is sent to the voice recognition system.

[1443] Step 4:

[1444] The server converts the voice data into text using a speech recognition system. The input is the voice data obtained in step 3, and the output is a text question. This text is sent to the generative AI means.

[1445] Step 5:

[1446] The server generates a prompt sentence based on the emotional information and the text question. The input is the emotional information obtained in step 2 and the text question obtained in step 4, and the output is the prompt sentence. For example, the generated prompt sentence is, "Question when the customer is happy: How do you use this product?"

[1447] Step 6:

[1448] The server uses a generative AI means to generate an answer based on the prompt. The input is the prompt obtained in step 5, and the output is the generated answer. This answer is sent to the display means.

[1449] Step 7:

[1450] The terminal (smart glasses) displays the generated answer. The input is the answer obtained in step 6, and the output is the text displayed on the smart glasses display. This allows the user (store clerk) to provide an appropriate answer to the customer.

[1451] Example 3

[1452] Next, a description will be given of Example 3 of Form Example 3. 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."

[1453] Conventional generative AI systems generate answers without considering the user's emotions, which can lead to lower user satisfaction. It is also difficult to provide appropriate answers based on the user's emotions, making it necessary to provide effective responses, especially when used in educational and event settings. This has made it difficult to improve user understanding and satisfaction.

[1454] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1455] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger application means for sending and receiving the Q&As generated by the generative AI means, a means for providing answers to questions from users via the messenger application means, an emotion engine means for recognizing user emotions, and a means for generating answers based on emotion information obtained from the emotion engine means. This makes it possible to provide appropriate answers in real time according to the user's emotions.

[1456] "Generative AI methods" refers to artificial intelligence techniques for generating detailed Q&A about specific products or topics.

[1457] "Messenger app means" refers to application software for sending and receiving Q&As generated by generative AI means.

[1458] "Means for providing answers to questions from users" refers to the function for providing answers to questions from users through messenger app means.

[1459] "Emotion engine means" refers to technology for recognizing emotions from a user's facial expressions, tone of voice, message context, etc.

[1460] The "means for generating an answer based on emotional information" refers to a function for generating an appropriate answer to a question from a user based on emotional information obtained from the emotion engine means.

[1461] This invention relates to a system for generating detailed Q&A about a specific product or topic. This system is composed of a generative AI means, a messenger app means, and an emotion engine means for recognizing user emotions.

[1462] The server uses a generative AI model, such as OpenAI's GPT-4 or a similar model, as a generative AI means. This generative AI means is designed to generate detailed answers to questions from users. The generated answers are sent to the user via a messenger app means. The messenger app means can be a common messaging platform such as Slack, Microsoft Teams, or WhatsApp.

[1463] Furthermore, the server uses, for example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API as an emotion engine means. This emotion engine means recognizes emotions from the user's facial expressions, tone of voice, message context, etc., and provides this information to the generative AI means. The generative AI means generates appropriate answers to questions from the user based on this emotion information. For example, if the emotion engine means recognizes that the user is angry, the generative AI means generates answers in a more polite and calm tone.

[1464] As a concrete example, consider the case where a teacher receives a question from a student, "I don't understand this math problem." The teacher opens the Slack app and types, "I don't understand this math problem." The teacher's device sends the typed question to a server via Slack's API. The server uses Microsoft Azure's Emotion API to recognize that the teacher is confused from the context of the question. The server uses OpenAI's GPT-4 to generate a careful and detailed solution to the math problem for the confused teacher. The server sends the generated answer to the teacher's device via Slack's API. The teacher's device displays an answer on the Slack app, such as, "Here's how to solve this math problem..."

[1465] An example of a prompt sentence is, "If a student is confused, please explain in an easy-to-understand way how to solve the math problem." In this way, the user can quickly obtain a detailed answer to their question. The flow of the specific process in Example 3 will be described with reference to FIG. 21.

[1466] Step 1:

[1467] The user enters a question.

[1468] The user uses the messenger app to input a question. For example, a teacher might type, "I don't understand this math problem." The input question is saved on the user's device.

[1469] Step 2:

[1470] The terminal sends a question to the server.

[1471] The device sends the entered question to the server through the API of the messenger app. For example, the Slack API is used to send the question to the server. The input is the user's question, and the output is the question sent to the server.

[1472] Step 3:

[1473] The server analyzes the user's emotions using an emotion engine.

[1474] The server passes the received question to the emotion engine, which analyzes the user's facial expression, tone of voice, and message context to recognize the user's emotion. For example, it uses Microsoft Azure's Emotion API to recognize that the user is confused. The input is the user's question, and the output is the user's emotional information.

[1475] Step 4:

[1476] The server generates answers using a generative AI model.

[1477] The server generates answers using a generative AI model based on the emotional information obtained from the emotion engine. For example, it uses OpenAI's GPT-4 to generate polite and detailed answers for confused users. The input is the user's question and emotional information, and the output is the generated answer.

[1478] Step 5:

[1479] The server sends the generated response to the terminal.

[1480] The server sends the generated answer to the device through the API of the messenger app. For example, it sends the answer using the Slack API. The input is the generated answer, and the output is sending the answer to the device.

[1481] Step 6:

[1482] The terminal displays the answer to the user.

[1483] The device displays the response received from the server to the user, who can then check the response on the messenger app. The input is the response from the server, and the output is the display of the response to the user.

[1484] (Application example 3)

[1485] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1486] Conventional customer support systems provide uniform answers without considering the user's feelings, resulting in low user satisfaction. Furthermore, in physical stores, it is difficult to provide quick and appropriate answers to customers' questions, and responses are often insufficient, especially in situations where an emotional response is required. This can sometimes ruin the customer experience.

[1487] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1488] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger application means for sending and receiving the Q&As generated by the generative AI means, a means for providing answers to questions from users via the messenger application means, an emotion engine means for recognizing user emotions, a means for generating answers based on emotion information recognized by the emotion engine means, and a means installed in a customer support robot located in a physical store. This makes it possible to provide appropriate answers in real time according to the user's emotions, thereby improving customer satisfaction.

[1489] "Generative AI methods" refers to artificial intelligence techniques that generate detailed Q&A about specific products or topics.

[1490] "Messenger App Means" refers to an application for sending and receiving Q&As generated by Generative AI Means.

[1491] "Means of providing answers to questions from users" refers to the function of providing appropriate answers to questions from users through messenger app means.

[1492] "Emotion engine means" refers to technology for recognizing emotions from a user's facial expressions, tone of voice, message context, etc.

[1493] "Means for generating answers based on emotional information" refers to a function that enables the generative AI means to generate appropriate answers for the user based on the emotional information recognized by the emotion engine means.

[1494] "Means to be installed in customer support robots installed in physical stores" refers to a function that is installed in a robot installed in a physical store and that uses generative AI means to provide answers to questions from customers.

[1495] A system for carrying out this invention includes generative AI means for generating detailed Q&As about specific products or themes, messenger application means for sending and receiving Q&As generated by the generative AI means, means for providing answers to questions from users through the messenger application means, emotion engine means for recognizing user emotions, means for generating answers based on emotion information recognized by the emotion engine means, and means installed in a customer support robot installed in a physical store.

[1496] The server uses, for example, the Transformers library as the generative AI means. The generative AI means generates detailed answers to questions from users. The messenger app means is an application for sending and receiving the generated Q&A, and receives questions from users and sends them to the generative AI means. The means for providing answers to questions from users returns answers to users through the messenger app means.

[1497] The emotion engine means is a technology for recognizing emotions from the user's facial expressions, tone of voice, message context, etc., and uses the EmotionRecognition library, for example. The emotion information recognized by the emotion engine means is provided to the generative AI means, which generates an appropriate response according to the user's emotions.

[1498] A customer support robot installed in a physical store uses a camera to capture the user's facial expressions and transmits them to an emotion engine means. The customer support robot then uses generative AI means to generate answers to the user's questions in real time and provides them to the user.

[1499] As a concrete example, consider the case where a customer asks, "Tell me about this product." If the customer appears to be troubled, the emotion engine means will recognize this as "trouble" and input the following prompt sentence to the generative AI means:

[1500] "If a user is having trouble, please politely answer the following question: Tell me about this product."

[1501] The generative AI means uses this prompt to generate a more helpful and polite response, such as, "This product uses the latest technology and is extremely high-performance. It is also designed to be easy to use, so even first-time users can use it with confidence."

[1502] In this way, it becomes possible to provide appropriate answers in real time according to the user's emotions, thereby improving customer satisfaction.

[1503] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1504] Step 1:

[1505] A user types a question into a customer support robot.

[1506] Input: User question (e.g. "Tell me about this product")

[1507] Output: The user's question is sent to the customer support robot.

[1508] Specific operation: The user enters a question through the robot's interface and presses the send button.

[1509] Step 2:

[1510] The customer support robot uses a camera to capture the user's facial expressions.

[1511] Input: User's facial expression video

[1512] Output: Captured facial expression data

[1513] Specific operation: The robot's camera captures the user's face and acquires video data.

[1514] Step 3:

[1515] The server recognizes the user's emotions using an emotion engine means.

[1516] Input: Captured facial expression data

[1517] Output: Recognized emotion information (e.g., "I'm in trouble")

[1518] Specific operation: The server uses the EmotionRecognition library to analyze facial expression data and identify the user's emotions.

[1519] Step 4:

[1520] The server generates a prompt using generative AI means.

[1521] Input: User question, recognized emotion information

[1522] Output: Generated prompt (e.g., "If the user is having trouble, please politely answer the following question: Tell me about this product.")

[1523] Specific operation: The server creates a prompt sentence based on the emotional information and inputs it into the generative AI model.

[1524] Step 5:

[1525] The server uses generative AI tools to generate answers to users' questions.

[1526] Input: Generated prompt text

[1527] Output: Generated answer (e.g., "This product uses the latest technology and is extremely high-performance. It is also designed to be easy to use, so even first-time users can use it with confidence.")

[1528] What happens: The server uses the Transformers library to generate an answer based on the prompt.

[1529] Step 6:

[1530] The customer support robot provides the generated answer to the user.

[1531] Input: Generated Answer

[1532] Output: The answer provided to the user

[1533] Specific behavior: The robot will respond to the user via voice or text.

[1534] 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.

[1535] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1536] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1537] 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.

[1538] [Third embodiment]

[1539] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1540] 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.

[1541] 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).

[1542] 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.

[1543] 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.

[1544] 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).

[1545] 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.

[1546] 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.

[1547] 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.

[1548] 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.

[1549] 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.

[1550] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1551] "Example 1"

[1552] One embodiment of the present invention is a system that uses a generative AI that generates detailed Q&As about specific products or themes, and a messenger app that sends and receives the Q&As generated by the generative AI. The generative AI generates answers to questions from users in real time. The messenger app sends the Q&As generated by the generative AI to users and sends questions from users to the generative AI.

[1553] "Example 2"

[1554] As a specific example, consider a sales negotiation scenario. Salespeople can receive answers to customer questions in real time through generative AI. This allows salespeople to respond to customer questions quickly, avoid missing sales opportunities, and improve customer satisfaction.

[1555] "Example 3"

[1556] The present invention is also useful in educational settings. Teachers can use generative AI to obtain detailed answers to questions from students, helping them improve their students' understanding. Furthermore, using the system of the present invention in Q&A sessions at events can also improve participant satisfaction.

[1557] The processing flow of each embodiment will be described below.

[1558] "Example 1"

[1559] Step 1: User types in a question through the messenger app.

[1560] Step 2: The messenger app sends the user's question to the generative AI.

[1561] Step 3: The generative AI generates answers to the user's questions in real time. Step 4: The messenger app sends the answers generated by the generative AI to the user.

[1562] "Example 2"

[1563] Step 1: A salesperson types a customer's question into a messenger app.

[1564] Step 2: The messenger app sends the salesperson's question to the generative AI.

[1565] Step 3: Generative AI generates answers to salespeople's questions in real time

[1566] .

[1567] Step 4: The messenger app sends the answer generated by the generative AI to the salesperson, who then responds to the customer based on the answer.

[1568] "Example 3"

[1569] Step 1: The teacher types the student's question into the messenger app.

[1570] Step 2: The messenger app sends the teacher's question to the generative AI.

[1571] Step 3: The generative AI generates answers to questions from the teacher in real time.

[1572] Step 4: The answer generated by the generative AI is sent to the teacher via a messaging app, who then responds to the student based on the answer.

[1573] Example 1

[1574] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1575] Conventional Q&A systems often had delays in responding to user questions, making it difficult to respond in real time. Providing detailed information on specific products or topics also required building and maintaining a massive database, which was costly. Furthermore, the interface for users to enter questions could be difficult to use, resulting in a poor user experience.

[1576] 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.

[1577] In this invention, the server includes a generation AI means for generating detailed Q&As about specific products or themes, a messenger application means for transmitting and receiving the Q&As generated by the generation AI means, a means for sending questions from users to the generation AI means through the messenger application means, and a means for sending answers generated by the generation AI means to users, thereby enabling users to receive detailed Q&As in real time.

[1578] A "generative AI tool" is a system that uses artificial intelligence technology to generate detailed Q&A about a specific product or topic.

[1579] The "messenger app means" is a communication application for sending questions from users and receiving answers from the generative AI means.

[1580] The "means for sending questions from users to generative AI means" is a function for sending questions entered by users through messenger app means to generative AI means.

[1581] "Means for sending an answer generated by a generative AI means to a user" is a function for sending an answer generated by a generative AI means to a user through a messenger app means.

[1582] A "prompt" is text containing a question from a user that is input to a generative AI means.

[1583] This invention is a system for generating detailed Q&A about a specific product or theme. The system includes a generative AI means, a messenger application means, a means for sending a question from a user to the generative AI means, and a means for sending an answer generated by the generative AI means to the user.

[1584] The server uses server hardware equipped with a high-performance GPU (e.g., a high-performance graphics processor) to run the generative AI means. Furthermore, the generative AI model employs an advanced generative AI model (e.g., a large-scale language model) that uses natural language processing technology. The generative AI means receives questions from users and generates appropriate answers to those questions in real time.

[1585] The device is a smartphone or PC with a messenger app installed that the user uses. This messenger app (e.g., a general communication application) sends questions from the user to the generative AI means and displays the answers from the generative AI means to the user.

[1586] Specifically, the data processing involves sending a question from the user to the server via a messenger app, where the generative AI analyzes the question and generates an appropriate answer, which is then sent back to the user via the messenger app.

[1587] For example, if a user asks, "What is the battery life like on my new smartphone?" the following happens:

[1588] 1. The user types a question using a messenger app.

[1589] 2. The messenger app sends the question to the server.

[1590] 3. The server uses generative AI methods to analyze the question and generate an appropriate answer.

[1591] 4. The generated answer (e.g., "The battery life of a new smartphone is typically around 24 hours. However, this may vary depending on usage.") is sent from the server to the messenger app.

[1592] 5. The Messenger app will display the generated answer to the user.

[1593] Example prompt sentence:

[1594] "What's the battery life like on my new smartphone?"

[1595] In this way, users can receive detailed Q&A in real time.

[1596] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1597] Step 1:

[1598] The user types a question through a messenger app.

[1599] Specifically, a user opens a messaging app installed on their smartphone or PC and types a question, for example, "What is the battery life of my new smartphone?"

[1600] Input: User question text

[1601] Output: Question text entered into the messenger app

[1602] Step 2:

[1603] The terminal sends a question to the server.

[1604] Specifically, the device sends the user's question to the server via the messenger app's API. The question is sent to the server in an appropriate format (e.g., JSON format).

[1605] Input: Question text entered into the messenger app

[1606] Output: Question text sent to the server

[1607] Step 3:

[1608] The server receives the question and inputs it as a prompt into the generative AI model.

[1609] Specifically, the server analyzes the received question and inputs it into the generative AI model as a prompt sentence, which is the user's question as is.

[1610] Input: Question text sent to the server

[1611] Output: The prompt sentence that is input to the generative AI model

[1612] Step 4:

[1613] A generative AI model generates answers to questions.

[1614] Specifically, the generative AI model generates an appropriate answer to the question based on the prompt sentence, for example, "The battery life of a new smartphone is usually about 24 hours. However, this may vary depending on usage."

[1615] Input: A prompt sentence entered into the generative AI model

[1616] Output: Answer text generated by the generative AI model

[1617] Step 5:

[1618] The server receives the generated response and sends it to the terminal.

[1619] Specifically, the server converts the answer received from the generative AI model back into an appropriate format (e.g., JSON format) and sends it to the terminal.

[1620] Input: Answer text generated by the generative AI model

[1621] Output: Answer text sent to the terminal

[1622] Step 6:

[1623] The terminal displays the answer to the user.

[1624] Specifically, the device receives the response from the server and displays it to the user via the messenger app. The user can then check the response on the chat screen of the messenger app.

[1625] Input: Answer text sent to the terminal

[1626] Output: Reply text displayed in the messenger app

[1627] (Application example 1)

[1628] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1629] On traditional online shopping sites, users would have to visit FAQ pages or contact customer support to get detailed information about products, which made it difficult to get a quick response. Furthermore, if users were unable to resolve their questions about a product, their desire to purchase would decrease, which could result in a decrease in sales. Furthermore, the burden on customer support would increase, making it difficult to operate efficiently.

[1630] 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.

[1631] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the Q&As generated by the generative AI means, a means for providing answers to questions from users through the messenger app means, an application means installed on a smartphone, and a means for users to input product-related questions through the application means, the generative AI means for generating answers to those questions in real time, and the means for providing the answers to users through the messenger app means. This allows users to quickly obtain detailed product information, increasing their desire to purchase. It also reduces the burden on customer support and enables more efficient operations.

[1632] "Generative AI methods" refers to artificial intelligence techniques for generating detailed Q&A about specific products or topics.

[1633] "Messenger App Means" refers to an application for sending and receiving Q&As generated by Generative AI Means.

[1634] "Means for providing answers to questions from users" refers to a function for providing users with answers generated by generative AI means in response to questions entered by users.

[1635] "Application means installed on a smartphone" refers to an application that runs on a smartphone and allows a user to input questions about a product.

[1636] "Means for inputting a question about a product, for the generative AI means to generate an answer to the question in real time, and for providing the answer to the user through the messenger app means" refers to a series of functions for a user to input a question about a product, for the generative AI means to generate an answer to the question in real time, and for providing the answer to the user through the messenger app means.

[1637] The following system configuration is used as an embodiment of the present invention.

[1638] The server includes a generative AI means for generating detailed Q&A about a specific product or topic, using a generative AI model such as OpenAI's GPT-3, and capable of generating answers in real time to user questions.

[1639] The terminal includes an application means installed on the smartphone. The application means provides an interface for the user to input a question about the product. When the user inputs a question, the question is transmitted to the server via a messenger application means.

[1640] The messenger app means is an application for sending and receiving Q&As generated by the generative AI means. For example, it is implemented as a web application using Flask. This messenger app means plays a role in sending questions from users to the generative AI means and returning generated answers to users.

[1641] Specifically, the process involves a user entering a question through a smartphone app, which is then sent to the server through a messenger app. The server's AI generator generates an answer to the question in real time and returns the answer to the user through the messenger app.

[1642] For example, if a user asks, "What is the battery life of this smartphone?", the generative AI means generates the answer, "This smartphone's battery life is approximately 10 hours under normal use." This answer is provided to the user via a messenger app means.

[1643] An example prompt sentence would be of the following format:

[1644] Q: What is the battery life of this phone?

[1645] A: This smartphone's battery life is approximately 10 hours under normal use.

[1646] In this way, users can quickly obtain detailed information about products, which increases their willingness to purchase. It also reduces the burden on customer support and enables more efficient operations.

[1647] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1648] Step 1:

[1649] A user starts the smartphone app and inputs a question about a product. The input question is transmitted to the messenger app means via the application means. The input data is the user's question, and the output data is the question transmitted to the messenger app means.

[1650] Step 2:

[1651] The messenger application means transmits a question received from a user to a server. The input data is the user's question, and the output data is the question to be transmitted to the server. Specifically, the messenger application means transmits the question data to the server using an HTTP request.

[1652] Step 3:

[1653] The server passes the received question to the generative AI means. The input data is the question received from the messenger app means, and the output data is the question passed to the generative AI means. Specifically, the server inputs the question data into the generative AI model.

[1654] Step 4:

[1655] The generative AI means generates answers to received questions in real time. The input data is the user's question, and the output data is the generated answer. Specifically, it uses a generative AI model (e.g., GPT-3) to generate a prompt sentence and generate an answer.

[1656] Step 5:

[1657] The server transmits the answer received from the generative AI means to the messenger application means. The input data is the generated answer, and the output data is the answer to be transmitted to the messenger application means. Specifically, the server transmits the answer data to the messenger application means using an HTTP response.

[1658] Step 6:

[1659] The messenger application means transmits the response received from the server to the smartphone application. The input data is the response received from the server, and the output data is the response sent to the smartphone application. Specifically, the application performs processing to display the response data within the application.

[1660] Step 7:

[1661] The user checks the answer generated by the generative AI means through the smartphone app. The input data is the answer received from the messenger app means, and the output data is the answer checked by the user. Specifically, the answer is displayed on the smartphone screen and the user views it.

[1662] Example 2

[1663] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1664] In traditional business negotiations and meetings, it can be difficult for salespeople and other participants to quickly and accurately answer questions from customers and other participants. This can lead to missed business opportunities and reduced customer satisfaction. Another issue is the lack of a way to instantly obtain appropriate answers in situations where real-time information provision is required.

[1665] 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.

[1666] In this invention, the server includes a means for a user to input a question, a means for the terminal to transmit the input to the server, a means for the server to transmit a prompt sentence to the generative AI model, a means for the generative AI model to generate an answer, a means for the server to transmit the answer to the terminal, and a means for the terminal to display the answer to the user, thereby enabling the user to quickly and accurately obtain answers to questions from customers and other participants.

[1667] A "user" is an entity that uses the system to enter questions and receive answers.

[1668] A "terminal" is a device through which a user inputs questions and communicates with the server, and includes laptops, tablets, etc.

[1669] The "server" is a computer system that receives questions from users, sends prompts to the generative AI model, and sends the generated answers to the terminal.

[1670] A "generative AI model" is an artificial intelligence model that generates appropriate answers based on prompt text, and examples include GPT-4.

[1671] A "prompt sentence" is a textual sentence that is converted to help the generative AI model properly understand the question.

[1672] The "means for inputting a question" is an interface that allows a user to input a question using a terminal.

[1673] The "means for transmitting input to a server" is a communication means by which the terminal transmits a question input by a user to a server.

[1674] The "means for sending a prompt sentence" is the means by which the server converts the user's question into a prompt sentence and sends it to the generative AI model.

[1675] The "means for generating an answer" refers to the means by which the generative AI model generates an answer based on the prompt sentence.

[1676] "Means for sending an answer to a terminal" refers to the means by which the server sends the answer obtained from the generative AI model to the terminal.

[1677] The "means for displaying the answer to the user" is an interface for displaying the answer received by the terminal from the server to the user.

[1678] This invention is a system that allows users to quickly and accurately obtain answers to questions from customers and other participants in business negotiations and meetings. The system allows users to input questions, generates answers in real time using a generative AI model, and provides the answers to users.

[1679] Hardware and software used

[1680] 1. Terminal

[1681] Use devices such as laptops and tablets.

[1682] Using a dedicated application or web browser, users enter questions and communicate with the server.

[1683] 2. Server

[1684] It uses a high-performance computer system to receive questions from users, send prompts to a generative AI model, and send the generated answers to the device.

[1685] Python, Node.js, etc. are used as server-side scripts.

[1686] 3. Generative AI Models

[1687] For example, GPT-4 is used as a generative AI model.

[1688] Generate appropriate answers based on the prompt.

[1689] Data processing and calculation

[1690] 1. The user enters a question

[1691] Users enter questions using the keyboard or touchscreen of their laptop or tablet.

[1692] Example: A salesperson types, "How long is the warranty on this product?"

[1693] 2. The device sends the input to the server

[1694] The terminal sends the entered question to the server as an HTTP request.

[1695] Software required: Dedicated application and web browser

[1696] 3. The server sends a prompt to the generative AI model

[1697] The server converts the received question into a prompt sentence suitable for the generative AI model and sends it to the generative AI model.

[1698] Example: A server-side script converts a prompt into a statement of the form "Generate an answer to the customer question: 'What is the warranty period for this product?'"

[1699] 4. Generative AI models generate answers

[1700] The generative AI model generates appropriate answers based on the prompt text.

[1701] Example: Generate the answer "This product has a one-year warranty."

[1702] 5. The server sends the answer to the device

[1703] The server sends the answer obtained from the generative AI model to the terminal as an HTTP response.

[1704] 6. The device displays the answer to the user

[1705] The terminal displays the answer received from the server on the screen and the user confirms it.

[1706] Software required: Dedicated application and web browser

[1707] Examples of specific examples and prompts

[1708] Specific examples

[1709] A salesperson is asked by a customer, "How long is the warranty on this product?"

[1710] The salesperson types into the terminal, "How long is the warranty on this product?"

[1711] The device sends the question to the server, which then sends the prompt to the generative AI model.

[1712] The generative AI model generates the answer, "This product has a one-year warranty."

[1713] The server sends the answer to the terminal, which displays it to the salesperson.

[1714] Prompt Sentence Examples

[1715] "Generate an answer to the customer question: 'How long is the warranty on this product?'"

[1716] The system allows users to get quick and accurate answers to questions from customers and other participants, increasing the success of business negotiations and meetings.

[1717] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1718] Step 1:

[1719] The user enters a question.

[1720] A user inputs a question using the keyboard or touch screen of a laptop or tablet. For example, a salesperson might input, "How long is the warranty period for this product?" The input data is a text question.

[1721] Step 2:

[1722] The device sends input to the server.

[1723] The device sends the question entered by the user to the server as an HTTP request. Specifically, a dedicated application or web browser sends the entered question to the server. The input data is the text question entered by the user, and the output data is the HTTP request sent to the server.

[1724] Step 3:

[1725] The server sends a prompt to the generative AI model.

[1726] The server converts the received question into a prompt suitable for the generative AI model and sends it to the generative AI model. Specifically, a server-side script (e.g., Python, Node.js) converts the question into a prompt in the format "Please generate an answer to customer question: 'How long is the warranty period for this product?'" and sends an API request to the generative AI model. The input data is the HTTP request sent to the server, and the output data is the prompt sent to the generative AI model.

[1727] Step 4:

[1728] A generative AI model generates the answer.

[1729] The generative AI model generates an appropriate answer based on the prompt. Specifically, the generative AI model (e.g., GPT-4) analyzes the received prompt and generates the answer, "This product has a one-year warranty." The input data is the prompt sent to the generative AI model, and the output data is the generated answer.

[1730] Step 5:

[1731] The server sends the response to the terminal.

[1732] The server sends the answer obtained from the generative AI model to the terminal as an HTTP response. Specifically, the server-side script sends the generated answer to the terminal as an HTTP response. The input data is the answer obtained from the generative AI model, and the output data is the HTTP response sent to the terminal.

[1733] Step 6:

[1734] The terminal displays the answer to the user.

[1735] The terminal displays the response received from the server to the user. Specifically, a dedicated application or web browser displays the received response on the screen, which the sales representative can then confirm. The input data is the HTTP response received from the server, and the output data is the text-formatted response that is displayed to the user.

[1736] (Application example 2)

[1737] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1738] In traditional sales negotiations and customer service in brick-and-mortar stores, it can be difficult for salespeople or store clerks to quickly and accurately answer customer questions. This can lead to lower customer satisfaction and missed business opportunities. Another issue is that the time it takes to search for information and respond to questions can hinder efficient business operations.

[1739] 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.

[1740] In this invention, the server includes a generative AI means, a messenger application means for transmitting and receiving Q&As generated by the generative AI means, a means for providing answers to questions from users through the messenger application means, and a means for receiving voice input from users using smart glasses, generating answers through the generative AI means, and displaying the answers on a display of the smart glasses. This enables salespeople and store clerks to quickly and accurately answer questions from customers, thereby improving customer satisfaction and work efficiency.

[1741] "Generative AI methods" are methods that use artificial intelligence technology to generate appropriate answers to questions from users.

[1742] "Messenger app means" refers to an application means for sending and receiving Q&A generated by generative AI means.

[1743] "Means for providing answers to questions from users" refers to means for providing answers to questions from users through messenger app means.

[1744] "Smart glasses" are wearable devices worn by users that have voice input and display functions.

[1745] The "means for obtaining voice input" refers to a means for obtaining voice input from a user using the smart glasses.

[1746] "Means for displaying on a display" refers to means for displaying the answer generated through the generative AI means on the display of the smart glasses.

[1747] A system for implementing this invention includes generative AI means, messenger application means, means for providing answers to questions from users, means for acquiring voice input using smart glasses, and display means.

[1748] 1. System Program

[1749] The system program is configured as follows:

[1750] Generative AI method: Uses OpenAI's API to generate appropriate answers to user questions.

[1751] Messenger app means: an application for sending and receiving questions and answers, which works in conjunction with smart glasses.

[1752] Voice input acquisition means: The microphone in the smart glasses is used to acquire voice input from the user.

[1753] Display means: Display the generated answer on the display of the smart glasses.

[1754] 2. Program processing explanation

[1755] The server uses OpenAI's API as the generative AI means. When a user wears the smart glasses and makes a voice input, the microphone in the smart glasses picks up the voice. The picked up voice data is sent to the server via the messenger app means. The server uses the generative AI means to convert the voice data into text and generate an appropriate answer. The generated answer is then sent again to the smart glasses via the messenger app means and displayed on the display.

[1756] 3. Specific Examples

[1757] For example, if a customer asks "Do you have this item in stock?" in a physical store, the microphone in the smart glasses will pick up the voice. The voice data will be sent to the server, and the generative AI means will generate a response such as "Yes, this item is in stock." This response will be displayed on the smart glasses' display, allowing the store clerk to quickly respond to the customer.

[1758] Prompt Sentence Examples

[1759] Customer Question: Is this item in stock?

[1760] A: Yes, this item is in stock.

[1761] In this way, salespeople and store clerks can quickly and accurately answer customer questions through the smart glasses, improving customer satisfaction.

[1762] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1763] Step 1:

[1764] The user wears the smart glasses and performs voice input.

[1765] Input: User's voice question

[1766] Output: Audio data

[1767] Specific operation: The user speaks a question into the microphone of the smart glasses, which then picks up the voice data.

[1768] Step 2:

[1769] The terminal transmits the voice data to the server via the messenger application means.

[1770] Input: Audio data

[1771] Output: Audio data sent to the server

[1772] Specific operation: The smart glasses transmit the acquired voice data to the server through the messenger app.

[1773] Step 3:

[1774] The server converts the audio data into text.

[1775] Input: Audio data

[1776] Output: Text data

[1777] Specific operation: The server uses voice recognition technology to convert the voice data into text data.

[1778] Step 4:

[1779] The server uses generative AI tools to generate answers based on the text data.

[1780] Input: Text data

[1781] Output: Answer text

[1782] What happens: The server uses generative AI tools (e.g., OpenAI API) to generate appropriate answers based on the text data.

[1783] Step 5:

[1784] The server transmits the generated answer text to the terminal via the messenger application means.

[1785] Input: Answer text

[1786] Output: Answer text sent to the terminal

[1787] Specific operation: The server sends the generated answer text to the smart glasses through a messenger app.

[1788] Step 6:

[1789] The terminal displays the answer text on the display of the smart glasses.

[1790] Input: Answer text

[1791] Output: Answer displayed on the smart glasses display

[1792] Specific operation: The smart glasses display the received answer text on the display and the user confirms it.

[1793] In this way, users can quickly and accurately answer customer questions through the smart glasses.

[1794] Example 3

[1795] Next, a third embodiment of the third embodiment will be described. 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."

[1796] In traditional education and events, it has been difficult to get quick and accurate answers to questions. In particular, questions that require specialized knowledge often require a lot of time and effort to provide answers. Furthermore, in situations where real-time answers are required, it is difficult to provide appropriate answers immediately. This can lead to a decline in the quality of education and the satisfaction of event participants.

[1797] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1798] In this invention, the server includes means for generating answers to questions from users using a generative AI model, communication means for transmitting and receiving the answers generated by the generative AI model, and means for receiving questions from users via the communication means and displaying the generated answers, thereby enabling users to obtain quick and accurate answers in real time.

[1799] A "generative AI model" is an artificial intelligence model used to generate answers to user questions.

[1800] "Communication means" refers to the means for sending and receiving answers generated by the generative AI model.

[1801] The "display means" is a means for displaying to the user the answer received through the communication means.

[1802] A "user" is a person or entity that utilizes the system to enter questions and receive answers.

[1803] A "question" is information or a question that a user inputs into the system.

[1804] An "answer" is the information or answer that a generative AI model generates in response to a question.

[1805] "Real-time" refers to the extremely short time between when a user enters a question and when they receive a response.

[1806] "Education" is the activity or process of imparting knowledge or skills.

[1807] An "event" is a gathering or event held for a specific purpose or theme.

[1808] A "meeting" is a place where multiple people gather to discuss and make decisions.

[1809] A "business meeting" is a place where business negotiations and transactions are conducted.

[1810] This invention is a system that uses a generative AI model to generate answers to user questions and provide them quickly and accurately. This system can be used in a variety of situations, such as education, events, meetings, and business negotiations.

[1811] Hardware and software used

[1812] Hardware

[1813] Server: A server with high-performance computing power is required, including CPU, GPU, memory, and storage.

[1814] Device: The device through which a user enters a question and receives a response. This can include a tablet, PC, or smartphone.

[1815] software

[1816] Generative AI models: For example, using advanced natural language processing models such as OpenAI's GPT-4.

[1817] Communication method: Uses network protocols (such as HTTP / HTTPS) to send and receive data over an internet connection.

[1818] Display method: Use an application or web browser to display the answers on your device.

[1819] Data processing and calculation

[1820] Data Entry

[1821] Users use the device to type in a question, for example, a teacher uses the tablet keyboard to type, "What is the speed of light?"

[1822] Data transmission

[1823] The device sends the entered question to the server. An internet connection is required for sending. When the device presses the "Send" button, the question is sent to the server via the internet.

[1824] Data Processing

[1825] The server analyzes the received question and converts it into a format suitable for the generative AI model. This process includes text preprocessing and tokenization. The server breaks down the text "What is the speed of light?" into tokens and converts it into a format that can be input to the generative AI model.

[1826] Generate answers

[1827] The server uses a generative AI model to generate a detailed answer to the question. The server inputs the question "What is the speed of light?" into the generative AI model and gets the answer "The speed of light is approximately 299,792,458 meters per second."

[1828] Data transmission

[1829] The server then sends the generated answer to the device. This again requires an internet connection. The server then sends the answer "The speed of light is approximately 299,792,458 meters per second" to the device via the internet.

[1830] Data Display

[1831] The device displays the received answer to the user on the device's screen. The device displays the text "The speed of light is approximately 299,792,458 meters per second" on the screen, and the teacher confirms it.

[1832] Examples of specific examples and prompts

[1833] Specific examples

[1834] A teacher is asked by a student during class, "What is the speed of light?"

[1835] The teacher uses a tablet to type in a question and presses the send button.

[1836] The terminal sends a query to the server.

[1837] The server analyzes the question and inputs it into a generative AI model.

[1838] The generative AI model generates the answer, "The speed of light is approximately 299,792,458 meters per second."

[1839] The server sends the generated response to the terminal.

[1840] The device displays the answers on the screen, and the teacher checks them and passes them on to the students.

[1841] Prompt Sentence Examples

[1842] "What is the speed of light?"

[1843] "What caused World War II?"

[1844] "What is the chemical formula for oxygen?"

[1845] This system enables users to obtain prompt and accurate answers in real time, thereby improving the quality of education and events. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1846] Step 1:

[1847] A user uses a terminal to input a question. The input question is in text format, such as "What is the speed of light?" The terminal receives the question and prepares it for transmission.

[1848] Input: A question typed into the device by the user (e.g., "What is the speed of light?")

[1849] Output: Question data ready to be sent

[1850] Step 2:

[1851] The device sends the entered question to the server. An internet connection is required for transmission, and the HTTP / HTTPS protocol is used. When the device presses the "Send" button, the question is sent to the server via the internet.

[1852] Input: Question data ready to be sent

[1853] Output: Question data sent to the server

[1854] Step 3:

[1855] The server analyzes the received question and converts it into a format suitable for the generative AI model. This process includes text preprocessing and tokenization. The server breaks down the text "What is the speed of light?" into tokens and converts it into a format that can be input to the generative AI model.

[1856] Input: Question data sent to the server

[1857] Output: Data converted into a format that can be fed into a generative AI model

[1858] Step 4:

[1859] The server uses a generative AI model to generate a detailed answer to the question. The server inputs the question "What is the speed of light?" into the generative AI model and gets the answer "The speed of light is approximately 299,792,458 meters per second."

[1860] Input: Data converted into a format that can be fed into a generative AI model

[1861] Output: Answer data obtained from the generative AI model

[1862] Step 5:

[1863] The server then sends the generated answer to the device. This again requires an internet connection and uses the HTTP / HTTPS protocol. The server then sends the answer "The speed of light is approximately 299,792,458 meters per second" to the device via the internet.

[1864] Input: Answer data obtained from a generative AI model

[1865] Output: Answer data sent to the device

[1866] Step 6:

[1867] The device displays the received answer to the user on the device's screen. The device displays the text "The speed of light is approximately 299,792,458 meters per second" on the screen, and the user confirms it.

[1868] Input: Answer data sent to the terminal

[1869] Output: Answer data displayed on the screen

[1870] In this way, users can get fast and accurate answers in real time.

[1871] (Application example 3)

[1872] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1873] In traditional Q&A sessions at educational settings and events, it has been difficult for teachers and moderators to provide quick and detailed answers to questions from participants. Furthermore, when real-time answers are required, limitations on human resources have become an issue. This has led to a decline in participant satisfaction and understanding.

[1874] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1875] In this invention, the server includes generative AI means, communication application means, means for providing answers to questions from users, means for teachers to obtain detailed answers to questions from students in educational settings, and means for generating answers in real time to questions from participants in Q&A sessions at events. This makes it possible to provide quick and detailed answers in educational settings and events, thereby improving participant satisfaction and understanding.

[1876] "Generative AI methods" refers to artificial intelligence technology that automatically generates answers to questions posed by users.

[1877] "Communication application means" refers to software for sending and receiving Q&As generated by generative AI means.

[1878] "Means for providing answers to questions from users" refers to a function for providing answers to questions from users through a communication application means.

[1879] "A means for teachers to obtain detailed answers to questions from students in educational settings" refers to a function that allows teachers to input questions from students and obtain detailed answers using generative AI means.

[1880] "A means for generating answers in real time to questions from participants in Q&A sessions at events" refers to a function that receives questions from participants in real time at an event and instantly generates answers using generative AI means.

[1881] In order to practice this invention, it is necessary to build a system that includes generative AI means, communication application means, means for providing answers to questions from users, means for teachers to obtain detailed answers to questions from students in educational settings, and means for generating answers in real time to questions from participants in Q&A sessions at events.

[1882] System configuration

[1883] 1. Generative AI means

[1884] The server uses generative AI models such as OpenAI's GPT-3 as a generative AI method, which allows it to automatically generate detailed answers to user questions.

[1885] 2. Communication Application Means

[1886] The server uses a smartphone application as a communication application means, which provides an interface for sending and receiving the Q&A generated by the generative AI means.

[1887] 3. Means of providing answers to user questions

[1888] The server receives a question from a user through the communication application means, generates an answer using the generative AI means, and provides the answer to the user again through the communication application means.

[1889] 4. A way for teachers to get detailed answers to student questions in educational settings

[1890] Teachers can use a smartphone application to input questions from students and get detailed answers using generative AI methods, thereby improving the quality of education.

[1891] 5. A way to generate real-time answers to attendee questions during event Q&A sessions

[1892] Event hosts and organizers can use a smartphone application to receive questions from attendees in real time and use generative AI tools to instantly generate answers and provide them to attendees.

[1893] Program processing explanation

[1894] The server uses the OpenAI API to access a generative AI model (GPT-3). It works as follows:

[1895] 1. The server imports the openai library and sets the API key.

[1896] 2. The server receives the question from the user and generates an answer using generative AI means.

[1897] 3. The server provides the generated answer to the user through a communication application means.

[1898] Specific examples

[1899] For example, if a teacher receives a question from a student such as "Please explain the process of photosynthesis," the following prompt sentence can be input into the generative AI model:

[1900] Prompt Sentence Examples

[1901] Explain the process of photosynthesis

[1902] The generative AI model generates detailed answers such as, "Photosynthesis is the process by which plants use light energy to produce glucose and oxygen from carbon dioxide and water. Chlorophyll, primarily found in leaves, absorbs light and converts it into chemical energy." These answers are provided to teachers via communication applications.

[1903] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1904] Step 1:

[1905] The user inputs a question using a device (smartphone application).

[1906] Input: User question (e.g., "Please explain the process of photosynthesis.")

[1907] Output: User question data

[1908] Specific operation: The user enters a question into the application's input field and presses the submit button.

[1909] Step 2:

[1910] The terminal transmits the user's question data to the server.

[1911] Input: User question data

[1912] Output: The query data sent to the server

[1913] Specific operation: The terminal sends the query data to the server via the Internet.

[1914] Step 3:

[1915] The server receives the question data and passes it to the generative AI means.

[1916] Input: Query data sent to the server

[1917] Output: Question data passed to the generative AI method

[1918] Specific operation: The server analyzes the received question data and passes it to the generative AI means (OpenAI's API).

[1919] Step 4:

[1920] A generative AI tool generates answers based on the question data.

[1921] Input: Question data passed to the generative AI method

[1922] Output: Generated response data

[1923] Specific operation: The generative AI method uses the question data as a prompt and generates an answer using an AI model (GPT-3).

[1924] Step 5:

[1925] The server receives the generated response data and transmits it to the terminal.

[1926] Input: Generated response data

[1927] Output: Response data sent to the device

[1928] Specific operation: The server sends the answer data received from the generative AI means to the terminal.

[1929] Step 6:

[1930] The terminal displays the answer data received from the server to the user.

[1931] Input: Answer data sent to the terminal

[1932] Output: Answer data displayed to the user

[1933] Specific operation: The terminal displays the received response data on the screen and provides it to the user.

[1934] Through the above processing steps, a user can input a question and obtain a detailed answer using generative AI means.

[1935] 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.

[1936] "Example 1"

[1937] One embodiment of the present invention is a system that incorporates an emotion engine that recognizes user emotions. This system includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the Q&As generated by the generative AI means, and a means for providing answers to questions from users via the messenger app means. Furthermore, an emotion engine that recognizes user emotions is incorporated. This emotion engine recognizes emotions from the user's facial expressions, tone of voice, message context, etc., and provides this information to the generative AI means. The generative AI means generates answers to user questions based on this emotion information. For example, if the user feels angry, the generative AI means will generate more polite answers.

[1938] "Example 2"

[1939] Another embodiment of the present invention is a system in which an emotion engine tracks changes in a user's emotions and a generative AI means adjusts responses in response to those changes. In this system, the emotion engine tracks changes in a user's emotions in real time and provides that information to the generative AI means. The generative AI means adjusts responses based on this information about changes in emotion. For example, if a user is initially happy but gradually begins to show signs of dissatisfaction, the generative AI means captures that change and adjusts the tone and content of the responses.

[1940] "Example 3"

[1941] One embodiment of the present invention is a system that incorporates an emotion engine that recognizes user emotions. This system includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the Q&As generated by the generative AI means, and a means for providing answers to questions from users via the messenger app means. Furthermore, an emotion engine that recognizes user emotions is incorporated. This emotion engine recognizes emotions from the user's facial expressions, tone of voice, message context, etc., and provides this information to the generative AI means. The generative AI means generates answers to user questions based on this emotion information. For example, if the user feels angry, the generative AI means will generate more polite answers.

[1942] The processing flow of each embodiment will be described below.

[1943] "Example 1"

[1944] Step 1: The user sends a question via a messenger app.

[1945] Step 2: The emotion engine recognizes emotions from the user's facial expressions, tone of voice, and message context.

[1946] Step 3: The emotion engine provides the recognized emotion information to the generative AI means.

[1947] Step 4: The generative AI method generates an answer to the user's question based on the emotional information.

[1948] Step 5: The generative AI method sends the generated answer to the user via a messenger app method.

[1949] "Example 2"

[1950] Step 1: The user sends a question via a messenger app.

[1951] Step 2: The emotion engine tracks changes in the user's emotions in real time. Step 3: The emotion engine provides the tracked emotion change information to the generative AI means.

[1952] Step 4: The generative AI tool adjusts the response based on the emotional change information.

[1953] Step 5: The generative AI method sends the adjusted response to the user via the messenger app method.

[1954] Example 1

[1955] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1956] Conventional Q&A systems generate answers without considering the user's feelings, which can lead to low user satisfaction. They also face the problem of being unable to respond to user questions quickly due to the difficulty of generating answers in real time. Furthermore, they sometimes fail to provide detailed information about specific products or topics, which can make it difficult to meet user needs.

[1957] 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.

[1958] In this invention, the server includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger application means for sending and receiving the Q&As generated by the generative AI means, an emotion engine means for recognizing the user's emotions, and a generative AI means for adjusting answers based on the emotion information provided by the emotion engine means. This makes it possible to provide detailed Q&As in real time that take the user's emotions into consideration.

[1959] "Generative AI methods" refers to artificial intelligence techniques for generating detailed Q&A about specific products or topics.

[1960] "Messenger app means" refers to application software for sending and receiving Q&As generated by generative AI means and providing answers to questions from users.

[1961] "Emotion engine means" refers to technology that recognizes the user's emotions and provides that information to generative AI means.

[1962] "Emotional information" refers to data regarding emotions recognized by the emotion engine means from the user's facial expression, tone of voice, message context, etc.

[1963] "Real-time" refers to generating and providing answers to user questions instantly.

[1964] "In-depth Q&A" refers to in-depth questions and answers about a specific product or topic.

[1965] The present invention is a system that combines a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the generated Q&As, and an emotion engine means for recognizing the user's emotions.

[1966] The server hosts a generative AI model that generates answers to user questions in real time. The generative AI model uses natural language processing techniques to receive user questions and generate appropriate answers.

[1967] The device (user's smartphone or PC) sends the user's question to the server through a messenger app, such as WhatsApp or Slack, and receives the generated answer.

[1968] The emotion engine recognizes emotions from the user's facial expressions, tone of voice, and message context. For example, it can use the emotion recognition API from Microsoft's Azure Cognitive Services. The emotion engine provides the recognized emotion information to the generative AI model.

[1969] The generative AI model generates answers to user questions based on the emotional information provided by the emotion engine. For example, if the emotion engine recognizes that the user is angry, the generative AI model will generate a more polite answer.

[1970] As a concrete example, consider a case where a user asks, "How do I return this product?" If the emotion engine recognizes anger in the user's message, the generative AI model will generate a polite response such as, "We're sorry. We'll explain the return process in detail."

[1971] Example prompt sentence:

[1972] User: How do I return this product?

[1973] Generative AI model: If the emotion engine recognizes that the user is angry, generate a polite response.

[1974] This system makes it possible to provide detailed Q&A in real time, taking into account the user's emotions.

[1975] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1976] Step 1:

[1977] A user types a question into a messenger app.

[1978] Input: Users enter text questions about a particular product or topic.

[1979] What happens: A user types "How do I return this product?" into a messenger app.

[1980] Step 2:

[1981] The terminal sends a question to the server.

[1982] Input: The question text entered by the user.

[1983] Output: The question data sent to the server.

[1984] Specific operation: The device sends the user's question to the server via the messenger app.

[1985] Step 3:

[1986] The server passes the question to the generative AI model.

[1987] Input: Question data sent from the terminal.

[1988] Output: Question data passed to the generative AI model.

[1989] Specific operation: The server passes the received question to the generative AI model.

[1990] Step 4:

[1991] A generative AI model generates the answer.

[1992] Input: The query data passed by the server.

[1993] Output: The initial answer text.

[1994] How it works: The generative AI model generates an initial response such as, "We will provide detailed instructions on how to return the item."

[1995] Step 5:

[1996] The emotion engine recognizes the user's emotions.

[1997] Input: User messages, facial expressions, tone of voice, etc.

[1998] Output: User's emotional information.

[1999] Specific behavior: The emotion engine recognizes anger from the user's message.

[2000] Step 6:

[2001] A generative AI model takes emotional information into account and adjusts the answer.

[2002] Input: Initial answer text, user sentiment information.

[2003] Output: The adjusted answer text.

[2004] Specific operation: The generative AI model uses emotional information to generate a polite response such as, "We're sorry. We'll explain in detail how to return the product."

[2005] Step 7:

[2006] The server sends the final answer to the device.

[2007] Input: The adjusted answer text.

[2008] Output: The final answer data sent to the device.

[2009] Specific operation: The server sends the final answer from the generative AI model to the device.

[2010] Step 8:

[2011] The terminal displays the answer to the user.

[2012] Input: The final answer data sent from the server.

[2013] Output: The answer text that is displayed to the user.

[2014] Specific behavior: The device will display the final response to the user through the messenger app.

[2015] (Application example 1)

[2016] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2017] Conventional customer support systems provide uniform answers without considering the user's emotions, which leads to a decline in user satisfaction. It is also difficult to respond in real time, so users need to provide prompt answers to their questions. Furthermore, because they are unable to respond appropriately to the user's emotions, there is an issue of a decline in the quality of support, especially for users with negative emotions such as anger or confusion.

[2018] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes: generative AI means for generating detailed Q&As about specific products or themes; messenger application means for sending and receiving the Q&As generated by the generative AI means; means for providing answers to questions from users via the messenger application means; emotion engine means for recognizing the user's emotions; means for the emotion engine means to recognize the user's emotions from the user's facial expressions, tone of voice, and message context and provide this information to the generative AI means; and means for the generative AI means to generate answers to questions from users based on the emotion information. This makes it possible to provide appropriate answers in real time that correspond to the user's emotions.

[2019] "Generative AI methods" refers to artificial intelligence techniques that generate detailed Q&A about specific products or topics.

[2020] "Messenger App Means" refers to a communication application for sending and receiving Q&As generated by Generative AI Means.

[2021] "Emotion engine means" refers to technology for recognizing emotions from a user's facial expressions, tone of voice, and message context.

[2022] "Means for providing answers to user questions" refers to technology for providing answers to user questions through messenger app means.

[2023] "Emotion information" refers to data relating to the user's emotions recognized by the emotion engine means.

[2024] "Generating in real time" refers to generating answers instantly to questions from users.

[2025] "Customer support" refers to assistance activities to address user questions or issues regarding products or services.

[2026] A system for implementing this invention includes a generative AI means for generating detailed Q&As about specific products or themes, a messenger app means for sending and receiving the generated Q&As, and an emotion engine means for recognizing user emotions. Specific embodiments of this system are described below.

[2027] System Configuration

[2028] 1. Hardware:

[2029] Device: Smartphone or tablet

[2030] Sensors: Camera and microphone (to recognize your facial expressions and tone of voice)

[2031] 2. Software:

[2032] Generative AI models: We will use OpenAI GPT-4 as an example.

[2033] Emotion recognition engine: As an example, we will use the Microsoft Azure Emotion API.

[2034] Messenger app: For example, using the Twilio API.

[2035] Data processing and calculation

[2036] 1. Get user's question:

[2037] The user's question is obtained as text data through the device's messenger app.

[2038] 2. Emotion recognition:

[2039] The user's facial expressions and tone of voice are transmitted to the emotion recognition engine means via the device's camera and microphone.

[2040] The emotion recognition engine means analyzes the user's emotions and provides the results to the generative AI means.

[2041] 3. Answer generation:

[2042] A generative AI tool takes emotional information into account and generates answers to user questions in real time.

[2043] 4. Submit your response:

[2044] The generated answer is sent to the user via a messenger app.

[2045] Specific examples

[2046] Example 1: When the user is angry

[2047] If a user asks, "My product hasn't arrived yet, what's going on?" and the emotion recognition engine means recognizes that the user is angry, the generative AI means will generate an answer like the following:

[2048] Example answer:

[2049] "We apologize for the inconvenience. We are currently checking the delivery status. Please wait a moment."

[2050] Example 2: When a user is having trouble

[2051] If a user asks, "I don't know how to use this product, what should I do?" and the emotion recognition engine means recognizes that the user is having trouble, the generative AI means will generate an answer like the following.

[2052] Example answer:

[2053] "Don't worry, here's a link to a video on how to use it. Let me know if you have any other questions."

[2054] Prompt Sentence Examples

[2055] An example of a prompt sentence to input to the generative AI model is as follows:

[2056] Prompt statement:

[2057] "If a user is upset, generate a polite response to the following question: Question: 'My item hasn't arrived, what's going on?'"

[2058] In this way, an emotion-responsive customer support system can provide a better customer experience by responding appropriately to the user's emotions.

[2059] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2060] Step 1:

[2061] A user inputs a question through a messenger app on the device. The input question is acquired as text data. The input data is the user's question text, and the output data is the question in text format.

[2062] Step 2:

[2063] The system captures the user's facial expressions and tone of voice in real time using the device's camera and microphone. The input data are the user's facial images and voice data, and the output data is multimedia information including these data.

[2064] Step 3:

[2065] The facial expression images and voice data captured by the terminal are sent to the emotion recognition engine means. The emotion recognition engine means analyzes these data and recognizes the user's emotion. The input data is multimedia information, and the output data is the user's emotion information.

[2066] Step 4:

[2067] The emotion recognition engine means provides the recognized emotion information to the generative AI means. The input data is the user's emotion information, and the output data is a prompt sentence containing the emotion information.

[2068] Step 5:

[2069] The generative AI method generates answers to user questions in real time, taking into account emotional information. The input data are a prompt containing emotional information and the user's question text, and the output data is the generated answer text.

[2070] Step 6:

[2071] The generated answer text is sent to the user through a messenger application means of the terminal, and the input data is the generated answer text, and the output data is the answer displayed to the user.

[2072] Step 7:

[2073] The user receives the answer and enters a follow-up question if necessary, and the process repeats again from step 1. The input data is the user's follow-up question text, and the output data is the new question text.

[2074] In this way, it is possible to provide an appropriate response in real time according to the user's feelings.

[2075] Example 2

[2076] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2077] In traditional business negotiations and meetings, it can be difficult for users to respond quickly and appropriately to customer questions. Furthermore, responses cannot be adjusted according to changes in the user's emotions, which can lead to lower customer satisfaction. This increases the risk of missed business opportunities.

[2078] 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.

[2079] In this invention, the server includes generative AI means, communication means, and emotion engine means, which allow users to receive appropriate answers to customer questions in real time and adjust the answers according to changes in the user's emotions.

[2080] "Generative AI methods" refers to artificial intelligence technology that generates appropriate answers to questions from users.

[2081] "Communication means" refers to the technology for sending and receiving data between the generative AI means and the user's device.

[2082] "Emotion engine means" refers to technology that tracks user emotions in real time and collects that data.

[2083] "Means for providing answers" refers to the technology for presenting the answers generated by the generative AI means to the user.

[2084] "Emotional Data" refers to information regarding a user's emotional state collected by emotion engine means.

[2085] "Means for adjusting responses" refers to technology that changes the tone and content of responses generated by generative AI means based on emotional data.

[2086] This invention is a system that enables a user to quickly and appropriately answer questions from customers in situations such as business negotiations and meetings. This system includes generative AI means, communication means, and emotion engine means.

[2087] Hardware and software used

[2088] Hardware: Servers, devices (PCs, tablets, smartphones)

[2089] Software: Generative AI models (e.g., general-purpose natural language processing models), emotion engines (e.g., emotion recognition software)

[2090] System configuration

[2091] 1. The server hosts the generative AI means and the emotion engine means. The server receives questions from users, passes them to the generative AI means to generate answers, and receives emotion data from the emotion engine means and provides it to the generative AI means.

[2092] 2. The terminal is a device used by the user to input questions in real time during a business meeting with a customer. The terminal sends the questions to the server, receives the answers from the server, and displays them to the user.

[2093] 3. The user inputs questions from customers into the device during business negotiations or meetings and receives answers from the generative AI means.

[2094] Details of data processing and calculation

[2095] The generative AI means generates appropriate answers to questions from users. For example, if a user asks, "How long is the warranty period for this product?", the generative AI means generates the answer, "The warranty period for this product is two years."

[2096] The communication means sends and receives data between the device and the server. Questions entered by the user into the device are sent to the server via the communication means. The server receives the answer from the generative AI means and sends it back to the device via the communication means.

[2097] The emotion engine means tracks the user's emotions in real time and collects the data, for example, when the user expresses dissatisfaction, the information is collected and sent to the server.

[2098] The response adjustment means changes the tone and content of the response generated by the generative AI means based on the emotional data. For example, if the user expresses dissatisfaction, the generative AI means may provide additional information such as, "Furthermore, if any problems occur during the warranty period, we will repair the product free of charge."

[2099] Specific examples

[2100] Sales scenario: A salesperson is explaining a new product when a customer asks, "How long is the warranty on this product?"

[2101] The user enters this question into the terminal.

[2102] The terminal sends a query to the server.

[2103] The server passes the question to a generative AI means to generate an answer.

[2104] The generative AI means generates an answer, "The warranty period for this product is two years," and returns it to the server.

[2105] The server sends the answer to the terminal, which displays it to the user.

[2106] The emotion engine means tracks changes in the user's emotions and collects information when the user is dissatisfied.

[2107] The server provides emotional data to the generative AI means to adjust the tone and content of the response.

[2108] The generative AI means provides the additional information, "Furthermore, if any problems arise during the warranty period, we will repair it free of charge."

[2109] The server sends the adjusted answer to the terminal, which displays it to the user.

[2110] Prompt Sentence Examples

[2111] Input prompt: "How long is the warranty on this product?"

[2112] Generated answer: "This product is covered by a two-year warranty. What's more, if a problem occurs during the warranty period, we'll repair it free of charge."

[2113] This system allows users to respond to customer questions quickly and appropriately, preventing missed business opportunities and improving customer satisfaction.

[2114] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2115] Step 1:

[2116] The user inputs a question into the terminal.

[2117] Input: A question the user receives from a customer (e.g., "How long is the warranty on this product?")

[2118] Specific actions: The user types a question into the input field on the terminal and presses the send button.

[2119] Output: Question data entered on the terminal

[2120] Step 2:

[2121] The terminal sends a question to the server.

[2122] Input: Question data entered into the terminal

[2123] Specific operation: The device generates an HTTP request and sends the query data to the server.

[2124] Output: Question data sent to the server

[2125] Step 3:

[2126] The server passes the question to the generative AI means.

[2127] Input: Question data sent to the server

[2128] Specific operation: The server analyzes the question data and makes an API call to pass it to the generative AI means.

[2129] Output: Question data passed to the generative AI method

[2130] Step 4:

[2131] A generative AI means generates answers to questions.

[2132] Input: Question data passed to the generative AI method

[2133] How it works: The generative AI means analyzes the question data and generates an appropriate answer (e.g., "This product has a two-year warranty").

[2134] Output: Generated response data

[2135] Step 5:

[2136] The server sends the generated response to the terminal.

[2137] Input: Generated response data

[2138] Specific operation: The server receives the generated response data and sends it to the terminal as an HTTP response.

[2139] Output: Answer data sent to the device

[2140] Step 6:

[2141] The terminal displays the answer to the user.

[2142] Input: Answer data sent to the terminal

[2143] Specific operation: The device displays the received answer data on the screen. The user can check the answer on the device screen.

[2144] Output: The answer displayed to the user

[2145] Step 7:

[2146] An emotion engine means tracks the emotions of the user.

[2147] Input: Emotional data such as the user's facial expressions and tone of voice

[2148] Specific operation: The emotion engine means analyzes the user's facial expressions and tone of voice in real time and tracks changes in emotions.

[2149] Output: Tracked emotion data

[2150] Step 8:

[2151] The server provides emotion data to the generative AI means.

[2152] Input: Tracked emotion data

[2153] Specific operation: The server makes an API call to provide the emotion data received from the emotion engine means to the generative AI means.

[2154] Output: Emotion data provided to the generative AI means

[2155] Step 9:

[2156] A generative AI tool adjusts the answer based on the emotional data.

[2157] Input: Emotion data provided to the generative AI method

[2158] What it does: The generative AI method analyzes the emotional data and adjusts the tone and content of the response (e.g., "What's more, if the issue occurs during the warranty period, we'll repair it free of charge").

[2159] Output: Adjusted response data

[2160] Step 10:

[2161] The server sends the adjusted response to the terminal.

[2162] Input: Adjusted response data

[2163] Specific operation: The server receives the adjusted response data and sends it to the terminal as an HTTP response.

[2164] Output: Adjusted response data sent to the device

[2165] Step 11:

[2166] The terminal displays the adjusted answer to the user.

[2167] Input: Adjusted response data sent to the device

[2168] Specific operation: The device displays the received adjusted answer data on the screen. The user checks the adjusted answer on the device screen.

[2169] Output: The adjusted answer...

Claims

1. A way to receive questions from users through messenger apps, an emotion engine means for recognizing the emotion of the user from the facial expression, tone of voice, and context of the question of the user; means for parsing the question and converting it into a prompt suitable for a generative AI model that generates Q&A about a particular product or topic; means for receiving an answer generated by the generative AI model by dynamically adjusting the content based on the prompt sentence and the user's emotion recognized by the emotion engine means; means for converting said response into a predetermined format; and means for providing the answer whose format has been converted to another person different from the user through the messenger app; system.

2. The system of claim 1 , wherein the response provided to the other person through the messenger app is displayed on a chat screen of the messenger app.

Images