System

Abstract

To provide a system.SOLUTION: A system includes: means for collecting advice of a generative AI to a question of a user; means for analyzing the question of the user using a natural language processing technique; means for generating the advice to the question of the user using the generative AI; means for recognizing a feeling of the user using a feeling engine; means for adjusting the advice on the basis of the feeling of the user; and means for providing the user with the adjusted advice.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] Generative AI has the ability to provide appropriate advice in response to user questions, but it has difficulty understanding how users should ask questions. Generative AI advice covers a wide range of areas, including marketing, research, brainstorming, programming, learning plans, recipe creation, and story writing, but there is a lack of effective ways to collect and provide this advice to users. [Means for solving the problem]

[0005] This invention provides a system including a means for collecting generative AI advice in response to a user's question, a means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe creation, story creation, etc., and a means for providing this advice to the user. Furthermore, the generative AI's advice includes instructions for improving the way the user asks questions, thereby providing guidelines for the user to ask the generative AI more effective questions. [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] In one embodiment of the present invention, the means for gathering generative AI advice includes an AI engine that receives a question from a user and generates generative AI advice in response to the question. The AI ​​engine uses natural language processing techniques to analyze the user's question and generate appropriate advice. For example, if a user asks, "How should I develop a marketing strategy?", the AI ​​engine generates advice such as, "Analyze your competitors, understand your target market, evaluate the strengths and weaknesses of your product, etc."

[0029] "Example 2"

[0030] In one embodiment of the present invention, the means for handling a wide range of tasks, such as marketing, research, brainstorming, programming, learning plans, recipe creation, and story writing, includes AI modules specialized in each area. These AI modules have expertise in their respective areas and generate specific advice in response to user questions. For example, if a user asks, "I don't know what to make," an AI module specialized in recipe creation generates advice such as, "I'll suggest a new recipe based on the ingredients you have on hand and your preferences."

[0031] "Example 3"

[0032] Furthermore, in one embodiment of the present invention, the means for providing the user with these pieces of advice includes a user interface. The user interface displays the generated advice to the user, allowing the user to easily understand the advice and take action based on it. For example, the user interface displays the generated advice in a text format so that the user can read it. The user interface also provides an input field where the user can enter a new question and receive advice in response to the question.

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

[0034] "Example 1"

[0035] Step 1: Receiving a question from the user In this step, a question from the user is received through the user interface.

[0036] Step 2: Analyze the question and generate advice. In this step, the AI ​​engine uses natural language processing technology to analyze the user's question and generate appropriate advice.

[0037] Step 3: Providing the generated advice to the user. In this step, the generated advice is displayed to the user through a user interface, allowing the user to easily understand the advice and take action based on it.

[0038] "Example 2"

[0039] Step 1: Receiving a question from the user In this step, a question from the user is received through the user interface.

[0040] Step 2: Analyze the question and select an AI module specialized in a specific domain. In this step, the AI ​​engine uses natural language processing technology to analyze the user's question and select an AI module specialized in a specific domain based on the content of the question.

[0041] Step 3: Generate advice using the selected AI module and provide it to the user. In this step, the selected AI module generates specific advice for the user's question and displays the generated advice to the user through the user interface.

[0042] "Example 3"

[0043] Step 1: Receiving a question from the user In this step, a question from the user is received through the user interface.

[0044] Step 2: Analyze the question and generate advice. In this step, the AI ​​engine uses natural language processing technology to analyze the user's question and generate appropriate advice.

[0045] Step 3: Providing the generated advice to the user. In this step, the generated advice is displayed to the user through a user interface, and the user accepts the advice.

[0046] to be easily understood and acted upon.

[0047] Step 4: User Enters New Question: In this step, the user interface provides an input field where the user can enter a new question and receive advice on it.

[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] Conventional generative AI systems can have difficulty providing appropriate advice in response to user questions. Furthermore, they lack guidelines and instructions for users to effectively ask generative AI, which can lead to problems with users being unable to accurately obtain the information they are looking for. Furthermore, they lack the flexibility to handle a wide range of tasks, including marketing, research, brainstorming, and programming.

[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 means for receiving a user's question, means including an AI engine using natural language processing technology for analyzing the received question, means for generating appropriate advice based on the analyzed question, means for providing the generated advice to the user, means for dealing with a wide range of areas such as marketing, research, brainstorming, programming and other work, study plans, recipe creation, story creation, etc., and means for providing this advice to the user. This enables the user to obtain appropriate advice in a wide range of areas, and also provides instructions for improving the way questions are asked and guidelines for asking more effective questions, allowing the user to accurately obtain the information they are looking for.

[0053] The "means for receiving a user's question" is an interface that allows the system to receive a question entered by the user.

[0054] "AI engine using natural language processing technology" refers to artificial intelligence technology that analyzes user questions and generates appropriate advice.

[0055] "Means for generating appropriate advice based on the analyzed questions" refers to the process by which the AI ​​engine creates specific advice for the user based on the analysis results.

[0056] "Means for providing generated advice to a user" refers to a method for displaying or transmitting advice generated by an AI engine to a user.

[0057] "A tool for a wide range of areas, including marketing, research, brainstorming, programming, study planning, recipe creation, and story writing" is a function that provides appropriate advice to users' questions in various fields.

[0058] "Instructions for improving how you ask questions" provide specific advice or guidelines to help users ask questions more effectively.

[0059] The "Guidelines for Asking More Effective Questions" provide guidelines and methods for users to ask appropriate questions to generative AI.

[0060] This invention is a system that provides generative AI advice in response to a user's question. This system includes an AI engine that receives the user's question, analyzes it using natural language processing technology, and generates appropriate advice. Specific embodiments of this system are described below.

[0061] First, the user enters a question using their own device (e.g., a PC or smartphone). For example, the user might enter, "How should I develop a marketing strategy?" This question is sent from the device to the server. Data is sent over the Internet.

[0062] The server passes the received question to an AI engine. This AI engine uses natural language processing technology to analyze the user's question. Specifically, a generative AI model such as GPT-4 (registered trademark) is used as the AI ​​engine. The AI ​​engine understands the content of the question and generates appropriate advice. For example, it generates advice such as "analyze competitors, understand the target market, and evaluate the strengths and weaknesses of the product."

[0063] The generated advice is sent to the user's device via the server. The device displays the received advice to the user. The user can check the displayed advice and use it as reference.

[0064] As a concrete example, the following prompt sentence can be input to a generative AI model:

[0065] Example prompt sentence:

[0066] How do I create a marketing strategy?

[0067] Given this prompt, the AI ​​engine might generate the following advice:

[0068] Example of generated advice:

[0069] "To develop a marketing strategy, it is important to first analyze your competitors, then understand your target market, and finally evaluate the strengths and weaknesses of your product."

[0070] In this way, users can get helpful advice for specific questions, and the system can be used in a wide range of areas, including marketing, research, brainstorming, programming, lesson planning, recipe creation, story writing, and more.

[0071] Additionally, the generative AI's advice includes instructions to improve the way users ask questions and guidelines for asking more effective questions, allowing users to use the generative AI more effectively.

[0072] To implement this system, it is important to use an appropriate combination of hardware and software, such as servers, terminals, and AI engines that use natural language processing technology (e.g., GPT-4).

[0073] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0074] Step 1:

[0075] The user enters a question

[0076] A user inputs a question using their own device (e.g., a PC or smartphone). For example, the user might input, "How should I develop a marketing strategy?" This input question becomes the starting point for the system's processing.

[0077] Step 2:

[0078] The device sends a question to the server

[0079] The terminal sends the question entered by the user to the server via the Internet using the HTTPS protocol. The input is the user's question, and the output is the question data sent to the server.

[0080] Step 3:

[0081] The server receives the question and passes it to the AI ​​engine.

[0082] The server receives questions sent from the device. The received questions are passed to the AI ​​engine in the server. The input is the question data received from the device, and the output is the question data passed to the AI ​​engine.

[0083] Step 4:

[0084] An AI engine analyzes the question and generates advice

[0085] The AI ​​engine analyzes the user's question using natural language processing technology. Specifically, it uses a generative AI model such as GPT-4 as the AI ​​engine. Based on the analyzed question, the AI ​​engine generates appropriate advice. For example, it generates advice such as "analyze competitors, understand the target market, and evaluate the strengths and weaknesses of the product." The input is the question data passed from the server, and the output is the generated advice.

[0086] Step 5:

[0087] The server receives the generated advice and sends it to the device.

[0088] The server receives the advice generated by the AI ​​engine. The received advice is then sent to the user's device via the Internet. The HTTPS protocol is again used for transmission. The input is the advice received from the AI ​​engine, and the output is the advice sent to the device.

[0089] Step 6:

[0090] The device displays the advice to the user.

[0091] The terminal receives advice sent from the server. The received advice is displayed in a format that is easy for the user to view. The user can check the displayed advice and use it as a reference. The input is the advice received from the server, and the output is the advice displayed to the user.

[0092] (Application example 1)

[0093] 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."

[0094] Conventional advice systems using generative AI allow users to receive advice by inputting specific questions, but there is a lack of means to provide appropriate advice in real time when selecting products in physical stores. This makes it difficult for users to obtain appropriate information when choosing products, resulting in a long time required for purchasing decisions. Furthermore, there is a lack of guidelines for users to ask effective questions to generative AI or instructions for improving the way questions are asked, which leads to a decline in the quality of the advice users receive.

[0095] 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.

[0096] In this invention, the server includes a means for collecting advice from the generative AI in response to user questions, a means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe creation, and story creation, a means for providing this advice to the user, and a means for the user to input questions when selecting products in a physical store and for the generative AI to provide advice in real time. This enables users to receive appropriate advice in real time when selecting products in a physical store, enabling faster purchasing decisions and improved quality of advice.

[0097] A "user" is an individual or organization that uses the system to input questions and receive advice from the generative AI.

[0098] A "question" is information or a question that a user inputs into a generative AI, and is input data for obtaining advice.

[0099] "Generative AI" is an artificial intelligence engine that analyzes users' questions and generates appropriate advice.

[0100] "Advice" refers to information or instructions that generative AI provides based on a user's question.

[0101] A "physical store" is a commercial facility located in a physical location where users can directly select and purchase products.

[0102] "Product selection" refers to the act of a user selecting a product to purchase in a physical store.

[0103] "Real-time" refers to the generative AI providing immediate advice as soon as the user types in a question.

[0104] "Marketing" refers to the activities and strategies used to promote the sale of products and services.

[0105] "Research" is an investigative activity aimed at gathering and analyzing specific information.

[0106] "Brainstorming" is an abbreviation of brainstorming, a creative activity in which ideas are freely exchanged.

[0107] A "program" is a sequence of instructions or code that is executed by a computer.

[0108] A "study plan" is a specific plan or schedule for achieving learning goals.

[0109] "Recipe development" is the act of coming up with cooking steps and ingredients.

[0110] "Story creation" is the act of creating a story or scenario.

[0111] To implement this invention, a user uses a smartphone application when selecting a product in a physical store. A specific embodiment of this system will be described below.

[0112] System Configuration

[0113] The system consists of the following main components:

[0114] 1. User device: Smartphone

[0115] 2. Server: A server that hosts the generative AI engine

[0116] 3. Software: Python (registered trademark), OpenAI (registered trademark) API

[0117] Program processing

[0118] The server includes a means for collecting generative AI advice in response to user questions, a means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation, a means for providing this advice to users, and a means for users to input questions when selecting products in a physical store and for the generative AI to provide advice in real time.

[0119] Hardware and Software

[0120] Hardware: The user device is a smartphone. The server is a high-performance computer that hosts the generative AI engine.

[0121] Software: Uses a Python program and OpenAI API. The Python program receives a user's question and calls OpenAI's API to generate advice using a generative AI model (e.g., GPT-3 (registered trademark)).

[0122] Data processing and calculation

[0123] When a user enters a question through a smartphone app, the question is sent to the server. The server receives the question and calls the OpenAI API through a Python program. The API sends the question as a prompt to the generative AI model, which then analyzes the question and generates appropriate advice. The generated advice is then returned from the server to the user's device and displayed to the user.

[0124] Specific examples

[0125] If a user asks, "Is this product cheaper than other stores?" in a physical store, the AI ​​engine will provide advice such as, "This product is priced averagely compared to other stores. We recommend checking the price online as well."

[0126] Example prompt sentence:

[0127] User Question: Is this product cheaper than other stores?

[0128] Please provide advice.

[0129] In this way, users can receive relevant advice in real time when choosing products in physical stores, enabling faster purchasing decisions and better advice.

[0130] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0131] Step 1:

[0132] The user launches the smartphone app and enters a question.

[0133] Input: User question (e.g. "Is this product cheaper than other stores?")

[0134] Output: User question data

[0135] Specific behavior: The user enters a question into the app's text input field and presses the submit button.

[0136] Step 2:

[0137] The terminal sends the user's question data to the server.

[0138] Input: User question data

[0139] Output: The query data sent to the server

[0140] Specific operation: The smartphone app sends the question data to the server as an HTTP request.

[0141] Step 3:

[0142] The server receives the query data and runs the Python program.

[0143] Input: Query data sent to the server

[0144] Output: Prompt sentence to the generative AI model

[0145] Specific operation: The server receives an HTTP request and passes the question data to the Python program, which converts the question data into a prompt.

[0146] Step 4:

[0147] The server calls the OpenAI API and sends a prompt to the generative AI model.

[0148] Input: prompt sentence for generative AI model

[0149] Output: Advice from a generative AI model

[0150] Specific operation: The Python program calls the OpenAI API and sends a prompt to a generative AI model (e.g., GPT-3).

[0151] Step 5:

[0152] A generative AI model analyzes the prompt and generates appropriate advice.

[0153] Input: prompt statement

[0154] Output: Generated advice

[0155] How it works: The generative AI model analyzes the prompt and generates advice based on its internal learning data.

[0156] Step 6:

[0157] The server receives the generated advice and returns it to the user terminal.

[0158] Input: Generated advice

[0159] Output: Advice sent to user terminal

[0160] Specific operation: The server receives advice from the generative AI model and sends it to the user device as an HTTP response.

[0161] Step 7:

[0162] The device receives the advice from the server and displays it to the user.

[0163] Input: Advice sent by the server

[0164] Output: Advice displayed to the user

[0165] Specific operation: The smartphone app receives the HTTP response and displays the advice on the screen.

[0166] In this way, users can get real-time, relevant advice when choosing products in a physical store.

[0167] Example 2

[0168] 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."

[0169] Conventional generative AI systems have difficulty providing appropriate advice in response to user questions, especially when dealing with a wide range of domains. Furthermore, there is a lack of guidelines and instructions for users to ask generative AI effective questions, which leads to a decline in the quality of user questions.

[0170] 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.

[0171] In this invention, the server includes means for inputting a user's question, means for transmitting the question to the server, means for selecting an appropriate AI module based on the question, means for inputting a prompt sentence to a generative AI model using the AI ​​module, means for the generative AI model to generate advice, means for providing the generated advice to a user, and means for handling a wide range of areas such as marketing, research, brainstorming, program creation, study plans, recipe creation, story creation, etc. This makes it possible to provide appropriate and specialized advice in response to a user's question, and to provide guidelines and instructions for users to ask effective questions to the generative AI.

[0172] A "means for inputting a user's question" is a device or software that provides an interface for a user to input a question to the system.

[0173] The "means for transmitting the question to the server" refers to a communication means for transmitting the question entered by the user to the server.

[0174] The "means for selecting an appropriate AI module based on the question" refers to an algorithm or program for analyzing the content of the user's question and selecting the AI ​​module that is most suitable for that content.

[0175] "Means for inputting a prompt sentence to a generative AI model using the AI ​​module" refers to means for creating and inputting an appropriate prompt sentence to a generative AI model using a selected AI module.

[0176] "Means for the generative AI model to generate advice" refers to means for the generative AI model to generate advice for the user based on the input prompt sentence.

[0177] "Means for providing the generated advice to the user" refers to means for displaying or notifying the user of the advice generated by the generative AI model.

[0178] "Means that cover a wide range of areas, including marketing, research, brainstorming, program creation, lesson planning, recipe development, and story writing" includes AI modules specialized in these wide-ranging areas, and are means for providing expert advice in each area.

[0179] This invention is a system for providing appropriate advice in response to a user's question. The system includes means for inputting a user's question, means for transmitting the question to a server, means for selecting an appropriate AI module based on the question, means for inputting a prompt sentence to a generative AI model using the AI ​​module, means for the generative AI model to generate advice, means for providing the generated advice to a user, and means for handling a wide range of areas such as marketing, research, brainstorming, program creation, study planning, recipe creation, and story creation.

[0180] Specifically, a user uses a device such as a smartphone or PC to input a question, such as "Tell me what to make for dinner tonight." The device receives this question and sends it to the server using an HTTP POST request.

[0181] The server analyzes the received question and selects the appropriate AI module based on its content. For example, if the question is about recipes, it selects an AI module that specializes in recipe creation. The server then uses the selected AI module to create a prompt to be input to the generative AI model. The prompt includes information about the user's question, ingredients on hand, and preferences.

[0182] Examples of specific prompts include:

[0183] User Asks: "What should I make for dinner tonight?"

[0184] Ingredients on hand: "Chicken, tomatoes, basil, cheese."

[0185] Favorite food: "Italian food"

[0186] The server inputs this prompt into a generative AI model, which then uses its internal algorithms to generate advice, such as "I recommend making Caprese chicken with chicken, tomatoes, basil, and cheese."

[0187] The generated advice is sent from the server to the device, and the device displays the advice to the user, who can then check the specific advice on the device screen.

[0188] The system allows users to receive expert advice in a wide range of areas and also provides guidelines and instructions to improve the quality of their questions, greatly improving user convenience.

[0189] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0190] Step 1:

[0191] The user enters a question.

[0192] Users open the application on their smartphone or computer and type into the text box, "Tell me what to make for dinner tonight," and the question is sent to the device.

[0193] Step 2:

[0194] The terminal sends a question to the server.

[0195] The terminal receives user input and sends a question to the server using an HTTP POST request: the input data is the user's question, and the output is the request sent to the server.

[0196] Step 3:

[0197] The server analyzes the question and selects the appropriate AI module.

[0198] The server analyzes the received question using natural language processing technology. Based on the analysis results, it determines that the question is about recipes and selects an AI module specialized in recipe creation. The input data is the user's question, and the output is the selected AI module.

[0199] Step 4:

[0200] The server inputs a prompt sentence into the generative AI model.

[0201] The server uses the selected AI module to create a prompt to be input to the generative AI model. The prompt includes information such as the user's question, ingredients on hand, and preferences. For example, a prompt might be generated as follows: "User question: 'Tell me what to make for dinner tonight' Ingredients on hand: 'Chicken, tomatoes, basil, cheese' Preferences: 'Italian food'." The input data is the user's question and related information, and the output is the prompt.

[0202] Step 5:

[0203] A generative AI model generates advice.

[0204] The generative AI model receives a prompt and uses its internal algorithm to generate advice, such as "I recommend making Caprese Chicken with chicken, tomatoes, basil, and cheese." The input data is the prompt, and the output is the generated advice.

[0205] Step 6:

[0206] The server transmits the generated advice to the terminal.

[0207] The server receives the advice obtained from the generative AI model and sends it to the terminal as an HTTP response. The input data is the generated advice, and the output is the response sent to the terminal.

[0208] Step 7:

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

[0210] The terminal displays the advice received from the server to the user. The user can see the advice on the terminal screen: "We recommend making Caprese Chicken with chicken, tomatoes, basil, and cheese." The input data is the advice from the server, and the output is what 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] Conventional generative AI systems can sometimes make it difficult for users to get appropriate advice when asking specific questions. They also lack specific assistance to improve the shopping experience in brick-and-mortar stores, such as when users don't know what to buy or want recipe suggestions using specific ingredients. Therefore, there is a need for a system that can provide appropriate advice in response to user questions and improve the shopping experience in brick-and-mortar stores.

[0214] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for collecting generative AI advice in response to a user's question, a means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation, a means for providing this advice to the user, a means for generating a prompt sentence for the generative AI model based on text entered by the user, and a means for displaying the generated advice to the user. This allows the user to receive appropriate advice when asking a specific question, improving the shopping experience in a physical store.

[0215] "Means for collecting advice from generative AI in response to user questions" is a function for collecting advice provided by generative AI in response to questions entered by users.

[0216] "A means to address a wide range of areas, including marketing, research, brainstorming, programming, study plans, recipe development, and story creation" is a function that uses generative AI modules specialized in various fields to provide appropriate advice to users' questions in each area.

[0217] "Means for providing these pieces of advice to users" refers to a function for displaying or notifying users of the advice provided by the generative AI.

[0218] "Means for generating prompt sentences for a generative AI model based on text entered by a user" refers to a function for automatically generating prompt sentences suitable for a generative AI model based on questions or requests entered by a user.

[0219] "Means for displaying generated advice to the user" refers to a function for visually displaying advice generated by the generative AI model to the user.

[0220] The following system configuration is used as an embodiment of this invention. The system includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe creation, and story creation; means for providing this advice to the user; means for generating prompt sentences for the generative AI model based on text entered by the user; and means for displaying the generated advice to the user.

[0221] Hardware and software used

[0222] Hardware: Smartphone

[0223] Software: Python, OpenAI API

[0224] Data processing and calculation

[0225] 1. Getting user input: A user types a question or request through a smartphone application, for example, "I don't know what to buy."

[0226] 2. Prompt generation: The server generates a prompt appropriate for the generative AI model based on the user's input. For example, it generates a prompt such as, "If the user says, 'I don't know what to buy,' please suggest new products based on the products they have on hand and their preferences."

[0227] 3. Calling the AI ​​model: The server passes the generated prompt sentence to the generative AI model via the OpenAI API to generate advice.

[0228] 4. Displaying Advice: The server displays the generated advice to the user through a smartphone application. For example, it displays advice such as "Suggested products: fresh vegetables, organic milk, whole wheat bread."

[0229] Specific examples

[0230] If a user uses a smartphone application and types "I don't know what to buy," the system works as follows:

[0231] 1. The user types, "I don't know what to buy."

[0232] 2. The server generates the following prompt based on the entered text:

[0233] If a user says, "I don't know what to buy," suggest new products based on what they have on hand and their preferences.

[0234] 3. The server passes this prompt to the generative AI model via the OpenAI API to generate advice.

[0235] 4. The server displays the generated advice to the user through a smartphone application, for example, "Suggested products: fresh vegetables, organic milk, whole wheat bread."

[0236] In this way, users can get the right advice for their specific questions, enhancing their in-store shopping experience.

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

[0238] Step 1:

[0239] A user inputs a question or request through a smartphone application. For example, they might input, "I don't know what to buy." This input becomes the initial data for the system.

[0240] Step 2:

[0241] The terminal sends the text entered by the user to the server. The input data is the text "I don't know what to buy."

[0242] Step 3:

[0243] The server generates a prompt sentence suitable for the generative AI model based on the received text. Specifically, it generates the following prompt sentence:

[0244] If a user says, "I don't know what to buy," suggest new products based on what they have on hand and their preferences.

[0245] This prompt sentence is generated.

[0246] Step 4:

[0247] The server passes the generated prompt sentence to the generative AI model through the OpenAI API. The input data is the generated prompt sentence, and the output data is the advice returned by the generative AI model.

[0248] Step 5:

[0249] The server receives the advice returned by the generative AI model, for example, "Suggested products: fresh vegetables, organic milk, whole wheat bread."

[0250] Step 6:

[0251] The server sends the received advice to the terminal for display to the user. The input data is the advice from the generative AI model, and the output data is the advice displayed to the user.

[0252] Step 7:

[0253] The device displays the advice received from the server to the user through a smartphone application. For example, the advice "Suggested products: fresh vegetables, organic milk, whole wheat bread" is displayed to the user.

[0254] In this way, users can get the right advice for their specific questions, improving their shopping experience in physical stores.

[0255] Example 3

[0256] 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."

[0257] In systems using conventional generative AI models, the process from when a user inputs a question to when they receive appropriate advice is complicated, and there are problems with a lack of guidelines or instructions for users to ask questions effectively. Another issue is that the generated advice is not properly communicated to users, making it difficult for them to act on it.

[0258] 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.

[0259] In this invention, the server includes means for receiving a user's question, means for transmitting the received question to the server, means for the server to input the question into a generative AI model and generate advice, means for transmitting the generated advice from the server to the terminal, means for the terminal to display the advice to the user, and means for the user to input a new question. This enables the user to effectively ask questions, appropriately receive the generated advice, and take action based on it.

[0260] "User" means an individual or entity that utilizes the System to enter questions and receive generated advice.

[0261] A "terminal" is an electronic device that a user uses to enter questions and view generated advice.

[0262] The "server" is a computer system that receives questions from users, inputs them into a generative AI model to generate advice, and sends it to the terminal.

[0263] A "generative AI model" is an artificial intelligence algorithm that generates appropriate advice based on a user's questions.

[0264] A "question" is information or a question that a user inputs into the system.

[0265] "Advice" is an answer or suggestion that a generative AI model generates based on a user's question.

[0266] A "user interface" is the part of a system that contains screens and input fields through which a user can enter questions and view generated advice.

[0267] A "prompt" is text containing a user question or instruction that is input into a generative AI model.

[0268] This invention is a system that allows a user to input a question and obtain appropriate advice using a generative AI model. This system includes a series of processes that receive the user's question, input it into the generative AI model, and provide the generated advice to the user.

[0269] Hardware and software used

[0270] Hardware

[0271] Device: An electronic device that allows users to input questions and view generated advice. Examples include computers, smartphones, and tablets.

[0272] Server: A computer system that receives questions from users, inputs them into a generative AI model to generate advice, and sends it to the device.

[0273] software

[0274] Generative AI models: Artificial intelligence algorithms that generate appropriate advice based on user questions. Examples include OpenAI's GPT-3.

[0275] User Interface: Software that contains screens and input fields for users to enter questions and view generated advice.

[0276] Data processing and calculation

[0277] Data Processing

[0278] Receiving user input: The user enters a question using the device's user interface. This input is in the form of text.

[0279] Sending a question: The device sends the question entered by the user to the server using a communication protocol such as an HTTP request.

[0280] Data Calculation

[0281] Advice generation: The server inputs the received question into the generative AI model and generates appropriate advice. The generative AI model generates text-based advice based on the input question.

[0282] Sending and displaying advice: The server sends the generated advice to the terminal, which displays the advice through a user interface.

[0283] Specific examples

[0284] Prompt Sentence Examples

[0285] Let's say a user wants advice on a new business idea. Here's an example prompt to input to a generative AI model:

[0286] Example prompt: "I have a new business idea in mind. How should I go about it?"

[0287] Example of advice generated: "First, conduct market research and identify your target audience. Then create a business plan and figure out how to raise funds."

[0288] In this way, the user can receive specific advice and decide on the next action based on it. This system enables the user to effectively ask questions, appropriately receive the generated advice, and take action based on it. The flow of the identification process in Example 3 will be described with reference to FIG. 15.

[0289] Step 1:

[0290] The user enters a question.

[0291] A user inputs a question using the user interface of a terminal. Specifically, the user inputs, "I'm thinking of a new business idea. How should I go about it?" This input is in text format. The input data is the user's question text.

[0292] Step 2:

[0293] The terminal sends a question to the server.

[0294] The terminal sends the question entered by the user to the server. This transmission is performed using a communication protocol such as an HTTP request. Specifically, the terminal sends the question "I'm thinking of a new business idea. How should I go about it?" to the server. The input data is the user's question text, and the output data is the question text sent to the server.

[0295] Step 3:

[0296] The server inputs the question into a generative AI model.

[0297] The server inputs the received question into the generative AI model. Specifically, the server inputs a prompt to the generative AI model: "I'm thinking of a new business idea. How should I go about it?" The input data is the question text sent to the server, and the output data is the prompt input to the generative AI model.

[0298] Step 4:

[0299] A generative AI model generates advice.

[0300] The generative AI model generates advice based on the input question. Specifically, the generative AI model generates the advice, "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the prompt sentence entered into the generative AI model, and the output data is the generated advice text.

[0301] Step 5:

[0302] The server receives the generated advice.

[0303] The server receives the advice returned from the generative AI model. Specifically, the server receives the advice, "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the advice text returned from the generative AI model, and the output data is the advice text received by the server.

[0304] Step 6:

[0305] The server sends the advice to the terminal.

[0306] The server sends the advice it receives to the terminal. This transmission is also performed using a communication protocol such as an HTTP request. Specifically, the server sends the advice to the terminal: "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the advice text received by the server, and the output data is the advice text sent to the terminal.

[0307] Step 7:

[0308] The terminal displays the advice to the user.

[0309] The terminal displays the received advice on the user interface. Specifically, the terminal displays on the user interface, "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the advice text sent to the terminal, and the output data is the advice text displayed on the user interface.

[0310] Step 8:

[0311] The user enters a new question.

[0312] The user can again enter a new question using the input field of the user interface. In a specific operation, the user enters "Please tell me the specific methods of market research." The input data is the newly entered question text, and the output data is the new question text entered into the user interface.

[0313] (Application example 3)

[0314] 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."

[0315] Conventional advice-giving systems using generative AI can provide advice in response to user questions, but it is difficult to provide advice specialized in a specific area. Furthermore, the interface for users to input new questions and receive advice in response to them is insufficient, resulting in a poor user experience. Providing appropriate advice for security-related questions is particularly important.

[0316] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for collecting generative AI advice in response to user questions, means for handling a wide range of areas such as marketing, research, brainstorming, programming, and other work, study plans, recipe development, and story creation, means for providing this advice to the user, means for providing optimal advice in response to security-related questions, and means for allowing the user to input new questions and receive advice in response to them through a user interface. This allows the user to receive advice specialized in a specific area, and in particular, appropriate advice in response to security-related questions.

[0317] A "user" is an individual or corporation that uses the system to input questions and receive advice from the generative AI.

[0318] A "question" is information or a question that a user inputs into a generative AI, which serves as a trigger for obtaining advice.

[0319] "Generative AI" refers to artificial intelligence that generates appropriate advice in response to user questions.

[0320] "Advice" refers to advice or suggestions provided by generative AI based on a user's questions.

[0321] "Marketing" refers to the activities and strategies aimed at promoting products and services.

[0322] "Research" is the activity of collecting and analyzing information on a particular topic or issue.

[0323] "Brainstorming" is an abbreviation of "brainstorming," a creative activity in which ideas are freely exchanged.

[0324] A "program" is a set of instructions or code that a computer executes.

[0325] A "study plan" is a specific plan or schedule for achieving learning goals.

[0326] "Recipe development" refers to the activity of coming up with cooking procedures and ingredients.

[0327] "Story writing" refers to the activity of creating a story or scenario.

[0328] "Security" refers to the measures and procedures for protecting information and physical assets.

[0329] A "user interface" is a screen or input device that allows a user to interact with a system.

[0330] A "means" is a method or device used to achieve a particular purpose.

[0331] A "system" is a structure or mechanism in which multiple elements work together to achieve a specific function.

[0332] The system for implementing this invention collects generative AI advice in response to user questions and provides advice tailored to specific domains, particularly those related to security.

[0333] System configuration

[0334] The system consists of the following main components:

[0335] 1. User device: The device on which the user enters their question and receives advice. This can be a smartphone or a computer.

[0336] 2. Server: Hosts the generative AI model and generates advice in response to user questions.

[0337] 3. User Interface: The interface through which users can enter their questions and receive advice.

[0338] Program processing

[0339] The server performs the following steps:

[0340] 1. Receiving a question: Receive a question entered from the user's terminal.

[0341] 2. Invoke a generative AI model: The received question is sent as a prompt to a generative AI model, such as OpenAI's GPT-3.

[0342] 3. Advice generation: A generative AI model generates advice in response to the question.

[0343] 4. Sending advice: The generated advice is sent to the user terminal.

[0344] Hardware and software used

[0345] Hardware: Smartphones, PCs, and servers with internet connectivity.

[0346] Software: Python, OpenAI API, front-end framework for user interface (e.g. React, Vue.js).

[0347] Specific examples

[0348] If a user asks, "Where is the best place to put a home security camera?" the system works as follows:

[0349] 1. A question is sent from the user device to the server.

[0350] 2. The server sends the question as a prompt to the generative AI model.

[0351] 3. A generative AI model generates advice in response to the question.

[0352] 4. The server sends the generated advice to the user device.

[0353] 5. Advice will be displayed on the user's device's user interface.

[0354] Prompt Sentence Examples

[0355] Security Question: Where is the best place to install a home security camera?

[0356] Please provide the best advice.

[0357] In this way, users can receive advice specific to a particular area, and in particular, get advice that is relevant to security-related questions.

[0358] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0359] Step 1:

[0360] The user inputs a question using a terminal. The input question is sent to the server through the user interface. The input data is a text question, such as "Where is the best place to install a home security camera?"

[0361] Step 2:

[0362] The server analyzes the received question and converts it into a format suitable for the generative AI model. In this conversion process, the question is formatted as a prompt. The input data is the user's question, and the output data is the prompt to be sent to the generative AI model.

[0363] Step 3:

[0364] The server sends a prompt to a generative AI model (e.g., OpenAI's GPT-3). The generative AI model receives the prompt and generates advice for the question. The input data is the prompt, and the output data is the generated advice.

[0365] Step 4:

[0366] The server analyzes the advice received from the generative AI model and converts it into a format that is easy for the user to understand. In this conversion process, the generated advice is formatted into text. The input data is the advice from the generative AI model, and the output data is the text to be displayed to the user.

[0367] Step 5:

[0368] The server sends the formatted advice to the user terminal, which displays the received advice on a user interface. The input data is the formatted advice, and the output data is the text displayed on the user interface.

[0369] Step 6:

[0370] The user checks the displayed advice and enters a new question if necessary. When a new question is entered, the process starts again from step 1. The input data is the user's new question, and the output data is the advice that is generated again.

[0371] 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.

[0372] "Example 1"

[0373] One embodiment of the present invention is a system incorporating an emotion engine. This system collects generative AI advice in response to user questions and provides it to the user. The emotion engine also recognizes the user's emotions and tailors the advice based on those emotions. For example, if the user feels frustrated, the emotion engine communicates this information to the generative AI, which then generates advice to calm the user.

[0374] "Example 2"

[0375] Another embodiment is a system in which an emotion engine provides optimal advice to a user based on the user's emotions. In this system, the emotion engine analyzes the user's emotions in real time and generates advice optimal for those emotions. For example, if the emotion engine senses that the user is feeling joy, the emotion engine communicates that information to a generative AI, and the AI ​​generates advice that amplifies that joy.

[0376] "Example 3"

[0377] In yet another embodiment, an emotion engine adjusts the generative AI's advice based on the user's emotions. In this system, the emotion engine analyzes the user's emotions in real time and adjusts the generative AI's advice based on those emotions. For example, if the user feels sad, the emotion engine communicates that information to the generative AI, which then generates advice to alleviate the sadness.

[0378] The processing flow of each embodiment will be described below.

[0379] "Example 1"

[0380] Step 1: The user asks the system a question.

[0381] Step 2: Generative AI generates advice in response to the user's question.

[0382] Step 3: The emotion engine recognizes the user's emotion.

[0383] Step 4: Adjust the generative AI's advice based on the emotions recognized by the emotion engine.

[0384] Step 5: Provide tailored advice to users.

[0385] "Example 2"

[0386] Step 1: The user asks the system a question.

[0387] Step 2: The emotion engine analyzes user emotions in real time.

[0388] Step 3: Based on the emotions analyzed by the emotion engine, the generative AI generates optimal advice for the user.

[0389] Step 4: Providing the generated advice to the user.

[0390] "Example 3"

[0391] Step 1: The user asks the system a question.

[0392] Step 2: The emotion engine analyzes user emotions in real time.

[0393] Step 3: Adjust the generative AI's advice based on the emotions analyzed by the emotion engine.

[0394] Step 4: Provide tailored advice to users.

[0395] Example 1

[0396] 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."

[0397] Conventional generative AI systems were unable to consider the user's emotions when providing advice in response to user questions, making it difficult to provide appropriate advice based on the user's psychological state. Furthermore, they lacked the functionality to provide guidelines and instructions for users to ask effective questions to generative AI, making it difficult for users to efficiently obtain the information they were looking for.

[0398] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for collecting generative AI advice in response to a user's question, means for analyzing the user's question using natural language processing technology, means for generating appropriate advice using a generative AI engine, means for recognizing the user's emotion using an emotion engine, means for adjusting the advice based on the user's emotion, and means for providing this advice to the user. This makes it possible to provide appropriate advice that takes the user's emotion into consideration, and to provide guidelines and instructions for the user to ask the generative AI effective questions.

[0399] "Generative AI" is an artificial intelligence technology that generates appropriate advice and information in response to users' questions and requests.

[0400] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[0401] A "generative AI engine" is a collection of software and algorithms that realizes generative AI, and has the ability to generate appropriate advice in response to user questions.

[0402] An "emotion engine" is a technology that recognizes a user's emotions and tailors appropriate advice based on those emotions.

[0403] A "user question" is a question or request that a user enters into the system.

[0404] "Advice" refers to advice or information provided by generative AI in response to a user's question.

[0405] "Analysis" is the process of understanding the intent and content of a user's question using natural language processing technology.

[0406] "Adjustment" is the process of appropriately modifying the generated advice based on the user's emotions recognized by the emotion engine.

[0407] "Providing" is the act of conveying the generated advice to the user.

[0408] MODE FOR CARRYING OUT THE INVENTION

[0409] This invention is a system that provides generative AI advice in response to user questions. The system includes natural language processing technology and a generative AI engine to analyze the user's question and generate appropriate advice. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the advice based on those emotions.

[0410] Hardware and software used

[0411] The server uses the following hardware and software to implement the system:

[0412] Natural language processing technology: Natural language processing models such as Google's BERT and OpenAI's GPT-3

[0413] Generative AI engine: Software and algorithms for realizing generative AI

[0414] Emotion engine: Emotion recognition technology such as Microsoft® Azure® Cognitive Services

[0415] Communication method: Communication between the server and the terminal using HTTP requests

[0416] System Operation

[0417] The user inputs a question through the device interface. For example, the user might input, "How should we develop a marketing strategy for a new product?" The device then sends this question to the server. The server then analyzes the received question using natural language processing technology and understands the intent of the question. Based on the analysis results, the generative AI engine generates appropriate advice.

[0418] Furthermore, the server uses an emotion engine to recognize the user's emotions. For example, if the emotion engine recognizes that the user is irritated, the server adjusts the advice generated by the generative AI engine. The adjusted advice will correspond to the user's emotions.

[0419] Specific examples

[0420] As a concrete example, consider the case where a user asks, "How should we develop a marketing strategy for a new product?" In this case, the server inputs the following prompt into the generative AI model:

[0421] Example prompt sentence:

[0422] A user asks: "How do I develop a marketing strategy for my new product?"

[0423] Prompt for the generative AI model: "What steps should I take to develop a marketing strategy for a new product? Please provide specific advice."

[0424] Based on this prompt, the generative AI model generates the following advice:

[0425] "To develop a marketing strategy for a new product, it is important to first conduct a competitor analysis and understand the target market. Next, evaluate the product's strengths and weaknesses and create a marketing message based on that. It is also necessary to choose the right advertising channels and carry out effective promotion."

[0426] If the emotion engine identifies the user's emotion as "frustrated," the generative AI will adjust its advice as follows:

[0427] "First, take a deep breath and relax. Then, calmly conduct a competitor analysis and understand your target market. Next, evaluate the strengths and weaknesses of your product and create a marketing message based on that. You also need to choose the right advertising channels and promote it effectively."

[0428] In this way, users can view advice on their device screen. This system allows users to receive appropriate advice based on their emotions, and also provides guidelines and instructions for asking effective questions to the generative AI.

[0429] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0430] Step 1: User enters question

[0431] A user inputs a question through the terminal interface. For example, the user inputs, "How should we develop a marketing strategy for a new product?" This input is stored as text data on the terminal.

[0432] Step 2: The device sends the question to the server

[0433] The device sends the user-entered question to the server as an HTTP POST request, for example to the endpoint https: / / example.com / api / questions. This request includes the user's question.

[0434] Step 3: The server receives the question and analyzes it using natural language processing technology

[0435] The server analyzes the received question using natural language processing technology. Specifically, it uses models such as Google's BERT and OpenAI's GPT-3 to understand the intent of the question. This analysis extracts keywords and context from the question. The input is the user's question, and the output is the analysis result.

[0436] Step 4: The server generates advice using a generative AI engine based on the analysis results.

[0437] The server uses a generative AI engine to generate advice based on the analysis results. For example, if a user asks, "How should we develop a marketing strategy for a new product?", the generative AI engine will generate advice such as, "Analyze competitors, understand the target market, and evaluate the product's strengths and weaknesses." The input is the analysis results, and the output is the generated advice.

[0438] Step 5: The server recognizes the user's emotion using the emotion engine.

[0439] The server uses an emotion engine to recognize the user's emotions. For example, it uses Microsoft's Azure Cognitive Services to analyze emotions from the user's voice and facial expressions. This analysis determines whether the user is irritated or not. The input is the user's voice and facial expression data, and the output is the emotion recognition result.

[0440] Step 6: The server adjusts the advice based on the emotion

[0441] The server adjusts the advice generated by the generative AI engine based on information obtained from the emotion engine. For example, if the emotion engine recognizes that the user is irritated, the server will adjust the advice to something like, "First, take a deep breath and relax. Then, calmly analyze the situation." The input is the emotion recognition result and the generated advice, and the output is the adjusted advice.

[0442] Step 7: The server sends the final advice to the device

[0443] The server sends the final advice to the terminal as an HTTP response, for example, in the form {"advice": "First, take a deep breath and relax. Then, calmly analyze the situation."}. The input is the adjusted advice, and the output is the HTTP response.

[0444] Step 8: The device displays the advice to the user

[0445] The device displays the advice received from the server to the user. The user can see advice on the device screen such as "First, take a deep breath and relax. Then, calmly analyze the situation." The input is the HTTP response from the server, and the output is the advice displayed to the user.

[0446] (Application example 1)

[0447] 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."

[0448] Conventional advice systems using generative AI provide uniform advice without considering the user's emotions, resulting in a decline in user satisfaction and reliability. Furthermore, there was a lack of specific applications for improving the shopping experience in physical stores. This resulted in the issue of users being unable to receive appropriate information or advice tailored to their emotions when asking about products.

[0449] 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.

[0450] In this invention, the server includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe creation, and story creation; means for providing this advice to the user; means including an emotion engine for recognizing the user's emotions and adjusting advice based on those emotions; and means for providing product information, emotion recognition, and personalized advice as an application installed on a smartphone in a physical store. This makes it possible to provide appropriate advice based on the user's emotions and improve the shopping experience in a physical store.

[0451] "Means for gathering generative AI advice in response to user questions" refers to an artificial intelligence engine that receives questions from users and generates appropriate advice in response to them.

[0452] "A tool for a wide range of areas, including marketing, research, brainstorming, programming, study plans, recipe creation, and story writing" refers to a function that provides advice to users on questions in a variety of fields.

[0453] "Means for providing these pieces of advice to the user" refers to the interface or communication means for conveying the generated advice to the user.

[0454] "Means including an emotion engine that recognizes a user's emotion and adjusts advice based on the emotion" refers to an engine that analyzes a user's emotion and adjusts the content and tone of advice based on the analysis result.

[0455] "A means of providing product information, recognizing emotions, and offering personalized advice as an application installed on a smartphone in a physical store" refers to an application installed on a smartphone that provides product information, recognizes users' emotions, and offers personalized advice in order to improve the shopping experience in a physical store.

[0456] A system for implementing this invention includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation; means for providing this advice to users; means including an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions; and means for providing product information, emotion recognition, and personalized advice as an application installed on a smartphone in a physical store.

[0457] The server receives questions from users and uses a generative AI engine to generate appropriate advice in response. The generative AI engine uses natural language processing technology to analyze the user's question and generate appropriate advice. For example, if a user asks, "How should I coordinate this shirt?", the generative AI engine will generate advice such as, "That shirt looks casual and stylish when paired with jeans. Also, adding accessories will make it even more stylish!"

[0458] The device uses a camera and microphone to recognize the user's emotions through an application installed on the smartphone. Emotion recognition is performed using software. It recognizes emotions from the user's voice and facial expressions and sends the results to a generative AI engine. For example, if the device recognizes that the user is excited, the generative AI engine will use that information to adjust the tone of its advice.

[0459] Users can receive the generated advice through a smartphone application. The application has functions to provide product information, recognize emotions, and provide personalized advice. For example, if a user asks, "How should I coordinate this shirt?" and emotion recognition determines that the user is "excited," the generative AI will provide advice such as, "That shirt looks casual and stylish when paired with jeans. Also, adding some accessories will make it even more stylish!"

[0460] An example prompt is:

[0461] User Question: How should I coordinate this shirt?

[0462] User sentiment: Excited

[0463] Please provide appropriate advice.

[0464] In this way, it is possible to provide appropriate advice based on the user's emotions and improve the shopping experience in physical stores.

[0465] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0466] Step 1:

[0467] The user launches the application on their smartphone and enters a question.

[0468] Input: User question (e.g., "How do I coordinate this shirt?")

[0469] Output: User question data

[0470] Specific behavior: The user enters a question into the application's input field and presses the submit button.

[0471] Step 2:

[0472] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice and recognize emotions.

[0473] Input: User's facial and voice data

[0474] Output: User's emotion data (e.g. "Excited")

[0475] How it works: The device uses emotion recognition software to analyze emotions from captured facial expressions and voice.

[0476] Step 3:

[0477] The terminal transmits the user's question data and emotion data to the server.

[0478] Input: User question data, user emotion data

[0479] Output: Data sent to the server

[0480] Specific operation: The terminal sends the user's question data and emotion data to the server via the Internet.

[0481] Step 4:

[0482] The server uses a generative AI engine to analyze the user's question and generate appropriate advice.

[0483] Input: User question data, user emotion data

[0484] Output: Generated advice (e.g., "That shirt looks great with jeans for a casual look. Plus, adding some accessories will make it even more stylish!")

[0485] Specific operation: The server uses the OpenAI API to generate prompt sentences based on the user's question and emotions, and sends them to the AI ​​engine to generate advice.

[0486] Step 5:

[0487] The server transmits the generated advice to the terminal.

[0488] Input: Generated advice

[0489] Output: Advice data sent to the terminal

[0490] Specific operation: The server transmits the generated advice to the terminal via the Internet.

[0491] Step 6:

[0492] The terminal displays the received advice to the user.

[0493] Input: Received advice data

[0494] Output: Advice displayed to the user

[0495] Specific operation: The device displays the generated advice on the application screen so that the user can check it.

[0496] Example 2

[0497] 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."

[0498] Conventional generative AI systems only provided general advice in response to user questions, making it difficult to provide specific advice tailored to a particular domain. Furthermore, they were unable to provide advice that took the user's emotions into account, preventing them from increasing user satisfaction. Furthermore, there was a lack of guidelines or instructions for users to effectively ask generative AI questions, making it difficult for users to accurately obtain the information they were looking for.

[0499] 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.

[0500] In this invention, the server includes: means for collecting generative AI advice in response to a user's question; means for handling a wide range of areas, such as marketing, research, brainstorming, program creation, lesson planning, recipe creation, and story creation; means for providing this advice to the user; means including an emotion engine for analyzing the user's emotions in real time and generating optimal advice based on those emotions; means for analyzing the user's request and forwarding it to an appropriate AI module; means for the AI ​​module to process data based on the request and generate results; and means for displaying the generated results to the user. This makes it possible to provide specific advice specialized for a specific area in response to the user's question and generate optimal advice that takes the user's emotions into consideration. Furthermore, by providing guidelines and instructions for the user to ask the generative AI effective questions, the user can accurately obtain the information they are looking for.

[0501] "Generative AI" is artificial intelligence that automatically generates advice and suggestions based on users' questions and requests.

[0502] The "emotion engine" is part of a system that analyzes users' emotions in real time and generates optimal advice based on those emotions.

[0503] An "AI module" is an artificial intelligence component that has specialized expertise in a particular area and provides specific advice in response to user questions about that area.

[0504] A "request" is a question or request that a user makes to the system.

[0505] "Processing data" means retrieving the necessary information based on the user's request and generating appropriate advice and suggestions.

[0506] "Generating results" refers to creating advice or suggestions that are obtained after the AI ​​module processes the data.

[0507] "Displaying to the user" means displaying the generated advice or suggestion on the user's device.

[0508] "Marketing" refers to all activities aimed at promoting products and services.

[0509] "Research" is the activity of collecting and analyzing information on a particular topic or issue.

[0510] "Brainstorming" is an abbreviation of "brainstorming," a creative activity in which ideas are freely exchanged.

[0511] "Programming" is the activity of designing and coding computer programs.

[0512] "Learning planning" is the activity of planning learning goals and methods.

[0513] "Recipe creation" is the activity of coming up with new recipes for dishes.

[0514] "Story writing" is the activity of creating a story or scenario.

[0515] This invention is a system that collects generative AI advice in response to user questions and is applicable to a wide range of fields, including marketing, research, brainstorming, program creation, lesson planning, recipe creation, story creation, etc. It also includes an emotion engine that analyzes user emotions in real time and provides optimal advice based on those emotions.

[0516] Hardware and software used

[0517] The system uses the following hardware and software:

[0518] Server: Parses requests, selects AI modules, generates and sends results.

[0519] Terminal: Enters requests from the user and displays results from the server.

[0520] Generative AI models: Generate advice and suggestions based on user questions.

[0521] Emotion Engine: Analyzes user emotions in real time and generates optimal advice based on those emotions.

[0522] Data processing and calculation

[0523] When the server receives a request from a user, it analyzes the request and forwards it to the appropriate AI module, which processes the data based on the request and generates a result, which is then sent to the terminal via the server and displayed to the user.

[0524] For example, consider the case where a user types, "I don't know what to make for dinner tonight." In this case, the server sends a request to the recipe-creation AI module, which suggests new recipes based on the ingredients the user has on hand and their preferences.

[0525] Prompt Sentence Examples

[0526] Here are some examples of prompts:

[0527] "The ingredients I have on hand are chicken and broccoli. Can you suggest a new recipe using them?"

[0528] "I'm a little tired today, so could you suggest some easy dinner recipes?"

[0529] This system allows users to receive specific advice tailored to a particular area, and through an emotion engine, they can get optimal advice based on their emotions, thereby increasing user satisfaction.

[0530] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0531] Step 1:

[0532] The user inputs a request from the terminal.

[0533] Specifically, the user opens an application on their smartphone or computer and types "I don't know what to make for dinner tonight" into a text box.

[0534] Input: A user question or request (e.g., "I don't know what to make for dinner tonight.")

[0535] Output: Request typed into the terminal

[0536] Step 2:

[0537] The device sends a request to the server.

[0538] The terminal converts the entered text into JSON format and sends it to the server as an HTTP request.

[0539] Input: The request typed into the terminal

[0540] Output: JSON representation of the request sent to the server

[0541] Step 3:

[0542] The server parses the request and forwards it to the appropriate AI module.

[0543] The server parses the received JSON data and extracts keywords such as "dinner" and "recipe," and then forwards the request to the recipe-creation AI module.

[0544] Input: The JSON formatted request sent to the server

[0545] Output: The request forwarded to the AI ​​module

[0546] Step 4:

[0547] The AI ​​module processes the data based on the request and generates the results.

[0548] The recipe creation AI module searches the database for recipes using "chicken" and "broccoli" and generates a recipe for "stir-fried chicken and broccoli."

[0549] Input: The request forwarded to the AI ​​module

[0550] Output: Generated recipe information

[0551] Step 5:

[0552] The server transmits the generated results to the terminal.

[0553] The server converts the generated recipe into JSON format and sends it to the terminal as an HTTP response.

[0554] Input: Generated recipe information

[0555] Output: Recipe information in JSON format sent to the device

[0556] Step 6:

[0557] The terminal displays the results to the user.

[0558] The device parses the received JSON data and displays the recipe for "Chicken and Broccoli Stir-fry" on the application interface.

[0559] Input: JSON format recipe information sent to the terminal

[0560] Output: Recipe information displayed to the user

[0561] In this way, the system works in cooperation with the user, terminal, and server to provide the user with the most suitable advice and suggestions.

[0562] (Application example 2)

[0563] 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."

[0564] In traditional brick-and-mortar shopping experiences, users had limited options for obtaining appropriate advice when they had difficulty choosing a product. It was also difficult to provide personalized support based on the user's emotions, which could result in a lower quality shopping experience. Furthermore, there was a lack of guidelines for users to effectively ask generative AI questions, which prevented users from improving the way they asked questions, making it difficult to obtain appropriate advice.

[0565] 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.

[0566] In this invention, the server includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas, such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation; means for providing this advice to the user; an emotion engine for analyzing user emotions in real time; means for generating optimal advice based on the emotion engine; means for providing specific advice in response to user questions in physical stores; and means including an application to be installed on a smartphone. This allows users to obtain specific advice in real time to improve their shopping experience in physical stores, realizing personalized responses based on the user's emotions. Furthermore, guidelines are provided for users to ask effective questions to the generative AI, improving the way they ask questions and obtaining more appropriate advice.

[0567] "Means for collecting advice from generative AI in response to user questions" is a function for collecting advice provided by generative AI in response to questions entered by users.

[0568] "A means to handle a wide range of areas, including marketing, research, brainstorming, programming, learning plans, recipe creation, and story writing" is a function that uses AI modules specialized in various fields to provide specific advice in each area.

[0569] The "means for providing these pieces of advice to the user" refers to a function for presenting the collected advice to the user in an appropriate format.

[0570] The "emotion engine that analyzes user emotions in real time" is a function that analyzes emotions from user input and behavior and obtains the results in real time.

[0571] The "means for generating optimal advice based on an emotion engine" is a function for generating optimal advice for a user based on the user's emotions analyzed by the emotion engine.

[0572] "Means for providing specific advice in response to user questions in physical stores" is a function for providing specific and appropriate advice in response to questions asked by users in physical stores.

[0573] "Means including applications installed on smartphones" refers to means for providing various functions to users through applications installed on smartphones.

[0574] A system for implementing this invention includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation; means for providing this advice to users; an emotion engine for analyzing user emotions in real time; means for generating optimal advice based on the emotion engine; means for providing specific advice in response to user questions in a physical store; and means including an application to be installed on a smartphone.

[0575] Hardware and Software

[0576] This system uses the following hardware and software:

[0577] Hardware: Smartphone

[0578] Software: Python, emotion recognition library, various AI modules

[0579] Data processing and calculation

[0580] The server receives questions entered by users on their smartphones and generates advice using a generative AI module. The generated advice is then optimized by an emotion engine that analyzes the user's emotions in real time. The emotion engine uses an emotion recognition library to analyze the user's emotions and provides optimal advice based on the results.

[0581] Specific examples

[0582] When a customer asks, "I don't know what to make today," an app installed on their smartphone receives the question. The emotion engine analyzes the user's emotion as "confusion," and the AI ​​module "suggests new recipes based on the ingredients on hand and their preferences."

[0583] Prompt Sentence Examples

[0584] User Input: "I don't know what to make today"

[0585] Sentiment analysis result: "confused"

[0586] Generated advice: "Tell us what ingredients you have on hand and we'll suggest a new recipe for you."

[0587] This way, users can get specific advice in real time to improve their in-store shopping experience.

[0588] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0589] Step 1:

[0590] The user types a question into their smartphone.

[0591] Input: User question (e.g. "I don't know what to cook today")

[0592] How it works: An application on a smartphone receives user input.

[0593] Output: User question text data

[0594] Step 2:

[0595] The terminal sends the user's question to the server.

[0596] Input: User question text data

[0597] How it works: The smartphone application sends question text data to the server.

[0598] Output: Question text data sent to the server

[0599] Step 3:

[0600] The server receives the user's question and analyzes the emotion using an emotion engine.

[0601] Input: Question text data sent to the server

[0602] How it works: The server uses an emotion recognition library to analyze the user's emotions from the question text data.

[0603] Output: User emotion data (e.g. "confused")

[0604] Step 4:

[0605] The server selects the optimal AI module based on the emotion data.

[0606] Input: User emotion data

[0607] How it works: The server analyzes the emotion data and selects the appropriate AI module.

[0608] Output: Selected AI module

[0609] Step 5:

[0610] The server uses the selected AI module to generate advice for the user's question.

[0611] Input: User question text data, selected AI module

[0612] How it works: The server uses the selected AI module to generate specific advice for the user's question.

[0613] Output: The generated advice (e.g., "Tell me what ingredients you have on hand and I'll suggest a new recipe.")

[0614] Step 6:

[0615] The server transmits the generated advice to the terminal.

[0616] Input: Generated advice

[0617] How it works: The server sends the generated advice to the smartphone application.

[0618] Output: Advice sent to your phone

[0619] Step 7:

[0620] The terminal displays the advice to the user.

[0621] Input: Advice sent to your phone

[0622] How it works: A smartphone application displays advice to the user.

[0623] Output: Advice displayed to the user (e.g., "Tell me what ingredients you have on hand and I'll suggest a new recipe for you.")

[0624] Example 3

[0625] 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."

[0626] Conventional generative AI systems provide advice without taking the user's emotional state into consideration, making it difficult to obtain advice that is appropriate for the user's emotions. Also, when users input new questions, they have few opportunities to learn how to ask effective questions, which can lead to a decline in the quality of advice from generative AI.

[0627] The identification process by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes means for collecting generative AI advice in response to user questions, means for analyzing user emotions in real time using a sentiment analysis engine, and means for adjusting the generative AI advice based on the user emotions. This makes it possible to provide advice suited to the user's emotions. In addition, by including means for providing a user interface that allows the user to input a new question and receive advice in response to it, the user can learn how to ask effective questions and improve the quality of advice from the generative AI.

[0628] "Generative AI" is an artificial intelligence system that generates advice and information in natural language based on user input.

[0629] A "sentiment analysis engine" is software or a system for analyzing a user's input text and identifying its emotional state in real time.

[0630] A "user interface" is software or a system that provides screens and input fields for a user to interact with the system.

[0631] "Means of gathering advice" refers to the functions and processes used by generative AI to collect the advice generated in response to user questions.

[0632] "Means for tailoring advice" refers to the functions and processes for adapting the generative AI's advice to the user's emotional state based on the results of the sentiment analysis engine.

[0633] "Real-time analysis means" means the functionality or process that performs sentiment analysis the moment a user input is made and makes the results immediately available.

[0634] MODE FOR CARRYING OUT THE INVENTION

[0635] This invention is a system in which a generative AI provides advice in response to a user's question and adjusts the advice based on the user's emotional state. The system includes a server, a terminal, a user interface, a sentiment analysis engine, and a generative AI model.

[0636] Hardware and software used

[0637] Hardware: Servers, user devices (PCs, smartphones)

[0638] Software: Generative AI models (e.g., GPT-4), sentiment analysis engines (e.g., IBM Watson® Tone Analyzer), user interfaces (web applications)

[0639] Specific operation of the system

[0640] 1. User enters question:

[0641] A user uses a terminal to enter a question into a user interface.

[0642] Example: A user types "I've been feeling tired at work lately. How can I refresh myself?" into a text input field in a web application and clicks the submit button.

[0643] 2. Perform sentiment analysis:

[0644] The server receives the user's input and sends it to the sentiment analysis engine.

[0645] A sentiment analysis engine analyzes the user's input text to identify their emotional state.

[0646] Example: A sentiment analysis engine detects "fatigue" and returns the result to the server.

[0647] 3. Advice Generation:

[0648] The server sends the results of the sentiment analysis to the generative AI model.

[0649] A generative AI model generates appropriate advice based on the user's emotional state.

[0650] Example: A generative AI model generates advice such as "Take a short break and do some light exercise" and returns the result to the server.

[0651] 4. Display Advice:

[0652] The server sends the generated advice to the user interface.

[0653] The user interface displays the advice in text format.

[0654] Example: The user interface displays "Take short breaks and engage in some light exercise."

[0655] Examples and prompts

[0656] Examples:

[0657] A user types, "I've been feeling tired at work lately. How can I refresh myself?"

[0658] The server sends the input to a sentiment analysis engine, which detects "fatigue."

[0659] The server sends the results of the sentiment analysis to a generative AI model, which then generates advice such as "Take a short break and do some light exercise."

[0660] The server sends the generated advice to the user interface, which displays it.

[0661] Example prompt sentence:

[0662] "If a user types, 'I've been feeling tired at work lately. How can I refresh myself?' the sentiment analysis engine will detect 'fatigue,' and the generative AI model will generate advice such as 'Take a short break and try some light exercise.'"

[0663] This system allows users to receive advice suited to their own emotional state and learn how to ask more effective questions. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0664] Step 1: User enters question

[0665] A user uses a terminal to enter a question into a user interface.

[0666] Input: A user types "I've been feeling tired at work lately. How can I refresh myself?" into a text input field in a web application and clicks the submit button.

[0667] Specific behavior: The user enters a question in the text input field and clicks the submit button, which sends the question to the server.

[0668] Output: The user's question is sent to the server.

[0669] Step 2: Perform sentiment analysis

[0670] The server receives the user's input and sends it to the sentiment analysis engine.

[0671] Input: The user's question text.

[0672] What happens: The server sends the user's input text to the sentiment analysis engine as an API request.

[0673] Data processing: A sentiment analysis engine analyzes the user's input text to identify their emotional state.

[0674] Output: The sentiment analysis engine detects "fatigue" and returns the result to the server.

[0675] Step 3: Advice Generation

[0676] The server sends the results of the sentiment analysis to the generative AI model.

[0677] Input: Sentiment analysis result "fatigue".

[0678] Specific operation: The server sends a prompt sentence containing "fatigue" as a result of sentiment analysis to the generative AI model as an API request.

[0679] Data computation: Generative AI models generate appropriate advice based on the user's emotional state.

[0680] Output: The generative AI model generates advice such as "Take a short break and do some light exercise" and returns the result to the server.

[0681] Step 4: View Advice

[0682] The server sends the generated advice to the user interface.

[0683] Input: Advice generated by a generative AI model.

[0684] Specific behavior: The server sends the generated advice "Take a short break and do some light exercise" to the user interface as an API response.

[0685] Output: The user interface displays the advice in text format.

[0686] What it does: The user interface displays the advice on the screen so the user can view it.

[0687] (Application example 3)

[0688] 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."

[0689] Conventional generative AI systems provide advice without considering the user's emotional state, making it impossible to provide appropriate advice based on the user's emotions. Furthermore, there were no systems that could provide emotion-based advice when the user entered a new question. For this reason, flexible responses based on the user's emotions are required.

[0690] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for collecting generative AI advice in response to user questions, means for handling a wide range of areas such as work such as marketing, research, brainstorming, and programming, study plans, recipe development, and story creation, means for providing this advice to the user, an emotion engine for analyzing the user's emotions in real time, means for adjusting the generative AI advice based on the user's emotions, and means for providing an input field in which the user can input a new question and receive advice in response to it. This makes it possible to provide appropriate advice according to the user's emotions.

[0691] "Means for collecting advice from generative AI in response to user questions" is a function for collecting advice provided by generative AI in response to questions entered by users.

[0692] "A means to cover a wide range of areas, including marketing, research, brainstorming, programming, learning plans, recipe development, and story writing" is a function that enables generative AI to provide appropriate advice in a variety of fields.

[0693] "Means for providing these pieces of advice to users" refers to a function for displaying the advice provided by the generative AI to users.

[0694] An "emotion engine that analyzes user emotions in real time" is a system that analyzes a user's emotional state in real time based on their input and actions.

[0695] "Means for adjusting the advice of the generative AI based on the user's emotions" refers to a function that appropriately changes the content of the advice provided by the generative AI according to the user's emotional state analyzed by the emotion engine.

[0696] "Means for providing an input field where users can enter new questions and receive advice in response" refers to a function that provides an interface where users can enter new questions and receive advice from generative AI in response to those questions.

[0697] A system for implementing this invention includes means for collecting generative AI advice in response to user questions, means for addressing a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story writing, means for providing this advice to the user, an emotion engine for analyzing user emotions in real time, means for adjusting the generative AI advice based on the user emotions, and means for providing an input field in which the user can enter new questions and receive advice in response to them.

[0698] System Program

[0699] The program of this system operates as follows.

[0700] 1. How to gather generative AI advice for user questions:

[0701] The server receives the question entered by the user and generates advice for that question using a generative AI model, such as OpenAI's GPT-3.

[0702] 2. A tool for a wide range of areas, including marketing, research, brainstorming, programming, lesson planning, recipe creation, story writing, etc.:

[0703] The server uses generative AI models to provide appropriate advice for questions in various fields, allowing users to receive advice in a wide range of areas.

[0704] 3. How these advices are provided to users:

[0705] The server displays the generated advice to the user through a user interface, which displays the advice in a text format so that the user can easily understand it.

[0706] 4. Sentiment engine that analyzes user sentiment in real time:

[0707] The server uses an emotion engine to analyze emotions from the user's input text in real time.

[0708] 5. How to tailor generative AI advice based on user sentiment:

[0709] The server then adjusts the advice provided by the generative AI based on the user's emotional state as analyzed by the emotion engine. For example, if the user is feeling anxious, the server generates advice to alleviate that anxiety.

[0710] 6. Provide an input field where users can enter new questions and receive advice on them:

[0711] The server provides an interface where users can enter new questions and receive advice from the generative AI on those questions.

[0712] Specific examples

[0713] For example, if a user types, "I've been seeing a lot of suspicious people around my house lately and it makes me anxious," the emotion engine will detect the word "anxiety" and generate the following prompt:

[0714] My users are worried. Can you offer some security advice?

[0715] If you feed this prompt to a generative AI model, it might generate advice like this:

[0716] "If you've noticed a lot of suspicious people around your home recently, consider the following:

[0717] 1. Install security cameras around your home.

[0718] 2. Share information with neighbors and increase patrols.

[0719] 3. If you see anyone suspicious, report it to the police immediately.

[0720] 4. Double-check that your doors and windows are locked and install a security system.

[0721] In this way, it becomes possible to provide appropriate advice according to the user's emotions.

[0722] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0723] Step 1:

[0724] A user inputs a question using a terminal. The input question is sent to the server as text data. The input data is text that includes the content of the user's question.

[0725] Step 2:

[0726] The server sends the received user question to a generative AI model. The generative AI model uses, for example, OpenAI's GPT-3, to generate advice for the question. The input data is text containing the user's question, and the output data is text containing the generated advice.

[0727] Step 3:

[0728] The server displays the generated advice in a user interface. The user interface displays the advice in a text format so that the user can easily understand it. The input data is the text containing the generated advice, and the output data is the text displayed in the user interface.

[0729] Step 4:

[0730] The server uses an emotion engine to analyze emotions from user input text in real time. The input data is text containing the user's question, and the output data is data indicating the analyzed emotional state.

[0731] Step 5:

[0732] The server appropriately adjusts the content of the advice provided by the generative AI based on the user's emotional state analyzed by the emotion engine. For example, if the user is feeling anxious, the server generates advice to alleviate the anxiety. The input data is data indicating the analyzed emotional state, and the output data is text containing the adjusted advice.

[0733] Step 6:

[0734] The server provides an interface where users can enter new questions and receive advice from the generative AI for those questions. The input data is text containing the newly entered question by the user, and the output data is text containing advice provided by the generative AI.

[0735] 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.

[0736] 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.

[0737] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0738] 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.

[0739] [Second embodiment]

[0740] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0741] 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.

[0742] 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).

[0743] 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.

[0744] 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.

[0745] 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).

[0746] 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.

[0747] 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.

[0748] 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.

[0749] 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.

[0750] 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.

[0751] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0752] "Example 1"

[0753] In one embodiment of the present invention, the means for gathering generative AI advice includes an AI engine that receives a question from a user and generates generative AI advice in response to the question. The AI ​​engine uses natural language processing techniques to analyze the user's question and generate appropriate advice. For example, if a user asks, "How should I develop a marketing strategy?", the AI ​​engine generates advice such as, "Analyze your competitors, understand your target market, evaluate the strengths and weaknesses of your product, etc."

[0754] "Example 2"

[0755] In one embodiment of the present invention, the means for handling a wide range of tasks, such as marketing, research, brainstorming, programming, learning plans, recipe creation, and story writing, includes AI modules specialized in each area. These AI modules have expertise in their respective areas and generate specific advice in response to user questions. For example, if a user asks, "I don't know what to make," an AI module specialized in recipe creation generates advice such as, "I'll suggest a new recipe based on the ingredients you have on hand and your preferences."

[0756] "Example 3"

[0757] Furthermore, in one embodiment of the present invention, the means for providing the user with these pieces of advice includes a user interface. The user interface displays the generated advice to the user, allowing the user to easily understand the advice and take action based on it. For example, the user interface displays the generated advice in a text format so that the user can read it. The user interface also provides an input field where the user can enter a new question and receive advice in response to the question.

[0758] The processing flow of each embodiment will be described below.

[0759] "Example 1"

[0760] Step 1: Receiving a question from the user In this step, a question from the user is received through the user interface.

[0761] Step 2: Analyze the question and generate advice. In this step, the AI ​​engine uses natural language processing technology to analyze the user's question and generate appropriate advice.

[0762] Step 3: Providing the generated advice to the user. In this step, the generated advice is displayed to the user through a user interface, allowing the user to easily understand the advice and take action based on it.

[0763] "Example 2"

[0764] Step 1: Receiving a question from the user In this step, a question from the user is received through the user interface.

[0765] Step 2: Analyze the question and select an AI module specialized in a specific domain. In this step, the AI ​​engine uses natural language processing technology to analyze the user's question and select an AI module specialized in a specific domain based on the content of the question.

[0766] Step 3: Generate advice using the selected AI module and provide it to the user. In this step, the selected AI module generates specific advice for the user's question and displays the generated advice to the user through the user interface.

[0767] "Example 3"

[0768] Step 1: Receiving a question from the user In this step, a question from the user is received through the user interface.

[0769] Step 2: Analyze the question and generate advice. In this step, the AI ​​engine uses natural language processing technology to analyze the user's question and generate appropriate advice.

[0770] Step 3: Providing the generated advice to the user. In this step, the generated advice is displayed to the user through a user interface, allowing the user to easily understand the advice and take action based on it.

[0771] Step 4: User Enters New Question: In this step, the user interface provides an input field where the user can enter a new question and receive advice on it.

[0772] Example 1

[0773] 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."

[0774] Conventional generative AI systems can have difficulty providing appropriate advice in response to user questions. Furthermore, they lack guidelines and instructions for users to effectively ask generative AI, which can lead to problems with users being unable to accurately obtain the information they are looking for. Furthermore, they lack the flexibility to handle a wide range of tasks, including marketing, research, brainstorming, and programming.

[0775] 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.

[0776] In this invention, the server includes means for receiving a user's question, means including an AI engine using natural language processing technology for analyzing the received question, means for generating appropriate advice based on the analyzed question, means for providing the generated advice to the user, means for dealing with a wide range of areas such as marketing, research, brainstorming, programming and other work, study plans, recipe creation, story creation, etc., and means for providing this advice to the user. This enables the user to obtain appropriate advice in a wide range of areas, and also provides instructions for improving the way questions are asked and guidelines for asking more effective questions, allowing the user to accurately obtain the information they are looking for.

[0777] The "means for receiving a user's question" is an interface that allows the system to receive a question entered by the user.

[0778] "AI engine using natural language processing technology" refers to artificial intelligence technology that analyzes user questions and generates appropriate advice.

[0779] "Means for generating appropriate advice based on the analyzed questions" refers to the process by which the AI ​​engine creates specific advice for the user based on the analysis results.

[0780] "Means for providing generated advice to a user" refers to a method for displaying or transmitting advice generated by an AI engine to a user.

[0781] "A tool for a wide range of areas, including marketing, research, brainstorming, programming, study planning, recipe creation, and story writing" is a function that provides appropriate advice to users' questions in various fields.

[0782] "Instructions for improving how you ask questions" provide specific advice or guidelines to help users ask questions more effectively.

[0783] The "Guidelines for Asking More Effective Questions" provide guidelines and methods for users to ask appropriate questions to generative AI.

[0784] This invention is a system that provides generative AI advice in response to a user's question. This system includes an AI engine that receives the user's question, analyzes it using natural language processing technology, and generates appropriate advice. Specific embodiments of this system are described below.

[0785] First, the user enters a question using their own device (e.g., a PC or smartphone). For example, the user might enter, "How should I develop a marketing strategy?" This question is sent from the device to the server. Data is sent over the Internet.

[0786] The server passes the received question to an AI engine. This AI engine uses natural language processing technology to analyze the user's question. Specifically, a generative AI model such as GPT-4 is used as the AI ​​engine. The AI ​​engine understands the content of the question and generates appropriate advice. For example, it generates advice such as "analyze competitors, understand the target market, and evaluate the strengths and weaknesses of the product."

[0787] The generated advice is sent to the user's device via the server. The device displays the received advice to the user. The user can check the displayed advice and use it as reference.

[0788] As a concrete example, the following prompt sentence can be input to a generative AI model:

[0789] Example prompt sentence:

[0790] How do I create a marketing strategy?

[0791] Given this prompt, the AI ​​engine might generate the following advice:

[0792] Example of generated advice:

[0793] "To develop a marketing strategy, it is important to first analyze your competitors, then understand your target market, and finally evaluate the strengths and weaknesses of your product."

[0794] In this way, users can get helpful advice for specific questions, and the system can be used in a wide range of areas, including marketing, research, brainstorming, programming, lesson planning, recipe creation, story writing, and more.

[0795] Additionally, the generative AI's advice includes instructions to improve the way users ask questions and guidelines for asking more effective questions, allowing users to use the generative AI more effectively.

[0796] To implement this system, it is important to use an appropriate combination of hardware and software, such as servers, terminals, and AI engines that use natural language processing technology (e.g., GPT-4).

[0797] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0798] Step 1:

[0799] The user enters a question

[0800] A user inputs a question using their own device (e.g., a PC or smartphone). For example, the user might input, "How should I develop a marketing strategy?" This input question becomes the starting point for the system's processing.

[0801] Step 2:

[0802] The device sends a question to the server

[0803] The terminal sends the question entered by the user to the server via the Internet using the HTTPS protocol. The input is the user's question, and the output is the question data sent to the server.

[0804] Step 3:

[0805] The server receives the question and passes it to the AI ​​engine.

[0806] The server receives questions sent from the device. The received questions are passed to the AI ​​engine in the server. The input is the question data received from the device, and the output is the question data passed to the AI ​​engine.

[0807] Step 4:

[0808] An AI engine analyzes the question and generates advice

[0809] The AI ​​engine analyzes the user's question using natural language processing technology. Specifically, it uses a generative AI model such as GPT-4 as the AI ​​engine. Based on the analyzed question, the AI ​​engine generates appropriate advice. For example, it generates advice such as "analyze competitors, understand the target market, and evaluate the strengths and weaknesses of the product." The input is the question data passed from the server, and the output is the generated advice.

[0810] Step 5:

[0811] The server receives the generated advice and sends it to the device.

[0812] The server receives the advice generated by the AI ​​engine. The received advice is then sent to the user's device via the Internet. The HTTPS protocol is again used for transmission. The input is the advice received from the AI ​​engine, and the output is the advice sent to the device.

[0813] Step 6:

[0814] The device displays the advice to the user.

[0815] The terminal receives advice sent from the server. The received advice is displayed in a format that is easy for the user to view. The user can check the displayed advice and use it as a reference. The input is the advice received from the server, and the output is the advice displayed to the user.

[0816] (Application example 1)

[0817] 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."

[0818] Conventional advice systems using generative AI allow users to receive advice by inputting specific questions, but there is a lack of means to provide appropriate advice in real time when selecting products in physical stores. This makes it difficult for users to obtain appropriate information when choosing products, resulting in a long time required for purchasing decisions. Furthermore, there is a lack of guidelines for users to ask effective questions to generative AI or instructions for improving the way questions are asked, which leads to a decline in the quality of the advice users receive.

[0819] 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.

[0820] In this invention, the server includes a means for collecting advice from the generative AI in response to user questions, a means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe creation, and story creation, a means for providing this advice to the user, and a means for the user to input questions when selecting products in a physical store and for the generative AI to provide advice in real time. This enables users to receive appropriate advice in real time when selecting products in a physical store, enabling faster purchasing decisions and improved quality of advice.

[0821] A "user" is an individual or organization that uses the system to input questions and receive advice from the generative AI.

[0822] A "question" is information or a question that a user inputs into a generative AI, and is input data for obtaining advice.

[0823] "Generative AI" is an artificial intelligence engine that analyzes users' questions and generates appropriate advice.

[0824] "Advice" refers to information or instructions that generative AI provides based on a user's question.

[0825] A "physical store" is a commercial facility located in a physical location where users can directly select and purchase products.

[0826] "Product selection" refers to the act of a user selecting a product to purchase in a physical store.

[0827] "Real-time" refers to the generative AI providing immediate advice as soon as the user types in a question.

[0828] "Marketing" refers to the activities and strategies used to promote the sale of products and services.

[0829] "Research" is an investigative activity aimed at gathering and analyzing specific information.

[0830] "Brainstorming" is an abbreviation of brainstorming, a creative activity in which ideas are freely exchanged.

[0831] A "program" is a sequence of instructions or code that is executed by a computer.

[0832] A "study plan" is a specific plan or schedule for achieving learning goals.

[0833] "Recipe development" is the act of coming up with cooking steps and ingredients.

[0834] "Story creation" is the act of creating a story or scenario.

[0835] To implement this invention, a user uses a smartphone application when selecting a product in a physical store. A specific embodiment of this system will be described below.

[0836] System Configuration

[0837] The system consists of the following main components:

[0838] 1. User device: Smartphone

[0839] 2. Server: A server that hosts the generative AI engine

[0840] 3. Software: Python, OpenAI API

[0841] Program processing

[0842] The server includes a means for collecting generative AI advice in response to user questions, a means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation, a means for providing this advice to users, and a means for users to input questions when selecting products in a physical store and for the generative AI to provide advice in real time.

[0843] Hardware and Software

[0844] Hardware: The user device is a smartphone. The server is a high-performance computer that hosts the generative AI engine.

[0845] Software: Uses a Python program and OpenAI API. The Python program receives a user question and calls OpenAI's API to generate advice using a generative AI model (e.g., GPT-3).

[0846] Data processing and calculation

[0847] When a user enters a question through a smartphone app, the question is sent to the server. The server receives the question and calls the OpenAI API through a Python program. The API sends the question as a prompt to the generative AI model, which then analyzes the question and generates appropriate advice. The generated advice is then returned from the server to the user's device and displayed to the user.

[0848] Specific examples

[0849] If a user asks, "Is this product cheaper than other stores?" in a physical store, the AI ​​engine will provide advice such as, "This product is priced averagely compared to other stores. We recommend checking the price online as well."

[0850] Example prompt sentence:

[0851] User Question: Is this product cheaper than other stores?

[0852] Please provide advice.

[0853] In this way, users can receive relevant advice in real time when choosing products in physical stores, enabling faster purchasing decisions and better advice.

[0854] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0855] Step 1:

[0856] The user launches the smartphone app and enters a question.

[0857] Input: User question (e.g. "Is this product cheaper than other stores?")

[0858] Output: User question data

[0859] Specific behavior: The user enters a question into the app's text input field and presses the submit button.

[0860] Step 2:

[0861] The terminal sends the user's question data to the server.

[0862] Input: User question data

[0863] Output: The query data sent to the server

[0864] Specific operation: The smartphone app sends the question data to the server as an HTTP request.

[0865] Step 3:

[0866] The server receives the query data and runs the Python program.

[0867] Input: Query data sent to the server

[0868] Output: Prompt sentence to the generative AI model

[0869] Specific operation: The server receives an HTTP request and passes the question data to the Python program, which converts the question data into a prompt.

[0870] Step 4:

[0871] The server calls the OpenAI API and sends a prompt to the generative AI model.

[0872] Input: prompt sentence for generative AI model

[0873] Output: Advice from a generative AI model

[0874] Specific operation: The Python program calls the OpenAI API and sends a prompt to a generative AI model (e.g., GPT-3).

[0875] Step 5:

[0876] A generative AI model analyzes the prompt and generates appropriate advice.

[0877] Input: prompt statement

[0878] Output: Generated advice

[0879] How it works: The generative AI model analyzes the prompt and generates advice based on its internal learning data.

[0880] Step 6:

[0881] The server receives the generated advice and returns it to the user terminal.

[0882] Input: Generated advice

[0883] Output: Advice sent to user terminal

[0884] Specific operation: The server receives advice from the generative AI model and sends it to the user device as an HTTP response.

[0885] Step 7:

[0886] The device receives the advice from the server and displays it to the user.

[0887] Input: Advice sent by the server

[0888] Output: Advice displayed to the user

[0889] Specific operation: The smartphone app receives the HTTP response and displays the advice on the screen.

[0890] In this way, users can get real-time, relevant advice when choosing products in a physical store.

[0891] Example 2

[0892] 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."

[0893] Conventional generative AI systems have difficulty providing appropriate advice in response to user questions, especially when dealing with a wide range of domains. Furthermore, there is a lack of guidelines and instructions for users to ask generative AI effective questions, which leads to a decline in the quality of user questions.

[0894] 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.

[0895] In this invention, the server includes means for inputting a user's question, means for transmitting the question to the server, means for selecting an appropriate AI module based on the question, means for inputting a prompt sentence to a generative AI model using the AI ​​module, means for the generative AI model to generate advice, means for providing the generated advice to a user, and means for handling a wide range of areas such as marketing, research, brainstorming, program creation, study plans, recipe creation, story creation, etc. This makes it possible to provide appropriate and specialized advice in response to a user's question, and to provide guidelines and instructions for users to ask effective questions to the generative AI.

[0896] A "means for inputting a user's question" is a device or software that provides an interface for a user to input a question to the system.

[0897] The "means for transmitting the question to the server" refers to a communication means for transmitting the question entered by the user to the server.

[0898] The "means for selecting an appropriate AI module based on the question" refers to an algorithm or program for analyzing the content of the user's question and selecting the AI ​​module that is most suitable for that content.

[0899] "Means for inputting a prompt sentence to a generative AI model using the AI ​​module" refers to means for creating and inputting an appropriate prompt sentence to a generative AI model using a selected AI module.

[0900] "Means for the generative AI model to generate advice" refers to means for the generative AI model to generate advice for the user based on the input prompt sentence.

[0901] "Means for providing the generated advice to the user" refers to means for displaying or notifying the user of the advice generated by the generative AI model.

[0902] "Means that cover a wide range of areas, including marketing, research, brainstorming, program creation, lesson planning, recipe development, and story writing" includes AI modules specialized in these wide-ranging areas, and are means for providing expert advice in each area.

[0903] This invention is a system for providing appropriate advice in response to a user's question. The system includes means for inputting a user's question, means for transmitting the question to a server, means for selecting an appropriate AI module based on the question, means for inputting a prompt sentence to a generative AI model using the AI ​​module, means for the generative AI model to generate advice, means for providing the generated advice to a user, and means for handling a wide range of areas such as marketing, research, brainstorming, program creation, study planning, recipe creation, and story creation.

[0904] Specifically, a user uses a device such as a smartphone or PC to input a question, such as "Tell me what to make for dinner tonight." The device receives this question and sends it to the server using an HTTP POST request.

[0905] The server analyzes the received question and selects the appropriate AI module based on its content. For example, if the question is about recipes, it selects an AI module that specializes in recipe creation. The server then uses the selected AI module to create a prompt to be input to the generative AI model. The prompt includes information about the user's question, ingredients on hand, and preferences.

[0906] Examples of specific prompts include:

[0907] User Asks: "What should I make for dinner tonight?"

[0908] Ingredients on hand: "Chicken, tomatoes, basil, cheese."

[0909] Favorite food: "Italian food"

[0910] The server inputs this prompt into a generative AI model, which then uses its internal algorithms to generate advice, such as "I recommend making Caprese chicken with chicken, tomatoes, basil, and cheese."

[0911] The generated advice is sent from the server to the device, and the device displays the advice to the user, who can then check the specific advice on the device screen.

[0912] The system allows users to receive expert advice in a wide range of areas and also provides guidelines and instructions to improve the quality of their questions, greatly improving user convenience.

[0913] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0914] Step 1:

[0915] The user enters a question.

[0916] Users open the application on their smartphone or computer and type into the text box, "Tell me what to make for dinner tonight," and the question is sent to the device.

[0917] Step 2:

[0918] The terminal sends a question to the server.

[0919] The terminal receives user input and sends a question to the server using an HTTP POST request: the input data is the user's question, and the output is the request sent to the server.

[0920] Step 3:

[0921] The server analyzes the question and selects the appropriate AI module.

[0922] The server analyzes the received question using natural language processing technology. Based on the analysis results, it determines that the question is about recipes and selects an AI module specialized in recipe creation. The input data is the user's question, and the output is the selected AI module.

[0923] Step 4:

[0924] The server inputs a prompt sentence into the generative AI model.

[0925] The server uses the selected AI module to create a prompt to be input to the generative AI model. The prompt includes information such as the user's question, ingredients on hand, and preferences. For example, a prompt might be generated as follows: "User question: 'Tell me what to make for dinner tonight' Ingredients on hand: 'Chicken, tomatoes, basil, cheese' Preferences: 'Italian food'." The input data is the user's question and related information, and the output is the prompt.

[0926] Step 5:

[0927] A generative AI model generates advice.

[0928] The generative AI model receives a prompt and uses its internal algorithm to generate advice, such as "I recommend making Caprese Chicken with chicken, tomatoes, basil, and cheese." The input data is the prompt, and the output is the generated advice.

[0929] Step 6:

[0930] The server transmits the generated advice to the terminal.

[0931] The server receives the advice obtained from the generative AI model and sends it to the terminal as an HTTP response. The input data is the generated advice, and the output is the response sent to the terminal.

[0932] Step 7:

[0933] The terminal displays the advice to the user.

[0934] The terminal displays the advice received from the server to the user. The user can see the advice on the terminal screen: "We recommend making Caprese Chicken with chicken, tomatoes, basil, and cheese." The input data is the advice from the server, and the output is what is displayed to the user.

[0935] (Application example 2)

[0936] 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."

[0937] Conventional generative AI systems can sometimes make it difficult for users to get appropriate advice when asking specific questions. They also lack specific assistance to improve the shopping experience in brick-and-mortar stores, such as when users don't know what to buy or want recipe suggestions using specific ingredients. Therefore, there is a need for a system that can provide appropriate advice in response to user questions and improve the shopping experience in brick-and-mortar stores.

[0938] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for collecting generative AI advice in response to a user's question, a means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation, a means for providing this advice to the user, a means for generating a prompt sentence for the generative AI model based on text entered by the user, and a means for displaying the generated advice to the user. This allows the user to receive appropriate advice when asking a specific question, improving the shopping experience in a physical store.

[0939] "Means for collecting advice from generative AI in response to user questions" is a function for collecting advice provided by generative AI in response to questions entered by users.

[0940] "A means to address a wide range of areas, including marketing, research, brainstorming, programming, study plans, recipe development, and story creation" is a function that uses generative AI modules specialized in various fields to provide appropriate advice to users' questions in each area.

[0941] "Means for providing these pieces of advice to users" refers to a function for displaying or notifying users of the advice provided by the generative AI.

[0942] "Means for generating prompt sentences for a generative AI model based on text entered by a user" refers to a function for automatically generating prompt sentences suitable for a generative AI model based on questions or requests entered by a user.

[0943] "Means for displaying generated advice to the user" refers to a function for visually displaying advice generated by the generative AI model to the user.

[0944] The following system configuration is used as an embodiment of this invention. The system includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe creation, and story creation; means for providing this advice to the user; means for generating prompt sentences for the generative AI model based on text entered by the user; and means for displaying the generated advice to the user.

[0945] Hardware and software used

[0946] Hardware: Smartphone

[0947] Software: Python, OpenAI API

[0948] Data processing and calculation

[0949] 1. Getting user input: A user types a question or request through a smartphone application, for example, "I don't know what to buy."

[0950] 2. Prompt generation: The server generates a prompt appropriate for the generative AI model based on the user's input. For example, it generates a prompt such as, "If the user says, 'I don't know what to buy,' please suggest new products based on the products they have on hand and their preferences."

[0951] 3. Calling the AI ​​model: The server passes the generated prompt sentence to the generative AI model via the OpenAI API to generate advice.

[0952] 4. Displaying Advice: The server displays the generated advice to the user through a smartphone application. For example, it displays advice such as "Suggested products: fresh vegetables, organic milk, whole wheat bread."

[0953] Specific examples

[0954] If a user uses a smartphone application and types "I don't know what to buy," the system works as follows:

[0955] 1. The user types, "I don't know what to buy."

[0956] 2. The server generates the following prompt based on the entered text:

[0957] If a user says, "I don't know what to buy," suggest new products based on what they have on hand and their preferences.

[0958] 3. The server passes this prompt to the generative AI model via the OpenAI API to generate advice.

[0959] 4. The server displays the generated advice to the user through a smartphone application, for example, "Suggested products: fresh vegetables, organic milk, whole wheat bread."

[0960] In this way, users can get the right advice for their specific questions, enhancing their in-store shopping experience.

[0961] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0962] Step 1:

[0963] A user inputs a question or request through a smartphone application. For example, they might input, "I don't know what to buy." This input becomes the initial data for the system.

[0964] Step 2:

[0965] The terminal sends the text entered by the user to the server. The input data is the text "I don't know what to buy."

[0966] Step 3:

[0967] The server generates a prompt sentence suitable for the generative AI model based on the received text. Specifically, it generates the following prompt sentence:

[0968] If a user says, "I don't know what to buy," suggest new products based on what they have on hand and their preferences.

[0969] This prompt sentence is generated.

[0970] Step 4:

[0971] The server passes the generated prompt sentence to the generative AI model through the OpenAI API. The input data is the generated prompt sentence, and the output data is the advice returned by the generative AI model.

[0972] Step 5:

[0973] The server receives the advice returned by the generative AI model, for example, "Suggested products: fresh vegetables, organic milk, whole wheat bread."

[0974] Step 6:

[0975] The server sends the received advice to the terminal for display to the user. The input data is the advice from the generative AI model, and the output data is the advice displayed to the user.

[0976] Step 7:

[0977] The device displays the advice received from the server to the user through a smartphone application. For example, the advice "Suggested products: fresh vegetables, organic milk, whole wheat bread" is displayed to the user.

[0978] In this way, users can get the right advice for their specific questions, improving their shopping experience in physical stores.

[0979] Example 3

[0980] 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."

[0981] In systems using conventional generative AI models, the process from when a user inputs a question to when they receive appropriate advice is complicated, and there are problems with a lack of guidelines or instructions for users to ask questions effectively. Another issue is that the generated advice is not properly communicated to users, making it difficult for them to act on it.

[0982] 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.

[0983] In this invention, the server includes means for receiving a user's question, means for transmitting the received question to the server, means for the server to input the question into a generative AI model and generate advice, means for transmitting the generated advice from the server to the terminal, means for the terminal to display the advice to the user, and means for the user to input a new question. This enables the user to effectively ask questions, appropriately receive the generated advice, and take action based on it.

[0984] "User" means an individual or entity that utilizes the System to enter questions and receive generated advice.

[0985] A "terminal" is an electronic device that a user uses to enter questions and view generated advice.

[0986] The "server" is a computer system that receives questions from users, inputs them into a generative AI model to generate advice, and sends it to the terminal.

[0987] A "generative AI model" is an artificial intelligence algorithm that generates appropriate advice based on a user's questions.

[0988] A "question" is information or a question that a user inputs into the system.

[0989] "Advice" is an answer or suggestion that a generative AI model generates based on a user's question.

[0990] A "user interface" is the part of a system that contains screens and input fields through which a user can enter questions and view generated advice.

[0991] A "prompt" is text containing a user question or instruction that is input into a generative AI model.

[0992] This invention is a system that allows a user to input a question and obtain appropriate advice using a generative AI model. This system includes a series of processes that receive the user's question, input it into the generative AI model, and provide the generated advice to the user.

[0993] Hardware and software used

[0994] Hardware

[0995] Device: An electronic device that allows users to input questions and view generated advice. Examples include computers, smartphones, and tablets.

[0996] Server: A computer system that receives questions from users, inputs them into a generative AI model to generate advice, and sends it to the device.

[0997] software

[0998] Generative AI models: Artificial intelligence algorithms that generate appropriate advice based on user questions. Examples include OpenAI's GPT-3.

[0999] User Interface: Software that contains screens and input fields for users to enter questions and view generated advice.

[1000] Data processing and calculation

[1001] Data Processing

[1002] Receiving user input: The user enters a question using the device's user interface. This input is in the form of text.

[1003] Sending a question: The device sends the question entered by the user to the server using a communication protocol such as an HTTP request.

[1004] Data Calculation

[1005] Advice generation: The server inputs the received question into the generative AI model and generates appropriate advice. The generative AI model generates text-based advice based on the input question.

[1006] Sending and displaying advice: The server sends the generated advice to the terminal, which displays the advice through a user interface.

[1007] Specific examples

[1008] Prompt Sentence Examples

[1009] Let's say a user wants advice on a new business idea. Here's an example prompt to input to a generative AI model:

[1010] Example prompt: "I have a new business idea in mind. How should I go about it?"

[1011] Example of advice generated: "First, conduct market research and identify your target audience. Then create a business plan and figure out how to raise funds."

[1012] In this way, the user can receive specific advice and decide on the next action based on it. This system enables the user to effectively ask questions, appropriately receive the generated advice, and take action based on it. The flow of the identification process in Example 3 will be described with reference to FIG. 15.

[1013] Step 1:

[1014] The user enters a question.

[1015] A user inputs a question using the user interface of a terminal. Specifically, the user inputs, "I'm thinking of a new business idea. How should I go about it?" This input is in text format. The input data is the user's question text.

[1016] Step 2:

[1017] The terminal sends a question to the server.

[1018] The terminal sends the question entered by the user to the server. This transmission is performed using a communication protocol such as an HTTP request. Specifically, the terminal sends the question "I'm thinking of a new business idea. How should I go about it?" to the server. The input data is the user's question text, and the output data is the question text sent to the server.

[1019] Step 3:

[1020] The server inputs the question into a generative AI model.

[1021] The server inputs the received question into the generative AI model. Specifically, the server inputs a prompt to the generative AI model: "I'm thinking of a new business idea. How should I go about it?" The input data is the question text sent to the server, and the output data is the prompt input to the generative AI model.

[1022] Step 4:

[1023] A generative AI model generates advice.

[1024] The generative AI model generates advice based on the input question. Specifically, the generative AI model generates the advice, "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the prompt sentence entered into the generative AI model, and the output data is the generated advice text.

[1025] Step 5:

[1026] The server receives the generated advice.

[1027] The server receives the advice returned from the generative AI model. Specifically, the server receives the advice, "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the advice text returned from the generative AI model, and the output data is the advice text received by the server.

[1028] Step 6:

[1029] The server sends the advice to the terminal.

[1030] The server sends the advice it receives to the terminal. This transmission is also performed using a communication protocol such as an HTTP request. Specifically, the server sends the advice to the terminal: "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the advice text received by the server, and the output data is the advice text sent to the terminal.

[1031] Step 7:

[1032] The terminal displays the advice to the user.

[1033] The terminal displays the received advice on the user interface. Specifically, the terminal displays on the user interface, "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the advice text sent to the terminal, and the output data is the advice text displayed on the user interface.

[1034] Step 8:

[1035] The user enters a new question.

[1036] The user can again enter a new question using the input field of the user interface. In a specific operation, the user enters "Please tell me the specific methods of market research." The input data is the newly entered question text, and the output data is the new question text entered into the user interface.

[1037] (Application example 3)

[1038] 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."

[1039] Conventional advice-giving systems using generative AI can provide advice in response to user questions, but it is difficult to provide advice specialized in a specific area. Furthermore, the interface for users to input new questions and receive advice in response to them is insufficient, resulting in a poor user experience. Providing appropriate advice for security-related questions is particularly important.

[1040] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for collecting generative AI advice in response to user questions, means for handling a wide range of areas such as marketing, research, brainstorming, programming, and other work, study plans, recipe development, and story creation, means for providing this advice to the user, means for providing optimal advice in response to security-related questions, and means for allowing the user to input new questions and receive advice in response to them through a user interface. This allows the user to receive advice specialized in a specific area, and in particular, appropriate advice in response to security-related questions.

[1041] A "user" is an individual or corporation that uses the system to input questions and receive advice from the generative AI.

[1042] A "question" is information or a question that a user inputs into a generative AI, which serves as a trigger for obtaining advice.

[1043] "Generative AI" refers to artificial intelligence that generates appropriate advice in response to user questions.

[1044] "Advice" refers to advice or suggestions provided by generative AI based on a user's questions.

[1045] "Marketing" refers to the activities and strategies aimed at promoting products and services.

[1046] "Research" is the activity of collecting and analyzing information on a particular topic or issue.

[1047] "Brainstorming" is an abbreviation of "brainstorming," a creative activity in which ideas are freely exchanged.

[1048] A "program" is a set of instructions or code that a computer executes.

[1049] A "study plan" is a specific plan or schedule for achieving learning goals.

[1050] "Recipe development" refers to the activity of coming up with cooking procedures and ingredients.

[1051] "Story writing" refers to the activity of creating a story or scenario.

[1052] "Security" refers to the measures and procedures for protecting information and physical assets.

[1053] A "user interface" is a screen or input device that allows a user to interact with a system.

[1054] A "means" is a method or device used to achieve a particular purpose.

[1055] A "system" is a structure or mechanism in which multiple elements work together to achieve a specific function.

[1056] The system for implementing this invention collects generative AI advice in response to user questions and provides advice tailored to specific domains, particularly those related to security.

[1057] System configuration

[1058] The system consists of the following main components:

[1059] 1. User device: The device on which the user enters their question and receives advice. This can be a smartphone or a computer.

[1060] 2. Server: Hosts the generative AI model and generates advice in response to user questions.

[1061] 3. User Interface: The interface through which users can enter their questions and receive advice.

[1062] Program processing

[1063] The server performs the following steps:

[1064] 1. Receiving a question: Receive a question entered from the user's terminal.

[1065] 2. Invoke a generative AI model: The received question is sent as a prompt to a generative AI model, such as OpenAI's GPT-3.

[1066] 3. Advice generation: A generative AI model generates advice in response to the question.

[1067] 4. Sending advice: The generated advice is sent to the user terminal.

[1068] Hardware and software used

[1069] Hardware: Smartphones, PCs, and servers with internet connectivity.

[1070] Software: Python, OpenAI API, front-end framework for user interface (e.g. React, Vue.js).

[1071] Specific examples

[1072] If a user asks, "Where is the best place to put a home security camera?" the system works as follows:

[1073] 1. A question is sent from the user device to the server.

[1074] 2. The server sends the question as a prompt to the generative AI model.

[1075] 3. A generative AI model generates advice in response to the question.

[1076] 4. The server sends the generated advice to the user device.

[1077] 5. Advice will be displayed on the user's device's user interface.

[1078] Prompt Sentence Examples

[1079] Security Question: Where is the best place to install a home security camera?

[1080] Please provide the best advice.

[1081] In this way, users can receive advice specific to a particular area, and in particular, get advice that is relevant to security-related questions.

[1082] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1083] Step 1:

[1084] The user inputs a question using a terminal. The input question is sent to the server through the user interface. The input data is a text question, such as "Where is the best place to install a home security camera?"

[1085] Step 2:

[1086] The server analyzes the received question and converts it into a format suitable for the generative AI model. In this conversion process, the question is formatted as a prompt. The input data is the user's question, and the output data is the prompt to be sent to the generative AI model.

[1087] Step 3:

[1088] The server sends a prompt to a generative AI model (e.g., OpenAI's GPT-3). The generative AI model receives the prompt and generates advice for the question. The input data is the prompt, and the output data is the generated advice.

[1089] Step 4:

[1090] The server analyzes the advice received from the generative AI model and converts it into a format that is easy for the user to understand. In this conversion process, the generated advice is formatted into text. The input data is the advice from the generative AI model, and the output data is the text to be displayed to the user.

[1091] Step 5:

[1092] The server sends the formatted advice to the user terminal, which displays the received advice on a user interface. The input data is the formatted advice, and the output data is the text displayed on the user interface.

[1093] Step 6:

[1094] The user checks the displayed advice and enters a new question if necessary. When a new question is entered, the process starts again from step 1. The input data is the user's new question, and the output data is the advice that is generated again.

[1095] 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.

[1096] "Example 1"

[1097] One embodiment of the present invention is a system incorporating an emotion engine. This system collects generative AI advice in response to user questions and provides it to the user. The emotion engine also recognizes the user's emotions and tailors the advice based on those emotions. For example, if the user feels frustrated, the emotion engine communicates this information to the generative AI, which then generates advice to calm the user.

[1098] "Example 2"

[1099] Another embodiment is a system in which an emotion engine provides optimal advice to a user based on the user's emotions. In this system, the emotion engine analyzes the user's emotions in real time and generates advice optimal for those emotions. For example, if the emotion engine senses that the user is feeling joy, the emotion engine communicates that information to a generative AI, and the AI ​​generates advice that amplifies that joy.

[1100] "Example 3"

[1101] In yet another embodiment, an emotion engine adjusts the generative AI's advice based on the user's emotions. In this system, the emotion engine analyzes the user's emotions in real time and adjusts the generative AI's advice based on those emotions. For example, if the user feels sad, the emotion engine communicates that information to the generative AI, which then generates advice to alleviate the sadness.

[1102] The processing flow of each embodiment will be described below.

[1103] "Example 1"

[1104] Step 1: The user asks the system a question.

[1105] Step 2: Generative AI generates advice in response to the user's question.

[1106] Step 3: The emotion engine recognizes the user's emotion.

[1107] Step 4: Adjust the generative AI's advice based on the emotions recognized by the emotion engine.

[1108] Step 5: Provide tailored advice to users.

[1109] "Example 2"

[1110] Step 1: The user asks the system a question.

[1111] Step 2: The emotion engine analyzes user emotions in real time.

[1112] Step 3: Based on the emotions analyzed by the emotion engine, the generative AI generates optimal advice for the user.

[1113] Step 4: Providing the generated advice to the user.

[1114] "Example 3"

[1115] Step 1: The user asks the system a question.

[1116] Step 2: The emotion engine analyzes user emotions in real time.

[1117] Step 3: Adjust the generative AI's advice based on the emotions analyzed by the emotion engine.

[1118] Step 4: Provide tailored advice to users.

[1119] Example 1

[1120] 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."

[1121] Conventional generative AI systems were unable to consider the user's emotions when providing advice in response to user questions, making it difficult to provide appropriate advice based on the user's psychological state. Furthermore, they lacked the functionality to provide guidelines and instructions for users to ask effective questions to generative AI, making it difficult for users to efficiently obtain the information they were looking for.

[1122] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for collecting generative AI advice in response to a user's question, means for analyzing the user's question using natural language processing technology, means for generating appropriate advice using a generative AI engine, means for recognizing the user's emotion using an emotion engine, means for adjusting the advice based on the user's emotion, and means for providing this advice to the user. This makes it possible to provide appropriate advice that takes the user's emotion into consideration, and to provide guidelines and instructions for the user to ask the generative AI effective questions.

[1123] "Generative AI" is an artificial intelligence technology that generates appropriate advice and information in response to users' questions and requests.

[1124] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[1125] A "generative AI engine" is a collection of software and algorithms that realizes generative AI, and has the ability to generate appropriate advice in response to user questions.

[1126] An "emotion engine" is a technology that recognizes a user's emotions and tailors appropriate advice based on those emotions.

[1127] A "user question" is a question or request that a user enters into the system.

[1128] "Advice" refers to advice or information provided by generative AI in response to a user's question.

[1129] "Analysis" is the process of understanding the intent and content of a user's question using natural language processing technology.

[1130] "Adjustment" is the process of appropriately modifying the generated advice based on the user's emotions recognized by the emotion engine.

[1131] "Providing" is the act of conveying the generated advice to the user.

[1132] MODE FOR CARRYING OUT THE INVENTION

[1133] This invention is a system that provides generative AI advice in response to user questions. The system includes natural language processing technology and a generative AI engine to analyze the user's question and generate appropriate advice. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the advice based on those emotions.

[1134] Hardware and software used

[1135] The server uses the following hardware and software to implement the system:

[1136] Natural language processing technology: Natural language processing models such as Google's BERT and OpenAI's GPT-3

[1137] Generative AI engine: Software and algorithms for realizing generative AI

[1138] Emotion engine: Emotion recognition technology such as Microsoft's Azure Cognitive Services

[1139] Communication method: Communication between the server and the terminal using HTTP requests

[1140] System Operation

[1141] The user inputs a question through the device interface. For example, the user might input, "How should we develop a marketing strategy for a new product?" The device then sends this question to the server. The server then analyzes the received question using natural language processing technology and understands the intent of the question. Based on the analysis results, the generative AI engine generates appropriate advice.

[1142] Furthermore, the server uses an emotion engine to recognize the user's emotions. For example, if the emotion engine recognizes that the user is irritated, the server adjusts the advice generated by the generative AI engine. The adjusted advice will correspond to the user's emotions.

[1143] Specific examples

[1144] As a concrete example, consider the case where a user asks, "How should we develop a marketing strategy for a new product?" In this case, the server inputs the following prompt into the generative AI model:

[1145] Example prompt sentence:

[1146] A user asks: "How do I develop a marketing strategy for my new product?"

[1147] Prompt for the generative AI model: "What steps should I take to develop a marketing strategy for a new product? Please provide specific advice."

[1148] Based on this prompt, the generative AI model generates the following advice:

[1149] "To develop a marketing strategy for a new product, it is important to first conduct a competitor analysis and understand the target market. Next, evaluate the product's strengths and weaknesses and create a marketing message based on that. It is also necessary to choose the right advertising channels and carry out effective promotion."

[1150] If the emotion engine identifies the user's emotion as "frustrated," the generative AI will adjust its advice as follows:

[1151] "First, take a deep breath and relax. Then, calmly conduct a competitor analysis and understand your target market. Next, evaluate the strengths and weaknesses of your product and create a marketing message based on that. You also need to choose the right advertising channels and promote it effectively."

[1152] In this way, users can view advice on their device screen. This system allows users to receive appropriate advice based on their emotions, and also provides guidelines and instructions for asking effective questions to the generative AI.

[1153] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1154] Step 1: User enters question

[1155] A user inputs a question through the terminal interface. For example, the user inputs, "How should we develop a marketing strategy for a new product?" This input is stored as text data on the terminal.

[1156] Step 2: The device sends the question to the server

[1157] The device sends the user-entered question to the server as an HTTP POST request, for example to the endpoint https: / / example.com / api / questions. This request includes the user's question.

[1158] Step 3: The server receives the question and analyzes it using natural language processing technology

[1159] The server analyzes the received question using natural language processing technology. Specifically, it uses models such as Google's BERT and OpenAI's GPT-3 to understand the intent of the question. This analysis extracts keywords and context from the question. The input is the user's question, and the output is the analysis result.

[1160] Step 4: The server generates advice using a generative AI engine based on the analysis results.

[1161] The server uses a generative AI engine to generate advice based on the analysis results. For example, if a user asks, "How should we develop a marketing strategy for a new product?", the generative AI engine will generate advice such as, "Analyze competitors, understand the target market, and evaluate the product's strengths and weaknesses." The input is the analysis results, and the output is the generated advice.

[1162] Step 5: The server recognizes the user's emotion using the emotion engine.

[1163] The server uses an emotion engine to recognize the user's emotions. For example, it uses Microsoft's Azure Cognitive Services to analyze emotions from the user's voice and facial expressions. This analysis determines whether the user is irritated or not. The input is the user's voice and facial expression data, and the output is the emotion recognition result.

[1164] Step 6: The server adjusts the advice based on the emotion

[1165] The server adjusts the advice generated by the generative AI engine based on information obtained from the emotion engine. For example, if the emotion engine recognizes that the user is irritated, the server will adjust the advice to something like, "First, take a deep breath and relax. Then, calmly analyze the situation." The input is the emotion recognition result and the generated advice, and the output is the adjusted advice.

[1166] Step 7: The server sends the final advice to the device

[1167] The server sends the final advice to the terminal as an HTTP response, for example, in the form {"advice": "First, take a deep breath and relax. Then, calmly analyze the situation."}. The input is the adjusted advice, and the output is the HTTP response.

[1168] Step 8: The device displays the advice to the user

[1169] The device displays the advice received from the server to the user. The user can see advice on the device screen such as "First, take a deep breath and relax. Then, calmly analyze the situation." The input is the HTTP response from the server, and the output is the advice displayed to the user.

[1170] (Application example 1)

[1171] 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."

[1172] Conventional advice systems using generative AI provide uniform advice without considering the user's emotions, resulting in a decline in user satisfaction and reliability. Furthermore, there was a lack of specific applications for improving the shopping experience in physical stores. This resulted in the issue of users being unable to receive appropriate information or advice tailored to their emotions when asking about products.

[1173] 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.

[1174] In this invention, the server includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe creation, and story creation; means for providing this advice to the user; means including an emotion engine for recognizing the user's emotions and adjusting advice based on those emotions; and means for providing product information, emotion recognition, and personalized advice as an application installed on a smartphone in a physical store. This makes it possible to provide appropriate advice based on the user's emotions and improve the shopping experience in a physical store.

[1175] "Means for gathering generative AI advice in response to user questions" refers to an artificial intelligence engine that receives questions from users and generates appropriate advice in response to them.

[1176] "A tool for a wide range of areas, including marketing, research, brainstorming, programming, study plans, recipe creation, and story writing" refers to a function that provides advice to users on questions in a variety of fields.

[1177] "Means for providing these pieces of advice to the user" refers to the interface or communication means for conveying the generated advice to the user.

[1178] "Means including an emotion engine that recognizes a user's emotion and adjusts advice based on the emotion" refers to an engine that analyzes a user's emotion and adjusts the content and tone of advice based on the analysis result.

[1179] "A means of providing product information, recognizing emotions, and offering personalized advice as an application installed on a smartphone in a physical store" refers to an application installed on a smartphone that provides product information, recognizes users' emotions, and offers personalized advice in order to improve the shopping experience in a physical store.

[1180] A system for implementing this invention includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation; means for providing this advice to users; means including an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions; and means for providing product information, emotion recognition, and personalized advice as an application installed on a smartphone in a physical store.

[1181] The server receives questions from users and uses a generative AI engine to generate appropriate advice in response. The generative AI engine uses natural language processing technology to analyze the user's question and generate appropriate advice. For example, if a user asks, "How should I coordinate this shirt?", the generative AI engine will generate advice such as, "That shirt looks casual and stylish when paired with jeans. Also, adding accessories will make it even more stylish!"

[1182] The device uses a camera and microphone to recognize the user's emotions through an application installed on the smartphone. Emotion recognition is performed using software. It recognizes emotions from the user's voice and facial expressions and sends the results to a generative AI engine. For example, if the device recognizes that the user is excited, the generative AI engine will use that information to adjust the tone of its advice.

[1183] Users can receive the generated advice through a smartphone application. The application has functions to provide product information, recognize emotions, and provide personalized advice. For example, if a user asks, "How should I coordinate this shirt?" and emotion recognition determines that the user is "excited," the generative AI will provide advice such as, "That shirt looks casual and stylish when paired with jeans. Also, adding some accessories will make it even more stylish!"

[1184] An example prompt is:

[1185] User Question: How should I coordinate this shirt?

[1186] User sentiment: Excited

[1187] Please provide appropriate advice.

[1188] In this way, it is possible to provide appropriate advice based on the user's emotions and improve the shopping experience in physical stores.

[1189] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1190] Step 1:

[1191] The user launches the application on their smartphone and enters a question.

[1192] Input: User question (e.g., "How do I coordinate this shirt?")

[1193] Output: User question data

[1194] Specific behavior: The user enters a question into the application's input field and presses the submit button.

[1195] Step 2:

[1196] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice and recognize emotions.

[1197] Input: User's facial and voice data

[1198] Output: User's emotion data (e.g. "Excited")

[1199] How it works: The device uses emotion recognition software to analyze emotions from captured facial expressions and voice.

[1200] Step 3:

[1201] The terminal transmits the user's question data and emotion data to the server.

[1202] Input: User question data, user emotion data

[1203] Output: Data sent to the server

[1204] Specific operation: The terminal sends the user's question data and emotion data to the server via the Internet.

[1205] Step 4:

[1206] The server uses a generative AI engine to analyze the user's question and generate appropriate advice.

[1207] Input: User question data, user emotion data

[1208] Output: Generated advice (e.g., "That shirt looks great with jeans for a casual look. Plus, adding some accessories will make it even more stylish!")

[1209] Specific operation: The server uses the OpenAI API to generate prompt sentences based on the user's question and emotions, and sends them to the AI ​​engine to generate advice.

[1210] Step 5:

[1211] The server transmits the generated advice to the terminal.

[1212] Input: Generated advice

[1213] Output: Advice data sent to the terminal

[1214] Specific operation: The server transmits the generated advice to the terminal via the Internet.

[1215] Step 6:

[1216] The terminal displays the received advice to the user.

[1217] Input: Received advice data

[1218] Output: Advice displayed to the user

[1219] Specific operation: The device displays the generated advice on the application screen so that the user can check it.

[1220] Example 2

[1221] 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."

[1222] Conventional generative AI systems only provided general advice in response to user questions, making it difficult to provide specific advice tailored to a particular domain. Furthermore, they were unable to provide advice that took the user's emotions into account, preventing them from increasing user satisfaction. Furthermore, there was a lack of guidelines or instructions for users to effectively ask generative AI questions, making it difficult for users to accurately obtain the information they were looking for.

[1223] 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.

[1224] In this invention, the server includes: means for collecting generative AI advice in response to a user's question; means for handling a wide range of areas, such as marketing, research, brainstorming, program creation, lesson planning, recipe creation, and story creation; means for providing this advice to the user; means including an emotion engine for analyzing the user's emotions in real time and generating optimal advice based on those emotions; means for analyzing the user's request and forwarding it to an appropriate AI module; means for the AI ​​module to process data based on the request and generate results; and means for displaying the generated results to the user. This makes it possible to provide specific advice specialized for a specific area in response to the user's question and generate optimal advice that takes the user's emotions into consideration. Furthermore, by providing guidelines and instructions for the user to ask the generative AI effective questions, the user can accurately obtain the information they are looking for.

[1225] "Generative AI" is artificial intelligence that automatically generates advice and suggestions based on users' questions and requests.

[1226] The "emotion engine" is part of a system that analyzes users' emotions in real time and generates optimal advice based on those emotions.

[1227] An "AI module" is an artificial intelligence component that has specialized expertise in a particular area and provides specific advice in response to user questions about that area.

[1228] A "request" is a question or request that a user makes to the system.

[1229] "Processing data" means retrieving the necessary information based on the user's request and generating appropriate advice and suggestions.

[1230] "Generating results" refers to creating advice or suggestions that are obtained after the AI ​​module processes the data.

[1231] "Displaying to the user" means displaying the generated advice or suggestion on the user's device.

[1232] "Marketing" refers to all activities aimed at promoting products and services.

[1233] "Research" is the activity of collecting and analyzing information on a particular topic or issue.

[1234] "Brainstorming" is an abbreviation of "brainstorming," a creative activity in which ideas are freely exchanged.

[1235] "Programming" is the activity of designing and coding computer programs.

[1236] "Learning planning" is the activity of planning learning goals and methods.

[1237] "Recipe creation" is the activity of coming up with new recipes for dishes.

[1238] "Story writing" is the activity of creating a story or scenario.

[1239] This invention is a system that collects generative AI advice in response to user questions and is applicable to a wide range of fields, including marketing, research, brainstorming, program creation, lesson planning, recipe creation, story creation, etc. It also includes an emotion engine that analyzes user emotions in real time and provides optimal advice based on those emotions.

[1240] Hardware and software used

[1241] The system uses the following hardware and software:

[1242] Server: Parses requests, selects AI modules, generates and sends results.

[1243] Terminal: Enters requests from the user and displays results from the server.

[1244] Generative AI models: Generate advice and suggestions based on user questions.

[1245] Emotion Engine: Analyzes user emotions in real time and generates optimal advice based on those emotions.

[1246] Data processing and calculation

[1247] When the server receives a request from a user, it analyzes the request and forwards it to the appropriate AI module, which processes the data based on the request and generates a result, which is then sent to the terminal via the server and displayed to the user.

[1248] For example, consider the case where a user types, "I don't know what to make for dinner tonight." In this case, the server sends a request to the recipe-creation AI module, which suggests new recipes based on the ingredients the user has on hand and their preferences.

[1249] Prompt Sentence Examples

[1250] Here are some examples of prompts:

[1251] "The ingredients I have on hand are chicken and broccoli. Can you suggest a new recipe using them?"

[1252] "I'm a little tired today, so could you suggest some easy dinner recipes?"

[1253] This system allows users to receive specific advice tailored to a particular area, and through an emotion engine, they can get optimal advice based on their emotions, thereby increasing user satisfaction.

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

[1255] Step 1:

[1256] The user inputs a request from the terminal.

[1257] Specifically, the user opens an application on their smartphone or computer and types "I don't know what to make for dinner tonight" into a text box.

[1258] Input: A user question or request (e.g., "I don't know what to make for dinner tonight.")

[1259] Output: Request typed into the terminal

[1260] Step 2:

[1261] The device sends a request to the server.

[1262] The terminal converts the entered text into JSON format and sends it to the server as an HTTP request.

[1263] Input: The request typed into the terminal

[1264] Output: JSON representation of the request sent to the server

[1265] Step 3:

[1266] The server parses the request and forwards it to the appropriate AI module.

[1267] The server parses the received JSON data and extracts keywords such as "dinner" and "recipe," and then forwards the request to the recipe-creation AI module.

[1268] Input: The JSON formatted request sent to the server

[1269] Output: The request forwarded to the AI ​​module

[1270] Step 4:

[1271] The AI ​​module processes the data based on the request and generates the results.

[1272] The recipe creation AI module searches the database for recipes using "chicken" and "broccoli" and generates a recipe for "stir-fried chicken and broccoli."

[1273] Input: The request forwarded to the AI ​​module

[1274] Output: Generated recipe information

[1275] Step 5:

[1276] The server transmits the generated results to the terminal.

[1277] The server converts the generated recipe into JSON format and sends it to the terminal as an HTTP response.

[1278] Input: Generated recipe information

[1279] Output: Recipe information in JSON format sent to the device

[1280] Step 6:

[1281] The terminal displays the results to the user.

[1282] The device parses the received JSON data and displays the recipe for "Chicken and Broccoli Stir-fry" on the application interface.

[1283] Input: JSON format recipe information sent to the terminal

[1284] Output: Recipe information displayed to the user

[1285] In this way, the system works in cooperation with the user, terminal, and server to provide the user with the most suitable advice and suggestions.

[1286] (Application example 2)

[1287] 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."

[1288] In traditional brick-and-mortar shopping experiences, users had limited options for obtaining appropriate advice when they had difficulty choosing a product. It was also difficult to provide personalized support based on the user's emotions, which could result in a lower quality shopping experience. Furthermore, there was a lack of guidelines for users to effectively ask generative AI questions, which prevented users from improving the way they asked questions, making it difficult to obtain appropriate advice.

[1289] 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.

[1290] In this invention, the server includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas, such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation; means for providing this advice to the user; an emotion engine for analyzing user emotions in real time; means for generating optimal advice based on the emotion engine; means for providing specific advice in response to user questions in physical stores; and means including an application to be installed on a smartphone. This allows users to obtain specific advice in real time to improve their shopping experience in physical stores, realizing personalized responses based on the user's emotions. Furthermore, guidelines are provided for users to ask effective questions to the generative AI, improving the way they ask questions and obtaining more appropriate advice.

[1291] "Means for collecting advice from generative AI in response to user questions" is a function for collecting advice provided by generative AI in response to questions entered by users.

[1292] "A means to handle a wide range of areas, including marketing, research, brainstorming, programming, learning plans, recipe creation, and story writing" is a function that uses AI modules specialized in various fields to provide specific advice in each area.

[1293] The "means for providing these pieces of advice to the user" refers to a function for presenting the collected advice to the user in an appropriate format.

[1294] The "emotion engine that analyzes user emotions in real time" is a function that analyzes emotions from user input and behavior and obtains the results in real time.

[1295] The "means for generating optimal advice based on an emotion engine" is a function for generating optimal advice for a user based on the user's emotions analyzed by the emotion engine.

[1296] "Means for providing specific advice in response to user questions in physical stores" is a function for providing specific and appropriate advice in response to questions asked by users in physical stores.

[1297] "Means including applications installed on smartphones" refers to means for providing various functions to users through applications installed on smartphones.

[1298] A system for implementing this invention includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation; means for providing this advice to users; an emotion engine for analyzing user emotions in real time; means for generating optimal advice based on the emotion engine; means for providing specific advice in response to user questions in a physical store; and means including an application to be installed on a smartphone.

[1299] Hardware and Software

[1300] This system uses the following hardware and software:

[1301] Hardware: Smartphone

[1302] Software: Python, emotion recognition library, various AI modules

[1303] Data processing and calculation

[1304] The server receives questions entered by users on their smartphones and generates advice using a generative AI module. The generated advice is then optimized by an emotion engine that analyzes the user's emotions in real time. The emotion engine uses an emotion recognition library to analyze the user's emotions and provides optimal advice based on the results.

[1305] Specific examples

[1306] When a customer asks, "I don't know what to make today," an app installed on their smartphone receives the question. The emotion engine analyzes the user's emotion as "confusion," and the AI ​​module "suggests new recipes based on the ingredients on hand and their preferences."

[1307] Prompt Sentence Examples

[1308] User Input: "I don't know what to make today"

[1309] Sentiment analysis result: "confused"

[1310] Generated advice: "Tell us what ingredients you have on hand and we'll suggest a new recipe for you."

[1311] This way, users can get specific advice in real time to improve their in-store shopping experience.

[1312] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1313] Step 1:

[1314] The user types a question into their smartphone.

[1315] Input: User question (e.g. "I don't know what to cook today")

[1316] How it works: An application on a smartphone receives user input.

[1317] Output: User question text data

[1318] Step 2:

[1319] The terminal sends the user's question to the server.

[1320] Input: User question text data

[1321] How it works: The smartphone application sends question text data to the server.

[1322] Output: Question text data sent to the server

[1323] Step 3:

[1324] The server receives the user's question and analyzes the emotion using an emotion engine.

[1325] Input: Question text data sent to the server

[1326] How it works: The server uses an emotion recognition library to analyze the user's emotions from the question text data.

[1327] Output: User emotion data (e.g. "confused")

[1328] Step 4:

[1329] The server selects the optimal AI module based on the emotion data.

[1330] Input: User emotion data

[1331] How it works: The server analyzes the emotion data and selects the appropriate AI module.

[1332] Output: Selected AI module

[1333] Step 5:

[1334] The server uses the selected AI module to generate advice for the user's question.

[1335] Input: User question text data, selected AI module

[1336] How it works: The server uses the selected AI module to generate specific advice for the user's question.

[1337] Output: The generated advice (e.g., "Tell me what ingredients you have on hand and I'll suggest a new recipe.")

[1338] Step 6:

[1339] The server transmits the generated advice to the terminal.

[1340] Input: Generated advice

[1341] How it works: The server sends the generated advice to the smartphone application.

[1342] Output: Advice sent to your phone

[1343] Step 7:

[1344] The terminal displays the advice to the user.

[1345] Input: Advice sent to your phone

[1346] How it works: A smartphone application displays advice to the user.

[1347] Output: Advice displayed to the user (e.g., "Tell me what ingredients you have on hand and I'll suggest a new recipe for you.")

[1348] Example 3

[1349] 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."

[1350] Conventional generative AI systems provide advice without taking the user's emotional state into consideration, making it difficult to obtain advice that is appropriate for the user's emotions. Also, when users input new questions, they have few opportunities to learn how to ask effective questions, which can lead to a decline in the quality of advice from generative AI.

[1351] The identification process by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes means for collecting generative AI advice in response to user questions, means for analyzing user emotions in real time using a sentiment analysis engine, and means for adjusting the generative AI advice based on the user emotions. This makes it possible to provide advice suited to the user's emotions. In addition, by including means for providing a user interface that allows the user to input a new question and receive advice in response to it, the user can learn how to ask effective questions and improve the quality of advice from the generative AI.

[1352] "Generative AI" is an artificial intelligence system that generates advice and information in natural language based on user input.

[1353] A "sentiment analysis engine" is software or a system for analyzing a user's input text and identifying its emotional state in real time.

[1354] A "user interface" is software or a system that provides screens and input fields for a user to interact with the system.

[1355] "Means of gathering advice" refers to the functions and processes used by generative AI to collect the advice generated in response to user questions.

[1356] "Means for tailoring advice" refers to the functions and processes for adapting the generative AI's advice to the user's emotional state based on the results of the sentiment analysis engine.

[1357] "Real-time analysis means" means the functionality or process that performs sentiment analysis the moment a user input is made and makes the results immediately available.

[1358] MODE FOR CARRYING OUT THE INVENTION

[1359] This invention is a system in which a generative AI provides advice in response to a user's question and adjusts the advice based on the user's emotional state. The system includes a server, a terminal, a user interface, a sentiment analysis engine, and a generative AI model.

[1360] Hardware and software used

[1361] Hardware: Servers, user devices (PCs, smartphones)

[1362] Software: Generative AI models (e.g., GPT-4), sentiment analysis engines (e.g., IBM Watson Tone Analyzer), user interfaces (web applications)

[1363] Specific operation of the system

[1364] 1. User enters question:

[1365] A user uses a terminal to enter a question into a user interface.

[1366] Example: A user types "I've been feeling tired at work lately. How can I refresh myself?" into a text input field in a web application and clicks the submit button.

[1367] 2. Perform sentiment analysis:

[1368] The server receives the user's input and sends it to the sentiment analysis engine.

[1369] A sentiment analysis engine analyzes the user's input text to identify their emotional state.

[1370] Example: A sentiment analysis engine detects "fatigue" and returns the result to the server.

[1371] 3. Advice Generation:

[1372] The server sends the results of the sentiment analysis to the generative AI model.

[1373] A generative AI model generates appropriate advice based on the user's emotional state.

[1374] Example: A generative AI model generates advice such as "Take a short break and do some light exercise" and returns the result to the server.

[1375] 4. Display Advice:

[1376] The server sends the generated advice to the user interface.

[1377] The user interface displays the advice in text format.

[1378] Example: The user interface displays "Take short breaks and engage in some light exercise."

[1379] Examples and prompts

[1380] Examples:

[1381] A user types, "I've been feeling tired at work lately. How can I refresh myself?"

[1382] The server sends the input to a sentiment analysis engine, which detects "fatigue."

[1383] The server sends the results of the sentiment analysis to a generative AI model, which then generates advice such as "Take a short break and do some light exercise."

[1384] The server sends the generated advice to the user interface, which displays it.

[1385] Example prompt sentence:

[1386] "If a user types, 'I've been feeling tired at work lately. How can I refresh myself?' the sentiment analysis engine will detect 'fatigue,' and the generative AI model will generate advice such as 'Take a short break and try some light exercise.'"

[1387] This system allows users to receive advice suited to their own emotional state and learn how to ask more effective questions. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1388] Step 1: User enters question

[1389] A user uses a terminal to enter a question into a user interface.

[1390] Input: A user types "I've been feeling tired at work lately. How can I refresh myself?" into a text input field in a web application and clicks the submit button.

[1391] Specific behavior: The user enters a question in the text input field and clicks the submit button, which sends the question to the server.

[1392] Output: The user's question is sent to the server.

[1393] Step 2: Perform sentiment analysis

[1394] The server receives the user's input and sends it to the sentiment analysis engine.

[1395] Input: The user's question text.

[1396] What happens: The server sends the user's input text to the sentiment analysis engine as an API request.

[1397] Data processing: A sentiment analysis engine analyzes the user's input text to identify their emotional state.

[1398] Output: The sentiment analysis engine detects "fatigue" and returns the result to the server.

[1399] Step 3: Advice generation

[1400] The server sends the results of the sentiment analysis to the generative AI model.

[1401] Input: Sentiment analysis result "fatigue".

[1402] Specific operation: The server sends a prompt sentence containing "fatigue" as a result of sentiment analysis to the generative AI model as an API request.

[1403] Data computation: Generative AI models generate appropriate advice based on the user's emotional state.

[1404] Output: The generative AI model generates advice such as "Take a short break and do some light exercise" and returns the result to the server.

[1405] Step 4: View Advice

[1406] The server sends the generated advice to the user interface.

[1407] Input: Advice generated by a generative AI model.

[1408] Specific behavior: The server sends the generated advice "Take a short break and do some light exercise" to the user interface as an API response.

[1409] Output: The user interface displays the advice in text format.

[1410] What it does: The user interface displays the advice on the screen so the user can view it.

[1411] (Application example 3)

[1412] 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."

[1413] Conventional generative AI systems provide advice without considering the user's emotional state, making it impossible to provide appropriate advice based on the user's emotions. Furthermore, there were no systems that could provide emotion-based advice when the user entered a new question. For this reason, flexible responses based on the user's emotions are required.

[1414] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for collecting generative AI advice in response to user questions, means for handling a wide range of areas such as work such as marketing, research, brainstorming, and programming, study plans, recipe development, and story creation, means for providing this advice to the user, an emotion engine for analyzing the user's emotions in real time, means for adjusting the generative AI advice based on the user's emotions, and means for providing an input field in which the user can input a new question and receive advice in response to it. This makes it possible to provide appropriate advice according to the user's emotions.

[1415] "Means for collecting advice from generative AI in response to user questions" is a function for collecting advice provided by generative AI in response to questions entered by users.

[1416] "A means to cover a wide range of areas, including marketing, research, brainstorming, programming, learning plans, recipe development, and story writing" is a function that enables generative AI to provide appropriate advice in a variety of fields.

[1417] "Means for providing these pieces of advice to users" refers to a function for displaying the advice provided by the generative AI to users.

[1418] An "emotion engine that analyzes user emotions in real time" is a system that analyzes a user's emotional state in real time based on their input and actions.

[1419] "Means for adjusting the advice of the generative AI based on the user's emotions" refers to a function that appropriately changes the content of the advice provided by the generative AI according to the user's emotional state analyzed by the emotion engine.

[1420] "Means for providing an input field where users can enter new questions and receive advice in response" refers to a function that provides an interface where users can enter new questions and receive advice from generative AI in response to those questions.

[1421] A system for implementing this invention includes means for collecting generative AI advice in response to user questions, means for addressing a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story writing, means for providing this advice to the user, an emotion engine for analyzing user emotions in real time, means for adjusting the generative AI advice based on the user emotions, and means for providing an input field in which the user can enter new questions and receive advice in response to them.

[1422] System Program

[1423] The program of this system operates as follows.

[1424] 1. How to gather generative AI advice for user questions:

[1425] The server receives the question entered by the user and generates advice for that question using a generative AI model, such as OpenAI's GPT-3.

[1426] 2. A tool for a wide range of areas, including marketing, research, brainstorming, programming, lesson planning, recipe creation, story writing, etc.:

[1427] The server uses generative AI models to provide appropriate advice for questions in various fields, allowing users to receive advice in a wide range of areas.

[1428] 3. How these advices are provided to users:

[1429] The server displays the generated advice to the user through a user interface, which displays the advice in a text format so that the user can easily understand it.

[1430] 4. Sentiment engine that analyzes user sentiment in real time:

[1431] The server uses an emotion engine to analyze emotions from the user's input text in real time.

[1432] 5. How to tailor generative AI advice based on user sentiment:

[1433] The server then adjusts the advice provided by the generative AI based on the user's emotional state as analyzed by the emotion engine. For example, if the user is feeling anxious, the server generates advice to alleviate that anxiety.

[1434] 6. Provide an input field where users can enter new questions and receive advice on them:

[1435] The server provides an interface where users can enter new questions and receive advice from the generative AI on those questions.

[1436] Specific examples

[1437] For example, if a user types, "I've been seeing a lot of suspicious people around my house lately and it makes me anxious," the emotion engine will detect the word "anxiety" and generate the following prompt:

[1438] My users are worried. Can you offer some security advice?

[1439] If you feed this prompt to a generative AI model, it might generate advice like this:

[1440] "If you've noticed a lot of suspicious people around your home recently, consider the following:

[1441] 1. Install security cameras around your home.

[1442] 2. Share information with neighbors and increase patrols.

[1443] 3. If you see anyone suspicious, report it to the police immediately.

[1444] 4. Double-check that your doors and windows are locked and install a security system.

[1445] In this way, it becomes possible to provide appropriate advice according to the user's emotions.

[1446] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1447] Step 1:

[1448] A user inputs a question using a terminal. The input question is sent to the server as text data. The input data is text that includes the content of the user's question.

[1449] Step 2:

[1450] The server sends the received user question to a generative AI model. The generative AI model uses, for example, OpenAI's GPT-3, to generate advice for the question. The input data is text containing the user's question, and the output data is text containing the generated advice.

[1451] Step 3:

[1452] The server displays the generated advice in a user interface. The user interface displays the advice in a text format so that the user can easily understand it. The input data is the text containing the generated advice, and the output data is the text displayed in the user interface.

[1453] Step 4:

[1454] The server uses an emotion engine to analyze emotions from user input text in real time. The input data is text containing the user's question, and the output data is data indicating the analyzed emotional state.

[1455] Step 5:

[1456] The server appropriately adjusts the content of the advice provided by the generative AI based on the user's emotional state analyzed by the emotion engine. For example, if the user is feeling anxious, the server generates advice to alleviate the anxiety. The input data is data indicating the analyzed emotional state, and the output data is text containing the adjusted advice.

[1457] Step 6:

[1458] The server provides an interface where users can enter new questions and receive advice from the generative AI for those questions. The input data is text containing the newly entered question by the user, and the output data is text containing advice provided by the generative AI.

[1459] 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.

[1460] 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.

[1461] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1462] 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.

[1463] [Third embodiment]

[1464] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1465] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1466] 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).

[1467] 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.

[1468] 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.

[1469] 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).

[1470] 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.

[1471] 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.

[1472] 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.

[1473] 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.

[1474] 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.

[1475] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1476] "Example 1"

[1477] In one embodiment of the present invention, the means for gathering generative AI advice includes an AI engine that receives a question from a user and generates generative AI advice in response to the question. The AI ​​engine uses natural language processing techniques to analyze the user's question and generate appropriate advice. For example, if a user asks, "How should I develop a marketing strategy?", the AI ​​engine generates advice such as, "Analyze your competitors, understand your target market, evaluate the strengths and weaknesses of your product, etc."

[1478] "Example 2"

[1479] In one embodiment of the present invention, the means for handling a wide range of tasks, such as marketing, research, brainstorming, programming, learning plans, recipe creation, and story writing, includes AI modules specialized in each area. These AI modules have expertise in their respective areas and generate specific advice in response to user questions. For example, if a user asks, "I don't know what to make," an AI module specialized in recipe creation generates advice such as, "I'll suggest a new recipe based on the ingredients you have on hand and your preferences."

[1480] "Example 3"

[1481] Furthermore, in one embodiment of the present invention, the means for providing the user with these pieces of advice includes a user interface. The user interface displays the generated advice to the user, allowing the user to easily understand the advice and take action based on it. For example, the user interface displays the generated advice in a text format so that the user can read it. The user interface also provides an input field where the user can enter a new question and receive advice in response to the question.

[1482] The processing flow of each embodiment will be described below.

[1483] "Example 1"

[1484] Step 1: Receiving a question from the user In this step, a question from the user is received through the user interface.

[1485] Step 2: Analyze the question and generate advice. In this step, the AI ​​engine uses natural language processing technology to analyze the user's question and generate appropriate advice.

[1486] Step 3: Providing the generated advice to the user. In this step, the generated advice is displayed to the user through a user interface, allowing the user to easily understand the advice and take action based on it.

[1487] "Example 2"

[1488] Step 1: Receiving a question from the user In this step, a question from the user is received through the user interface.

[1489] Step 2: Analyze the question and select an AI module specialized in a specific domain. In this step, the AI ​​engine uses natural language processing technology to analyze the user's question and select an AI module specialized in a specific domain based on the content of the question.

[1490] Step 3: Generate advice using the selected AI module and provide it to the user. In this step, the selected AI module generates specific advice for the user's question and displays the generated advice to the user through the user interface.

[1491] "Example 3"

[1492] Step 1: Receiving a question from the user In this step, a question from the user is received through the user interface.

[1493] Step 2: Analyze the question and generate advice. In this step, the AI ​​engine uses natural language processing technology to analyze the user's question and generate appropriate advice.

[1494] Step 3: Providing the generated advice to the user. In this step, the generated advice is displayed to the user through a user interface, allowing the user to easily understand the advice and take action based on it.

[1495] Step 4: User Enters New Question: In this step, the user interface provides an input field where the user can enter a new question and receive advice on it.

[1496] Example 1

[1497] 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."

[1498] Conventional generative AI systems can have difficulty providing appropriate advice in response to user questions. Furthermore, they lack guidelines and instructions for users to effectively ask generative AI, which can lead to problems with users being unable to accurately obtain the information they are looking for. Furthermore, they lack the flexibility to handle a wide range of tasks, including marketing, research, brainstorming, and programming.

[1499] 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.

[1500] In this invention, the server includes means for receiving a user's question, means including an AI engine using natural language processing technology for analyzing the received question, means for generating appropriate advice based on the analyzed question, means for providing the generated advice to the user, means for dealing with a wide range of areas such as marketing, research, brainstorming, programming and other work, study plans, recipe creation, story creation, etc., and means for providing this advice to the user. This enables the user to obtain appropriate advice in a wide range of areas, and also provides instructions for improving the way questions are asked and guidelines for asking more effective questions, allowing the user to accurately obtain the information they are looking for.

[1501] The "means for receiving a user's question" is an interface that allows the system to receive a question entered by the user.

[1502] "AI engine using natural language processing technology" refers to artificial intelligence technology that analyzes user questions and generates appropriate advice.

[1503] "Means for generating appropriate advice based on the analyzed questions" refers to the process by which the AI ​​engine creates specific advice for the user based on the analysis results.

[1504] "Means for providing generated advice to a user" refers to a method for displaying or transmitting advice generated by an AI engine to a user.

[1505] "A tool for a wide range of areas, including marketing, research, brainstorming, programming, study planning, recipe creation, and story writing" is a function that provides appropriate advice to users' questions in various fields.

[1506] "Instructions for improving how you ask questions" provide specific advice or guidelines to help users ask questions more effectively.

[1507] The "Guidelines for Asking More Effective Questions" provide guidelines and methods for users to ask appropriate questions to generative AI.

[1508] This invention is a system that provides generative AI advice in response to a user's question. This system includes an AI engine that receives the user's question, analyzes it using natural language processing technology, and generates appropriate advice. Specific embodiments of this system are described below.

[1509] First, the user enters a question using their own device (e.g., a PC or smartphone). For example, the user might enter, "How should I develop a marketing strategy?" This question is sent from the device to the server. Data is sent over the Internet.

[1510] The server passes the received question to an AI engine. This AI engine uses natural language processing technology to analyze the user's question. Specifically, a generative AI model such as GPT-4 is used as the AI ​​engine. The AI ​​engine understands the content of the question and generates appropriate advice. For example, it generates advice such as "analyze competitors, understand the target market, and evaluate the strengths and weaknesses of the product."

[1511] The generated advice is sent to the user's device via the server. The device displays the received advice to the user. The user can check the displayed advice and use it as reference.

[1512] As a concrete example, the following prompt sentence can be input to a generative AI model:

[1513] Example prompt sentence:

[1514] How do I create a marketing strategy?

[1515] Given this prompt, the AI ​​engine might generate the following advice:

[1516] Example of generated advice:

[1517] "To develop a marketing strategy, it is important to first analyze your competitors, then understand your target market, and finally evaluate the strengths and weaknesses of your product."

[1518] In this way, users can get helpful advice for specific questions, and the system can be used in a wide range of areas, including marketing, research, brainstorming, programming, lesson planning, recipe creation, story writing, and more.

[1519] Additionally, the generative AI's advice includes instructions to improve the way users ask questions and guidelines for asking more effective questions, allowing users to use the generative AI more effectively.

[1520] To implement this system, it is important to use an appropriate combination of hardware and software, such as servers, terminals, and AI engines that use natural language processing technology (e.g., GPT-4).

[1521] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1522] Step 1:

[1523] The user enters a question

[1524] A user inputs a question using their own device (e.g., a PC or smartphone). For example, the user might input, "How should I develop a marketing strategy?" This input question becomes the starting point for the system's processing.

[1525] Step 2:

[1526] The device sends a question to the server

[1527] The terminal sends the question entered by the user to the server via the Internet using the HTTPS protocol. The input is the user's question, and the output is the question data sent to the server.

[1528] Step 3:

[1529] The server receives the question and passes it to the AI ​​engine.

[1530] The server receives questions sent from the device. The received questions are passed to the AI ​​engine in the server. The input is the question data received from the device, and the output is the question data passed to the AI ​​engine.

[1531] Step 4:

[1532] An AI engine analyzes the question and generates advice

[1533] The AI ​​engine analyzes the user's question using natural language processing technology. Specifically, it uses a generative AI model such as GPT-4 as the AI ​​engine. Based on the analyzed question, the AI ​​engine generates appropriate advice. For example, it generates advice such as "analyze competitors, understand the target market, and evaluate the strengths and weaknesses of the product." The input is the question data passed from the server, and the output is the generated advice.

[1534] Step 5:

[1535] The server receives the generated advice and sends it to the device.

[1536] The server receives the advice generated by the AI ​​engine. The received advice is then sent to the user's device via the Internet. The HTTPS protocol is again used for transmission. The input is the advice received from the AI ​​engine, and the output is the advice sent to the device.

[1537] Step 6:

[1538] The device displays the advice to the user.

[1539] The terminal receives advice sent from the server. The received advice is displayed in a format that is easy for the user to view. The user can check the displayed advice and use it as a reference. The input is the advice received from the server, and the output is the advice displayed to the user.

[1540] (Application example 1)

[1541] 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."

[1542] Conventional advice systems using generative AI allow users to receive advice by inputting specific questions, but there is a lack of means to provide appropriate advice in real time when selecting products in physical stores. This makes it difficult for users to obtain appropriate information when choosing products, resulting in a long time required for purchasing decisions. Furthermore, there is a lack of guidelines for users to ask effective questions to generative AI or instructions for improving the way questions are asked, which leads to a decline in the quality of the advice users receive.

[1543] 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.

[1544] In this invention, the server includes a means for collecting advice from the generative AI in response to user questions, a means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe creation, and story creation, a means for providing this advice to the user, and a means for the user to input questions when selecting products in a physical store and for the generative AI to provide advice in real time. This enables users to receive appropriate advice in real time when selecting products in a physical store, enabling faster purchasing decisions and improved quality of advice.

[1545] A "user" is an individual or organization that uses the system to input questions and receive advice from the generative AI.

[1546] A "question" is information or a question that a user inputs into a generative AI, and is input data for obtaining advice.

[1547] "Generative AI" is an artificial intelligence engine that analyzes users' questions and generates appropriate advice.

[1548] "Advice" refers to information or instructions that generative AI provides based on a user's question.

[1549] A "physical store" is a commercial facility located in a physical location where users can directly select and purchase products.

[1550] "Product selection" refers to the act of a user selecting a product to purchase in a physical store.

[1551] "Real-time" refers to the generative AI providing immediate advice as soon as the user types in a question.

[1552] "Marketing" refers to the activities and strategies used to promote the sale of products and services.

[1553] "Research" is an investigative activity aimed at gathering and analyzing specific information.

[1554] "Brainstorming" is an abbreviation of brainstorming, a creative activity in which ideas are freely exchanged.

[1555] A "program" is a sequence of instructions or code that is executed by a computer.

[1556] A "study plan" is a specific plan or schedule for achieving learning goals.

[1557] "Recipe development" is the act of coming up with cooking steps and ingredients.

[1558] "Story creation" is the act of creating a story or scenario.

[1559] To implement this invention, a user uses a smartphone application when selecting a product in a physical store. A specific embodiment of this system will be described below.

[1560] System Configuration

[1561] The system consists of the following main components:

[1562] 1. User device: Smartphone

[1563] 2. Server: A server that hosts the generative AI engine

[1564] 3. Software: Python, OpenAI API

[1565] Program processing

[1566] The server includes a means for collecting generative AI advice in response to user questions, a means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation, a means for providing this advice to users, and a means for users to input questions when selecting products in a physical store and for the generative AI to provide advice in real time.

[1567] Hardware and Software

[1568] Hardware: The user device is a smartphone. The server is a high-performance computer that hosts the generative AI engine.

[1569] Software: Uses a Python program and OpenAI API. The Python program receives a user question and calls OpenAI's API to generate advice using a generative AI model (e.g., GPT-3).

[1570] Data processing and calculation

[1571] When a user enters a question through a smartphone app, the question is sent to the server. The server receives the question and calls the OpenAI API through a Python program. The API sends the question as a prompt to the generative AI model, which then analyzes the question and generates appropriate advice. The generated advice is then returned from the server to the user's device and displayed to the user.

[1572] Specific examples

[1573] If a user asks, "Is this product cheaper than other stores?" in a physical store, the AI ​​engine will provide advice such as, "This product is priced averagely compared to other stores. We recommend checking the price online as well."

[1574] Example prompt sentence:

[1575] User Question: Is this product cheaper than other stores?

[1576] Please provide advice.

[1577] In this way, users can receive relevant advice in real time when choosing products in physical stores, enabling faster purchasing decisions and better advice.

[1578] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1579] Step 1:

[1580] The user launches the smartphone app and enters a question.

[1581] Input: User question (e.g. "Is this product cheaper than other stores?")

[1582] Output: User question data

[1583] Specific behavior: The user enters a question into the app's text input field and presses the submit button.

[1584] Step 2:

[1585] The terminal sends the user's question data to the server.

[1586] Input: User question data

[1587] Output: The query data sent to the server

[1588] Specific operation: The smartphone app sends the question data to the server as an HTTP request.

[1589] Step 3:

[1590] The server receives the query data and runs the Python program.

[1591] Input: Query data sent to the server

[1592] Output: Prompt sentence to the generative AI model

[1593] Specific operation: The server receives an HTTP request and passes the question data to the Python program, which converts the question data into a prompt.

[1594] Step 4:

[1595] The server calls the OpenAI API and sends a prompt to the generative AI model.

[1596] Input: prompt sentence for generative AI model

[1597] Output: Advice from a generative AI model

[1598] Specific operation: The Python program calls the OpenAI API and sends a prompt to a generative AI model (e.g., GPT-3).

[1599] Step 5:

[1600] A generative AI model analyzes the prompt and generates appropriate advice.

[1601] Input: prompt statement

[1602] Output: Generated advice

[1603] How it works: The generative AI model analyzes the prompt and generates advice based on its internal learning data.

[1604] Step 6:

[1605] The server receives the generated advice and returns it to the user terminal.

[1606] Input: Generated advice

[1607] Output: Advice sent to user terminal

[1608] Specific operation: The server receives advice from the generative AI model and sends it to the user device as an HTTP response.

[1609] Step 7:

[1610] The device receives the advice from the server and displays it to the user.

[1611] Input: Advice sent by the server

[1612] Output: Advice displayed to the user

[1613] Specific operation: The smartphone app receives the HTTP response and displays the advice on the screen.

[1614] In this way, users can get real-time, relevant advice when choosing products in a physical store.

[1615] Example 2

[1616] 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."

[1617] Conventional generative AI systems have difficulty providing appropriate advice in response to user questions, especially when dealing with a wide range of domains. Furthermore, there is a lack of guidelines and instructions for users to ask generative AI effective questions, which leads to a decline in the quality of user questions.

[1618] 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.

[1619] In this invention, the server includes means for inputting a user's question, means for transmitting the question to the server, means for selecting an appropriate AI module based on the question, means for inputting a prompt sentence to a generative AI model using the AI ​​module, means for the generative AI model to generate advice, means for providing the generated advice to a user, and means for handling a wide range of areas such as marketing, research, brainstorming, program creation, study plans, recipe creation, story creation, etc. This makes it possible to provide appropriate and specialized advice in response to a user's question, and to provide guidelines and instructions for users to ask effective questions to the generative AI.

[1620] A "means for inputting a user's question" is a device or software that provides an interface for a user to input a question to the system.

[1621] The "means for transmitting the question to the server" refers to a communication means for transmitting the question entered by the user to the server.

[1622] The "means for selecting an appropriate AI module based on the question" refers to an algorithm or program for analyzing the content of the user's question and selecting the AI ​​module that is most suitable for that content.

[1623] "Means for inputting a prompt sentence to a generative AI model using the AI ​​module" refers to means for creating and inputting an appropriate prompt sentence to a generative AI model using a selected AI module.

[1624] "Means for the generative AI model to generate advice" refers to means for the generative AI model to generate advice for the user based on the input prompt sentence.

[1625] "Means for providing the generated advice to the user" refers to means for displaying or notifying the user of the advice generated by the generative AI model.

[1626] "Means that cover a wide range of areas, including marketing, research, brainstorming, program creation, lesson planning, recipe development, and story writing" includes AI modules specialized in these wide-ranging areas, and are means for providing expert advice in each area.

[1627] This invention is a system for providing appropriate advice in response to a user's question. The system includes means for inputting a user's question, means for transmitting the question to a server, means for selecting an appropriate AI module based on the question, means for inputting a prompt sentence to a generative AI model using the AI ​​module, means for the generative AI model to generate advice, means for providing the generated advice to a user, and means for handling a wide range of areas such as marketing, research, brainstorming, program creation, study planning, recipe creation, and story creation.

[1628] Specifically, a user uses a device such as a smartphone or PC to input a question, such as "Tell me what to make for dinner tonight." The device receives this question and sends it to the server using an HTTP POST request.

[1629] The server analyzes the received question and selects the appropriate AI module based on its content. For example, if the question is about recipes, it selects an AI module that specializes in recipe creation. The server then uses the selected AI module to create a prompt to be input to the generative AI model. The prompt includes information about the user's question, ingredients on hand, and preferences.

[1630] Examples of specific prompts include:

[1631] User Asks: "What should I make for dinner tonight?"

[1632] Ingredients on hand: "Chicken, tomatoes, basil, cheese."

[1633] Favorite food: "Italian food"

[1634] The server inputs this prompt into a generative AI model, which then uses its internal algorithms to generate advice, such as "I recommend making Caprese chicken with chicken, tomatoes, basil, and cheese."

[1635] The generated advice is sent from the server to the device, and the device displays the advice to the user, who can then check the specific advice on the device screen.

[1636] The system allows users to receive expert advice in a wide range of areas and also provides guidelines and instructions to improve the quality of their questions, greatly improving user convenience.

[1637] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1638] Step 1:

[1639] The user enters a question.

[1640] Users open the application on their smartphone or computer and type into the text box, "Tell me what to make for dinner tonight," and the question is sent to the device.

[1641] Step 2:

[1642] The terminal sends a question to the server.

[1643] The terminal receives user input and sends a question to the server using an HTTP POST request: the input data is the user's question, and the output is the request sent to the server.

[1644] Step 3:

[1645] The server analyzes the question and selects the appropriate AI module.

[1646] The server analyzes the received question using natural language processing technology. Based on the analysis results, it determines that the question is about recipes and selects an AI module specialized in recipe creation. The input data is the user's question, and the output is the selected AI module.

[1647] Step 4:

[1648] The server inputs a prompt sentence into the generative AI model.

[1649] The server uses the selected AI module to create a prompt to be input to the generative AI model. The prompt includes information such as the user's question, ingredients on hand, and preferences. For example, a prompt might be generated as follows: "User question: 'Tell me what to make for dinner tonight' Ingredients on hand: 'Chicken, tomatoes, basil, cheese' Preferences: 'Italian food'." The input data is the user's question and related information, and the output is the prompt.

[1650] Step 5:

[1651] A generative AI model generates advice.

[1652] The generative AI model receives a prompt and uses its internal algorithm to generate advice, such as "I recommend making Caprese Chicken with chicken, tomatoes, basil, and cheese." The input data is the prompt, and the output is the generated advice.

[1653] Step 6:

[1654] The server transmits the generated advice to the terminal.

[1655] The server receives the advice obtained from the generative AI model and sends it to the terminal as an HTTP response. The input data is the generated advice, and the output is the response sent to the terminal.

[1656] Step 7:

[1657] The terminal displays the advice to the user.

[1658] The terminal displays the advice received from the server to the user. The user can see the advice on the terminal screen: "We recommend making Caprese Chicken with chicken, tomatoes, basil, and cheese." The input data is the advice from the server, and the output is what is displayed to the user.

[1659] (Application example 2)

[1660] 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."

[1661] Conventional generative AI systems can sometimes make it difficult for users to get appropriate advice when asking specific questions. They also lack specific assistance to improve the shopping experience in brick-and-mortar stores, such as when users don't know what to buy or want recipe suggestions using specific ingredients. Therefore, there is a need for a system that can provide appropriate advice in response to user questions and improve the shopping experience in brick-and-mortar stores.

[1662] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for collecting generative AI advice in response to a user's question, a means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation, a means for providing this advice to the user, a means for generating a prompt sentence for the generative AI model based on text entered by the user, and a means for displaying the generated advice to the user. This allows the user to receive appropriate advice when asking a specific question, improving the shopping experience in a physical store.

[1663] "Means for collecting advice from generative AI in response to user questions" is a function for collecting advice provided by generative AI in response to questions entered by users.

[1664] "A means to address a wide range of areas, including marketing, research, brainstorming, programming, study plans, recipe development, and story creation" is a function that uses generative AI modules specialized in various fields to provide appropriate advice to users' questions in each area.

[1665] "Means for providing these pieces of advice to users" refers to a function for displaying or notifying users of the advice provided by the generative AI.

[1666] "Means for generating prompt sentences for a generative AI model based on text entered by a user" refers to a function for automatically generating prompt sentences suitable for a generative AI model based on questions or requests entered by a user.

[1667] "Means for displaying generated advice to the user" refers to a function for visually displaying advice generated by the generative AI model to the user.

[1668] The following system configuration is used as an embodiment of this invention. The system includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe creation, and story creation; means for providing this advice to the user; means for generating prompt sentences for the generative AI model based on text entered by the user; and means for displaying the generated advice to the user.

[1669] Hardware and software used

[1670] Hardware: Smartphone

[1671] Software: Python, OpenAI API

[1672] Data processing and calculation

[1673] 1. Getting user input: A user types a question or request through a smartphone application, for example, "I don't know what to buy."

[1674] 2. Prompt generation: The server generates a prompt appropriate for the generative AI model based on the user's input. For example, it generates a prompt such as, "If the user says, 'I don't know what to buy,' please suggest new products based on the products they have on hand and their preferences."

[1675] 3. Calling the AI ​​model: The server passes the generated prompt sentence to the generative AI model via the OpenAI API to generate advice.

[1676] 4. Displaying Advice: The server displays the generated advice to the user through a smartphone application. For example, it displays advice such as "Suggested products: fresh vegetables, organic milk, whole wheat bread."

[1677] Specific examples

[1678] If a user uses a smartphone application and types "I don't know what to buy," the system works as follows:

[1679] 1. The user types, "I don't know what to buy."

[1680] 2. The server generates the following prompt based on the entered text:

[1681] If a user says, "I don't know what to buy," suggest new products based on what they have on hand and their preferences.

[1682] 3. The server passes this prompt to the generative AI model via the OpenAI API to generate advice.

[1683] 4. The server displays the generated advice to the user through a smartphone application, for example, "Suggested products: fresh vegetables, organic milk, whole wheat bread."

[1684] In this way, users can get the right advice for their specific questions, enhancing their in-store shopping experience.

[1685] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1686] Step 1:

[1687] A user inputs a question or request through a smartphone application. For example, they might input, "I don't know what to buy." This input becomes the initial data for the system.

[1688] Step 2:

[1689] The terminal sends the text entered by the user to the server. The input data is the text "I don't know what to buy."

[1690] Step 3:

[1691] The server generates a prompt sentence suitable for the generative AI model based on the received text. Specifically, it generates the following prompt sentence:

[1692] If a user says, "I don't know what to buy," suggest new products based on what they have on hand and their preferences.

[1693] This prompt sentence is generated.

[1694] Step 4:

[1695] The server passes the generated prompt sentence to the generative AI model through the OpenAI API. The input data is the generated prompt sentence, and the output data is the advice returned by the generative AI model.

[1696] Step 5:

[1697] The server receives the advice returned by the generative AI model, for example, "Suggested products: fresh vegetables, organic milk, whole wheat bread."

[1698] Step 6:

[1699] The server sends the received advice to the terminal for display to the user. The input data is the advice from the generative AI model, and the output data is the advice displayed to the user.

[1700] Step 7:

[1701] The device displays the advice received from the server to the user through a smartphone application. For example, the advice "Suggested products: fresh vegetables, organic milk, whole wheat bread" is displayed to the user.

[1702] In this way, users can get the right advice for their specific questions, improving their shopping experience in physical stores.

[1703] Example 3

[1704] 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."

[1705] In systems using conventional generative AI models, the process from when a user inputs a question to when they receive appropriate advice is complicated, and there are problems with a lack of guidelines or instructions for users to ask questions effectively. Another issue is that the generated advice is not properly communicated to users, making it difficult for them to act on it.

[1706] 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.

[1707] In this invention, the server includes means for receiving a user's question, means for transmitting the received question to the server, means for the server to input the question into a generative AI model and generate advice, means for transmitting the generated advice from the server to the terminal, means for the terminal to display the advice to the user, and means for the user to input a new question. This enables the user to effectively ask questions, appropriately receive the generated advice, and take action based on it.

[1708] "User" means an individual or entity that utilizes the System to enter questions and receive generated advice.

[1709] A "terminal" is an electronic device that a user uses to enter questions and view generated advice.

[1710] The "server" is a computer system that receives questions from users, inputs them into a generative AI model to generate advice, and sends it to the terminal.

[1711] A "generative AI model" is an artificial intelligence algorithm that generates appropriate advice based on a user's questions.

[1712] A "question" is information or a question that a user inputs into the system.

[1713] "Advice" is an answer or suggestion that a generative AI model generates based on a user's question.

[1714] A "user interface" is the part of a system that contains screens and input fields through which a user can enter questions and view generated advice.

[1715] A "prompt" is text containing a user question or instruction that is input into a generative AI model.

[1716] This invention is a system that allows a user to input a question and obtain appropriate advice using a generative AI model. This system includes a series of processes that receive the user's question, input it into the generative AI model, and provide the generated advice to the user.

[1717] Hardware and software used

[1718] Hardware

[1719] Device: An electronic device that allows users to input questions and view generated advice. Examples include computers, smartphones, and tablets.

[1720] Server: A computer system that receives questions from users, inputs them into a generative AI model to generate advice, and sends it to the device.

[1721] software

[1722] Generative AI models: Artificial intelligence algorithms that generate appropriate advice based on user questions. Examples include OpenAI's GPT-3.

[1723] User Interface: Software that contains screens and input fields for users to enter questions and view generated advice.

[1724] Data processing and calculation

[1725] Data Processing

[1726] Receiving user input: The user enters a question using the device's user interface. This input is in the form of text.

[1727] Sending a question: The device sends the question entered by the user to the server using a communication protocol such as an HTTP request.

[1728] Data Calculation

[1729] Advice generation: The server inputs the received question into the generative AI model and generates appropriate advice. The generative AI model generates text-based advice based on the input question.

[1730] Sending and displaying advice: The server sends the generated advice to the terminal, which displays the advice through a user interface.

[1731] Specific examples

[1732] Prompt Sentence Examples

[1733] Let's say a user wants advice on a new business idea. Here's an example prompt to input to a generative AI model:

[1734] Example prompt: "I have a new business idea in mind. How should I go about it?"

[1735] Example of advice generated: "First, conduct market research and identify your target audience. Then create a business plan and figure out how to raise funds."

[1736] In this way, the user can receive specific advice and decide on the next action based on it. This system enables the user to effectively ask questions, appropriately receive the generated advice, and take action based on it. The flow of the identification process in Example 3 will be described with reference to FIG. 15.

[1737] Step 1:

[1738] The user enters a question.

[1739] A user inputs a question using the user interface of a terminal. Specifically, the user inputs, "I'm thinking of a new business idea. How should I go about it?" This input is in text format. The input data is the user's question text.

[1740] Step 2:

[1741] The terminal sends a question to the server.

[1742] The terminal sends the question entered by the user to the server. This transmission is performed using a communication protocol such as an HTTP request. Specifically, the terminal sends the question "I'm thinking of a new business idea. How should I go about it?" to the server. The input data is the user's question text, and the output data is the question text sent to the server.

[1743] Step 3:

[1744] The server inputs the question into a generative AI model.

[1745] The server inputs the received question into the generative AI model. Specifically, the server inputs a prompt to the generative AI model: "I'm thinking of a new business idea. How should I go about it?" The input data is the question text sent to the server, and the output data is the prompt input to the generative AI model.

[1746] Step 4:

[1747] A generative AI model generates advice.

[1748] The generative AI model generates advice based on the input question. Specifically, the generative AI model generates the advice, "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the prompt sentence entered into the generative AI model, and the output data is the generated advice text.

[1749] Step 5:

[1750] The server receives the generated advice.

[1751] The server receives the advice returned from the generative AI model. Specifically, the server receives the advice, "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the advice text returned from the generative AI model, and the output data is the advice text received by the server.

[1752] Step 6:

[1753] The server sends the advice to the terminal.

[1754] The server sends the advice it receives to the terminal. This transmission is also performed using a communication protocol such as an HTTP request. Specifically, the server sends the advice to the terminal: "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the advice text received by the server, and the output data is the advice text sent to the terminal.

[1755] Step 7:

[1756] The terminal displays the advice to the user.

[1757] The terminal displays the received advice on the user interface. Specifically, the terminal displays on the user interface, "First, conduct market research and identify your target audience. Then, create a business plan and consider how to raise funds." The input data is the advice text sent to the terminal, and the output data is the advice text displayed on the user interface.

[1758] Step 8:

[1759] The user enters a new question.

[1760] The user can again enter a new question using the input field of the user interface. In a specific operation, the user enters "Please tell me the specific methods of market research." The input data is the newly entered question text, and the output data is the new question text entered into the user interface.

[1761] (Application example 3)

[1762] 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."

[1763] Conventional advice-giving systems using generative AI can provide advice in response to user questions, but it is difficult to provide advice specialized in a specific area. Furthermore, the interface for users to input new questions and receive advice in response to them is insufficient, resulting in a poor user experience. Providing appropriate advice for security-related questions is particularly important.

[1764] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for collecting generative AI advice in response to user questions, means for handling a wide range of areas such as marketing, research, brainstorming, programming, and other work, study plans, recipe development, and story creation, means for providing this advice to the user, means for providing optimal advice in response to security-related questions, and means for allowing the user to input new questions and receive advice in response to them through a user interface. This allows the user to receive advice specialized in a specific area, and in particular, appropriate advice in response to security-related questions.

[1765] A "user" is an individual or corporation that uses the system to input questions and receive advice from the generative AI.

[1766] A "question" is information or a question that a user inputs into a generative AI, which serves as a trigger for obtaining advice.

[1767] "Generative AI" refers to artificial intelligence that generates appropriate advice in response to user questions.

[1768] "Advice" refers to advice or suggestions provided by generative AI based on a user's questions.

[1769] "Marketing" refers to the activities and strategies aimed at promoting products and services.

[1770] "Research" is the activity of collecting and analyzing information on a particular topic or issue.

[1771] "Brainstorming" is an abbreviation of "brainstorming," a creative activity in which ideas are freely exchanged.

[1772] A "program" is a set of instructions or code that a computer executes.

[1773] A "study plan" is a specific plan or schedule for achieving learning goals.

[1774] "Recipe development" refers to the activity of coming up with cooking procedures and ingredients.

[1775] "Story writing" refers to the activity of creating a story or scenario.

[1776] "Security" refers to the measures and procedures for protecting information and physical assets.

[1777] A "user interface" is a screen or input device that allows a user to interact with a system.

[1778] A "means" is a method or device used to achieve a particular purpose.

[1779] A "system" is a structure or mechanism in which multiple elements work together to achieve a specific function.

[1780] The system for implementing this invention collects generative AI advice in response to user questions and provides advice tailored to specific domains, particularly those related to security.

[1781] System configuration

[1782] The system consists of the following main components:

[1783] 1. User device: The device on which the user enters their question and receives advice. This can be a smartphone or a computer.

[1784] 2. Server: Hosts the generative AI model and generates advice in response to user questions.

[1785] 3. User Interface: The interface through which users can enter their questions and receive advice.

[1786] Program processing

[1787] The server performs the following steps:

[1788] 1. Receiving a question: Receive a question entered from the user's terminal.

[1789] 2. Invoke a generative AI model: The received question is sent as a prompt to a generative AI model, such as OpenAI's GPT-3.

[1790] 3. Advice generation: A generative AI model generates advice in response to the question.

[1791] 4. Sending advice: The generated advice is sent to the user terminal.

[1792] Hardware and software used

[1793] Hardware: Smartphones, PCs, and servers with internet connectivity.

[1794] Software: Python, OpenAI API, front-end framework for user interface (e.g. React, Vue.js).

[1795] Specific examples

[1796] If a user asks, "Where is the best place to put a home security camera?" the system works as follows:

[1797] 1. A question is sent from the user device to the server.

[1798] 2. The server sends the question as a prompt to the generative AI model.

[1799] 3. A generative AI model generates advice in response to the question.

[1800] 4. The server sends the generated advice to the user device.

[1801] 5. Advice will be displayed on the user's device's user interface.

[1802] Prompt Sentence Examples

[1803] Security Question: Where is the best place to install a home security camera?

[1804] Please provide the best advice.

[1805] In this way, users can receive advice specific to a particular area, and in particular, get advice that is relevant to security-related questions.

[1806] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1807] Step 1:

[1808] The user inputs a question using a terminal. The input question is sent to the server through the user interface. The input data is a text question, such as "Where is the best place to install a home security camera?"

[1809] Step 2:

[1810] The server analyzes the received question and converts it into a format suitable for the generative AI model. In this conversion process, the question is formatted as a prompt. The input data is the user's question, and the output data is the prompt to be sent to the generative AI model.

[1811] Step 3:

[1812] The server sends a prompt to a generative AI model (e.g., OpenAI's GPT-3). The generative AI model receives the prompt and generates advice for the question. The input data is the prompt, and the output data is the generated advice.

[1813] Step 4:

[1814] The server analyzes the advice received from the generative AI model and converts it into a format that is easy for the user to understand. In this conversion process, the generated advice is formatted into text. The input data is the advice from the generative AI model, and the output data is the text to be displayed to the user.

[1815] Step 5:

[1816] The server sends the formatted advice to the user terminal, which displays the received advice on a user interface. The input data is the formatted advice, and the output data is the text displayed on the user interface.

[1817] Step 6:

[1818] The user checks the displayed advice and enters a new question if necessary. When a new question is entered, the process starts again from step 1. The input data is the user's new question, and the output data is the advice that is generated again.

[1819] 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.

[1820] "Example 1"

[1821] One embodiment of the present invention is a system incorporating an emotion engine. This system collects generative AI advice in response to user questions and provides it to the user. The emotion engine also recognizes the user's emotions and tailors the advice based on those emotions. For example, if the user feels frustrated, the emotion engine communicates this information to the generative AI, which then generates advice to calm the user.

[1822] "Example 2"

[1823] Another embodiment is a system in which an emotion engine provides optimal advice to a user based on the user's emotions. In this system, the emotion engine analyzes the user's emotions in real time and generates advice optimal for those emotions. For example, if the emotion engine senses that the user is feeling joy, the emotion engine communicates that information to a generative AI, and the AI ​​generates advice that amplifies that joy.

[1824] "Example 3"

[1825] In yet another embodiment, an emotion engine adjusts the generative AI's advice based on the user's emotions. In this system, the emotion engine analyzes the user's emotions in real time and adjusts the generative AI's advice based on those emotions. For example, if the user feels sad, the emotion engine communicates that information to the generative AI, which then generates advice to alleviate the sadness.

[1826] The processing flow of each embodiment will be described below.

[1827] "Example 1"

[1828] Step 1: The user asks the system a question.

[1829] Step 2: Generative AI generates advice in response to the user's question.

[1830] Step 3: The emotion engine recognizes the user's emotion.

[1831] Step 4: Adjust the generative AI's advice based on the emotions recognized by the emotion engine.

[1832] Step 5: Provide tailored advice to users.

[1833] "Example 2"

[1834] Step 1: The user asks the system a question.

[1835] Step 2: The emotion engine analyzes user emotions in real time.

[1836] Step 3: Based on the emotions analyzed by the emotion engine, the generative AI generates optimal advice for the user.

[1837] Step 4: Providing the generated advice to the user.

[1838] "Example 3"

[1839] Step 1: The user asks the system a question.

[1840] Step 2: The emotion engine analyzes user emotions in real time.

[1841] Step 3: Adjust the generative AI's advice based on the emotions analyzed by the emotion engine.

[1842] Step 4: Provide tailored advice to users.

[1843] Example 1

[1844] 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."

[1845] Conventional generative AI systems were unable to consider the user's emotions when providing advice in response to user questions, making it difficult to provide appropriate advice based on the user's psychological state. Furthermore, they lacked the functionality to provide guidelines and instructions for users to ask effective questions to generative AI, making it difficult for users to efficiently obtain the information they were looking for.

[1846] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for collecting generative AI advice in response to a user's question, means for analyzing the user's question using natural language processing technology, means for generating appropriate advice using a generative AI engine, means for recognizing the user's emotion using an emotion engine, means for adjusting the advice based on the user's emotion, and means for providing this advice to the user. This makes it possible to provide appropriate advice that takes the user's emotion into consideration, and to provide guidelines and instructions for the user to ask the generative AI effective questions.

[1847] "Generative AI" is an artificial intelligence technology that generates appropriate advice and information in response to users' questions and requests.

[1848] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language.

[1849] A "generative AI engine" is a collection of software and algorithms that realizes generative AI, and has the ability to generate appropriate advice in response to user questions.

[1850] An "emotion engine" is a technology that recognizes a user's emotions and tailors appropriate advice based on those emotions.

[1851] A "user question" is a question or request that a user enters into the system.

[1852] "Advice" refers to advice or information provided by generative AI in response to a user's question.

[1853] "Analysis" is the process of understanding the intent and content of a user's question using natural language processing technology.

[1854] "Adjustment" is the process of appropriately modifying the generated advice based on the user's emotions recognized by the emotion engine.

[1855] "Providing" is the act of conveying the generated advice to the user.

[1856] MODE FOR CARRYING OUT THE INVENTION

[1857] This invention is a system that provides generative AI advice in response to user questions. The system includes natural language processing technology and a generative AI engine to analyze the user's question and generate appropriate advice. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the advice based on those emotions.

[1858] Hardware and software used

[1859] The server uses the following hardware and software to implement the system:

[1860] Natural language processing technology: Natural language processing models such as Google's BERT and OpenAI's GPT-3

[1861] Generative AI engine: Software and algorithms for realizing generative AI

[1862] Emotion engine: Emotion recognition technology such as Microsoft's Azure Cognitive Services

[1863] Communication method: Communication between the server and the terminal using HTTP requests

[1864] System Operation

[1865] The user inputs a question through the device interface. For example, the user might input, "How should we develop a marketing strategy for a new product?" The device then sends this question to the server. The server then analyzes the received question using natural language processing technology and understands the intent of the question. Based on the analysis results, the generative AI engine generates appropriate advice.

[1866] Furthermore, the server uses an emotion engine to recognize the user's emotions. For example, if the emotion engine recognizes that the user is irritated, the server adjusts the advice generated by the generative AI engine. The adjusted advice will correspond to the user's emotions.

[1867] Specific examples

[1868] As a concrete example, consider the case where a user asks, "How should we develop a marketing strategy for a new product?" In this case, the server inputs the following prompt into the generative AI model:

[1869] Example prompt sentence:

[1870] A user asks: "How do I develop a marketing strategy for my new product?"

[1871] Prompt for the generative AI model: "What steps should I take to develop a marketing strategy for a new product? Please provide specific advice."

[1872] Based on this prompt, the generative AI model generates the following advice:

[1873] "To develop a marketing strategy for a new product, it is important to first conduct a competitor analysis and understand the target market. Next, evaluate the product's strengths and weaknesses and create a marketing message based on that. It is also necessary to choose the right advertising channels and carry out effective promotion."

[1874] If the emotion engine identifies the user's emotion as "frustrated," the generative AI will adjust its advice as follows:

[1875] "First, take a deep breath and relax. Then, calmly conduct a competitor analysis and understand your target market. Next, evaluate the strengths and weaknesses of your product and create a marketing message based on that. You also need to choose the right advertising channels and promote it effectively."

[1876] In this way, users can view advice on their device screen. This system allows users to receive appropriate advice based on their emotions, and also provides guidelines and instructions for asking effective questions to the generative AI.

[1877] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1878] Step 1: User enters question

[1879] A user inputs a question through the terminal interface. For example, the user inputs, "How should we develop a marketing strategy for a new product?" This input is stored as text data on the terminal.

[1880] Step 2: The device sends the question to the server

[1881] The device sends the user-entered question to the server as an HTTP POST request, for example to the endpoint https: / / example.com / api / questions. This request includes the user's question.

[1882] Step 3: The server receives the question and analyzes it using natural language processing technology

[1883] The server analyzes the received question using natural language processing technology. Specifically, it uses models such as Google's BERT and OpenAI's GPT-3 to understand the intent of the question. This analysis extracts keywords and context from the question. The input is the user's question, and the output is the analysis result.

[1884] Step 4: The server generates advice using a generative AI engine based on the analysis results.

[1885] The server uses a generative AI engine to generate advice based on the analysis results. For example, if a user asks, "How should we develop a marketing strategy for a new product?", the generative AI engine will generate advice such as, "Analyze competitors, understand the target market, and evaluate the product's strengths and weaknesses." The input is the analysis results, and the output is the generated advice.

[1886] Step 5: The server recognizes the user's emotion using the emotion engine.

[1887] The server uses an emotion engine to recognize the user's emotions. For example, it uses Microsoft's Azure Cognitive Services to analyze emotions from the user's voice and facial expressions. This analysis determines whether the user is irritated or not. The input is the user's voice and facial expression data, and the output is the emotion recognition result.

[1888] Step 6: The server adjusts the advice based on the emotion

[1889] The server adjusts the advice generated by the generative AI engine based on information obtained from the emotion engine. For example, if the emotion engine recognizes that the user is irritated, the server will adjust the advice to something like, "First, take a deep breath and relax. Then, calmly analyze the situation." The input is the emotion recognition result and the generated advice, and the output is the adjusted advice.

[1890] Step 7: The server sends the final advice to the device

[1891] The server sends the final advice to the terminal as an HTTP response, for example, in the form {"advice": "First, take a deep breath and relax. Then, calmly analyze the situation."}. The input is the adjusted advice, and the output is the HTTP response.

[1892] Step 8: The device displays the advice to the user

[1893] The device displays the advice received from the server to the user. The user can see advice on the device screen such as "First, take a deep breath and relax. Then, calmly analyze the situation." The input is the HTTP response from the server, and the output is the advice displayed to the user.

[1894] (Application example 1)

[1895] 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."

[1896] Conventional advice systems using generative AI provide uniform advice without considering the user's emotions, resulting in a decline in user satisfaction and reliability. Furthermore, there was a lack of specific applications for improving the shopping experience in physical stores. This resulted in the issue of users being unable to receive appropriate information or advice tailored to their emotions when asking about products.

[1897] 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.

[1898] In this invention, the server includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe creation, and story creation; means for providing this advice to the user; means including an emotion engine for recognizing the user's emotions and adjusting advice based on those emotions; and means for providing product information, emotion recognition, and personalized advice as an application installed on a smartphone in a physical store. This makes it possible to provide appropriate advice based on the user's emotions and improve the shopping experience in a physical store.

[1899] "Means for gathering generative AI advice in response to user questions" refers to an artificial intelligence engine that receives questions from users and generates appropriate advice in response to them.

[1900] "A tool for a wide range of areas, including marketing, research, brainstorming, programming, study plans, recipe creation, and story writing" refers to a function that provides advice to users on questions in a variety of fields.

[1901] "Means for providing these pieces of advice to the user" refers to the interface or communication means for conveying the generated advice to the user.

[1902] "Means including an emotion engine that recognizes a user's emotion and adjusts advice based on that emotion" refers to an engine that analyzes a user's emotion and adjusts the content and tone of advice based on the analysis result.

[1903] "A means of providing product information, recognizing emotions, and offering personalized advice as an application installed on a smartphone in a physical store" refers to an application installed on a smartphone that provides product information, recognizes users' emotions, and offers personalized advice in order to improve the shopping experience in a physical store.

[1904] A system for implementing this invention includes: means for collecting generative AI advice in response to user questions; means for handling a wide range of areas such as marketing, research, brainstorming, programming, study plans, recipe development, and story creation; means for providing this advice to users; means including an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions; and means for providing product information, emotion recognition, and personalized advice as an application installed on a smartphone in a physical store.

[1905] The server receives questions from users and uses a generative AI engine to generate appropriate advice in response. The generative AI engine uses natural language processing technology to analyze the user's question and generate appropriate advice. For example, if a user asks, "How should I coordinate this shirt?", the generative AI engine will generate advice such as, "That shirt looks casual and stylish when paired with jeans. Also, adding accessories will make it even more stylish!"

[1906] The device uses a camera and microphone to recognize the user's emotions through an application installed on the smartphone. Emotion recognition is performed using software. It recognizes emotions from the user's voice and facial expressions and sends the results to a generative AI engine. For example, if the device recognizes that the user is excited, the generative AI engine will use that information to adjust the tone of its advice.

[1907] Users can receive the generated advice through a smartphone application. The application has functions to provide product information, recognize emotions, and provide personalized advice. For example, if a user asks, "How should I coordinate this shirt?" and emotion recognition determines that the user is "excited," the generative AI will provide advice such as, "That shirt looks casual and stylish when paired with jeans. Also, adding some accessories will make it even more stylish!"

[1908] An example prompt is:

[1909] User Question: How should I coordinate this shirt?

[1910] User sentiment: Excited

[1911] Please provide appropriate advice.

[1912] In this way, it is possible to provide appropriate advice based on the user's emotions and improve the shopping experience in physical stores.

[1913] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1914] Step 1:

[1915] The user launches the application on their smartphone and enters a question.

[1916] Input: User question (e.g., "How do I coordinate this shirt?")

[1917] Output: User question data

[1918] Specific behavior: The user enters a question into the application's input field and presses the submit button.

[1919] Step 2:

[1920] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice and recognize emotions.

[1921] Input: User's facial and voice data

[1922] Output: User's emotion data (e.g. "Excited")

[1923] How it works: The device uses emotion recognition software to analyze emotions from captured facial expressions and voice.

[1924] Step 3:

[1925] The terminal transmits the user's question data and emotion data to the server.

[1926] Input: User question data, user emotion data

[1927] Output: Data sent to the server

[1928] Specific operation: The terminal sends the user's question data and emotion data to the server via the Internet.

[1929] Step 4:

[1930] The server uses a generative AI engine to analyze the user's question and generate appropriate advice. 【...

Claims

1. a means for collecting generative AI advice in response to a user's question; means for analyzing the user's question using natural language processing techniques; A means for generating advice in response to the user's question using a generative AI; means for recognizing an emotion of the user using an emotion engine; means for adjusting the advice based on emotions of the user; means for providing tailored advice to said user; A system including:

2. The generative AI advice includes instructions for improving the way the user asks questions. The system of claim 1 .

3. A means for generating a prompt sentence for a generative AI based on the user's question; and a means for inputting the generated prompt sentence to the generation system AI. The system of claim 1 .

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