system

Abstract

We provide the system. [Solution] A means for initializing a database containing information about generative artificial intelligence and storing said information, A natural language processing algorithm means that receives input from a user and analyzes said input, A means for searching for relevant information from the database based on the analyzed input and selecting the most appropriate information, A means for generating and presenting the selected information to the user as a response, A means of obtaining user feedback and updating the learning model, A system that includes this.

Description

【Technical Field】 , 【0005】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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 Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 [[ID=​​​​​​​​​This invention provides an interactive system designed to enable users to effectively learn about generative artificial intelligence. First, it initializes and maintains a database containing comprehensive information about generative artificial intelligence. Next, it receives input from the user and analyzes that input using a natural language processing algorithm. Based on the analysis results, it searches the database for appropriate information and selects the optimal information. This selected information is then presented to the user as a generated response. Furthermore, it improves the system's performance by obtaining feedback from the user and continuously updating the learning model. In this way, this invention supports many people in deepening their understanding of and utilizing generative AI. 【0006】 "Generative artificial intelligence" is an artificial intelligence technology that has algorithms that generate new data from input data. 【0007】 A "database" is a system for managing and retrieving a collection of information that has been collected and stored according to a specific purpose. 【0008】 "Natural language processing algorithms" refer to technologies that use computational methods to interpret and understand human language. 【0009】 "User" refers to a person who operates or uses a system or product. 【0010】 "Feedback" is the act of obtaining responses, evaluations, and opinions from users, and the process of using that feedback to improve products and services. 【0011】 A "learning model" is a concept of a computer program or system that learns from data to perform a specific task. 【0012】 A "response" refers to the information or data that a system provides in response to user input. [Brief explanation of the drawing] 【0013】 [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0014】 Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings. 【0015】 First, the terms used in the following description will be explained. 【0016】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), and the like. 【0017】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0018】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0019】 In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like. 【0020】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 As shown in Figure 1, the 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. 【0024】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0025】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0026】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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. 【0027】 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0028】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30. 【0031】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0032】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0033】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0034】 In an embodiment of the present invention, a method for constructing an interactive learning support system utilizing generative artificial intelligence will be described. This system is designed to help users overcome questions or lack of knowledge about generative AI and is operated through interaction between a server, a terminal, and the user. 【0035】 The server first initializes a comprehensive database of generative AI, which stores fundamental theoretical and technical information related to text, image, audio, and video generation. This forms a knowledge base capable of responding to a wide range of user questions. 【0036】 The terminal provides an interface for user input. This interface primarily allows text input, but can also include voice recognition functionality as needed. The user inputs questions about the generated AI through the terminal, and the system provides information corresponding to those questions. 【0037】 The user input received is analyzed by the server using natural language processing algorithms. This analysis identifies which generative AI technology the input relates to, and then retrieves specific information about that technology from the database. 【0038】 The retrieved information is formatted appropriately by the server and provided to the user in an easy-to-understand manner. For example, if the question concerns text generation, the server might present the user with an overview of the relevant technology, practical application examples, and basic operating procedures. 【0039】 Furthermore, the server receives and analyzes user feedback to improve the system itself. Specifically, if a user provides unclear points regarding a response, that information is used to improve the database and natural language processing algorithms. This allows for the provision of more appropriate information in subsequent interactions. 【0040】 For example, if a user inputs "I want to know about examples of speech generation technology use," the server provides information on the fundamental technologies related to speech generation, well-known examples, and available software tools, and further sends the user a document explaining the basic usage of those tools. In this way, the system of the present invention provides practical support for deepening understanding of generation AI. 【0041】 The following describes the processing flow. 【0042】 Step 1: 【0043】 The server initializes and loads a database containing information about the generative AI. This includes fundamental information and related technologies for generating text, images, audio, and video. 【0044】 Step 2: 【0045】 The terminal provides an interface for users to input questions and inquiries. Users can use this interface to input any questions related to the generated AI. 【0046】 Step 3: 【0047】 Users can input or voice-inform their device about specific questions or topics for which they want information regarding the generative AI. 【0048】 Step 4: 【0049】 The terminal sends user input to the server. The input is passed to the server as text data. 【0050】 Step 5: 【0051】 The server analyzes the received input using a natural language processing algorithm. Here, keywords are extracted to identify which generative AI field the question relates to. 【0052】 Step 6: 【0053】 The server searches the database for appropriate information based on the analysis results and selects the most suitable information to meet the user's needs. 【0054】 Step 7: 【0055】 The server reconstructs the selected information into a user-friendly and useful format to create a response. 【0056】 Step 8: 【0057】 The terminal displays the generated response to the user. In some cases, it may also present visual materials such as images and diagrams. 【0058】 Step 9: 【0059】 Users learn based on the information presented, and if they have further questions, they send additional questions or feedback to the server via their device. 【0060】 Step 10: 【0061】 The server receives user feedback, analyzes it, and uses it to improve the entire system. It updates its learning model to provide better responses in subsequent interactions. 【0062】 (Example 1) 【0063】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0064】 In recent years, while generative artificial intelligence technology has advanced, a challenge remains: users often lack sufficient knowledge about this technology. There is a need to provide systems that enable users to resolve their questions about generative AI technology and obtain necessary information quickly and effectively. 【0065】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0066】 In this invention, the server includes means for initializing and storing a knowledge set relating to generative artificial intelligence, natural language processing means for receiving and analyzing inquiries from users, and means for searching for relevant knowledge from the knowledge set and selecting the most appropriate knowledge based on the analyzed inquiries. This enables users to effectively obtain the information necessary to answer questions about generative AI. 【0067】 "Generative artificial intelligence" refers to all technologies that automatically generate text, images, audio, videos, and other content based on user input. 【0068】 A "knowledge set" refers to a database that systematically collects, classifies, and maintains theoretical and technical information related to generative artificial intelligence in an accessible format. 【0069】 "Natural language processing means" refers to algorithms and technologies for analyzing text input from users and understanding its meaning. 【0070】 An "inquiry" refers to a question or keyword that a user enters into the system to request information about generative artificial intelligence. 【0071】 "Opinions" refer to the feedback and evaluations that users provide to the system's response. 【0072】 "Visual information" refers to information such as diagrams and images that are added to text information to aid in visual understanding. 【0073】 "Dialogue history" refers to the log of all inquiries and responses that took place between the user and the system. 【0074】 This invention describes a specific method for implementing an interactive learning support system based on generative artificial intelligence. The system operates primarily through interaction between a server, a terminal, and a user. 【0075】 Server Role 【0076】 The server is a central information processing unit for initializing and maintaining a knowledge set related to generative artificial intelligence. The server is equipped with large-capacity storage and a high-performance processor, and the knowledge set contains various data related to text generation, image generation, speech generation, and video generation. The server analyzes user inquiries using natural language processing tools, searches for relevant knowledge, and selects the most appropriate one. NLP algorithms and machine learning models operate during this process. 【0077】 Terminal role 【0078】 The terminal is an input / output device used by the user, providing an interface for the user to access the system. The terminal is equipped with a keyboard or touchscreen for text input, and in some cases, a microphone for voice input. The user makes inquiries about the generated AI through the terminal and receives the results. The terminal visually presents the received results to the user to aid in understanding. 【0079】 User roles 【0080】 Users can use the system to obtain information about generated AI and deepen their understanding of it. Users can ask specific questions about technologies that interest them and learn based on the information they receive. 【0081】 Specific example 【0082】 For example, if a user enters the prompt "I want to know about examples of speech generation technology use," the server parses this query and searches its knowledge set for relevant information about speech generation technology. As a result, the server appropriately organizes information such as an overview of speech generation technology, famous examples, and available tools, and presents it to the user through the terminal. The user can then deepen their understanding of speech generation technology based on this information. 【0083】 In this way, the system of the present invention effectively provides learning support for generative AI and contributes to improving the user's knowledge. 【0084】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0085】 Step 1: 【0086】 The terminal provides an interface for the user to access the system. The user inputs questions about the generated AI in text or voice. The input questions are saved as digital data and prepared to be sent to the server. 【0087】 Step 2: 【0088】 The server receives user data sent from the terminal. Using a specified natural language processing algorithm, the server analyzes the user's question. This process analyzes the input text, extracts relevant keywords and concepts, and identifies which generative AI technologies are associated with it. 【0089】 Step 3: 【0090】 The server matches keywords and concepts obtained from the analysis against a knowledge database. Through a database search algorithm, the server retrieves information related to the user's question and selects the most relevant knowledge. 【0091】 Step 4: 【0092】 The server constructs a user-friendly response based on selected knowledge. During this process, the server organizes search results and can add visual aids and supplementary explanations. This ensures that the user receives specific and clear information. 【0093】 Step 5: 【0094】 The terminal receives responses sent from the server and displays them to the user. Responses are displayed as text, but can also be output as speech using speech synthesis technology if necessary. The user can then learn about the generating AI based on this information. 【0095】 Step 6: 【0096】 Users send feedback about the information they receive to the server via their device. This feedback includes their satisfaction with the question and suggestions for improvement. This input is collected by the server and used to improve natural language processing algorithms and update the knowledge set. 【0097】 (Application Example 1) 【0098】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0099】 In providing information on generative artificial intelligence, there is a need to quickly and efficiently deliver optimal information and educational content tailored to the varying levels of understanding and learning needs of users. Current systems make it difficult to access specialized information on generative AI, and lack mechanisms to effectively utilize individual learning progress and feedback, making it challenging to maximize learning efficiency. 【0100】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0101】 In this invention, the server includes means for initializing a database containing information on generative artificial intelligence and storing said information, means for receiving input from a user and analyzing said input with a natural language processing algorithm, and means for delivering educational content linked to the generated information and supporting the user's understanding. This enables users to efficiently learn about generative AI and deepen their understanding using content optimized for their individual learning needs. 【0102】 A "database containing information on generative artificial intelligence" is a collection of data that organizes and stores information covering theories, technologies, and applications related to generative artificial intelligence technology. 【0103】 "User input" refers to data expressed in text or voice as questions or requests for information related to generative artificial intelligence. 【0104】 A "natural language processing algorithm" is a computational method that analyzes user input, understands its meaning, and extracts relevant information. 【0105】 "Educational content linked to generated information" refers to learning materials and interactive content designed based on analyzed generative artificial intelligence information, with the aim of deepening understanding of that information. 【0106】 "Means to support user understanding" refer to methods and processes for presenting information related to generative artificial intelligence in an easy-to-understand manner and enhancing its educational effectiveness. 【0107】 The system for implementing this invention is configured as follows: The server initializes a database containing information on generative artificial intelligence and stores diverse information on generative artificial intelligence technology. This database covers everything from the theory to the practical applications of generative AI and serves as a foundation for enabling diverse responses to user questions. 【0108】 Users connected via a device send questions about the generated AI to the server through text or voice input. The device provides a simple and intuitive interface, making it easy for users to input information. Specific hardware such as smartphones and tablets are envisioned. 【0109】 The server analyzes the received input using natural language processing algorithms and searches for relevant data in the database. During the analysis process, a natural language processing framework is used to extract keywords and context from the input data. This allows the server to accurately understand the intent of the user's question and select the most relevant information. 【0110】 The selected information, along with the generated educational content, is sent to the device and presented to the user. This allows users not only to learn the fundamental theory of generative AI but also to deepen their practical understanding through interactive learning materials. For example, a user who wants to learn about the text generation process using generative AI will be provided with visual materials on the theoretical background and tutorials on how to use the actual tools. 【0111】 Furthermore, user feedback is sent to the server and used to improve the learning model. This enables more accurate information to be provided in subsequent interactions. For example, if a user enters a prompt such as "I want to learn about the basic theory and applications of image generation AI," relevant materials and demonstration content will be provided based on that request, allowing the user to experience AI image generation technology firsthand. 【0112】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0113】 Step 1: 【0114】 The terminal receives prompts from the user regarding image generation AI as input. The user uses the text input field displayed on the terminal's interface to enter questions such as, "I want to learn about the basic theory and applications of image generation AI." This becomes the initial input data for the system. 【0115】 Step 2: 【0116】 The terminal sends prompts entered by the user to the server. The server receives these prompts as input and applies a natural language processing algorithm. The algorithm analyzes the input data, extracts relevant keywords and phrases, and performs data processing to form database queries. 【0117】 Step 3: 【0118】 The server searches the database based on the analyzed keywords. Since the database contains information on theories and applications related to generative AI, the server selects the most relevant information from the search results. This data processing generates appropriate response data for the user's question. 【0119】 Step 4: 【0120】 The server composes interactive educational content along with search results and outputs it to the terminal. For example, it might combine text explaining the theory behind image generation AI with visual demonstration content based on that theory. This data processing results in content that provides the user with an optimal learning experience. 【0121】 Step 5: 【0122】 The device presents the received information and content to the user. The user reviews explanatory text and visual materials on the screen and gains knowledge about the generating AI. This output information also includes interactive elements, allowing the user to directly manipulate the content and learn from it. 【0123】 Step 6: 【0124】 After users view content, they enter feedback, and this data is acquired by their device. The device then sends this feedback to the server. The server analyzes the received feedback and uses it to update learning models and databases. This data processing can further improve the overall system response and content accuracy in the future. 【0125】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0126】 In an embodiment of the present invention, a method for constructing an interactive learning system is described, which combines generative artificial intelligence technology with user emotion recognition. This system involves a server, a terminal, and a user, and uses an emotion engine to make interactions with the user more effective and personalized. 【0127】 The server initializes a database containing comprehensive information about generative artificial intelligence. This allows it to quickly and appropriately provide information when a user asks a question about generative AI. In addition, the server's built-in natural language processing algorithms analyze the user's input data, enabling it to properly understand the user's questions. 【0128】 Furthermore, in this embodiment, an emotion engine is integrated into the server. The emotion engine recognizes emotions from the user's input text and voice. For example, it can analyze the user's emotional state from the content of the text, the words used, and the tone of voice. 【0129】 The terminal provides an interface for receiving user input. Here, a new emotion indicator is displayed, allowing the user to select or adjust their own emotions. The user inputs questions about the generating AI along with their emotion information. 【0130】 When the server receives emotion information along with user input data, it generates a response in a manner appropriate to that emotion. For example, if the user indicates an emotion of confusion, the server will attempt to resolve the issue by providing a more detailed and understandable explanation or by offering specific examples. 【0131】 For example, if a user expresses anxiety along with a question such as "I don't understand the basics of speech generation technology," the server will generate a response that uses reassuring language and relatable examples, along with basic knowledge of speech generation technology. 【0132】 Emotional data accumulated through user interactions is analyzed by the server and used to improve the accuracy of responses in subsequent interactions. This makes it easier for users to advance the generative AI's learning through the system, enabling the provision of support optimized for each individual user. 【0133】 The following describes the processing flow. 【0134】 Step 1: 【0135】 The server initializes a database containing information about generative artificial intelligence and makes it available to users in response to their inquiries. 【0136】 Step 2: 【0137】 The device provides an interface that allows users to input questions about the generated AI. This interface includes text input boxes and, in some cases, voice input options. 【0138】 Step 3: 【0139】 Users enter questions and inquiries about the generative AI into their device using an easy-to-read input method. Input can be in the form of text or voice. 【0140】 Step 4: 【0141】 The terminal sends user input to the server. At the same time, it also sends the emotional information selected via the emotional indicator. 【0142】 Step 5: 【0143】 The server analyzes the user's input using a natural language processing algorithm to identify which generative AI technology the question relates to. 【0144】 Step 6: 【0145】 The server uses an emotion engine to recognize emotions from user input. Based on this recognized emotion information, it analyzes the user's state. 【0146】 Step 7: 【0147】 Based on the analyzed input and emotional information, the server searches the database for relevant information and selects information appropriate to the user's emotional state. For example, if the emotion is confusion, it will include detailed guidance and encouragement. 【0148】 Step 8: 【0149】 The server combines the selected information and generates a response that takes the user's emotions into consideration. 【0150】 Step 9: 【0151】 The terminal receives a response from the server and presents it to the user. In some cases, presenting visual materials or examples can be effective. 【0152】 Step 10: 【0153】 Users review the information presented and, if they have further questions or new feedback, send it to the server via their device. 【0154】 Step 11: 【0155】 The server analyzes dialogue logs and sentiment data based on user feedback and new inputs, and uses this information to improve the system. This allows for the provision of optimized responses to the user in future interactions. 【0156】 (Example 2) 【0157】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0158】 In dialogue systems using generative artificial intelligence, there is a problem in providing appropriate and effective information while considering the individual emotional state of the user. Furthermore, conventional systems have the problem of uniform responses to users and being unable to respond flexibly to individual emotional changes and states, which can lead to decreased user satisfaction. 【0159】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0160】 In this invention, the server includes means for initializing and storing an information source containing information about generative artificial intelligence; natural language processing means for receiving and analyzing data from a user; and emotion recognition means for detecting the user's emotions and adjusting the response accordingly. This enables the provision of personalized information tailored to each user's emotional state. 【0161】 "Information source" refers to a database or repository that stores information about generative artificial intelligence and makes it accessible as needed. 【0162】 "Natural language processing means" refers to language understanding technology that analyzes input data from users and generates appropriate responses. 【0163】 "Emotion recognition means" refers to technology that identifies an emotional state from the user's input data and generates a response corresponding to that state. 【0164】 "Generative artificial intelligence" refers to artificial intelligence technology that learns from large amounts of data and automatically generates new information and responses. 【0165】 "Response" refers to information or answers provided by generative artificial intelligence based on user input. 【0166】 "User" refers to an individual or end-user who acquires and learns information through interaction with the system. 【0167】 "Feedback" refers to evaluation information and opinions obtained from users, and the system is improved and adjusted based on this feedback. 【0168】 This invention relates to a system that provides an interactive interface that responds to the user's emotions using generative artificial intelligence technology. The system is constructed in a manner that involves three parties: a server, a terminal, and a user. 【0169】 The server initializes information sources containing information about generative artificial intelligence and stores them as a database. The server is equipped with natural language processing algorithms that analyze input data received from the user. This analysis provides a foundation for accurately understanding the user's questions and generating responses. 【0170】 Furthermore, the server incorporates an emotion recognition engine. This engine detects emotions from the user's input text and voice, and adjusts the response to be appropriate to the user's emotions. This emotion recognition uses elements such as the content and tone of the text and the voice signal. 【0171】 The terminal functions as the user interface. Through the terminal, users can enter questions into text input boxes or make inquiries by voice. The terminal may also display indicators that allow users to select or adjust their emotions. 【0172】 As a concrete example, if a user enters the prompt "I want to learn the basics of generative AI," the server will retrieve relevant basic information from its sources and generate a response in an easy-to-understand format. At the same time, if the user expresses anxiety, the server will generate a response using reassuring language. 【0173】 This system allows users to efficiently acquire knowledge from the generated AI in a way that aligns with their own emotions. User feedback and emotional data collected by the server are further used to improve the system's performance, enabling better personalization in subsequent interactions. 【0174】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0175】 Step 1: 【0176】 Users input questions about the generated AI by operating a terminal. This is typically done using a text input box, but voice input is also possible. Users can also select or adjust their own emotional state using the provided emotion indicators. The input data, along with the question content and emotion information, is sent to the server. 【0177】 Step 2: 【0178】 The server takes in text data and sentiment information received from the user and analyzes it using natural language processing algorithms. Morphological and syntactic analysis is performed on the input data to convert the user's questions into specific operational commands. Simultaneously, the sentiment recognition engine analyzes the input sentiment information to identify the user's emotional state. The analysis results form the basis for generating the next response. 【0179】 Step 3: 【0180】 The server searches for relevant knowledge from information sources based on the analyzed question. It uses database queries to identify the target information and select the most appropriate content. This process also considers the user's emotional state, ensuring that information with an appropriate tone and level of detail is chosen. The selected knowledge then becomes the basis for generating the response. 【0181】 Step 4: 【0182】 The server uses knowledge selected through a generative AI model to generate the optimal response for the user. This response is not only accurate but also tailored to the user's emotional state. For users expressing anxiety, the system is designed to provide reassurance through familiar language and examples. The response text is sent to the device as soon as it is generated. 【0183】 Step 5: 【0184】 The terminal presents the response sent from the server to the user. Information is displayed in a way that is easily understandable to the user through visual representations and audio responses. In this step, the response speed and interface design are carefully considered to enhance the user experience. 【0185】 Step 6: 【0186】 Users can provide further questions or feedback in response to the answers they receive. This user feedback is collected by the server and used to update the learning device and improve system performance. This allows the system to continuously improve itself, preparing to deliver a more refined and personalized experience in subsequent interactions. 【0187】 (Application Example 2) 【0188】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0189】 In caregiving settings, it is difficult to appropriately understand the emotions of service users and provide individualized support and communication. In particular, traditional systems are insufficient to handle situations requiring responses based on emotional changes or different support for each user. This raises concerns about decreased user satisfaction and increased stress. 【0190】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0191】 In this invention, the server includes means for initializing a database containing information related to generative artificial intelligence and storing said information, means for receiving input from a user and analyzing said input using a natural language processing algorithm, and means for analyzing the user's emotions and generating a response corresponding to those emotions. This enables the server to understand the user's emotions and provide personalized responses based on those emotions. 【0192】 "Generative artificial intelligence" is an artificial intelligence technology that has the ability to generate new data based on input data. 【0193】 A "database" is an information system that systematically stores information and makes it easily accessible when needed. 【0194】 A "natural language processing algorithm" is a set of processing techniques for handling human language using computers. 【0195】 "Emotion analysis" is a technology that identifies emotions and emotional states from user input data. 【0196】 A "response" is the information that the system generates and presents in response to input from the user. 【0197】 "Feedback" refers to reaction information such as evaluations and opinions provided by users. 【0198】 A "learning model" is a computer model that is built to learn specific patterns and rules based on data, enabling it to perform autonomous reasoning and decision-making. 【0199】 This invention is a system that combines generative artificial intelligence technology and emotion recognition technology to identify the emotions of users in care settings and realize personalized communication and support. Specific embodiments are shown below. 【0200】 The server builds a database containing information about generative artificial intelligence. This database serves as a source of information for responding quickly and accurately to user inquiries. The server also uses natural language processing algorithms to analyze and understand user input. 【0201】 Furthermore, the server incorporates an emotion engine that analyzes the user's emotions. This engine recognizes the user's emotional state—for example, emotions such as joy, anxiety, and anger—from the input text and voice data. For this purpose, natural language processing libraries such as Google's TENSORFLOW and IBM's Watson are used. 【0202】 The terminal provides an interface for receiving user input and displays indicators related to emotions. This terminal comprises a wide range of user devices, including personal digital assistants (PDAs) such as smartphones. 【0203】 Users input questions along with emotional information. The server receives this emotional information and generates a response accordingly. The generated response uses emotionally sensitive and friendly language, utilizing technologies such as OpenAI's GPT-4®. 【0204】 For example, if a user enters information indicating anxiety, such as "I'm not feeling well today," the system can respond with a kind message like, "Please let me know if there's anything I can do to help." 【0205】 An example of a prompt message generated using a generative AI model is one that asks, "What actions can be taken to reassure a user who is showing signs of anxiety?" This allows for appropriate responses that are sensitive to the user's feelings. 【0206】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0207】 Step 1: 【0208】 The device receives voice or text input from the user. The user also inputs an indicator showing their emotional state. The input data includes the user's questions and emotional indicator. 【0209】 Step 2: 【0210】 The server receives input data sent from the terminal and analyzes the question using natural language processing algorithms. Specifically, it uses Google's TensorFlow to tokenize the text and extract context. This process clarifies what the user is asking. 【0211】 Step 3: 【0212】 The server uses an emotion analysis engine to determine the user's emotional state. It analyzes the input text and voice tone to identify emotions such as "anxiety" or "joy." Based on the analysis results, it adjusts the response style. 【0213】 Step 4: 【0214】 The server searches the database for an appropriate answer based on the analyzed question content and emotional state. Depending on the situation, it uses a generative artificial intelligence model (e.g., OpenAI's GPT-4) to generate a response that is most understandable and empathetic to the user. 【0215】 Step 5: 【0216】 The generated response is presented to the user via the terminal. The server adds expressions and examples to the response content that take into account the user's emotional state. For example, reassuring words are used for a user who is showing anxiety. 【0217】 Step 6: 【0218】 Users provide feedback on the responses they receive. The server receives this feedback and updates its learning model. This allows the system to continuously learn to provide more accurate and personalized responses. 【0219】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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. 【0220】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0221】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0222】 [Second Embodiment] 【0223】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0224】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0225】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0226】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0227】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0228】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0229】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0230】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0231】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0232】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0233】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0234】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0235】 In an embodiment of the present invention, a method for constructing an interactive learning support system utilizing generative artificial intelligence will be described. This system is designed to help users overcome questions or lack of knowledge about generative AI and is operated through interaction between a server, a terminal, and the user. 【0236】 The server first initializes a comprehensive database of generative AI, which stores fundamental theoretical and technical information related to text, image, audio, and video generation. This forms a knowledge base capable of responding to a wide range of user questions. 【0237】 The terminal provides an interface for user input. This interface primarily allows text input, but can also include voice recognition functionality as needed. The user inputs questions about the generated AI through the terminal, and the system provides information corresponding to those questions. 【0238】 The user input received is analyzed by the server using natural language processing algorithms. This analysis identifies which generative AI technology the input relates to, and then retrieves specific information about that technology from the database. 【0239】 The retrieved information is formatted appropriately by the server and provided to the user in an easy-to-understand manner. For example, if the question concerns text generation, the server might present the user with an overview of the relevant technology, practical application examples, and basic operating procedures. 【0240】 Furthermore, the server receives and analyzes user feedback to improve the system itself. Specifically, if a user provides unclear points regarding a response, that information is used to improve the database and natural language processing algorithms. This allows for the provision of more appropriate information in subsequent interactions. 【0241】 For example, if a user inputs "I want to know about examples of speech generation technology use," the server provides information on the fundamental technologies related to speech generation, well-known examples, and available software tools, and further sends the user a document explaining the basic usage of those tools. In this way, the system of the present invention provides practical support for deepening understanding of generation AI. 【0242】 The following describes the processing flow. 【0243】 Step 1: 【0244】 The server initializes and loads a database containing information about the generative AI. This includes fundamental information and related technologies for generating text, images, audio, and video. 【0245】 Step 2: 【0246】 The terminal provides an interface for users to input questions and inquiries. Users can use this interface to input any questions related to the generated AI. 【0247】 Step 3: 【0248】 Users can input or voice-inform their device about specific questions or topics for which they want information regarding the generative AI. 【0249】 Step 4: 【0250】 The terminal sends user input to the server. The input is passed to the server as text data. 【0251】 Step 5: 【0252】 The server analyzes the received input using a natural language processing algorithm. Here, keywords are extracted to identify which generative AI field the question relates to. 【0253】 Step 6: 【0254】 The server searches the database for appropriate information based on the analysis results and selects the most suitable information to meet the user's needs. 【0255】 Step 7: 【0256】 The server reconstructs the selected information into a user-friendly and useful format to create a response. 【0257】 Step 8: 【0258】 The terminal displays the generated response to the user. In some cases, it may also present visual materials such as images and diagrams. 【0259】 Step 9: 【0260】 Users learn based on the information presented, and if they have further questions, they send additional questions or feedback to the server via their device. 【0261】 Step 10: 【0262】 The server receives user feedback, analyzes it, and uses it to improve the entire system. It updates its learning model to provide better responses in subsequent interactions. 【0263】 (Example 1) 【0264】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0265】 In recent years, while generative artificial intelligence technology has advanced, a challenge remains: users often lack sufficient knowledge about this technology. There is a need to provide systems that enable users to resolve their questions about generative AI technology and obtain necessary information quickly and effectively. 【0266】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0267】 In this invention, the server includes means for initializing and storing a knowledge set relating to generative artificial intelligence, natural language processing means for receiving and analyzing inquiries from users, and means for searching for relevant knowledge from the knowledge set and selecting the most appropriate knowledge based on the analyzed inquiries. This enables users to effectively obtain the information necessary to answer questions about generative AI. 【0268】 "Generative artificial intelligence" refers to all technologies that automatically generate text, images, audio, videos, and other content based on user input. 【0269】 A "knowledge set" refers to a database that systematically collects, classifies, and maintains theoretical and technical information related to generative artificial intelligence in an accessible format. 【0270】 "Natural language processing means" refers to algorithms and technologies for analyzing text input from users and understanding its meaning. 【0271】 An "inquiry" refers to a question or keyword that a user enters into the system to request information about generative artificial intelligence. 【0272】 "Opinions" refer to the feedback and evaluations that users provide to the system's response. 【0273】 "Visual information" refers to information such as diagrams and images that are added to text information to aid in visual understanding. 【0274】 "Dialogue history" refers to the log of all inquiries and responses that took place between the user and the system. 【0275】 This invention describes a specific method for implementing an interactive learning support system based on generative artificial intelligence. The system operates primarily through interaction between a server, a terminal, and a user. 【0276】 Server Role 【0277】 The server is a central information processing unit for initializing and maintaining a knowledge set related to generative artificial intelligence. The server is equipped with large-capacity storage and a high-performance processor, and the knowledge set contains various data related to text generation, image generation, speech generation, and video generation. The server analyzes user inquiries using natural language processing tools, searches for relevant knowledge, and selects the most appropriate one. NLP algorithms and machine learning models operate during this process. 【0278】 Terminal role 【0279】 The terminal is an input / output device used by the user, providing an interface for the user to access the system. The terminal is equipped with a keyboard or touchscreen for text input, and in some cases, a microphone for voice input. The user makes inquiries about the generated AI through the terminal and receives the results. The terminal visually presents the received results to the user to aid in understanding. 【0280】 User roles 【0281】 Users can use the system to obtain information about generated AI and deepen their understanding of it. Users can ask specific questions about technologies that interest them and learn based on the information they receive. 【0282】 Specific example 【0283】 For example, if a user enters the prompt "I want to know about examples of speech generation technology use," the server parses this query and searches its knowledge set for relevant information about speech generation technology. As a result, the server appropriately organizes information such as an overview of speech generation technology, famous examples, and available tools, and presents it to the user through the terminal. The user can then deepen their understanding of speech generation technology based on this information. 【0284】 In this way, the system of the present invention effectively provides learning support for generative AI and contributes to the improvement of the user's knowledge. 【0285】 The flow of the specific process in Example 1 will be described with reference to FIG. 11. 【0286】 Step 1: 【0287】 The terminal provides an interface for the user to access the system. The user inputs a question regarding generative AI in text or voice. The input question is secured as digital data and is ready to be transmitted to the server. 【0288】 Step 2: 【0289】 The server receives the user's data transmitted from the terminal. Using the specified natural language processing algorithm, the server analyzes the user's question. In this process, the input text is analyzed, relevant keywords and concepts are extracted, and it is determined which generative AI technology the question is related to. 【0290】 Step 3: 【0291】 The server matches the keywords and concepts obtained from the analysis with the knowledge set database. Through the database search algorithm, the server searches for information related to the user's question and selects the most relevant knowledge. 【0292】 Step 4: 【0293】 Based on the selected knowledge, the server constructs a response that is easy for the user to understand. In this process, the server can organize the search results and add materials for visual presentation and supplementary explanations. As a result, specific and clear information is output for the user. 【0294】 Step 5: 【0295】 The terminal receives responses sent from the server and displays them to the user. Responses are displayed as text, but can also be output as speech using speech synthesis technology if necessary. The user can then learn about the generating AI based on this information. 【0296】 Step 6: 【0297】 Users send feedback about the information they receive to the server via their device. This feedback includes their satisfaction with the question and suggestions for improvement. This input is collected by the server and used to improve natural language processing algorithms and update the knowledge set. 【0298】 (Application Example 1) 【0299】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0300】 In providing information on generative artificial intelligence, there is a need to quickly and efficiently deliver optimal information and educational content tailored to the varying levels of understanding and learning needs of users. Current systems make it difficult to access specialized information on generative AI, and lack mechanisms to effectively utilize individual learning progress and feedback, making it challenging to maximize learning efficiency. 【0301】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0302】 In this invention, the server includes means for initializing a database containing information on generative artificial intelligence and storing the information, natural language processing algorithm means for receiving an input from a user and analyzing the input, and means for delivering educational content linked to the generated information to assist the user's understanding. As a result, the user can efficiently learn knowledge about generative AI and deepen their understanding using content optimized for individual learning needs. 【0303】 The "database containing information on generative artificial intelligence" is a data set that organizes and stores information covering theories, technologies, and applications related to generative artificial intelligence technology. 【0304】 The "input from the user" is data that expresses questions or information requests regarding generative artificial intelligence in text or voice. 【0305】 The "natural language processing algorithm" is a computational method for analyzing an input from a user, understanding its meaning, and extracting relevant information. 【0306】 The "educational content linked to the generated information" is learning materials or interactive content designed based on the analyzed generative artificial intelligence information, aiming to deepen the understanding of that information. 【0307】 The "means for assisting the user's understanding" is a method or process for presenting information related to generative artificial intelligence in an easy-to-understand manner and enhancing the educational effect. 【0308】 The system for implementing this invention is configured as follows. The server initializes a database containing information on generative artificial intelligence and accumulates various information related to generative artificial intelligence technology. This database covers everything from the theory to the practical application of generative AI and serves as a basis for enabling various responses to user questions. 【0309】 <所 Users connected via a device send questions about the generated AI to the server through text or voice input. The device provides a simple and intuitive interface, making it easy for users to input information. Specific hardware such as smartphones and tablets are envisioned. 【0310】 The server analyzes the received input using natural language processing algorithms and searches for relevant data in the database. During the analysis process, a natural language processing framework is used to extract keywords and context from the input data. This allows the server to accurately understand the intent of the user's question and select the most relevant information. 【0311】 The selected information, along with the generated educational content, is sent to the device and presented to the user. This allows users not only to learn the fundamental theory of generative AI but also to deepen their practical understanding through interactive learning materials. For example, a user who wants to learn about the text generation process using generative AI will be provided with visual materials on the theoretical background and tutorials on how to use the actual tools. 【0312】 Furthermore, user feedback is sent to the server and used to improve the learning model. This enables more accurate information to be provided in subsequent interactions. For example, if a user enters a prompt such as "I want to learn about the basic theory and applications of image generation AI," relevant materials and demonstration content will be provided based on that request, allowing the user to experience AI image generation technology firsthand. 【0313】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0314】 Step 1: 【0315】 The terminal receives prompts from the user regarding image generation AI as input. The user uses the text input field displayed on the terminal's interface to enter questions such as, "I want to learn about the basic theory and applications of image generation AI." This becomes the initial input data for the system. 【0316】 Step 2: 【0317】 The terminal sends prompts entered by the user to the server. The server receives these prompts as input and applies a natural language processing algorithm. The algorithm analyzes the input data, extracts relevant keywords and phrases, and performs data processing to form database queries. 【0318】 Step 3: 【0319】 The server searches the database based on the analyzed keywords. Since the database contains information on theories and applications related to generative AI, the server selects the most relevant information from the search results. This data processing generates appropriate response data for the user's question. 【0320】 Step 4: 【0321】 The server composes interactive educational content along with search results and outputs it to the terminal. For example, it might combine text explaining the theory behind image generation AI with visual demonstration content based on that theory. This data processing results in content that provides the user with an optimal learning experience. 【0322】 Step 5: 【0323】 The device presents the received information and content to the user. The user reviews explanatory text and visual materials on the screen and gains knowledge about the generating AI. This output information also includes interactive elements, allowing the user to directly manipulate the content and learn from it. 【0324】 Step 6: 【0325】 After users view content, they enter feedback, and this data is acquired by their device. The device then sends this feedback to the server. The server analyzes the received feedback and uses it to update learning models and databases. This data processing can further improve the overall system response and content accuracy in the future. 【0326】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0327】 In an embodiment of the present invention, a method for constructing an interactive learning system is described, which combines generative artificial intelligence technology with user emotion recognition. This system involves a server, a terminal, and a user, and uses an emotion engine to make interactions with the user more effective and personalized. 【0328】 The server initializes a database containing comprehensive information about generative artificial intelligence. This allows it to quickly and appropriately provide information when a user asks a question about generative AI. In addition, the server's built-in natural language processing algorithms analyze the user's input data, enabling it to properly understand the user's questions. 【0329】 Furthermore, in this embodiment, an emotion engine is integrated into the server. The emotion engine recognizes emotions from the user's input text and voice. For example, it can analyze the user's emotional state from the content of the text, the words used, and the tone of voice. 【0330】 The terminal provides an interface for receiving user input. Here, a new emotion indicator is displayed, allowing the user to select or adjust their own emotions. The user inputs questions about the generating AI along with their emotion information. 【0331】 When the server receives emotion information along with user input data, it generates a response in a manner appropriate to that emotion. For example, if the user indicates an emotion of confusion, the server will attempt to resolve the issue by providing a more detailed and understandable explanation or by offering specific examples. 【0332】 For example, if a user expresses anxiety along with a question such as "I don't understand the basics of speech generation technology," the server will generate a response that uses reassuring language and relatable examples, along with basic knowledge of speech generation technology. 【0333】 Emotional data accumulated through user interactions is analyzed by the server and used to improve the accuracy of responses in subsequent interactions. This makes it easier for users to advance the generative AI's learning through the system, enabling the provision of support optimized for each individual user. 【0334】 The following describes the processing flow. 【0335】 Step 1: 【0336】 The server initializes a database containing information about generative artificial intelligence and makes it available to users in response to their inquiries. 【0337】 Step 2: 【0338】 The device provides an interface that allows users to input questions about the generated AI. This interface includes text input boxes and, in some cases, voice input options. 【0339】 Step 3: 【0340】 Users enter questions and inquiries about the generative AI into their device using an easy-to-read input method. Input can be in the form of text or voice. 【0341】 Step 4: 【0342】 The terminal sends user input to the server. At the same time, it also sends the emotional information selected via the emotional indicator. 【0343】 Step 5: 【0344】 The server analyzes the user's input using a natural language processing algorithm to identify which generative AI technology the question relates to. 【0345】 Step 6: 【0346】 The server uses an emotion engine to recognize emotions from user input. Based on this recognized emotion information, it analyzes the user's state. 【0347】 Step 7: 【0348】 Based on the analyzed input and emotional information, the server searches the database for relevant information and selects information appropriate to the user's emotional state. For example, if the emotion is confusion, it will include detailed guidance and encouragement. 【0349】 Step 8: 【0350】 The server combines the selected information and generates a response that takes the user's emotions into consideration. 【0351】 Step 9: 【0352】 The terminal receives a response from the server and presents it to the user. In some cases, presenting visual materials or examples can be effective. 【0353】 Step 10: 【0354】 Users review the information presented and, if they have further questions or new feedback, send it to the server via their device. 【0355】 Step 11: 【0356】 The server analyzes dialogue logs and sentiment data based on user feedback and new inputs, and uses this information to improve the system. This allows for the provision of optimized responses to the user in future interactions. 【0357】 (Example 2) 【0358】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0359】 In dialogue systems using generative artificial intelligence, there is a problem in providing appropriate and effective information while considering the individual emotional state of the user. Furthermore, conventional systems have the problem of uniform responses to users and being unable to respond flexibly to individual emotional changes and states, which can lead to decreased user satisfaction. 【0360】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0361】 In this invention, the server includes means for initializing and storing an information source containing information about generative artificial intelligence; natural language processing means for receiving and analyzing data from a user; and emotion recognition means for detecting the user's emotions and adjusting the response accordingly. This enables the provision of personalized information tailored to each user's emotional state. 【0362】 "Information source" refers to a database or repository that stores information about generative artificial intelligence and makes it accessible as needed. 【0363】 "Natural language processing means" refers to language understanding technology that analyzes input data from users and generates appropriate responses. 【0364】 "Emotion recognition means" refers to technology that identifies an emotional state from the user's input data and generates a response corresponding to that state. 【0365】 "Generative artificial intelligence" refers to artificial intelligence technology that learns from large amounts of data and automatically generates new information and responses. 【0366】 "Response" refers to information or answers provided by generative artificial intelligence based on user input. 【0367】 "User" refers to an individual or end-user who acquires and learns information through interaction with the system. 【0368】 "Feedback" refers to evaluation information and opinions obtained from users, and the system is improved and adjusted based on this feedback. 【0369】 This invention relates to a system that provides an interactive interface that responds to the user's emotions using generative artificial intelligence technology. The system is constructed in a manner that involves three parties: a server, a terminal, and a user. 【0370】 The server initializes information sources containing information about generative artificial intelligence and stores them as a database. The server is equipped with natural language processing algorithms that analyze input data received from the user. This analysis provides a foundation for accurately understanding the user's questions and generating responses. 【0371】 Furthermore, the server incorporates an emotion recognition engine. This engine detects emotions from the user's input text and voice, and adjusts the response to be appropriate to the user's emotions. This emotion recognition uses elements such as the content and tone of the text and the voice signal. 【0372】 The terminal functions as the user interface. Through the terminal, users can enter questions into text input boxes or make inquiries by voice. The terminal may also display indicators that allow users to select or adjust their emotions. 【0373】 As a concrete example, if a user enters the prompt "I want to learn the basics of generative AI," the server will retrieve relevant basic information from its sources and generate a response in an easy-to-understand format. At the same time, if the user expresses anxiety, the server will generate a response using reassuring language. 【0374】 This system allows users to efficiently acquire knowledge from the generated AI in a way that aligns with their own emotions. User feedback and emotional data collected by the server are further used to improve the system's performance, enabling better personalization in subsequent interactions. 【0375】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0376】 Step 1: 【0377】 Users input questions about the generated AI by operating a terminal. This is typically done using a text input box, but voice input is also possible. Users can also select or adjust their own emotional state using the provided emotion indicators. The input data, along with the question content and emotion information, is sent to the server. 【0378】 Step 2: 【0379】 The server takes in text data and sentiment information received from the user and analyzes it using natural language processing algorithms. Morphological and syntactic analysis is performed on the input data to convert the user's questions into specific operational commands. Simultaneously, the sentiment recognition engine analyzes the input sentiment information to identify the user's emotional state. The analysis results form the basis for generating the next response. 【0380】 Step 3: 【0381】 The server searches for relevant knowledge from information sources based on the analyzed question. It uses database queries to identify the target information and select the most appropriate content. This process also considers the user's emotional state, ensuring that information with an appropriate tone and level of detail is chosen. The selected knowledge then becomes the basis for generating the response. 【0382】 Step 4: 【0383】 The server uses knowledge selected through a generative AI model to generate the optimal response for the user. This response is not only accurate but also tailored to the user's emotional state. For users expressing anxiety, the system is designed to provide reassurance through familiar language and examples. The response text is sent to the device as soon as it is generated. 【0384】 Step 5: 【0385】 The terminal presents the response sent from the server to the user. Information is displayed in a way that is easily understandable to the user through visual representations and audio responses. In this step, the response speed and interface design are carefully considered to enhance the user experience. 【0386】 Step 6: 【0387】 Users can provide further questions or feedback in response to the answers they receive. This user feedback is collected by the server and used to update the learning device and improve system performance. This allows the system to continuously improve itself, preparing to deliver a more refined and personalized experience in subsequent interactions. 【0388】 (Application Example 2) 【0389】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal". 【0390】 In caregiving settings, it is difficult to appropriately understand the emotions of service users and provide individualized support and communication. In particular, traditional systems are insufficient to handle situations requiring responses based on emotional changes or different support for each user. This raises concerns about decreased user satisfaction and increased stress. 【0391】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0392】 In this invention, the server includes means for initializing a database containing information related to generative artificial intelligence and storing said information, means for receiving input from a user and analyzing said input using a natural language processing algorithm, and means for analyzing the user's emotions and generating a response corresponding to those emotions. This enables the server to understand the user's emotions and provide personalized responses based on those emotions. 【0393】 "Generative artificial intelligence" is an artificial intelligence technology that has the ability to generate new data based on input data. 【0394】 A "database" is an information system that systematically stores information and makes it easily accessible when needed. 【0395】 A "natural language processing algorithm" is a set of processing techniques for handling human language using computers. 【0396】 "Emotion analysis" is a technology that identifies emotions and emotional states from user input data. 【0397】 A "response" is the information that the system generates and presents in response to input from the user. 【0398】 "Feedback" refers to reaction information such as evaluations and opinions provided by users. 【0399】 A "learning model" is a computer model that is built to learn specific patterns and rules based on data, enabling it to perform autonomous reasoning and decision-making. 【0400】 This invention is a system that combines generative artificial intelligence technology and emotion recognition technology to identify the emotions of users in care settings and realize personalized communication and support. Specific embodiments are shown below. 【0401】 The server builds a database containing information about generative artificial intelligence. This database serves as a source of information for responding quickly and accurately to user inquiries. The server also uses natural language processing algorithms to analyze and understand user input. 【0402】 Furthermore, the server incorporates an emotion engine to analyze the user's emotions. This engine recognizes the user's emotional state—for example, emotions such as joy, anxiety, and anger—from the input text and audio data. For this purpose, natural language processing libraries such as Google's TensorFlow and IBM's Watson are used. 【0403】 The terminal provides an interface for receiving user input and displays indicators related to emotions. This terminal comprises a wide range of user devices, including personal digital assistants (PDAs) such as smartphones. 【0404】 Users input questions along with emotional information. The server receives this emotional information and generates a response accordingly. The generated response uses friendly and emotionally sensitive language, such as OpenAI's GPT-4, to address the user's feelings. 【0405】 For example, if a user enters information indicating anxiety, such as "I'm not feeling well today," the system can respond with a kind message like, "Please let me know if there's anything I can do to help." 【0406】 An example of a prompt message generated using a generative AI model is one that asks, "What actions can be taken to reassure a user who is showing signs of anxiety?" This allows for appropriate responses that are sensitive to the user's feelings. 【0407】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0408】 Step 1: 【0409】 The device receives voice or text input from the user. The user also inputs an indicator showing their emotional state. The input data includes the user's questions and emotional indicator. 【0410】 Step 2: 【0411】 The server receives input data sent from the terminal and analyzes the question using natural language processing algorithms. Specifically, it uses Google's TensorFlow to tokenize the text and extract context. This process clarifies what the user is asking. 【0412】 Step 3: 【0413】 The server uses an emotion analysis engine to determine the user's emotional state. It analyzes the input text and voice tone to identify emotions such as "anxiety" or "joy." Based on the analysis results, it adjusts the response style. 【0414】 Step 4: 【0415】 The server searches the database for an appropriate answer based on the analyzed question content and emotional state. Depending on the situation, it uses a generative artificial intelligence model (e.g., OpenAI's GPT-4) to generate a response that is most understandable and empathetic to the user. 【0416】 Step 5: 【0417】 The generated response is presented to the user via the terminal. The server adds expressions and examples to the response content that take into account the user's emotional state. For example, reassuring words are used for a user who is showing anxiety. 【0418】 Step 6: 【0419】 Users provide feedback on the responses they receive. The server receives this feedback and updates its learning model. This allows the system to continuously learn to provide more accurate and personalized responses. 【0420】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0421】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0422】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0423】 [Third Embodiment] 【0424】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0425】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0426】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0427】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0428】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0429】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0430】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0431】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0432】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0433】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0434】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0435】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0436】 In an embodiment of the present invention, a method for constructing an interactive learning support system utilizing generative artificial intelligence will be described. This system is designed to help users overcome questions or lack of knowledge about generative AI and is operated through interaction between a server, a terminal, and the user. 【0437】 The server first initializes a comprehensive database of generative AI, which stores fundamental theoretical and technical information related to text, image, audio, and video generation. This forms a knowledge base capable of responding to a wide range of user questions. 【0438】 The terminal provides an interface for user input. This interface primarily allows text input, but can also include voice recognition functionality as needed. The user inputs questions about the generated AI through the terminal, and the system provides information corresponding to those questions. 【0439】 The user input received is analyzed by the server using natural language processing algorithms. This analysis identifies which generative AI technology the input relates to, and then retrieves specific information about that technology from the database. 【0440】 The retrieved information is formatted appropriately by the server and provided to the user in an easy-to-understand manner. For example, if the question concerns text generation, the server might present the user with an overview of the relevant technology, practical application examples, and basic operating procedures. 【0441】 Furthermore, the server receives and analyzes user feedback to improve the system itself. Specifically, if a user provides unclear points regarding a response, that information is used to improve the database and natural language processing algorithms. This allows for the provision of more appropriate information in subsequent interactions. 【0442】 For example, if a user inputs "I want to know about examples of speech generation technology use," the server provides information on the fundamental technologies related to speech generation, well-known examples, and available software tools, and further sends the user a document explaining the basic usage of those tools. In this way, the system of the present invention provides practical support for deepening understanding of generation AI. 【0443】 The following describes the processing flow. 【0444】 Step 1: 【0445】 The server initializes and loads a database containing information about the generative AI. This includes fundamental information and related technologies for generating text, images, audio, and video. 【0446】 Step 2: 【0447】 The terminal provides an interface for users to input questions and inquiries. Users can use this interface to input any questions related to the generated AI. 【0448】 Step 3: 【0449】 Users can input or voice-inform their device about specific questions or topics for which they want information regarding the generative AI. 【0450】 Step 4: 【0451】 The terminal sends user input to the server. The input is passed to the server as text data. 【0452】 Step 5: 【0453】 The server analyzes the received input using a natural language processing algorithm. Here, keywords are extracted to identify which generative AI field the question relates to. 【0454】 Step 6: 【0455】 The server searches the database for appropriate information based on the analysis results and selects the most suitable information to meet the user's needs. 【0456】 Step 7: 【0457】 The server reconstructs the selected information into a user-friendly and useful format to create a response. 【0458】 Step 8: 【0459】 The terminal displays the generated response to the user. In some cases, it may also present visual materials such as images and diagrams. 【0460】 Step 9: 【0461】 Users learn based on the information presented, and if they have further questions, they send additional questions or feedback to the server via their device. 【0462】 Step 10: 【0463】 The server receives user feedback, analyzes it, and uses it to improve the entire system. It updates its learning model to provide better responses in subsequent interactions. 【0464】 (Example 1) 【0465】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0466】 In recent years, while generative artificial intelligence technology has advanced, a challenge remains: users often lack sufficient knowledge about this technology. There is a need to provide systems that enable users to resolve their questions about generative AI technology and obtain necessary information quickly and effectively. 【0467】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0468】 In this invention, the server includes means for initializing and storing a knowledge set relating to generative artificial intelligence, natural language processing means for receiving and analyzing inquiries from users, and means for searching for relevant knowledge from the knowledge set and selecting the most appropriate knowledge based on the analyzed inquiries. This enables users to effectively obtain the information necessary to answer questions about generative AI. 【0469】 "Generative artificial intelligence" refers to all technologies that automatically generate text, images, audio, videos, and other content based on user input. 【0470】 A "knowledge set" refers to a database that systematically collects, classifies, and maintains theoretical and technical information related to generative artificial intelligence in an accessible format. 【0471】 "Natural language processing means" refers to algorithms and technologies for analyzing text input from users and understanding its meaning. 【0472】 An "inquiry" refers to a question or keyword that a user enters into the system to request information about generative artificial intelligence. 【0473】 "Opinions" refer to the feedback and evaluations that users provide to the system's response. 【0474】 "Visual information" refers to information such as diagrams and images that are added to text information to aid in visual understanding. 【0475】 "Dialogue history" refers to the log of all inquiries and responses that took place between the user and the system. 【0476】 This invention describes a specific method for implementing an interactive learning support system based on generative artificial intelligence. The system operates primarily through interaction between a server, a terminal, and a user. 【0477】 Server Role 【0478】 The server is a central information processing unit for initializing and maintaining a knowledge set related to generative artificial intelligence. The server is equipped with large-capacity storage and a high-performance processor, and the knowledge set contains various data related to text generation, image generation, speech generation, and video generation. The server analyzes user inquiries using natural language processing tools, searches for relevant knowledge, and selects the most appropriate one. NLP algorithms and machine learning models operate during this process. 【0479】 Terminal role 【0480】 The terminal is an input / output device used by the user, providing an interface for the user to access the system. The terminal is equipped with a keyboard or touchscreen for text input, and in some cases, a microphone for voice input. The user makes inquiries about the generated AI through the terminal and receives the results. The terminal visually presents the received results to the user to aid in understanding. 【0481】 User roles 【0482】 Users can use the system to obtain information about generated AI and deepen their understanding of it. Users can ask specific questions about technologies that interest them and learn based on the information they receive. 【0483】 Specific example 【0484】 For example, if a user enters the prompt "I want to know about examples of speech generation technology use," the server parses this query and searches its knowledge set for relevant information about speech generation technology. As a result, the server appropriately organizes information such as an overview of speech generation technology, famous examples, and available tools, and presents it to the user through the terminal. The user can then deepen their understanding of speech generation technology based on this information. 【0485】 In this way, the system of the present invention effectively provides learning support for generative AI and contributes to improving the user's knowledge. 【0486】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0487】 Step 1: 【0488】 The terminal provides an interface for the user to access the system. The user inputs questions about the generated AI in text or voice. The input questions are saved as digital data and prepared to be sent to the server. 【0489】 Step 2: 【0490】 The server receives user data sent from the terminal. Using a specified natural language processing algorithm, the server analyzes the user's question. This process analyzes the input text, extracts relevant keywords and concepts, and identifies which generative AI technologies are associated with it. 【0491】 Step 3: 【0492】 The server matches keywords and concepts obtained from the analysis against a knowledge database. Through a database search algorithm, the server retrieves information related to the user's question and selects the most relevant knowledge. 【0493】 Step 4: 【0494】 The server constructs a user-friendly response based on selected knowledge. During this process, the server organizes search results and can add visual aids and supplementary explanations. This ensures that the user receives specific and clear information. 【0495】 Step 5: 【0496】 The terminal receives responses sent from the server and displays them to the user. Responses are displayed as text, but can also be output as speech using speech synthesis technology if necessary. The user can then learn about the generating AI based on this information. 【0497】 Step 6: 【0498】 Users send feedback about the information they receive to the server via their device. This feedback includes their satisfaction with the question and suggestions for improvement. This input is collected by the server and used to improve natural language processing algorithms and update the knowledge set. 【0499】 (Application Example 1) 【0500】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0501】 In providing information on generative artificial intelligence, there is a need to quickly and efficiently deliver optimal information and educational content tailored to the varying levels of understanding and learning needs of users. Current systems make it difficult to access specialized information on generative AI, and lack mechanisms to effectively utilize individual learning progress and feedback, making it challenging to maximize learning efficiency. 【0502】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0503】 In this invention, the server includes means for initializing a database containing information on generative artificial intelligence and storing said information, means for receiving input from a user and analyzing said input with a natural language processing algorithm, and means for delivering educational content linked to the generated information and supporting the user's understanding. This enables users to efficiently learn about generative AI and deepen their understanding using content optimized for their individual learning needs. 【0504】 A "database containing information on generative artificial intelligence" is a collection of data that organizes and stores information covering theories, technologies, and applications related to generative artificial intelligence technology. 【0505】 "User input" refers to data expressed in text or voice as questions or requests for information related to generative artificial intelligence. 【0506】 A "natural language processing algorithm" is a computational method that analyzes user input, understands its meaning, and extracts relevant information. 【0507】 "Educational content linked to generated information" refers to learning materials and interactive content designed based on analyzed generative artificial intelligence information, with the aim of deepening understanding of that information. 【0508】 "Means to support user understanding" refer to methods and processes for presenting information related to generative artificial intelligence in an easy-to-understand manner and enhancing its educational effectiveness. 【0509】 The system for implementing this invention is configured as follows: The server initializes a database containing information on generative artificial intelligence and stores diverse information on generative artificial intelligence technology. This database covers everything from the theory to the practical applications of generative AI and serves as a foundation for enabling diverse responses to user questions. 【0510】 Users connected via a device send questions about the generated AI to the server through text or voice input. The device provides a simple and intuitive interface, making it easy for users to input information. Specific hardware such as smartphones and tablets are envisioned. 【0511】 The server analyzes the received input using natural language processing algorithms and searches for relevant data in the database. During the analysis process, a natural language processing framework is used to extract keywords and context from the input data. This allows the server to accurately understand the intent of the user's question and select the most relevant information. 【0512】 The selected information, along with the generated educational content, is sent to the device and presented to the user. This allows users not only to learn the fundamental theory of generative AI but also to deepen their practical understanding through interactive learning materials. For example, a user who wants to learn about the text generation process using generative AI will be provided with visual materials on the theoretical background and tutorials on how to use the actual tools. 【0513】 Furthermore, user feedback is sent to the server and used to improve the learning model. This enables more accurate information to be provided in subsequent interactions. For example, if a user enters a prompt such as "I want to learn about the basic theory and applications of image generation AI," relevant materials and demonstration content will be provided based on that request, allowing the user to experience AI image generation technology firsthand. 【0514】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0515】 Step 1: 【0516】 The terminal receives prompts from the user regarding image generation AI as input. The user uses the text input field displayed on the terminal's interface to enter questions such as, "I want to learn about the basic theory and applications of image generation AI." This becomes the initial input data for the system. 【0517】 Step 2: 【0518】 The terminal sends prompts entered by the user to the server. The server receives these prompts as input and applies a natural language processing algorithm. The algorithm analyzes the input data, extracts relevant keywords and phrases, and performs data processing to form database queries. 【0519】 Step 3: 【0520】 The server searches the database based on the analyzed keywords. Since the database contains information on theories and applications related to generative AI, the server selects the most relevant information from the search results. This data processing generates appropriate response data for the user's question. 【0521】 Step 4: 【0522】 The server composes interactive educational content along with search results and outputs it to the terminal. For example, it might combine text explaining the theory behind image generation AI with visual demonstration content based on that theory. This data processing results in content that provides the user with an optimal learning experience. 【0523】 Step 5: 【0524】 The device presents the received information and content to the user. The user reviews explanatory text and visual materials on the screen and gains knowledge about the generating AI. This output information also includes interactive elements, allowing the user to directly manipulate the content and learn from it. 【0525】 Step 6: 【0526】 After users view content, they enter feedback, and this data is acquired by their device. The device then sends this feedback to the server. The server analyzes the received feedback and uses it to update learning models and databases. This data processing can further improve the overall system response and content accuracy in the future. 【0527】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0528】 In an embodiment of the present invention, a method for constructing an interactive learning system is described, which combines generative artificial intelligence technology with user emotion recognition. This system involves a server, a terminal, and a user, and uses an emotion engine to make interactions with the user more effective and personalized. 【0529】 The server initializes a database containing comprehensive information about generative artificial intelligence. This allows it to quickly and appropriately provide information when a user asks a question about generative AI. In addition, the server's built-in natural language processing algorithms analyze the user's input data, enabling it to properly understand the user's questions. 【0530】 Furthermore, in this embodiment, an emotion engine is integrated into the server. The emotion engine recognizes emotions from the user's input text and voice. For example, it can analyze the user's emotional state from the content of the text, the words used, and the tone of voice. 【0531】 The terminal provides an interface for receiving user input. Here, a new emotion indicator is displayed, allowing the user to select or adjust their own emotions. The user inputs questions about the generating AI along with their emotion information. 【0532】 When the server receives emotion information along with user input data, it generates a response in a manner appropriate to that emotion. For example, if the user indicates an emotion of confusion, the server will attempt to resolve the issue by providing a more detailed and understandable explanation or by offering specific examples. 【0533】 For example, if a user expresses anxiety along with a question such as "I don't understand the basics of speech generation technology," the server will generate a response that uses reassuring language and relatable examples, along with basic knowledge of speech generation technology. 【0534】 Emotional data accumulated through user interactions is analyzed by the server and used to improve the accuracy of responses in subsequent interactions. This makes it easier for users to advance the generative AI's learning through the system, enabling the provision of support optimized for each individual user. 【0535】 The following describes the processing flow. 【0536】 Step 1: 【0537】 The server initializes a database containing information about generative artificial intelligence and makes it available to users in response to their inquiries. 【0538】 Step 2: 【0539】 The device provides an interface that allows users to input questions about the generated AI. This interface includes text input boxes and, in some cases, voice input options. 【0540】 Step 3: 【0541】 Users enter questions and inquiries about the generative AI into their device using an easy-to-read input method. Input can be in the form of text or voice. 【0542】 Step 4: 【0543】 The terminal sends user input to the server. At the same time, it also sends the emotional information selected via the emotional indicator. 【0544】 Step 5: 【0545】 The server analyzes the user's input using a natural language processing algorithm to identify which generative AI technology the question relates to. 【0546】 Step 6: 【0547】 The server uses an emotion engine to recognize emotions from user input. Based on this recognized emotion information, it analyzes the user's state. 【0548】 Step 7: 【0549】 Based on the analyzed input and emotional information, the server searches the database for relevant information and selects information appropriate to the user's emotional state. For example, if the emotion is confusion, it will include detailed guidance and encouragement. 【0550】 Step 8: 【0551】 The server combines the selected information and generates a response that takes the user's emotions into consideration. 【0552】 Step 9: 【0553】 The terminal receives a response from the server and presents it to the user. In some cases, presenting visual materials or examples can be effective. 【0554】 Step 10: 【0555】 Users review the information presented and, if they have further questions or new feedback, send it to the server via their device. 【0556】 Step 11: 【0557】 The server analyzes dialogue logs and sentiment data based on user feedback and new inputs, and uses this information to improve the system. This allows for the provision of optimized responses to the user in future interactions. 【0558】 (Example 2) 【0559】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0560】 In dialogue systems using generative artificial intelligence, there is a problem in providing appropriate and effective information while considering the individual emotional state of the user. Furthermore, conventional systems have the problem of uniform responses to users and being unable to respond flexibly to individual emotional changes and states, which can lead to decreased user satisfaction. 【0561】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0562】 In this invention, the server includes means for initializing and storing an information source containing information about generative artificial intelligence; natural language processing means for receiving and analyzing data from a user; and emotion recognition means for detecting the user's emotions and adjusting the response accordingly. This enables the provision of personalized information tailored to each user's emotional state. 【0563】 "Information source" refers to a database or repository that stores information about generative artificial intelligence and makes it accessible as needed. 【0564】 "Natural language processing means" refers to language understanding technology that analyzes input data from users and generates appropriate responses. 【0565】 "Emotion recognition means" refers to technology that identifies an emotional state from the user's input data and generates a response corresponding to that state. 【0566】 "Generative artificial intelligence" refers to artificial intelligence technology that learns from large amounts of data and automatically generates new information and responses. 【0567】 "Response" refers to information or answers provided by generative artificial intelligence based on user input. 【0568】 "User" refers to an individual or end-user who acquires and learns information through interaction with the system. 【0569】 "Feedback" refers to evaluation information and opinions obtained from users, and the system is improved and adjusted based on this feedback. 【0570】 This invention relates to a system that provides an interactive interface that responds to the user's emotions using generative artificial intelligence technology. The system is constructed in a manner that involves three parties: a server, a terminal, and a user. 【0571】 The server initializes information sources containing information about generative artificial intelligence and stores them as a database. The server is equipped with natural language processing algorithms that analyze input data received from the user. This analysis provides a foundation for accurately understanding the user's questions and generating responses. 【0572】 Furthermore, the server incorporates an emotion recognition engine. This engine detects emotions from the user's input text and voice, and adjusts the response to be appropriate to the user's emotions. This emotion recognition uses elements such as the content and tone of the text and the voice signal. 【0573】 The terminal functions as the user interface. Through the terminal, users can enter questions into text input boxes or make inquiries by voice. The terminal may also display indicators that allow users to select or adjust their emotions. 【0574】 As a concrete example, if a user enters the prompt "I want to learn the basics of generative AI," the server will retrieve relevant basic information from its sources and generate a response in an easy-to-understand format. At the same time, if the user expresses anxiety, the server will generate a response using reassuring language. 【0575】 This system allows users to efficiently acquire knowledge from the generated AI in a way that aligns with their own emotions. User feedback and emotional data collected by the server are further used to improve the system's performance, enabling better personalization in subsequent interactions. 【0576】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0577】 Step 1: 【0578】 Users input questions about the generated AI by operating a terminal. This is typically done using a text input box, but voice input is also possible. Users can also select or adjust their own emotional state using the provided emotion indicators. The input data, along with the question content and emotion information, is sent to the server. 【0579】 Step 2: 【0580】 The server takes in text data and sentiment information received from the user and analyzes it using natural language processing algorithms. Morphological and syntactic analysis is performed on the input data to convert the user's questions into specific operational commands. Simultaneously, the sentiment recognition engine analyzes the input sentiment information to identify the user's emotional state. The analysis results form the basis for generating the next response. 【0581】 Step 3: 【0582】 The server searches for relevant knowledge from information sources based on the analyzed question. It uses database queries to identify the target information and select the most appropriate content. This process also considers the user's emotional state, ensuring that information with an appropriate tone and level of detail is chosen. The selected knowledge then becomes the basis for generating the response. 【0583】 Step 4: 【0584】 The server uses knowledge selected through a generative AI model to generate the optimal response for the user. This response is not only accurate but also tailored to the user's emotional state. For users expressing anxiety, the system is designed to provide reassurance through familiar language and examples. The response text is sent to the device as soon as it is generated. 【0585】 Step 5: 【0586】 The terminal presents the response sent from the server to the user. Information is displayed in a way that is easily understandable to the user through visual representations and audio responses. In this step, the response speed and interface design are carefully considered to enhance the user experience. 【0587】 Step 6: 【0588】 Users can provide further questions or feedback in response to the answers they receive. This user feedback is collected by the server and used to update the learning device and improve system performance. This allows the system to continuously improve itself, preparing to deliver a more refined and personalized experience in subsequent interactions. 【0589】 (Application Example 2) 【0590】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0591】 In caregiving settings, it is difficult to appropriately understand the emotions of service users and provide individualized support and communication. In particular, traditional systems are insufficient to handle situations requiring responses based on emotional changes or different support for each user. This raises concerns about decreased user satisfaction and increased stress. 【0592】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0593】 In this invention, the server includes means for initializing a database containing information related to generative artificial intelligence and storing said information, means for receiving input from a user and analyzing said input using a natural language processing algorithm, and means for analyzing the user's emotions and generating a response corresponding to those emotions. This enables the server to understand the user's emotions and provide personalized responses based on those emotions. 【0594】 "Generative artificial intelligence" is an artificial intelligence technology that has the ability to generate new data based on input data. 【0595】 A "database" is an information system that systematically stores information and makes it easily accessible when needed. 【0596】 A "natural language processing algorithm" is a set of processing techniques for handling human language using computers. 【0597】 "Emotion analysis" is a technology that identifies emotions and emotional states from user input data. 【0598】 A "response" is the information that the system generates and presents in response to input from the user. 【0599】 "Feedback" refers to reaction information such as evaluations and opinions provided by users. 【0600】 A "learning model" is a computer model that is built to learn specific patterns and rules based on data, enabling it to perform autonomous reasoning and decision-making. 【0601】 This invention is a system that combines generative artificial intelligence technology and emotion recognition technology to identify the emotions of users in care settings and realize personalized communication and support. Specific embodiments are shown below. 【0602】 The server builds a database containing information about generative artificial intelligence. This database serves as a source of information for responding quickly and accurately to user inquiries. The server also uses natural language processing algorithms to analyze and understand user input. 【0603】 Furthermore, the server incorporates an emotion engine to analyze the user's emotions. This engine recognizes the user's emotional state—for example, emotions such as joy, anxiety, and anger—from the input text and audio data. For this purpose, natural language processing libraries such as Google's TensorFlow and IBM's Watson are used. 【0604】 The terminal provides an interface for receiving user input and displays indicators related to emotions. This terminal comprises a wide range of user devices, including personal digital assistants (PDAs) such as smartphones. 【0605】 Users input questions along with emotional information. The server receives this emotional information and generates a response accordingly. The generated response uses friendly and emotionally sensitive language, such as OpenAI's GPT-4, to address the user's feelings. 【0606】 For example, if a user enters information indicating anxiety, such as "I'm not feeling well today," the system can respond with a kind message like, "Please let me know if there's anything I can do to help." 【0607】 An example of a prompt message generated using a generative AI model is one that asks, "What actions can be taken to reassure a user who is showing signs of anxiety?" This allows for appropriate responses that are sensitive to the user's feelings. 【0608】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0609】 Step 1: 【0610】 The device receives voice or text input from the user. The user also inputs an indicator showing their emotional state. The input data includes the user's questions and emotional indicator. 【0611】 Step 2: 【0612】 The server receives input data sent from the terminal and analyzes the question using natural language processing algorithms. Specifically, it uses Google's TensorFlow to tokenize the text and extract context. This process clarifies what the user is asking. 【0613】 Step 3: 【0614】 The server uses an emotion analysis engine to determine the user's emotional state. It analyzes the input text and voice tone to identify emotions such as "anxiety" or "joy." Based on the analysis results, it adjusts the response style. 【0615】 Step 4: 【0616】 The server searches the database for an appropriate answer based on the analyzed question content and emotional state. Depending on the situation, it uses a generative artificial intelligence model (e.g., OpenAI's GPT-4) to generate a response that is most understandable and empathetic to the user. 【0617】 Step 5: 【0618】 The generated response is presented to the user via the terminal. The server adds expressions and examples to the response content that take into account the user's emotional state. For example, reassuring words are used for a user who is showing anxiety. 【0619】 Step 6: 【0620】 Users provide feedback on the responses they receive. The server receives this feedback and updates its learning model. This allows the system to continuously learn to provide more accurate and personalized responses. 【0621】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0622】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0623】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0624】 [Fourth Embodiment] 【0625】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0626】 As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server. 【0627】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0628】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0629】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0630】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0631】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0632】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0633】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0634】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0635】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0636】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0637】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0638】 In an embodiment of the present invention, a method for constructing an interactive learning support system utilizing generative artificial intelligence will be described. This system is designed to help users overcome questions or lack of knowledge about generative AI and is operated through interaction between a server, a terminal, and the user. 【0639】 The server first initializes a comprehensive database of generative AI, which stores fundamental theoretical and technical information related to text, image, audio, and video generation. This forms a knowledge base capable of responding to a wide range of user questions. 【0640】 The terminal provides an interface for user input. This interface primarily allows text input, but can also include voice recognition functionality as needed. The user inputs questions about the generated AI through the terminal, and the system provides information corresponding to those questions. 【0641】 The user input received is analyzed by the server using natural language processing algorithms. This analysis identifies which generative AI technology the input relates to, and then retrieves specific information about that technology from the database. 【0642】 The retrieved information is formatted appropriately by the server and provided to the user in an easy-to-understand manner. For example, if the question concerns text generation, the server might present the user with an overview of the relevant technology, practical application examples, and basic operating procedures. 【0643】 Furthermore, the server receives and analyzes user feedback to improve the system itself. Specifically, if a user provides unclear points regarding a response, that information is used to improve the database and natural language processing algorithms. This allows for the provision of more appropriate information in subsequent interactions. 【0644】 For example, if a user inputs "I want to know about examples of speech generation technology use," the server provides information on the fundamental technologies related to speech generation, well-known examples, and available software tools, and further sends the user a document explaining the basic usage of those tools. In this way, the system of the present invention provides practical support for deepening understanding of generation AI. 【0645】 The following describes the processing flow. 【0646】 Step 1: 【0647】 The server initializes and loads a database containing information about the generative AI. This includes fundamental information and related technologies for generating text, images, audio, and video. 【0648】 Step 2: 【0649】 The terminal provides an interface for users to input questions and inquiries. Users can use this interface to input any questions related to the generated AI. 【0650】 Step 3: 【0651】 Users can input or voice-inform their device about specific questions or topics for which they want information regarding the generative AI. 【0652】 Step 4: 【0653】 The terminal sends user input to the server. The input is passed to the server as text data. 【0654】 Step 5: 【0655】 The server analyzes the received input using a natural language processing algorithm. Here, keywords are extracted to identify which generative AI field the question relates to. 【0656】 Step 6: 【0657】 The server searches the database for appropriate information based on the analysis results and selects the most suitable information to meet the user's needs. 【0658】 Step 7: 【0659】 The server reconstructs the selected information into a user-friendly and useful format to create a response. 【0660】 Step 8: 【0661】 The terminal displays the generated response to the user. In some cases, it may also present visual materials such as images and diagrams. 【0662】 Step 9: 【0663】 Users learn based on the information presented, and if they have further questions, they send additional questions or feedback to the server via their device. 【0664】 Step 10: 【0665】 The server receives user feedback, analyzes it, and uses it to improve the entire system. It updates its learning model to provide better responses in subsequent interactions. 【0666】 (Example 1) 【0667】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0668】 In recent years, while generative artificial intelligence technology has advanced, a challenge remains: users often lack sufficient knowledge about this technology. There is a need to provide systems that enable users to resolve their questions about generative AI technology and obtain necessary information quickly and effectively. 【0669】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0670】 In this invention, the server includes means for initializing and storing a knowledge set relating to generative artificial intelligence, natural language processing means for receiving and analyzing inquiries from users, and means for searching for relevant knowledge from the knowledge set and selecting the most appropriate knowledge based on the analyzed inquiries. This enables users to effectively obtain the information necessary to answer questions about generative AI. 【0671】 "Generative artificial intelligence" refers to all technologies that automatically generate text, images, audio, videos, and other content based on user input. 【0672】 A "knowledge set" refers to a database that systematically collects, classifies, and maintains theoretical and technical information related to generative artificial intelligence in an accessible format. 【0673】 "Natural language processing means" refers to algorithms and technologies for analyzing text input from users and understanding its meaning. 【0674】 An "inquiry" refers to a question or keyword that a user enters into the system to request information about generative artificial intelligence. 【0675】 "Opinions" refer to the feedback and evaluations that users provide to the system's response. 【0676】 "Visual information" refers to information such as diagrams and images that are added to text information to aid in visual understanding. 【0677】 "Dialogue history" refers to the log of all inquiries and responses that took place between the user and the system. 【0678】 This invention describes a specific method for implementing an interactive learning support system based on generative artificial intelligence. The system operates primarily through interaction between a server, a terminal, and a user. 【0679】 Server Role 【0680】 The server is a central information processing unit for initializing and maintaining a knowledge set related to generative artificial intelligence. The server is equipped with large-capacity storage and a high-performance processor, and the knowledge set contains various data related to text generation, image generation, speech generation, and video generation. The server analyzes user inquiries using natural language processing tools, searches for relevant knowledge, and selects the most appropriate one. NLP algorithms and machine learning models operate during this process. 【0681】 Terminal role 【0682】 The terminal is an input / output device used by the user, providing an interface for the user to access the system. The terminal is equipped with a keyboard or touchscreen for text input, and in some cases, a microphone for voice input. The user makes inquiries about the generated AI through the terminal and receives the results. The terminal visually presents the received results to the user to aid in understanding. 【0683】 User roles 【0684】 Users can use the system to obtain information about generated AI and deepen their understanding of it. Users can ask specific questions about technologies that interest them and learn based on the information they receive. 【0685】 Specific example 【0686】 For example, if a user enters the prompt "I want to know about examples of speech generation technology use," the server parses this query and searches its knowledge set for relevant information about speech generation technology. As a result, the server appropriately organizes information such as an overview of speech generation technology, famous examples, and available tools, and presents it to the user through the terminal. The user can then deepen their understanding of speech generation technology based on this information. 【0687】 In this way, the system of the present invention effectively provides learning support for generative AI and contributes to improving the user's knowledge. 【0688】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0689】 Step 1: 【0690】 The terminal provides an interface for the user to access the system. The user inputs questions about the generated AI in text or voice. The input questions are saved as digital data and prepared to be sent to the server. 【0691】 Step 2: 【0692】 The server receives user data sent from the terminal. Using a specified natural language processing algorithm, the server analyzes the user's question. This process analyzes the input text, extracts relevant keywords and concepts, and identifies which generative AI technologies are associated with it. 【0693】 Step 3: 【0694】 The server matches keywords and concepts obtained from the analysis against a knowledge database. Through a database search algorithm, the server retrieves information related to the user's question and selects the most relevant knowledge. 【0695】 Step 4: 【0696】 The server constructs a user-friendly response based on selected knowledge. During this process, the server organizes search results and can add visual aids and supplementary explanations. This ensures that the user receives specific and clear information. 【0697】 Step 5: 【0698】 The terminal receives responses sent from the server and displays them to the user. Responses are displayed as text, but can also be output as speech using speech synthesis technology if necessary. The user can then learn about the generating AI based on this information. 【0699】 Step 6: 【0700】 Users send feedback about the information they receive to the server via their device. This feedback includes their satisfaction with the question and suggestions for improvement. This input is collected by the server and used to improve natural language processing algorithms and update the knowledge set. 【0701】 (Application Example 1) 【0702】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0703】 In providing information on generative artificial intelligence, there is a need to quickly and efficiently deliver optimal information and educational content tailored to the varying levels of understanding and learning needs of users. Current systems make it difficult to access specialized information on generative AI, and lack mechanisms to effectively utilize individual learning progress and feedback, making it challenging to maximize learning efficiency. 【0704】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0705】 In this invention, the server includes means for initializing a database containing information on generative artificial intelligence and storing said information, means for receiving input from a user and analyzing said input with a natural language processing algorithm, and means for delivering educational content linked to the generated information and supporting the user's understanding. This enables users to efficiently learn about generative AI and deepen their understanding using content optimized for their individual learning needs. 【0706】 A "database containing information on generative artificial intelligence" is a collection of data that organizes and stores information covering theories, technologies, and applications related to generative artificial intelligence technology. 【0707】 "User input" refers to data expressed in text or voice as questions or requests for information related to generative artificial intelligence. 【0708】 A "natural language processing algorithm" is a computational method that analyzes user input, understands its meaning, and extracts relevant information. 【0709】 "Educational content linked to generated information" refers to learning materials and interactive content designed based on analyzed generative artificial intelligence information, with the aim of deepening understanding of that information. 【0710】 "Means to support user understanding" refer to methods and processes for presenting information related to generative artificial intelligence in an easy-to-understand manner and enhancing its educational effectiveness. 【0711】 The system for implementing this invention is configured as follows: The server initializes a database containing information on generative artificial intelligence and stores diverse information on generative artificial intelligence technology. This database covers everything from the theory to the practical applications of generative AI and serves as a foundation for enabling diverse responses to user questions. 【0712】 Users connected via a device send questions about the generated AI to the server through text or voice input. The device provides a simple and intuitive interface, making it easy for users to input information. Specific hardware such as smartphones and tablets are envisioned. 【0713】 The server analyzes the received input using natural language processing algorithms and searches for relevant data in the database. During the analysis process, a natural language processing framework is used to extract keywords and context from the input data. This allows the server to accurately understand the intent of the user's question and select the most relevant information. 【0714】 The selected information, along with the generated educational content, is sent to the device and presented to the user. This allows users not only to learn the fundamental theory of generative AI but also to deepen their practical understanding through interactive learning materials. For example, a user who wants to learn about the text generation process using generative AI will be provided with visual materials on the theoretical background and tutorials on how to use the actual tools. 【0715】 Furthermore, user feedback is sent to the server and used to improve the learning model. This enables more accurate information to be provided in subsequent interactions. For example, if a user enters a prompt such as "I want to learn about the basic theory and applications of image generation AI," relevant materials and demonstration content will be provided based on that request, allowing the user to experience AI image generation technology firsthand. 【0716】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0717】 Step 1: 【0718】 The terminal receives prompts from the user regarding image generation AI as input. The user uses the text input field displayed on the terminal's interface to enter questions such as, "I want to learn about the basic theory and applications of image generation AI." This becomes the initial input data for the system. 【0719】 Step 2: 【0720】 The terminal sends prompts entered by the user to the server. The server receives these prompts as input and applies a natural language processing algorithm. The algorithm analyzes the input data, extracts relevant keywords and phrases, and performs data processing to form database queries. 【0721】 Step 3: 【0722】 The server searches the database based on the analyzed keywords. Since the database contains information on theories and applications related to generative AI, the server selects the most relevant information from the search results. This data processing generates appropriate response data for the user's question. 【0723】 Step 4: 【0724】 The server composes interactive educational content along with search results and outputs it to the terminal. For example, it might combine text explaining the theory behind image generation AI with visual demonstration content based on that theory. This data processing results in content that provides the user with an optimal learning experience. 【0725】 Step 5: 【0726】 The device presents the received information and content to the user. The user reviews explanatory text and visual materials on the screen and gains knowledge about the generating AI. This output information also includes interactive elements, allowing the user to directly manipulate the content and learn from it. 【0727】 Step 6: 【0728】 After users view content, they enter feedback, and this data is acquired by their device. The device then sends this feedback to the server. The server analyzes the received feedback and uses it to update learning models and databases. This data processing can further improve the overall system response and content accuracy in the future. 【0729】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0730】 In an embodiment of the present invention, a method for constructing an interactive learning system is described, which combines generative artificial intelligence technology with user emotion recognition. This system involves a server, a terminal, and a user, and uses an emotion engine to make interactions with the user more effective and personalized. 【0731】 The server initializes a database containing comprehensive information about generative artificial intelligence. This allows it to quickly and appropriately provide information when a user asks a question about generative AI. In addition, the server's built-in natural language processing algorithms analyze the user's input data, enabling it to properly understand the user's questions. 【0732】 Furthermore, in this embodiment, an emotion engine is integrated into the server. The emotion engine recognizes emotions from the user's input text and voice. For example, it can analyze the user's emotional state from the content of the text, the words used, and the tone of voice. 【0733】 The terminal provides an interface for receiving user input. Here, a new emotion indicator is displayed, allowing the user to select or adjust their own emotions. The user inputs questions about the generating AI along with their emotion information. 【0734】 When the server receives emotion information along with user input data, it generates a response in a manner appropriate to that emotion. For example, if the user indicates an emotion of confusion, the server will attempt to resolve the issue by providing a more detailed and understandable explanation or by offering specific examples. 【0735】 For example, if a user expresses anxiety along with a question such as "I don't understand the basics of speech generation technology," the server will generate a response that uses reassuring language and relatable examples, along with basic knowledge of speech generation technology. 【0736】 Emotional data accumulated through user interactions is analyzed by the server and used to improve the accuracy of responses in subsequent interactions. This makes it easier for users to advance the generative AI's learning through the system, enabling the provision of support optimized for each individual user. 【0737】 The following describes the processing flow. 【0738】 Step 1: 【0739】 The server initializes a database containing information about generative artificial intelligence and makes it available to users in response to their inquiries. 【0740】 Step 2: 【0741】 The device provides an interface that allows users to input questions about the generated AI. This interface includes text input boxes and, in some cases, voice input options. 【0742】 Step 3: 【0743】 Users enter questions and inquiries about the generative AI into their device using an easy-to-read input method. Input can be in the form of text or voice. 【0744】 Step 4: 【0745】 The terminal sends user input to the server. At the same time, it also sends the emotional information selected via the emotional indicator. 【0746】 Step 5: 【0747】 The server analyzes the user's input using a natural language processing algorithm to identify which generative AI technology the question relates to. 【0748】 Step 6: 【0749】 The server uses an emotion engine to recognize emotions from user input. Based on this recognized emotion information, it analyzes the user's state. 【0750】 Step 7: 【0751】 Based on the analyzed input and emotional information, the server searches the database for relevant information and selects information appropriate to the user's emotional state. For example, if the emotion is confusion, it will include detailed guidance and encouragement. 【0752】 Step 8: 【0753】 The server combines the selected information and generates a response that takes the user's emotions into consideration. 【0754】 Step 9: 【0755】 The terminal receives a response from the server and presents it to the user. In some cases, presenting visual materials or examples can be effective. 【0756】 Step 10: 【0757】 Users review the information presented and, if they have further questions or new feedback, send it to the server via their device. 【0758】 Step 11: 【0759】 The server analyzes dialogue logs and sentiment data based on user feedback and new inputs, and uses this information to improve the system. This allows for the provision of optimized responses to the user in future interactions. 【0760】 (Example 2) 【0761】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0762】 In dialogue systems using generative artificial intelligence, there is a problem in providing appropriate and effective information while considering the individual emotional state of the user. Furthermore, conventional systems have the problem of uniform responses to users and being unable to respond flexibly to individual emotional changes and states, which can lead to decreased user satisfaction. 【0763】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0764】 In this invention, the server includes means for initializing and storing an information source containing information about generative artificial intelligence; natural language processing means for receiving and analyzing data from a user; and emotion recognition means for detecting the user's emotions and adjusting the response accordingly. This enables the provision of personalized information tailored to each user's emotional state. 【0765】 "Information source" refers to a database or repository that stores information about generative artificial intelligence and makes it accessible as needed. 【0766】 "Natural language processing means" refers to language understanding technology that analyzes input data from users and generates appropriate responses. 【0767】 "Emotion recognition means" refers to technology that identifies an emotional state from the user's input data and generates a response corresponding to that state. 【0768】 "Generative artificial intelligence" refers to artificial intelligence technology that learns from large amounts of data and automatically generates new information and responses. 【0769】 "Response" refers to information or answers provided by generative artificial intelligence based on user input. 【0770】 "User" refers to an individual or end-user who acquires and learns information through interaction with the system. 【0771】 "Feedback" refers to evaluation information and opinions obtained from users, and the system is improved and adjusted based on this feedback. 【0772】 This invention relates to a system that provides an interactive interface that responds to the user's emotions using generative artificial intelligence technology. The system is constructed in a manner that involves three parties: a server, a terminal, and a user. 【0773】 The server initializes information sources containing information about generative artificial intelligence and stores them as a database. The server is equipped with natural language processing algorithms that analyze input data received from the user. This analysis provides a foundation for accurately understanding the user's questions and generating responses. 【0774】 Furthermore, the server incorporates an emotion recognition engine. This engine detects emotions from the user's input text and voice, and adjusts the response to be appropriate to the user's emotions. This emotion recognition uses elements such as the content and tone of the text and the voice signal. 【0775】 The terminal functions as the user interface. Through the terminal, users can enter questions into text input boxes or make inquiries by voice. The terminal may also display indicators that allow users to select or adjust their emotions. 【0776】 As a concrete example, if a user enters the prompt "I want to learn the basics of generative AI," the server will retrieve relevant basic information from its sources and generate a response in an easy-to-understand format. At the same time, if the user expresses anxiety, the server will generate a response using reassuring language. 【0777】 This system allows users to efficiently acquire knowledge from the generated AI in a way that aligns with their own emotions. User feedback and emotional data collected by the server are further used to improve the system's performance, enabling better personalization in subsequent interactions. 【0778】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0779】 Step 1: 【0780】 Users input questions about the generated AI by operating a terminal. This is typically done using a text input box, but voice input is also possible. Users can also select or adjust their own emotional state using the provided emotion indicators. The input data, along with the question content and emotion information, is sent to the server. 【0781】 Step 2: 【0782】 The server takes in text data and sentiment information received from the user and analyzes it using natural language processing algorithms. Morphological and syntactic analysis is performed on the input data to convert the user's questions into specific operational commands. Simultaneously, the sentiment recognition engine analyzes the input sentiment information to identify the user's emotional state. The analysis results form the basis for generating the next response. 【0783】 Step 3: 【0784】 The server searches for relevant knowledge from information sources based on the analyzed question. It uses database queries to identify the target information and select the most appropriate content. This process also considers the user's emotional state, ensuring that information with an appropriate tone and level of detail is chosen. The selected knowledge then becomes the basis for generating the response. 【0785】 Step 4: 【0786】 The server uses knowledge selected through a generative AI model to generate the optimal response for the user. This response is not only accurate but also tailored to the user's emotional state. For users expressing anxiety, the system is designed to provide reassurance through familiar language and examples. The response text is sent to the device as soon as it is generated. 【0787】 Step 5: 【0788】 The terminal presents the response sent from the server to the user. Information is displayed in a way that is easily understandable to the user through visual representations and audio responses. In this step, the response speed and interface design are carefully considered to enhance the user experience. 【0789】 Step 6: 【0790】 Users can provide further questions or feedback in response to the answers they receive. This user feedback is collected by the server and used to update the learning device and improve system performance. This allows the system to continuously improve itself, preparing to deliver a more refined and personalized experience in subsequent interactions. 【0791】 (Application Example 2) 【0792】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0793】 In caregiving settings, it is difficult to appropriately understand the emotions of service users and provide individualized support and communication. In particular, traditional systems are insufficient to handle situations requiring responses based on emotional changes or different support for each user. This raises concerns about decreased user satisfaction and increased stress. 【0794】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0795】 In this invention, the server includes means for initializing a database containing information related to generative artificial intelligence and storing said information, means for receiving input from a user and analyzing said input using a natural language processing algorithm, and means for analyzing the user's emotions and generating a response corresponding to those emotions. This enables the server to understand the user's emotions and provide personalized responses based on those emotions. 【0796】 "Generative artificial intelligence" is an artificial intelligence technology that has the ability to generate new data based on input data. 【0797】 A "database" is an information system that systematically stores information and makes it easily accessible when needed. 【0798】 A "natural language processing algorithm" is a set of processing techniques for handling human language using computers. 【0799】 "Emotion analysis" is a technology that identifies emotions and emotional states from user input data. 【0800】 A "response" is the information that the system generates and presents in response to input from the user. 【0801】 "Feedback" refers to reaction information such as evaluations and opinions provided by users. 【0802】 A "learning model" is a computer model that is built to learn specific patterns and rules based on data, enabling it to perform autonomous reasoning and decision-making. 【0803】 This invention is a system that combines generative artificial intelligence technology and emotion recognition technology to identify the emotions of users in care settings and realize personalized communication and support. Specific embodiments are shown below. 【0804】 The server builds a database containing information about generative artificial intelligence. This database serves as a source of information for responding quickly and accurately to user inquiries. The server also uses natural language processing algorithms to analyze and understand user input. 【0805】 Furthermore, the server incorporates an emotion engine to analyze the user's emotions. This engine recognizes the user's emotional state—for example, emotions such as joy, anxiety, and anger—from the input text and audio data. For this purpose, natural language processing libraries such as Google's TensorFlow and IBM's Watson are used. 【0806】 The terminal provides an interface for receiving user input and displays indicators related to emotions. This terminal comprises a wide range of user devices, including personal digital assistants (PDAs) such as smartphones. 【0807】 Users input questions along with emotional information. The server receives this emotional information and generates a response accordingly. The generated response uses friendly and emotionally sensitive language, such as OpenAI's GPT-4, to address the user's feelings. 【0808】 For example, if a user enters information indicating anxiety, such as "I'm not feeling well today," the system can respond with a kind message like, "Please let me know if there's anything I can do to help." 【0809】 An example of a prompt message generated using a generative AI model is one that asks, "What actions can be taken to reassure a user who is showing signs of anxiety?" This allows for appropriate responses that are sensitive to the user's feelings. 【0810】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0811】 Step 1: 【0812】 The device receives voice or text input from the user. The user also inputs an indicator showing their emotional state. The input data includes the user's questions and emotional indicator. 【0813】 Step 2: 【0814】 The server receives input data sent from the terminal and analyzes the question using natural language processing algorithms. Specifically, it uses Google's TensorFlow to tokenize the text and extract context. This process clarifies what the user is asking. 【0815】 Step 3: 【0816】 The server uses an emotion analysis engine to determine the user's emotional state. It analyzes the input text and voice tone to identify emotions such as "anxiety" or "joy." Based on the analysis results, it adjusts the response style. 【0817】 Step 4: 【0818】 The server searches the database for an appropriate answer based on the analyzed question content and emotional state. Depending on the situation, it uses a generative artificial intelligence model (e.g., OpenAI's GPT-4) to generate a response that is most understandable and empathetic to the user. 【0819】 Step 5: 【0820】 The generated response is presented to the user via the terminal. The server adds expressions and examples to the response content that take into account the user's emotional state. For example, reassuring words are used for a user who is showing anxiety. 【0821】 Step 6: 【0822】 Users provide feedback on the responses they receive. The server receives this feedback and updates its learning model. This allows the system to continuously learn to provide more accurate and personalized responses. 【0823】 The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0824】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0825】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0826】 Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0827】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0828】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0829】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0830】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0831】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0832】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0833】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0834】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0835】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0836】 Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12. 【0837】 Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0838】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using this memory. 【0839】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0840】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0841】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0842】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0843】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. 【0844】 The following is further disclosed regarding the embodiments described above. 【0845】 (Claim 1) 【0846】 A means for initializing a database containing information about generative artificial intelligence and storing said information, 【0847】 A natural language processing algorithm means that receives input from a user and analyzes said input, 【0848】 A means for searching for relevant information from the database based on the analyzed input and selecting the most appropriate information, 【0849】 A means for generating and presenting the selected information to the user as a response, 【0850】 A means of obtaining user feedback and updating the learning model, 【0851】 A system that includes this. 【0852】 (Claim 2) 【0853】 The system according to claim 1, wherein the information generated as the response includes visual material. 【0854】 (Claim 3) 【0855】 The system according to claim 1, which analyzes user interaction logs and updates an information database to improve the performance of the system. 【0856】 "Example 1" 【0857】 (Claim 1) 【0858】 A means for initializing a set of knowledge relating to generative artificial intelligence and for holding said knowledge, 【0859】 A natural language processing means that receives inquiries from users and analyzes those inquiries, 【0860】 A means for searching for relevant knowledge from the knowledge set based on the analyzed query and selecting the optimal knowledge, 【0861】 A means of structuring and presenting the selected knowledge as a response to the user, 【0862】 A means of obtaining and analyzing user feedback to improve system performance, 【0863】 A system that includes this. 【0864】 (Claim 2) 【0865】 The system according to claim 1, wherein visual information is added to the knowledge that constitutes the response. 【0866】 (Claim 3) 【0867】 The system according to claim 1, wherein the system evaluates the history of interactions with users and expands the knowledge set in order to improve the efficiency of the system. 【0868】 "Application Example 1" 【0869】 (Claim 1) 【0870】 A means for initializing a database containing information about generative artificial intelligence and storing said information, 【0871】 A natural language processing algorithm means that receives input from a user and analyzes said input, 【0872】 A means for searching for relevant information from the database based on the analyzed input and selecting the most appropriate information, 【0873】 A means for generating and presenting the selected information to the user as a response, 【0874】 A means of supporting user understanding by distributing educational content linked to the generated information, 【0875】 A means of obtaining user feedback and updating the learning model, 【0876】 A system that includes this. 【0877】 (Claim 2) 【0878】 The system according to claim 1, further comprising visual materials in the information generated as the response, and providing interactive teaching materials. 【0879】 (Claim 3) 【0880】 The system according to claim 1, which analyzes user interaction logs, updates an information database to improve the system's performance, and recommends the next learning content. 【0881】 "Example 2 of combining an emotion engine" 【0882】 (Claim 1) 【0883】 A means for initializing a source of information containing information about generative artificial intelligence and storing said information, 【0884】 A natural language processing means that receives data from users and analyzes said data, 【0885】 A means for searching for relevant knowledge from the information source based on the analyzed data and selecting the most appropriate knowledge, 【0886】 A means for generating and presenting the selected knowledge as a response to the user, 【0887】 An emotion recognition means that detects the user's emotions and adjusts the response according to those emotions, 【0888】 A means of obtaining user feedback and updating the learning device, 【0889】 A system that includes this. 【0890】 (Claim 2) 【0891】 The system according to claim 1, wherein the knowledge generated as the response includes visual materials. 【0892】 (Claim 3) 【0893】 The system according to claim 1, which analyzes the history of interactions with users and updates the information source in order to improve the performance of the system. 【0894】 "Application example 2 when combining with an emotional engine" 【0895】 (Claim 1) 【0896】 A means for initializing a database containing information about generative artificial intelligence and storing said information, 【0897】 A natural language processing algorithm means that receives input from a user and analyzes said input, 【0898】 A means for searching for relevant information from the database based on the analyzed input and selecting the most appropriate information, 【0899】 A means for generating and presenting the selected information to the user as a response, 【0900】 A means for analyzing the user's emotions and generating a response corresponding to those emotions, 【0901】 A means of obtaining user feedback and updating the learning model, 【0902】 A system that includes this. 【0903】 (Claim 2) 【0904】 The system according to claim 1, wherein the information generated as the response includes visual materials. 【0905】 (Claim 3) 【0906】 The system according to claim 1, which analyzes user interaction logs and sentiment data and updates the information database to improve the performance of the system. [Explanation of symbols] 【0907】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A means for initializing a database containing information about generative artificial intelligence and storing said information, A natural language processing algorithm means that receives input from a user and analyzes said input, A means for searching for relevant information from the database based on the analyzed input and selecting the most appropriate information, A means for generating and presenting the selected information to the user as a response, A means of obtaining user feedback and updating the learning model, A system that includes this. [Claim 2] The system according to claim 1, wherein the information generated as the response includes visual materials. [Claim 3] The system according to claim 1, which analyzes user interaction logs and updates an information database to improve the performance of the system.

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