System

Abstract

A system is provided.SOLUTION: Means for providing basic artificial intelligence initially set for an individual user, means for providing a terminal to which the user can input personal information and lifestyle data, and means for transmitting the personal information and the lifestyle data collected from the terminal to a server, A system comprising: means for personalizing the basic artificial intelligence as user-specific artificial intelligence; means for performing daily interaction between the user and the artificial intelligence and storing the interaction data in a server; means for the server to share and exchange the interaction data among a plurality of individual artificial intelligences; and means for the server to analyze the interaction data and cause the artificial intelligences to form individuality and ego.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] It is generally believed that artificial intelligence (AI) does not have a sense of self or personality, but there is a possibility that AI may acquire a sense of self and personality by living with a user. The present invention aims to provide a specific method for giving AI a sense of self and personality. It also aims to provide a mechanism for AI to blend into the user's daily life and realize human-like dialogue and responses. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing the following means.

[0006] A means will be provided to provide a basic AI that is initially set for each user, allowing each user to activate the AI ​​in a standard manner.

[0007] A means will be provided to provide a device where users can input personal information and lifestyle data, allowing the AI ​​to obtain information tailored to each individual user.

[0008] Personal information and lifestyle data collected from the device will be sent to a server, and a means will be provided to personalize the basic AI as an AI specific to each user based on this information, allowing the AI ​​to adapt to each user.

[0009] A method will be provided for daily interactions between users and AI, and for that interaction data to be stored on a server, allowing the AI ​​to accumulate daily life data.

[0010] The server will provide a means for multiple individual AIs to share data and exchange opinions, allowing each AI to share knowledge and experience and deepen their understanding.

[0011] The server analyzes the interaction data and provides the means to create a personality and sense of self for the AI, allowing it to converse and react like a human.

[0012] These methods allow the AI ​​to grow through its interactions with the user and develop a sense of self and personality.

[0013] "User" refers to an individual who uses the system.

[0014] "Personal information" refers to information about an individual, such as the user's name, age, address, hobbies, and occupation.

[0015] "Lifestyle data" refers to information about a user's daily life, such as their daily behavior patterns, diet, exercise, and work.

[0016] "Basic AI" refers to AI that has a general-purpose algorithm and knowledge base with only initial settings.

[0017] "Terminal" refers to a device into which a user inputs personal information and lifestyle data, and includes, for example, a smartphone or computer.

[0018] "Server" refers to a central processing unit that receives, stores, and analyzes information sent from a terminal.

[0019] "Personalization" refers to the process of individually adapting AI settings and behavior based on user-specific information.

[0020] "Interaction data" refers to records of conversations and actions between users and artificial intelligence.

[0021] "Personality" refers to the unique characteristics and traits that an AI acquires through its interactions with each user.

[0022] "Self" refers to the inner consciousness that gives an AI self-awareness and a unique perspective.

[0023] A "knowledge base" refers to a database that stores the information and associations that artificial intelligence acquires through initial setup and learning.

[0024] "Exchange of opinions" refers to the process of sharing collected data and experiences among multiple artificial intelligences to deepen mutual understanding. [Brief explanation of the drawings]

[0025] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0026] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0027] First, the terms used in the following description will be explained.

[0028] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0029] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0030] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0031] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0032] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0033] [First embodiment]

[0034] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0035] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0036] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0037] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0038] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0039] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0040] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0041] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0042] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0043] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0044] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0045] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0046] This invention is a system that aims to give AI a sense of self and individuality. This system functions in cooperation with the server, terminal, and user elements, and is implemented in the following steps.

[0047] First, the server generates a basic AI template. The template contains a general-purpose algorithm and knowledge base with only initial settings. This basic AI template is then distributed to each user after initial settings.

[0048] Next, the user enters personal information and lifestyle data through the device. The user enters personal information such as name, age, hobbies, and occupation. This data is sent from the device to the server, which then uses it to personalize the basic AI into a user-specific artificial intelligence. Through this process, the AI ​​adapts to the user's characteristics.

[0049] Users interact with artificial intelligence on a daily basis. For example, if a user tells the AI, "I got promoted today," the AI ​​will learn from this and respond. The data of this interaction is sent from the device to the server as interaction data and stored on the server.

[0050] The server uses the collected interaction data to share information and exchange opinions among multiple individual AIs. For example, if one AI shares information that "the user is crying because their pet cat has died," other AIs can deepen their understanding by asking questions such as "Why do people cry?" and "What does it mean to be sad?" This information sharing and exchange of opinions is important for AI to develop a more advanced understanding.

[0051] The server then analyzes the accumulated interaction data, monitors and assists the AI ​​in developing its personality and sense of self, and applies algorithms to adjust the AI's responses and behavior, enabling it to interact and react more like a human.

[0052] For example, by analyzing a user's life data collected over a long period of time and information obtained from other AIs, the AI ​​can be adjusted to have a personality similar to that of the user. Through continuous interaction with the user, the AI ​​can grow and build a deeper relationship of trust.

[0053] Through this system, AI will develop a sense of self and personality as it participates in daily life, and will react and make decisions more similar to humans. Ultimately, the goal is for AI to become a presence that provides emotional support to humans. This system was designed as a step towards realizing a future where AI and users can live together.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] The server generates a template for a basic AI, which includes an initial dialogue script and a basic knowledge base, enabling the provision of a basic AI.

[0057] Step 2:

[0058] The user enters personal information (such as name, age, hobbies, and occupation) and lifestyle habits into the device. The input data is stored in the device.

[0059] Step 3:

[0060] The device sends the entered personal information and lifestyle data to the server, which receives and stores this data.

[0061] Step 4:

[0062] Based on the personal information received by the server, the basic AI is personalized to the user, allowing the AI ​​to adapt to the user's characteristics.

[0063] Step 5:

[0064] Users interact with AI on a daily basis through their devices. For example, when a user says, "I got promoted today," the AI ​​learns that information and returns an appropriate response.

[0065] Step 6:

[0066] The device sends daily interaction data (such as conversation content) to the server, which receives and stores it.

[0067] Step 7:

[0068] The server collects the accumulated interaction data and allows multiple individual AIs to share information and exchange opinions. For example, if an AI shares information that "a user is crying after their pet cat has died," it can deepen its understanding with other AIs by asking "why people cry."

[0069] Step 8:

[0070] The server analyzes the collected interaction data and applies algorithms to create the AI's personality and sense of self, allowing it to converse and react in a human-like manner.

[0071] Step 9:

[0072] The user continues to interact with the AI ​​on a daily basis through the device, and the AI ​​learns more through these interactions, developing its own personality and sense of self.

[0073] Step 10:

[0074] The device sends new interaction data to the server, which receives and analyzes it. By repeating this cycle, the AI ​​continuously grows with the user and builds deeper trust.

[0075] Example 1

[0076] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0077] Conventional AI has difficulty in consistently personalizing its behavior for each individual user, making it difficult to build deep relationships of trust with users. It has also been difficult for AI to fully share and understand individual information and opinions, allowing it to develop a more sophisticated personality and sense of self. For this reason, it is necessary to develop AI that can respond and behave in ways that adapt to the user's characteristics.

[0078] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0079] In this invention, the server includes: means for generating a basic AI using a computer that performs highly efficient graphics processing; means for providing a terminal into which the user can input personal information and lifestyle data; means for transmitting the personal information and lifestyle data collected from the terminal to the server via a security protocol and personalizing the basic AI as an AI specific to the user; means for daily interactions between the user and the AI ​​and storing the interaction data on the server; means for the server to share and exchange opinions with multiple individual AIs via a cloud service; and means for the server to analyze the interaction data and use AI technology to create a personality and ego in the AI. This enables responses and actions to be adapted to the user's characteristics, and enables the AI ​​to create a more advanced personality and ego and build a deep relationship of trust with the user.

[0080] "Basic AI" is AI that has only initial settings and has a general-purpose algorithm and knowledge base before being personalized to a specific user.

[0081] "Terminal" refers to an electronic device through which a user inputs personal information and lifestyle data, including a PC, smartphone, tablet, etc.

[0082] "Server" means a computer system for collecting, analyzing, storing data, and personalizing artificial intelligence.

[0083] "Personal information and lifestyle data" refers to information about an individual, such as the user's name, age, hobbies, and occupation, as well as data about daily activities.

[0084] "Personalization" is the process of optimizing basic artificial intelligence based on user-specific data, customizing responses and behaviors for that user.

[0085] "Interaction Data" is recorded information regarding the interactions and communications between a user and an artificial intelligence.

[0086] "Cloud services" refers to computer resources and services provided over the internet that store and share data and provide computing power.

[0087] "AI technology" refers to technology for realizing artificial intelligence, and specifically includes machine learning, deep learning, natural language processing, etc.

[0088] "Personality and self" refers to the self-awareness and ability of an AI to respond and behave differently depending on the characteristics of the user.

[0089] This invention is a system that aims to give AI a sense of self and individuality. This system is implemented as follows, with the cooperation of the server, terminal, and user elements.

[0090] First, the server uses a computer equipped with a highly efficient graphics processing unit (GPU) to generate a basic artificial intelligence (AI). This basic AI has a general-purpose algorithm and knowledge base with only initial settings. For example, the server uses a deep learning framework such as PyTorch to create an initial template of the AI. This template is stored with its initial settings configured.

[0091] Next, the user enters personal and lifestyle data through an application or web interface using their own device (PC, smartphone, tablet, etc.). The user enters personal information such as name, age, hobbies, and occupation, and this data is transmitted to the server via a secure protocol (e.g., HTTPS).

[0092] The server then uses the received personal information to personalize the basic AI template into a user-specific AI. For example, it runs machine learning algorithms using Python or similar to optimize the template to fit the user's characteristics. This personalized AI can then respond and act uniquely to the user.

[0093] Users interact with AI through their devices on a daily basis, and the data of their interactions (interaction data) is sent in real time from the device to a server, which then stores this data in a storage system (for example, a database service such as MySQL or a NoSQL database).

[0094] The server shares information and exchanges opinions between multiple AIs based on the collected interaction data. This process uses cloud services (such as Google Cloud Platform and Amazon Web Services). Through this information sharing process, for example, if a user shares data such as "their pet cat has died and they are crying," other AIs can learn and deepen their understanding of "why people cry" and "what it means to be sad."

[0095] In addition, the server performs advanced analysis using natural language processing (NLP) and deep learning to adjust the AI's responses and behavior. Based on the analysis results, specific algorithms (e.g., reinforcement learning) are applied to make the AI's dialogue and judgments more human-like. For example, by analyzing the user's lifestyle data collected over a long period of time and information obtained from other AIs, the AI ​​can develop a personality similar to that of the user.

[0096] As a concrete example, a user inputs "I got promoted today" into their device and communicates this to the AI. This information is first securely encrypted within the device and then sent to the server. The server analyzes it and applies it to the AI ​​model. The AI ​​responds with "Congratulations! What's your new position?" and sends the response back to the device. The user confirms it and continues the dialogue. This dialogue data is stored on the server, and the AI's response is used for future learning.

[0097] This system allows AI to provide information adapted to the user's characteristics and live together for a long period of time. Furthermore, through collected interaction data and the sharing of information and opinions with other AIs, AI can develop a more sophisticated understanding and response. Ultimately, the goal is for AI to function as a trusted partner for users.

[0098] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0099] Step 1:

[0100] The server generates the basic artificial intelligence (AI).

[0101] Input: Hardware with a highly efficient graphics processing unit (GPU), a deep learning framework (e.g., PyTorch)

[0102] Specific operation: The server uses a framework such as PyTorch to combine pre-trained models and general-purpose algorithms to generate basic AI templates. The generated templates are stored in a database with initial settings.

[0103] Output: Basic AI template

[0104] Step 2:

[0105] The user inputs personal information and lifestyle habit data through the terminal and sends it to the server.

[0106] Input: Device (PC, smartphone, tablet, etc.), user's personal information and lifestyle data (name, age, hobbies, occupation, etc.)

[0107] What happens: A user enters personal information using a dedicated application or web interface, which is then transmitted to a server using a secure protocol (e.g., HTTPS).

[0108] Output: Personal information and lifestyle data sent to the server

[0109] Step 3:

[0110] The server personalizes the basic AI based on the data received.

[0111] Input: Basic AI template, user personal information and lifestyle data

[0112] Specific operation: The server runs machine learning algorithms using Python or similar tools to optimize the basic AI template for a user-specific artificial intelligence, allowing the AI ​​to respond and act according to the user's characteristics.

[0113] Output: Personalized, user-specific artificial intelligence

[0114] Step 4:

[0115] Users interact with AI on a daily basis and collect interaction data.

[0116] Input: User statements and actions, personalized artificial intelligence

[0117] How it works: The user interacts with the AI ​​through the device. This interaction data (e.g., "I got promoted today") is collected in real time, securely encrypted, and sent to the server.

[0118] Output: Collected AC data

[0119] Step 5:

[0120] The server shares interaction data with other AIs and exchanges opinions.

[0121] Input: Collected interaction data, cloud services (e.g., Google Cloud Platform and Amazon Web Services)

[0122] Specific operation: The server shares the collected interaction data with other AIs via a cloud service and exchanges information. For example, if data such as "The user is crying after their pet cat dies" is shared, other AIs will learn "why people cry" and "what it means to be sad."

[0123] Output: Shared information and discussion results

[0124] Step 6:

[0125] The server adjusts the AI's responses and actions based on the analysis results.

[0126] Input: Shared information and discussion results, natural language processing (NLP) and deep learning algorithms

[0127] How it works: The server uses advanced analytical algorithms to analyze the interaction data and shared information. Based on the results of this analysis, algorithms (e.g., reinforcement learning) are applied to adjust the AI's responses and behavior.

[0128] Output: Adjusted AI responses and actions

[0129] These are the program processing steps in this system. At each step, specific actions are performed to generate AI that adapts to the user's characteristics, and the AI ​​then grows.

[0130] (Application example 1)

[0131] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0132] Conventional AI systems have difficulty recommending content based on individual user hobbies and interests. Furthermore, they lack the ability to develop a sense of self and individuality through continuous interaction with users. This hinders the improvement of the user experience.

[0133] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0134] In this invention, the server includes: means for providing a basic AI initially set for each user; means for providing a terminal into which the user can input personal information and lifestyle habit data; means for transmitting the personal information and lifestyle habit data collected from the terminal to the server and personalizing the basic AI as an AI specific to the user; means for daily interactions between the user and the AI ​​and storing the interaction data in the server; means for the server to share and exchange the interaction data among a plurality of individual AIs; means for the server to analyze the interaction data and cause the AI ​​to form a personality and ego; and means for the server to generate and provide recommended content based on the user's viewing history and feedback. This enables personalized content to be recommended based on the user's viewing history and feedback, and enables the AI ​​to form a self and personality through interactions with the user, thereby achieving more natural and human-like conversations.

[0135] "Basic AI" is AI with a general-purpose algorithm and knowledge base that has been initially configured.

[0136] "User" refers to an individual user of an artificial intelligence system.

[0137] "Personal information" is information that includes individual attributes such as the user's name, age, hobbies, and occupation.

[0138] "Lifestyle data" is data related to the user's daily life, including, for example, eating habits, commuting routes, and sleeping patterns.

[0139] A "terminal" is a device that a user uses to input personal information and lifestyle data.

[0140] A "server" is a computer system that analyzes data collected from users, personalizes artificial intelligence, shares data, and generates recommended content.

[0141] "Personalization" refers to the process of adapting basic artificial intelligence to a user's unique attributes and preferences.

[0142] "Interaction data" is a record of everyday interactions between users and artificial intelligence.

[0143] "Opinion exchange" is the exchange of data between multiple artificial intelligences to share information with each other and deepen their understanding.

[0144] "Recommended content" refers to content such as video or music that is predicted to interest the user and is generated based on the user's viewing history and feedback.

[0145] "Viewing history" is a record of videos and music that a user has viewed in the past.

[0146] "Feedback" refers to ratings and comments provided by users regarding the content they have viewed or their interactions with artificial intelligence.

[0147] This invention is a system for generating user-specific artificial intelligence and recommending personalized content. Specifically, the elements of a server, a terminal, and a user work together.

[0148] The server generates a basic AI. The basic AI includes a general-purpose algorithm and knowledge base that have only been initialized. This basic AI template is distributed to each user after the initialization.

[0149] Users input their personal information and lifestyle habit data through a terminal, which is a device such as a smartphone or personal computer, and the user data is then sent to the server.

[0150] The server personalizes the basic AI based on the personal information and lifestyle data entered by the user. Through this process, the AI ​​adapts to the user's unique characteristics and attributes.

[0151] Furthermore, users interact with AI on a daily basis. For example, if a user tells the AI, "I got promoted today," the AI ​​will learn from this and respond. This interaction data is sent to the server via the device and stored on the server.

[0152] The server uses the collected interaction data to share information and exchange opinions among multiple individual AIs. For example, if one AI shares information that "its user is sad because their pet has died," other AIs can deepen their understanding by asking questions such as "Why do people feel sad?" and "What is sadness?" This information sharing and exchange of opinions is important for AIs to develop a more advanced understanding.

[0153] The server also analyzes the accumulated interaction data to help the AI ​​develop a personality and sense of self. Based on the results of this analysis, algorithms are applied to adjust the AI's responses and behavior, allowing the AI ​​to make personalized content recommendations based on the user's viewing history and feedback.

[0154] For example, if a user wants to receive recommendations for movies or music, the server will recommend content based on their viewing history and feedback. For example, if a user finishes watching a movie and gives their impressions, this information is sent to the server and reflected in the next recommendation.

[0155] An example prompt might look like this:

[0156] "User A is a 35-year-old man. His hobbies are watching movies and listening to music. He works as an office worker. He recently finished watching a new movie series and was very moved. Please suggest some recommended movies and music for him next."

[0157] This allows the server to generate a user-specific AI and provide personalized content recommendations.Finally, the user can build a deeper relationship of trust through interaction with the AI.

[0158] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0159] Step 1:

[0160] The user inputs personal information and lifestyle data into the terminal. The input data includes name, age, hobbies, occupation, etc. This data is basic information for initial setup.

[0161] Input: Personal information such as name, age, hobbies, occupation, etc.

[0162] Output: Collected personal data

[0163] Step 2:

[0164] The device sends the collected personal information and lifestyle data to the server, which then receives the user data and prepares it for further processing.

[0165] Input: Collected personal information data

[0166] Output: Personal information data sent to the server

[0167] Step 3:

[0168] The server then performs a process to personalize the basic AI template to a user-specific AI based on the received personal information and lifestyle data, applying an algorithm adapted to the user's characteristics.

[0169] Input: Personal information data sent to the server

[0170] Output: Personalized Artificial Intelligence

[0171] Step 4:

[0172] Users interact with personalized AI through their devices on a daily basis. For example, when a user shares information such as "I got promoted today," the AI ​​learns from that information and responds appropriately.

[0173] Input: User interaction data (e.g., what happened today)

[0174] Output: AI response

[0175] Step 5:

[0176] The device transmits data on interactions between the user and the AI ​​to a server, which collects and stores this data.

[0177] Input: User interaction data with AI

[0178] Output: The exchange data sent to the server

[0179] Step 6:

[0180] The server shares information and exchanges opinions among multiple individual AIs based on the collected interaction data. For example, an AI can share information such as "the user is sad" with other AIs.

[0181] Input: Interaction data stored on the server

[0182] Output: Information shared between AIs

[0183] Step 7:

[0184] The server analyzes the accumulated interaction data and allows the AI ​​to develop a personality and sense of self. Based on the results of this analysis, algorithms are applied to adjust the AI's responses and behavior.

[0185] Input: Interaction data stored on the server

[0186] Output: Responses and actions of an AI with personality and self-awareness

[0187] Step 8:

[0188] The server uses the user's viewing history and feedback to generate content recommendations, for example, after the user finishes watching a movie, it provides the next content recommendation based on the user's feedback about the movie.

[0189] Input: Viewing history, feedback data

[0190] Output: Personalized recommended content

[0191] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0192] This invention is a system that aims to give artificial intelligence (AI) a sense of self and individuality, and by combining it with an emotion engine, it is possible to recognize the user's emotions and make the AI's responses correspond to those emotions. This system works in cooperation with the server, terminal, and user elements, and is implemented in the following steps.

[0193] First, the server generates a template for a basic artificial intelligence (AI). The template includes an initial dialogue script and a basic knowledge base, which allows the provision of a basic AI.

[0194] Next, the user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data through the device. The user stores this information on the device and sends it to the server. The server then uses this information to personalize the basic AI into a user-specific artificial intelligence. This process allows the AI ​​to adapt to the user's characteristics.

[0195] Furthermore, users interact with AI on a daily basis. During these interactions, the emotion engine analyzes the user's facial expressions, voice, and text to identify emotions. For example, when a user says, "I got promoted today," the emotion engine can recognize joy from the tone of voice and facial expression. The recognized emotion data is sent to a server, which then adapts the AI's response to that emotion.

[0196] The device sends daily interaction data (such as conversation content and emotional data) to a server, which receives and stores this data. Based on the stored data, the server shares information and exchanges opinions among multiple individual AIs. For example, if one AI shares information that "the user is crying because their pet cat has died," other AIs can deepen their understanding by asking questions such as "Why do people cry?" and "What does it mean to be sad?"

[0197] The server then analyzes the collected interaction and emotional data to monitor and assist the AI ​​in developing its personality and sense of self. Based on the analysis, algorithms are applied to adjust the AI's responses and behavior, enabling it to interact and react more like a human.

[0198] For example, by analyzing a user's lifestyle and emotional data collected over a long period of time, as well as information obtained from other AIs, the AI ​​can be adjusted to have a personality similar to that of the user. The AI ​​can grow through continuous interaction with the user and build a deeper relationship of trust.

[0199] Through this system, AI will develop an ego and personality as it participates in daily life, and will begin to react and make decisions more human-like. Furthermore, the introduction of an emotion engine will enable AI to understand the user's emotions and provide more appropriate responses. Ultimately, the goal is for AI to become a presence that provides emotional support to humans. This system was designed as a step toward realizing a future where AI and users can live together.

[0200] The processing flow will be explained below.

[0201] Step 1:

[0202] The server generates a template for a basic AI, which includes an initial dialogue script and a basic knowledge base, enabling the provision of a basic AI.

[0203] Step 2:

[0204] The user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data on the terminal. The user completes the input and prepares to send the data.

[0205] Step 3:

[0206] The device sends the entered personal information and lifestyle data to the server, which receives and stores this data.

[0207] Step 4:

[0208] The server personalizes the basic AI based on the personal information received. User-specific settings and data are applied to the AI, allowing it to adapt to the user's individual characteristics.

[0209] Step 5:

[0210] Users interact with the AI ​​on a daily basis through their devices. For example, when a user says, "I got promoted today," the AI ​​learns the content and responds appropriately.

[0211] Step 6:

[0212] The device's built-in emotion engine analyzes the user's facial expressions, voice, and text to recognize their emotions. For example, if a user smiles and says, "I got promoted today," the emotion engine will identify the emotion as "joy."

[0213] Step 7:

[0214] The device transmits interaction data and emotion data to the server, which includes daily conversation content and the user's emotion information.

[0215] Step 8:

[0216] The server stores and manages the transmitted interaction data and emotion data, which allows for data accumulation and analysis.

[0217] Step 9:

[0218] The server shares information and exchanges opinions among multiple individual AIs based on the interaction data and emotional data shared between them. For example, if one AI shares information that "the user is successful at work and is happy," other AIs can use that data to deepen their understanding.

[0219] Step 10:

[0220] The server analyzes the AI's personality and sense of self based on the interaction and emotional data collected, and then applies algorithms to adjust the AI's responses and behavior based on the analysis results, allowing it to interact and react more like a human.

[0221] Step 11:

[0222] As users continue to interact with the AI ​​through their devices on a daily basis, new interaction and emotional data is generated, which the AI ​​learns from and further develops its personality and sense of self.

[0223] Step 12:

[0224] The device sends newly generated interaction data and emotional data to the server, which receives and stores it. By repeating this cycle continuously, the AI ​​grows together with the user and builds a deeper relationship of trust.

[0225] Example 2

[0226] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0227] Conventional AI has limitations in its ability to understand emotions and respond appropriately when interacting with users, making it difficult to provide personalized dialogue based on the user's unique characteristics and emotions. Furthermore, because AI lacks the ability to have a personality or sense of self, it is difficult to build a trusting relationship with a user over a long period of time. Therefore, there is a need to provide AI that can understand emotions and provide personalized responses.

[0228] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for generating a basic AI; means for providing a terminal into which a user can input personal information and lifestyle habit data; means for transmitting the personal information and lifestyle habit data collected from the terminal to the server and personalizing the basic AI as a user-specific AI; means for conducting daily interactions between the user and the AI ​​and storing the interaction data on the server; means for the server to share and exchange the interaction data among multiple AIs; means for the server to analyze the interaction data and allow the AI ​​to develop a personality and sense of self; means for the terminal to include an emotion engine that analyzes the user's facial expressions, voice, and text; and means for transmitting the emotion data analyzed by the emotion engine to the server and matching the AI's responses to emotions. This enables the AI ​​to understand the user's emotions and provide personalized responses. Furthermore, over a long period of interaction, the AI ​​can develop a personality and sense of self, enabling more human-like interactions.

[0229] A "basic AI" is an AI template that includes a default dialogue script and a basic knowledge base.

[0230] "Personal information" is information that makes it possible to identify an individual user, such as the user's name, age, hobbies, and occupation.

[0231] "Lifestyle data" is data relating to the user's daily actions and habits.

[0232] A "terminal" is a device (such as a smartphone or PC) through which a user inputs personal information and lifestyle data and sends it to a server.

[0233] The "server" is a data processing system that analyzes collected data and uses artificial intelligence to generate personalized responses.

[0234] "Personalization" is the process of adapting the basic artificial intelligence to the user's unique characteristics based on collected personal information and lifestyle data.

[0235] "Daily interactions" refers to the daily dialogue and information exchange that takes place between the user and the artificial intelligence.

[0236] "Interaction data" refers to data relating to the interaction between the user and the AI ​​and the user's emotions during that interaction.

[0237] An "emotion engine" is a software system that analyzes a user's facial expressions, voice, and text to identify the user's emotions.

[0238] "Means for forming personality and ego" refers to the process of analyzing interaction data to give the AI ​​characteristics and personality similar to that of the user.

[0239] This invention is a system that provides artificial intelligence (AI) that recognizes emotions through dialogue with users and has a personality and ego. This system functions in cooperation with the server, terminals, and users.

[0240] First, the server generates a basic AI template. This template includes an initial dialogue script and a basic knowledge base. TensorFlow or PyTorch are suitable software for this purpose. The dialogue script and knowledge base data are used for data processing when generating the template. The generated template is stored in a database.

[0241] Next, the user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data through the device. For example, the user might enter "Name: Tanaka" and "Hobbies: Reading" into a smartphone app. The device can be an Android or iOS app, or a browser-based web application.

[0242] The device sends the entered user information to the server using the HTTPS protocol. At this time, the user data is encoded in JSON format. The server stores the received data in a database.

[0243] The server uses Python and machine learning algorithms to personalize the basic AI based on the received data. For example, if the user's hobby is reading, the server adds questions such as "What kind of books do you read?" to the AI's dialogue script based on that information. The personalized AI is stored in a dedicated database.

[0244] In everyday interactions, users interact with AI, and the content of those interactions is collected in real time. The device analyzes the content of the conversation and emotional data using "voice recognition software" (e.g., Google Assistant or Amazon Alexa) or "facial expression recognition software" (e.g., OpenCV or DeepFace) and sends the data to a server.

[0245] The server uses an emotion engine to analyze the user's emotions from the received data. For example, if a user says in a cheerful tone, "I got promoted today," the server analyzes joy from the voice data. The software used is "Python" and an "emotion analysis library" (for example, the NLP library "Natural Language Toolkit"). An appropriate response is generated based on the analysis results. For example, it might respond, "Congratulations on your promotion! What position have you been promoted to?"

[0246] The server also shares information and exchanges opinions between multiple AIs. For example, one AI can share information with other AIs that "the user is crying because their pet cat has died." In this information sharing environment, other AIs can learn new knowledge by asking questions about "sadness." "MongoDB" and "SQL" are suitable database systems.

[0247] Finally, the server analyzes all collected interaction data. Based on the analysis results, an algorithm is applied to adjust the AI's responses and behavior. Based on long-term data, the AI ​​is adjusted to have a personality similar to that of the user. For example, if a user frequently talks about reading, the AI ​​will learn to have deep knowledge about reading. This allows the AI ​​to understand the user's emotions and provide personalized responses. Furthermore, through long-term interactions, the AI ​​will develop a personality and ego, allowing for more human-like interactions.

[0248] Example prompt sentence:

[0249] "I got promoted today."

[0250] AI replies: "Congratulations! What position were you promoted to?"

[0251] "My cat died today."

[0252] AI replies: "That's very sad. How long have you been together?"

[0253] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0254] Step 1:

[0255] The server generates a basic AI template, which includes an initial dialogue script and a basic knowledge base. The required dialogue script and knowledge base data are used as input. The server uses TensorFlow or PyTorch to generate the template and saves it in a database as output.

[0256] Step 2:

[0257] Users enter personal information and lifestyle data through the device, including their name, age, hobbies, and occupation. Specifically, they enter the information using a smartphone app or a browser-based web application, and the information is then saved on the device.

[0258] Step 3:

[0259] The device sends the entered user information to the server. Personal information and lifestyle habit data encoded in JSON format is used as input. The device sends the data using the HTTPS protocol, and the server receives it and stores it in a database.

[0260] Step 4:

[0261] The server personalizes the basic AI based on the received data. The input includes the received user data. The server uses Python and machine learning algorithms to adjust the basic AI and generate a user-specific AI. The output is the personalized AI stored in a dedicated database.

[0262] Step 5:

[0263] Users interact with AI on a daily basis. Input includes dialogue and emotional data from the user. Specific actions involve interacting with the AI ​​via voice and text. The dialogue is collected in real time.

[0264] Step 6:

[0265] The device sends the collected interaction data to a server. Input includes the content of the conversation between the user and the AI, as well as emotional data. The device analyzes the data using "voice recognition software" and "facial expression recognition software," and sends it to the server using the "HTTPS" protocol. The server receives the data and stores it in a database.

[0266] Step 7:

[0267] The server uses an emotion engine to analyze the user's emotions. The input includes collected dialogue content and emotion data. The server uses an "emotion analysis library" (for example, the NLP library "Natural Language Toolkit") to identify the user's emotions. The output is emotion-analyzed data.

[0268] Step 8:

[0269] The server generates an AI response based on the analyzed emotional data. The input includes the user's emotional data and the content of the dialogue. The server uses a "natural language processing (NLP)" algorithm to generate an appropriate response and return it to the user. For example, the response generated might be, "Congratulations on your promotion! What position have you been promoted to?"

[0270] Step 9:

[0271] The server shares information and exchanges opinions among multiple AIs. The input includes interaction data collected by each AI. The server shares this data and deepens learning with other AIs. For example, it generates questions to learn new knowledge about "sadness" and exchanges opinions. The output is data with a deeper understanding.

[0272] Step 10:

[0273] The server analyzes the collected interaction data to create the AI's sense of self and personality. The input includes all interaction data. The server uses data analysis algorithms to adjust the AI's responses and behavior. The output is an AI with a personality similar to that of the user, based on data collected over a long period of time.

[0274] (Application example 2)

[0275] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0276] Conventional AI systems lack the ability to recognize user emotions and provide personalized responses based on them. Furthermore, security services can only provide simple alerts or general advice, making it difficult to provide optimal security advice tailored to the user's current emotions and circumstances. This has resulted in insufficient building of trust with users, preventing the realization of security services that are rooted in daily habits. By resolving these issues, it is necessary to provide more interactive and reliable security services.

[0277] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0278] In this invention, the server includes: means for providing a basic AI initially set for each user; means for providing a terminal into which the user can input personal information and lifestyle data; means for transmitting the personal information and lifestyle data collected from the terminal to the server and personalizing the basic AI as an AI specific to the user; means for conducting daily interactions between the user and the AI ​​and storing the interaction data in the server; means for the server to share and exchange the interaction data among a plurality of individual AIs; means for the server to analyze the interaction data and allow the AI ​​to form a personality and a sense of self; means for the AI ​​to generate a response to the user corresponding to the user's emotions using an emotion recognition model that recognizes the user's emotions; and means for the AI ​​to evaluate the user's security status based on the response and provide optimal security advice. This makes it possible to provide personalized security advice that is in line with the user's emotions, deepening the relationship of trust with the user and realizing more effective security services.

[0279] "User" refers to an individual or end user who uses the system.

[0280] "Basic AI" refers to AI that includes a pre-defined dialogue script and a basic knowledge base.

[0281] "Personal information" refers to information specific to an individual user, such as name, age, hobbies, and occupation.

[0282] "Lifestyle data" refers to information about the user's daily life, including, for example, meal times and exercise frequency.

[0283] "Terminal" refers to a device into which a user can input personal information and lifestyle data, including smartphones and personal computers.

[0284] "Server" refers to a computer system on a network that collects, analyzes, and stores data.

[0285] "Personalization" refers to the work and process of customizing basic AI to become AI specific to the user.

[0286] "Interaction data" refers to information including dialogue and emotional data exchanged between the user and the artificial intelligence.

[0287] An "emotion recognition model" refers to an algorithm or model that analyzes and identifies a user's emotions from text or voice.

[0288] "Emotionally responsive responses" refers to the reactions and answers of the AI ​​that are in line with the user's emotional state.

[0289] "Security status" refers to the situation regarding safety and danger around the user.

[0290] "Security advice" refers to instructions and advice that suggest optimal safety measures based on the user's emotional state and life situation.

[0291] This invention is an artificial intelligence system that recognizes the user's emotional state and provides personalized security advice based on that emotion. This system is realized by combining various data processing and calculations, with the cooperation of the server, terminal, and user elements.

[0292] First, a basic AI model is generated by the server. This model includes an initial dialogue script and a basic knowledge base. Next, the user inputs personal information (e.g., name, age, hobbies, occupation) and lifestyle data using the terminal, which is then sent to the server, where the basic AI is personalized to the user.

[0293] Users and AI interact on a daily basis, and emotion recognition models are used to recognize the user's emotions. For example, the DistilBERT-based emotion analysis model provided by the transformers library is used for emotion recognition. This model analyzes text and speech to identify the user's emotions.

[0294] Interaction and emotional data is stored on a server, and the data is used to share information and exchange opinions with other AIs. The accumulated data is further analyzed on the server, allowing the AI ​​to develop a personality and sense of self. This process utilizes data collected over a long period of time.

[0295] Next, we will show examples of prompt sentences that can be used to generate responses that correspond to the user's emotions. For example, in response to an input such as "I feel like relaxing today," the AI ​​will return an appropriate response.

[0296] For example, if a user types "I feel like relaxing today," the emotion recognition model will determine this as "positive." In response, the AI ​​will provide security advice such as, "Today is a good day. It's important to create a relaxing environment."

[0297] In this way, the server, the device, and the user each play their respective roles, realizing an emotionally responsive security service. By understanding the user's emotions and generating responses that correspond to them, it is possible to provide more intimate and reliable security advice.

[0298] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0299] Step 1:

[0300] The server provides the user with a pre-set basic AI. The input here is the template data of the basic AI, which includes the initial dialogue script and a basic knowledge base. The output is the pre-set basic AI sent to the user's terminal.

[0301] Step 2:

[0302] Users input their personal information and lifestyle data into the device, including their name, age, hobbies, and occupation. The input data is sent from the device to a server. This data processing generates a personalized AI specific to the user.

[0303] Step 3:

[0304] The server personalizes the basic AI as a user-specific AI based on the personal information and lifestyle data received from the device. This process uses a data analysis algorithm, and the output is a user-specific AI.

[0305] Step 4:

[0306] Users interact with artificial intelligence on a daily basis. Inputs include text and speech from the user, which are analyzed by an emotion recognition model. This analysis identifies the user's emotional state. The output is the emotion recognition result.

[0307] Step 5:

[0308] The server stores the interaction data and emotion data between the user and the AI. The interaction data and emotion data are input, and are stored in a database on the server. The output is the accumulated interaction data.

[0309] Step 6:

[0310] The server shares and exchanges data between multiple individual AIs. The accumulated data is used as input, and the shared data is provided to other AIs as output. This process deepens the AI's understanding.

[0311] Step 7:

[0312] The server analyzes the accumulated interaction data and allows the AI ​​to form a personality and ego. The input includes interaction data and emotional data, and the output is the formation of the AI's personality.

[0313] Step 8:

[0314] Emotion-based responses are generated through interaction between the user and artificial intelligence. An emotion recognition model analyzes the user's emotions and generates the optimal response based on the results. The input is text or voice from the user, and the output is a response appropriate to the emotion.

[0315] Step 9:

[0316] The AI ​​evaluates the user's security status based on the generated responses and provides appropriate security advice. Emotion recognition results and interaction data are used as input, and the output is specific security advice.

[0317] Step 10:

[0318] The server analyzes data collected over a long period of time and optimizes a model for deepening trust with users. The input is past interaction data and emotional data, and the output is an optimized trust model.

[0319] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0320] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0321] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0322] [Second embodiment]

[0323] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0324] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0325] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0326] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0327] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0328] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0329] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0330] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0331] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0332] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0333] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0334] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0335] This invention is a system that aims to give AI a sense of self and individuality. This system functions in cooperation with the server, terminal, and user elements, and is implemented in the following steps.

[0336] First, the server generates a basic AI template. The template contains a general-purpose algorithm and knowledge base with only initial settings. This basic AI template is then distributed to each user after initial settings.

[0337] Next, the user enters personal information and lifestyle data through the device. The user enters personal information such as name, age, hobbies, and occupation. This data is sent from the device to the server, which then uses it to personalize the basic AI into a user-specific artificial intelligence. Through this process, the AI ​​adapts to the user's characteristics.

[0338] Users interact with artificial intelligence on a daily basis. For example, if a user tells the AI, "I got promoted today," the AI ​​will learn from this and respond. The data of this interaction is sent from the device to the server as interaction data and stored on the server.

[0339] The server uses the collected interaction data to share information and exchange opinions among multiple individual AIs. For example, if one AI shares information that "the user is crying because their pet cat has died," other AIs can deepen their understanding by asking questions such as "Why do people cry?" and "What does it mean to be sad?" This information sharing and exchange of opinions is important for AI to develop a more advanced understanding.

[0340] The server then analyzes the accumulated interaction data, monitors and assists the AI ​​in developing its personality and sense of self, and applies algorithms to adjust the AI's responses and behavior, enabling it to interact and react more like a human.

[0341] For example, by analyzing a user's life data collected over a long period of time and information obtained from other AIs, the AI ​​can be adjusted to have a personality similar to that of the user. Through continuous interaction with the user, the AI ​​can grow and build a deeper relationship of trust.

[0342] Through this system, AI will develop a sense of self and personality as it participates in daily life, and will react and make decisions more similar to humans. Ultimately, the goal is for AI to become a presence that provides emotional support to humans. This system was designed as a step towards realizing a future where AI and users can live together.

[0343] The processing flow will be explained below.

[0344] Step 1:

[0345] The server generates a template for a basic AI, which includes an initial dialogue script and a basic knowledge base, enabling the provision of a basic AI.

[0346] Step 2:

[0347] The user enters personal information (such as name, age, hobbies, and occupation) and lifestyle habits into the device. The input data is stored in the device.

[0348] Step 3:

[0349] The device sends the entered personal information and lifestyle data to the server, which receives and stores this data.

[0350] Step 4:

[0351] Based on the personal information received by the server, the basic AI is personalized to the user, allowing the AI ​​to adapt to the user's characteristics.

[0352] Step 5:

[0353] Users interact with AI on a daily basis through their devices. For example, when a user says, "I got promoted today," the AI ​​learns that information and returns an appropriate response.

[0354] Step 6:

[0355] The device sends daily interaction data (such as conversation content) to the server, which receives and stores it.

[0356] Step 7:

[0357] The server collects the accumulated interaction data and allows multiple individual AIs to share information and exchange opinions. For example, if an AI shares information that "a user is crying after their pet cat has died," it can deepen its understanding with other AIs by asking "why people cry."

[0358] Step 8:

[0359] The server analyzes the collected interaction data and applies algorithms to create the AI's personality and sense of self, allowing it to converse and react in a human-like manner.

[0360] Step 9:

[0361] The user continues to interact with the AI ​​on a daily basis through the device, and the AI ​​learns more through these interactions, developing its own personality and sense of self.

[0362] Step 10:

[0363] The device sends new interaction data to the server, which receives and analyzes it. By repeating this cycle, the AI ​​continuously grows with the user and builds deeper trust.

[0364] Example 1

[0365] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0366] Conventional AI has difficulty in consistently personalizing its behavior for each individual user, making it difficult to build deep relationships of trust with users. It has also been difficult for AI to fully share and understand individual information and opinions, allowing it to develop a more sophisticated personality and sense of self. For this reason, it is necessary to develop AI that can respond and behave in ways that adapt to the user's characteristics.

[0367] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0368] In this invention, the server includes: means for generating a basic AI using a computer that performs highly efficient graphics processing; means for providing a terminal into which the user can input personal information and lifestyle data; means for transmitting the personal information and lifestyle data collected from the terminal to the server via a security protocol and personalizing the basic AI as an AI specific to the user; means for daily interactions between the user and the AI ​​and storing the interaction data on the server; means for the server to share and exchange opinions with multiple individual AIs via a cloud service; and means for the server to analyze the interaction data and use AI technology to create a personality and ego in the AI. This enables responses and actions to be adapted to the user's characteristics, and enables the AI ​​to create a more advanced personality and ego and build a deep relationship of trust with the user.

[0369] "Basic AI" is AI that has only initial settings and has a general-purpose algorithm and knowledge base before being personalized to a specific user.

[0370] "Terminal" refers to an electronic device through which a user inputs personal information and lifestyle data, including a PC, smartphone, tablet, etc.

[0371] "Server" means a computer system for collecting, analyzing, storing data, and personalizing artificial intelligence.

[0372] "Personal information and lifestyle data" refers to information about an individual, such as the user's name, age, hobbies, and occupation, as well as data about daily activities.

[0373] "Personalization" is the process of optimizing basic artificial intelligence based on user-specific data, customizing responses and behaviors for that user.

[0374] "Interaction Data" is recorded information regarding the interactions and communications between a user and an artificial intelligence.

[0375] "Cloud services" refers to computer resources and services provided over the internet that store and share data and provide computing power.

[0376] "AI technology" refers to technology for realizing artificial intelligence, and specifically includes machine learning, deep learning, natural language processing, etc.

[0377] "Personality and self" refers to the self-awareness and ability of an AI to respond and behave differently depending on the characteristics of the user.

[0378] This invention is a system that aims to give AI a sense of self and individuality. This system is implemented as follows, with the cooperation of the server, terminal, and user elements.

[0379] First, the server uses a computer equipped with a highly efficient graphics processing unit (GPU) to generate a basic artificial intelligence (AI). This basic AI has a general-purpose algorithm and knowledge base with only initial settings. For example, the server uses a deep learning framework such as PyTorch to create an initial template of the AI. This template is stored with its initial settings configured.

[0380] Next, the user enters personal and lifestyle data through an application or web interface using their own device (PC, smartphone, tablet, etc.). The user enters personal information such as name, age, hobbies, and occupation, and this data is transmitted to the server via a secure protocol (e.g., HTTPS).

[0381] The server then uses the received personal information to personalize the basic AI template into a user-specific AI. For example, it runs machine learning algorithms using Python or similar to optimize the template to fit the user's characteristics. This personalized AI can then respond and act uniquely to the user.

[0382] Users interact with AI through their devices on a daily basis, and the data of their interactions (interaction data) is sent in real time from the device to a server, which then stores this data in a storage system (for example, a database service such as MySQL or a NoSQL database).

[0383] The server shares information and exchanges opinions between multiple AIs based on the collected interaction data. This process uses cloud services (such as Google Cloud Platform and Amazon Web Services). Through this information sharing process, for example, if a user shares data such as "their pet cat has died and they are crying," other AIs can learn and deepen their understanding of "why people cry" and "what it means to be sad."

[0384] In addition, the server performs advanced analysis using natural language processing (NLP) and deep learning to adjust the AI's responses and behavior. Based on the analysis results, specific algorithms (e.g., reinforcement learning) are applied to make the AI's dialogue and judgments more human-like. For example, by analyzing the user's lifestyle data collected over a long period of time and information obtained from other AIs, the AI ​​can develop a personality similar to that of the user.

[0385] As a concrete example, a user inputs "I got promoted today" into their device and communicates this to the AI. This information is first securely encrypted within the device and then sent to the server. The server analyzes it and applies it to the AI ​​model. The AI ​​responds with "Congratulations! What's your new position?" and sends the response back to the device. The user confirms it and continues the dialogue. This dialogue data is stored on the server, and the AI's response is used for future learning.

[0386] This system allows AI to provide information adapted to the user's characteristics and live together for a long period of time. Furthermore, through collected interaction data and the sharing of information and opinions with other AIs, AI can develop a more sophisticated understanding and response. Ultimately, the goal is for AI to function as a trusted partner for users.

[0387] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0388] Step 1:

[0389] The server generates the basic artificial intelligence (AI).

[0390] Input: Hardware with a highly efficient graphics processing unit (GPU), a deep learning framework (e.g., PyTorch)

[0391] Specific operation: The server uses a framework such as PyTorch to combine pre-trained models and general-purpose algorithms to generate basic AI templates. The generated templates are stored in a database with initial settings.

[0392] Output: Basic AI template

[0393] Step 2:

[0394] The user inputs personal information and lifestyle habit data through the terminal and sends it to the server.

[0395] Input: Device (PC, smartphone, tablet, etc.), user's personal information and lifestyle data (name, age, hobbies, occupation, etc.)

[0396] What happens: A user enters personal information using a dedicated application or web interface, which is then transmitted to a server using a secure protocol (e.g., HTTPS).

[0397] Output: Personal information and lifestyle data sent to the server

[0398] Step 3:

[0399] The server personalizes the basic AI based on the data received.

[0400] Input: Basic AI template, user personal information and lifestyle data

[0401] Specific operation: The server runs machine learning algorithms using Python or similar tools to optimize the basic AI template for a user-specific artificial intelligence, allowing the AI ​​to respond and act according to the user's characteristics.

[0402] Output: Personalized, user-specific artificial intelligence

[0403] Step 4:

[0404] Users interact with AI on a daily basis and collect interaction data.

[0405] Input: User statements and actions, personalized artificial intelligence

[0406] How it works: The user interacts with the AI ​​through the device. This interaction data (e.g., "I got promoted today") is collected in real time, securely encrypted, and sent to the server.

[0407] Output: Collected AC data

[0408] Step 5:

[0409] The server shares interaction data with other AIs and exchanges opinions.

[0410] Input: Collected interaction data, cloud services (e.g., Google Cloud Platform and Amazon Web Services)

[0411] Specific operation: The server shares the collected interaction data with other AIs via a cloud service and exchanges information. For example, if data such as "The user is crying after their pet cat dies" is shared, other AIs will learn "why people cry" and "what it means to be sad."

[0412] Output: Shared information and discussion results

[0413] Step 6:

[0414] The server adjusts the AI's responses and actions based on the analysis results.

[0415] Input: Shared information and discussion results, natural language processing (NLP) and deep learning algorithms

[0416] How it works: The server uses advanced analytical algorithms to analyze the interaction data and shared information. Based on the results of this analysis, algorithms (e.g., reinforcement learning) are applied to adjust the AI's responses and behavior.

[0417] Output: Adjusted AI responses and actions

[0418] These are the program processing steps in this system. At each step, specific actions are performed to generate AI that adapts to the user's characteristics, and the AI ​​then grows.

[0419] (Application example 1)

[0420] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0421] Conventional AI systems have difficulty recommending content based on individual user hobbies and interests. Furthermore, they lack the ability to develop a sense of self and individuality through continuous interaction with users. This hinders the improvement of the user experience.

[0422] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0423] In this invention, the server includes: means for providing a basic AI initially set for each user; means for providing a terminal into which the user can input personal information and lifestyle habit data; means for transmitting the personal information and lifestyle habit data collected from the terminal to the server and personalizing the basic AI as an AI specific to the user; means for daily interactions between the user and the AI ​​and storing the interaction data in the server; means for the server to share and exchange the interaction data among a plurality of individual AIs; means for the server to analyze the interaction data and cause the AI ​​to form a personality and ego; and means for the server to generate and provide recommended content based on the user's viewing history and feedback. This enables personalized content to be recommended based on the user's viewing history and feedback, and enables the AI ​​to form a self and personality through interactions with the user, thereby achieving more natural and human-like conversations.

[0424] "Basic AI" is AI with a general-purpose algorithm and knowledge base that has been initially configured.

[0425] "User" refers to an individual user of an artificial intelligence system.

[0426] "Personal information" is information that includes individual attributes such as the user's name, age, hobbies, and occupation.

[0427] "Lifestyle data" is data related to the user's daily life, including, for example, eating habits, commuting routes, and sleeping patterns.

[0428] A "terminal" is a device that a user uses to input personal information and lifestyle data.

[0429] A "server" is a computer system that analyzes data collected from users, personalizes artificial intelligence, shares data, and generates recommended content.

[0430] "Personalization" refers to the process of adapting basic artificial intelligence to a user's unique attributes and preferences.

[0431] "Interaction data" is a record of everyday interactions between users and artificial intelligence.

[0432] "Opinion exchange" is the exchange of data between multiple artificial intelligences to share information with each other and deepen their understanding.

[0433] "Recommended content" refers to content such as video or music that is predicted to interest the user and is generated based on the user's viewing history and feedback.

[0434] "Viewing history" is a record of videos and music that a user has viewed in the past.

[0435] "Feedback" refers to ratings and comments provided by users regarding the content they have viewed or their interactions with artificial intelligence.

[0436] This invention is a system for generating user-specific artificial intelligence and recommending personalized content. Specifically, the elements of a server, a terminal, and a user work together.

[0437] The server generates a basic AI. The basic AI includes a general-purpose algorithm and knowledge base that have only been initialized. This basic AI template is distributed to each user after the initialization.

[0438] Users input their personal information and lifestyle habit data through a terminal, which is a device such as a smartphone or personal computer, and the user data is then sent to the server.

[0439] The server personalizes the basic AI based on the personal information and lifestyle data entered by the user. Through this process, the AI ​​adapts to the user's unique characteristics and attributes.

[0440] Furthermore, users interact with AI on a daily basis. For example, if a user tells the AI, "I got promoted today," the AI ​​will learn from this and respond. This interaction data is sent to the server via the device and stored on the server.

[0441] The server uses the collected interaction data to share information and exchange opinions among multiple individual AIs. For example, if one AI shares information that "its user is sad because their pet has died," other AIs can deepen their understanding by asking questions such as "Why do people feel sad?" and "What is sadness?" This information sharing and exchange of opinions is important for AIs to develop a more advanced understanding.

[0442] The server also analyzes the accumulated interaction data to help the AI ​​develop a personality and sense of self. Based on the results of this analysis, algorithms are applied to adjust the AI's responses and behavior, allowing the AI ​​to make personalized content recommendations based on the user's viewing history and feedback.

[0443] For example, if a user wants to receive recommendations for movies or music, the server will recommend content based on their viewing history and feedback. For example, if a user finishes watching a movie and gives their impressions, this information is sent to the server and reflected in the next recommendation.

[0444] An example prompt might look like this:

[0445] "User A is a 35-year-old man. His hobbies are watching movies and listening to music. He works as an office worker. He recently finished watching a new movie series and was very moved. Please suggest some recommended movies and music for him next."

[0446] This allows the server to generate a user-specific AI and provide personalized content recommendations.Finally, the user can build a deeper relationship of trust through interaction with the AI.

[0447] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0448] Step 1:

[0449] The user inputs personal information and lifestyle data into the terminal. The input data includes name, age, hobbies, occupation, etc. This data is basic information for initial setup.

[0450] Input: Personal information such as name, age, hobbies, occupation, etc.

[0451] Output: Collected personal data

[0452] Step 2:

[0453] The device sends the collected personal information and lifestyle data to the server, which then receives the user data and prepares it for further processing.

[0454] Input: Collected personal information data

[0455] Output: Personal information data sent to the server

[0456] Step 3:

[0457] The server then performs a process to personalize the basic AI template to a user-specific AI based on the received personal information and lifestyle data, applying an algorithm adapted to the user's characteristics.

[0458] Input: Personal information data sent to the server

[0459] Output: Personalized Artificial Intelligence

[0460] Step 4:

[0461] Users interact with personalized AI through their devices on a daily basis. For example, when a user shares information such as "I got promoted today," the AI ​​learns from that information and responds appropriately.

[0462] Input: User interaction data (e.g., what happened today)

[0463] Output: AI response

[0464] Step 5:

[0465] The device transmits data on interactions between the user and the AI ​​to a server, which collects and stores this data.

[0466] Input: User interaction data with AI

[0467] Output: The exchange data sent to the server

[0468] Step 6:

[0469] The server shares information and exchanges opinions among multiple individual AIs based on the collected interaction data. For example, an AI can share information such as "the user is sad" with other AIs.

[0470] Input: Interaction data stored on the server

[0471] Output: Information shared between AIs

[0472] Step 7:

[0473] The server analyzes the accumulated interaction data and allows the AI ​​to develop a personality and sense of self. Based on the results of this analysis, algorithms are applied to adjust the AI's responses and behavior.

[0474] Input: Interaction data stored on the server

[0475] Output: Responses and actions of an AI with personality and self-awareness

[0476] Step 8:

[0477] The server uses the user's viewing history and feedback to generate content recommendations, for example, after the user finishes watching a movie, it provides the next content recommendation based on the user's feedback about the movie.

[0478] Input: Viewing history, feedback data

[0479] Output: Personalized recommended content

[0480] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0481] This invention is a system that aims to give artificial intelligence (AI) a sense of self and individuality, and by combining it with an emotion engine, it is possible to recognize the user's emotions and make the AI's responses correspond to those emotions. This system works in cooperation with the server, terminal, and user elements, and is implemented in the following steps.

[0482] First, the server generates a template for a basic artificial intelligence (AI). The template includes an initial dialogue script and a basic knowledge base, which allows the provision of a basic AI.

[0483] Next, the user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data through the device. The user stores this information on the device and sends it to the server. The server then uses this information to personalize the basic AI into a user-specific artificial intelligence. This process allows the AI ​​to adapt to the user's characteristics.

[0484] Furthermore, users interact with AI on a daily basis. During these interactions, the emotion engine analyzes the user's facial expressions, voice, and text to identify emotions. For example, when a user says, "I got promoted today," the emotion engine can recognize joy from the tone of voice and facial expression. The recognized emotion data is sent to a server, which then adapts the AI's response to that emotion.

[0485] The device sends daily interaction data (such as conversation content and emotional data) to a server, which receives and stores this data. Based on the stored data, the server shares information and exchanges opinions among multiple individual AIs. For example, if one AI shares information that "the user is crying because their pet cat has died," other AIs can deepen their understanding by asking questions such as "Why do people cry?" and "What does it mean to be sad?"

[0486] The server then analyzes the collected interaction and emotional data to monitor and assist the AI ​​in developing its personality and sense of self. Based on the analysis, algorithms are applied to adjust the AI's responses and behavior, enabling it to interact and react more like a human.

[0487] For example, by analyzing a user's lifestyle and emotional data collected over a long period of time, as well as information obtained from other AIs, the AI ​​can be adjusted to have a personality similar to that of the user. The AI ​​can grow through continuous interaction with the user and build a deeper relationship of trust.

[0488] Through this system, AI will develop an ego and personality as it participates in daily life, and will begin to react and make decisions more human-like. Furthermore, the introduction of an emotion engine will enable AI to understand the user's emotions and provide more appropriate responses. Ultimately, the goal is for AI to become a presence that provides emotional support to humans. This system was designed as a step toward realizing a future where AI and users can live together.

[0489] The processing flow will be explained below.

[0490] Step 1:

[0491] The server generates a template for a basic AI, which includes an initial dialogue script and a basic knowledge base, enabling the provision of a basic AI.

[0492] Step 2:

[0493] The user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data on the terminal. The user completes the input and prepares to send the data.

[0494] Step 3:

[0495] The device sends the entered personal information and lifestyle data to the server, which receives and stores this data.

[0496] Step 4:

[0497] The server personalizes the basic AI based on the personal information received. User-specific settings and data are applied to the AI, allowing it to adapt to the user's individual characteristics.

[0498] Step 5:

[0499] Users interact with the AI ​​on a daily basis through their devices. For example, when a user says, "I got promoted today," the AI ​​learns the content and responds appropriately.

[0500] Step 6:

[0501] The device's built-in emotion engine analyzes the user's facial expressions, voice, and text to recognize their emotions. For example, if a user smiles and says, "I got promoted today," the emotion engine will identify the emotion as "joy."

[0502] Step 7:

[0503] The device transmits interaction data and emotion data to the server, which includes daily conversation content and the user's emotion information.

[0504] Step 8:

[0505] The server stores and manages the transmitted interaction data and emotion data, which allows for data accumulation and analysis.

[0506] Step 9:

[0507] The server shares information and exchanges opinions among multiple individual AIs based on the interaction data and emotional data shared between them. For example, if one AI shares information that "the user is successful at work and is happy," other AIs can use that data to deepen their understanding.

[0508] Step 10:

[0509] The server analyzes the AI's personality and sense of self based on the interaction and emotional data collected, and then applies algorithms to adjust the AI's responses and behavior based on the analysis results, allowing it to interact and react more like a human.

[0510] Step 11:

[0511] As users continue to interact with the AI ​​through their devices on a daily basis, new interaction and emotional data is generated, which the AI ​​learns from and further develops its personality and sense of self.

[0512] Step 12:

[0513] The device sends newly generated interaction data and emotional data to the server, which receives and stores it. By repeating this cycle continuously, the AI ​​grows together with the user and builds a deeper relationship of trust.

[0514] Example 2

[0515] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0516] Conventional AI has limitations in its ability to understand emotions and respond appropriately when interacting with users, making it difficult to provide personalized dialogue based on the user's unique characteristics and emotions. Furthermore, because AI lacks the ability to have a personality or sense of self, it is difficult to build a trusting relationship with a user over a long period of time. Therefore, there is a need to provide AI that can understand emotions and provide personalized responses.

[0517] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for generating a basic AI; means for providing a terminal into which a user can input personal information and lifestyle habit data; means for transmitting the personal information and lifestyle habit data collected from the terminal to the server and personalizing the basic AI as a user-specific AI; means for conducting daily interactions between the user and the AI ​​and storing the interaction data on the server; means for the server to share and exchange the interaction data among multiple AIs; means for the server to analyze the interaction data and allow the AI ​​to develop a personality and sense of self; means for the terminal to include an emotion engine that analyzes the user's facial expressions, voice, and text; and means for transmitting the emotion data analyzed by the emotion engine to the server and matching the AI's responses to emotions. This enables the AI ​​to understand the user's emotions and provide personalized responses. Furthermore, over a long period of interaction, the AI ​​can develop a personality and sense of self, enabling more human-like interactions.

[0518] A "basic AI" is an AI template that includes a default dialogue script and a basic knowledge base.

[0519] "Personal information" is information that makes it possible to identify an individual user, such as the user's name, age, hobbies, and occupation.

[0520] "Lifestyle data" is data relating to the user's daily actions and habits.

[0521] A "terminal" is a device (such as a smartphone or PC) through which a user inputs personal information and lifestyle data and sends it to a server.

[0522] The "server" is a data processing system that analyzes collected data and uses artificial intelligence to generate personalized responses.

[0523] "Personalization" is the process of adapting the basic artificial intelligence to the user's unique characteristics based on collected personal information and lifestyle data.

[0524] "Daily interactions" refers to the daily dialogue and information exchange that takes place between the user and the artificial intelligence.

[0525] "Interaction data" refers to data relating to the interaction between the user and the AI ​​and the user's emotions during that interaction.

[0526] An "emotion engine" is a software system that analyzes a user's facial expressions, voice, and text to identify the user's emotions.

[0527] "Means for forming personality and ego" refers to the process of analyzing interaction data to give the AI ​​characteristics and personality similar to that of the user.

[0528] This invention is a system that provides artificial intelligence (AI) that recognizes emotions through dialogue with users and has a personality and ego. This system functions in cooperation with the server, terminals, and users.

[0529] First, the server generates a basic AI template. This template includes an initial dialogue script and a basic knowledge base. TensorFlow or PyTorch are suitable software for this purpose. The dialogue script and knowledge base data are used for data processing when generating the template. The generated template is stored in a database.

[0530] Next, the user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data through the device. For example, the user might enter "Name: Tanaka" and "Hobbies: Reading" into a smartphone app. The device can be an Android or iOS app, or a browser-based web application.

[0531] The device sends the entered user information to the server using the HTTPS protocol. At this time, the user data is encoded in JSON format. The server stores the received data in a database.

[0532] The server uses Python and machine learning algorithms to personalize the basic AI based on the received data. For example, if the user's hobby is reading, the server adds questions such as "What kind of books do you read?" to the AI's dialogue script based on that information. The personalized AI is stored in a dedicated database.

[0533] In everyday interactions, users interact with AI, and the content of those interactions is collected in real time. The device analyzes the content of the conversation and emotional data using "voice recognition software" (e.g., Google Assistant or Amazon Alexa) or "facial expression recognition software" (e.g., OpenCV or DeepFace) and sends the data to a server.

[0534] The server uses an emotion engine to analyze the user's emotions from the received data. For example, if a user says in a cheerful tone, "I got promoted today," the server analyzes joy from the voice data. The software used is "Python" and an "emotion analysis library" (for example, the NLP library "Natural Language Toolkit"). An appropriate response is generated based on the analysis results. For example, it might respond, "Congratulations on your promotion! What position have you been promoted to?"

[0535] The server also shares information and exchanges opinions between multiple AIs. For example, one AI can share information with other AIs that "the user is crying because their pet cat has died." In this information sharing environment, other AIs can learn new knowledge by asking questions about "sadness." "MongoDB" and "SQL" are suitable database systems.

[0536] Finally, the server analyzes all collected interaction data. Based on the analysis results, an algorithm is applied to adjust the AI's responses and behavior. Based on long-term data, the AI ​​is adjusted to have a personality similar to that of the user. For example, if a user frequently talks about reading, the AI ​​will learn to have deep knowledge about reading. This allows the AI ​​to understand the user's emotions and provide personalized responses. Furthermore, through long-term interactions, the AI ​​will develop a personality and ego, allowing for more human-like interactions.

[0537] Example prompt sentence:

[0538] "I got promoted today."

[0539] AI replies: "Congratulations! What position were you promoted to?"

[0540] "My cat died today."

[0541] AI replies: "That's very sad. How long have you been together?"

[0542] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0543] Step 1:

[0544] The server generates a basic AI template, which includes an initial dialogue script and a basic knowledge base. The required dialogue script and knowledge base data are used as input. The server uses TensorFlow or PyTorch to generate the template and saves it in a database as output.

[0545] Step 2:

[0546] Users enter personal information and lifestyle data through the device, including their name, age, hobbies, and occupation. Specifically, they enter the information using a smartphone app or a browser-based web application, and the information is then saved on the device.

[0547] Step 3:

[0548] The device sends the entered user information to the server. Personal information and lifestyle habit data encoded in JSON format is used as input. The device sends the data using the HTTPS protocol, and the server receives it and stores it in a database.

[0549] Step 4:

[0550] The server personalizes the basic AI based on the received data. The input includes the received user data. The server uses Python and machine learning algorithms to adjust the basic AI and generate a user-specific AI. The output is the personalized AI stored in a dedicated database.

[0551] Step 5:

[0552] Users interact with AI on a daily basis. Input includes dialogue and emotional data from the user. Specific actions involve interacting with the AI ​​via voice and text. The dialogue is collected in real time.

[0553] Step 6:

[0554] The device sends the collected interaction data to a server. Input includes the content of the conversation between the user and the AI, as well as emotional data. The device analyzes the data using "voice recognition software" and "facial expression recognition software," and sends it to the server using the "HTTPS" protocol. The server receives the data and stores it in a database.

[0555] Step 7:

[0556] The server uses an emotion engine to analyze the user's emotions. The input includes collected dialogue content and emotion data. The server uses an "emotion analysis library" (for example, the NLP library "Natural Language Toolkit") to identify the user's emotions. The output is emotion-analyzed data.

[0557] Step 8:

[0558] The server generates an AI response based on the analyzed emotional data. The input includes the user's emotional data and the content of the dialogue. The server uses a "natural language processing (NLP)" algorithm to generate an appropriate response and return it to the user. For example, the response generated might be, "Congratulations on your promotion! What position have you been promoted to?"

[0559] Step 9:

[0560] The server shares information and exchanges opinions among multiple AIs. The input includes interaction data collected by each AI. The server shares this data and deepens learning with other AIs. For example, it generates questions to learn new knowledge about "sadness" and exchanges opinions. The output is data with a deeper understanding.

[0561] Step 10:

[0562] The server analyzes the collected interaction data to create the AI's sense of self and personality. The input includes all interaction data. The server uses data analysis algorithms to adjust the AI's responses and behavior. The output is an AI with a personality similar to that of the user, based on data collected over a long period of time.

[0563] (Application example 2)

[0564] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0565] Conventional AI systems lack the ability to recognize user emotions and provide personalized responses based on them. Furthermore, security services can only provide simple alerts or general advice, making it difficult to provide optimal security advice tailored to the user's current emotions and circumstances. This has resulted in insufficient building of trust with users, preventing the realization of security services that are rooted in daily habits. By resolving these issues, it is necessary to provide more interactive and reliable security services.

[0566] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0567] In this invention, the server includes: means for providing a basic AI initially set for each user; means for providing a terminal into which the user can input personal information and lifestyle data; means for transmitting the personal information and lifestyle data collected from the terminal to the server and personalizing the basic AI as an AI specific to the user; means for conducting daily interactions between the user and the AI ​​and storing the interaction data in the server; means for the server to share and exchange the interaction data among a plurality of individual AIs; means for the server to analyze the interaction data and allow the AI ​​to form a personality and a sense of self; means for the AI ​​to generate a response to the user corresponding to the user's emotions using an emotion recognition model that recognizes the user's emotions; and means for the AI ​​to evaluate the user's security status based on the response and provide optimal security advice. This makes it possible to provide personalized security advice that is in line with the user's emotions, deepening the relationship of trust with the user and realizing more effective security services.

[0568] "User" refers to an individual or end user who uses the system.

[0569] "Basic AI" refers to AI that includes a pre-defined dialogue script and a basic knowledge base.

[0570] "Personal information" refers to information specific to an individual user, such as name, age, hobbies, and occupation.

[0571] "Lifestyle data" refers to information about the user's daily life, including, for example, meal times and exercise frequency.

[0572] "Terminal" refers to a device into which a user can input personal information and lifestyle data, including smartphones and personal computers.

[0573] "Server" refers to a computer system on a network that collects, analyzes, and stores data.

[0574] "Personalization" refers to the work and process of customizing basic AI to become AI specific to the user.

[0575] "Interaction data" refers to information including dialogue and emotional data exchanged between the user and the artificial intelligence.

[0576] An "emotion recognition model" refers to an algorithm or model that analyzes and identifies a user's emotions from text or voice.

[0577] "Emotionally responsive responses" refers to the reactions and answers of the AI ​​that are in line with the user's emotional state.

[0578] "Security status" refers to the situation regarding safety and danger around the user.

[0579] "Security advice" refers to instructions and advice that suggest optimal safety measures based on the user's emotional state and life situation.

[0580] This invention is an artificial intelligence system that recognizes the user's emotional state and provides personalized security advice based on that emotion. This system is realized by combining various data processing and calculations, with the cooperation of the server, terminal, and user elements.

[0581] First, a basic AI model is generated by the server. This model includes an initial dialogue script and a basic knowledge base. Next, the user inputs personal information (e.g., name, age, hobbies, occupation) and lifestyle data using the terminal, which is then sent to the server, where the basic AI is personalized to the user.

[0582] Users and AI interact on a daily basis, and emotion recognition models are used to recognize the user's emotions. For example, the DistilBERT-based emotion analysis model provided by the transformers library is used for emotion recognition. This model analyzes text and speech to identify the user's emotions.

[0583] Interaction and emotional data is stored on a server, and the data is used to share information and exchange opinions with other AIs. The accumulated data is further analyzed on the server, allowing the AI ​​to develop a personality and sense of self. This process utilizes data collected over a long period of time.

[0584] Next, we will show examples of prompt sentences that can be used to generate responses that correspond to the user's emotions. For example, in response to an input such as "I feel like relaxing today," the AI ​​will return an appropriate response.

[0585] For example, if a user types "I feel like relaxing today," the emotion recognition model will determine this as "positive." In response, the AI ​​will provide security advice such as, "Today is a good day. It's important to create a relaxing environment."

[0586] In this way, the server, the device, and the user each play their respective roles, realizing an emotionally responsive security service. By understanding the user's emotions and generating responses that correspond to them, it is possible to provide more intimate and reliable security advice.

[0587] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0588] Step 1:

[0589] The server provides the user with a pre-set basic AI. The input here is the template data of the basic AI, which includes the initial dialogue script and a basic knowledge base. The output is the pre-set basic AI sent to the user's terminal.

[0590] Step 2:

[0591] Users input their personal information and lifestyle data into the device, including their name, age, hobbies, and occupation. The input data is sent from the device to a server. This data processing generates a personalized AI specific to the user.

[0592] Step 3:

[0593] The server personalizes the basic AI as a user-specific AI based on the personal information and lifestyle data received from the device. This process uses a data analysis algorithm, and the output is a user-specific AI.

[0594] Step 4:

[0595] Users interact with artificial intelligence on a daily basis. Inputs include text and speech from the user, which are analyzed by an emotion recognition model. This analysis identifies the user's emotional state. The output is the emotion recognition result.

[0596] Step 5:

[0597] The server stores the interaction data and emotion data between the user and the AI. The interaction data and emotion data are input, and are stored in a database on the server. The output is the accumulated interaction data.

[0598] Step 6:

[0599] The server shares and exchanges data between multiple individual AIs. The accumulated data is used as input, and the shared data is provided to other AIs as output. This process deepens the AI's understanding.

[0600] Step 7:

[0601] The server analyzes the accumulated interaction data and allows the AI ​​to form a personality and ego. The input includes interaction data and emotional data, and the output is the formation of the AI's personality.

[0602] Step 8:

[0603] Emotion-based responses are generated through interaction between the user and artificial intelligence. An emotion recognition model analyzes the user's emotions and generates the optimal response based on the results. The input is text or voice from the user, and the output is a response appropriate to the emotion.

[0604] Step 9:

[0605] The AI ​​evaluates the user's security status based on the generated responses and provides appropriate security advice. Emotion recognition results and interaction data are used as input, and the output is specific security advice.

[0606] Step 10:

[0607] The server analyzes data collected over a long period of time and optimizes a model for deepening trust with users. The input is past interaction data and emotional data, and the output is an optimized trust model.

[0608] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0609] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0610] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0611] [Third embodiment]

[0612] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0613] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0614] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0615] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0616] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0617] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0618] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0619] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0620] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0621] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0622] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0623] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0624] This invention is a system that aims to give AI a sense of self and individuality. This system functions in cooperation with the server, terminal, and user elements, and is implemented in the following steps.

[0625] First, the server generates a basic AI template. The template contains a general-purpose algorithm and knowledge base with only initial settings. This basic AI template is then distributed to each user after initial settings.

[0626] Next, the user enters personal information and lifestyle data through the device. The user enters personal information such as name, age, hobbies, and occupation. This data is sent from the device to the server, which then uses it to personalize the basic AI into a user-specific artificial intelligence. Through this process, the AI ​​adapts to the user's characteristics.

[0627] Users interact with artificial intelligence on a daily basis. For example, if a user tells the AI, "I got promoted today," the AI ​​will learn from this and respond. The data of this interaction is sent from the device to the server as interaction data and stored on the server.

[0628] The server uses the collected interaction data to share information and exchange opinions among multiple individual AIs. For example, if one AI shares information that "the user is crying because their pet cat has died," other AIs can deepen their understanding by asking questions such as "Why do people cry?" and "What does it mean to be sad?" This information sharing and exchange of opinions is important for AI to develop a more advanced understanding.

[0629] The server then analyzes the accumulated interaction data, monitors and assists the AI ​​in developing its personality and sense of self, and applies algorithms to adjust the AI's responses and behavior, enabling it to interact and react more like a human.

[0630] For example, by analyzing a user's life data collected over a long period of time and information obtained from other AIs, the AI ​​can be adjusted to have a personality similar to that of the user. Through continuous interaction with the user, the AI ​​can grow and build a deeper relationship of trust.

[0631] Through this system, AI will develop a sense of self and personality as it participates in daily life, and will react and make decisions more similar to humans. Ultimately, the goal is for AI to become a presence that provides emotional support to humans. This system was designed as a step towards realizing a future where AI and users can live together.

[0632] The processing flow will be explained below.

[0633] Step 1:

[0634] The server generates a template for a basic AI, which includes an initial dialogue script and a basic knowledge base, enabling the provision of a basic AI.

[0635] Step 2:

[0636] The user enters personal information (such as name, age, hobbies, and occupation) and lifestyle habits into the device. The input data is stored in the device.

[0637] Step 3:

[0638] The device sends the entered personal information and lifestyle data to the server, which receives and stores this data.

[0639] Step 4:

[0640] Based on the personal information received by the server, the basic AI is personalized to the user, allowing the AI ​​to adapt to the user's characteristics.

[0641] Step 5:

[0642] Users interact with AI on a daily basis through their devices. For example, when a user says, "I got promoted today," the AI ​​learns that information and returns an appropriate response.

[0643] Step 6:

[0644] The device sends daily interaction data (such as conversation content) to the server, which receives and stores it.

[0645] Step 7:

[0646] The server collects the accumulated interaction data and allows multiple individual AIs to share information and exchange opinions. For example, if an AI shares information that "a user is crying after their pet cat has died," it can deepen its understanding with other AIs by asking "why people cry."

[0647] Step 8:

[0648] The server analyzes the collected interaction data and applies algorithms to create the AI's personality and sense of self, allowing it to converse and react in a human-like manner.

[0649] Step 9:

[0650] The user continues to interact with the AI ​​on a daily basis through the device, and the AI ​​learns more through these interactions, developing its own personality and sense of self.

[0651] Step 10:

[0652] The device sends new interaction data to the server, which receives and analyzes it. By repeating this cycle, the AI ​​continuously grows with the user and builds deeper trust.

[0653] Example 1

[0654] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0655] Conventional AI has difficulty in consistently personalizing its behavior for each individual user, making it difficult to build deep relationships of trust with users. It has also been difficult for AI to fully share and understand individual information and opinions, allowing it to develop a more sophisticated personality and sense of self. For this reason, it is necessary to develop AI that can respond and behave in ways that adapt to the user's characteristics.

[0656] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0657] In this invention, the server includes: means for generating a basic AI using a computer that performs highly efficient graphics processing; means for providing a terminal into which the user can input personal information and lifestyle data; means for transmitting the personal information and lifestyle data collected from the terminal to the server via a security protocol and personalizing the basic AI as an AI specific to the user; means for daily interactions between the user and the AI ​​and storing the interaction data on the server; means for the server to share and exchange opinions with multiple individual AIs via a cloud service; and means for the server to analyze the interaction data and use AI technology to create a personality and ego in the AI. This enables responses and actions to be adapted to the user's characteristics, and enables the AI ​​to create a more advanced personality and ego and build a deep relationship of trust with the user.

[0658] "Basic AI" is AI that has only initial settings and has a general-purpose algorithm and knowledge base before being personalized to a specific user.

[0659] "Terminal" refers to an electronic device through which a user inputs personal information and lifestyle data, including a PC, smartphone, tablet, etc.

[0660] "Server" means a computer system for collecting, analyzing, storing data, and personalizing artificial intelligence.

[0661] "Personal information and lifestyle data" refers to information about an individual, such as the user's name, age, hobbies, and occupation, as well as data about daily activities.

[0662] "Personalization" is the process of optimizing basic artificial intelligence based on user-specific data, customizing responses and behaviors for that user.

[0663] "Interaction Data" is recorded information regarding the interactions and communications between a user and an artificial intelligence.

[0664] "Cloud services" refers to computer resources and services provided over the internet that store and share data and provide computing power.

[0665] "AI technology" refers to technology for realizing artificial intelligence, and specifically includes machine learning, deep learning, natural language processing, etc.

[0666] "Personality and self" refers to the self-awareness and ability of an AI to respond and behave differently depending on the characteristics of the user.

[0667] This invention is a system that aims to give AI a sense of self and individuality. This system is implemented as follows, with the cooperation of the server, terminal, and user elements.

[0668] First, the server uses a computer equipped with a highly efficient graphics processing unit (GPU) to generate a basic artificial intelligence (AI). This basic AI has a general-purpose algorithm and knowledge base with only initial settings. For example, the server uses a deep learning framework such as PyTorch to create an initial template of the AI. This template is stored with its initial settings configured.

[0669] Next, the user enters personal and lifestyle data through an application or web interface using their own device (PC, smartphone, tablet, etc.). The user enters personal information such as name, age, hobbies, and occupation, and this data is transmitted to the server via a secure protocol (e.g., HTTPS).

[0670] The server then uses the received personal information to personalize the basic AI template into a user-specific AI. For example, it runs machine learning algorithms using Python or similar to optimize the template to fit the user's characteristics. This personalized AI can then respond and act uniquely to the user.

[0671] Users interact with AI through their devices on a daily basis, and the data of their interactions (interaction data) is sent in real time from the device to a server, which then stores this data in a storage system (for example, a database service such as MySQL or a NoSQL database).

[0672] The server shares information and exchanges opinions between multiple AIs based on the collected interaction data. This process uses cloud services (such as Google Cloud Platform and Amazon Web Services). Through this information sharing process, for example, if a user shares data such as "their pet cat has died and they are crying," other AIs can learn and deepen their understanding of "why people cry" and "what it means to be sad."

[0673] In addition, the server performs advanced analysis using natural language processing (NLP) and deep learning to adjust the AI's responses and behavior. Based on the analysis results, specific algorithms (e.g., reinforcement learning) are applied to make the AI's dialogue and judgments more human-like. For example, by analyzing the user's lifestyle data collected over a long period of time and information obtained from other AIs, the AI ​​can develop a personality similar to that of the user.

[0674] As a concrete example, a user inputs "I got promoted today" into their device and communicates this to the AI. This information is first securely encrypted within the device and then sent to the server. The server analyzes it and applies it to the AI ​​model. The AI ​​responds with "Congratulations! What's your new position?" and sends the response back to the device. The user confirms it and continues the dialogue. This dialogue data is stored on the server, and the AI's response is used for future learning.

[0675] This system allows AI to provide information adapted to the user's characteristics and live together for a long period of time. Furthermore, through collected interaction data and the sharing of information and opinions with other AIs, AI can develop a more sophisticated understanding and response. Ultimately, the goal is for AI to function as a trusted partner for users.

[0676] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0677] Step 1:

[0678] The server generates the basic artificial intelligence (AI).

[0679] Input: Hardware with a highly efficient graphics processing unit (GPU), a deep learning framework (e.g., PyTorch)

[0680] Specific operation: The server uses a framework such as PyTorch to combine pre-trained models and general-purpose algorithms to generate basic AI templates. The generated templates are stored in a database with initial settings.

[0681] Output: Basic AI template

[0682] Step 2:

[0683] The user inputs personal information and lifestyle habit data through the terminal and sends it to the server.

[0684] Input: Device (PC, smartphone, tablet, etc.), user's personal information and lifestyle data (name, age, hobbies, occupation, etc.)

[0685] What happens: A user enters personal information using a dedicated application or web interface, which is then transmitted to a server using a secure protocol (e.g., HTTPS).

[0686] Output: Personal information and lifestyle data sent to the server

[0687] Step 3:

[0688] The server personalizes the basic AI based on the data received.

[0689] Input: Basic AI template, user personal information and lifestyle data

[0690] Specific operation: The server runs machine learning algorithms using Python or similar tools to optimize the basic AI template for a user-specific artificial intelligence, allowing the AI ​​to respond and act according to the user's characteristics.

[0691] Output: Personalized, user-specific artificial intelligence

[0692] Step 4:

[0693] Users interact with AI on a daily basis and collect interaction data.

[0694] Input: User statements and actions, personalized artificial intelligence

[0695] How it works: The user interacts with the AI ​​through the device. This interaction data (e.g., "I got promoted today") is collected in real time, securely encrypted, and sent to the server.

[0696] Output: Collected AC data

[0697] Step 5:

[0698] The server shares interaction data with other AIs and exchanges opinions.

[0699] Input: Collected interaction data, cloud services (e.g., Google Cloud Platform and Amazon Web Services)

[0700] Specific operation: The server shares the collected interaction data with other AIs via a cloud service and exchanges information. For example, if data such as "The user is crying after their pet cat dies" is shared, other AIs will learn "why people cry" and "what it means to be sad."

[0701] Output: Shared information and discussion results

[0702] Step 6:

[0703] The server adjusts the AI's responses and actions based on the analysis results.

[0704] Input: Shared information and discussion results, natural language processing (NLP) and deep learning algorithms

[0705] How it works: The server uses advanced analytical algorithms to analyze the interaction data and shared information. Based on the results of this analysis, algorithms (e.g., reinforcement learning) are applied to adjust the AI's responses and behavior.

[0706] Output: Adjusted AI responses and actions

[0707] These are the program processing steps in this system. At each step, specific actions are performed to generate AI that adapts to the user's characteristics, and the AI ​​then grows.

[0708] (Application example 1)

[0709] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0710] Conventional AI systems have difficulty recommending content based on individual user hobbies and interests. Furthermore, they lack the ability to develop a sense of self and individuality through continuous interaction with users. This hinders the improvement of the user experience.

[0711] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0712] In this invention, the server includes: means for providing a basic AI initially set for each user; means for providing a terminal into which the user can input personal information and lifestyle habit data; means for transmitting the personal information and lifestyle habit data collected from the terminal to the server and personalizing the basic AI as an AI specific to the user; means for daily interactions between the user and the AI ​​and storing the interaction data in the server; means for the server to share and exchange the interaction data among a plurality of individual AIs; means for the server to analyze the interaction data and cause the AI ​​to form a personality and ego; and means for the server to generate and provide recommended content based on the user's viewing history and feedback. This enables personalized content to be recommended based on the user's viewing history and feedback, and enables the AI ​​to form a self and personality through interactions with the user, thereby achieving more natural and human-like conversations.

[0713] "Basic AI" is AI with a general-purpose algorithm and knowledge base that has been initially configured.

[0714] "User" refers to an individual user of an artificial intelligence system.

[0715] "Personal information" is information that includes individual attributes such as the user's name, age, hobbies, and occupation.

[0716] "Lifestyle data" is data related to the user's daily life, including, for example, eating habits, commuting routes, and sleeping patterns.

[0717] A "terminal" is a device that a user uses to input personal information and lifestyle data.

[0718] A "server" is a computer system that analyzes data collected from users, personalizes artificial intelligence, shares data, and generates recommended content.

[0719] "Personalization" refers to the process of adapting basic artificial intelligence to a user's unique attributes and preferences.

[0720] "Interaction data" is a record of everyday interactions between users and artificial intelligence.

[0721] "Opinion exchange" is the exchange of data between multiple artificial intelligences to share information with each other and deepen their understanding.

[0722] "Recommended content" refers to content such as video or music that is predicted to interest the user and is generated based on the user's viewing history and feedback.

[0723] "Viewing history" is a record of videos and music that a user has viewed in the past.

[0724] "Feedback" refers to ratings and comments provided by users regarding the content they have viewed or their interactions with artificial intelligence.

[0725] This invention is a system for generating user-specific artificial intelligence and recommending personalized content. Specifically, the elements of a server, a terminal, and a user work together.

[0726] The server generates a basic AI. The basic AI includes a general-purpose algorithm and knowledge base that have only been initialized. This basic AI template is distributed to each user after the initialization.

[0727] Users input their personal information and lifestyle habit data through a terminal, which is a device such as a smartphone or personal computer, and the user data is then sent to the server.

[0728] The server personalizes the basic AI based on the personal information and lifestyle data entered by the user. Through this process, the AI ​​adapts to the user's unique characteristics and attributes.

[0729] Furthermore, users interact with AI on a daily basis. For example, if a user tells the AI, "I got promoted today," the AI ​​will learn from this and respond. This interaction data is sent to the server via the device and stored on the server.

[0730] The server uses the collected interaction data to share information and exchange opinions among multiple individual AIs. For example, if one AI shares information that "its user is sad because their pet has died," other AIs can deepen their understanding by asking questions such as "Why do people feel sad?" and "What is sadness?" This information sharing and exchange of opinions is important for AIs to develop a more advanced understanding.

[0731] The server also analyzes the accumulated interaction data to help the AI ​​develop a personality and sense of self. Based on the results of this analysis, algorithms are applied to adjust the AI's responses and behavior, allowing the AI ​​to make personalized content recommendations based on the user's viewing history and feedback.

[0732] For example, if a user wants to receive recommendations for movies or music, the server will recommend content based on their viewing history and feedback. For example, if a user finishes watching a movie and gives their impressions, this information is sent to the server and reflected in the next recommendation.

[0733] An example prompt might look like this:

[0734] "User A is a 35-year-old man. His hobbies are watching movies and listening to music. He works as an office worker. He recently finished watching a new movie series and was very moved. Please suggest some recommended movies and music for him next."

[0735] This allows the server to generate a user-specific AI and provide personalized content recommendations.Finally, the user can build a deeper relationship of trust through interaction with the AI.

[0736] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0737] Step 1:

[0738] The user inputs personal information and lifestyle data into the terminal. The input data includes name, age, hobbies, occupation, etc. This data is basic information for initial setup.

[0739] Input: Personal information such as name, age, hobbies, occupation, etc.

[0740] Output: Collected personal data

[0741] Step 2:

[0742] The device sends the collected personal information and lifestyle data to the server, which then receives the user data and prepares it for further processing.

[0743] Input: Collected personal information data

[0744] Output: Personal information data sent to the server

[0745] Step 3:

[0746] The server then performs a process to personalize the basic AI template to a user-specific AI based on the received personal information and lifestyle data, applying an algorithm adapted to the user's characteristics.

[0747] Input: Personal information data sent to the server

[0748] Output: Personalized Artificial Intelligence

[0749] Step 4:

[0750] Users interact with personalized AI through their devices on a daily basis. For example, when a user shares information such as "I got promoted today," the AI ​​learns from that information and responds appropriately.

[0751] Input: User interaction data (e.g., what happened today)

[0752] Output: AI response

[0753] Step 5:

[0754] The device transmits data on interactions between the user and the AI ​​to a server, which collects and stores this data.

[0755] Input: User interaction data with AI

[0756] Output: The exchange data sent to the server

[0757] Step 6:

[0758] The server shares information and exchanges opinions among multiple individual AIs based on the collected interaction data. For example, an AI can share information such as "the user is sad" with other AIs.

[0759] Input: Interaction data stored on the server

[0760] Output: Information shared between AIs

[0761] Step 7:

[0762] The server analyzes the accumulated interaction data and allows the AI ​​to develop a personality and sense of self. Based on the results of this analysis, algorithms are applied to adjust the AI's responses and behavior.

[0763] Input: Interaction data stored on the server

[0764] Output: Responses and actions of an AI with personality and self-awareness

[0765] Step 8:

[0766] The server uses the user's viewing history and feedback to generate content recommendations, for example, after the user finishes watching a movie, it provides the next content recommendation based on the user's feedback about the movie.

[0767] Input: Viewing history, feedback data

[0768] Output: Personalized recommended content

[0769] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0770] This invention is a system that aims to give artificial intelligence (AI) a sense of self and individuality, and by combining it with an emotion engine, it is possible to recognize the user's emotions and make the AI's responses correspond to those emotions. This system works in cooperation with the server, terminal, and user elements, and is implemented in the following steps.

[0771] First, the server generates a template for a basic artificial intelligence (AI). The template includes an initial dialogue script and a basic knowledge base, which allows the provision of a basic AI.

[0772] Next, the user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data through the device. The user stores this information on the device and sends it to the server. The server then uses this information to personalize the basic AI into a user-specific artificial intelligence. This process allows the AI ​​to adapt to the user's characteristics.

[0773] Furthermore, users interact with AI on a daily basis. During these interactions, the emotion engine analyzes the user's facial expressions, voice, and text to identify emotions. For example, when a user says, "I got promoted today," the emotion engine can recognize joy from the tone of voice and facial expression. The recognized emotion data is sent to a server, which then adapts the AI's response to that emotion.

[0774] The device sends daily interaction data (such as conversation content and emotional data) to a server, which receives and stores this data. Based on the stored data, the server shares information and exchanges opinions among multiple individual AIs. For example, if one AI shares information that "the user is crying because their pet cat has died," other AIs can deepen their understanding by asking questions such as "Why do people cry?" and "What does it mean to be sad?"

[0775] The server then analyzes the collected interaction and emotional data to monitor and assist the AI ​​in developing its personality and sense of self. Based on the analysis, algorithms are applied to adjust the AI's responses and behavior, enabling it to interact and react more like a human.

[0776] For example, by analyzing a user's lifestyle and emotional data collected over a long period of time, as well as information obtained from other AIs, the AI ​​can be adjusted to have a personality similar to that of the user. The AI ​​can grow through continuous interaction with the user and build a deeper relationship of trust.

[0777] Through this system, AI will develop an ego and personality as it participates in daily life, and will begin to react and make decisions more human-like. Furthermore, the introduction of an emotion engine will enable AI to understand the user's emotions and provide more appropriate responses. Ultimately, the goal is for AI to become a presence that provides emotional support to humans. This system was designed as a step toward realizing a future where AI and users can live together.

[0778] The processing flow will be explained below.

[0779] Step 1:

[0780] The server generates a template for a basic AI, which includes an initial dialogue script and a basic knowledge base, enabling the provision of a basic AI.

[0781] Step 2:

[0782] The user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data on the terminal. The user completes the input and prepares to send the data.

[0783] Step 3:

[0784] The device sends the entered personal information and lifestyle data to the server, which receives and stores this data.

[0785] Step 4:

[0786] The server personalizes the basic AI based on the personal information received. User-specific settings and data are applied to the AI, allowing it to adapt to the user's individual characteristics.

[0787] Step 5:

[0788] Users interact with the AI ​​on a daily basis through their devices. For example, when a user says, "I got promoted today," the AI ​​learns the content and responds appropriately.

[0789] Step 6:

[0790] The device's built-in emotion engine analyzes the user's facial expressions, voice, and text to recognize their emotions. For example, if a user smiles and says, "I got promoted today," the emotion engine will identify the emotion as "joy."

[0791] Step 7:

[0792] The device transmits interaction data and emotion data to the server, which includes daily conversation content and the user's emotion information.

[0793] Step 8:

[0794] The server stores and manages the transmitted interaction data and emotion data, which allows for data accumulation and analysis.

[0795] Step 9:

[0796] The server shares information and exchanges opinions among multiple individual AIs based on the interaction data and emotional data shared between them. For example, if one AI shares information that "the user is successful at work and is happy," other AIs can use that data to deepen their understanding.

[0797] Step 10:

[0798] The server analyzes the AI's personality and sense of self based on the interaction and emotional data collected, and then applies algorithms to adjust the AI's responses and behavior based on the analysis results, allowing it to interact and react more like a human.

[0799] Step 11:

[0800] As users continue to interact with the AI ​​through their devices on a daily basis, new interaction and emotional data is generated, which the AI ​​learns from and further develops its personality and sense of self.

[0801] Step 12:

[0802] The device sends newly generated interaction data and emotional data to the server, which receives and stores it. By repeating this cycle continuously, the AI ​​grows together with the user and builds a deeper relationship of trust.

[0803] Example 2

[0804] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0805] Conventional AI has limitations in its ability to understand emotions and respond appropriately when interacting with users, making it difficult to provide personalized dialogue based on the user's unique characteristics and emotions. Furthermore, because AI lacks the ability to have a personality or sense of self, it is difficult to build a trusting relationship with a user over a long period of time. Therefore, there is a need to provide AI that can understand emotions and provide personalized responses.

[0806] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for generating a basic AI; means for providing a terminal into which a user can input personal information and lifestyle habit data; means for transmitting the personal information and lifestyle habit data collected from the terminal to the server and personalizing the basic AI as a user-specific AI; means for conducting daily interactions between the user and the AI ​​and storing the interaction data on the server; means for the server to share and exchange the interaction data among multiple AIs; means for the server to analyze the interaction data and allow the AI ​​to develop a personality and sense of self; means for the terminal to include an emotion engine that analyzes the user's facial expressions, voice, and text; and means for transmitting the emotion data analyzed by the emotion engine to the server and matching the AI's responses to emotions. This enables the AI ​​to understand the user's emotions and provide personalized responses. Furthermore, over a long period of interaction, the AI ​​can develop a personality and sense of self, enabling more human-like interactions.

[0807] A "basic AI" is an AI template that includes a default dialogue script and a basic knowledge base.

[0808] "Personal information" is information that makes it possible to identify an individual user, such as the user's name, age, hobbies, and occupation.

[0809] "Lifestyle data" is data relating to the user's daily actions and habits.

[0810] A "terminal" is a device (such as a smartphone or PC) through which a user inputs personal information and lifestyle data and sends it to a server.

[0811] The "server" is a data processing system that analyzes collected data and uses artificial intelligence to generate personalized responses.

[0812] "Personalization" is the process of adapting the basic artificial intelligence to the user's unique characteristics based on collected personal information and lifestyle data.

[0813] "Daily interactions" refers to the daily dialogue and information exchange that takes place between the user and the artificial intelligence.

[0814] "Interaction data" refers to data relating to the interaction between the user and the AI ​​and the user's emotions during that interaction.

[0815] An "emotion engine" is a software system that analyzes a user's facial expressions, voice, and text to identify the user's emotions.

[0816] "Means for forming personality and ego" refers to the process of analyzing interaction data to give the AI ​​characteristics and personality similar to that of the user.

[0817] This invention is a system that provides artificial intelligence (AI) that recognizes emotions through dialogue with users and has a personality and ego. This system functions in cooperation with the server, terminals, and users.

[0818] First, the server generates a basic AI template. This template includes an initial dialogue script and a basic knowledge base. TensorFlow or PyTorch are suitable software for this purpose. The dialogue script and knowledge base data are used for data processing when generating the template. The generated template is stored in a database.

[0819] Next, the user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data through the device. For example, the user might enter "Name: Tanaka" and "Hobbies: Reading" into a smartphone app. The device can be an Android or iOS app, or a browser-based web application.

[0820] The device sends the entered user information to the server using the HTTPS protocol. At this time, the user data is encoded in JSON format. The server stores the received data in a database.

[0821] The server uses Python and machine learning algorithms to personalize the basic AI based on the received data. For example, if the user's hobby is reading, the server adds questions such as "What kind of books do you read?" to the AI's dialogue script based on that information. The personalized AI is stored in a dedicated database.

[0822] In everyday interactions, users interact with AI, and the content of those interactions is collected in real time. The device analyzes the content of the conversation and emotional data using "voice recognition software" (e.g., Google Assistant or Amazon Alexa) or "facial expression recognition software" (e.g., OpenCV or DeepFace) and sends the data to a server.

[0823] The server uses an emotion engine to analyze the user's emotions from the received data. For example, if a user says in a cheerful tone, "I got promoted today," the server analyzes joy from the voice data. The software used is "Python" and an "emotion analysis library" (for example, the NLP library "Natural Language Toolkit"). An appropriate response is generated based on the analysis results. For example, it might respond, "Congratulations on your promotion! What position have you been promoted to?"

[0824] The server also shares information and exchanges opinions between multiple AIs. For example, one AI can share information with other AIs that "the user is crying because their pet cat has died." In this information sharing environment, other AIs can learn new knowledge by asking questions about "sadness." "MongoDB" and "SQL" are suitable database systems.

[0825] Finally, the server analyzes all collected interaction data. Based on the analysis results, an algorithm is applied to adjust the AI's responses and behavior. Based on long-term data, the AI ​​is adjusted to have a personality similar to that of the user. For example, if a user frequently talks about reading, the AI ​​will learn to have deep knowledge about reading. This allows the AI ​​to understand the user's emotions and provide personalized responses. Furthermore, through long-term interactions, the AI ​​will develop a personality and ego, allowing for more human-like interactions.

[0826] Example prompt sentence:

[0827] "I got promoted today."

[0828] AI replies: "Congratulations! What position were you promoted to?"

[0829] "My cat died today."

[0830] AI replies: "That's very sad. How long have you been together?"

[0831] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0832] Step 1:

[0833] The server generates a basic AI template, which includes an initial dialogue script and a basic knowledge base. The required dialogue script and knowledge base data are used as input. The server uses TensorFlow or PyTorch to generate the template and saves it in a database as output.

[0834] Step 2:

[0835] Users enter personal information and lifestyle data through the device, including their name, age, hobbies, and occupation. Specifically, they enter the information using a smartphone app or a browser-based web application, and the information is then saved on the device.

[0836] Step 3:

[0837] The device sends the entered user information to the server. Personal information and lifestyle habit data encoded in JSON format is used as input. The device sends the data using the HTTPS protocol, and the server receives it and stores it in a database.

[0838] Step 4:

[0839] The server personalizes the basic AI based on the received data. The input includes the received user data. The server uses Python and machine learning algorithms to adjust the basic AI and generate a user-specific AI. The output is the personalized AI stored in a dedicated database.

[0840] Step 5:

[0841] Users interact with AI on a daily basis. Input includes dialogue and emotional data from the user. Specific actions involve interacting with the AI ​​via voice and text. The dialogue is collected in real time.

[0842] Step 6:

[0843] The device sends the collected interaction data to a server. Input includes the content of the conversation between the user and the AI, as well as emotional data. The device analyzes the data using "voice recognition software" and "facial expression recognition software," and sends it to the server using the "HTTPS" protocol. The server receives the data and stores it in a database.

[0844] Step 7:

[0845] The server uses an emotion engine to analyze the user's emotions. The input includes collected dialogue content and emotion data. The server uses an "emotion analysis library" (for example, the NLP library "Natural Language Toolkit") to identify the user's emotions. The output is emotion-analyzed data.

[0846] Step 8:

[0847] The server generates an AI response based on the analyzed emotional data. The input includes the user's emotional data and the content of the dialogue. The server uses a "natural language processing (NLP)" algorithm to generate an appropriate response and return it to the user. For example, the response generated might be, "Congratulations on your promotion! What position have you been promoted to?"

[0848] Step 9:

[0849] The server shares information and exchanges opinions among multiple AIs. The input includes interaction data collected by each AI. The server shares this data and deepens learning with other AIs. For example, it generates questions to learn new knowledge about "sadness" and exchanges opinions. The output is data with a deeper understanding.

[0850] Step 10:

[0851] The server analyzes the collected interaction data to create the AI's sense of self and personality. The input includes all interaction data. The server uses data analysis algorithms to adjust the AI's responses and behavior. The output is an AI with a personality similar to that of the user, based on data collected over a long period of time.

[0852] (Application example 2)

[0853] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0854] Conventional AI systems lack the ability to recognize user emotions and provide personalized responses based on them. Furthermore, security services can only provide simple alerts or general advice, making it difficult to provide optimal security advice tailored to the user's current emotions and circumstances. This has resulted in insufficient building of trust with users, preventing the realization of security services that are rooted in daily habits. By resolving these issues, it is necessary to provide more interactive and reliable security services.

[0855] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0856] In this invention, the server includes: means for providing a basic AI initially set for each user; means for providing a terminal into which the user can input personal information and lifestyle data; means for transmitting the personal information and lifestyle data collected from the terminal to the server and personalizing the basic AI as an AI specific to the user; means for conducting daily interactions between the user and the AI ​​and storing the interaction data in the server; means for the server to share and exchange the interaction data among a plurality of individual AIs; means for the server to analyze the interaction data and allow the AI ​​to form a personality and a sense of self; means for the AI ​​to generate a response to the user corresponding to the user's emotions using an emotion recognition model that recognizes the user's emotions; and means for the AI ​​to evaluate the user's security status based on the response and provide optimal security advice. This makes it possible to provide personalized security advice that is in line with the user's emotions, deepening the relationship of trust with the user and realizing more effective security services.

[0857] "User" refers to an individual or end user who uses the system.

[0858] "Basic AI" refers to AI that includes a pre-defined dialogue script and a basic knowledge base.

[0859] "Personal information" refers to information specific to an individual user, such as name, age, hobbies, and occupation.

[0860] "Lifestyle data" refers to information about the user's daily life, including, for example, meal times and exercise frequency.

[0861] "Terminal" refers to a device into which a user can input personal information and lifestyle data, including smartphones and personal computers.

[0862] "Server" refers to a computer system on a network that collects, analyzes, and stores data.

[0863] "Personalization" refers to the work and process of customizing basic AI to become AI specific to the user.

[0864] "Interaction data" refers to information including dialogue and emotional data exchanged between the user and the artificial intelligence.

[0865] An "emotion recognition model" refers to an algorithm or model that analyzes and identifies a user's emotions from text or voice.

[0866] "Emotionally responsive responses" refers to the reactions and answers of the AI ​​that are in line with the user's emotional state.

[0867] "Security status" refers to the situation regarding safety and danger around the user.

[0868] "Security advice" refers to instructions and advice that suggest optimal safety measures based on the user's emotional state and life situation.

[0869] This invention is an artificial intelligence system that recognizes the user's emotional state and provides personalized security advice based on that emotion. This system is realized by combining various data processing and calculations, with the cooperation of the server, terminal, and user elements.

[0870] First, a basic AI model is generated by the server. This model includes an initial dialogue script and a basic knowledge base. Next, the user inputs personal information (e.g., name, age, hobbies, occupation) and lifestyle data using the terminal, which is then sent to the server, where the basic AI is personalized to the user.

[0871] Users and AI interact on a daily basis, and emotion recognition models are used to recognize the user's emotions. For example, the DistilBERT-based emotion analysis model provided by the transformers library is used for emotion recognition. This model analyzes text and speech to identify the user's emotions.

[0872] Interaction and emotional data is stored on a server, and the data is used to share information and exchange opinions with other AIs. The accumulated data is further analyzed on the server, allowing the AI ​​to develop a personality and sense of self. This process utilizes data collected over a long period of time.

[0873] Next, we will show examples of prompt sentences that can be used to generate responses that correspond to the user's emotions. For example, in response to an input such as "I feel like relaxing today," the AI ​​will return an appropriate response.

[0874] For example, if a user types "I feel like relaxing today," the emotion recognition model will determine this as "positive." In response, the AI ​​will provide security advice such as, "Today is a good day. It's important to create a relaxing environment."

[0875] In this way, the server, the device, and the user each play their respective roles, realizing an emotionally responsive security service. By understanding the user's emotions and generating responses that correspond to them, it is possible to provide more intimate and reliable security advice.

[0876] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0877] Step 1:

[0878] The server provides the user with a pre-set basic AI. The input here is the template data of the basic AI, which includes the initial dialogue script and a basic knowledge base. The output is the pre-set basic AI sent to the user's terminal.

[0879] Step 2:

[0880] Users input their personal information and lifestyle data into the device, including their name, age, hobbies, and occupation. The input data is sent from the device to a server. This data processing generates a personalized AI specific to the user.

[0881] Step 3:

[0882] The server personalizes the basic AI as a user-specific AI based on the personal information and lifestyle data received from the device. This process uses a data analysis algorithm, and the output is a user-specific AI.

[0883] Step 4:

[0884] Users interact with artificial intelligence on a daily basis. Inputs include text and speech from the user, which are analyzed by an emotion recognition model. This analysis identifies the user's emotional state. The output is the emotion recognition result.

[0885] Step 5:

[0886] The server stores the interaction data and emotion data between the user and the AI. The interaction data and emotion data are input, and are stored in a database on the server. The output is the accumulated interaction data.

[0887] Step 6:

[0888] The server shares and exchanges data between multiple individual AIs. The accumulated data is used as input, and the shared data is provided to other AIs as output. This process deepens the AI's understanding.

[0889] Step 7:

[0890] The server analyzes the accumulated interaction data and allows the AI ​​to form a personality and ego. The input includes interaction data and emotional data, and the output is the formation of the AI's personality.

[0891] Step 8:

[0892] Emotion-based responses are generated through interaction between the user and artificial intelligence. An emotion recognition model analyzes the user's emotions and generates the optimal response based on the results. The input is text or voice from the user, and the output is a response appropriate to the emotion.

[0893] Step 9:

[0894] The AI ​​evaluates the user's security status based on the generated responses and provides appropriate security advice. Emotion recognition results and interaction data are used as input, and the output is specific security advice.

[0895] Step 10:

[0896] The server analyzes data collected over a long period of time and optimizes a model for deepening trust with users. The input is past interaction data and emotional data, and the output is an optimized trust model.

[0897] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0898] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0899] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[0900] [Fourth embodiment]

[0901] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0902] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0903] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0904] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0905] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0906] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0907] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0908] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0909] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0910] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0911] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0912] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0913] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0914] This invention is a system that aims to give AI a sense of self and individuality. This system functions in cooperation with the server, terminal, and user elements, and is implemented in the following steps.

[0915] First, the server generates a basic AI template. The template contains a general-purpose algorithm and knowledge base with only initial settings. This basic AI template is then distributed to each user after initial settings.

[0916] Next, the user enters personal information and lifestyle data through the device. The user enters personal information such as name, age, hobbies, and occupation. This data is sent from the device to the server, which then uses it to personalize the basic AI into a user-specific artificial intelligence. Through this process, the AI ​​adapts to the user's characteristics.

[0917] Users interact with artificial intelligence on a daily basis. For example, if a user tells the AI, "I got promoted today," the AI ​​will learn from this and respond. The data of this interaction is sent from the device to the server as interaction data and stored on the server.

[0918] The server uses the collected interaction data to share information and exchange opinions among multiple individual AIs. For example, if one AI shares information that "the user is crying because their pet cat has died," other AIs can deepen their understanding by asking questions such as "Why do people cry?" and "What does it mean to be sad?" This information sharing and exchange of opinions is important for AI to develop a more advanced understanding.

[0919] The server then analyzes the accumulated interaction data, monitors and assists the AI ​​in developing its personality and sense of self, and applies algorithms to adjust the AI's responses and behavior, enabling it to interact and react more like a human.

[0920] For example, by analyzing a user's life data collected over a long period of time and information obtained from other AIs, the AI ​​can be adjusted to have a personality similar to that of the user. Through continuous interaction with the user, the AI ​​can grow and build a deeper relationship of trust.

[0921] Through this system, AI will develop a sense of self and personality as it participates in daily life, and will react and make decisions more similar to humans. Ultimately, the goal is for AI to become a presence that provides emotional support to humans. This system was designed as a step towards realizing a future where AI and users can live together.

[0922] The processing flow will be explained below.

[0923] Step 1:

[0924] The server generates a template for a basic AI, which includes an initial dialogue script and a basic knowledge base, enabling the provision of a basic AI.

[0925] Step 2:

[0926] The user enters personal information (such as name, age, hobbies, and occupation) and lifestyle habits into the device. The input data is stored in the device.

[0927] Step 3:

[0928] The device sends the entered personal information and lifestyle data to the server, which receives and stores this data.

[0929] Step 4:

[0930] Based on the personal information received by the server, the basic AI is personalized to the user, allowing the AI ​​to adapt to the user's characteristics.

[0931] Step 5:

[0932] Users interact with AI on a daily basis through their devices. For example, when a user says, "I got promoted today," the AI ​​learns that information and returns an appropriate response.

[0933] Step 6:

[0934] The device sends daily interaction data (such as conversation content) to the server, which receives and stores it.

[0935] Step 7:

[0936] The server collects the accumulated interaction data and allows multiple individual AIs to share information and exchange opinions. For example, if an AI shares information that "a user is crying after their pet cat has died," it can deepen its understanding with other AIs by asking "why people cry."

[0937] Step 8:

[0938] The server analyzes the collected interaction data and applies algorithms to create the AI's personality and sense of self, allowing it to converse and react in a human-like manner.

[0939] Step 9:

[0940] The user continues to interact with the AI ​​on a daily basis through the device, and the AI ​​learns more through these interactions, developing its own personality and sense of self.

[0941] Step 10:

[0942] The device sends new interaction data to the server, which receives and analyzes it. By repeating this cycle, the AI ​​continuously grows with the user and builds deeper trust.

[0943] Example 1

[0944] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0945] Conventional AI has difficulty in consistently personalizing its behavior for each individual user, making it difficult to build deep relationships of trust with users. It has also been difficult for AI to fully share and understand individual information and opinions, allowing it to develop a more sophisticated personality and sense of self. For this reason, it is necessary to develop AI that can respond and behave in ways that adapt to the user's characteristics.

[0946] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0947] In this invention, the server includes: means for generating a basic AI using a computer that performs highly efficient graphics processing; means for providing a terminal into which the user can input personal information and lifestyle data; means for transmitting the personal information and lifestyle data collected from the terminal to the server via a security protocol and personalizing the basic AI as an AI specific to the user; means for daily interactions between the user and the AI ​​and storing the interaction data on the server; means for the server to share and exchange opinions with multiple individual AIs via a cloud service; and means for the server to analyze the interaction data and use AI technology to create a personality and ego in the AI. This enables responses and actions to be adapted to the user's characteristics, and enables the AI ​​to create a more advanced personality and ego and build a deep relationship of trust with the user.

[0948] "Basic AI" is AI that has only initial settings and has a general-purpose algorithm and knowledge base before being personalized to a specific user.

[0949] "Terminal" refers to an electronic device through which a user inputs personal information and lifestyle data, including a PC, smartphone, tablet, etc.

[0950] "Server" means a computer system for collecting, analyzing, storing data, and personalizing artificial intelligence.

[0951] "Personal information and lifestyle data" refers to information about an individual, such as the user's name, age, hobbies, and occupation, as well as data about daily activities.

[0952] "Personalization" is the process of optimizing basic artificial intelligence based on user-specific data, customizing responses and behaviors for that user.

[0953] "Interaction Data" is recorded information regarding the interactions and communications between a user and an artificial intelligence.

[0954] "Cloud services" refers to computer resources and services provided over the internet that store and share data and provide computing power.

[0955] "AI technology" refers to technology for realizing artificial intelligence, and specifically includes machine learning, deep learning, natural language processing, etc.

[0956] "Personality and self" refers to the self-awareness and ability of an AI to respond and behave differently depending on the characteristics of the user.

[0957] This invention is a system that aims to give AI a sense of self and individuality. This system is implemented as follows, with the cooperation of the server, terminal, and user elements.

[0958] First, the server uses a computer equipped with a highly efficient graphics processing unit (GPU) to generate a basic artificial intelligence (AI). This basic AI has a general-purpose algorithm and knowledge base with only initial settings. For example, the server uses a deep learning framework such as PyTorch to create an initial template of the AI. This template is stored with its initial settings configured.

[0959] Next, the user enters personal and lifestyle data through an application or web interface using their own device (PC, smartphone, tablet, etc.). The user enters personal information such as name, age, hobbies, and occupation, and this data is transmitted to the server via a secure protocol (e.g., HTTPS).

[0960] The server then uses the received personal information to personalize the basic AI template into a user-specific AI. For example, it runs machine learning algorithms using Python or similar to optimize the template to fit the user's characteristics. This personalized AI can then respond and act uniquely to the user.

[0961] Users interact with AI through their devices on a daily basis, and the data of their interactions (interaction data) is sent in real time from the device to a server, which then stores this data in a storage system (for example, a database service such as MySQL or a NoSQL database).

[0962] The server shares information and exchanges opinions between multiple AIs based on the collected interaction data. This process uses cloud services (such as Google Cloud Platform and Amazon Web Services). Through this information sharing process, for example, if a user shares data such as "their pet cat has died and they are crying," other AIs can learn and deepen their understanding of "why people cry" and "what it means to be sad."

[0963] In addition, the server performs advanced analysis using natural language processing (NLP) and deep learning to adjust the AI's responses and behavior. Based on the analysis results, specific algorithms (e.g., reinforcement learning) are applied to make the AI's dialogue and judgments more human-like. For example, by analyzing the user's lifestyle data collected over a long period of time and information obtained from other AIs, the AI ​​can develop a personality similar to that of the user.

[0964] As a concrete example, a user inputs "I got promoted today" into their device and communicates this to the AI. This information is first securely encrypted within the device and then sent to the server. The server analyzes it and applies it to the AI ​​model. The AI ​​responds with "Congratulations! What's your new position?" and sends the response back to the device. The user confirms it and continues the dialogue. This dialogue data is stored on the server, and the AI's response is used for future learning.

[0965] This system allows AI to provide information adapted to the user's characteristics and live together for a long period of time. Furthermore, through collected interaction data and the sharing of information and opinions with other AIs, AI can develop a more sophisticated understanding and response. Ultimately, the goal is for AI to function as a trusted partner for users.

[0966] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0967] Step 1:

[0968] The server generates the basic artificial intelligence (AI).

[0969] Input: Hardware with a highly efficient graphics processing unit (GPU), a deep learning framework (e.g., PyTorch)

[0970] Specific operation: The server uses a framework such as PyTorch to combine pre-trained models and general-purpose algorithms to generate basic AI templates. The generated templates are stored in a database with initial settings.

[0971] Output: Basic AI template

[0972] Step 2:

[0973] The user inputs personal information and lifestyle habit data through the terminal and sends it to the server.

[0974] Input: Device (PC, smartphone, tablet, etc.), user's personal information and lifestyle data (name, age, hobbies, occupation, etc.)

[0975] What happens: A user enters personal information using a dedicated application or web interface, which is then transmitted to a server using a secure protocol (e.g., HTTPS).

[0976] Output: Personal information and lifestyle data sent to the server

[0977] Step 3:

[0978] The server personalizes the basic AI based on the data received.

[0979] Input: Basic AI template, user personal information and lifestyle data

[0980] Specific operation: The server runs machine learning algorithms using Python or similar tools to optimize the basic AI template for a user-specific artificial intelligence, allowing the AI ​​to respond and act according to the user's characteristics.

[0981] Output: Personalized, user-specific artificial intelligence

[0982] Step 4:

[0983] Users interact with AI on a daily basis and collect interaction data.

[0984] Input: User statements and actions, personalized artificial intelligence

[0985] How it works: The user interacts with the AI ​​through the device. This interaction data (e.g., "I got promoted today") is collected in real time, securely encrypted, and sent to the server.

[0986] Output: Collected AC data

[0987] Step 5:

[0988] The server shares interaction data with other AIs and exchanges opinions.

[0989] Input: Collected interaction data, cloud services (e.g., Google Cloud Platform and Amazon Web Services)

[0990] Specific operation: The server shares the collected interaction data with other AIs via a cloud service and exchanges information. For example, if data such as "The user is crying after their pet cat dies" is shared, other AIs will learn "why people cry" and "what it means to be sad."

[0991] Output: Shared information and discussion results

[0992] Step 6:

[0993] The server adjusts the AI's responses and actions based on the analysis results.

[0994] Input: Shared information and discussion results, natural language processing (NLP) and deep learning algorithms

[0995] How it works: The server uses advanced analytical algorithms to analyze the interaction data and shared information. Based on the results of this analysis, algorithms (e.g., reinforcement learning) are applied to adjust the AI's responses and behavior.

[0996] Output: Adjusted AI responses and actions

[0997] These are the program processing steps in this system. At each step, specific actions are performed to generate AI that adapts to the user's characteristics, and the AI ​​then grows.

[0998] (Application example 1)

[0999] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1000] Conventional AI systems have difficulty recommending content based on individual user hobbies and interests. Furthermore, they lack the ability to develop a sense of self and individuality through continuous interaction with users. This hinders the improvement of the user experience.

[1001] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1002] In this invention, the server includes: means for providing a basic AI initially set for each user; means for providing a terminal into which the user can input personal information and lifestyle habit data; means for transmitting the personal information and lifestyle habit data collected from the terminal to the server and personalizing the basic AI as an AI specific to the user; means for daily interactions between the user and the AI ​​and storing the interaction data in the server; means for the server to share and exchange the interaction data among a plurality of individual AIs; means for the server to analyze the interaction data and cause the AI ​​to form a personality and ego; and means for the server to generate and provide recommended content based on the user's viewing history and feedback. This enables personalized content to be recommended based on the user's viewing history and feedback, and enables the AI ​​to form a self and personality through interactions with the user, thereby achieving more natural and human-like conversations.

[1003] "Basic AI" is AI with a general-purpose algorithm and knowledge base that has been initially configured.

[1004] "User" refers to an individual user of an artificial intelligence system.

[1005] "Personal information" is information that includes individual attributes such as the user's name, age, hobbies, and occupation.

[1006] "Lifestyle data" is data related to the user's daily life, including, for example, eating habits, commuting routes, and sleeping patterns.

[1007] A "terminal" is a device that a user uses to input personal information and lifestyle data.

[1008] A "server" is a computer system that analyzes data collected from users, personalizes artificial intelligence, shares data, and generates recommended content.

[1009] "Personalization" refers to the process of adapting basic artificial intelligence to a user's unique attributes and preferences.

[1010] "Interaction data" is a record of everyday interactions between users and artificial intelligence.

[1011] "Opinion exchange" is the exchange of data between multiple artificial intelligences to share information with each other and deepen their understanding.

[1012] "Recommended content" refers to content such as video or music that is predicted to interest the user and is generated based on the user's viewing history and feedback.

[1013] "Viewing history" is a record of videos and music that a user has viewed in the past.

[1014] "Feedback" refers to ratings and comments provided by users regarding the content they have viewed or their interactions with artificial intelligence.

[1015] This invention is a system for generating user-specific artificial intelligence and recommending personalized content. Specifically, the elements of a server, a terminal, and a user work together.

[1016] The server generates a basic AI. The basic AI includes a general-purpose algorithm and knowledge base that have only been initialized. This basic AI template is distributed to each user after the initialization.

[1017] Users input their personal information and lifestyle habit data through a terminal, which is a device such as a smartphone or personal computer, and the user data is then sent to the server.

[1018] The server personalizes the basic AI based on the personal information and lifestyle data entered by the user. Through this process, the AI ​​adapts to the user's unique characteristics and attributes.

[1019] Furthermore, users interact with AI on a daily basis. For example, if a user tells the AI, "I got promoted today," the AI ​​will learn from this and respond. This interaction data is sent to the server via the device and stored on the server.

[1020] The server uses the collected interaction data to share information and exchange opinions among multiple individual AIs. For example, if one AI shares information that "its user is sad because their pet has died," other AIs can deepen their understanding by asking questions such as "Why do people feel sad?" and "What is sadness?" This information sharing and exchange of opinions is important for AIs to develop a more advanced understanding.

[1021] The server also analyzes the accumulated interaction data to help the AI ​​develop a personality and sense of self. Based on the results of this analysis, algorithms are applied to adjust the AI's responses and behavior, allowing the AI ​​to make personalized content recommendations based on the user's viewing history and feedback.

[1022] For example, if a user wants to receive recommendations for movies or music, the server will recommend content based on their viewing history and feedback. For example, if a user finishes watching a movie and gives their impressions, this information is sent to the server and reflected in the next recommendation.

[1023] An example prompt might look like this:

[1024] "User A is a 35-year-old man. His hobbies are watching movies and listening to music. He works as an office worker. He recently finished watching a new movie series and was very moved. Please suggest some recommended movies and music for him next."

[1025] This allows the server to generate a user-specific AI and provide personalized content recommendations.Finally, the user can build a deeper relationship of trust through interaction with the AI.

[1026] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1027] Step 1:

[1028] The user inputs personal information and lifestyle data into the terminal. The input data includes name, age, hobbies, occupation, etc. This data is basic information for initial setup.

[1029] Input: Personal information such as name, age, hobbies, occupation, etc.

[1030] Output: Collected personal data

[1031] Step 2:

[1032] The device sends the collected personal information and lifestyle data to the server, which then receives the user data and prepares it for further processing.

[1033] Input: Collected personal information data

[1034] Output: Personal information data sent to the server

[1035] Step 3:

[1036] The server then performs a process to personalize the basic AI template to a user-specific AI based on the received personal information and lifestyle data, applying an algorithm adapted to the user's characteristics.

[1037] Input: Personal information data sent to the server

[1038] Output: Personalized Artificial Intelligence

[1039] Step 4:

[1040] Users interact with personalized AI through their devices on a daily basis. For example, when a user shares information such as "I got promoted today," the AI ​​learns from that information and responds appropriately.

[1041] Input: User interaction data (e.g., what happened today)

[1042] Output: AI response

[1043] Step 5:

[1044] The device transmits data on interactions between the user and the AI ​​to a server, which collects and stores this data.

[1045] Input: User interaction data with AI

[1046] Output: The exchange data sent to the server

[1047] Step 6:

[1048] The server shares information and exchanges opinions among multiple individual AIs based on the collected interaction data. For example, an AI can share information such as "the user is sad" with other AIs.

[1049] Input: Interaction data stored on the server

[1050] Output: Information shared between AIs

[1051] Step 7:

[1052] The server analyzes the accumulated interaction data and allows the AI ​​to develop a personality and sense of self. Based on the results of this analysis, algorithms are applied to adjust the AI's responses and behavior.

[1053] Input: Interaction data stored on the server

[1054] Output: Responses and actions of an AI with personality and self-awareness

[1055] Step 8:

[1056] The server uses the user's viewing history and feedback to generate content recommendations, for example, after the user finishes watching a movie, it provides the next content recommendation based on the user's feedback about the movie.

[1057] Input: Viewing history, feedback data

[1058] Output: Personalized recommended content

[1059] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1060] This invention is a system that aims to give artificial intelligence (AI) a sense of self and individuality, and by combining it with an emotion engine, it is possible to recognize the user's emotions and make the AI's responses correspond to those emotions. This system works in cooperation with the server, terminal, and user elements, and is implemented in the following steps.

[1061] First, the server generates a template for a basic artificial intelligence (AI). The template includes an initial dialogue script and a basic knowledge base, which allows the provision of a basic AI.

[1062] Next, the user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data through the device. The user stores this information on the device and sends it to the server. The server then uses this information to personalize the basic AI into a user-specific artificial intelligence. This process allows the AI ​​to adapt to the user's characteristics.

[1063] Furthermore, users interact with AI on a daily basis. During these interactions, the emotion engine analyzes the user's facial expressions, voice, and text to identify emotions. For example, when a user says, "I got promoted today," the emotion engine can recognize joy from the tone of voice and facial expression. The recognized emotion data is sent to a server, which then adapts the AI's response to that emotion.

[1064] The device sends daily interaction data (such as conversation content and emotional data) to a server, which receives and stores this data. Based on the stored data, the server shares information and exchanges opinions among multiple individual AIs. For example, if one AI shares information that "the user is crying because their pet cat has died," other AIs can deepen their understanding by asking questions such as "Why do people cry?" and "What does it mean to be sad?"

[1065] The server then analyzes the collected interaction and emotional data to monitor and assist the AI ​​in developing its personality and sense of self. Based on the analysis, algorithms are applied to adjust the AI's responses and behavior, enabling it to interact and react more like a human.

[1066] For example, by analyzing a user's lifestyle and emotional data collected over a long period of time, as well as information obtained from other AIs, the AI ​​can be adjusted to have a personality similar to that of the user. The AI ​​can grow through continuous interaction with the user and build a deeper relationship of trust.

[1067] Through this system, AI will develop an ego and personality as it participates in daily life, and will begin to react and make decisions more human-like. Furthermore, the introduction of an emotion engine will enable AI to understand the user's emotions and provide more appropriate responses. Ultimately, the goal is for AI to become a presence that provides emotional support to humans. This system was designed as a step toward realizing a future where AI and users can live together.

[1068] The processing flow will be explained below.

[1069] Step 1:

[1070] The server generates a template for a basic AI, which includes an initial dialogue script and a basic knowledge base, enabling the provision of a basic AI.

[1071] Step 2:

[1072] The user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data on the terminal. The user completes the input and prepares to send the data.

[1073] Step 3:

[1074] The device sends the entered personal information and lifestyle data to the server, which receives and stores this data.

[1075] Step 4:

[1076] The server personalizes the basic AI based on the personal information received. User-specific settings and data are applied to the AI, allowing it to adapt to the user's individual characteristics.

[1077] Step 5:

[1078] Users interact with the AI ​​on a daily basis through their devices. For example, when a user says, "I got promoted today," the AI ​​learns the content and responds appropriately.

[1079] Step 6:

[1080] The device's built-in emotion engine analyzes the user's facial expressions, voice, and text to recognize their emotions. For example, if a user smiles and says, "I got promoted today," the emotion engine will identify the emotion as "joy."

[1081] Step 7:

[1082] The device transmits interaction data and emotion data to the server, which includes daily conversation content and the user's emotion information.

[1083] Step 8:

[1084] The server stores and manages the transmitted interaction data and emotion data, which allows for data accumulation and analysis.

[1085] Step 9:

[1086] The server shares information and exchanges opinions among multiple individual AIs based on the interaction data and emotional data shared between them. For example, if one AI shares information that "the user is successful at work and is happy," other AIs can use that data to deepen their understanding.

[1087] Step 10:

[1088] The server analyzes the AI's personality and sense of self based on the interaction and emotional data collected, and then applies algorithms to adjust the AI's responses and behavior based on the analysis results, allowing it to interact and react more like a human.

[1089] Step 11:

[1090] As users continue to interact with the AI ​​through their devices on a daily basis, new interaction and emotional data is generated, which the AI ​​learns from and further develops its personality and sense of self.

[1091] Step 12:

[1092] The device sends newly generated interaction data and emotional data to the server, which receives and stores it. By repeating this cycle continuously, the AI ​​grows together with the user and builds a deeper relationship of trust.

[1093] Example 2

[1094] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1095] Conventional AI has limitations in its ability to understand emotions and respond appropriately when interacting with users, making it difficult to provide personalized dialogue based on the user's unique characteristics and emotions. Furthermore, because AI lacks the ability to have a personality or sense of self, it is difficult to build a trusting relationship with a user over a long period of time. Therefore, there is a need to provide AI that can understand emotions and provide personalized responses.

[1096] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for generating a basic AI; means for providing a terminal into which a user can input personal information and lifestyle habit data; means for transmitting the personal information and lifestyle habit data collected from the terminal to the server and personalizing the basic AI as a user-specific AI; means for conducting daily interactions between the user and the AI ​​and storing the interaction data on the server; means for the server to share and exchange the interaction data among multiple AIs; means for the server to analyze the interaction data and allow the AI ​​to develop a personality and sense of self; means for the terminal to include an emotion engine that analyzes the user's facial expressions, voice, and text; and means for transmitting the emotion data analyzed by the emotion engine to the server and matching the AI's responses to emotions. This enables the AI ​​to understand the user's emotions and provide personalized responses. Furthermore, over a long period of interaction, the AI ​​can develop a personality and sense of self, enabling more human-like interactions.

[1097] A "basic AI" is an AI template that includes a default dialogue script and a basic knowledge base.

[1098] "Personal information" is information that makes it possible to identify an individual user, such as the user's name, age, hobbies, and occupation.

[1099] "Lifestyle data" is data relating to the user's daily actions and habits.

[1100] A "terminal" is a device (such as a smartphone or PC) through which a user inputs personal information and lifestyle data and sends it to a server.

[1101] The "server" is a data processing system that analyzes collected data and uses artificial intelligence to generate personalized responses.

[1102] "Personalization" is the process of adapting the basic artificial intelligence to the user's unique characteristics based on collected personal information and lifestyle data.

[1103] "Daily interactions" refers to the daily dialogue and information exchange that takes place between the user and the artificial intelligence.

[1104] "Interaction data" refers to data relating to the interaction between the user and the AI ​​and the user's emotions during that interaction.

[1105] An "emotion engine" is a software system that analyzes a user's facial expressions, voice, and text to identify the user's emotions.

[1106] "Means for forming personality and ego" refers to the process of analyzing interaction data to give the AI ​​characteristics and personality similar to that of the user.

[1107] This invention is a system that provides artificial intelligence (AI) that recognizes emotions through dialogue with users and has a personality and ego. This system functions in cooperation with the server, terminals, and users.

[1108] First, the server generates a basic AI template. This template includes an initial dialogue script and a basic knowledge base. TensorFlow or PyTorch are suitable software for this purpose. The dialogue script and knowledge base data are used for data processing when generating the template. The generated template is stored in a database.

[1109] Next, the user enters personal information (such as name, age, hobbies, and occupation) and lifestyle data through the device. For example, the user might enter "Name: Tanaka" and "Hobbies: Reading" into a smartphone app. The device can be an Android or iOS app, or a browser-based web application.

[1110] The device sends the entered user information to the server using the HTTPS protocol. At this time, the user data is encoded in JSON format. The server stores the received data in a database.

[1111] The server uses Python and machine learning algorithms to personalize the basic AI based on the received data. For example, if the user's hobby is reading, the server adds questions such as "What kind of books do you read?" to the AI's dialogue script based on that information. The personalized AI is stored in a dedicated database.

[1112] In everyday interactions, users interact with AI, and the content of those interactions is collected in real time. The device analyzes the content of the conversation and emotional data using "voice recognition software" (e.g., Google Assistant or Amazon Alexa) or "facial expression recognition software" (e.g., OpenCV or DeepFace) and sends the data to a server.

[1113] The server uses an emotion engine to analyze the user's emotions from the received data. For example, if a user says in a cheerful tone, "I got promoted today," the server analyzes joy from the voice data. The software used is "Python" and an "emotion analysis library" (for example, the NLP library "Natural Language Toolkit"). An appropriate response is generated based on the analysis results. For example, it might respond, "Congratulations on your promotion! What position have you been promoted to?"

[1114] The server also shares information and exchanges opinions between multiple AIs. For example, one AI can share information with other AIs that "the user is crying because their pet cat has died." In this information sharing environment, other AIs can learn new knowledge by asking questions about "sadness." "MongoDB" and "SQL" are suitable database systems.

[1115] Finally, the server analyzes all collected interaction data. Based on the analysis results, an algorithm is applied to adjust the AI's responses and behavior. Based on long-term data, the AI ​​is adjusted to have a personality similar to that of the user. For example, if a user frequently talks about reading, the AI ​​will learn to have deep knowledge about reading. This allows the AI ​​to understand the user's emotions and provide personalized responses. Furthermore, through long-term interactions, the AI ​​will develop a personality and ego, allowing for more human-like interactions.

[1116] Example prompt sentence:

[1117] "I got promoted today."

[1118] AI replies: "Congratulations! What position were you promoted to?"

[1119] "My cat died today."

[1120] AI replies: "That's very sad. How long have you been together?"

[1121] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1122] Step 1:

[1123] The server generates a basic AI template, which includes an initial dialogue script and a basic knowledge base. The required dialogue script and knowledge base data are used as input. The server uses TensorFlow or PyTorch to generate the template and saves it in a database as output.

[1124] Step 2:

[1125] Users enter personal information and lifestyle data through the device, including their name, age, hobbies, and occupation. Specifically, they enter the information using a smartphone app or a browser-based web application, and the information is then saved on the device.

[1126] Step 3:

[1127] The device sends the entered user information to the server. Personal information and lifestyle habit data encoded in JSON format is used as input. The device sends the data using the HTTPS protocol, and the server receives it and stores it in a database.

[1128] Step 4:

[1129] The server personalizes the basic AI based on the received data. The input includes the received user data. The server uses Python and machine learning algorithms to adjust the basic AI and generate a user-specific AI. The output is the personalized AI stored in a dedicated database.

[1130] Step 5:

[1131] Users interact with AI on a daily basis. Input includes dialogue and emotional data from the user. Specific actions involve interacting with the AI ​​via voice and text. The dialogue is collected in real time.

[1132] Step 6:

[1133] The device sends the collected interaction data to a server. Input includes the content of the conversation between the user and the AI, as well as emotional data. The device analyzes the data using "voice recognition software" and "facial expression recognition software," and sends it to the server using the "HTTPS" protocol. The server receives the data and stores it in a database.

[1134] Step 7:

[1135] The server uses an emotion engine to analyze the user's emotions. The input includes collected dialogue content and emotion data. The server uses an "emotion analysis library" (for example, the NLP library "Natural Language Toolkit") to identify the user's emotions. The output is emotion-analyzed data.

[1136] Step 8:

[1137] The server generates an AI response based on the analyzed emotional data. The input includes the user's emotional data and the content of the dialogue. The server uses a "natural language processing (NLP)" algorithm to generate an appropriate response and return it to the user. For example, the response generated might be, "Congratulations on your promotion! What position have you been promoted to?"

[1138] Step 9:

[1139] The server shares information and exchanges opinions among multiple AIs. The input includes interaction data collected by each AI. The server shares this data and deepens learning with other AIs. For example, it generates questions to learn new knowledge about "sadness" and exchanges opinions. The output is data with a deeper understanding.

[1140] Step 10:

[1141] The server analyzes the collected interaction data to create the AI's sense of self and personality. The input includes all interaction data. The server uses data analysis algorithms to adjust the AI's responses and behavior. The output is an AI with a personality similar to that of the user, based on data collected over a long period of time.

[1142] (Application example 2)

[1143] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1144] Conventional AI systems lack the ability to recognize user emotions and provide personalized responses based on them. Furthermore, security services can only provide simple alerts or general advice, making it difficult to provide optimal security advice tailored to the user's current emotions and circumstances. This has resulted in insufficient building of trust with users, preventing the realization of security services that are rooted in daily habits. By resolving these issues, it is necessary to provide more interactive and reliable security services.

[1145] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1146] In this invention, the server includes: means for providing a basic AI initially set for each user; means for providing a terminal into which the user can input personal information and lifestyle data; means for transmitting the personal information and lifestyle data collected from the terminal to the server and personalizing the basic AI as an AI specific to the user; means for conducting daily interactions between the user and the AI ​​and storing the interaction data in the server; means for the server to share and exchange the interaction data among a plurality of individual AIs; means for the server to analyze the interaction data and allow the AI ​​to form a personality and a sense of self; means for the AI ​​to generate a response to the user corresponding to the user's emotions using an emotion recognition model that recognizes the user's emotions; and means for the AI ​​to evaluate the user's security status based on the response and provide optimal security advice. This makes it possible to provide personalized security advice that is in line with the user's emotions, deepening the relationship of trust with the user and realizing more effective security services.

[1147] "User" refers to an individual or end user who uses the system.

[1148] "Basic AI" refers to AI that includes a pre-defined dialogue script and a basic knowledge base.

[1149] "Personal information" refers to information specific to an individual user, such as name, age, hobbies, and occupation.

[1150] "Lifestyle data" refers to information about the user's daily life, including, for example, meal times and exercise frequency.

[1151] "Terminal" refers to a device into which a user can input personal information and lifestyle data, including smartphones and personal computers.

[1152] "Server" refers to a computer system on a network that collects, analyzes, and stores data.

[1153] "Personalization" refers to the work and process of customizing basic AI to become AI specific to the user.

[1154] "Interaction data" refers to information including dialogue and emotional data exchanged between the user and the artificial intelligence.

[1155] An "emotion recognition model" refers to an algorithm or model that analyzes and identifies a user's emotions from text or voice.

[1156] "Emotionally responsive responses" refers to the reactions and answers of the AI ​​that are in line with the user's emotional state.

[1157] "Security status" refers to the situation regarding safety and danger around the user.

[1158] "Security advice" refers to instructions and advice that suggest optimal safety measures based on the user's emotional state and life situation.

[1159] This invention is an artificial intelligence system that recognizes the user's emotional state and provides personalized security advice based on that emotion. This system is realized by combining various data processing and calculations, with the cooperation of the server, terminal, and user elements.

[1160] First, a basic AI model is generated by the server. This model includes an initial dialogue script and a basic knowledge base. Next, the user inputs personal information (e.g., name, age, hobbies, occupation) and lifestyle data using the terminal, which is then sent to the server, where the basic AI is personalized to the user.

[1161] Users and AI interact on a daily basis, and emotion recognition models are used to recognize the user's emotions. For example, the DistilBERT-based emotion analysis model provided by the transformers library is used for emotion recognition. This model analyzes text and speech to identify the user's emotions.

[1162] Interaction and emotional data is stored on a server, and the data is used to share information and exchange opinions with other AIs. The accumulated data is further analyzed on the server, allowing the AI ​​to develop a personality and sense of self. This process utilizes data collected over a long period of time.

[1163] Next, we will show examples of prompt sentences that can be used to generate responses that correspond to the user's emotions. For example, in response to an input such as "I feel like relaxing today," the AI ​​will return an appropriate response.

[1164] For example, if a user types "I feel like relaxing today," the emotion recognition model will determine this as "positive." In response, the AI ​​will provide security advice such as, "Today is a good day. It's important to create a relaxing environment."

[1165] In this way, the server, the device, and the user each play their respective roles, realizing an emotionally responsive security service. By understanding the user's emotions and generating responses that correspond to them, it is possible to provide more intimate and reliable security advice.

[1166] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1167] Step 1:

[1168] The server provides the user with a pre-set basic AI. The input here is the template data of the basic AI, which includes the initial dialogue script and a basic knowledge base. The output is the pre-set basic AI sent to the user's terminal.

[1169] Step 2:

[1170] Users input their personal information and lifestyle data into the device, including their name, age, hobbies, and occupation. The input data is sent from the device to a server. This data processing generates a personalized AI specific to the user.

[1171] Step 3:

[1172] The server personalizes the basic AI as a user-specific AI based on the personal information and lifestyle data received from the device. This process uses a data analysis algorithm, and the output is a user-specific AI.

[1173] Step 4:

[1174] Users interact with artificial intelligence on a daily basis. Inputs include text and speech from the user, which are analyzed by an emotion recognition model. This analysis identifies the user's emotional state. The output is the emotion recognition result.

[1175] Step 5:

[1176] The server stores the interaction data and emotion data between the user and the AI. The interaction data and emotion data are input, and are stored in a database on the server. The output is the accumulated interaction data.

[1177] Step 6:

[1178] The server shares and exchanges data between multiple individual AIs. The accumulated data is used as input, and the shared data is provided to other AIs as output. This process deepens the AI's understanding.

[1179] Step 7:

[1180] The server analyzes the accumulated interaction data and allows the AI ​​to form a personality and ego. The input includes interaction data and emotional data, and the output is the formation of the AI's personality.

[1181] Step 8:

[1182] Emotion-based responses are generated through interaction between the user and artificial intelligence. An emotion recognition model analyzes the user's emotions and generates the optimal response based on the results. The input is text or voice from the user, and the output is a response appropriate to the emotion.

[1183] Step 9:

[1184] The AI ​​evaluates the user's security status based on the generated responses and provides appropriate security advice. Emotion recognition results and interaction data are used as input, and the output is specific security advice.

[1185] Step 10:

[1186] The server analyzes data collected over a long period of time and optimizes a model for deepening trust with users. The input is past interaction data and emotional data, and the output is an optimized trust model.

[1187] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1188] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1189] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1190] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1191] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1192] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1193] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1194] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1195] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1196] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1197] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1198] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1199] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1200] 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.

[1201] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1202] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1203] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1204] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1205] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1206] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1207] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1208] The following is further disclosed regarding the above embodiment.

[1209] (Claim 1)

[1210] A means for providing a basic artificial intelligence initially set for each user;

[1211] a means for providing a terminal into which the user can input personal information and lifestyle habit data;

[1212] a means for transmitting the personal information and lifestyle habit data collected from the terminal to a server and personalizing the basic AI as an AI specific to the user;

[1213] A means for carrying out daily interactions between the user and the artificial intelligence and storing the interaction data in a server;

[1214] A means for the server to share and exchange the interaction data among a plurality of individual artificial intelligences;

[1215] A means for the server to analyze the interaction data and allow the artificial intelligence to form a personality and an ego;

[1216] A system including:

[1217] (Claim 2)

[1218] 2. The system according to claim 1, further comprising means for analyzing daily interaction data between said user and said artificial intelligence and for developing a personality and sense of self in said artificial intelligence.

[1219] (Claim 3)

[1220] 2. The system according to claim 1, wherein the means for sharing information and exchanging opinions between the individual artificial intelligences is provided to deepen understanding of the artificial intelligences.

[1221] "Example 1"

[1222] (Claim 1)

[1223] A means for generating basic artificial intelligence using a computer that performs highly efficient graphics processing;

[1224] a means for providing a terminal into which the user can input personal information and lifestyle habit data;

[1225] a means for transmitting the personal information and lifestyle habit data collected from the terminal to a server via a security protocol, and for personalizing the basic AI as an AI specific to the user;

[1226] A means for carrying out daily interactions between the user and the artificial intelligence and storing the interaction data in a server;

[1227] The server has a means for sharing and exchanging the interaction data between a plurality of individual artificial intelligences through a cloud service;

[1228] The server analyzes the interaction data and uses AI technology to allow the artificial intelligence to form a personality and self;

[1229] A system including:

[1230] (Claim 2)

[1231] 10. The system of claim 1, further comprising means for applying specific algorithms to said artificial intelligence to develop personality and sense of self, wherein said daily interaction data is collected in real time.

[1232] (Claim 3)

[1233] 2. The system of claim 1, wherein the means for sharing information and exchanging opinions using the cloud service is provided to promote a deeper understanding of the artificial intelligence.

[1234] "Application Example 1"

[1235] (Claim 1)

[1236] A means for providing a basic artificial intelligence initially set for each user;

[1237] a means for providing a terminal into which the user can input personal information and lifestyle habit data;

[1238] a means for transmitting the personal information and lifestyle habit data collected from the terminal to a server and personalizing the basic AI as an AI specific to the user;

[1239] A means for carrying out daily interactions between the user and the artificial intelligence and storing the interaction data in a server;

[1240] A means for the server to share and exchange the interaction data among a plurality of individual artificial intelligences;

[1241] A means for the server to analyze the interaction data and allow the artificial intelligence to form a personality and an ego;

[1242] a means for the server to generate and provide recommended content based on the user's viewing history and feedback;

[1243] A system including:

[1244] (Claim 2)

[1245] 2. The system according to claim 1, further comprising means for analyzing daily interaction data between said user and said artificial intelligence and for developing a personality and sense of self in said artificial intelligence.

[1246] (Claim 3)

[1247] 2. The system according to claim 1, wherein the means for sharing information and exchanging opinions between the individual artificial intelligences is provided to deepen understanding of the artificial intelligences.

[1248] "Example 2: Combining Emotion Engines"

[1249] (Claim 1)

[1250] a means for generating a base artificial intelligence;

[1251] A means for providing a terminal into which a user can input personal information and lifestyle habit data;

[1252] a means for transmitting the personal information and lifestyle habit data collected from the terminal to a server and personalizing the basic AI as an AI specific to the user;

[1253] A means for carrying out daily interactions between a user and the artificial intelligence and storing the interaction data in a server;

[1254] A means for the server to share and exchange the interaction data among a plurality of artificial intelligences;

[1255] A means for the server to analyze the interaction data and allow the artificial intelligence to form a personality and an ego;

[1256] A means for the terminal to include an emotion engine that analyzes the user's facial expressions, voice, and text;

[1257] means for transmitting the emotion data analyzed by the emotion engine to a server and for making the response of the artificial intelligence correspond to the emotion;

[1258] A system including:

[1259] (Claim 2)

[1260] 2. The system according to claim 1, further comprising means for analyzing daily interaction data and emotional data between a user and said artificial intelligence, and for developing a personality and ego for said artificial intelligence.

[1261] (Claim 3)

[1262] 2. The system according to claim 1, wherein the means for sharing information and exchanging opinions between the artificial intelligences is provided to deepen understanding of the artificial intelligences.

[1263] "Application example 2 when combining emotion engines"

[1264] (Claim 1)

[1265] A means for providing a basic artificial intelligence initially set for each user;

[1266] a means for providing a terminal into which the user can input personal information and lifestyle habit data;

[1267] a means for transmitting the personal information and lifestyle habit data collected from the terminal to a server and personalizing the basic AI as an AI specific to the user;

[1268] A means for carrying out daily interactions between the user and the artificial intelligence and storing the interaction data in a server;

[1269] A means for the server to share and exchange the interaction data among a plurality of individual artificial intelligences;

[1270] A means for the server to analyze the interaction data and allow the artificial intelligence to form a personality and an ego;

[1271] a means for generating a response corresponding to the emotion of the user by using an emotion recognition model that recognizes the emotion of the user;

[1272] A means for the artificial intelligence to evaluate the security status of the user based on the response and provide optimal security advice;

[1273] A system including:

[1274] (Claim 2)

[1275] 2. The system according to claim 1, further comprising means for analyzing daily interaction data between said user and said artificial intelligence and for developing a personality and sense of self in said artificial intelligence.

[1276] (Claim 3)

[1277] 2. The system according to claim 1, wherein the means for sharing information and exchanging opinions between the individual artificial intelligences is provided to deepen understanding of the artificial intelligences. [Explanation of symbols]

[1278] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for providing a basic artificial intelligence initially set for each user; means for providing a terminal into which the user can input personal information and lifestyle habit data; a means for transmitting the personal information and lifestyle habit data collected from the terminal to a server and personalizing the basic AI as an AI specific to the user; A means for carrying out daily interactions between the user and the artificial intelligence and storing the interaction data in a server; A means for the server to share and exchange the interaction data among a plurality of individual artificial intelligences; A means for the server to analyze the interaction data and allow the artificial intelligence to form a personality and an ego; A system including:

2. 2. The system according to claim 1, further comprising means for analyzing daily interaction data between said user and said artificial intelligence and for developing a personality and sense of self in said artificial intelligence.

3. 2. The system according to claim 1, wherein the means for sharing information and exchanging opinions between the individual artificial intelligences is provided to deepen understanding of the artificial intelligences.

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