System

Abstract

A system is provided.SOLUTION: A system comprising: means for operating a plurality of artificial intelligences imitating a human brain in a virtual environment; means for accelerating a time of the virtual environment in which the artificial intelligences operate; means for acquiring an invention or a culture generated in the virtual environment and storing the invention or the culture in a database; and means for analyzing the acquired invention or culture and specifying a useful technology.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] With current artificial intelligence technology, it is difficult to generate creative inventions and cultures like humans, and it is also difficult to predict and acquire future technologies and cultures in a short period of time. While conventional technology makes it possible to make individual inventions and predictions, it does not provide a method for operating a large number of artificial intelligences that mimic the human brain in a virtual environment and acquiring new inventions and cultures through their activities there. Against this background, there is a need for a system that can efficiently acquire new inventions and cultures and utilize them in the real world. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a means for operating multiple artificial intelligences modeled on the human brain in a virtual environment. It also provides a system including a means for accelerating time in the virtual environment in which the artificial intelligences operate, and a means for acquiring inventions and cultures generated in the virtual environment and storing them in a database. Furthermore, by providing a means for analyzing the acquired inventions and cultures and identifying useful technologies, it is possible to efficiently acquire new inventions and cultures and utilize them in the real world.

[0006] "Artificial intelligence" refers to systems or programs that mimic human intelligence and have cognitive functions.

[0007] A "virtual environment" is a virtual space or world simulated on a computer.

[0008] "Time acceleration" is a technique that allows time to pass faster in a virtual environment than in the real world.

[0009] An "invention" is the creation of a new structure, method, device, etc., that achieves a technological advance.

[0010] "Culture" refers to the social behaviors, customs, and values ​​generated and developed by artificial intelligence within a virtual environment.

[0011] A "database" is a system that can efficiently store, manage, and search large amounts of data.

[0012] "Analysis" is the process of deriving useful information and results by carefully examining and analyzing collected data.

[0013] "Characteristics" refer to the individual abilities, skills, and personality traits that an AI possesses.

[0014] "Feedback" refers to the process of collecting opinions and information from users and reflecting them in the system. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] This invention is a system that operates multiple artificial intelligences modeled after the human brain in a virtual environment, and accelerates time in the virtual world to efficiently generate and acquire inventions and culture. This system is composed of a server, terminals, and users, each playing their own role.

[0037] Server processing

[0038] Setting up and building a virtual environment

[0039] The server sets the basic structure of the virtual environment (topography, climate, social systems, etc.) For example, it models the topography of a city and sets the physical laws and environmental variables to simulate the growth of the city.

[0040] The server sets a time acceleration factor, causing time in the virtual environment to progress faster than in reality, allowing long-term changes to be observed in a short period of time.

[0041] Artificial Intelligence Instance Generation

[0042] The server generates multiple AI models modeled after the human brain, each with different characteristics and initial skill sets—for example, one model might be good at engineering, while another might be talented at art.

[0043] These AIs operate autonomously within the virtual environment, growing and developing as they interact with each other.

[0044] Running an activity simulation

[0045] The server simulates the activities of the AI ​​in a virtual environment, observes the process of the AI ​​generating inventions and culture, and collects the generated data.

[0046] For example, the process by which new energy technologies are developed or new musical genres are formed can be simulated in a virtual urban environment.

[0047] Data collection and analysis

[0048] The server stores the inventions and cultures generated within the virtual environment in a database.

[0049] The collected data is analyzed to identify useful technologies and cultures, which then lead to patent applications and technological applications in the real world.

[0050] Processing by the terminal

[0051] Providing a user interface

[0052] The device provides the user with an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time. For example, a dashboard displays the activity history of each AI and the progress of inventions.

[0053] The terminal will have an interface designed to make it easy for users to search for information about specific inventions or cultures.

[0054] Receiving and sending feedback

[0055] The terminal receives feedback from the user and sends it to the server, which uses the feedback to improve the system or propose new inventions.

[0056] For example, a user can input an idea for a new energy source and the idea can be tested in a virtual environment.

[0057] User Action

[0058] Virtual environment observation and intervention

[0059] Users can observe the status of the virtual environment through their devices, for example, checking the development of the virtual city and the activity history of the AI ​​in real time.

[0060] Users can also intervene in the virtual environment and artificial intelligence, for example by introducing certain technologies into the virtual environment and observing their effects.

[0061] Specific examples

[0062] For example, to simulate the invention of a new energy source in a virtual environment:

[0063] 1. Setting up the virtual environment: The server sets up the basic data (topography, climate, energy demand, etc.) to simulate a city.

[0064] 2. Generation of artificial intelligence: The server generates an artificial intelligence model that is strong in energy engineering and an artificial intelligence model that is knowledgeable in socioeconomics.

[0065] 3. Start of activity simulation: The server simulates the research and development of new energy sources in a virtual city. Each AI cooperates to develop new technologies.

[0066] 4. Data collection and analysis: The server stores the generated data on the new energy sources in a database and analyzes them. Based on the analysis results, patent applications and real-world applications can be made.

[0067] In this way, the present invention provides an innovative system that can efficiently generate new technologies and cultures and utilize them in the real world.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] The server sets the basic structure of the virtual environment. It generates terrain data within the virtual environment and establishes climatic conditions and social systems. For example, it builds a model of a city and places the necessary infrastructure and housing there. It also sets the laws of physics and environmental variables (temperature, humidity, etc.).

[0071] Step 2:

[0072] The server sets a time acceleration factor, which sets the passage of time in the virtual environment to hundreds of seconds of virtual time per second of real time, allowing long-term changes to be observed in a short period of time.

[0073] Step 3:

[0074] The server generates multiple AI models modeled after the human brain, each with its own unique characteristics and initial skill set—for example, one AI may be good at engineering, while another may be talented in art.

[0075] Step 4:

[0076] The server allows the AIs generated within the virtual environment to begin acting autonomously, creating an environment in which they can influence each other and develop, for example, working together to develop new energy technologies within a city.

[0077] Step 5:

[0078] The server simulates the AI's activities in the virtual environment, observing, for example, the invention of a new energy source or the formation of a new culture, and collecting necessary data. The AI-generated inventions and cultural data are then stored in a database.

[0079] Step 6:

[0080] The server analyzes the collected data, identifies technologies and cultures that are useful in the real world, generates patent documents based on the analysis results, prepares patent applications, and provides appropriate feedback to users to allow them to access the system.

[0081] Step 7:

[0082] The terminal provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time, allowing users to observe the activity history of each AI and the progress of their inventions.

[0083] Step 8:

[0084] The device receives feedback from users and sends it to the server. Users input and submit ideas for new inventions and system improvements, which are reflected in the virtual environment and the activities of the artificial intelligence. This allows the entire system to evolve in a way that meets user expectations.

[0085] Step 9:

[0086] Users can observe the situation in the virtual environment through their devices and intervene in specific locations or artificial intelligence, for example, to observe the impact of the introduction of new technology or to issue instructions to accelerate a specific project.

[0087] In this way, by having the server, terminal, and user fulfill their respective roles, a system is realized in which new inventions and cultures can be efficiently generated and acquired through the activities of artificial intelligence within the virtual environment, and then utilized in the real world.

[0088] Example 1

[0089] 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."

[0090] Conventional artificial intelligence systems have had problems with the efficient creation and acquisition of new technologies and cultures. They also lack the ability to manage time in virtual environments, visualize the activities of intelligent models with diverse characteristics, and incorporate user feedback. Therefore, there has been a need for a system that can solve these problems and efficiently create and acquire new technologies and cultures using an intelligent model that mimics the human brain.

[0091] 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.

[0092] In this invention, the server includes a means for operating a plurality of intelligent models imitating the human brain in a virtual space, a means for accelerating the time of the virtual space in which the intelligent models are active, a means for acquiring innovations and cultures generated in the virtual space and storing them in an information base, and a means for analyzing the acquired innovations and cultures and identifying useful technologies, thereby enabling the efficient generation and acquisition of new technologies and cultures using intelligent models.

[0093] An "intelligent model" is an information processing system that mimics the human brain, has multiple characteristics and capabilities, and operates autonomously within a virtual space.

[0094] A "virtual space" is a virtual environment that mimics a real physical environment using digital technology, allowing people and intelligent models to interact with each other.

[0095] "Time acceleration" is a technique that sets the speed at which time progresses in a virtual space to be faster than real time, allowing long-term changes and developments to be observed in a short period of time.

[0096] "Innovation" is a general term for new technologies, ideas, or inventions generated within the virtual world.

[0097] "Culture" is a general term for new art forms, music, literature, customs, or other social phenomena that are generated within virtual spaces.

[0098] An "information base" is a digital storage system for storing innovations and culture generated within virtual space as data.

[0099] "Analysis" is the process of examining the data stored in an information base in detail to extract specific patterns and useful information.

[0100] "Feedback" refers to opinions, suggestions, or evaluations sent by users, and is information that is useful for improving the virtual space or intelligent model or for starting new activities.

[0101] This invention is a system that operates an intelligent model that mimics the human brain in a virtual space, and accelerates time in the virtual space, thereby efficiently generating and acquiring innovation and culture.

[0102] Server processing

[0103] Setting up and building a virtual space

[0104] The server sets the basic structure of the virtual space. Specifically, it sets elements such as the terrain, climate, and social systems. For example, it models cities in mountainous regions and warm climates. The server also sets a time acceleration factor, making time progress faster in the virtual space than in reality. This can be set so that one second is equivalent to one year.

[0105] Intelligent Model Instantiation

[0106] The server generates multiple intelligent models modeled after the human brain. Each intelligent model has different characteristics and skill sets. For example, there is a model specializing in energy engineering and another specializing in art. These intelligent models operate autonomously within the virtual space, growing and developing as they interact with each other.

[0107] Running an activity simulation

[0108] The server simulates the activities of intelligent models in a virtual space. For example, an intelligent model specializing in energy engineering researches new energy sources, while an intelligent model specializing in economics analyzes their social impact. This results in the creation of new technologies and cultures.

[0109] Data collection and analysis

[0110] The server stores the innovations and cultures generated in the virtual world in a database. The collected data is analyzed by the server to identify useful technologies and cultures. The results of this analysis are used for patent applications and real-world applications.

[0111] Processing by the terminal

[0112] Providing a user interface

[0113] The terminal provides users with an interface that visualizes the status of the virtual space and the activities of the intelligent models in real time. For example, a dashboard visually displays the activity history of each intelligent model and the progress of inventions. The terminal is also designed to make it easy for users to search for information on specific innovations or cultures.

[0114] Receiving and sending feedback

[0115] The device receives feedback from the user and sends it to the server. For example, the user can input an idea for a new energy source, and the idea is tested in the virtual space. The server then modifies the virtual space and intelligent model based on the received feedback and starts a new simulation.

[0116] User Action

[0117] Observation and intervention in virtual spaces

[0118] Users can observe the state of the virtual space through their devices. For example, they can check the development of the virtual city and the activity history of the intelligent model in real time. Furthermore, users can intervene in the virtual space and the intelligent model. Specifically, they can introduce new technologies into the virtual space and observe their effects.

[0119] Specific examples

[0120] Simulation of the invention of a new energy source

[0121] 1. Virtual Space Setup: The server sets up terrain data to simulate a mountainous city, with a warm climate and medium energy demands.

[0122] 2. Generation of intelligent models: The server generates an intelligent model specialized in energy engineering and an intelligent model specialized in socioeconomics, and provides initial data to each.

[0123] 3. Start of activity simulation: The server simulates the research and development of new energy sources in a virtual city. The energy engineering model conducts research on new technologies, and the economics model analyzes the economic impact of the technologies.

[0124] 4. Data collection and analysis: The server stores the generated data on the new energy sources in a database and analyzes them. Based on the analysis results, a patent application is prepared.

[0125] An example prompt is:

[0126] "Simulate the research and development of new energy sources. Set a virtual city with the following parameters: terrain is mountainous, climate is temperate, and energy demand is moderate. Use an AI specialized in energy engineering and an AI specialized in socioeconomics to analyze the development of new technologies and their economic impact."

[0127] In this way, this invention provides an innovative system for efficiently generating and acquiring new technologies and cultures and applying them to the real world.

[0128] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0129] Step 1:

[0130] The server sets up the virtual space. As input, the server receives basic parameters such as topography, climate, and social systems. Based on these parameters, it processes data to build a digital environment. Specifically, it inputs topographical data for mountainous areas and information on temperate climates, and generates the basic structure of a virtual city based on that data. The output is the basic structure of the virtual space.

[0131] Step 2:

[0132] The server instantiates intelligent models. The server receives input parameters for generating intelligent models with different characteristics and skill sets. For example, information for generating an AI model specialized in energy engineering or an AI model specialized in art is used as input. The server instantiates an intelligent model based on these parameters and inputs the initial skill set and knowledge base. The output is the generated multiple intelligent models.

[0133] Step 3:

[0134] The server runs the activity simulation. The inputs are the virtual space setting information and the generated intelligent model. The server sets up a scenario in which the intelligent model will operate autonomously, and by setting a time acceleration factor, it simulates a time progression speed where, for example, one second is equivalent to one year. In concrete terms, an AI specialized in energy engineering researches new energy sources, while another AI analyzes the social impact of that technology. The output here is data on the generated technology and culture.

[0135] Step 4:

[0136] The server collects and analyzes data. It receives as input data on technology and culture generated as a result of the activity simulation. The server stores this data in a database and applies analytical algorithms to extract useful information. Specifically, it records the development process and results of new energy technologies in the database and performs data analysis to identify highly energy-efficient technologies. The output from this process is the analysis results. Based on these results, patent applications are prepared.

[0137] Step 5:

[0138] The terminal provides a user interface. As input, it receives data on the virtual space and the activity status of the intelligent models sent from the server. The terminal visualizes this data and displays it on a dashboard so that the user can easily understand it. Specifically, it graphically displays the activity history of each intelligent model, research progress, and data on the generated technology. Here, the visualized information is provided to the user as output.

[0139] Step 6:

[0140] The device receives and sends feedback. As input, it receives feedback and suggestions from users. The device converts this into an appropriate format and sends it to the server. For example, a user can input a suggestion for a new energy-efficient technology and send the suggestion to the server for testing in the virtual space. Here, the output is the feedback sent to the server.

[0141] Step 7:

[0142] The user observes the virtual space and intervenes. The input is visualized data provided by the terminal. Based on this data, the user makes specific interventions in the virtual space or intelligent model. For example, a new technology can be introduced into the virtual space and its impact can be observed in real time. A specific action involves the user introducing a new energy technology into a virtual city and analyzing the economic impact of that technology. The output is the results of the intervention and feedback.

[0143] Through these steps, inventions can utilize intellectual models to efficiently generate new technologies and cultures and apply them to the real world.

[0144] (Application example 1)

[0145] 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."

[0146] Production planning in modern factories involves complex intertwining factors, making it difficult to create efficient and optimal plans. Furthermore, conventional simulation and optimization methods require enormous computational resources and time, making real-time adjustments and optimization difficult. This creates a need for efficient production plans that can be quickly applied to actual production lines. Furthermore, a means of quickly and effectively incorporating user feedback is also required.

[0147] 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.

[0148] In this invention, the server includes means for simulating virtual factory settings, equipment layout, and production lines in a virtual environment, means for generating artificial intelligence models with different skill sets and optimizing production plans in the virtual factory, and means for accelerating the time in the virtual environment. This enables efficient simulation of various production plans in a short period of time and the derivation of optimal production plans. Furthermore, by quickly applying these optimized plans to a real production line, efficient production management and optimal resource utilization can be achieved. Furthermore, by incorporating user feedback in real time, the latest and optimal production plans can be maintained.

[0149] A "virtual factory" is a virtual environment that mimics a real factory, where the layout of equipment and the structure of production lines are simulated on a computer.

[0150] "Equipment layout" refers to the layout of machines and devices within a factory, and is a factor that affects production efficiency and work flow.

[0151] A "production line" is a series of steps organized into a single flow during the manufacturing process of a product, and is an important element for efficient production.

[0152] An "artificial intelligence model" is a computational model designed to mimic human intelligence and perform machine learning and data analysis.

[0153] "Different skill sets" refer to the unique collection of abilities and expertise each AI model possesses, enabling it to perform well in specific fields.

[0154] "Accelerating time in a virtual environment" means making time pass faster in a virtual environment than in the real world, a means of observing long-term effects in the short term.

[0155] "Optimization" refers to adjusting systems and processes to achieve the best results for a specific purpose, with the aim of operating efficiently.

[0156] "Feedback" refers to opinions and impressions provided by users, and is information used to help improve systems and processes.

[0157] "Real-time" refers to processing and responses that are carried out in line with the real time axis, meaning that results are obtained almost immediately.

[0158] A "production plan" is a plan for production activities in a factory, including resource allocation, process order, schedule, etc.

[0159] "Simulation" is a method of imitating real-world systems and processes in a virtual environment to make predictions and analyses.

[0160] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment to efficiently generate and acquire inventions and culture. This system is composed of a server, terminals, and users, each playing their own role.

[0161] Server processing

[0162] Setting up and building a virtual environment

[0163] The server configures the virtual factory, equipment layout, and production line configuration. It generates multiple AI models with different skill sets and runs them in the virtual environment. It also accelerates the time in the virtual environment, running short-term and long-term simulations. For example, it can simulate the layout that maximizes factory production efficiency and the optimal production line.

[0164] Artificial Intelligence Instance Generation

[0165] The server generates multiple artificial intelligence (AI) models with different characteristics and skill sets. Each AI model excels in a specific skill and performs activities to optimize the factory's production plan. For example, some AI models specialize in quality control, while others optimize production schedules.

[0166] Running an activity simulation

[0167] The server simulates the AI's activities within the virtual factory, allowing it to test different production plans and derive the most efficient one. The generated data is stored in a database and later analyzed. For example, different production lines and layout patterns can be tried to find the optimal combination.

[0168] Data collection and analysis

[0169] The server stores production plans and other data generated within the virtual environment in a database and provides tools to analyze this data and identify the most useful techniques and plans. For example, the generated data can be used to find the optimal plan to reduce production costs.

[0170] Processing by the terminal

[0171] Providing a user interface

[0172] The terminal provides users with an interface that visualizes the virtual factory settings and AI activity in real time. For example, a dashboard displays the efficiency and quality status of each production line. The terminal is also designed to allow users to easily search and access information related to specific production plans.

[0173] Receiving and sending feedback

[0174] The terminal receives feedback from the user and sends it to the server. The feedback is used to improve the system and propose new production plans. For example, the user can input a new equipment layout proposal and try it out in the virtual environment.

[0175] User Action

[0176] Virtual Factory Observation and Intervention

[0177] Users can observe the status of the virtual factory through their terminals. For example, they can check the efficiency and quality fluctuations of the virtual factory's production line in real time. Users can also intervene in the virtual environment and artificial intelligence. For example, they can introduce a specific production plan into the virtual environment and observe its effects.

[0178] Specific examples

[0179] For example, to simulate the optimization of a new production line in a virtual factory:

[0180] 1. Setting up the virtual environment: The server sets up the factory equipment layout and basic data for the production line.

[0181] 2. Generation of artificial intelligence: The server generates an AI model that is strong in areas such as efficiency, quality control, and schedule management.

[0182] 3. Start of activity simulation: The server simulates the testing of a new production plan in the virtual factory. Each AI model cooperates to optimize the plan.

[0183] 4. Data collection and analysis: The server collects and analyzes data related to the generated production plan. Based on the analysis results, the optimal plan is applied to the real-world factory.

[0184] As a result, the present invention can provide an innovative system for quickly generating an efficient production plan and applying it to a real factory.

[0185] Example prompt for a generative AI model:

[0186] "Simulate a new production plan within this virtual factory. Consider the efficiency, quality, and schedule of each production process and propose the optimal production plan."

[0187] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0188] Step 1:

[0189] Virtual Factory Configuration

[0190] The server sets and builds the basic data of the virtual factory (terrain, climate, equipment layout, production lines, etc.). The input is the factory's equipment information and layout diagram, and the output is a factory model in the virtual environment. Specifically, the server reads the terrain data and 3D models and places them in the virtual space.

[0191] Step 2:

[0192] Generating artificial intelligence models

[0193] The server generates artificial intelligence models with different skill sets. The input is the skill set information to be given to each AI model, and the output is the generated AI model. Specifically, it instantiates AI with engineering concepts, AI specialized in quality control, AI specialized in schedule optimization, etc., and places them in the virtual environment.

[0194] Step 3:

[0195] Starting the simulation

[0196] The server simulates AI activity within a virtual factory. The input is the virtual environment and AI model, and the output is the simulation result data. The server accelerates time to test multiple scenarios at high speed. Specifically, it calculates fluctuations in production line efficiency and quality, and executes the plans proposed by each AI model.

[0197] Step 4:

[0198] Data collection

[0199] The server collects data generated within the virtual environment. The input is activity data obtained from the simulation, and the output is data stored in a database. Specifically, metrics such as production efficiency and costs from each simulation are collected and stored in the database.

[0200] Step 5:

[0201] Data analysis

[0202] The server analyzes the collected data. The input is simulation data retrieved from the database, and the output is the identification of the optimal production plan and technology. The server applies statistical analysis and machine learning algorithms to derive useful results. Specifically, it identifies the most efficient plan or the least costly plan.

[0203] Step 6:

[0204] Visualizing the results

[0205] The terminal presents the analysis results to the user. The input is the analyzed data, and the output is a report displayed on the user interface. Specifically, the dashboard displays items such as production efficiency, quality control, and costs in graphs and tables.

[0206] Step 7:

[0207] Receiving Feedback

[0208] The terminal receives feedback input from the user. The input is the user's feedback information, and the output is feedback data sent to the server. In concrete terms, the user inputs new placement plans or improvement plans, which are then sent to the server.

[0209] Step 8:

[0210] Reflecting feedback

[0211] The server adjusts and updates the virtual factory and AI model based on the received feedback. The input is the feedback data from the user, and the output is an updated virtual environment and AI model. Specifically, the server incorporates the user's proposed layout plan into the simulation and tests its efficiency again.

[0212] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0213] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment, accelerating time to efficiently generate and acquire inventions and culture, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to dynamically respond to the user's emotions. This system is composed of the roles of a server, a terminal, and a user.

[0214] Server processing

[0215] Setting up and building a virtual environment

[0216] The server sets the basic structure of the virtual environment (topography, climate, social systems, etc.). Specifically, it creates a virtual environment modeled on the topography of a city and sets the physical laws and environmental variables (temperature, humidity, etc.).

[0217] Next, we set a time acceleration factor to accelerate the time in the virtual environment, which allows us to simulate several hours of virtual environment in one second of real time.

[0218] Artificial Intelligence Instance Generation

[0219] The server generates multiple AI models modeled after the human brain, each with different characteristics and skill sets—for example, one AI model might specialize in engineering, while another might be interested in art.

[0220] The generated AIs begin to operate autonomously within the virtual environment, cooperating and interacting with each other to create new inventions and cultures.

[0221] Running an activity simulation

[0222] The server simulates the activities of the AIs in the virtual environment, collects data on the inventions and cultures generated by each AI, and stores it in a database.

[0223] For example, observe the process of research and development of new energy technologies within a virtual city and save the results.

[0224] Data collection and analysis

[0225] The server analyzes the collected data to identify technologies and cultures that are useful in the real world, generates patent documents based on the analyzed data, and prepares patent applications.

[0226] It also includes the ability to provide appropriate feedback to help users access the system.

[0227] Processing by the terminal

[0228] Providing a user interface

[0229] The device provides an interface that visualizes the status of the virtual environment and the activity of the AI ​​in real time, allowing the user to check the progress of the virtual environment and the activity history of the AI ​​through this interface.

[0230] For example, a dashboard-style interface will clearly display the activities of each AI and the status of ongoing projects.

[0231] Receiving and sending feedback

[0232] The device receives feedback from the user and sends it to the server, where the user can input new ideas and suggestions for improvement, which are then reflected in the system.

[0233] For example, you can enter an idea for a new energy technology and watch it being tested in a virtual environment.

[0234] Incorporating an emotion engine

[0235] emotion recognition

[0236] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to recognize the user's emotions in real time. The server dynamically adjusts the virtual environment and artificial intelligence settings based on this emotional data.

[0237] For example, if it senses that the user is excited, it may speed up projects within the virtual environment or add new, challenging tasks.

[0238] Emotion-based responses

[0239] The emotion engine recognizes user emotions and adjusts the AI's responses and behaviors in real time, improving the user experience and increasing the system's effectiveness.

[0240] For example, if a user is dissatisfied, the AI ​​will be instructed to prioritize resolving that issue.

[0241] User Action

[0242] Virtual environment observation and intervention

[0243] Users can observe the virtual environment through their terminals and intervene if necessary, for example to observe the impact of the introduction of new technology or to issue instructions to accelerate a particular project.

[0244] By providing feedback on new technologies and improvement ideas from users, the impact of these can be reflected in the virtual environment.

[0245] Specific examples

[0246] For example, to simulate the invention of a new energy source:

[0247] 1. Setting up the virtual environment: The server builds a city model and sets up the climatic conditions and energy demands.

[0248] 2. Generation of artificial intelligence: The server generates an artificial intelligence model specialized in energy engineering and an artificial intelligence model knowledgeable in socioeconomics.

[0249] 3. Start of activity simulation: The server simulates the activities of these artificial intelligences in advancing research and development of new energy sources within the virtual city.

[0250] 4. Use of emotion engine: The device detects the user's emotions, such as excitement or anxiety, and sends that data to the server, which then adjusts the AI's behavior based on that information.

[0251] 5. Data Collection and Analysis: The server collects and analyzes data on new energy sources, identifies useful technologies, and uses the results in patent applications.

[0252] In this way, the present invention provides a more adaptive and effective invention creation system in a virtual environment by appropriately reflecting the user's emotions.

[0253] The processing flow will be explained below.

[0254] Step 1:

[0255] The server sets the basic structure of the virtual environment. It generates terrain data within the virtual environment and establishes climatic conditions and social systems. For example, it models the terrain of a city and places the necessary infrastructure and housing. It also sets the laws of physics and environmental variables (temperature, humidity, etc.).

[0256] Step 2:

[0257] The server sets a time acceleration factor, which sets the passage of time in the virtual environment to hundreds of seconds of virtual time per second of real time, allowing long-term changes to be observed in a short period of time.

[0258] Step 3:

[0259] The server generates multiple AI models modeled after the human brain, each with its own unique characteristics and initial skill set. For example, one AI may be good at engineering, while another may be talented in art.

[0260] Step 4:

[0261] The server then configures the generated AI to begin acting autonomously, creating an environment in which AIs can influence each other and develop, for example, working together to develop new energy technologies for a city.

[0262] Step 5:

[0263] The server simulates the activities of AI within a virtual environment, collects data on inventions and culture generated by the AI, and stores it in a database. For example, it observes the process of developing new energy technologies within a virtual city and records the results.

[0264] Step 6:

[0265] The server analyzes the collected data, identifies technologies and cultures that are useful in the real world, generates patent documents based on the analysis results, prepares patent applications, and provides appropriate feedback to users to allow them to access the system.

[0266] Step 7:

[0267] The device provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time. Through this interface, the user can observe the progress of the virtual environment and the activity history of the AI. For example, a dashboard-style interface displays the activities of each AI and the progress of the project.

[0268] Step 8:

[0269] The device receives feedback from the user and sends it to the server, for example, a user can input an idea for a new energy technology, which is then tested in the virtual environment.

[0270] Step 9:

[0271] The server dynamically adjusts the settings of the virtual environment and the AI ​​based on user feedback by analyzing the feedback and reflecting it in a way that affects the behavior of the virtual environment and the AI.

[0272] Step 10:

[0273] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize the user's emotions in real time. The server receives the recognized emotion data and adjusts the behavior of the virtual environment and artificial intelligence based on it. For example, if the user is excited, it may accelerate projects in the virtual environment or add new, challenging tasks.

[0274] Step 11:

[0275] The device adjusts the AI's responses and behavior in real time based on the user's emotions recognized by the emotion engine. For example, if the user is feeling dissatisfied, the AI ​​will be set to prioritize solving that problem.

[0276] Step 12:

[0277] The server stores the emotion data recognized by the emotion engine in a database for later analysis. This allows the server to accumulate a user's emotion history, enabling more accurate emotion recognition and response.

[0278] In this way, a system is realized in which the server, terminal, user, and emotion engine cooperate to efficiently generate new inventions and culture through the activities of artificial intelligence within a virtual environment and utilize them in the real world.

[0279] Example 2

[0280] 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."

[0281] Conventional AI systems have been inefficient in generating new inventions and culture, and have difficulty dynamically responding to user emotions. This has led to problems such as a poor user experience and limited system effectiveness. Furthermore, there has been a lack of means to rapidly collect and analyze large amounts of data by accelerating time in virtual environments.

[0282] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0283] In this invention, the server

[0284] A means for operating multiple artificial intelligences that mimic the human brain in a virtual environment;

[0285] means for accelerating time in a virtual environment in which said artificial intelligence operates;

[0286] A means for acquiring inventions and cultures generated within the virtual environment and storing them in a database;

[0287] A means for analyzing the acquired inventions and cultures and identifying useful technologies;

[0288] means for recognizing a user's emotions and dynamically adjusting settings of the virtual environment and artificial intelligence based on said emotion data;

[0289] Includes.

[0290] This not only enables the efficient creation of new inventions and cultures in virtual environments, but also enables dynamic responses to users' emotions, improving the quality of the user experience. Furthermore, time acceleration allows for the rapid collection and analysis of large amounts of data, facilitating applications in the real world.

[0291] "Artificial intelligence" refers to computer systems that mimic human intelligence and have capabilities such as learning, reasoning, and self-correction.

[0292] A "virtual environment" is a simulated environment generated on a computer system, in which physical laws, social systems, etc. can be set.

[0293] "Time acceleration" is a function that allows time in a virtual environment to progress faster than real time.

[0294] A "database" is a collection of electronically stored data, and a system that allows for efficient searching, management, and updating of necessary data.

[0295] The "emotion engine" is a function that recognizes the user's emotions in real time and adjusts the system's operation based on that emotional data.

[0296] "Feedback" refers to opinions and reactions provided by users to a system.

[0297] "Dynamic adjustment" is the ability of a system to automatically change its behavior and settings based on real-time data and conditions.

[0298] "Analysis" is the process of analyzing collected data and deriving useful information and insights from it.

[0299] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment, accelerating time and efficiently generating and acquiring inventions and culture. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system enables dynamic responses according to the user's emotions. This system is composed of a server, a terminal, and a user, each playing a role.

[0300] Server processing

[0301] The server uses Python or a similar programming language to build the virtual environment. It uses a simulation engine to create a city model, set physical laws and environmental variables, and set a time acceleration factor to accelerate the progression of time in the virtual environment.

[0302] Next, machine learning libraries such as TensorFlow and PyTorch are used to generate multiple AI models that mimic the human brain. Each AI model is given different characteristics and skill sets, and begins to operate autonomously within the virtual environment. The server collects the data generated by these AI models and stores it in a database.

[0303] The server then applies machine learning algorithms to analyze the collected data, identifying useful technologies and cultures and automatically generating patent application documents based on the analysis results.

[0304] Processing by the terminal

[0305] The device provides a user interface using a web application or dedicated software. This interface allows users to visualize the status of the virtual environment and the activity of the AI ​​in real time. Various data is displayed in dashboard format, making operation easy.

[0306] Users can provide feedback through their devices, which can be specific ideas or suggestions for improvement, and the devices then send this to the server, which then dynamically adjusts the virtual environment and AI settings based on this feedback.

[0307] Incorporating an emotion engine

[0308] The emotion engine uses OpenCV and TensorFlow to analyze the user's facial expressions, voice, and text data in real time. The analysis results are sent to the server as emotion data, and the server dynamically adjusts the virtual environment and artificial intelligence settings based on this data.

[0309] For example, if the user is excited, the server will accelerate projects in the virtual environment or add new challenging tasks, and if the user is frustrated, the artificial intelligence will be instructed to prioritize solving that problem.

[0310] Specific examples

[0311] For example, to simulate the invention of a new energy source, we proceed as follows:

[0312] 1. Setting up the virtual environment: The server builds a city model and sets up the climatic conditions and energy demands.

[0313] 2. Generation of artificial intelligence: The server generates an artificial intelligence model specialized in energy engineering and an artificial intelligence model knowledgeable in socioeconomics.

[0314] 3. Start of activity simulation: The server simulates the activities of these artificial intelligences in advancing research and development of new energy sources within the virtual city.

[0315] 4. Use of emotion engine: The device detects the user's emotions, such as excitement or anxiety, and sends that data to the server, which then adjusts the AI's behavior based on that information.

[0316] 5. Data Collection and Analysis: The server collects and analyzes data on new energy sources, identifies useful technologies, and uses the results in patent applications.

[0317] Example prompt: "I would like to present an idea for a new energy technology and observe how it evolves in a virtual environment."

[0318] As described above, the present invention provides an efficient and effective invention generation system that combines a virtual environment and dynamic responses based on the user's emotions.

[0319] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0320] Step 1: Configure and build a virtual environment

[0321] The server uses Python to create a virtual environment. Using a simulation engine like SimCity, it models the topography of a city and sets environmental variables such as climate conditions and energy demand. Parameters such as the city name, temperature, and humidity are received as input. Data processing involves generating a virtual environment based on these parameters. The output is a model of the constructed virtual city. Specifically, the server executes commands such as "simcity.create_city('Tokyo', temperature=25, humidity=60)".

[0322] Step 2: Setting time acceleration

[0323] The server sets a time acceleration factor to accelerate time in the virtual environment. As input, it receives a time acceleration factor value. As data processing, it applies this factor to the time variables of the virtual environment. As output, it obtains an accelerated time environment. Specifically, the server executes the command "simcity.set_time_acceleration(100)".

[0324] Step 3: Instantiating the Artificial Intelligence

[0325] The server generates an artificial intelligence model using TensorFlow or PyTorch. As input, it receives the type of AI model and its skill set. As data processing, it generates AI instances with different characteristics and skills based on this information. As output, it obtains the generated AI instances. Specifically, the server executes a command such as "ai_instance = AIModel('Engineer', skills=['mechanics', 'dynamics'])".

[0326] Step 4: Start the activity simulation

[0327] The server makes the generated AI model operate autonomously within the virtual environment. As input, it receives the AI ​​model and task information. As data processing, it assigns a task to the AI ​​model and begins operating within the virtual environment. As output, it obtains the AI ​​model's activity data and deliverables. Specifically, the server executes the command "simcity.assign_task(ai_engineer, 'develop energy source')".

[0328] Step 5: Data collection and storage

[0329] The server collects the activity data of the AI ​​model and stores it in a database. As input, it receives the activity data of the AI ​​model. As data processing, it organizes this data and converts it into a format that can be stored in the database. As output, it obtains the data stored in the database. Specifically, the server executes the code "database.save('energy_research_results', ai_engineer.results)".

[0330] Step 6: Data analysis and technology identification

[0331] The server analyzes the collected data and identifies useful technologies. As input, it receives stored activity data. As data processing, it analyzes the data using machine learning algorithms and identifies useful technologies. As output, it obtains information about the identified technologies. Specifically, the server executes the command "analyze_data('energy_research_results')".

[0332] Step 7: Providing a User Interface

[0333] The device provides a user interface and visualizes the virtual environment and AI activity in real time. It uses the activity data received from the server as input. It converts this data into a format that can be visualized as data processing. It outputs a dashboard-style interface. Specifically, the device executes the code "dashboard.update('AI Activity', ai_activity_data)".

[0334] Step 8: Receiving and sending feedback

[0335] The device receives feedback from the user and sends it to the server. As input, it receives the user's feedback data. As data processing, it converts this feedback data into an appropriate format. As output, it sends the feedback to the server. Specifically, the device executes the code "user_feedback = get_user_input()" and "send_to_server(user_feedback)".

[0336] Step 9: Emotion recognition and dynamic regulation

[0337] The server uses an emotion engine to recognize the user's emotions in real time. As input, it receives the user's facial expressions, voice, and text data. As data processing, it analyzes this data to identify emotions. As output, it obtains the user's emotion data. Specifically, the server executes the code "emotion = detect_emotion(camera_feed)" and "send_to_server(emotion_data)".

[0338] Step 10: Dynamic adjustment of virtual environment and AI

[0339] The server dynamically adjusts the virtual environment and artificial intelligence settings based on the acquired emotional data. It receives emotional data as input. It processes the data by changing the AI's behavior and virtual environment settings based on this data. It outputs the adjusted virtual environment and AI behavior data. Specifically, the server executes the command "adjust_AI_behavior(emotion_data)".

[0340] (Application example 2)

[0341] 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."

[0342] When autonomous vehicles are operating, various unexpected situations and obstacles can occur. These can increase passenger anxiety and discomfort, resulting in problems such as reduced operational efficiency and safety. Furthermore, it is necessary to properly identify passenger emotions and respond flexibly accordingly, but current systems are inadequate in this regard. Therefore, it is necessary to provide flexible responses to unexpected situations and dynamic measures according to passenger emotions.

[0343] 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.

[0344] In this invention, the server includes means for operating multiple artificial intelligences modeled on the human brain in a virtual environment, means for accelerating time in the virtual environment, means for acquiring inventions and cultures generated in the virtual environment and storing them in a database, means for analyzing the acquired inventions and cultures and identifying useful technologies, means for managing the operation of the autonomous vehicle, recognizing and dynamically responding to user emotions, and means for the autonomous vehicle to search for an alternative route in the event of an obstacle and providing measures to reassure passengers based on their emotions. This enables the autonomous vehicle to respond flexibly to unexpected situations and quickly and appropriately to passenger emotions.

[0345] "Artificial intelligence" is a system that performs intellectual tasks using algorithms and programs that mimic the functions of the human brain.

[0346] A "virtual environment" is a model of the real world reproduced on a computer system, and is a simulated space that includes elements such as terrain, climate, and social systems.

[0347] "Means of accelerating time" is a technology that allows time in a virtual environment to pass faster than actual time, making it possible to simulate a long period of time in a short period of time.

[0348] A "database" is an information system for efficiently storing, searching, and managing large amounts of data, and stores data on the aforementioned inventions and cultures.

[0349] An "autonomous mobile object" is a machine that operates and moves on its own initiative without the need for external control, and specifically refers to self-driving vehicles.

[0350] "Means for recognizing emotions" refers to technology that identifies a user's psychological state by analyzing the user's facial expressions, voice, text data, etc.

[0351] "Dynamic response means" refers to the ability to adjust the system in real time according to the situation and the user's emotions, and to execute the optimal response or action.

[0352] The "means for searching alternative routes" is an algorithm that considers new routes and allows a moving vehicle to adopt the optimal route depending on traffic conditions and obstacles.

[0353] "Reassuring measures" are measures or actions to reduce the user's anxiety or stress, and include, for example, playing music or providing information.

[0354] System Configuration

[0355] The system of the present invention is realized with the following configuration.

[0356] Server processing

[0357] 1. Configure and build the virtual environment:

[0358] The server first sets up a virtual environment, creating a virtual space modeled on the city's topography and climate. It also sets the laws of physics and environmental variables within this virtual environment. It also sets a time acceleration factor, allowing the virtual environment to progress faster than real time.

[0359] 2. Artificial Intelligence Generation:

[0360] The server generates multiple AIs modeled after the human brain, each with its own unique characteristics and skills. For example, models specializing in energy engineering and socioeconomics are included. These AIs operate autonomously within the virtual environment, generating new inventions and cultures.

[0361] 3. Data Collection and Analysis:

[0362] The server collects data on inventions and cultures generated in the virtual environment, stores it in a database, and analyzes the collected data to identify technologies and cultures that are useful in the real world, enabling the generation of patent documents and patent applications.

[0363] Processing by the terminal

[0364] 1. Real-time visualization:

[0365] The device provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time, allowing the user to observe the virtual environment and the activities of the AI ​​in detail.

[0366] 2. Incorporating feedback:

[0367] The device receives feedback from the user and sends it to a server, which dynamically adjusts the settings of the virtual environment and artificial intelligence based on this feedback.

[0368] Incorporating an emotion engine

[0369] 1. Emotion recognition:

[0370] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize the user's emotions in real time. This emotional data is received by the server and used to adjust the behavior of the virtual environment and artificial intelligence.

[0371] 2. Emotion-based responses:

[0372] Based on the user's emotions, the server adjusts the autonomous vehicle's behavior and responses in real time. For example, if the user feels anxious, the server may search for an alternative route.

[0373] Hardware and software used

[0374] Hardware: Autonomous mobile devices (e.g., self-driving cars), high-performance server computers (e.g., NVIDIA Drive)

[0375] Software: Python programming language, machine learning libraries (e.g., TensorFlow), emotion recognition libraries (e.g., OpenCV)

[0376] Specific examples

[0377] For example, consider an application example when traffic congestion occurs.

[0378] 1. The server runs an autonomous vehicle in a virtual environment where random traffic jams may occur.

[0379] 2. At this point, the autonomous vehicle's artificial intelligence will become anxious and search for an alternative route.

[0380] 3. The user can observe this situation through the device and provide feedback as needed, for example, allowing the user to suggest valid alternative routes.

[0381] 4. The emotion engine recognizes the user's anxiety and communicates it to the server, which then adjusts the AI's behavior and takes steps to alleviate the anxiety.

[0382] Prompt Sentence Examples

[0383] A prompt to input to a generative AI model how a self-driving vehicle will behave in a given traffic situation:

[0384] When an autonomous vehicle is traveling according to a city model, it suddenly encounters a traffic jam. Considering that the ongoing load factor is 0.8, what should be the next action? The emotional state of the vehicle is anxious, but please also suggest ways to reassure the passengers.

[0385] In this way, the present invention enables dynamic and adaptive responses according to the user's emotions, thereby enhancing the operation management of autonomous vehicles.

[0386] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0387] Step 1: Configure and build a virtual environment

[0388] The server sets the basic structure of the city, including its topography, climate, and social systems. At the same time, it also sets the laws of physics and environmental variables (temperature, humidity, etc.). Using city model data as input, a virtual environment is constructed as output. Specifically, a 3D model of the city is generated using computer graphics and run on a simulation engine.

[0389] Step 2: Generate artificial intelligence

[0390] The server generates multiple AI models modeled after the human brain. Different characteristics and skills are input to each AI. The input is data defining the characteristics and skills, and the output is the generation of multiple AI instances. Specifically, machine learning algorithms are applied to each AI model, and specific skills are learned using training data.

[0391] Step 3: Set the time acceleration factor

[0392] The server sets a time acceleration factor to accelerate time in the virtual environment. The input is the time acceleration factor, and the output is the speed of virtual time relative to real time. Specifically, the server controls the progression of time in the virtual environment by changing the simulation time step.

[0393] Step 4: Simulating AI activity

[0394] The server simulates the activities of the AI ​​generated within the virtual environment. The virtual environment, AI instances, and environmental variables are used as input, and the AI's activity history data is generated as output. Specifically, each AI acts autonomously within the simulation engine and performs designated tasks.

[0395] Step 5: Collect and store data

[0396] The server collects data on the AI's activities within the virtual environment, as well as the inventions and cultural data it generates, and stores them in a database. Simulation data is used as input, and an organized database is generated as output. Specifically, a data collection agent collects the activity data of each AI and stores it in the database in an appropriate format.

[0397] Step 6: Data analysis and feedback

[0398] The server analyzes the data stored in the database to identify useful technologies and generates patent documents based on the analysis results. The acquired data is used as input, and an analysis report and patent documents are generated as output. Specifically, data analysis algorithms are used to identify interesting patterns and generate technology feasibility reports.

[0399] Step 7: Real-time visualization

[0400] The device displays the status of the virtual environment and the activity of the AI ​​in real time. It uses the virtual environment and AI activity data as input and provides a visualized graphical interface as output. Specifically, it displays real-time data in a dashboard format while updating it.

[0401] Step 8: Incorporating user feedback

[0402] The device receives feedback from the user and sends it to the server. The server dynamically adjusts the virtual environment and AI based on the feedback. The user's feedback data is used as input, and the parameters of the virtual environment and AI are dynamically updated as output. Specifically, after receiving the feedback data, the simulation parameters are recalculated and applied in real time.

[0403] Step 9: Emotion recognition and response adjustment

[0404] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize their emotional state. The server then adjusts the AI's behavior based on this information. The input is the user's emotional data, and the output is an emotion-based response action. Specifically, the emotion recognition software performs real-time analysis and takes reassuring action as needed.

[0405] Step 10: Encountering obstacles and finding alternative routes

[0406] When an autonomous vehicle encounters a fault in the virtual environment or in the real world, the server searches for an alternative route and provides reassurance measures. Using fault information and current traffic information as input, the server generates the optimal alternative route and reassurance measures as output. Specifically, the server analyzes traffic congestion and accident information and presents a safe and fast alternative route.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] [Second embodiment]

[0411] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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).

[0417] 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.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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."

[0423] This invention is a system that operates multiple artificial intelligences modeled after the human brain in a virtual environment, and accelerates time in the virtual world to efficiently generate and acquire inventions and culture. This system is composed of a server, terminals, and users, each playing their own role.

[0424] Server processing

[0425] Setting up and building a virtual environment

[0426] The server sets the basic structure of the virtual environment (topography, climate, social systems, etc.) For example, it models the topography of a city and sets the physical laws and environmental variables to simulate the growth of the city.

[0427] The server sets a time acceleration factor, causing time in the virtual environment to progress faster than in reality, allowing long-term changes to be observed in a short period of time.

[0428] Artificial Intelligence Instance Generation

[0429] The server generates multiple AI models modeled after the human brain, each with different characteristics and initial skill sets—for example, one model might be good at engineering, while another might be talented at art.

[0430] These AIs operate autonomously within the virtual environment, growing and developing as they interact with each other.

[0431] Running an activity simulation

[0432] The server simulates the activities of the AI ​​in a virtual environment, observes the process of the AI ​​generating inventions and culture, and collects the generated data.

[0433] For example, the process by which new energy technologies are developed or new musical genres are formed can be simulated in a virtual urban environment.

[0434] Data collection and analysis

[0435] The server stores the inventions and cultures generated within the virtual environment in a database.

[0436] The collected data is analyzed to identify useful technologies and cultures, which then lead to patent applications and technological applications in the real world.

[0437] Processing by the terminal

[0438] Providing a user interface

[0439] The device provides the user with an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time. For example, a dashboard displays the activity history of each AI and the progress of inventions.

[0440] The terminal will have an interface designed to make it easy for users to search for information about specific inventions or cultures.

[0441] Receiving and sending feedback

[0442] The terminal receives feedback from the user and sends it to the server, which uses the feedback to improve the system or propose new inventions.

[0443] For example, a user can input an idea for a new energy source and the idea can be tested in a virtual environment.

[0444] User Action

[0445] Virtual environment observation and intervention

[0446] Users can observe the status of the virtual environment through their devices, for example, checking the development of the virtual city and the activity history of the AI ​​in real time.

[0447] Users can also intervene in the virtual environment and artificial intelligence, for example by introducing certain technologies into the virtual environment and observing their effects.

[0448] Specific examples

[0449] For example, to simulate the invention of a new energy source in a virtual environment:

[0450] 1. Setting up the virtual environment: The server sets up the basic data (topography, climate, energy demand, etc.) to simulate a city.

[0451] 2. Generation of artificial intelligence: The server generates an artificial intelligence model that is strong in energy engineering and an artificial intelligence model that is knowledgeable in socioeconomics.

[0452] 3. Start of activity simulation: The server simulates the research and development of new energy sources in a virtual city. Each AI cooperates to develop new technologies.

[0453] 4. Data collection and analysis: The server stores the generated data on the new energy sources in a database and analyzes them. Based on the analysis results, patent applications and real-world applications can be made.

[0454] In this way, the present invention provides an innovative system that can efficiently generate new technologies and cultures and utilize them in the real world.

[0455] The processing flow will be explained below.

[0456] Step 1:

[0457] The server sets the basic structure of the virtual environment. It generates terrain data within the virtual environment and establishes climatic conditions and social systems. For example, it builds a model of a city and places the necessary infrastructure and housing there. It also sets the laws of physics and environmental variables (temperature, humidity, etc.).

[0458] Step 2:

[0459] The server sets a time acceleration factor, which sets the passage of time in the virtual environment to hundreds of seconds of virtual time per second of real time, allowing long-term changes to be observed in a short period of time.

[0460] Step 3:

[0461] The server generates multiple AI models modeled after the human brain, each with its own unique characteristics and initial skill set—for example, one AI may be good at engineering, while another may be talented in art.

[0462] Step 4:

[0463] The server allows the AIs generated within the virtual environment to begin acting autonomously, creating an environment in which they can influence each other and develop, for example, working together to develop new energy technologies within a city.

[0464] Step 5:

[0465] The server simulates the AI's activities in the virtual environment, observing, for example, the invention of a new energy source or the formation of a new culture, and collecting necessary data. The AI-generated inventions and cultural data are then stored in a database.

[0466] Step 6:

[0467] The server analyzes the collected data, identifies technologies and cultures that are useful in the real world, generates patent documents based on the analysis results, prepares patent applications, and provides appropriate feedback to users to allow them to access the system.

[0468] Step 7:

[0469] The terminal provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time, allowing users to observe the activity history of each AI and the progress of their inventions.

[0470] Step 8:

[0471] The device receives feedback from users and sends it to the server. Users input and submit ideas for new inventions and system improvements, which are reflected in the virtual environment and the activities of the artificial intelligence. This allows the entire system to evolve in a way that meets user expectations.

[0472] Step 9:

[0473] Users can observe the situation in the virtual environment through their devices and intervene in specific locations or artificial intelligence, for example, to observe the impact of the introduction of new technology or to issue instructions to accelerate a specific project.

[0474] In this way, by having the server, terminal, and user fulfill their respective roles, a system is realized in which new inventions and cultures can be efficiently generated and acquired through the activities of artificial intelligence within the virtual environment, and then utilized in the real world.

[0475] Example 1

[0476] 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."

[0477] Conventional artificial intelligence systems have had problems with the efficient creation and acquisition of new technologies and cultures. They also lack the ability to manage time in virtual environments, visualize the activities of intelligent models with diverse characteristics, and incorporate user feedback. Therefore, there has been a need for a system that can solve these problems and efficiently create and acquire new technologies and cultures using an intelligent model that mimics the human brain.

[0478] 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.

[0479] In this invention, the server includes a means for operating a plurality of intelligent models imitating the human brain in a virtual space, a means for accelerating the time of the virtual space in which the intelligent models are active, a means for acquiring innovations and cultures generated in the virtual space and storing them in an information base, and a means for analyzing the acquired innovations and cultures and identifying useful technologies, thereby enabling the efficient generation and acquisition of new technologies and cultures using intelligent models.

[0480] An "intelligent model" is an information processing system that mimics the human brain, has multiple characteristics and capabilities, and operates autonomously within a virtual space.

[0481] A "virtual space" is a virtual environment that mimics a real physical environment using digital technology, allowing people and intelligent models to interact with each other.

[0482] "Time acceleration" is a technique that sets the speed at which time progresses in a virtual space to be faster than real time, allowing long-term changes and developments to be observed in a short period of time.

[0483] "Innovation" is a general term for new technologies, ideas, or inventions generated within the virtual world.

[0484] "Culture" is a general term for new art forms, music, literature, customs, or other social phenomena that are generated within virtual spaces.

[0485] An "information base" is a digital storage system for storing innovations and culture generated within virtual space as data.

[0486] "Analysis" is the process of examining the data stored in an information base in detail to extract specific patterns and useful information.

[0487] "Feedback" refers to opinions, suggestions, or evaluations sent by users, and is information that is useful for improving the virtual space or intelligent model or for starting new activities.

[0488] This invention is a system that operates an intelligent model that mimics the human brain in a virtual space, and accelerates time in the virtual space, thereby efficiently generating and acquiring innovation and culture.

[0489] Server processing

[0490] Setting up and building a virtual space

[0491] The server sets the basic structure of the virtual space. Specifically, it sets elements such as the terrain, climate, and social systems. For example, it models cities in mountainous regions and warm climates. The server also sets a time acceleration factor, making time progress faster in the virtual space than in reality. This can be set so that one second is equivalent to one year.

[0492] Intelligent Model Instantiation

[0493] The server generates multiple intelligent models modeled after the human brain. Each intelligent model has different characteristics and skill sets. For example, there is a model specializing in energy engineering and another specializing in art. These intelligent models operate autonomously within the virtual space, growing and developing as they interact with each other.

[0494] Running an activity simulation

[0495] The server simulates the activities of intelligent models in a virtual space. For example, an intelligent model specializing in energy engineering researches new energy sources, while an intelligent model specializing in economics analyzes their social impact. This results in the creation of new technologies and cultures.

[0496] Data collection and analysis

[0497] The server stores the innovations and cultures generated in the virtual world in a database. The collected data is analyzed by the server to identify useful technologies and cultures. The results of this analysis are used for patent applications and real-world applications.

[0498] Processing by the terminal

[0499] Providing a user interface

[0500] The terminal provides users with an interface that visualizes the status of the virtual space and the activities of the intelligent models in real time. For example, a dashboard visually displays the activity history of each intelligent model and the progress of inventions. The terminal is also designed to make it easy for users to search for information on specific innovations or cultures.

[0501] Receiving and sending feedback

[0502] The device receives feedback from the user and sends it to the server. For example, the user can input an idea for a new energy source, and the idea is tested in the virtual space. The server then modifies the virtual space and intelligent model based on the received feedback and starts a new simulation.

[0503] User Action

[0504] Observation and intervention in virtual spaces

[0505] Users can observe the state of the virtual space through their devices. For example, they can check the development of the virtual city and the activity history of the intelligent model in real time. Furthermore, users can intervene in the virtual space and the intelligent model. Specifically, they can introduce new technologies into the virtual space and observe their effects.

[0506] Specific examples

[0507] Simulation of the invention of a new energy source

[0508] 1. Virtual Space Setup: The server sets up terrain data to simulate a mountainous city, with a warm climate and medium energy demands.

[0509] 2. Generation of intelligent models: The server generates an intelligent model specialized in energy engineering and an intelligent model specialized in socioeconomics, and provides initial data to each.

[0510] 3. Start of activity simulation: The server simulates the research and development of new energy sources in a virtual city. The energy engineering model conducts research on new technologies, and the economics model analyzes the economic impact of the technologies.

[0511] 4. Data collection and analysis: The server stores the generated data on the new energy sources in a database and analyzes them. Based on the analysis results, a patent application is prepared.

[0512] An example prompt is:

[0513] "Simulate the research and development of new energy sources. Set a virtual city with the following parameters: terrain is mountainous, climate is temperate, and energy demand is moderate. Use an AI specialized in energy engineering and an AI specialized in socioeconomics to analyze the development of new technologies and their economic impact."

[0514] In this way, this invention provides an innovative system for efficiently generating and acquiring new technologies and cultures and applying them to the real world.

[0515] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0516] Step 1:

[0517] The server sets up the virtual space. As input, the server receives basic parameters such as topography, climate, and social systems. Based on these parameters, it processes data to build a digital environment. Specifically, it inputs topographical data for mountainous areas and information on temperate climates, and generates the basic structure of a virtual city based on that data. The output is the basic structure of the virtual space.

[0518] Step 2:

[0519] The server instantiates intelligent models. The server receives input parameters for generating intelligent models with different characteristics and skill sets. For example, information for generating an AI model specialized in energy engineering or an AI model specialized in art is used as input. The server instantiates an intelligent model based on these parameters and inputs the initial skill set and knowledge base. The output is the generated multiple intelligent models.

[0520] Step 3:

[0521] The server runs the activity simulation. The inputs are the virtual space setting information and the generated intelligent model. The server sets up a scenario in which the intelligent model will operate autonomously, and by setting a time acceleration factor, it simulates a time progression speed where, for example, one second is equivalent to one year. In concrete terms, an AI specialized in energy engineering researches new energy sources, while another AI analyzes the social impact of that technology. The output here is data on the generated technology and culture.

[0522] Step 4:

[0523] The server collects and analyzes data. It receives as input data on technology and culture generated as a result of the activity simulation. The server stores this data in a database and applies analytical algorithms to extract useful information. Specifically, it records the development process and results of new energy technologies in the database and performs data analysis to identify highly energy-efficient technologies. The output from this process is the analysis results. Based on these results, patent applications are prepared.

[0524] Step 5:

[0525] The terminal provides a user interface. As input, it receives data on the virtual space and the activity status of the intelligent models sent from the server. The terminal visualizes this data and displays it on a dashboard so that the user can easily understand it. Specifically, it graphically displays the activity history of each intelligent model, research progress, and data on the generated technology. Here, the visualized information is provided to the user as output.

[0526] Step 6:

[0527] The device receives and sends feedback. As input, it receives feedback and suggestions from users. The device converts this into an appropriate format and sends it to the server. For example, a user can input a suggestion for a new energy-efficient technology and send the suggestion to the server for testing in the virtual space. Here, the output is the feedback sent to the server.

[0528] Step 7:

[0529] The user observes the virtual space and intervenes. The input is visualized data provided by the terminal. Based on this data, the user makes specific interventions in the virtual space or intelligent model. For example, a new technology can be introduced into the virtual space and its impact can be observed in real time. A specific action involves the user introducing a new energy technology into a virtual city and analyzing the economic impact of that technology. The output is the results of the intervention and feedback.

[0530] Through these steps, inventions can utilize intellectual models to efficiently generate new technologies and cultures and apply them to the real world.

[0531] (Application example 1)

[0532] 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."

[0533] Production planning in modern factories involves complex intertwining factors, making it difficult to create efficient and optimal plans. Furthermore, conventional simulation and optimization methods require enormous computational resources and time, making real-time adjustments and optimization difficult. This creates a need for efficient production plans that can be quickly applied to actual production lines. Furthermore, a means of quickly and effectively incorporating user feedback is also required.

[0534] 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.

[0535] In this invention, the server includes means for simulating virtual factory settings, equipment layout, and production lines in a virtual environment, means for generating artificial intelligence models with different skill sets and optimizing production plans in the virtual factory, and means for accelerating the time in the virtual environment. This enables efficient simulation of various production plans in a short period of time and the derivation of optimal production plans. Furthermore, by quickly applying these optimized plans to a real production line, efficient production management and optimal resource utilization can be achieved. Furthermore, by incorporating user feedback in real time, the latest and optimal production plans can be maintained.

[0536] A "virtual factory" is a virtual environment that mimics a real factory, where the layout of equipment and the structure of production lines are simulated on a computer.

[0537] "Equipment layout" refers to the layout of machines and devices within a factory, and is a factor that affects production efficiency and work flow.

[0538] A "production line" is a series of steps organized into a single flow during the manufacturing process of a product, and is an important element for efficient production.

[0539] An "artificial intelligence model" is a computational model designed to mimic human intelligence and perform machine learning and data analysis.

[0540] "Different skill sets" refer to the unique collection of abilities and expertise each AI model possesses, enabling it to perform well in specific fields.

[0541] "Accelerating time in a virtual environment" means making time pass faster in a virtual environment than in the real world, a means of observing long-term effects in the short term.

[0542] "Optimization" refers to adjusting systems and processes to achieve the best results for a specific purpose, with the aim of operating efficiently.

[0543] "Feedback" refers to opinions and impressions provided by users, and is information used to help improve systems and processes.

[0544] "Real-time" refers to processing and responses that are carried out in line with the real time axis, meaning that results are obtained almost immediately.

[0545] A "production plan" is a plan for production activities in a factory, including resource allocation, process order, schedule, etc.

[0546] "Simulation" is a method of imitating real-world systems and processes in a virtual environment to make predictions and analyses.

[0547] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment to efficiently generate and acquire inventions and culture. This system is composed of a server, terminals, and users, each playing their own role.

[0548] Server processing

[0549] Setting up and building a virtual environment

[0550] The server configures the virtual factory, equipment layout, and production line configuration. It generates multiple AI models with different skill sets and runs them in the virtual environment. It also accelerates the time in the virtual environment, running short-term and long-term simulations. For example, it can simulate the layout that maximizes factory production efficiency and the optimal production line.

[0551] Artificial Intelligence Instance Generation

[0552] The server generates multiple artificial intelligence (AI) models with different characteristics and skill sets. Each AI model excels in a specific skill and performs activities to optimize the factory's production plan. For example, some AI models specialize in quality control, while others optimize production schedules.

[0553] Running an activity simulation

[0554] The server simulates the AI's activities within the virtual factory, allowing it to test different production plans and derive the most efficient one. The generated data is stored in a database and later analyzed. For example, different production lines and layout patterns can be tried to find the optimal combination.

[0555] Data collection and analysis

[0556] The server stores production plans and other data generated within the virtual environment in a database and provides tools to analyze this data and identify the most useful techniques and plans. For example, the generated data can be used to find the optimal plan to reduce production costs.

[0557] Processing by the terminal

[0558] Providing a user interface

[0559] The terminal provides users with an interface that visualizes the virtual factory settings and AI activity in real time. For example, a dashboard displays the efficiency and quality status of each production line. The terminal is also designed to allow users to easily search and access information related to specific production plans.

[0560] Receiving and sending feedback

[0561] The terminal receives feedback from the user and sends it to the server. The feedback is used to improve the system and propose new production plans. For example, the user can input a new equipment layout proposal and try it out in the virtual environment.

[0562] User Action

[0563] Virtual Factory Observation and Intervention

[0564] Users can observe the status of the virtual factory through their terminals. For example, they can check the efficiency and quality fluctuations of the virtual factory's production line in real time. Users can also intervene in the virtual environment and artificial intelligence. For example, they can introduce a specific production plan into the virtual environment and observe its effects.

[0565] Specific examples

[0566] For example, to simulate the optimization of a new production line in a virtual factory:

[0567] 1. Setting up the virtual environment: The server sets up the factory equipment layout and basic data for the production line.

[0568] 2. Generation of artificial intelligence: The server generates an AI model that is strong in areas such as efficiency, quality control, and schedule management.

[0569] 3. Start of activity simulation: The server simulates the testing of a new production plan in the virtual factory. Each AI model cooperates to optimize the plan.

[0570] 4. Data collection and analysis: The server collects and analyzes data related to the generated production plan. Based on the analysis results, the optimal plan is applied to the real-world factory.

[0571] As a result, the present invention can provide an innovative system for quickly generating an efficient production plan and applying it to a real factory.

[0572] Example prompt for a generative AI model:

[0573] "Simulate a new production plan within this virtual factory. Consider the efficiency, quality, and schedule of each production process and propose the optimal production plan."

[0574] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0575] Step 1:

[0576] Virtual Factory Configuration

[0577] The server sets and builds the basic data of the virtual factory (terrain, climate, equipment layout, production lines, etc.). The input is the factory's equipment information and layout diagram, and the output is a factory model in the virtual environment. Specifically, the server reads the terrain data and 3D models and places them in the virtual space.

[0578] Step 2:

[0579] Generating artificial intelligence models

[0580] The server generates artificial intelligence models with different skill sets. The input is the skill set information to be given to each AI model, and the output is the generated AI model. Specifically, it instantiates AI with engineering concepts, AI specialized in quality control, AI specialized in schedule optimization, etc., and places them in the virtual environment.

[0581] Step 3:

[0582] Starting the simulation

[0583] The server simulates AI activity within a virtual factory. The input is the virtual environment and AI model, and the output is the simulation result data. The server accelerates time to test multiple scenarios at high speed. Specifically, it calculates fluctuations in production line efficiency and quality, and executes the plans proposed by each AI model.

[0584] Step 4:

[0585] Data collection

[0586] The server collects data generated within the virtual environment. The input is activity data obtained from the simulation, and the output is data stored in a database. Specifically, metrics such as production efficiency and costs from each simulation are collected and stored in the database.

[0587] Step 5:

[0588] Data analysis

[0589] The server analyzes the collected data. The input is simulation data retrieved from the database, and the output is the identification of the optimal production plan and technology. The server applies statistical analysis and machine learning algorithms to derive useful results. Specifically, it identifies the most efficient plan or the least costly plan.

[0590] Step 6:

[0591] Visualizing the results

[0592] The terminal presents the analysis results to the user. The input is the analyzed data, and the output is a report displayed on the user interface. Specifically, the dashboard displays items such as production efficiency, quality control, and costs in graphs and tables.

[0593] Step 7:

[0594] Receiving Feedback

[0595] The terminal receives feedback input from the user. The input is the user's feedback information, and the output is feedback data sent to the server. In concrete terms, the user inputs new placement plans or improvement plans, which are then sent to the server.

[0596] Step 8:

[0597] Reflecting feedback

[0598] The server adjusts and updates the virtual factory and AI model based on the received feedback. The input is the feedback data from the user, and the output is an updated virtual environment and AI model. Specifically, the server incorporates the user's proposed layout plan into the simulation and tests its efficiency again.

[0599] 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.

[0600] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment, accelerating time to efficiently generate and acquire inventions and culture, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to dynamically respond to the user's emotions. This system is composed of the roles of a server, a terminal, and a user.

[0601] Server processing

[0602] Setting up and building a virtual environment

[0603] The server sets the basic structure of the virtual environment (topography, climate, social systems, etc.). Specifically, it creates a virtual environment modeled on the topography of a city and sets the physical laws and environmental variables (temperature, humidity, etc.).

[0604] Next, we set a time acceleration factor to accelerate the time in the virtual environment, which allows us to simulate several hours of virtual environment in one second of real time.

[0605] Artificial Intelligence Instance Generation

[0606] The server generates multiple AI models modeled after the human brain, each with different characteristics and skill sets—for example, one AI model might specialize in engineering, while another might be interested in art.

[0607] The generated AIs begin to operate autonomously within the virtual environment, cooperating and interacting with each other to create new inventions and cultures.

[0608] Running an activity simulation

[0609] The server simulates the activities of the AIs in the virtual environment, collects data on the inventions and cultures generated by each AI, and stores it in a database.

[0610] For example, observe the process of research and development of new energy technologies within a virtual city and save the results.

[0611] Data collection and analysis

[0612] The server analyzes the collected data to identify technologies and cultures that are useful in the real world, generates patent documents based on the analyzed data, and prepares patent applications.

[0613] It also includes the ability to provide appropriate feedback to help users access the system.

[0614] Processing by the terminal

[0615] Providing a user interface

[0616] The device provides an interface that visualizes the status of the virtual environment and the activity of the AI ​​in real time, allowing the user to check the progress of the virtual environment and the activity history of the AI ​​through this interface.

[0617] For example, a dashboard-style interface will clearly display the activities of each AI and the status of ongoing projects.

[0618] Receiving and sending feedback

[0619] The device receives feedback from the user and sends it to the server, where the user can input new ideas and suggestions for improvement, which are then reflected in the system.

[0620] For example, you can enter an idea for a new energy technology and watch it being tested in a virtual environment.

[0621] Incorporating an emotion engine

[0622] emotion recognition

[0623] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to recognize the user's emotions in real time. The server dynamically adjusts the virtual environment and artificial intelligence settings based on this emotional data.

[0624] For example, if it senses that the user is excited, it may speed up projects within the virtual environment or add new, challenging tasks.

[0625] Emotion-based responses

[0626] The emotion engine recognizes user emotions and adjusts the AI's responses and behaviors in real time, improving the user experience and increasing the system's effectiveness.

[0627] For example, if a user is dissatisfied, the AI ​​will be instructed to prioritize resolving that issue.

[0628] User Action

[0629] Virtual environment observation and intervention

[0630] Users can observe the virtual environment through their terminals and intervene if necessary, for example to observe the impact of the introduction of new technology or to issue instructions to accelerate a particular project.

[0631] By providing feedback on new technologies and improvement ideas from users, the impact of these can be reflected in the virtual environment.

[0632] Specific examples

[0633] For example, to simulate the invention of a new energy source:

[0634] 1. Setting up the virtual environment: The server builds a city model and sets up the climatic conditions and energy demands.

[0635] 2. Generation of artificial intelligence: The server generates an artificial intelligence model specialized in energy engineering and an artificial intelligence model knowledgeable in socioeconomics.

[0636] 3. Start of activity simulation: The server simulates the activities of these artificial intelligences in advancing research and development of new energy sources within the virtual city.

[0637] 4. Use of emotion engine: The device detects the user's emotions, such as excitement or anxiety, and sends that data to the server, which then adjusts the AI's behavior based on that information.

[0638] 5. Data Collection and Analysis: The server collects and analyzes data on new energy sources, identifies useful technologies, and uses the results in patent applications.

[0639] In this way, the present invention provides a more adaptive and effective invention creation system in a virtual environment by appropriately reflecting the user's emotions.

[0640] The processing flow will be explained below.

[0641] Step 1:

[0642] The server sets the basic structure of the virtual environment. It generates terrain data within the virtual environment and establishes climatic conditions and social systems. For example, it models the terrain of a city and places the necessary infrastructure and housing. It also sets the laws of physics and environmental variables (temperature, humidity, etc.).

[0643] Step 2:

[0644] The server sets a time acceleration factor, which sets the passage of time in the virtual environment to hundreds of seconds of virtual time per second of real time, allowing long-term changes to be observed in a short period of time.

[0645] Step 3:

[0646] The server generates multiple AI models modeled after the human brain, each with its own unique characteristics and initial skill set. For example, one AI may be good at engineering, while another may be talented in art.

[0647] Step 4:

[0648] The server then configures the generated AI to begin acting autonomously, creating an environment in which AIs can influence each other and develop, for example, working together to develop new energy technologies for a city.

[0649] Step 5:

[0650] The server simulates the activities of AI within a virtual environment, collects data on inventions and culture generated by the AI, and stores it in a database. For example, it observes the process of developing new energy technologies within a virtual city and records the results.

[0651] Step 6:

[0652] The server analyzes the collected data, identifies technologies and cultures that are useful in the real world, generates patent documents based on the analysis results, prepares patent applications, and provides appropriate feedback to users to allow them to access the system.

[0653] Step 7:

[0654] The device provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time. Through this interface, the user can observe the progress of the virtual environment and the activity history of the AI. For example, a dashboard-style interface displays the activities of each AI and the progress of the project.

[0655] Step 8:

[0656] The device receives feedback from the user and sends it to the server, for example, a user can input an idea for a new energy technology, which is then tested in the virtual environment.

[0657] Step 9:

[0658] The server dynamically adjusts the settings of the virtual environment and the AI ​​based on user feedback by analyzing the feedback and reflecting it in a way that affects the behavior of the virtual environment and the AI.

[0659] Step 10:

[0660] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize the user's emotions in real time. The server receives the recognized emotion data and adjusts the behavior of the virtual environment and artificial intelligence based on it. For example, if the user is excited, it may accelerate projects in the virtual environment or add new, challenging tasks.

[0661] Step 11:

[0662] The device adjusts the AI's responses and behavior in real time based on the user's emotions recognized by the emotion engine. For example, if the user is feeling dissatisfied, the AI ​​will be set to prioritize solving that problem.

[0663] Step 12:

[0664] The server stores the emotion data recognized by the emotion engine in a database for later analysis. This allows the server to accumulate a user's emotion history, enabling more accurate emotion recognition and response.

[0665] In this way, a system is realized in which the server, terminal, user, and emotion engine cooperate to efficiently generate new inventions and culture through the activities of artificial intelligence within a virtual environment and utilize them in the real world.

[0666] Example 2

[0667] 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."

[0668] Conventional AI systems have been inefficient in generating new inventions and culture, and have difficulty dynamically responding to user emotions. This has led to problems such as a poor user experience and limited system effectiveness. Furthermore, there has been a lack of means to rapidly collect and analyze large amounts of data by accelerating time in virtual environments.

[0669] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0670] In this invention, the server

[0671] A means for operating multiple artificial intelligences that mimic the human brain in a virtual environment;

[0672] means for accelerating time in a virtual environment in which said artificial intelligence operates;

[0673] A means for acquiring inventions and cultures generated within the virtual environment and storing them in a database;

[0674] A means for analyzing the acquired inventions and cultures and identifying useful technologies;

[0675] means for recognizing a user's emotions and dynamically adjusting settings of the virtual environment and artificial intelligence based on said emotion data;

[0676] Includes.

[0677] This not only enables the efficient creation of new inventions and cultures in virtual environments, but also enables dynamic responses to users' emotions, improving the quality of the user experience. Furthermore, time acceleration allows for the rapid collection and analysis of large amounts of data, facilitating applications in the real world.

[0678] "Artificial intelligence" refers to computer systems that mimic human intelligence and have capabilities such as learning, reasoning, and self-correction.

[0679] A "virtual environment" is a simulated environment generated on a computer system, in which physical laws, social systems, etc. can be set.

[0680] "Time acceleration" is a function that allows time in a virtual environment to progress faster than real time.

[0681] A "database" is a collection of electronically stored data, and a system that allows for efficient searching, management, and updating of necessary data.

[0682] The "emotion engine" is a function that recognizes the user's emotions in real time and adjusts the system's operation based on that emotional data.

[0683] "Feedback" refers to opinions and reactions provided by users to a system.

[0684] "Dynamic adjustment" is the ability of a system to automatically change its behavior and settings based on real-time data and conditions.

[0685] "Analysis" is the process of analyzing collected data and deriving useful information and insights from it.

[0686] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment, accelerating time and efficiently generating and acquiring inventions and culture. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system enables dynamic responses according to the user's emotions. This system is composed of a server, a terminal, and a user, each playing a role.

[0687] Server processing

[0688] The server uses Python or a similar programming language to build the virtual environment. It uses a simulation engine to create a city model, set physical laws and environmental variables, and set a time acceleration factor to accelerate the progression of time in the virtual environment.

[0689] Next, machine learning libraries such as TensorFlow and PyTorch are used to generate multiple AI models that mimic the human brain. Each AI model is given different characteristics and skill sets, and begins to operate autonomously within the virtual environment. The server collects the data generated by these AI models and stores it in a database.

[0690] The server then applies machine learning algorithms to analyze the collected data, identifying useful technologies and cultures and automatically generating patent application documents based on the analysis results.

[0691] Processing by the terminal

[0692] The device provides a user interface using a web application or dedicated software. This interface allows users to visualize the status of the virtual environment and the activity of the AI ​​in real time. Various data is displayed in dashboard format, making operation easy.

[0693] Users can provide feedback through their devices, which can be specific ideas or suggestions for improvement, and the devices then send this to the server, which then dynamically adjusts the virtual environment and AI settings based on this feedback.

[0694] Incorporating an emotion engine

[0695] The emotion engine uses OpenCV and TensorFlow to analyze the user's facial expressions, voice, and text data in real time. The analysis results are sent to the server as emotion data, and the server dynamically adjusts the virtual environment and artificial intelligence settings based on this data.

[0696] For example, if the user is excited, the server will accelerate projects in the virtual environment or add new challenging tasks, and if the user is frustrated, the artificial intelligence will be instructed to prioritize solving that problem.

[0697] Specific examples

[0698] For example, to simulate the invention of a new energy source, we proceed as follows:

[0699] 1. Setting up the virtual environment: The server builds a city model and sets up the climatic conditions and energy demands.

[0700] 2. Generation of artificial intelligence: The server generates an artificial intelligence model specialized in energy engineering and an artificial intelligence model knowledgeable in socioeconomics.

[0701] 3. Start of activity simulation: The server simulates the activities of these artificial intelligences in advancing research and development of new energy sources within the virtual city.

[0702] 4. Use of emotion engine: The device detects the user's emotions, such as excitement or anxiety, and sends that data to the server, which then adjusts the AI's behavior based on that information.

[0703] 5. Data Collection and Analysis: The server collects and analyzes data on new energy sources, identifies useful technologies, and uses the results in patent applications.

[0704] Example prompt: "I would like to present an idea for a new energy technology and observe how it evolves in a virtual environment."

[0705] As described above, the present invention provides an efficient and effective invention generation system that combines a virtual environment and dynamic responses based on the user's emotions.

[0706] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0707] Step 1: Configure and build a virtual environment

[0708] The server uses Python to create a virtual environment. Using a simulation engine like SimCity, it models the topography of a city and sets environmental variables such as climate conditions and energy demand. Parameters such as the city name, temperature, and humidity are received as input. Data processing involves generating a virtual environment based on these parameters. The output is a model of the constructed virtual city. Specifically, the server executes commands such as "simcity.create_city('Tokyo', temperature=25, humidity=60)".

[0709] Step 2: Setting time acceleration

[0710] The server sets a time acceleration factor to accelerate time in the virtual environment. As input, it receives a time acceleration factor value. As data processing, it applies this factor to the time variables of the virtual environment. As output, it obtains an accelerated time environment. Specifically, the server executes the command "simcity.set_time_acceleration(100)".

[0711] Step 3: Instantiating the Artificial Intelligence

[0712] The server generates an artificial intelligence model using TensorFlow or PyTorch. As input, it receives the type of AI model and its skill set. As data processing, it generates AI instances with different characteristics and skills based on this information. As output, it obtains the generated AI instances. Specifically, the server executes a command such as "ai_instance = AIModel('Engineer', skills=['mechanics', 'dynamics'])".

[0713] Step 4: Start the activity simulation

[0714] The server makes the generated AI model operate autonomously within the virtual environment. As input, it receives the AI ​​model and task information. As data processing, it assigns a task to the AI ​​model and begins operating within the virtual environment. As output, it obtains the AI ​​model's activity data and deliverables. Specifically, the server executes the command "simcity.assign_task(ai_engineer, 'develop energy source')".

[0715] Step 5: Data collection and storage

[0716] The server collects the activity data of the AI ​​model and stores it in a database. As input, it receives the activity data of the AI ​​model. As data processing, it organizes this data and converts it into a format that can be stored in the database. As output, it obtains the data stored in the database. Specifically, the server executes the code "database.save('energy_research_results', ai_engineer.results)".

[0717] Step 6: Data analysis and technology identification

[0718] The server analyzes the collected data and identifies useful technologies. As input, it receives stored activity data. As data processing, it analyzes the data using machine learning algorithms and identifies useful technologies. As output, it obtains information about the identified technologies. Specifically, the server executes the command "analyze_data('energy_research_results')".

[0719] Step 7: Providing a User Interface

[0720] The device provides a user interface and visualizes the virtual environment and AI activity in real time. It uses the activity data received from the server as input. It converts this data into a format that can be visualized as data processing. It outputs a dashboard-style interface. Specifically, the device executes the code "dashboard.update('AI Activity', ai_activity_data)".

[0721] Step 8: Receiving and sending feedback

[0722] The device receives feedback from the user and sends it to the server. As input, it receives the user's feedback data. As data processing, it converts this feedback data into an appropriate format. As output, it sends the feedback to the server. Specifically, the device executes the code "user_feedback = get_user_input()" and "send_to_server(user_feedback)".

[0723] Step 9: Emotion recognition and dynamic regulation

[0724] The server uses an emotion engine to recognize the user's emotions in real time. As input, it receives the user's facial expressions, voice, and text data. As data processing, it analyzes this data to identify emotions. As output, it obtains the user's emotion data. Specifically, the server executes the code "emotion = detect_emotion(camera_feed)" and "send_to_server(emotion_data)".

[0725] Step 10: Dynamic adjustment of virtual environment and AI

[0726] The server dynamically adjusts the virtual environment and artificial intelligence settings based on the acquired emotional data. It receives emotional data as input. It processes the data by changing the AI's behavior and virtual environment settings based on this data. It outputs the adjusted virtual environment and AI behavior data. Specifically, the server executes the command "adjust_AI_behavior(emotion_data)".

[0727] (Application example 2)

[0728] 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."

[0729] When autonomous vehicles are operating, various unexpected situations and obstacles can occur. These can increase passenger anxiety and discomfort, resulting in problems such as reduced operational efficiency and safety. Furthermore, it is necessary to properly identify passenger emotions and respond flexibly accordingly, but current systems are inadequate in this regard. Therefore, it is necessary to provide flexible responses to unexpected situations and dynamic measures according to passenger emotions.

[0730] 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.

[0731] In this invention, the server includes means for operating multiple artificial intelligences modeled on the human brain in a virtual environment, means for accelerating time in the virtual environment, means for acquiring inventions and cultures generated in the virtual environment and storing them in a database, means for analyzing the acquired inventions and cultures and identifying useful technologies, means for managing the operation of the autonomous vehicle, recognizing and dynamically responding to user emotions, and means for the autonomous vehicle to search for an alternative route in the event of an obstacle and providing measures to reassure passengers based on their emotions. This enables the autonomous vehicle to respond flexibly to unexpected situations and quickly and appropriately to passenger emotions.

[0732] "Artificial intelligence" is a system that performs intellectual tasks using algorithms and programs that mimic the functions of the human brain.

[0733] A "virtual environment" is a model of the real world reproduced on a computer system, and is a simulated space that includes elements such as terrain, climate, and social systems.

[0734] "Means of accelerating time" is a technology that allows time in a virtual environment to pass faster than actual time, making it possible to simulate a long period of time in a short period of time.

[0735] A "database" is an information system for efficiently storing, searching, and managing large amounts of data, and stores data on the aforementioned inventions and cultures.

[0736] An "autonomous mobile object" is a machine that operates and moves on its own initiative without the need for external control, and specifically refers to self-driving vehicles.

[0737] "Means for recognizing emotions" refers to technology that identifies a user's psychological state by analyzing the user's facial expressions, voice, text data, etc.

[0738] "Dynamic response means" refers to the ability to adjust the system in real time according to the situation and the user's emotions, and to execute the optimal response or action.

[0739] The "means for searching alternative routes" is an algorithm that considers new routes and allows a moving vehicle to adopt the optimal route depending on traffic conditions and obstacles.

[0740] "Reassuring measures" are measures or actions to reduce the user's anxiety or stress, and include, for example, playing music or providing information.

[0741] System Configuration

[0742] The system of the present invention is realized with the following configuration.

[0743] Server processing

[0744] 1. Configure and build the virtual environment:

[0745] The server first sets up a virtual environment, creating a virtual space modeled on the city's topography and climate. It also sets the laws of physics and environmental variables within this virtual environment. It also sets a time acceleration factor, allowing the virtual environment to progress faster than real time.

[0746] 2. Artificial Intelligence Generation:

[0747] The server generates multiple AIs modeled after the human brain, each with its own unique characteristics and skills. For example, models specializing in energy engineering and socioeconomics are included. These AIs operate autonomously within the virtual environment, generating new inventions and cultures.

[0748] 3. Data Collection and Analysis:

[0749] The server collects data on inventions and cultures generated in the virtual environment, stores it in a database, and analyzes the collected data to identify technologies and cultures that are useful in the real world, enabling the generation of patent documents and patent applications.

[0750] Processing by the terminal

[0751] 1. Real-time visualization:

[0752] The device provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time, allowing the user to observe the virtual environment and the activities of the AI ​​in detail.

[0753] 2. Incorporating feedback:

[0754] The device receives feedback from the user and sends it to a server, which dynamically adjusts the settings of the virtual environment and artificial intelligence based on this feedback.

[0755] Incorporating an emotion engine

[0756] 1. Emotion recognition:

[0757] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize the user's emotions in real time. This emotional data is received by the server and used to adjust the behavior of the virtual environment and artificial intelligence.

[0758] 2. Emotion-based responses:

[0759] Based on the user's emotions, the server adjusts the autonomous vehicle's behavior and responses in real time. For example, if the user feels anxious, the server may search for an alternative route.

[0760] Hardware and software used

[0761] Hardware: Autonomous mobile devices (e.g., self-driving cars), high-performance server computers (e.g., NVIDIA Drive)

[0762] Software: Python programming language, machine learning libraries (e.g., TensorFlow), emotion recognition libraries (e.g., OpenCV)

[0763] Specific examples

[0764] For example, consider an application example when traffic congestion occurs.

[0765] 1. The server runs an autonomous vehicle in a virtual environment where random traffic jams may occur.

[0766] 2. At this point, the autonomous vehicle's artificial intelligence will become anxious and search for an alternative route.

[0767] 3. The user can observe this situation through the device and provide feedback as needed, for example, allowing the user to suggest valid alternative routes.

[0768] 4. The emotion engine recognizes the user's anxiety and communicates it to the server, which then adjusts the AI's behavior and takes steps to alleviate the anxiety.

[0769] Prompt Sentence Examples

[0770] A prompt to input to a generative AI model how a self-driving vehicle will behave in a given traffic situation:

[0771] When an autonomous vehicle is traveling according to a city model, it suddenly encounters a traffic jam. Considering that the ongoing load factor is 0.8, what should be the next action? The emotional state of the vehicle is anxious, but please also suggest ways to reassure the passengers.

[0772] In this way, the present invention enables dynamic and adaptive responses according to the user's emotions, thereby enhancing the operation management of autonomous vehicles.

[0773] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0774] Step 1: Configure and build a virtual environment

[0775] The server sets the basic structure of the city, including its topography, climate, and social systems. At the same time, it also sets the laws of physics and environmental variables (temperature, humidity, etc.). Using city model data as input, a virtual environment is constructed as output. Specifically, a 3D model of the city is generated using computer graphics and run on a simulation engine.

[0776] Step 2: Generate artificial intelligence

[0777] The server generates multiple AI models modeled after the human brain. Different characteristics and skills are input to each AI. The input is data defining the characteristics and skills, and the output is the generation of multiple AI instances. Specifically, machine learning algorithms are applied to each AI model, and specific skills are learned using training data.

[0778] Step 3: Set the time acceleration factor

[0779] The server sets a time acceleration factor to accelerate time in the virtual environment. The input is the time acceleration factor, and the output is the speed of virtual time relative to real time. Specifically, the server controls the progression of time in the virtual environment by changing the simulation time step.

[0780] Step 4: Simulating AI activity

[0781] The server simulates the activities of the AI ​​generated within the virtual environment. The virtual environment, AI instances, and environmental variables are used as input, and the AI's activity history data is generated as output. Specifically, each AI acts autonomously within the simulation engine and performs designated tasks.

[0782] Step 5: Collect and store data

[0783] The server collects data on the AI's activities within the virtual environment, as well as the inventions and cultural data it generates, and stores them in a database. Simulation data is used as input, and an organized database is generated as output. Specifically, a data collection agent collects the activity data of each AI and stores it in the database in an appropriate format.

[0784] Step 6: Data analysis and feedback

[0785] The server analyzes the data stored in the database to identify useful technologies and generates patent documents based on the analysis results. The acquired data is used as input, and an analysis report and patent documents are generated as output. Specifically, data analysis algorithms are used to identify interesting patterns and generate technology feasibility reports.

[0786] Step 7: Real-time visualization

[0787] The device displays the status of the virtual environment and the activity of the AI ​​in real time. It uses the virtual environment and AI activity data as input and provides a visualized graphical interface as output. Specifically, it displays real-time data in a dashboard format while updating it.

[0788] Step 8: Incorporating user feedback

[0789] The device receives feedback from the user and sends it to the server. The server dynamically adjusts the virtual environment and AI based on the feedback. The user's feedback data is used as input, and the parameters of the virtual environment and AI are dynamically updated as output. Specifically, after receiving the feedback data, the simulation parameters are recalculated and applied in real time.

[0790] Step 9: Emotion recognition and response adjustment

[0791] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize their emotional state. The server then adjusts the AI's behavior based on this information. The input is the user's emotional data, and the output is an emotion-based response action. Specifically, the emotion recognition software performs real-time analysis and takes reassuring action as needed.

[0792] Step 10: Encountering obstacles and finding alternative routes

[0793] When an autonomous vehicle encounters a fault in the virtual environment or in the real world, the server searches for an alternative route and provides reassurance measures. Using fault information and current traffic information as input, the server generates the optimal alternative route and reassurance measures as output. Specifically, the server analyzes traffic congestion and accident information and presents a safe and fast alternative route.

[0794] 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.

[0795] 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.

[0796] 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.

[0797] [Third embodiment]

[0798] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0799] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0800] 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).

[0801] 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.

[0802] 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.

[0803] 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).

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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."

[0810] This invention is a system that operates multiple artificial intelligences modeled after the human brain in a virtual environment, and accelerates time in the virtual world to efficiently generate and acquire inventions and culture. This system is composed of a server, terminals, and users, each playing their own role.

[0811] Server processing

[0812] Setting up and building a virtual environment

[0813] The server sets the basic structure of the virtual environment (topography, climate, social systems, etc.) For example, it models the topography of a city and sets the physical laws and environmental variables to simulate the growth of the city.

[0814] The server sets a time acceleration factor, causing time in the virtual environment to progress faster than in reality, allowing long-term changes to be observed in a short period of time.

[0815] Artificial Intelligence Instance Generation

[0816] The server generates multiple AI models modeled after the human brain, each with different characteristics and initial skill sets—for example, one model might be good at engineering, while another might be talented at art.

[0817] These AIs operate autonomously within the virtual environment, growing and developing as they interact with each other.

[0818] Running an activity simulation

[0819] The server simulates the activities of the AI ​​in a virtual environment, observes the process of the AI ​​generating inventions and culture, and collects the generated data.

[0820] For example, the process by which new energy technologies are developed or new musical genres are formed can be simulated in a virtual urban environment.

[0821] Data collection and analysis

[0822] The server stores the inventions and cultures generated within the virtual environment in a database.

[0823] The collected data is analyzed to identify useful technologies and cultures, which then lead to patent applications and technological applications in the real world.

[0824] Processing by the terminal

[0825] Providing a user interface

[0826] The device provides the user with an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time. For example, a dashboard displays the activity history of each AI and the progress of inventions.

[0827] The terminal will have an interface designed to make it easy for users to search for information about specific inventions or cultures.

[0828] Receiving and sending feedback

[0829] The terminal receives feedback from the user and sends it to the server, which uses the feedback to improve the system or propose new inventions.

[0830] For example, a user can input an idea for a new energy source and the idea can be tested in a virtual environment.

[0831] User Action

[0832] Virtual environment observation and intervention

[0833] Users can observe the status of the virtual environment through their devices, for example, checking the development of the virtual city and the activity history of the AI ​​in real time.

[0834] Users can also intervene in the virtual environment and artificial intelligence, for example by introducing certain technologies into the virtual environment and observing their effects.

[0835] Specific examples

[0836] For example, to simulate the invention of a new energy source in a virtual environment:

[0837] 1. Setting up the virtual environment: The server sets up the basic data (topography, climate, energy demand, etc.) to simulate a city.

[0838] 2. Generation of artificial intelligence: The server generates an artificial intelligence model that is strong in energy engineering and an artificial intelligence model that is knowledgeable in socioeconomics.

[0839] 3. Start of activity simulation: The server simulates the research and development of new energy sources in a virtual city. Each AI cooperates to develop new technologies.

[0840] 4. Data collection and analysis: The server stores the generated data on the new energy sources in a database and analyzes them. Based on the analysis results, patent applications and real-world applications can be made.

[0841] In this way, the present invention provides an innovative system that can efficiently generate new technologies and cultures and utilize them in the real world.

[0842] The processing flow will be explained below.

[0843] Step 1:

[0844] The server sets the basic structure of the virtual environment. It generates terrain data within the virtual environment and establishes climatic conditions and social systems. For example, it builds a model of a city and places the necessary infrastructure and housing there. It also sets the laws of physics and environmental variables (temperature, humidity, etc.).

[0845] Step 2:

[0846] The server sets a time acceleration factor, which sets the passage of time in the virtual environment to hundreds of seconds of virtual time per second of real time, allowing long-term changes to be observed in a short period of time.

[0847] Step 3:

[0848] The server generates multiple AI models modeled after the human brain, each with its own unique characteristics and initial skill set—for example, one AI may be good at engineering, while another may be talented in art.

[0849] Step 4:

[0850] The server allows the AIs generated within the virtual environment to begin acting autonomously, creating an environment in which they can influence each other and develop, for example, working together to develop new energy technologies within a city.

[0851] Step 5:

[0852] The server simulates the AI's activities in the virtual environment, observing, for example, the invention of a new energy source or the formation of a new culture, and collecting necessary data. The AI-generated inventions and cultural data are then stored in a database.

[0853] Step 6:

[0854] The server analyzes the collected data, identifies technologies and cultures that are useful in the real world, generates patent documents based on the analysis results, prepares patent applications, and provides appropriate feedback to users to allow them to access the system.

[0855] Step 7:

[0856] The terminal provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time, allowing users to observe the activity history of each AI and the progress of their inventions.

[0857] Step 8:

[0858] The device receives feedback from users and sends it to the server. Users input and submit ideas for new inventions and system improvements, which are reflected in the virtual environment and the activities of the artificial intelligence. This allows the entire system to evolve in a way that meets user expectations.

[0859] Step 9:

[0860] Users can observe the situation in the virtual environment through their devices and intervene in specific locations or artificial intelligence, for example, to observe the impact of the introduction of new technology or to issue instructions to accelerate a specific project.

[0861] In this way, by having the server, terminal, and user fulfill their respective roles, a system is realized in which new inventions and cultures can be efficiently generated and acquired through the activities of artificial intelligence within the virtual environment, and then utilized in the real world.

[0862] Example 1

[0863] 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."

[0864] Conventional artificial intelligence systems have had problems with the efficient creation and acquisition of new technologies and cultures. They also lack the ability to manage time in virtual environments, visualize the activities of intelligent models with diverse characteristics, and incorporate user feedback. Therefore, there has been a need for a system that can solve these problems and efficiently create and acquire new technologies and cultures using an intelligent model that mimics the human brain.

[0865] 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.

[0866] In this invention, the server includes a means for operating a plurality of intelligent models imitating the human brain in a virtual space, a means for accelerating the time of the virtual space in which the intelligent models are active, a means for acquiring innovations and cultures generated in the virtual space and storing them in an information base, and a means for analyzing the acquired innovations and cultures and identifying useful technologies, thereby enabling the efficient generation and acquisition of new technologies and cultures using intelligent models.

[0867] An "intelligent model" is an information processing system that mimics the human brain, has multiple characteristics and capabilities, and operates autonomously within a virtual space.

[0868] A "virtual space" is a virtual environment that mimics a real physical environment using digital technology, allowing people and intelligent models to interact with each other.

[0869] "Time acceleration" is a technique that sets the speed at which time progresses in a virtual space to be faster than real time, allowing long-term changes and developments to be observed in a short period of time.

[0870] "Innovation" is a general term for new technologies, ideas, or inventions generated within the virtual world.

[0871] "Culture" is a general term for new art forms, music, literature, customs, or other social phenomena that are generated within virtual spaces.

[0872] An "information base" is a digital storage system for storing innovations and culture generated within virtual space as data.

[0873] "Analysis" is the process of examining the data stored in an information base in detail to extract specific patterns and useful information.

[0874] "Feedback" refers to opinions, suggestions, or evaluations sent by users, and is information that is useful for improving the virtual space or intelligent model or for starting new activities.

[0875] This invention is a system that operates an intelligent model that mimics the human brain in a virtual space, and accelerates time in the virtual space, thereby efficiently generating and acquiring innovation and culture.

[0876] Server processing

[0877] Setting up and building a virtual space

[0878] The server sets the basic structure of the virtual space. Specifically, it sets elements such as the terrain, climate, and social systems. For example, it models cities in mountainous regions and warm climates. The server also sets a time acceleration factor, making time progress faster in the virtual space than in reality. This can be set so that one second is equivalent to one year.

[0879] Intelligent Model Instantiation

[0880] The server generates multiple intelligent models modeled after the human brain. Each intelligent model has different characteristics and skill sets. For example, there is a model specializing in energy engineering and another specializing in art. These intelligent models operate autonomously within the virtual space, growing and developing as they interact with each other.

[0881] Running an activity simulation

[0882] The server simulates the activities of intelligent models in a virtual space. For example, an intelligent model specializing in energy engineering researches new energy sources, while an intelligent model specializing in economics analyzes their social impact. This results in the creation of new technologies and cultures.

[0883] Data collection and analysis

[0884] The server stores the innovations and cultures generated in the virtual world in a database. The collected data is analyzed by the server to identify useful technologies and cultures. The results of this analysis are used for patent applications and real-world applications.

[0885] Processing by the terminal

[0886] Providing a user interface

[0887] The terminal provides users with an interface that visualizes the status of the virtual space and the activities of the intelligent models in real time. For example, a dashboard visually displays the activity history of each intelligent model and the progress of inventions. The terminal is also designed to make it easy for users to search for information on specific innovations or cultures.

[0888] Receiving and sending feedback

[0889] The device receives feedback from the user and sends it to the server. For example, the user can input an idea for a new energy source, and the idea is tested in the virtual space. The server then modifies the virtual space and intelligent model based on the received feedback and starts a new simulation.

[0890] User Action

[0891] Observation and intervention in virtual spaces

[0892] Users can observe the state of the virtual space through their devices. For example, they can check the development of the virtual city and the activity history of the intelligent model in real time. Furthermore, users can intervene in the virtual space and the intelligent model. Specifically, they can introduce new technologies into the virtual space and observe their effects.

[0893] Specific examples

[0894] Simulation of the invention of a new energy source

[0895] 1. Virtual Space Setup: The server sets up terrain data to simulate a mountainous city, with a warm climate and medium energy demands.

[0896] 2. Generation of intelligent models: The server generates an intelligent model specialized in energy engineering and an intelligent model specialized in socioeconomics, and provides initial data to each.

[0897] 3. Start of activity simulation: The server simulates the research and development of new energy sources in a virtual city. The energy engineering model conducts research on new technologies, and the economics model analyzes the economic impact of the technologies.

[0898] 4. Data collection and analysis: The server stores the generated data on the new energy sources in a database and analyzes them. Based on the analysis results, a patent application is prepared.

[0899] An example prompt is:

[0900] "Simulate the research and development of new energy sources. Set a virtual city with the following parameters: terrain is mountainous, climate is temperate, and energy demand is moderate. Use an AI specialized in energy engineering and an AI specialized in socioeconomics to analyze the development of new technologies and their economic impact."

[0901] In this way, this invention provides an innovative system for efficiently generating and acquiring new technologies and cultures and applying them to the real world.

[0902] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0903] Step 1:

[0904] The server sets up the virtual space. As input, the server receives basic parameters such as topography, climate, and social systems. Based on these parameters, it processes data to build a digital environment. Specifically, it inputs topographical data for mountainous areas and information on temperate climates, and generates the basic structure of a virtual city based on that data. The output is the basic structure of the virtual space.

[0905] Step 2:

[0906] The server instantiates intelligent models. The server receives input parameters for generating intelligent models with different characteristics and skill sets. For example, information for generating an AI model specialized in energy engineering or an AI model specialized in art is used as input. The server instantiates an intelligent model based on these parameters and inputs the initial skill set and knowledge base. The output is the generated multiple intelligent models.

[0907] Step 3:

[0908] The server runs the activity simulation. The inputs are the virtual space setting information and the generated intelligent model. The server sets up a scenario in which the intelligent model will operate autonomously, and by setting a time acceleration factor, it simulates a time progression speed where, for example, one second is equivalent to one year. In concrete terms, an AI specialized in energy engineering researches new energy sources, while another AI analyzes the social impact of that technology. The output here is data on the generated technology and culture.

[0909] Step 4:

[0910] The server collects and analyzes data. It receives as input data on technology and culture generated as a result of the activity simulation. The server stores this data in a database and applies analytical algorithms to extract useful information. Specifically, it records the development process and results of new energy technologies in the database and performs data analysis to identify highly energy-efficient technologies. The output from this process is the analysis results. Based on these results, patent applications are prepared.

[0911] Step 5:

[0912] The terminal provides a user interface. As input, it receives data on the virtual space and the activity status of the intelligent models sent from the server. The terminal visualizes this data and displays it on a dashboard so that the user can easily understand it. Specifically, it graphically displays the activity history of each intelligent model, research progress, and data on the generated technology. Here, the visualized information is provided to the user as output.

[0913] Step 6:

[0914] The device receives and sends feedback. As input, it receives feedback and suggestions from users. The device converts this into an appropriate format and sends it to the server. For example, a user can input a suggestion for a new energy-efficient technology and send the suggestion to the server for testing in the virtual space. Here, the output is the feedback sent to the server.

[0915] Step 7:

[0916] The user observes the virtual space and intervenes. The input is visualized data provided by the terminal. Based on this data, the user makes specific interventions in the virtual space or intelligent model. For example, a new technology can be introduced into the virtual space and its impact can be observed in real time. A specific action involves the user introducing a new energy technology into a virtual city and analyzing the economic impact of that technology. The output is the results of the intervention and feedback.

[0917] Through these steps, inventions can utilize intellectual models to efficiently generate new technologies and cultures and apply them to the real world.

[0918] (Application example 1)

[0919] 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."

[0920] Production planning in modern factories involves complex intertwining factors, making it difficult to create efficient and optimal plans. Furthermore, conventional simulation and optimization methods require enormous computational resources and time, making real-time adjustments and optimization difficult. This creates a need for efficient production plans that can be quickly applied to actual production lines. Furthermore, a means of quickly and effectively incorporating user feedback is also required.

[0921] 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.

[0922] In this invention, the server includes means for simulating virtual factory settings, equipment layout, and production lines in a virtual environment, means for generating artificial intelligence models with different skill sets and optimizing production plans in the virtual factory, and means for accelerating the time in the virtual environment. This enables efficient simulation of various production plans in a short period of time and the derivation of optimal production plans. Furthermore, by quickly applying these optimized plans to a real production line, efficient production management and optimal resource utilization can be achieved. Furthermore, by incorporating user feedback in real time, the latest and optimal production plans can be maintained.

[0923] A "virtual factory" is a virtual environment that mimics a real factory, where the layout of equipment and the structure of production lines are simulated on a computer.

[0924] "Equipment layout" refers to the layout of machines and devices within a factory, and is a factor that affects production efficiency and work flow.

[0925] A "production line" is a series of steps organized into a single flow during the manufacturing process of a product, and is an important element for efficient production.

[0926] An "artificial intelligence model" is a computational model designed to mimic human intelligence and perform machine learning and data analysis.

[0927] "Different skill sets" refer to the unique collection of abilities and expertise each AI model possesses, enabling it to perform well in specific fields.

[0928] "Accelerating time in a virtual environment" means making time pass faster in a virtual environment than in the real world, a means of observing long-term effects in the short term.

[0929] "Optimization" refers to adjusting systems and processes to achieve the best results for a specific purpose, with the aim of operating efficiently.

[0930] "Feedback" refers to opinions and impressions provided by users, and is information used to help improve systems and processes.

[0931] "Real-time" refers to processing and responses that are carried out in line with the real time axis, meaning that results are obtained almost immediately.

[0932] A "production plan" is a plan for production activities in a factory, including resource allocation, process order, schedule, etc.

[0933] "Simulation" is a method of imitating real-world systems and processes in a virtual environment to make predictions and analyses.

[0934] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment to efficiently generate and acquire inventions and culture. This system is composed of a server, terminals, and users, each playing their own role.

[0935] Server processing

[0936] Setting up and building a virtual environment

[0937] The server configures the virtual factory, equipment layout, and production line configuration. It generates multiple AI models with different skill sets and runs them in the virtual environment. It also accelerates the time in the virtual environment, running short-term and long-term simulations. For example, it can simulate the layout that maximizes factory production efficiency and the optimal production line.

[0938] Artificial Intelligence Instance Generation

[0939] The server generates multiple artificial intelligence (AI) models with different characteristics and skill sets. Each AI model excels in a specific skill and performs activities to optimize the factory's production plan. For example, some AI models specialize in quality control, while others optimize production schedules.

[0940] Running an activity simulation

[0941] The server simulates the AI's activities within the virtual factory, allowing it to test different production plans and derive the most efficient one. The generated data is stored in a database and later analyzed. For example, different production lines and layout patterns can be tried to find the optimal combination.

[0942] Data collection and analysis

[0943] The server stores production plans and other data generated within the virtual environment in a database and provides tools to analyze this data and identify the most useful techniques and plans. For example, the generated data can be used to find the optimal plan to reduce production costs.

[0944] Processing by the terminal

[0945] Providing a user interface

[0946] The terminal provides users with an interface that visualizes the virtual factory settings and AI activity in real time. For example, a dashboard displays the efficiency and quality status of each production line. The terminal is also designed to allow users to easily search and access information related to specific production plans.

[0947] Receiving and sending feedback

[0948] The terminal receives feedback from the user and sends it to the server. The feedback is used to improve the system and propose new production plans. For example, the user can input a new equipment layout proposal and try it out in the virtual environment.

[0949] User Action

[0950] Virtual Factory Observation and Intervention

[0951] Users can observe the status of the virtual factory through their terminals. For example, they can check the efficiency and quality fluctuations of the virtual factory's production line in real time. Users can also intervene in the virtual environment and artificial intelligence. For example, they can introduce a specific production plan into the virtual environment and observe its effects.

[0952] Specific examples

[0953] For example, to simulate the optimization of a new production line in a virtual factory:

[0954] 1. Setting up the virtual environment: The server sets up the factory equipment layout and basic data for the production line.

[0955] 2. Generation of artificial intelligence: The server generates an AI model that is strong in areas such as efficiency, quality control, and schedule management.

[0956] 3. Start of activity simulation: The server simulates the testing of a new production plan in the virtual factory. Each AI model cooperates to optimize the plan.

[0957] 4. Data collection and analysis: The server collects and analyzes data related to the generated production plan. Based on the analysis results, the optimal plan is applied to the real-world factory.

[0958] As a result, the present invention can provide an innovative system for quickly generating an efficient production plan and applying it to a real factory.

[0959] Example prompt for a generative AI model:

[0960] "Simulate a new production plan within this virtual factory. Consider the efficiency, quality, and schedule of each production process and propose the optimal production plan."

[0961] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0962] Step 1:

[0963] Virtual Factory Configuration

[0964] The server sets and builds the basic data of the virtual factory (terrain, climate, equipment layout, production lines, etc.). The input is the factory's equipment information and layout diagram, and the output is a factory model in the virtual environment. Specifically, the server reads the terrain data and 3D models and places them in the virtual space.

[0965] Step 2:

[0966] Generating artificial intelligence models

[0967] The server generates artificial intelligence models with different skill sets. The input is the skill set information to be given to each AI model, and the output is the generated AI model. Specifically, it instantiates AI with engineering concepts, AI specialized in quality control, AI specialized in schedule optimization, etc., and places them in the virtual environment.

[0968] Step 3:

[0969] Starting the simulation

[0970] The server simulates AI activity within a virtual factory. The input is the virtual environment and AI model, and the output is the simulation result data. The server accelerates time to test multiple scenarios at high speed. Specifically, it calculates fluctuations in production line efficiency and quality, and executes the plans proposed by each AI model.

[0971] Step 4:

[0972] Data collection

[0973] The server collects data generated within the virtual environment. The input is activity data obtained from the simulation, and the output is data stored in a database. Specifically, metrics such as production efficiency and costs from each simulation are collected and stored in the database.

[0974] Step 5:

[0975] Data analysis

[0976] The server analyzes the collected data. The input is simulation data retrieved from the database, and the output is the identification of the optimal production plan and technology. The server applies statistical analysis and machine learning algorithms to derive useful results. Specifically, it identifies the most efficient plan or the least costly plan.

[0977] Step 6:

[0978] Visualizing the results

[0979] The terminal presents the analysis results to the user. The input is the analyzed data, and the output is a report displayed on the user interface. Specifically, the dashboard displays items such as production efficiency, quality control, and costs in graphs and tables.

[0980] Step 7:

[0981] Receiving Feedback

[0982] The terminal receives feedback input from the user. The input is the user's feedback information, and the output is feedback data sent to the server. In concrete terms, the user inputs new placement plans or improvement plans, which are then sent to the server.

[0983] Step 8:

[0984] Reflecting feedback

[0985] The server adjusts and updates the virtual factory and AI model based on the received feedback. The input is the feedback data from the user, and the output is an updated virtual environment and AI model. Specifically, the server incorporates the user's proposed layout plan into the simulation and tests its efficiency again.

[0986] 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.

[0987] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment, accelerating time to efficiently generate and acquire inventions and culture, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to dynamically respond to the user's emotions. This system is composed of the roles of a server, a terminal, and a user.

[0988] Server processing

[0989] Setting up and building a virtual environment

[0990] The server sets the basic structure of the virtual environment (topography, climate, social systems, etc.). Specifically, it creates a virtual environment modeled on the topography of a city and sets the physical laws and environmental variables (temperature, humidity, etc.).

[0991] Next, we set a time acceleration factor to accelerate the time in the virtual environment, which allows us to simulate several hours of virtual environment in one second of real time.

[0992] Artificial Intelligence Instance Generation

[0993] The server generates multiple AI models modeled after the human brain, each with different characteristics and skill sets—for example, one AI model might specialize in engineering, while another might be interested in art.

[0994] The generated AIs begin to operate autonomously within the virtual environment, cooperating and interacting with each other to create new inventions and cultures.

[0995] Running an activity simulation

[0996] The server simulates the activities of the AIs in the virtual environment, collects data on the inventions and cultures generated by each AI, and stores it in a database.

[0997] For example, observe the process of research and development of new energy technologies within a virtual city and save the results.

[0998] Data collection and analysis

[0999] The server analyzes the collected data to identify technologies and cultures that are useful in the real world, generates patent documents based on the analyzed data, and prepares patent applications.

[1000] It also includes the ability to provide appropriate feedback to help users access the system.

[1001] Processing by the terminal

[1002] Providing a user interface

[1003] The device provides an interface that visualizes the status of the virtual environment and the activity of the AI ​​in real time, allowing the user to check the progress of the virtual environment and the activity history of the AI ​​through this interface.

[1004] For example, a dashboard-style interface will clearly display the activities of each AI and the status of ongoing projects.

[1005] Receiving and sending feedback

[1006] The device receives feedback from the user and sends it to the server, where the user can input new ideas and suggestions for improvement, which are then reflected in the system.

[1007] For example, you can enter an idea for a new energy technology and watch it being tested in a virtual environment.

[1008] Incorporating an emotion engine

[1009] emotion recognition

[1010] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to recognize the user's emotions in real time. The server dynamically adjusts the virtual environment and artificial intelligence settings based on this emotional data.

[1011] For example, if it senses that the user is excited, it may speed up projects within the virtual environment or add new, challenging tasks.

[1012] Emotion-based responses

[1013] The emotion engine recognizes user emotions and adjusts the AI's responses and behaviors in real time, improving the user experience and increasing the system's effectiveness.

[1014] For example, if a user is dissatisfied, the AI ​​will be instructed to prioritize resolving that issue.

[1015] User Action

[1016] Virtual environment observation and intervention

[1017] Users can observe the virtual environment through their terminals and intervene if necessary, for example to observe the impact of the introduction of new technology or to issue instructions to accelerate a particular project.

[1018] By providing feedback on new technologies and improvement ideas from users, the impact of these can be reflected in the virtual environment.

[1019] Specific examples

[1020] For example, to simulate the invention of a new energy source:

[1021] 1. Setting up the virtual environment: The server builds a city model and sets up the climatic conditions and energy demands.

[1022] 2. Generation of artificial intelligence: The server generates an artificial intelligence model specialized in energy engineering and an artificial intelligence model knowledgeable in socioeconomics.

[1023] 3. Start of activity simulation: The server simulates the activities of these artificial intelligences in advancing research and development of new energy sources within the virtual city.

[1024] 4. Use of emotion engine: The device detects the user's emotions, such as excitement or anxiety, and sends that data to the server, which then adjusts the AI's behavior based on that information.

[1025] 5. Data Collection and Analysis: The server collects and analyzes data on new energy sources, identifies useful technologies, and uses the results in patent applications.

[1026] In this way, the present invention provides a more adaptive and effective invention creation system in a virtual environment by appropriately reflecting the user's emotions.

[1027] The processing flow will be explained below.

[1028] Step 1:

[1029] The server sets the basic structure of the virtual environment. It generates terrain data within the virtual environment and establishes climatic conditions and social systems. For example, it models the terrain of a city and places the necessary infrastructure and housing. It also sets the laws of physics and environmental variables (temperature, humidity, etc.).

[1030] Step 2:

[1031] The server sets a time acceleration factor, which sets the passage of time in the virtual environment to hundreds of seconds of virtual time per second of real time, allowing long-term changes to be observed in a short period of time.

[1032] Step 3:

[1033] The server generates multiple AI models modeled after the human brain, each with its own unique characteristics and initial skill set. For example, one AI may be good at engineering, while another may be talented in art.

[1034] Step 4:

[1035] The server then configures the generated AI to begin acting autonomously, creating an environment in which AIs can influence each other and develop, for example, working together to develop new energy technologies for a city.

[1036] Step 5:

[1037] The server simulates the activities of AI within a virtual environment, collects data on inventions and culture generated by the AI, and stores it in a database. For example, it observes the process of developing new energy technologies within a virtual city and records the results.

[1038] Step 6:

[1039] The server analyzes the collected data, identifies technologies and cultures that are useful in the real world, generates patent documents based on the analysis results, prepares patent applications, and provides appropriate feedback to users to allow them to access the system.

[1040] Step 7:

[1041] The device provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time. Through this interface, the user can observe the progress of the virtual environment and the activity history of the AI. For example, a dashboard-style interface displays the activities of each AI and the progress of the project.

[1042] Step 8:

[1043] The device receives feedback from the user and sends it to the server, for example, a user can input an idea for a new energy technology, which is then tested in the virtual environment.

[1044] Step 9:

[1045] The server dynamically adjusts the settings of the virtual environment and the AI ​​based on user feedback by analyzing the feedback and reflecting it in a way that affects the behavior of the virtual environment and the AI.

[1046] Step 10:

[1047] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize the user's emotions in real time. The server receives the recognized emotion data and adjusts the behavior of the virtual environment and artificial intelligence based on it. For example, if the user is excited, it may accelerate projects in the virtual environment or add new, challenging tasks.

[1048] Step 11:

[1049] The device adjusts the AI's responses and behavior in real time based on the user's emotions recognized by the emotion engine. For example, if the user is feeling dissatisfied, the AI ​​will be set to prioritize solving that problem.

[1050] Step 12:

[1051] The server stores the emotion data recognized by the emotion engine in a database for later analysis. This allows the server to accumulate a user's emotion history, enabling more accurate emotion recognition and response.

[1052] In this way, a system is realized in which the server, terminal, user, and emotion engine cooperate to efficiently generate new inventions and culture through the activities of artificial intelligence within a virtual environment and utilize them in the real world.

[1053] Example 2

[1054] 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."

[1055] Conventional AI systems have been inefficient in generating new inventions and culture, and have difficulty dynamically responding to user emotions. This has led to problems such as a poor user experience and limited system effectiveness. Furthermore, there has been a lack of means to rapidly collect and analyze large amounts of data by accelerating time in virtual environments.

[1056] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1057] In this invention, the server

[1058] A means for operating multiple artificial intelligences that mimic the human brain in a virtual environment;

[1059] means for accelerating time in a virtual environment in which said artificial intelligence operates;

[1060] A means for acquiring inventions and cultures generated within the virtual environment and storing them in a database;

[1061] A means for analyzing the acquired inventions and cultures and identifying useful technologies;

[1062] means for recognizing a user's emotions and dynamically adjusting settings of the virtual environment and artificial intelligence based on said emotion data;

[1063] Includes.

[1064] This not only enables the efficient creation of new inventions and cultures in virtual environments, but also enables dynamic responses to users' emotions, improving the quality of the user experience. Furthermore, time acceleration allows for the rapid collection and analysis of large amounts of data, facilitating applications in the real world.

[1065] "Artificial intelligence" refers to computer systems that mimic human intelligence and have capabilities such as learning, reasoning, and self-correction.

[1066] A "virtual environment" is a simulated environment generated on a computer system, in which physical laws, social systems, etc. can be set.

[1067] "Time acceleration" is a function that allows time in a virtual environment to progress faster than real time.

[1068] A "database" is a collection of electronically stored data, and a system that allows for efficient searching, management, and updating of necessary data.

[1069] The "emotion engine" is a function that recognizes the user's emotions in real time and adjusts the system's operation based on that emotional data.

[1070] "Feedback" refers to opinions and reactions provided by users to a system.

[1071] "Dynamic adjustment" is the ability of a system to automatically change its behavior and settings based on real-time data and conditions.

[1072] "Analysis" is the process of analyzing collected data and deriving useful information and insights from it.

[1073] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment, accelerating time and efficiently generating and acquiring inventions and culture. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system enables dynamic responses according to the user's emotions. This system is composed of a server, a terminal, and a user, each playing a role.

[1074] Server processing

[1075] The server uses Python or a similar programming language to build the virtual environment. It uses a simulation engine to create a city model, set physical laws and environmental variables, and set a time acceleration factor to accelerate the progression of time in the virtual environment.

[1076] Next, machine learning libraries such as TensorFlow and PyTorch are used to generate multiple AI models that mimic the human brain. Each AI model is given different characteristics and skill sets, and begins to operate autonomously within the virtual environment. The server collects the data generated by these AI models and stores it in a database.

[1077] The server then applies machine learning algorithms to analyze the collected data, identifying useful technologies and cultures and automatically generating patent application documents based on the analysis results.

[1078] Processing by the terminal

[1079] The device provides a user interface using a web application or dedicated software. This interface allows users to visualize the status of the virtual environment and the activity of the AI ​​in real time. Various data is displayed in dashboard format, making operation easy.

[1080] Users can provide feedback through their devices, which can be specific ideas or suggestions for improvement, and the devices then send this to the server, which then dynamically adjusts the virtual environment and AI settings based on this feedback.

[1081] Incorporating an emotion engine

[1082] The emotion engine uses OpenCV and TensorFlow to analyze the user's facial expressions, voice, and text data in real time. The analysis results are sent to the server as emotion data, and the server dynamically adjusts the virtual environment and artificial intelligence settings based on this data.

[1083] For example, if the user is excited, the server will accelerate projects in the virtual environment or add new challenging tasks, and if the user is frustrated, the artificial intelligence will be instructed to prioritize solving that problem.

[1084] Specific examples

[1085] For example, to simulate the invention of a new energy source, we proceed as follows:

[1086] 1. Setting up the virtual environment: The server builds a city model and sets up the climatic conditions and energy demands.

[1087] 2. Generation of artificial intelligence: The server generates an artificial intelligence model specialized in energy engineering and an artificial intelligence model knowledgeable in socioeconomics.

[1088] 3. Start of activity simulation: The server simulates the activities of these artificial intelligences in advancing research and development of new energy sources within the virtual city.

[1089] 4. Use of emotion engine: The device detects the user's emotions, such as excitement or anxiety, and sends that data to the server, which then adjusts the AI's behavior based on that information.

[1090] 5. Data Collection and Analysis: The server collects and analyzes data on new energy sources, identifies useful technologies, and uses the results in patent applications.

[1091] Example prompt: "I would like to present an idea for a new energy technology and observe how it evolves in a virtual environment."

[1092] As described above, the present invention provides an efficient and effective invention generation system that combines a virtual environment and dynamic responses based on the user's emotions.

[1093] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1094] Step 1: Configure and build a virtual environment

[1095] The server uses Python to create a virtual environment. Using a simulation engine like SimCity, it models the topography of a city and sets environmental variables such as climate conditions and energy demand. Parameters such as the city name, temperature, and humidity are received as input. Data processing involves generating a virtual environment based on these parameters. The output is a model of the constructed virtual city. Specifically, the server executes commands such as "simcity.create_city('Tokyo', temperature=25, humidity=60)".

[1096] Step 2: Setting time acceleration

[1097] The server sets a time acceleration factor to accelerate time in the virtual environment. As input, it receives a time acceleration factor value. As data processing, it applies this factor to the time variables of the virtual environment. As output, it obtains an accelerated time environment. Specifically, the server executes the command "simcity.set_time_acceleration(100)".

[1098] Step 3: Instantiating the Artificial Intelligence

[1099] The server generates an artificial intelligence model using TensorFlow or PyTorch. As input, it receives the type of AI model and its skill set. As data processing, it generates AI instances with different characteristics and skills based on this information. As output, it obtains the generated AI instances. Specifically, the server executes a command such as "ai_instance = AIModel('Engineer', skills=['mechanics', 'dynamics'])".

[1100] Step 4: Start the activity simulation

[1101] The server makes the generated AI model operate autonomously within the virtual environment. As input, it receives the AI ​​model and task information. As data processing, it assigns a task to the AI ​​model and begins operating within the virtual environment. As output, it obtains the AI ​​model's activity data and deliverables. Specifically, the server executes the command "simcity.assign_task(ai_engineer, 'develop energy source')".

[1102] Step 5: Data collection and storage

[1103] The server collects the activity data of the AI ​​model and stores it in a database. As input, it receives the activity data of the AI ​​model. As data processing, it organizes this data and converts it into a format that can be stored in the database. As output, it obtains the data stored in the database. Specifically, the server executes the code "database.save('energy_research_results', ai_engineer.results)".

[1104] Step 6: Data analysis and technology identification

[1105] The server analyzes the collected data and identifies useful technologies. As input, it receives stored activity data. As data processing, it analyzes the data using machine learning algorithms and identifies useful technologies. As output, it obtains information about the identified technologies. Specifically, the server executes the command "analyze_data('energy_research_results')".

[1106] Step 7: Providing a User Interface

[1107] The device provides a user interface and visualizes the virtual environment and AI activity in real time. It uses the activity data received from the server as input. It converts this data into a format that can be visualized as data processing. It outputs a dashboard-style interface. Specifically, the device executes the code "dashboard.update('AI Activity', ai_activity_data)".

[1108] Step 8: Receiving and sending feedback

[1109] The device receives feedback from the user and sends it to the server. As input, it receives the user's feedback data. As data processing, it converts this feedback data into an appropriate format. As output, it sends the feedback to the server. Specifically, the device executes the code "user_feedback = get_user_input()" and "send_to_server(user_feedback)".

[1110] Step 9: Emotion recognition and dynamic regulation

[1111] The server uses an emotion engine to recognize the user's emotions in real time. As input, it receives the user's facial expressions, voice, and text data. As data processing, it analyzes this data to identify emotions. As output, it obtains the user's emotion data. Specifically, the server executes the code "emotion = detect_emotion(camera_feed)" and "send_to_server(emotion_data)".

[1112] Step 10: Dynamic adjustment of virtual environment and AI

[1113] The server dynamically adjusts the virtual environment and artificial intelligence settings based on the acquired emotional data. It receives emotional data as input. It processes the data by changing the AI's behavior and virtual environment settings based on this data. It outputs the adjusted virtual environment and AI behavior data. Specifically, the server executes the command "adjust_AI_behavior(emotion_data)".

[1114] (Application example 2)

[1115] 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."

[1116] When autonomous vehicles are operating, various unexpected situations and obstacles can occur. These can increase passenger anxiety and discomfort, resulting in problems such as reduced operational efficiency and safety. Furthermore, it is necessary to properly identify passenger emotions and respond flexibly accordingly, but current systems are inadequate in this regard. Therefore, it is necessary to provide flexible responses to unexpected situations and dynamic measures according to passenger emotions.

[1117] 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.

[1118] In this invention, the server includes means for operating multiple artificial intelligences modeled on the human brain in a virtual environment, means for accelerating time in the virtual environment, means for acquiring inventions and cultures generated in the virtual environment and storing them in a database, means for analyzing the acquired inventions and cultures and identifying useful technologies, means for managing the operation of the autonomous vehicle, recognizing and dynamically responding to user emotions, and means for the autonomous vehicle to search for an alternative route in the event of an obstacle and providing measures to reassure passengers based on their emotions. This enables the autonomous vehicle to respond flexibly to unexpected situations and quickly and appropriately to passenger emotions.

[1119] "Artificial intelligence" is a system that performs intellectual tasks using algorithms and programs that mimic the functions of the human brain.

[1120] A "virtual environment" is a model of the real world reproduced on a computer system, and is a simulated space that includes elements such as terrain, climate, and social systems.

[1121] "Means of accelerating time" is a technology that allows time in a virtual environment to pass faster than actual time, making it possible to simulate a long period of time in a short period of time.

[1122] A "database" is an information system for efficiently storing, searching, and managing large amounts of data, and stores data on the aforementioned inventions and cultures.

[1123] An "autonomous mobile object" is a machine that operates and moves on its own initiative without the need for external control, and specifically refers to self-driving vehicles.

[1124] "Means for recognizing emotions" refers to technology that identifies a user's psychological state by analyzing the user's facial expressions, voice, text data, etc.

[1125] "Dynamic response means" refers to the ability to adjust the system in real time according to the situation and the user's emotions, and to execute the optimal response or action.

[1126] The "means for searching alternative routes" is an algorithm that considers new routes and allows a moving vehicle to adopt the optimal route depending on traffic conditions and obstacles.

[1127] "Reassuring measures" are measures or actions to reduce the user's anxiety or stress, and include, for example, playing music or providing information.

[1128] System Configuration

[1129] The system of the present invention is realized with the following configuration.

[1130] Server processing

[1131] 1. Configure and build the virtual environment:

[1132] The server first sets up a virtual environment, creating a virtual space modeled on the city's topography and climate. It also sets the laws of physics and environmental variables within this virtual environment. It also sets a time acceleration factor, allowing the virtual environment to progress faster than real time.

[1133] 2. Artificial Intelligence Generation:

[1134] The server generates multiple AIs modeled after the human brain, each with its own unique characteristics and skills. For example, models specializing in energy engineering and socioeconomics are included. These AIs operate autonomously within the virtual environment, generating new inventions and cultures.

[1135] 3. Data Collection and Analysis:

[1136] The server collects data on inventions and cultures generated in the virtual environment, stores it in a database, and analyzes the collected data to identify technologies and cultures that are useful in the real world, enabling the generation of patent documents and patent applications.

[1137] Processing by the terminal

[1138] 1. Real-time visualization:

[1139] The device provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time, allowing the user to observe the virtual environment and the activities of the AI ​​in detail.

[1140] 2. Incorporating feedback:

[1141] The device receives feedback from the user and sends it to a server, which dynamically adjusts the settings of the virtual environment and artificial intelligence based on this feedback.

[1142] Incorporating an emotion engine

[1143] 1. Emotion recognition:

[1144] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize the user's emotions in real time. This emotional data is received by the server and used to adjust the behavior of the virtual environment and artificial intelligence.

[1145] 2. Emotion-based responses:

[1146] Based on the user's emotions, the server adjusts the autonomous vehicle's behavior and responses in real time. For example, if the user feels anxious, the server may search for an alternative route.

[1147] Hardware and software used

[1148] Hardware: Autonomous mobile devices (e.g., self-driving cars), high-performance server computers (e.g., NVIDIA Drive)

[1149] Software: Python programming language, machine learning libraries (e.g., TensorFlow), emotion recognition libraries (e.g., OpenCV)

[1150] Specific examples

[1151] For example, consider an application example when traffic congestion occurs.

[1152] 1. The server runs an autonomous vehicle in a virtual environment where random traffic jams may occur.

[1153] 2. At this point, the autonomous vehicle's artificial intelligence will become anxious and search for an alternative route.

[1154] 3. The user can observe this situation through the device and provide feedback as needed, for example, allowing the user to suggest valid alternative routes.

[1155] 4. The emotion engine recognizes the user's anxiety and communicates it to the server, which then adjusts the AI's behavior and takes steps to alleviate the anxiety.

[1156] Prompt Sentence Examples

[1157] A prompt to input to a generative AI model how a self-driving vehicle will behave in a given traffic situation:

[1158] When an autonomous vehicle is traveling according to a city model, it suddenly encounters a traffic jam. Considering that the ongoing load factor is 0.8, what should be the next action? The emotional state of the vehicle is anxious, but please also suggest ways to reassure the passengers.

[1159] In this way, the present invention enables dynamic and adaptive responses according to the user's emotions, thereby enhancing the operation management of autonomous vehicles.

[1160] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1161] Step 1: Configure and build a virtual environment

[1162] The server sets the basic structure of the city, including its topography, climate, and social systems. At the same time, it also sets the laws of physics and environmental variables (temperature, humidity, etc.). Using city model data as input, a virtual environment is constructed as output. Specifically, a 3D model of the city is generated using computer graphics and run on a simulation engine.

[1163] Step 2: Generate artificial intelligence

[1164] The server generates multiple AI models modeled after the human brain. Different characteristics and skills are input to each AI. The input is data defining the characteristics and skills, and the output is the generation of multiple AI instances. Specifically, machine learning algorithms are applied to each AI model, and specific skills are learned using training data.

[1165] Step 3: Set the time acceleration factor

[1166] The server sets a time acceleration factor to accelerate time in the virtual environment. The input is the time acceleration factor, and the output is the speed of virtual time relative to real time. Specifically, the server controls the progression of time in the virtual environment by changing the simulation time step.

[1167] Step 4: Simulating AI activity

[1168] The server simulates the activities of the AI ​​generated within the virtual environment. The virtual environment, AI instances, and environmental variables are used as input, and the AI's activity history data is generated as output. Specifically, each AI acts autonomously within the simulation engine and performs designated tasks.

[1169] Step 5: Collect and store data

[1170] The server collects data on the AI's activities within the virtual environment, as well as the inventions and cultural data it generates, and stores them in a database. Simulation data is used as input, and an organized database is generated as output. Specifically, a data collection agent collects the activity data of each AI and stores it in the database in an appropriate format.

[1171] Step 6: Data analysis and feedback

[1172] The server analyzes the data stored in the database to identify useful technologies and generates patent documents based on the analysis results. The acquired data is used as input, and an analysis report and patent documents are generated as output. Specifically, data analysis algorithms are used to identify interesting patterns and generate technology feasibility reports.

[1173] Step 7: Real-time visualization

[1174] The device displays the status of the virtual environment and the activity of the AI ​​in real time. It uses the virtual environment and AI activity data as input and provides a visualized graphical interface as output. Specifically, it displays real-time data in a dashboard format while updating it.

[1175] Step 8: Incorporating user feedback

[1176] The device receives feedback from the user and sends it to the server. The server dynamically adjusts the virtual environment and AI based on the feedback. The user's feedback data is used as input, and the parameters of the virtual environment and AI are dynamically updated as output. Specifically, after receiving the feedback data, the simulation parameters are recalculated and applied in real time.

[1177] Step 9: Emotion recognition and response adjustment

[1178] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize their emotional state. The server then adjusts the AI's behavior based on this information. The input is the user's emotional data, and the output is an emotion-based response action. Specifically, the emotion recognition software performs real-time analysis and takes reassuring action as needed.

[1179] Step 10: Encountering obstacles and finding alternative routes

[1180] When an autonomous vehicle encounters a fault in the virtual environment or in the real world, the server searches for an alternative route and provides reassurance measures. Using fault information and current traffic information as input, the server generates the optimal alternative route and reassurance measures as output. Specifically, the server analyzes traffic congestion and accident information and presents a safe and fast alternative route.

[1181] 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.

[1182] 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.

[1183] 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.

[1184] [Fourth embodiment]

[1185] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1186] 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.

[1187] 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).

[1188] 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.

[1189] 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.

[1190] 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).

[1191] 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.

[1192] 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.

[1193] 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.

[1194] 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.

[1195] 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.

[1196] 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.

[1197] 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."

[1198] This invention is a system that operates multiple artificial intelligences modeled after the human brain in a virtual environment, and accelerates time in the virtual world to efficiently generate and acquire inventions and culture. This system is composed of a server, terminals, and users, each playing their own role.

[1199] Server processing

[1200] Setting up and building a virtual environment

[1201] The server sets the basic structure of the virtual environment (topography, climate, social systems, etc.) For example, it models the topography of a city and sets the physical laws and environmental variables to simulate the growth of the city.

[1202] The server sets a time acceleration factor, causing time in the virtual environment to progress faster than in reality, allowing long-term changes to be observed in a short period of time.

[1203] Artificial Intelligence Instance Generation

[1204] The server generates multiple AI models modeled after the human brain, each with different characteristics and initial skill sets—for example, one model might be good at engineering, while another might be talented at art.

[1205] These AIs operate autonomously within the virtual environment, growing and developing as they interact with each other.

[1206] Running an activity simulation

[1207] The server simulates the activities of the AI ​​in a virtual environment, observes the process of the AI ​​generating inventions and culture, and collects the generated data.

[1208] For example, the process by which new energy technologies are developed or new musical genres are formed can be simulated in a virtual urban environment.

[1209] Data collection and analysis

[1210] The server stores the inventions and cultures generated within the virtual environment in a database.

[1211] The collected data is analyzed to identify useful technologies and cultures, which then lead to patent applications and technological applications in the real world.

[1212] Processing by the terminal

[1213] Providing a user interface

[1214] The device provides the user with an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time. For example, a dashboard displays the activity history of each AI and the progress of inventions.

[1215] The terminal will have an interface designed to make it easy for users to search for information about specific inventions or cultures.

[1216] Receiving and sending feedback

[1217] The terminal receives feedback from the user and sends it to the server, which uses the feedback to improve the system or propose new inventions.

[1218] For example, a user can input an idea for a new energy source and the idea can be tested in a virtual environment.

[1219] User Action

[1220] Virtual environment observation and intervention

[1221] Users can observe the status of the virtual environment through their devices, for example, checking the development of the virtual city and the activity history of the AI ​​in real time.

[1222] Users can also intervene in the virtual environment and artificial intelligence, for example by introducing certain technologies into the virtual environment and observing their effects.

[1223] Specific examples

[1224] For example, to simulate the invention of a new energy source in a virtual environment:

[1225] 1. Setting up the virtual environment: The server sets up the basic data (topography, climate, energy demand, etc.) to simulate a city.

[1226] 2. Generation of artificial intelligence: The server generates an artificial intelligence model that is strong in energy engineering and an artificial intelligence model that is knowledgeable in socioeconomics.

[1227] 3. Start of activity simulation: The server simulates the research and development of new energy sources in a virtual city. Each AI cooperates to develop new technologies.

[1228] 4. Data collection and analysis: The server stores the generated data on the new energy sources in a database and analyzes them. Based on the analysis results, patent applications and real-world applications can be made.

[1229] In this way, the present invention provides an innovative system that can efficiently generate new technologies and cultures and utilize them in the real world.

[1230] The processing flow will be explained below.

[1231] Step 1:

[1232] The server sets the basic structure of the virtual environment. It generates terrain data within the virtual environment and establishes climatic conditions and social systems. For example, it builds a model of a city and places the necessary infrastructure and housing there. It also sets the laws of physics and environmental variables (temperature, humidity, etc.).

[1233] Step 2:

[1234] The server sets a time acceleration factor, which sets the passage of time in the virtual environment to hundreds of seconds of virtual time per second of real time, allowing long-term changes to be observed in a short period of time.

[1235] Step 3:

[1236] The server generates multiple AI models modeled after the human brain, each with its own unique characteristics and initial skill set—for example, one AI may be good at engineering, while another may be talented in art.

[1237] Step 4:

[1238] The server allows the AIs generated within the virtual environment to begin acting autonomously, creating an environment in which they can influence each other and develop, for example, working together to develop new energy technologies within a city.

[1239] Step 5:

[1240] The server simulates the AI's activities in the virtual environment, observing, for example, the invention of a new energy source or the formation of a new culture, and collecting necessary data. The AI-generated inventions and cultural data are then stored in a database.

[1241] Step 6:

[1242] The server analyzes the collected data, identifies technologies and cultures that are useful in the real world, generates patent documents based on the analysis results, prepares patent applications, and provides appropriate feedback to users to allow them to access the system.

[1243] Step 7:

[1244] The terminal provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time, allowing users to observe the activity history of each AI and the progress of their inventions.

[1245] Step 8:

[1246] The device receives feedback from users and sends it to the server. Users input and submit ideas for new inventions and system improvements, which are reflected in the virtual environment and the activities of the artificial intelligence. This allows the entire system to evolve in a way that meets user expectations.

[1247] Step 9:

[1248] Users can observe the situation in the virtual environment through their devices and intervene in specific locations or artificial intelligence, for example, to observe the impact of the introduction of new technology or to issue instructions to accelerate a specific project.

[1249] In this way, by having the server, terminal, and user fulfill their respective roles, a system is realized in which new inventions and cultures can be efficiently generated and acquired through the activities of artificial intelligence within the virtual environment, and then utilized in the real world.

[1250] Example 1

[1251] 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."

[1252] Conventional artificial intelligence systems have had problems with the efficient creation and acquisition of new technologies and cultures. They also lack the ability to manage time in virtual environments, visualize the activities of intelligent models with diverse characteristics, and incorporate user feedback. Therefore, there has been a need for a system that can solve these problems and efficiently create and acquire new technologies and cultures using an intelligent model that mimics the human brain.

[1253] 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.

[1254] In this invention, the server includes a means for operating a plurality of intelligent models imitating the human brain in a virtual space, a means for accelerating the time of the virtual space in which the intelligent models are active, a means for acquiring innovations and cultures generated in the virtual space and storing them in an information base, and a means for analyzing the acquired innovations and cultures and identifying useful technologies, thereby enabling the efficient generation and acquisition of new technologies and cultures using intelligent models.

[1255] An "intelligent model" is an information processing system that mimics the human brain, has multiple characteristics and capabilities, and operates autonomously within a virtual space.

[1256] A "virtual space" is a virtual environment that mimics a real physical environment using digital technology, allowing people and intelligent models to interact with each other.

[1257] "Time acceleration" is a technique that sets the speed at which time progresses in a virtual space to be faster than real time, allowing long-term changes and developments to be observed in a short period of time.

[1258] "Innovation" is a general term for new technologies, ideas, or inventions generated within the virtual world.

[1259] "Culture" is a general term for new art forms, music, literature, customs, or other social phenomena that are generated within virtual spaces.

[1260] An "information base" is a digital storage system for storing innovations and culture generated within virtual space as data.

[1261] "Analysis" is the process of examining the data stored in an information base in detail to extract specific patterns and useful information.

[1262] "Feedback" refers to opinions, suggestions, or evaluations sent by users, and is information that is useful for improving the virtual space or intelligent model or for starting new activities.

[1263] This invention is a system that operates an intelligent model that mimics the human brain in a virtual space, and accelerates time in the virtual space, thereby efficiently generating and acquiring innovation and culture.

[1264] Server processing

[1265] Setting up and building a virtual space

[1266] The server sets the basic structure of the virtual space. Specifically, it sets elements such as the terrain, climate, and social systems. For example, it models cities in mountainous regions and warm climates. The server also sets a time acceleration factor, making time progress faster in the virtual space than in reality. This can be set so that one second is equivalent to one year.

[1267] Intelligent Model Instantiation

[1268] The server generates multiple intelligent models modeled after the human brain. Each intelligent model has different characteristics and skill sets. For example, there is a model specializing in energy engineering and another specializing in art. These intelligent models operate autonomously within the virtual space, growing and developing as they interact with each other.

[1269] Running an activity simulation

[1270] The server simulates the activities of intelligent models in a virtual space. For example, an intelligent model specializing in energy engineering researches new energy sources, while an intelligent model specializing in economics analyzes their social impact. This results in the creation of new technologies and cultures.

[1271] Data collection and analysis

[1272] The server stores the innovations and cultures generated in the virtual world in a database. The collected data is analyzed by the server to identify useful technologies and cultures. The results of this analysis are used for patent applications and real-world applications.

[1273] Processing by the terminal

[1274] Providing a user interface

[1275] The terminal provides users with an interface that visualizes the status of the virtual space and the activities of the intelligent models in real time. For example, a dashboard visually displays the activity history of each intelligent model and the progress of inventions. The terminal is also designed to make it easy for users to search for information on specific innovations or cultures.

[1276] Receiving and sending feedback

[1277] The device receives feedback from the user and sends it to the server. For example, the user can input an idea for a new energy source, and the idea is tested in the virtual space. The server then modifies the virtual space and intelligent model based on the received feedback and starts a new simulation.

[1278] User Action

[1279] Observation and intervention in virtual spaces

[1280] Users can observe the state of the virtual space through their devices. For example, they can check the development of the virtual city and the activity history of the intelligent model in real time. Furthermore, users can intervene in the virtual space and the intelligent model. Specifically, they can introduce new technologies into the virtual space and observe their effects.

[1281] Specific examples

[1282] Simulation of the invention of a new energy source

[1283] 1. Virtual Space Setup: The server sets up terrain data to simulate a mountainous city, with a warm climate and medium energy demands.

[1284] 2. Generation of intelligent models: The server generates an intelligent model specialized in energy engineering and an intelligent model specialized in socioeconomics, and provides initial data to each.

[1285] 3. Start of activity simulation: The server simulates the research and development of new energy sources in a virtual city. The energy engineering model conducts research on new technologies, and the economics model analyzes the economic impact of the technologies.

[1286] 4. Data collection and analysis: The server stores the generated data on the new energy sources in a database and analyzes them. Based on the analysis results, a patent application is prepared.

[1287] An example prompt is:

[1288] "Simulate the research and development of new energy sources. Set a virtual city with the following parameters: terrain is mountainous, climate is temperate, and energy demand is moderate. Use an AI specialized in energy engineering and an AI specialized in socioeconomics to analyze the development of new technologies and their economic impact."

[1289] In this way, this invention provides an innovative system for efficiently generating and acquiring new technologies and cultures and applying them to the real world.

[1290] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1291] Step 1:

[1292] The server sets up the virtual space. As input, the server receives basic parameters such as topography, climate, and social systems. Based on these parameters, it processes data to build a digital environment. Specifically, it inputs topographical data for mountainous areas and information on temperate climates, and generates the basic structure of a virtual city based on that data. The output is the basic structure of the virtual space.

[1293] Step 2:

[1294] The server instantiates intelligent models. The server receives input parameters for generating intelligent models with different characteristics and skill sets. For example, information for generating an AI model specialized in energy engineering or an AI model specialized in art is used as input. The server instantiates an intelligent model based on these parameters and inputs the initial skill set and knowledge base. The output is the generated multiple intelligent models.

[1295] Step 3:

[1296] The server runs the activity simulation. The inputs are the virtual space setting information and the generated intelligent model. The server sets up a scenario in which the intelligent model will operate autonomously, and by setting a time acceleration factor, it simulates a time progression speed where, for example, one second is equivalent to one year. In concrete terms, an AI specialized in energy engineering researches new energy sources, while another AI analyzes the social impact of that technology. The output here is data on the generated technology and culture.

[1297] Step 4:

[1298] The server collects and analyzes data. It receives as input data on technology and culture generated as a result of the activity simulation. The server stores this data in a database and applies analytical algorithms to extract useful information. Specifically, it records the development process and results of new energy technologies in the database and performs data analysis to identify highly energy-efficient technologies. The output from this process is the analysis results. Based on these results, patent applications are prepared.

[1299] Step 5:

[1300] The terminal provides a user interface. As input, it receives data on the virtual space and the activity status of the intelligent models sent from the server. The terminal visualizes this data and displays it on a dashboard so that the user can easily understand it. Specifically, it graphically displays the activity history of each intelligent model, research progress, and data on the generated technology. Here, the visualized information is provided to the user as output.

[1301] Step 6:

[1302] The device receives and sends feedback. As input, it receives feedback and suggestions from users. The device converts this into an appropriate format and sends it to the server. For example, a user can input a suggestion for a new energy-efficient technology and send the suggestion to the server for testing in the virtual space. Here, the output is the feedback sent to the server.

[1303] Step 7:

[1304] The user observes the virtual space and intervenes. The input is visualized data provided by the terminal. Based on this data, the user makes specific interventions in the virtual space or intelligent model. For example, a new technology can be introduced into the virtual space and its impact can be observed in real time. A specific action involves the user introducing a new energy technology into a virtual city and analyzing the economic impact of that technology. The output is the results of the intervention and feedback.

[1305] Through these steps, inventions can utilize intellectual models to efficiently generate new technologies and cultures and apply them to the real world.

[1306] (Application example 1)

[1307] 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."

[1308] Production planning in modern factories involves complex intertwining factors, making it difficult to create efficient and optimal plans. Furthermore, conventional simulation and optimization methods require enormous computational resources and time, making real-time adjustments and optimization difficult. This creates a need for efficient production plans that can be quickly applied to actual production lines. Furthermore, a means of quickly and effectively incorporating user feedback is also required.

[1309] 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.

[1310] In this invention, the server includes means for simulating virtual factory settings, equipment layout, and production lines in a virtual environment, means for generating artificial intelligence models with different skill sets and optimizing production plans in the virtual factory, and means for accelerating the time in the virtual environment. This enables efficient simulation of various production plans in a short period of time and the derivation of optimal production plans. Furthermore, by quickly applying these optimized plans to a real production line, efficient production management and optimal resource utilization can be achieved. Furthermore, by incorporating user feedback in real time, the latest and optimal production plans can be maintained.

[1311] A "virtual factory" is a virtual environment that mimics a real factory, where the layout of equipment and the structure of production lines are simulated on a computer.

[1312] "Equipment layout" refers to the layout of machines and devices within a factory, and is a factor that affects production efficiency and work flow.

[1313] A "production line" is a series of steps organized into a single flow during the manufacturing process of a product, and is an important element for efficient production.

[1314] An "artificial intelligence model" is a computational model designed to mimic human intelligence and perform machine learning and data analysis.

[1315] "Different skill sets" refer to the unique collection of abilities and expertise each AI model possesses, enabling it to perform well in specific fields.

[1316] "Accelerating time in a virtual environment" means making time pass faster in a virtual environment than in the real world, a means of observing long-term effects in the short term.

[1317] "Optimization" refers to adjusting systems and processes to achieve the best results for a specific purpose, with the aim of operating efficiently.

[1318] "Feedback" refers to opinions and impressions provided by users, and is information used to help improve systems and processes.

[1319] "Real-time" refers to processing and responses that are carried out in line with the real time axis, meaning that results are obtained almost immediately.

[1320] A "production plan" is a plan for production activities in a factory, including resource allocation, process order, schedule, etc.

[1321] "Simulation" is a method of imitating real-world systems and processes in a virtual environment to make predictions and analyses.

[1322] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment to efficiently generate and acquire inventions and culture. This system is composed of a server, terminals, and users, each playing their own role.

[1323] Server processing

[1324] Setting up and building a virtual environment

[1325] The server configures the virtual factory, equipment layout, and production line configuration. It generates multiple AI models with different skill sets and runs them in the virtual environment. It also accelerates the time in the virtual environment, running short-term and long-term simulations. For example, it can simulate the layout that maximizes factory production efficiency and the optimal production line.

[1326] Artificial Intelligence Instance Generation

[1327] The server generates multiple artificial intelligence (AI) models with different characteristics and skill sets. Each AI model excels in a specific skill and performs activities to optimize the factory's production plan. For example, some AI models specialize in quality control, while others optimize production schedules.

[1328] Running an activity simulation

[1329] The server simulates the AI's activities within the virtual factory, allowing it to test different production plans and derive the most efficient one. The generated data is stored in a database and later analyzed. For example, different production lines and layout patterns can be tried to find the optimal combination.

[1330] Data collection and analysis

[1331] The server stores production plans and other data generated within the virtual environment in a database and provides tools to analyze this data and identify the most useful techniques and plans. For example, the generated data can be used to find the optimal plan to reduce production costs.

[1332] Processing by the terminal

[1333] Providing a user interface

[1334] The terminal provides users with an interface that visualizes the virtual factory settings and AI activity in real time. For example, a dashboard displays the efficiency and quality status of each production line. The terminal is also designed to allow users to easily search and access information related to specific production plans.

[1335] Receiving and sending feedback

[1336] The terminal receives feedback from the user and sends it to the server. The feedback is used to improve the system and propose new production plans. For example, the user can input a new equipment layout proposal and try it out in the virtual environment.

[1337] User Action

[1338] Virtual Factory Observation and Intervention

[1339] Users can observe the status of the virtual factory through their terminals. For example, they can check the efficiency and quality fluctuations of the virtual factory's production line in real time. Users can also intervene in the virtual environment and artificial intelligence. For example, they can introduce a specific production plan into the virtual environment and observe its effects.

[1340] Specific examples

[1341] For example, to simulate the optimization of a new production line in a virtual factory:

[1342] 1. Setting up the virtual environment: The server sets up the factory equipment layout and basic data for the production line.

[1343] 2. Generation of artificial intelligence: The server generates an AI model that is strong in areas such as efficiency, quality control, and schedule management.

[1344] 3. Start of activity simulation: The server simulates the testing of a new production plan in the virtual factory. Each AI model cooperates to optimize the plan.

[1345] 4. Data collection and analysis: The server collects and analyzes data related to the generated production plan. Based on the analysis results, the optimal plan is applied to the real-world factory.

[1346] As a result, the present invention can provide an innovative system for quickly generating an efficient production plan and applying it to a real factory.

[1347] Example prompt for a generative AI model:

[1348] "Simulate a new production plan within this virtual factory. Consider the efficiency, quality, and schedule of each production process and propose the optimal production plan."

[1349] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1350] Step 1:

[1351] Virtual Factory Configuration

[1352] The server sets and builds the basic data of the virtual factory (terrain, climate, equipment layout, production lines, etc.). The input is the factory's equipment information and layout diagram, and the output is a factory model in the virtual environment. Specifically, the server reads the terrain data and 3D models and places them in the virtual space.

[1353] Step 2:

[1354] Generating artificial intelligence models

[1355] The server generates artificial intelligence models with different skill sets. The input is the skill set information to be given to each AI model, and the output is the generated AI model. Specifically, it instantiates AI with engineering concepts, AI specialized in quality control, AI specialized in schedule optimization, etc., and places them in the virtual environment.

[1356] Step 3:

[1357] Starting the simulation

[1358] The server simulates AI activity within a virtual factory. The input is the virtual environment and AI model, and the output is the simulation result data. The server accelerates time to test multiple scenarios at high speed. Specifically, it calculates fluctuations in production line efficiency and quality, and executes the plans proposed by each AI model.

[1359] Step 4:

[1360] Data collection

[1361] The server collects data generated within the virtual environment. The input is activity data obtained from the simulation, and the output is data stored in a database. Specifically, metrics such as production efficiency and costs from each simulation are collected and stored in the database.

[1362] Step 5:

[1363] Data analysis

[1364] The server analyzes the collected data. The input is simulation data retrieved from the database, and the output is the identification of the optimal production plan and technology. The server applies statistical analysis and machine learning algorithms to derive useful results. Specifically, it identifies the most efficient plan or the least costly plan.

[1365] Step 6:

[1366] Visualizing the results

[1367] The terminal presents the analysis results to the user. The input is the analyzed data, and the output is a report displayed on the user interface. Specifically, the dashboard displays items such as production efficiency, quality control, and costs in graphs and tables.

[1368] Step 7:

[1369] Receiving Feedback

[1370] The terminal receives feedback input from the user. The input is the user's feedback information, and the output is feedback data sent to the server. In concrete terms, the user inputs new placement plans or improvement plans, which are then sent to the server.

[1371] Step 8:

[1372] Reflecting feedback

[1373] The server adjusts and updates the virtual factory and AI model based on the received feedback. The input is the feedback data from the user, and the output is an updated virtual environment and AI model. Specifically, the server incorporates the user's proposed layout plan into the simulation and tests its efficiency again.

[1374] 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.

[1375] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment, accelerating time to efficiently generate and acquire inventions and culture, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to dynamically respond to the user's emotions. This system is composed of the roles of a server, a terminal, and a user.

[1376] Server processing

[1377] Setting up and building a virtual environment

[1378] The server sets the basic structure of the virtual environment (topography, climate, social systems, etc.). Specifically, it creates a virtual environment modeled on the topography of a city and sets the physical laws and environmental variables (temperature, humidity, etc.).

[1379] Next, we set a time acceleration factor to accelerate the time in the virtual environment, which allows us to simulate several hours of virtual environment in one second of real time.

[1380] Artificial Intelligence Instance Generation

[1381] The server generates multiple AI models modeled after the human brain, each with different characteristics and skill sets—for example, one AI model might specialize in engineering, while another might be interested in art.

[1382] The generated AIs begin to operate autonomously within the virtual environment, cooperating and interacting with each other to create new inventions and cultures.

[1383] Running an activity simulation

[1384] The server simulates the activities of the AIs in the virtual environment, collects data on the inventions and cultures generated by each AI, and stores it in a database.

[1385] For example, observe the process of research and development of new energy technologies within a virtual city and save the results.

[1386] Data collection and analysis

[1387] The server analyzes the collected data to identify technologies and cultures that are useful in the real world, generates patent documents based on the analyzed data, and prepares patent applications.

[1388] It also includes the ability to provide appropriate feedback to help users access the system.

[1389] Processing by the terminal

[1390] Providing a user interface

[1391] The device provides an interface that visualizes the status of the virtual environment and the activity of the AI ​​in real time, allowing the user to check the progress of the virtual environment and the activity history of the AI ​​through this interface.

[1392] For example, a dashboard-style interface will clearly display the activities of each AI and the status of ongoing projects.

[1393] Receiving and sending feedback

[1394] The device receives feedback from the user and sends it to the server, where the user can input new ideas and suggestions for improvement, which are then reflected in the system.

[1395] For example, you can enter an idea for a new energy technology and watch it being tested in a virtual environment.

[1396] Incorporating an emotion engine

[1397] emotion recognition

[1398] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to recognize the user's emotions in real time. The server dynamically adjusts the virtual environment and artificial intelligence settings based on this emotional data.

[1399] For example, if it senses that the user is excited, it may speed up projects within the virtual environment or add new, challenging tasks.

[1400] Emotion-based responses

[1401] The emotion engine recognizes user emotions and adjusts the AI's responses and behaviors in real time, improving the user experience and increasing the system's effectiveness.

[1402] For example, if a user is dissatisfied, the AI ​​will be instructed to prioritize resolving that issue.

[1403] User Action

[1404] Virtual environment observation and intervention

[1405] Users can observe the virtual environment through their terminals and intervene if necessary, for example to observe the impact of the introduction of new technology or to issue instructions to accelerate a particular project.

[1406] By providing feedback on new technologies and improvement ideas from users, the impact of these can be reflected in the virtual environment.

[1407] Specific examples

[1408] For example, to simulate the invention of a new energy source:

[1409] 1. Setting up the virtual environment: The server builds a city model and sets up the climatic conditions and energy demands.

[1410] 2. Generation of artificial intelligence: The server generates an artificial intelligence model specialized in energy engineering and an artificial intelligence model knowledgeable in socioeconomics.

[1411] 3. Start of activity simulation: The server simulates the activities of these artificial intelligences in advancing research and development of new energy sources within the virtual city.

[1412] 4. Use of emotion engine: The device detects the user's emotions, such as excitement or anxiety, and sends that data to the server, which then adjusts the AI's behavior based on that information.

[1413] 5. Data Collection and Analysis: The server collects and analyzes data on new energy sources, identifies useful technologies, and uses the results in patent applications.

[1414] In this way, the present invention provides a more adaptive and effective invention creation system in a virtual environment by appropriately reflecting the user's emotions.

[1415] The processing flow will be explained below.

[1416] Step 1:

[1417] The server sets the basic structure of the virtual environment. It generates terrain data within the virtual environment and establishes climatic conditions and social systems. For example, it models the terrain of a city and places the necessary infrastructure and housing. It also sets the laws of physics and environmental variables (temperature, humidity, etc.).

[1418] Step 2:

[1419] The server sets a time acceleration factor, which sets the passage of time in the virtual environment to hundreds of seconds of virtual time per second of real time, allowing long-term changes to be observed in a short period of time.

[1420] Step 3:

[1421] The server generates multiple AI models modeled after the human brain, each with its own unique characteristics and initial skill set. For example, one AI may be good at engineering, while another may be talented in art.

[1422] Step 4:

[1423] The server then configures the generated AI to begin acting autonomously, creating an environment in which AIs can influence each other and develop, for example, working together to develop new energy technologies for a city.

[1424] Step 5:

[1425] The server simulates the activities of AI within a virtual environment, collects data on inventions and culture generated by the AI, and stores it in a database. For example, it observes the process of developing new energy technologies within a virtual city and records the results.

[1426] Step 6:

[1427] The server analyzes the collected data, identifies technologies and cultures that are useful in the real world, generates patent documents based on the analysis results, prepares patent applications, and provides appropriate feedback to users to allow them to access the system.

[1428] Step 7:

[1429] The device provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time. Through this interface, the user can observe the progress of the virtual environment and the activity history of the AI. For example, a dashboard-style interface displays the activities of each AI and the progress of the project.

[1430] Step 8:

[1431] The device receives feedback from the user and sends it to the server, for example, a user can input an idea for a new energy technology, which is then tested in the virtual environment.

[1432] Step 9:

[1433] The server dynamically adjusts the settings of the virtual environment and the AI ​​based on user feedback by analyzing the feedback and reflecting it in a way that affects the behavior of the virtual environment and the AI.

[1434] Step 10:

[1435] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize the user's emotions in real time. The server receives the recognized emotion data and adjusts the behavior of the virtual environment and artificial intelligence based on it. For example, if the user is excited, it may accelerate projects in the virtual environment or add new, challenging tasks.

[1436] Step 11:

[1437] The device adjusts the AI's responses and behavior in real time based on the user's emotions recognized by the emotion engine. For example, if the user is feeling dissatisfied, the AI ​​will be set to prioritize solving that problem.

[1438] Step 12:

[1439] The server stores the emotion data recognized by the emotion engine in a database for later analysis. This allows the server to accumulate a user's emotion history, enabling more accurate emotion recognition and response.

[1440] In this way, a system is realized in which the server, terminal, user, and emotion engine cooperate to efficiently generate new inventions and culture through the activities of artificial intelligence within a virtual environment and utilize them in the real world.

[1441] Example 2

[1442] 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."

[1443] Conventional AI systems have been inefficient in generating new inventions and culture, and have difficulty dynamically responding to user emotions. This has led to problems such as a poor user experience and limited system effectiveness. Furthermore, there has been a lack of means to rapidly collect and analyze large amounts of data by accelerating time in virtual environments.

[1444] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1445] In this invention, the server

[1446] A means for operating multiple artificial intelligences that mimic the human brain in a virtual environment;

[1447] means for accelerating time in a virtual environment in which said artificial intelligence operates;

[1448] A means for acquiring inventions and cultures generated within the virtual environment and storing them in a database;

[1449] A means for analyzing the acquired inventions and cultures and identifying useful technologies;

[1450] means for recognizing a user's emotions and dynamically adjusting settings of the virtual environment and artificial intelligence based on said emotion data;

[1451] Includes.

[1452] This not only enables the efficient creation of new inventions and cultures in virtual environments, but also enables dynamic responses to users' emotions, improving the quality of the user experience. Furthermore, time acceleration allows for the rapid collection and analysis of large amounts of data, facilitating applications in the real world.

[1453] "Artificial intelligence" refers to computer systems that mimic human intelligence and have capabilities such as learning, reasoning, and self-correction.

[1454] A "virtual environment" is a simulated environment generated on a computer system, in which physical laws, social systems, etc. can be set.

[1455] "Time acceleration" is a function that allows time in a virtual environment to progress faster than real time.

[1456] A "database" is a collection of electronically stored data, and a system that allows for efficient searching, management, and updating of necessary data.

[1457] The "emotion engine" is a function that recognizes the user's emotions in real time and adjusts the system's operation based on that emotional data.

[1458] "Feedback" refers to opinions and reactions provided by users to a system.

[1459] "Dynamic adjustment" is the ability of a system to automatically change its behavior and settings based on real-time data and conditions.

[1460] "Analysis" is the process of analyzing collected data and deriving useful information and insights from it.

[1461] This invention is a system that operates multiple artificial intelligences modeled on the human brain in a virtual environment, accelerating time and efficiently generating and acquiring inventions and culture. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system enables dynamic responses according to the user's emotions. This system is composed of a server, a terminal, and a user, each playing a role.

[1462] Server processing

[1463] The server uses Python or a similar programming language to build the virtual environment. It uses a simulation engine to create a city model, set physical laws and environmental variables, and set a time acceleration factor to accelerate the progression of time in the virtual environment.

[1464] Next, machine learning libraries such as TensorFlow and PyTorch are used to generate multiple AI models that mimic the human brain. Each AI model is given different characteristics and skill sets, and begins to operate autonomously within the virtual environment. The server collects the data generated by these AI models and stores it in a database.

[1465] The server then applies machine learning algorithms to analyze the collected data, identifying useful technologies and cultures and automatically generating patent application documents based on the analysis results.

[1466] Processing by the terminal

[1467] The device provides a user interface using a web application or dedicated software. This interface allows users to visualize the status of the virtual environment and the activity of the AI ​​in real time. Various data is displayed in dashboard format, making operation easy.

[1468] Users can provide feedback through their devices, which can be specific ideas or suggestions for improvement, and the devices then send this to the server, which then dynamically adjusts the virtual environment and AI settings based on this feedback.

[1469] Incorporating an emotion engine

[1470] The emotion engine uses OpenCV and TensorFlow to analyze the user's facial expressions, voice, and text data in real time. The analysis results are sent to the server as emotion data, and the server dynamically adjusts the virtual environment and artificial intelligence settings based on this data.

[1471] For example, if the user is excited, the server will accelerate projects in the virtual environment or add new challenging tasks, and if the user is frustrated, the artificial intelligence will be instructed to prioritize solving that problem.

[1472] Specific examples

[1473] For example, to simulate the invention of a new energy source, we proceed as follows:

[1474] 1. Setting up the virtual environment: The server builds a city model and sets up the climatic conditions and energy demands.

[1475] 2. Generation of artificial intelligence: The server generates an artificial intelligence model specialized in energy engineering and an artificial intelligence model knowledgeable in socioeconomics.

[1476] 3. Start of activity simulation: The server simulates the activities of these artificial intelligences in advancing research and development of new energy sources within the virtual city.

[1477] 4. Use of emotion engine: The device detects the user's emotions, such as excitement or anxiety, and sends that data to the server, which then adjusts the AI's behavior based on that information.

[1478] 5. Data Collection and Analysis: The server collects and analyzes data on new energy sources, identifies useful technologies, and uses the results in patent applications.

[1479] Example prompt: "I would like to present an idea for a new energy technology and observe how it evolves in a virtual environment."

[1480] As described above, the present invention provides an efficient and effective invention generation system that combines a virtual environment and dynamic responses based on the user's emotions.

[1481] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1482] Step 1: Configure and build a virtual environment

[1483] The server uses Python to create a virtual environment. Using a simulation engine like SimCity, it models the topography of a city and sets environmental variables such as climate conditions and energy demand. Parameters such as the city name, temperature, and humidity are received as input. Data processing involves generating a virtual environment based on these parameters. The output is a model of the constructed virtual city. Specifically, the server executes commands such as "simcity.create_city('Tokyo', temperature=25, humidity=60)".

[1484] Step 2: Setting time acceleration

[1485] The server sets a time acceleration factor to accelerate time in the virtual environment. As input, it receives a time acceleration factor value. As data processing, it applies this factor to the time variables of the virtual environment. As output, it obtains an accelerated time environment. Specifically, the server executes the command "simcity.set_time_acceleration(100)".

[1486] Step 3: Instantiating the Artificial Intelligence

[1487] The server generates an artificial intelligence model using TensorFlow or PyTorch. As input, it receives the type of AI model and its skill set. As data processing, it generates AI instances with different characteristics and skills based on this information. As output, it obtains the generated AI instances. Specifically, the server executes a command such as "ai_instance = AIModel('Engineer', skills=['mechanics', 'dynamics'])".

[1488] Step 4: Start the activity simulation

[1489] The server makes the generated AI model operate autonomously within the virtual environment. As input, it receives the AI ​​model and task information. As data processing, it assigns a task to the AI ​​model and begins operating within the virtual environment. As output, it obtains the AI ​​model's activity data and deliverables. Specifically, the server executes the command "simcity.assign_task(ai_engineer, 'develop energy source')".

[1490] Step 5: Data collection and storage

[1491] The server collects the activity data of the AI ​​model and stores it in a database. As input, it receives the activity data of the AI ​​model. As data processing, it organizes this data and converts it into a format that can be stored in the database. As output, it obtains the data stored in the database. Specifically, the server executes the code "database.save('energy_research_results', ai_engineer.results)".

[1492] Step 6: Data analysis and technology identification

[1493] The server analyzes the collected data and identifies useful technologies. As input, it receives stored activity data. As data processing, it analyzes the data using machine learning algorithms and identifies useful technologies. As output, it obtains information about the identified technologies. Specifically, the server executes the command "analyze_data('energy_research_results')".

[1494] Step 7: Providing a User Interface

[1495] The device provides a user interface and visualizes the virtual environment and AI activity in real time. It uses the activity data received from the server as input. It converts this data into a format that can be visualized as data processing. It outputs a dashboard-style interface. Specifically, the device executes the code "dashboard.update('AI Activity', ai_activity_data)".

[1496] Step 8: Receiving and sending feedback

[1497] The device receives feedback from the user and sends it to the server. As input, it receives the user's feedback data. As data processing, it converts this feedback data into an appropriate format. As output, it sends the feedback to the server. Specifically, the device executes the code "user_feedback = get_user_input()" and "send_to_server(user_feedback)".

[1498] Step 9: Emotion recognition and dynamic regulation

[1499] The server uses an emotion engine to recognize the user's emotions in real time. As input, it receives the user's facial expressions, voice, and text data. As data processing, it analyzes this data to identify emotions. As output, it obtains the user's emotion data. Specifically, the server executes the code "emotion = detect_emotion(camera_feed)" and "send_to_server(emotion_data)".

[1500] Step 10: Dynamic adjustment of virtual environment and AI

[1501] The server dynamically adjusts the virtual environment and artificial intelligence settings based on the acquired emotional data. It receives emotional data as input. It processes the data by changing the AI's behavior and virtual environment settings based on this data. It outputs the adjusted virtual environment and AI behavior data. Specifically, the server executes the command "adjust_AI_behavior(emotion_data)".

[1502] (Application example 2)

[1503] 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."

[1504] When autonomous vehicles are operating, various unexpected situations and obstacles can occur. These can increase passenger anxiety and discomfort, resulting in problems such as reduced operational efficiency and safety. Furthermore, it is necessary to properly identify passenger emotions and respond flexibly accordingly, but current systems are inadequate in this regard. Therefore, it is necessary to provide flexible responses to unexpected situations and dynamic measures according to passenger emotions.

[1505] 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.

[1506] In this invention, the server includes means for operating multiple artificial intelligences modeled on the human brain in a virtual environment, means for accelerating time in the virtual environment, means for acquiring inventions and cultures generated in the virtual environment and storing them in a database, means for analyzing the acquired inventions and cultures and identifying useful technologies, means for managing the operation of the autonomous vehicle, recognizing and dynamically responding to user emotions, and means for the autonomous vehicle to search for an alternative route in the event of an obstacle and providing measures to reassure passengers based on their emotions. This enables the autonomous vehicle to respond flexibly to unexpected situations and quickly and appropriately to passenger emotions.

[1507] "Artificial intelligence" is a system that performs intellectual tasks using algorithms and programs that mimic the functions of the human brain.

[1508] A "virtual environment" is a model of the real world reproduced on a computer system, and is a simulated space that includes elements such as terrain, climate, and social systems.

[1509] "Means of accelerating time" is a technology that allows time in a virtual environment to pass faster than actual time, making it possible to simulate a long period of time in a short period of time.

[1510] A "database" is an information system for efficiently storing, searching, and managing large amounts of data, and stores data on the aforementioned inventions and cultures.

[1511] An "autonomous mobile object" is a machine that operates and moves on its own initiative without the need for external control, and specifically refers to self-driving vehicles.

[1512] "Means for recognizing emotions" refers to technology that identifies a user's psychological state by analyzing the user's facial expressions, voice, text data, etc.

[1513] "Dynamic response means" refers to the ability to adjust the system in real time according to the situation and the user's emotions, and to execute the optimal response or action.

[1514] The "means for searching alternative routes" is an algorithm that considers new routes and allows a moving vehicle to adopt the optimal route depending on traffic conditions and obstacles.

[1515] "Reassuring measures" are measures or actions to reduce the user's anxiety or stress, and include, for example, playing music or providing information.

[1516] System Configuration

[1517] The system of the present invention is realized with the following configuration.

[1518] Server processing

[1519] 1. Configure and build the virtual environment:

[1520] The server first sets up a virtual environment, creating a virtual space modeled on the city's topography and climate. It also sets the laws of physics and environmental variables within this virtual environment. It also sets a time acceleration factor, allowing the virtual environment to progress faster than real time.

[1521] 2. Artificial Intelligence Generation:

[1522] The server generates multiple AIs modeled after the human brain, each with its own unique characteristics and skills. For example, models specializing in energy engineering and socioeconomics are included. These AIs operate autonomously within the virtual environment, generating new inventions and cultures.

[1523] 3. Data Collection and Analysis:

[1524] The server collects data on inventions and cultures generated in the virtual environment, stores it in a database, and analyzes the collected data to identify technologies and cultures that are useful in the real world, enabling the generation of patent documents and patent applications.

[1525] Processing by the terminal

[1526] 1. Real-time visualization:

[1527] The device provides an interface that visualizes the status of the virtual environment and the activities of the AI ​​in real time, allowing the user to observe the virtual environment and the activities of the AI ​​in detail.

[1528] 2. Incorporating feedback:

[1529] The device receives feedback from the user and sends it to a server, which dynamically adjusts the settings of the virtual environment and artificial intelligence based on this feedback.

[1530] Incorporating an emotion engine

[1531] 1. Emotion recognition:

[1532] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize the user's emotions in real time. This emotional data is received by the server and used to adjust the behavior of the virtual environment and artificial intelligence.

[1533] 2. Emotion-based responses:

[1534] Based on the user's emotions, the server adjusts the autonomous vehicle's behavior and responses in real time. For example, if the user feels anxious, the server may search for an alternative route.

[1535] Hardware and software used

[1536] Hardware: Autonomous mobile devices (e.g., self-driving cars), high-performance server computers (e.g., NVIDIA Drive)

[1537] Software: Python programming language, machine learning libraries (e.g., TensorFlow), emotion recognition libraries (e.g., OpenCV)

[1538] Specific examples

[1539] For example, consider an application example when traffic congestion occurs.

[1540] 1. The server runs an autonomous vehicle in a virtual environment where random traffic jams may occur.

[1541] 2. At this point, the autonomous vehicle's artificial intelligence will become anxious and search for an alternative route.

[1542] 3. The user can observe this situation through the device and provide feedback as needed, for example, allowing the user to suggest valid alternative routes.

[1543] 4. The emotion engine recognizes the user's anxiety and communicates it to the server, which then adjusts the AI's behavior and takes steps to alleviate the anxiety.

[1544] Prompt Sentence Examples

[1545] A prompt to input to a generative AI model how a self-driving vehicle will behave in a given traffic situation:

[1546] When an autonomous vehicle is traveling according to a city model, it suddenly encounters a traffic jam. Considering that the ongoing load factor is 0.8, what should be the next action? The emotional state of the vehicle is anxious, but please also suggest ways to reassure the passengers.

[1547] In this way, the present invention enables dynamic and adaptive responses according to the user's emotions, thereby enhancing the operation management of autonomous vehicles.

[1548] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1549] Step 1: Configure and build a virtual environment

[1550] The server sets the basic structure of the city, including its topography, climate, and social systems. At the same time, it also sets the laws of physics and environmental variables (temperature, humidity, etc.). Using city model data as input, a virtual environment is constructed as output. Specifically, a 3D model of the city is generated using computer graphics and run on a simulation engine.

[1551] Step 2: Generate artificial intelligence

[1552] The server generates multiple AI models modeled after the human brain. Different characteristics and skills are input to each AI. The input is data defining the characteristics and skills, and the output is the generation of multiple AI instances. Specifically, machine learning algorithms are applied to each AI model, and specific skills are learned using training data.

[1553] Step 3: Set the time acceleration factor

[1554] The server sets a time acceleration factor to accelerate time in the virtual environment. The input is the time acceleration factor, and the output is the speed of virtual time relative to real time. Specifically, the server controls the progression of time in the virtual environment by changing the simulation time step.

[1555] Step 4: Simulating AI activity

[1556] The server simulates the activities of the AI ​​generated within the virtual environment. The virtual environment, AI instances, and environmental variables are used as input, and the AI's activity history data is generated as output. Specifically, each AI acts autonomously within the simulation engine and performs designated tasks.

[1557] Step 5: Collect and store data

[1558] The server collects data on the AI's activities within the virtual environment, as well as the inventions and cultural data it generates, and stores them in a database. Simulation data is used as input, and an organized database is generated as output. Specifically, a data collection agent collects the activity data of each AI and stores it in the database in an appropriate format.

[1559] Step 6: Data analysis and feedback

[1560] The server analyzes the data stored in the database to identify useful technologies and generates patent documents based on the analysis results. The acquired data is used as input, and an analysis report and patent documents are generated as output. Specifically, data analysis algorithms are used to identify interesting patterns and generate technology feasibility reports.

[1561] Step 7: Real-time visualization

[1562] The device displays the status of the virtual environment and the activity of the AI ​​in real time. It uses the virtual environment and AI activity data as input and provides a visualized graphical interface as output. Specifically, it displays real-time data in a dashboard format while updating it.

[1563] Step 8: Incorporating user feedback

[1564] The device receives feedback from the user and sends it to the server. The server dynamically adjusts the virtual environment and AI based on the feedback. The user's feedback data is used as input, and the parameters of the virtual environment and AI are dynamically updated as output. Specifically, after receiving the feedback data, the simulation parameters are recalculated and applied in real time.

[1565] Step 9: Emotion recognition and response adjustment

[1566] The emotion engine analyzes the user's facial expressions, voice, and text data to recognize their emotional state. The server then adjusts the AI's behavior based on this information. The input is the user's emotional data, and the output is an emotion-based response action. Specifically, the emotion recognition software performs real-time analysis and takes reassuring action as needed.

[1567] Step 10: Encountering obstacles and finding alternative routes

[1568] When an autonomous vehicle encounters a fault in the virtual environment or in the real world, the server searches for an alternative route and provides reassurance measures. Using fault information and current traffic information as input, the server generates the optimal alternative route and reassurance measures as output. Specifically, the server analyzes traffic congestion and accident information and presents a safe and fast alternative route.

[1569] 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.

[1570] 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.

[1571] 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.

[1572] 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.

[1573] 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.

[1574] 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.

[1575] 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).

[1576] 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.

[1577] 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."

[1578] 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.

[1579] 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).

[1580] 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.

[1581] 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.

[1582] 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.

[1583] 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.

[1584] 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.

[1585] 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 diff...

Claims

1. A means for operating multiple artificial intelligences that mimic the human brain in a virtual environment; means for accelerating time in a virtual environment in which said artificial intelligence operates; A means for acquiring inventions and cultures generated within the virtual environment and storing them in a database; A means for analyzing the acquired inventions and cultures and identifying useful technologies; A system including:

2. The system of claim 1 further comprising means for providing the artificial intelligence with unique characteristics and skills to facilitate diverse activities within the virtual environment.

3. A means for visualizing the status of the virtual environment and the activity of the artificial intelligence in real time; The system of claim 1 further comprising means for receiving feedback from a user and incorporating it into the virtual environment and artificial intelligence.

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