System

Abstract

An object of a system according to an embodiment is to design an ideal prefecture in a virtual space and construct an administrative system while interacting with residents.SOLUTION: A system includes a design part, an avatar generation part, an administrative system construction part, an interaction part, an event holding part, and an economic activity part. A design part designs an ideal prefecture. The avatar generator generates a resident avatar. The administrative system construction unit constructs a unique administrative system. The interaction unit interacts with residents. The event holding unit holds a plurality of events. The economic activity unit activates economic activity.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 conventional technology, it was difficult to design an ideal prefecture in virtual space and build an administrative system while interacting with residents.

[0005] The system according to the embodiment aims to design an ideal prefecture in a virtual space and build an administrative system while interacting with residents. [Means for solving the problem]

[0006] The system according to the embodiment includes a design unit, an avatar generation unit, an administrative system construction unit, a communication unit, an event hosting unit, and an economic activity unit. The design unit designs an ideal prefecture. The avatar generation unit generates resident avatars. The administrative system construction unit constructs a unique administrative system. The communication unit interacts with residents. The event hosting unit hosts multiple events. The economic activity unit stimulates economic activity. [Effects of the Invention]

[0007] The system according to the embodiment allows users to design their ideal prefecture in a virtual space and build an administrative system while interacting with residents. [Brief explanation of the drawings]

[0008] [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. DETAILED DESCRIPTION OF THE INVENTION

[0009] 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.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] 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.

[0013] 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.

[0014] 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), and Bluetooth (registered trademark).

[0015] 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."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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).

[0019] 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.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. 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 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. 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.

[0022] 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.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The metaverse operating system according to an embodiment of the present invention is a system in which users create and operate their ideal prefectures within the metaverse. This allows users to design their ideal prefectures, generate resident avatars, build their own administrative systems, interact with residents, hold various events, and stimulate economic activity.

[0029] The metaverse operating system according to the embodiment includes a design unit, an avatar generation unit, an administrative system construction unit, an exchange unit, an event hosting unit, and an economic activity unit. The design unit designs an ideal prefecture. For example, a user can freely design the terrain, cities, nature, culture, etc. The design unit can also arrange natural features such as mountains, rivers, and lakes and determine the layout of cities and building designs. The design unit can also incorporate specific traditions and customs. The avatar generation unit generates resident avatars. For example, using a generation AI, the resident avatar's appearance, personality, occupation, etc. can be set. The avatar generation unit can also create residents of various ages and occupations, from young to elderly, to build a vibrant society. The avatar generation unit can also simulate the behavior patterns and social relationships of the resident avatars to build a more realistic virtual society. The administrative system construction unit builds a unique administrative system. For example, using a generation AI, the resident avatar can propose and implement an optimal administrative system. The administrative system construction unit can also implement tax reforms, introduce educational programs, and improve medical services in response to resident needs. Furthermore, the Administrative System Construction Department can analyze resident behavioral data and propose optimal tax and welfare policies. The Communication Department interacts with residents. For example, it can use generative AI to collect resident opinions and requests and then plan and implement policies based on them. The Communication Department can also improve public services and launch new projects based on resident feedback. The Communication Department can also analyze resident emotional states and hold emotion-based policy discussions. The Event Organizing Department organizes various events. For example, it can use generative AI to support event planning and management and promote resident participation. The Event Organizing Department can also organize festivals showcasing local specialties and sports competitions to deepen resident interaction. The Event Organizing Department can monitor resident emotional states in real time and adjust the progress of events. The Economic Activity Department stimulates economic activity. For example, it can use generative AI to optimize economic activity and enrich residents' lives.The economic activity department can also revitalize the economy by conducting transactions using virtual currencies and selling digital art using NFTs. Furthermore, the economic activity department can add economic collaboration functions with other virtual cities and build a system for mutual benefit. This allows the metaverse management system according to the embodiment to enable users to create and manage their ideal prefectures within the metaverse. For example, users can design cities with rich natural environments, build a society where diverse residents coexist, introduce efficient administrative systems, actively interact with residents, and revitalize the region through various events. Furthermore, building an economic system utilizing virtual currencies and NFTs can enrich the lives of residents and achieve sustainable development.

[0030] The design department can use the generation AI to learn the user's past design history and preferences and propose optimal terrain and city layouts. For example, the generation AI analyzes the user's past design history and learns the user's preferences and tendencies. For example, the design department makes optimal proposals based on city layouts and natural terrain arrangements that the user has designed in the past. The design department also uses the generation AI to learn the user's preferences and propose optimal terrain and city layouts. For example, it proposes designs that reflect the user's preferred natural landscapes and urban features. Furthermore, the design department uses the generation AI to propose optimal terrain and city layouts based on the user's past design history. For example, it analyzes data on designs that the user has created in the past and makes optimal proposals. This makes it possible to propose optimal designs based on the user's preferences.

[0031] The design department can incorporate climate change simulations to create designs that take long-term environmental impacts into account. For example, the design department uses climate change simulations to design terrain and cities that take into account the impacts of future climate change. For example, they can design appropriate drainage systems for areas at high risk of flooding. The design department also uses climate change simulations to create designs that take long-term environmental impacts into account. For example, they can propose urban plans to reduce greenhouse gas emissions. Furthermore, the design department can incorporate climate change simulations to create designs that take long-term environmental impacts into account. For example, they can set up nature conservation areas to minimize the impact on the ecosystem. This enables sustainable designs that take long-term environmental impacts into account.

[0032] The avatar generation unit uses generation AI to simulate the behavior patterns and social relationships of resident avatars, thereby building a more realistic virtual society. The avatar generation unit, for example, uses generation AI to simulate the behavior patterns of resident avatars and build a realistic virtual society. For example, it recreates how resident avatars behave in their daily lives. The avatar generation unit also uses generation AI to simulate the social relationships of resident avatars and build a realistic virtual society. For example, it recreates how resident avatars build friendships and workplace relationships. The avatar generation unit also uses generation AI to simulate the behavior patterns and social relationships of resident avatars and build a more realistic virtual society. For example, it recreates how resident avatars play their roles within the community. This makes it possible to build a realistic virtual society.

[0033] The administrative system construction department can use generative AI to analyze resident behavioral data and propose optimal tax systems and welfare policies. For example, the administrative system construction department uses generative AI to analyze resident behavioral data and propose optimal tax systems. For example, it sets optimal tax rates and deduction amounts based on resident income and consumption patterns. The administrative system construction department also uses generative AI to analyze resident behavioral data and propose optimal welfare policies. For example, it provides optimal medical services and welfare programs based on resident health conditions and living environments. Furthermore, the administrative system construction department uses generative AI to analyze resident behavioral data and propose optimal tax systems and welfare policies. For example, it reforms the tax system in accordance with resident needs, introduces educational programs, and improves medical services. This makes it possible to propose optimal tax systems and welfare policies based on resident behavioral data.

[0034] The Communication Department can use generation AI to collect residents' opinions and requests in real time and provide instant feedback. For example, the Communication Department can use generation AI to collect residents' opinions and requests in real time and provide instant feedback. For example, it can respond immediately to opinions submitted by residents. The Communication Department can also use generation AI to collect residents' opinions and requests in real time and provide instant feedback. For example, it can provide instant feedback on event ideas proposed by residents. The Communication Department can also use generation AI to collect residents' opinions and requests in real time and provide instant feedback. For example, it can respond immediately to improvements to public services requested by residents. This makes it possible to respond quickly to residents' opinions and requests.

[0035] The event hosting department can use the generation AI to analyze residents' interests and propose the most suitable event. For example, the event hosting department uses the generation AI to analyze residents' interests and propose the most suitable event. For example, it plans an event based on a theme that residents are interested in. The event hosting department also uses the generation AI to analyze residents' interests and propose the most suitable event. For example, it plans an event based on a social issue that residents are concerned about. The event hosting department also uses the generation AI to analyze residents' interests and propose the most suitable event. For example, it proposes the most suitable event based on data on events that residents have previously participated in. This makes it possible to propose the most suitable event based on residents' interests and propose the most suitable event.

[0036] The economic activity department can use the generation AI to analyze virtual currency transaction data and propose optimal economic policies. The economic activity department, for example, uses the generation AI to analyze virtual currency transaction data and propose optimal economic policies. For example, it sets optimal tax rates based on transaction volume and price fluctuations. The economic activity department also uses the generation AI to analyze virtual currency transaction data and propose optimal economic policies. For example, it proposes optimal monetary policies based on transaction history. Furthermore, the economic activity department uses the generation AI to analyze virtual currency transaction data and propose optimal economic policies. For example, it predicts price fluctuations and proposes optimal transaction timing. This makes it possible to propose optimal economic policies based on virtual currency transaction data.

[0037] The Economic Activities Department can add economic collaboration functions with other virtual cities and build a system for mutual benefit. The Economic Activities Department can, for example, add economic collaboration functions with other virtual cities and build a system for mutual benefit. For example, it can promote the mutual use and trading of virtual currencies. The Economic Activities Department can also add economic collaboration functions with other virtual cities and build a system for mutual benefit. For example, it can launch joint projects and share resources. The Economic Activities Department can also add economic collaboration functions with other virtual cities and build a system for mutual benefit. For example, it can conclude trade agreements and strengthen economic collaboration. This makes it possible to mutually benefit through economic collaboration with other virtual cities.

[0038] The Economic Activity Department can add an AI-based market prediction function to achieve efficient economic management. The Economic Activity Department can add an AI-based market prediction function to achieve efficient economic management. For example, it can predict price fluctuations in virtual currencies and suggest optimal trading timing. The Economic Activity Department can also add an AI-based market prediction function to achieve efficient economic management. For example, it can predict the balance between supply and demand and create optimal production plans. The Economic Activity Department can also add an AI-based market prediction function to achieve efficient economic management. For example, it can predict fluctuations in economic indicators and suggest optimal policies. In this way, the AI-based market prediction function makes efficient economic management possible.

[0039] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0040] The Metaverse Operating System also includes an Education Department, which allows users to design and implement educational programs in the virtual space. For example, users can create virtual classrooms and teach classes to student avatars. The Education Department can also use generative AI to monitor the learning progress of student avatars in real time and propose optimal learning plans. The Education Department also provides interactive learning materials for learning different cultures and languages, allowing users to enjoy a diverse educational experience.

[0041] The metaverse operating system further includes a health management unit. The health management unit allows users to manage their health within the virtual space. For example, a user can set up a virtual fitness center and provide exercise programs for resident avatars. The health management unit can also use generative AI to analyze the health data of resident avatars and propose optimal health management plans. Furthermore, the health management unit can set up virtual medical facilities and provide medical services to resident avatars.

[0042] The metaverse operating system further includes a tourism department. The tourism department allows users to design tourist destinations in the virtual space and attract tourist avatars. For example, users can create virtual landmarks and tourist attractions and provide tours to tourist avatars. The tourism department can also use generation AI to analyze the interests and concerns of tourist avatars and propose optimal sightseeing plans. Furthermore, the tourism department can set up virtual accommodations and restaurants and provide a variety of services to tourist avatars.

[0043] The metaverse operating system further includes a shopping unit that provides a customized shopping experience based on user behavior data without using an emotion estimation function. The shopping unit can analyze the user's past purchase history and interests to suggest optimal products. For example, it can suggest related products based on products the user has previously purchased. The shopping unit can also analyze the user's interests to suggest products that pique the user's interest. Furthermore, the shopping unit can provide sale information at the optimal time based on the user's behavior data.

[0044] The metaverse operating system further includes a travel module that provides customized travel plans based on the user's behavioral data without using an emotion estimation function. The travel module can analyze the user's past travel history and interests to propose optimal travel plans. For example, the travel module can propose related tourist spots based on places the user has visited in the past. The travel module can also analyze the user's interests and propose interesting travel destinations. Furthermore, the travel module can provide travel information at the optimal time based on the user's behavioral data.

[0045] The metaverse operating system further includes a learning unit that provides a customized learning plan based on the user's behavioral data without using an emotion estimation function. The learning unit can analyze the user's past learning history and interests to propose an optimal learning plan. For example, it can propose related learning content based on what the user has learned in the past. The learning unit can also analyze the user's interests and propose learning themes that pique their interest. Furthermore, the learning unit can provide learning information at the optimal time based on the user's behavioral data.

[0046] The processing flow of the first embodiment will be briefly explained below.

[0047] Step 1: The design team designs the ideal prefecture. Users can freely design the terrain, cities, nature, culture, and more. For example, they can place natural features such as mountains, rivers, and lakes, and decide the layout of cities and the design of buildings. They can also incorporate specific traditions and customs. Step 2: The avatar generation unit generates resident avatars. Using the generation AI, it is possible to set the appearance, personality, occupation, etc. of the resident avatars. This allows for the creation of residents of various age groups and occupations, from young people to the elderly, to build a vibrant society. Furthermore, it is possible to simulate the behavior patterns and social relationships of the resident avatars and create a more realistic virtual society. Step 3: The Administrative System Construction Department will build a unique administrative system. Using generative AI, it will be able to propose and implement the optimal administrative system. This will enable tax reforms tailored to the needs of residents, the introduction of educational programs, and the improvement of medical services. Furthermore, it will be able to analyze resident behavior data and propose optimal tax systems and welfare policies. Step 4: The Communication Department interacts with residents. Using generative AI, it can collect residents' opinions and requests and formulate and implement policies based on them. Based on feedback from residents, it can improve public services and launch new projects. Furthermore, it can analyze residents' emotional state and hold emotion-based policy discussions. Step 5: The Event Organizer organizes various events. Generative AI can be used to support the planning and management of events and encourage resident participation. Events can be held to promote local specialties or sports competitions, deepening interactions among residents. Furthermore, the emotional state of residents can be monitored in real time and the progress of events can be adjusted accordingly. Step 6: The Economic Activity Department stimulates economic activity. Generative AI can be used to optimize economic activity and enrich the lives of residents. The economy can be stimulated through cryptocurrency transactions and the sale of digital art using NFTs. Furthermore, economic collaboration with other virtual cities can be added, creating a system for mutual benefit.

[0048] (Example 2) The metaverse operating system according to an embodiment of the present invention is a system in which users create and operate their ideal prefectures within the metaverse. This allows users to design their ideal prefectures, generate resident avatars, build their own administrative systems, interact with residents, hold various events, and stimulate economic activity.

[0049] The metaverse operating system according to the embodiment includes a design unit, an avatar generation unit, an administrative system construction unit, an exchange unit, an event hosting unit, and an economic activity unit. The design unit designs an ideal prefecture. For example, a user can freely design the terrain, cities, nature, culture, etc. The design unit can also arrange natural features such as mountains, rivers, and lakes and determine the layout of cities and building designs. The design unit can also incorporate specific traditions and customs. The avatar generation unit generates resident avatars. For example, using a generation AI, the resident avatar's appearance, personality, occupation, etc. can be set. The avatar generation unit can also create residents of various ages and occupations, from young to elderly, to build a vibrant society. The avatar generation unit can also simulate the behavior patterns and social relationships of the resident avatars to build a more realistic virtual society. The administrative system construction unit builds a unique administrative system. For example, using a generation AI, the resident avatar can propose and implement an optimal administrative system. The administrative system construction unit can also implement tax reforms, introduce educational programs, and improve medical services in response to resident needs. Furthermore, the Administrative System Construction Department can analyze resident behavioral data and propose optimal tax and welfare policies. The Communication Department interacts with residents. For example, it can use generative AI to collect resident opinions and requests and then plan and implement policies based on them. The Communication Department can also improve public services and launch new projects based on resident feedback. The Communication Department can also analyze resident emotional states and hold emotion-based policy discussions. The Event Organizing Department organizes various events. For example, it can use generative AI to support event planning and management and promote resident participation. The Event Organizing Department can also organize festivals showcasing local specialties and sports competitions to deepen resident interaction. The Event Organizing Department can monitor resident emotional states in real time and adjust the progress of events. The Economic Activity Department stimulates economic activity. For example, it can use generative AI to optimize economic activity and enrich residents' lives.The economic activity department can also revitalize the economy by conducting transactions using virtual currencies and selling digital art using NFTs. Furthermore, the economic activity department can add economic collaboration functions with other virtual cities and build a system for mutual benefit. This allows the metaverse management system according to the embodiment to enable users to create and manage their ideal prefectures within the metaverse. For example, users can design cities with rich natural environments, build a society where diverse residents coexist, introduce efficient administrative systems, actively interact with residents, and revitalize the region through various events. Furthermore, building an economic system utilizing virtual currencies and NFTs can enrich the lives of residents and achieve sustainable development.

[0050] The design department can use the generation AI to learn the user's past design history and preferences and propose optimal terrain and city layouts. For example, the generation AI analyzes the user's past design history and learns the user's preferences and tendencies. For example, the design department makes optimal proposals based on city layouts and natural terrain arrangements that the user has designed in the past. The design department also uses the generation AI to learn the user's preferences and propose optimal terrain and city layouts. For example, it proposes designs that reflect the user's preferred natural landscapes and urban features. Furthermore, the design department uses the generation AI to propose optimal terrain and city layouts based on the user's past design history. For example, it analyzes data on designs that the user has created in the past and makes optimal proposals. This makes it possible to propose optimal designs based on the user's preferences.

[0051] The design department can incorporate climate change simulations to create designs that take long-term environmental impacts into account. For example, the design department uses climate change simulations to design terrain and cities that take into account the impacts of future climate change. For example, they can design appropriate drainage systems for areas at high risk of flooding. The design department also uses climate change simulations to create designs that take long-term environmental impacts into account. For example, they can propose urban plans to reduce greenhouse gas emissions. Furthermore, the design department can incorporate climate change simulations to create designs that take long-term environmental impacts into account. For example, they can set up nature conservation areas to minimize the impact on the ecosystem. This enables sustainable designs that take long-term environmental impacts into account.

[0052] The design department can use the emotion estimation function to analyze the emotions felt by the user while designing in real time and make design suggestions that elicit positive emotions. For example, the design department can use the emotion estimation function to monitor the emotions felt by the user while designing in real time and make design suggestions that elicit positive emotions. For example, new design ideas can be presented when the user is enjoying themselves. The design department can also use the emotion estimation function to analyze the emotions felt by the user in real time and make design suggestions that elicit positive emotions. For example, a design that has a relaxing effect can be proposed when the user is relaxed. The design department can also use the emotion estimation function to analyze the emotions felt by the user while designing in real time and make design suggestions that elicit positive emotions. For example, a design that increases concentration can be proposed when the user is concentrating. This makes it possible to make design suggestions based on the user's emotions.

[0053] The avatar generation unit uses generation AI to simulate the behavior patterns and social relationships of resident avatars, thereby building a more realistic virtual society. The avatar generation unit, for example, uses generation AI to simulate the behavior patterns of resident avatars and build a realistic virtual society. For example, it recreates how resident avatars behave in their daily lives. The avatar generation unit also uses generation AI to simulate the social relationships of resident avatars and build a realistic virtual society. For example, it recreates how resident avatars build friendships and workplace relationships. The avatar generation unit also uses generation AI to simulate the behavior patterns and social relationships of resident avatars and build a more realistic virtual society. For example, it recreates how resident avatars play their roles within the community. This makes it possible to build a realistic virtual society.

[0054] The avatar generation unit can use the emotion estimation function to monitor the emotional state of the resident avatar in real time and make adjustments to maintain social harmony. The avatar generation unit, for example, uses the emotion estimation function to monitor the emotional state of the resident avatar in real time. For example, if the resident avatar is feeling stressed, the cause is identified. The avatar generation unit also uses the emotion estimation function to monitor the emotional state of the resident avatar in real time and make adjustments to maintain social harmony. For example, if the resident avatar is feeling anxious, a relaxation program is provided. The avatar generation unit also uses the emotion estimation function to monitor the emotional state of the resident avatar in real time and make adjustments to maintain social harmony. For example, if the resident avatar is feeling angry, counseling is provided. This makes it possible to make adjustments based on the emotional state of the resident avatar.

[0055] The administrative system construction department can use generative AI to analyze resident behavioral data and propose optimal tax systems and welfare policies. For example, the administrative system construction department uses generative AI to analyze resident behavioral data and propose optimal tax systems. For example, it sets optimal tax rates and deduction amounts based on resident income and consumption patterns. The administrative system construction department also uses generative AI to analyze resident behavioral data and propose optimal welfare policies. For example, it provides optimal medical services and welfare programs based on resident health conditions and living environments. Furthermore, the administrative system construction department uses generative AI to analyze resident behavioral data and propose optimal tax systems and welfare policies. For example, it reforms the tax system in accordance with resident needs, introduces educational programs, and improves medical services. This makes it possible to propose optimal tax systems and welfare policies based on resident behavioral data.

[0056] The Communication Department can use generation AI to collect residents' opinions and requests in real time and provide instant feedback. For example, the Communication Department can use generation AI to collect residents' opinions and requests in real time and provide instant feedback. For example, it can respond immediately to opinions submitted by residents. The Communication Department can also use generation AI to collect residents' opinions and requests in real time and provide instant feedback. For example, it can provide instant feedback on event ideas proposed by residents. The Communication Department can also use generation AI to collect residents' opinions and requests in real time and provide instant feedback. For example, it can respond immediately to improvements to public services requested by residents. This makes it possible to respond quickly to residents' opinions and requests.

[0057] The communication department can use the emotion estimation function to analyze the emotional state of residents and hold policy discussions based on their emotions. The communication department, for example, uses the emotion estimation function to analyze the emotional state of residents and hold policy discussions based on their emotions. For example, it discusses issues that residents are worried about. The communication department also uses the emotion estimation function to analyze the emotional state of residents and hold policy discussions based on their emotions. For example, it discusses projects that residents are happy about. The communication department also uses the emotion estimation function to analyze the emotional state of residents and hold policy discussions based on their emotions. For example, it discusses issues that residents are angry about. This makes it possible to hold policy discussions based on the emotional state of residents.

[0058] The event hosting department can use the generation AI to analyze residents' interests and propose the most suitable event. For example, the event hosting department uses the generation AI to analyze residents' interests and propose the most suitable event. For example, it plans an event based on a theme that residents are interested in. The event hosting department also uses the generation AI to analyze residents' interests and propose the most suitable event. For example, it plans an event based on a social issue that residents are concerned about. The event hosting department also uses the generation AI to analyze residents' interests and propose the most suitable event. For example, it proposes the most suitable event based on data on events that residents have previously participated in. This makes it possible to propose the most suitable event based on residents' interests and propose the most suitable event.

[0059] The event hosting unit can use the emotion estimation function to monitor the emotional states of residents in real time and adjust the progress of the event. The event hosting unit, for example, uses the emotion estimation function to monitor the emotional states of residents in real time and adjust the progress of the event. For example, if the residents are enjoying themselves, the event is extended. The event hosting unit also uses the emotion estimation function to monitor the emotional states of residents in real time and adjust the progress of the event. For example, if the residents are bored, the program is changed. The event hosting unit also uses the emotion estimation function to monitor the emotional states of residents in real time and adjust the progress of the event. For example, if the residents are tired, a break is provided. This makes it possible to adjust the progress of the event based on the emotional states of the residents.

[0060] The economic activity department can use the generation AI to analyze virtual currency transaction data and propose optimal economic policies. The economic activity department, for example, uses the generation AI to analyze virtual currency transaction data and propose optimal economic policies. For example, it sets optimal tax rates based on transaction volume and price fluctuations. The economic activity department also uses the generation AI to analyze virtual currency transaction data and propose optimal economic policies. For example, it proposes optimal monetary policies based on transaction history. Furthermore, the economic activity department uses the generation AI to analyze virtual currency transaction data and propose optimal economic policies. For example, it predicts price fluctuations and proposes optimal transaction timing. This makes it possible to propose optimal economic policies based on virtual currency transaction data.

[0061] The economic activity department can use the emotion estimation function to analyze residents' emotional reactions to economic activities and formulate economic policies based on their emotions. The economic activity department, for example, uses the emotion estimation function to analyze residents' emotional reactions to economic activities and formulate economic policies based on their emotions. For example, if residents are feeling anxious, economic support measures are proposed. The economic activity department also uses the emotion estimation function to analyze residents' emotional reactions to economic activities and formulate economic policies based on their emotions. For example, if residents are satisfied, policies are proposed to maintain that satisfaction. The economic activity department also uses the emotion estimation function to analyze residents' emotional reactions to economic activities and formulate economic policies based on their emotions. For example, if residents have expectations, policies are proposed to meet those expectations. This makes it possible to formulate economic policies based on residents' emotional reactions.

[0062] The Economic Activities Department can add economic collaboration functions with other virtual cities and build a system for mutual benefit. The Economic Activities Department can, for example, add economic collaboration functions with other virtual cities and build a system for mutual benefit. For example, it can promote the mutual use and trading of virtual currencies. The Economic Activities Department can also add economic collaboration functions with other virtual cities and build a system for mutual benefit. For example, it can launch joint projects and share resources. The Economic Activities Department can also add economic collaboration functions with other virtual cities and build a system for mutual benefit. For example, it can conclude trade agreements and strengthen economic collaboration. This makes it possible to mutually benefit through economic collaboration with other virtual cities.

[0063] The Economic Activity Department can add an AI-based market prediction function to achieve efficient economic management. The Economic Activity Department can add an AI-based market prediction function to achieve efficient economic management. For example, it can predict price fluctuations in virtual currencies and suggest optimal trading timing. The Economic Activity Department can also add an AI-based market prediction function to achieve efficient economic management. For example, it can predict the balance between supply and demand and create optimal production plans. The Economic Activity Department can also add an AI-based market prediction function to achieve efficient economic management. For example, it can predict fluctuations in economic indicators and suggest optimal policies. In this way, the AI-based market prediction function makes efficient economic management possible.

[0064] The economic activity department can use the emotion estimation function to identify areas for improvement in economic activities based on residents' emotional responses and improve resident satisfaction. The economic activity department, for example, uses the emotion estimation function to identify areas for improvement in economic activities based on residents' emotional responses. For example, improving economic policies that residents are dissatisfied with. The economic activity department also uses the emotion estimation function to identify areas for improvement in economic activities based on residents' emotional responses. For example, further strengthening economic activities that residents are satisfied with. The economic activity department also uses the emotion estimation function to identify areas for improvement in economic activities based on residents' emotional responses. For example, proposing improvement measures to realize economic activities that residents expect. This makes it possible to improve economic activities based on residents' emotional responses.

[0065] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0066] The Metaverse Operating System also includes an Education Department, which allows users to design and implement educational programs in the virtual space. For example, users can create virtual classrooms and teach classes to student avatars. The Education Department can also use generative AI to monitor the learning progress of student avatars in real time and propose optimal learning plans. The Education Department also provides interactive learning materials for learning different cultures and languages, allowing users to enjoy a diverse educational experience.

[0067] The metaverse operating system further includes a health management unit. The health management unit allows users to manage their health within the virtual space. For example, a user can set up a virtual fitness center and provide exercise programs for resident avatars. The health management unit can also use generative AI to analyze the health data of resident avatars and propose optimal health management plans. Furthermore, the health management unit can set up virtual medical facilities and provide medical services to resident avatars.

[0068] The metaverse operating system further includes a tourism department. The tourism department allows users to design tourist destinations in the virtual space and attract tourist avatars. For example, users can create virtual landmarks and tourist attractions and provide tours to tourist avatars. The tourism department can also use generation AI to analyze the interests and concerns of tourist avatars and propose optimal sightseeing plans. Furthermore, the tourism department can set up virtual accommodations and restaurants and provide a variety of services to tourist avatars.

[0069] The metaverse operating system further includes an advertising unit that uses an emotion estimation function to deliver advertisements based on the user's emotions. The advertising unit can analyze the user's emotional state in real time and deliver advertisements at optimal timing. For example, when the user is relaxed, the advertising unit can deliver advertisements introducing relaxation products. Furthermore, when the user is excited, the advertising unit can deliver advertisements related to entertainment. Furthermore, when the user is stressed, the advertising unit can deliver advertisements introducing stress relief products.

[0070] The metaverse operating system further includes a music unit that uses an emotion estimation function to provide a customized music playlist based on the user's emotions. The music unit can analyze the user's emotional state in real time and suggest optimal music. For example, when the user is relaxing, the music unit can suggest music with a relaxing effect. When the user is concentrating, the music unit can suggest music that improves concentration. When the user is having fun, the music unit can suggest energetic music.

[0071] The metaverse operating system further includes a feedback unit that uses the emotion estimation function to provide feedback based on the user's emotions. The feedback unit can analyze the user's emotional state in real time and provide optimal feedback. For example, the feedback unit can provide an encouraging message when the user is feeling anxious. The feedback unit can also provide a message of praise when the user is happy. The feedback unit can also provide advice to stay calm when the user is feeling angry.

[0072] The metaverse operating system further includes a fitness module that uses an emotion estimation function to provide a customized exercise program based on the user's emotions. The fitness module can analyze the user's emotional state in real time and suggest an optimal exercise program. For example, the fitness module can suggest a yoga or stretching program when the user is relaxed. The fitness module can also suggest a high-intensity exercise program when the user is energetic. The fitness module can also suggest a relaxation exercise program when the user is feeling stressed.

[0073] The metaverse operating system further includes a shopping unit that provides a customized shopping experience based on user behavior data without using an emotion estimation function. The shopping unit can analyze the user's past purchase history and interests to suggest optimal products. For example, it can suggest related products based on products the user has previously purchased. The shopping unit can also analyze the user's interests to suggest products that pique the user's interest. Furthermore, the shopping unit can provide sale information at the optimal time based on the user's behavior data.

[0074] The metaverse operating system further includes a travel module that provides customized travel plans based on the user's behavioral data without using an emotion estimation function. The travel module can analyze the user's past travel history and interests to propose optimal travel plans. For example, the travel module can propose related tourist spots based on places the user has visited in the past. The travel module can also analyze the user's interests and propose interesting travel destinations. Furthermore, the travel module can provide travel information at the optimal time based on the user's behavioral data.

[0075] The metaverse operating system further includes a learning unit that provides a customized learning plan based on the user's behavioral data without using an emotion estimation function. The learning unit can analyze the user's past learning history and interests to propose an optimal learning plan. For example, it can propose related learning content based on what the user has learned in the past. The learning unit can also analyze the user's interests and propose learning themes that pique their interest. Furthermore, the learning unit can provide learning information at the optimal time based on the user's behavioral data.

[0076] The processing flow of the second embodiment will be briefly explained below.

[0077] Step 1: The design team designs the ideal prefecture. Users can freely design the terrain, cities, nature, culture, and more. For example, they can place natural features such as mountains, rivers, and lakes, and decide the layout of cities and the design of buildings. They can also incorporate specific traditions and customs. Step 2: The avatar generation unit generates resident avatars. Using the generation AI, it is possible to set the appearance, personality, occupation, etc. of the resident avatars. This allows for the creation of residents of various age groups and occupations, from young people to the elderly, to build a vibrant society. Furthermore, it is possible to simulate the behavior patterns and social relationships of the resident avatars and create a more realistic virtual society. Step 3: The Administrative System Construction Department will build a unique administrative system. Using generative AI, it will be able to propose and implement the optimal administrative system. This will enable tax reforms tailored to the needs of residents, the introduction of educational programs, and the improvement of medical services. Furthermore, it will be able to analyze resident behavior data and propose optimal tax systems and welfare policies. Step 4: The Communication Department interacts with residents. Using generative AI, it can collect residents' opinions and requests and formulate and implement policies based on them. Based on feedback from residents, it can improve public services and launch new projects. Furthermore, it can analyze residents' emotional state and hold emotion-based policy discussions. Step 5: The Event Organizer organizes various events. Generative AI can be used to support the planning and management of events and encourage resident participation. Events can be held to promote local specialties or sports competitions, deepening interactions among residents. Furthermore, the emotional state of residents can be monitored in real time and the progress of events can be adjusted accordingly. Step 6: The Economic Activity Department stimulates economic activity. Generative AI can be used to optimize economic activity and enrich the lives of residents. The economy can be stimulated through cryptocurrency transactions and the sale of digital art using NFTs. Furthermore, economic collaboration with other virtual cities can be added, creating a system for mutual benefit.

[0078] 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.

[0079] 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> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). 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 speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. 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. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0080] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0081] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0082] 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.

[0083] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0084] 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.

[0085] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0086] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0091] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0092] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0093] 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.

[0094] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0095] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0096] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0097] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0098] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0099] 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.

[0100] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0101] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0106] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0107] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0108] 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.

[0109] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0110] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0111] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0112] 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.

[0113] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0114] 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.

[0115] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0116] 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 image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0117] 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.

[0118] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the 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.

[0119] 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.

[0120] 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.

[0121] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0122] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0123] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0124] 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.

[0125] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0126] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0127] 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.

[0128] FIG. 9 illustrates 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 behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions 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.

[0129] 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.

[0130] 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).

[0131] 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 expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, 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 expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0132] 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."

[0133] 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.

[0134] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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. A processor also includes 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.

[0139] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0140] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0141] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0142] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0143] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0144] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0145] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. The design department designs the ideal prefecture, an avatar generation unit that generates resident avatars; The Administrative System Construction Department, which builds its own administrative system, The Exchange Department, which interacts with residents, An event organization that holds multiple events, An economic activity department that stimulates economic activity. A system characterized by:

2. The design department The generative AI learns the user's past design history and preferences and proposes optimal terrain and urban layouts.

2. The system of claim 1.

3. The avatar generation unit Using the generation AI, the behavioral patterns and social relationships of the resident avatars are simulated to create a more realistic virtual society.

2. The system of claim 1.

4. The administrative system construction department Using the generative AI, the behavioral data of the residents is analyzed and optimal tax and welfare policies are proposed.

2. The system of claim 1.

5. The AC section is Using the generation AI, the opinions and requests of the residents are collected in real time and feedback is provided immediately.

2. The system of claim 1.

6. The event organizing department Monitor the emotional state of the residents in real time and adjust the progress of the event.

2. The system of claim 1.

7. The Economic Activities Department Analyzing the residents' emotional reactions to the economic activities and formulating an economic policy based on their emotions 2. The system of claim 1.

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