system

Abstract

We provide the system. [Solution] A means of training computer models using individual skills and knowledge, and sharing those computer models with others in a virtual space, A means of selecting a computer model published in a virtual space, importing it into the user's terminal, and using it to support business operations. A means of automating and streamlining business processes by utilizing computer models from others, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a problem that specific skills and knowledge possessed by individual human resources within an organization cannot be fully utilized and the information cannot be effectively shared. Also, in order to improve business efficiency, an environment that can quickly incorporate various knowledge as needed is required. Conventional systems often rely on specialized personnel to achieve these purposes and have limitations in business automation. Against this background, there is a demand for improving the efficiency of the entire organization through effective knowledge sharing and business automation.

Means for Solving the Problems

[0005] This invention provides a system that allows others to easily use computer models trained based on an individual's skills and knowledge by making them publicly available in a virtual space. Specifically, it includes means for individual users to generate computer models that reflect their own skills and knowledge, and to register and share them in a virtual space. Furthermore, it provides means for others to automate and streamline business processes by utilizing the publicly available computer models. In addition, this system achieves knowledge utilization and operational efficiency within organizations by managing user access and using a model selection algorithm that suits specific business needs.

[0006] "Individual skills" refer to the specialized abilities and knowledge possessed by a particular individual, and the skill set necessary to perform tasks and duties.

[0007] "Knowledge" refers to information and understanding gained through experience and learning, and includes matters based on theories and practices in a particular field.

[0008] A "computer model" is software that executes algorithms and data structures designed for a specific purpose, and includes AI trained to efficiently perform specific tasks.

[0009] A "virtual space" refers to an online shared space built using digital technology, where users can mutually utilize information and resources.

[0010] "Public" refers to the act of making specific information or resources accessible to others, and in this context, it means making a computer model available for use in a virtual space.

[0011] "Business process automation" refers to the automatic execution of a series of procedures in daily operations by a computer system, with the aim of improving efficiency by minimizing human intervention.

[0012] "Efficiency" refers to increasing the speed and accuracy of achieving objectives while minimizing the resources and time required, and in particular, it means improving productivity in business operations.

[0013] "User access management" refers to the process of appropriately setting and controlling users' rights to use specific information and resources, and includes the protection of security and privacy.

[0014] An "algorithm" refers to a series of calculations or processing steps that are executed in a specific order to solve a particular task or problem. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

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

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] The system according to the present invention generates a virtual computer model (hereinafter referred to as an AI agent) based on an individual's skills and knowledge, and makes it available in a virtual space, thereby providing an environment that can be used by others. This embodiment includes the processes of training, sharing, and using the AI ​​agent.

[0037] Server operation

[0038] The server registers user-generated AI agents within the virtual space. Here, the server receives the AI ​​agent's code and associated metadata (e.g., the agent's area of ​​expertise and intended use) and stores it in a database. After publication, the server manages the listing display to make it easier for other users to access those agents using the search function within the virtual space.

[0039] Terminal operation

[0040] The terminal provides the ability to search for and select AI agents through a user interface. Users retrieve AI agents from the server that meet their business needs and import them into the terminal. The terminal then uses these agents to automate specific business tasks. For example, to assist in creating marketing strategies, the terminal can deploy AI agents with appropriate marketing skills to help generate proposal materials.

[0041] User actions

[0042] Users prepare training data to model their expertise and use that data to customize an AI agent. The trained AI agent has the functionality to support specific business processes and tasks. Users publish the completed agent in a virtual space, making it available for use by other employees within the company. Furthermore, users can select AI agents created by other employees and use them to improve work efficiency and optimize processes.

[0043] Thus, the present invention provides a system and its embodiments for streamlining business processes while effectively utilizing individual knowledge and skills. Through mutual cooperation between servers, terminals, and users, knowledge sharing and business support are facilitated.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] Users collect their own expertise and skills as training data. This data is prepared for input into AI tools, and the necessary information is organized according to the nature of the work.

[0047] Step 2:

[0048] The user trains an AI agent based on training data to generate a model that aligns with their objectives. Here, the machine learning environment on the AI ​​system is used to fine-tune the algorithm, giving the agent the ability to perform specific tasks.

[0049] Step 3:

[0050] The user submits a registration request to the server for the completed AI agent. Based on the received data, the server saves the agent's metadata and code to a database and configures its public access settings within the virtual space.

[0051] Step 4:

[0052] The server displays and manages a list of publicly available AI agent information within the virtual space. This allows other users to easily search for and access available agents.

[0053] Step 5:

[0054] The terminal provides an AI agent search function via a user interface. Users select an AI agent based on their specific skills and objectives. Based on the selection, the terminal imports the appropriate agent from the server.

[0055] Step 6:

[0056] The device uses imported AI agents to perform and automate user-specified business processes. Examples include tasks such as data analysis, report generation, and schedule management.

[0057] Step 7:

[0058] Users evaluate the results of tasks performed by the AI ​​agent and provide feedback as needed to improve performance. This feedback may be used for subsequent training.

[0059] Through the steps described above, the system of the present invention enables the effective utilization of individual skills and knowledge and improves the efficiency of work.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] To facilitate information sharing and improve operational efficiency, there is a need for technology that provides an environment where individual expertise can be easily modeled and effectively shared with others.

[0063] In particular, there is a need for systems that enable the automation and optimization of business processes. In addition, there is a need for methods that allow users to select the most suitable computer model according to their individual needs and work content, and to maximize its utilization.

[0064] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0065] This invention includes a server that provides means for training a computer model based on an individual's expertise and sharing that model with others in an information space; means for selecting a computer model published in the information space and importing it into an information processing terminal to provide business support; means for utilizing the computer models of others to automate and optimize business procedures; means for creating prompt statements using a generated AI model and training an agent; and means for publishing the trained agent in a virtual space and managing an information list to make it easily accessible to others. This enables users to efficiently utilize their expertise and simultaneously achieve business process efficiency and knowledge sharing.

[0066] "Individual expertise" refers to a deep understanding and skills based on an individual's technical abilities and experience in a specific field.

[0067] A "computer model" is a computer program or algorithm built to perform a specific task based on data.

[0068] "Information space" refers to a virtual area where information is stored in digital format and can be accessed and manipulated by users.

[0069] An "information processing terminal" is a computing device used for inputting, processing, and outputting data, and includes personal computers and smartphones.

[0070] "Business support" refers to auxiliary functions and services provided to efficiently carry out specific tasks.

[0071] "Automating business procedures" means mechanizing processes to reduce manual operations by humans, thereby improving efficiency and accuracy.

[0072] "Optimization" is the process of adjusting a system or process to achieve the greatest effect under given conditions.

[0073] A "generative AI model" is an artificial intelligence system that learns patterns based on large amounts of data and generates output for new data.

[0074] A "prompt" is a form of instruction or question given to a generative AI model to elicit a specific output.

[0075] An "agent" is a software program designed to perform a specific task independently.

[0076] The system of this invention aims to generate AI agents, which are computer models based on an individual's expertise, and share them within a virtual space. This system functions with three main components: a server, a terminal, and a user.

[0077] First, the user digitizes their expertise and uses that data to train an AI agent using a generative AI model. The user creates a prompt sentence suitable for a specific purpose and inputs this prompt sentence into the generative AI model to generate an AI agent. As a concrete example, the user might create a prompt sentence such as, "Create an AI agent based on voice data to improve the sales process."

[0078] Next, the server receives the AI ​​agent code and associated metadata sent by the user. This metadata includes the agent's area of ​​expertise and intended use. The server stores this information in a database and then publishes the AI ​​agent in the virtual space. The published agents are managed by the server in an information list format, and care is taken to ensure that other users can easily access them.

[0079] The terminal navigates a virtual space through a user interface and provides functions for users to search for and select the necessary AI agents. The terminal has the ability to import selected agents from the server and utilize them for various business support purposes. For example, the terminal can use a marketing-adapted AI agent to assist in the automatic generation of materials proposing marketing strategies.

[0080] Through the above process, the system effectively models user expertise and provides an environment for automating and optimizing business processes. Furthermore, by utilizing the most suitable AI agent according to individual business needs within this environment, it is possible to promote the streamlining of business processes and the sharing of knowledge.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user prepares their expertise as training data. Here, the user collects data related to specific tasks and organizes it in text, audio, or image format. The input includes existing business data and experience-based knowledge. This is then formatted into the form necessary for input into the generating AI model, resulting in a dataset that serves as the foundation for building the AI ​​agent.

[0084] Step 2:

[0085] The user creates a prompt and inputs it into a generative AI model to generate an AI agent. The input consists of the created prompt (e.g., "Create an AI agent based on voice data to improve the sales process.") and training data. The generative AI model trains the AI ​​agent based on this input and generates an AI agent that reflects expertise as output.

[0086] Step 3:

[0087] The server stores AI agents and their associated metadata received from users in a database. Input includes the AI ​​agent's code and metadata indicating its area of ​​expertise and intended use. The server combines and manages this information, then converts it into an output format that can be publicly shared in the virtual space.

[0088] Step 4:

[0089] The server exposes trained AI agents within a virtual space and manages a list of information accessible to other users. The input is the AI ​​agent data saved in the previous step. The server uses this data to configure access permissions and list displays, providing an environment where users can easily search for agents.

[0090] Step 5:

[0091] The terminal imports an AI agent selected from a virtual space via a user interface and uses it to support business operations. The input is information about the AI ​​agent chosen by the user. Based on this data, the terminal runs the agent in the execution environment and provides the user with functions that help improve work efficiency. Specifically, the agent automatically generates marketing strategy proposal materials, reducing work time.

[0092] (Application Example 1)

[0093] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0094] In modern cities, there is a need to efficiently solve various local problems while utilizing the individual expertise of residents. However, traditional methods lack sufficient mechanisms for effectively sharing individual knowledge and skills and putting them to practical use in problem-solving, thus necessitating more efficient and effective solutions.

[0095] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0096] This invention includes a server that provides means for training information processing models using individual skills and knowledge and sharing those information processing models with others in a virtual space; means for selecting publicly available information processing models in the virtual space, importing them into an information terminal, and providing business support; means for utilizing information processing models of others to automate and streamline business processes; and means for sharing information processing models within a community and using them to solve urban problems. This enables the efficient resolution of urban problems.

[0097] "Individual skills and knowledge" refers to the collection of specialized abilities and knowledge possessed by a particular person.

[0098] An "information processing model" is an artificial intelligence model built on an individual's skills and knowledge to analyze data and make decisions.

[0099] A "virtual space" is a simulation or virtual space on the internet that is generated using digital technology.

[0100] "Means of sharing with others" refers to methods for making certain information or technology accessible and usable by other users.

[0101] An "information terminal" refers to a device capable of processing and displaying digital information, specifically a smartphone or computer.

[0102] "Business support" refers to technical or knowledge-based assistance provided to efficiently carry out specific business activities.

[0103] "Automation" refers to the process of having machines or software perform tasks or processes that were previously done by humans.

[0104] "Efficiency improvement" means optimizing processes and methods to obtain the greatest possible results with limited resources.

[0105] A "community" is a group of people who share common interests or goals, and is a group associated with a particular region or field.

[0106] "Urban problem solving" refers to methods and means for resolving various social, environmental, and economic challenges that arise in cities.

[0107] The system for implementing this invention enables the generation and use of information processing models based on individual knowledge. Servers, terminals, and users each play their respective roles and work in coordination.

[0108] First, the server registers information processing models generated using an individual's skills and knowledge within a virtual space, making them accessible to others. To this end, the server uses a database such as Firebase Firestore to manage the model's code and metadata, displaying them as a searchable list. The server also controls user access and distributes the appropriate model to information terminals.

[0109] Next, users can access a virtual space using an information terminal equipped with a dedicated application, search for and select an information processing model that meets their needs. The selected model is downloaded to the information terminal and used to support business operations and solve urban problems. A concrete example would be an AI agent that assists in designing ecologically friendly transportation systems.

[0110] This application utilizes development environments such as ANDROID® Studio and Xcode, and runs on information devices including smartphones and tablets. The information processing model is trained based on expertise provided by residents and is exposed to the virtual space via Firebase.

[0111] Furthermore, an example of a specific prompt that a user might use is, "Based on the following dataset, build an AI agent specializing in designing ecologically friendly transportation systems in urban areas." This prompt helps the information processing model provide the insights necessary to solve urban problems.

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] The server receives training data provided by the user and generates an information processing model. It receives training data and user skill information as input and constructs the information processing model using machine learning algorithms. The output is the information processing model registered in the virtual space.

[0115] Step 2:

[0116] The user accesses the virtual space using a dedicated application and searches for a list of publicly available information processing models. The user specifies search criteria (e.g., ecologically friendly) as input and retrieves the corresponding information processing models from the server. The output is a list of models displayed on the user's information terminal.

[0117] Step 3:

[0118] The user selects an appropriate information processing model and downloads it to their information terminal. The server encrypts and transmits the selected model, which is then decoded on the user's terminal and integrated into a business support application. The output is the integrated information processing model, ready for use in solving urban problems.

[0119] Step 4:

[0120] The information processing model executed on the terminal performs data calculations based on user prompts. It receives prompts as input and utilizes its internal knowledge to generate a predetermined analysis or proposal. The output might be, for example, a proposal for an optimal urban transportation plan.

[0121] Step 5:

[0122] The server collects user feedback and new data, and incorporates this information to improve the accuracy of the information processing model. It receives user feedback as input and retrains the model. The output is the improved new information processing model.

[0123] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0124] This invention combines a system that shares computer models (AI agents) based on individual skills and knowledge within a virtual space to enable business support and automation with an emotion engine that recognizes user emotions. In this configuration, the user's emotional state is analyzed in real time, enabling the adaptation and optimization of business processes based on that information.

[0125] Server operation

[0126] The server registers user-generated AI agents and emotion engines within the virtual space and manages the usage status of each agent. The server maintains a database for selecting agents and adjusting business processes based on user emotion data. It also utilizes the emotion analysis results obtained by the emotion engine as training data for AI agents, supporting the continuous optimization of the model.

[0127] Terminal operation

[0128] The terminal enhances user support through the collaboration of agents and an emotion engine. The terminal displays emotional data acquired from the emotion engine via the user interface and adjusts agent performance based on this information. It also provides a function to automatically select and import the appropriate AI agent according to the user's current emotional state. For example, if the user is experiencing stress, an agent specializing in stress reduction will be prioritized.

[0129] User actions

[0130] Users can utilize AI agents while considering their own emotional state. The agents work in conjunction with an emotion engine to automatically provide responses and handle tasks in a way that matches the user's mood. By selecting an agent based on their emotions, users can receive work support tailored to their individual needs. For example, if a project is deemed difficult to fulfill, an agent with optimization skills can be used to help resolve the project's challenges.

[0131] This invention enables a system that incorporates an emotion engine, expanding the possibilities for adapting to tasks based on the user's emotional state and further improving work efficiency. This mechanism provides users with a more comfortable and effective work environment.

[0132] The following describes the processing flow.

[0133] Step 1:

[0134] Users collect training data to generate AI agents tailored to their specific work needs. This data reflects the skills and knowledge required for particular tasks and operations.

[0135] Step 2:

[0136] Users train AI agents based on training data and register the models on the server. The trained AI agents have the ability to provide business support based on their skill sets.

[0137] Step 3:

[0138] The server stores registered AI agents and their metadata within a virtual space, making them accessible to other users when needed. The server also maintains the necessary infrastructure and databases to ensure the operation of the emotion engine.

[0139] Step 4:

[0140] The user activates the emotion engine in preparation for starting work. The emotion engine recognizes the user's emotional state in real time from their facial expressions, tone of voice, and input actions, and analyzes the data.

[0141] Step 5:

[0142] The emotion engine analyzes the user's emotions and displays the results on the device. Based on these results, the device selects a more supportive agent if the user is feeling stressed, and presents a more adaptable agent if work efficiency is declining.

[0143] Step 6:

[0144] The device selects an appropriate AI agent and imports it from the server into the device. The agent chosen is the one best suited to the user's emotional state.

[0145] Step 7:

[0146] The AI ​​agent starts operating on the device and provides instructions and work support tailored to the user's emotional state. This includes features such as making suggestions in a way that does not cause user dissatisfaction.

[0147] Step 8:

[0148] Users evaluate the AI ​​agent's performance and the support provided by the emotion engine, and provide feedback. The server uses this feedback to improve the performance of both the agent and the emotion engine.

[0149] As a result, advanced business support that adapts to the user's emotions becomes possible, and the present invention provides a more effective work environment.

[0150] (Example 2)

[0151] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0152] There is a need to provide an environment that effectively and efficiently utilizes individual skills and knowledge to support business operations using information processing equipment. However, current systems have the problem of not providing support optimized for individual needs because they do not take into account the emotional state of the user. In addition, selecting publicly available information processing equipment and adjusting it for different users is difficult, resulting in insufficient efficiency in business operations.

[0153] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0154] In this invention, the server includes means for training an information processing device using an individual's skills and knowledge and sharing that information processing device with others in a virtual space; means for analyzing the user's emotions and optimizing the information processing device based on the analysis results; and means for selecting an appropriate information processing device based on the analyzed emotional data and importing it to the terminal. This enables business support optimized for the user's emotional state, thereby achieving increased efficiency and automation of business processes.

[0155] "Skills" refer to the techniques and abilities necessary to effectively perform a specific task or job.

[0156] "Knowledge" is the understanding and memory of information acquired through education and experience, and is used for problem-solving and decision-making.

[0157] An "information processing device" is a device that includes computers and servers and is used for processing and analyzing data.

[0158] A "virtual space" is a computer simulation environment that does not have a physical existence and is constructed using digital technology.

[0159] "Emotion" refers to a person's feelings and mood, and is a concept that encompasses mental and psychological states such as joy, sadness, and stress.

[0160] "Analysis" is the act of breaking down data or events into smaller parts and then logically investigating and examining them to clarify their meaning and structure.

[0161] "Optimization" refers to adjusting a system or process to achieve maximum effectiveness and minimum cost under specific conditions.

[0162] A "terminal" refers to a device that connects to an information processing device and performs information input and output, and includes computers and smartphones.

[0163] "Import" refers to the operation of taking in data or information processing equipment from an external source, and adding new functions or information to a system or software.

[0164] This invention is a system for sharing information processing devices based on individual skills and knowledge within a virtual space to support users' work. Furthermore, it includes a function to analyze the user's emotions and optimize the information processing device based on the analysis results.

[0165] The server registers information processing devices created by individuals in a virtual space and manages them so that other users can share them. A common database system is used for this purpose. For example, MongoDB is used to manage and store data based on users' skills and knowledge.

[0166] The device captures the user's facial expressions and voice in real time and sends this data to an emotion analysis engine. It analyzes the user's emotions using facial recognition with OpenCV and a voice analysis API. Based on these analysis results, the operation of the information processing device is optimized to provide the user with the most suitable work support.

[0167] Users can review the content of their work support using the interface provided through their terminal and select options as needed. For example, if analysis reveals that the user is experiencing stress, the system will select an information processing device from the server that is effective in reducing stress, import it into the terminal, and use it. It is also possible to input prompts into the generating AI model to receive advice tailored to specific tasks. By entering prompts such as, "Please suggest ways to reduce the stress the user is currently experiencing," appropriate advice can be obtained.

[0168] This system enables flexible and effective work support tailored to the user's emotional state, thereby improving the efficiency of business processes.

[0169] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0170] Step 1:

[0171] The server registers the information processing devices trained by individuals in the virtual space. It receives data from the information processing devices entered by the user and stores this data in MongoDB. At this stage, the model based on the user's skills and knowledge is primarily managed. As a result, the virtual space is ready for others to access.

[0172] Step 2:

[0173] The device captures the user's facial expressions and voice in real time and inputs this data into an emotion analysis engine. OpenCV is used to analyze facial expressions from the video feed, and voice is processed by a voice analysis API. The output is the user's emotional state, which is sent to the server in JSON format. This information forms the basis for subsequent processing.

[0174] Step 3:

[0175] The server analyzes the received emotional state data and stores the information in a database. Machine learning algorithms are used in the analysis to compare the data with the user's past emotional history. As a result, a deeper understanding of the user's patterns is gained.

[0176] Step 4:

[0177] The terminal receives analysis results from the server and selects the appropriate information processing device based on them. Here, a Python script is used to perform the selection algorithmically. The appropriate information processing device is then presented to the user as output based on the input sentiment data and business needs.

[0178] Step 5:

[0179] The user reviews the presented information processing device and selects one as needed. The selected information processing device, through the user interface, can also send prompt messages to a generating AI model. A prompt message such as "Please provide suggestions to improve my current emotional state" is output, and the user receives appropriate countermeasures.

[0180] Step 6:

[0181] The server then saves the final user selection results back to the database for use in future analysis and optimization processes. By utilizing user interaction feedback for continuous improvement, it's possible to enhance the overall system performance.

[0182] (Application Example 2)

[0183] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0184] Conventional business support systems provide uniform support without considering the user's feelings or emotional state, which means they cannot adequately meet the individual needs of each user. Furthermore, because they cannot adjust work processes based on emotional states, they can lead to excessive stress and inefficient work operations.

[0185] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0186] This invention includes a server that trains a digital processing unit model using individual skills and knowledge and shares that digital processing unit model with others in the electrical space; a server that analyzes the user's emotional state, selects a digital processing unit model based on the analysis results, and adjusts the work process; and a server that utilizes the digital processing unit models of others to automate and streamline the work process. This enables optimal work support tailored to the user's emotional state, resulting in improved work efficiency and reduced stress.

[0187] "Individual skills and knowledge" refers to the unique abilities and information that an individual possesses, and is used in training the digital processing unit model.

[0188] A "digital processing unit model" refers to a program that runs on a computer or similar system, and is an algorithm trained to perform a specific task.

[0189] "Electrical space" refers to a computer network environment where digital information is exchanged and stored.

[0190] "Sharing with others" refers to making a trained digital processing unit model accessible to other users.

[0191] "User's emotional state" refers to the feelings and mental condition a user experiences at a particular time.

[0192] "Analysis" refers to the act of processing data to understand the emotional state of a user and deriving specific results or information.

[0193] "Adjusting the work process" refers to the act of changing the flow and procedures of work to the most optimal ones in accordance with the emotional state of the user.

[0194] "Automation and streamlining of business processes" refers to reducing manual operations and ensuring that tasks are performed with minimal time and effort.

[0195] The system that realizes this invention functions with the involvement of a server, terminals, and users. The server is responsible for training digital processing unit models based on the skills and knowledge of individual users and sharing those models with others in the electronic space. To analyze the user's emotional state, an emotion recognition engine is used, which processes voice and image data to understand the user's feelings in real time. The analyzed emotion data is then sent back to the server and used to select digital processing unit models and adjust work processes.

[0196] On the server, "Microsoft® Azure® Emotion API" or "Amazon Rekognition" can be used as the emotion recognition engine. These software programs rapidly process large amounts of emotion data and accurately determine the user's stress and relaxation levels. The processed emotion data serves as training data to optimize the algorithms of the digital processing unit model and provide the most effective work support for the user.

[0197] The device receives model and emotion data from the server and performs various actions on the user based on that information. For example, if the device analyzes that the user is feeling stressed, it may play relaxing music or adjust the room lighting to a calming level.

[0198] A concrete example would be a scenario where, upon returning home tired from work, the device starts playing "relaxing background music." In this case, a possible prompt message might be, "Please create a quiet environment so as not to distract you while you are concentrating on your work."

[0199] This invention enables more nuanced support tailored to the user's emotional state, leading to an expected improvement in the user experience.

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] The server collects skill and knowledge data provided by individual users. It then trains a digital processing model based on this data. The input is the user's skill and knowledge data, and the output is the trained digital processing model. This model includes algorithms optimized to support the user's specific tasks.

[0203] Step 2:

[0204] The server uses an emotion recognition engine to analyze the user's emotional state from audio and image input data. The input is the user's audio and image data, and the output is the analyzed emotional state data. The server processes this data in real time using the emotion recognition engine to identify the user's current emotional state.

[0205] Step 3:

[0206] The server selects the optimal digital processing model based on the analyzed emotional state data. The input is the user's emotional state data and a list of available models; the output is the selected model. The selected model provides the most appropriate work support for the user's current emotions.

[0207] Step 4:

[0208] The terminal receives a selected digital processing unit model and performs actions for the user based on that model. The input is the selected model, and the output is the performed action. The terminal makes suggestions based on the user's emotional state and takes specific actions, such as adjusting music or lighting.

[0209] Step 5:

[0210] Users utilize services provided by the terminal to obtain a comfortable work environment. User feedback is used to optimize the next digital processing unit model. The input is the services from the terminal, and the output is the user's work efficiency and stress reduction. Even if users do not provide direct feedback, sentiment data is saved as reference for selecting the next model.

[0211] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0212] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0213] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0214] [Second Embodiment]

[0215] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0216] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0217] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0218] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0219] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0220] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0221] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0222] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0223] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0224] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0225] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0226] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0227] The system according to the present invention generates a virtual computer model (hereinafter referred to as an AI agent) based on an individual's skills and knowledge, and makes it available in a virtual space, thereby providing an environment that can be used by others. This embodiment includes the processes of training, sharing, and using the AI ​​agent.

[0228] Server operation

[0229] The server registers user-generated AI agents within the virtual space. Here, the server receives the AI ​​agent's code and associated metadata (e.g., the agent's area of ​​expertise and intended use) and stores it in a database. After publication, the server manages the listing display to make it easier for other users to access those agents using the search function within the virtual space.

[0230] Terminal operation

[0231] The terminal provides the ability to search for and select AI agents through a user interface. Users retrieve AI agents from the server that meet their business needs and import them into the terminal. The terminal then uses these agents to automate specific business tasks. For example, to assist in creating marketing strategies, the terminal can deploy AI agents with appropriate marketing skills to help generate proposal materials.

[0232] User actions

[0233] Users prepare training data to model their expertise and use that data to customize an AI agent. The trained AI agent has the functionality to support specific business processes and tasks. Users publish the completed agent in a virtual space, making it available for use by other employees within the company. Furthermore, users can select AI agents created by other employees and use them to improve work efficiency and optimize processes.

[0234] Thus, the present invention provides a system and its embodiments for streamlining business processes while effectively utilizing individual knowledge and skills. Through mutual cooperation between servers, terminals, and users, knowledge sharing and business support are facilitated.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] Users collect their own expertise and skills as training data. This data is prepared for input into AI tools, and the necessary information is organized according to the nature of the work.

[0238] Step 2:

[0239] The user trains an AI agent based on training data to generate a model that aligns with their objectives. Here, the machine learning environment on the AI ​​system is used to fine-tune the algorithm, giving the agent the ability to perform specific tasks.

[0240] Step 3:

[0241] The user submits a registration request to the server for the completed AI agent. Based on the received data, the server saves the agent's metadata and code to a database and configures its public access settings within the virtual space.

[0242] Step 4:

[0243] The server displays and manages a list of publicly available AI agent information within the virtual space. This allows other users to easily search for and access available agents.

[0244] Step 5:

[0245] The terminal provides an AI agent search function via a user interface. Users select an AI agent based on their specific skills and objectives. Based on the selection, the terminal imports the appropriate agent from the server.

[0246] Step 6:

[0247] The device uses imported AI agents to perform and automate user-specified business processes. Examples include tasks such as data analysis, report generation, and schedule management.

[0248] Step 7:

[0249] Users evaluate the results of tasks performed by the AI ​​agent and provide feedback as needed to improve performance. This feedback may be used for subsequent training.

[0250] Through the steps described above, the system of the present invention enables the effective utilization of individual skills and knowledge and improves the efficiency of work.

[0251] (Example 1)

[0252] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0253] To facilitate information sharing and improve operational efficiency, there is a need for technology that provides an environment where individual expertise can be easily modeled and effectively shared with others.

[0254] In particular, there is a need for systems that enable the automation and optimization of business processes. In addition, there is a need for methods that allow users to select the most suitable computer model according to their individual needs and business content, and to maximize its utilization.

[0255] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0256] This invention includes a server that provides means for training a computer model based on an individual's expertise and sharing that model with others in an information space; means for selecting a computer model published in the information space and importing it into an information processing terminal to provide business support; means for utilizing the computer models of others to automate and optimize business procedures; means for creating prompt statements using a generated AI model and training an agent; and means for publishing the trained agent in a virtual space and managing an information list to make it easily accessible to others. This enables users to efficiently utilize their expertise and simultaneously achieve business process efficiency and knowledge sharing.

[0257] "Individual expertise" refers to a deep understanding and skills based on an individual's technical abilities and experience in a specific field.

[0258] A "computer model" is a computer program or algorithm built to perform a specific task based on data.

[0259] "Information space" refers to a virtual area where information is stored in digital format and can be accessed and manipulated by users.

[0260] An "information processing terminal" is a computing device used for inputting, processing, and outputting data, and includes personal computers and smartphones.

[0261] "Business support" refers to auxiliary functions and services provided to efficiently carry out specific tasks.

[0262] "Automating business procedures" means mechanizing processes to reduce manual operations by humans, thereby improving efficiency and accuracy.

[0263] "Optimization" is the process of adjusting a system or process to achieve the greatest effect under given conditions.

[0264] A "generative AI model" is an artificial intelligence system that learns patterns based on large amounts of data and generates output for new data.

[0265] A "prompt" is a form of instruction or question given to a generative AI model to elicit a specific output.

[0266] An "agent" is a software program designed to perform a specific task independently.

[0267] The system of this invention aims to generate AI agents, which are computer models based on an individual's expertise, and share them within a virtual space. This system functions with three main components: a server, a terminal, and a user.

[0268] First, the user digitizes their expertise and uses that data to train an AI agent using a generative AI model. The user creates a prompt sentence suitable for a specific purpose and inputs this prompt sentence into the generative AI model to generate an AI agent. As a concrete example, the user might create a prompt sentence such as, "Create an AI agent based on voice data to improve the sales process."

[0269] Next, the server receives the AI ​​agent code and associated metadata sent by the user. This metadata includes the agent's area of ​​expertise and intended use. The server stores this information in a database and then publishes the AI ​​agent in the virtual space. The published agents are managed by the server in an information list format, and care is taken to ensure that other users can easily access them.

[0270] The terminal navigates a virtual space through a user interface and provides functions for users to search for and select the necessary AI agents. The terminal has the ability to import selected agents from the server and utilize them for various business support purposes. For example, the terminal can use a marketing-adapted AI agent to assist in the automatic generation of materials proposing marketing strategies.

[0271] Through the above process, the system effectively models user expertise and provides an environment for automating and optimizing business processes. Furthermore, by utilizing the most suitable AI agent according to individual business needs within this environment, it is possible to promote the streamlining of business processes and the sharing of knowledge.

[0272] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0273] Step 1:

[0274] The user prepares their expertise as training data. Here, the user collects data related to specific tasks and organizes it in text, audio, or image format. The input includes existing business data and experience-based knowledge. This is then formatted into the form necessary for input into the generating AI model, resulting in a dataset that serves as the foundation for building the AI ​​agent.

[0275] Step 2:

[0276] The user creates a prompt and inputs it into a generative AI model to generate an AI agent. The input consists of the created prompt (e.g., "Create an AI agent based on voice data to improve the sales process.") and training data. The generative AI model trains the AI ​​agent based on this input and generates an AI agent that reflects expertise as output.

[0277] Step 3:

[0278] The server stores the AI agent received from the user and its related metadata in the database. As input, there is the code of the AI agent and metadata indicating the field of expertise and purpose of use. The server combines and manages this information and converts it into a form that can be publicly available in the virtual space as output.

[0279] Step 4:

[0280] The server publicly releases the trained AI agent within the virtual space and manages a list of information accessible to other users. As input, there is the data of the AI agent stored in the previous step. The server utilizes it to organize access rights and list display, and provides an environment where users can easily search for agents as output.

[0281] Step 5:

[0282] The terminal imports the AI agent selected from the virtual space through the user interface and uses it for business support. As input, it is the information of the AI agent selected by the user. The terminal operates the agent in the execution environment based on this data and provides functions useful for improving business efficiency to the user as output. Specifically, the agent automatically generates proposal materials for marketing strategies and shortens the working hours.

[0283] (Application Example 1)

[0284] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0285] In modern cities, while making use of the individual expertise of residents, it is required to efficiently solve various problems in the region. However, in the conventional method, since the mechanism for effectively sharing personal knowledge and skills and using them for actual problem-solving is insufficient, more efficient and effective solutions are needed.

[0286] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0287] In this invention, the server includes means for training an information processing model using an individual's skills and knowledge and sharing the information processing model with others in a virtual space, means for selecting an information processing model published in the virtual space, importing it into an information terminal, and providing business support, means for leveraging the information processing models of others to automate and streamline business processes, and means for sharing information processing models within a community and using them to solve urban problems. This enables the efficient solution of urban problems.

[0288] "An individual's skills and knowledge" refers to the collection of specialized abilities and knowledge possessed by a specific person.

[0289] "An information processing model" is an artificial intelligence model for analyzing data and making judgments, constructed based on an individual's skills and knowledge.

[0290] "A virtual space" is a simulation or virtual space on the Internet generated by digital technology.

[0291] "Means for sharing with others" is a method for enabling other users to access and utilize certain information or technology.

[0292] "An information terminal" refers to a device capable of processing and displaying digital information, specifically a smartphone or a computer.

[0293] "Business support" is the technical or knowledge-based assistance provided to efficiently conduct specific business activities.

[0294] "Automation" means enabling machines or software to perform tasks or processes that were previously done by humans.

[0295] "Efficiency improvement" means optimizing processes and methods to obtain the greatest possible results with limited resources.

[0296] A "community" is a group of people who share common interests or goals, and is a group associated with a particular region or field.

[0297] "Urban problem solving" refers to methods and means for resolving various social, environmental, and economic challenges that arise in cities.

[0298] The system for implementing this invention enables the generation and use of information processing models based on individual knowledge. Servers, terminals, and users each play their respective roles and work in coordination.

[0299] First, the server registers information processing models generated using an individual's skills and knowledge within a virtual space, making them accessible to others. To this end, the server uses a database such as Firebase Firestore to manage the model's code and metadata, displaying them as a searchable list. The server also controls user access and distributes the appropriate model to information terminals.

[0300] Next, users can access a virtual space using an information terminal equipped with a dedicated application, search for and select an information processing model that meets their needs. The selected model is downloaded to the information terminal and used to support business operations and solve urban problems. A concrete example would be an AI agent that assists in designing ecologically friendly transportation systems.

[0301] This application utilizes development environments such as Android Studio and Xcode and runs on information devices including smartphones and tablets. The information processing model is trained based on expertise provided by residents and is exposed to the virtual space via Firebase.

[0302] Also, as an example of a specific prompt sentence used by the user, there is an instruction such as "Please construct an AI agent specializing in the design of an ecological-friendly transportation system in urban areas based on the following dataset." This prompt helps the information processing model provide the knowledge necessary for solving urban problems.

[0303] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0304] Step 1:

[0305] The server receives the training data provided by the user and generates an information processing model. It receives the training data and the user's skill information as inputs, and constructs an information processing model using a machine learning algorithm. The output is the information processing model registered in the virtual space.

[0306] Step 2:

[0307] The user accesses the virtual space using a dedicated application and searches for a list of publicly available information processing models. The user specifies search conditions (such as ecological-friendly, etc.) as inputs and obtains the corresponding information processing model from the server. The output is the model list displayed on the user's information terminal.

[0308] Step 3:

[0309] The user selects an appropriate information processing model and downloads it to the information terminal. The server encrypts and transmits the selected model, which is decoded on the user's terminal side and incorporated into the application for business support. The output is the incorporated information processing model, which is in a state where it can be utilized for solving urban problems.

[0310] Step 4:

[0311] The information processing model executed on the terminal performs data calculations based on user prompts. It receives prompts as input and utilizes its internal knowledge to generate a predetermined analysis or proposal. The output might be, for example, a proposal for an optimal urban transportation plan.

[0312] Step 5:

[0313] The server collects user feedback and new data, and incorporates this information to improve the accuracy of the information processing model. It receives user feedback as input and retrains the model. The output is the improved new information processing model.

[0314] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0315] This invention combines a system that shares computer models (AI agents) based on individual skills and knowledge within a virtual space to enable business support and automation with an emotion engine that recognizes user emotions. In this configuration, the user's emotional state is analyzed in real time, enabling the adaptation and optimization of business processes based on that information.

[0316] Server operation

[0317] The server registers user-generated AI agents and emotion engines within the virtual space and manages the usage status of each agent. The server maintains a database for selecting agents and adjusting business processes based on user emotion data. It also utilizes the emotion analysis results obtained by the emotion engine as training data for AI agents, supporting the continuous optimization of the model.

[0318] Terminal operation

[0319] The terminal enhances user support through the collaboration of agents and an emotion engine. The terminal displays emotional data acquired from the emotion engine via the user interface and adjusts agent performance based on this information. It also provides a function to automatically select and import the appropriate AI agent according to the user's current emotional state. For example, if the user is experiencing stress, an agent specializing in stress reduction will be prioritized.

[0320] User actions

[0321] Users can utilize AI agents while considering their own emotional state. The agents work in conjunction with an emotion engine to automatically provide responses and handle tasks in a way that matches the user's mood. By selecting an agent based on their emotions, users can receive work support tailored to their individual needs. For example, if a project is deemed difficult to fulfill, an agent with optimization skills can be used to help resolve the project's challenges.

[0322] This invention enables a system that incorporates an emotion engine, expanding the possibilities for adapting to tasks based on the user's emotional state and further improving work efficiency. This mechanism provides users with a more comfortable and effective work environment.

[0323] The following describes the processing flow.

[0324] Step 1:

[0325] Users collect training data to generate AI agents tailored to their specific work needs. This data reflects the skills and knowledge required for particular tasks and operations.

[0326] Step 2:

[0327] Users train AI agents based on training data and register the models on the server. The trained AI agents have the ability to provide business support based on their skill sets.

[0328] Step 3:

[0329] The server stores registered AI agents and their metadata within a virtual space, making them accessible to other users when needed. The server also maintains the necessary infrastructure and databases to ensure the operation of the emotion engine.

[0330] Step 4:

[0331] The user activates the emotion engine in preparation for starting work. The emotion engine recognizes the user's emotional state in real time from their facial expressions, tone of voice, and input actions, and analyzes the data.

[0332] Step 5:

[0333] The emotion engine analyzes the user's emotions and displays the results on the device. Based on these results, the device selects a more supportive agent if the user is feeling stressed, and presents a more adaptable agent if work efficiency is declining.

[0334] Step 6:

[0335] The device selects an appropriate AI agent and imports it from the server into the device. The agent chosen is the one best suited to the user's emotional state.

[0336] Step 7:

[0337] The AI ​​agent starts operating on the device and provides instructions and work support tailored to the user's emotional state. This includes features such as making suggestions in a way that does not cause user dissatisfaction.

[0338] Step 8:

[0339] Users evaluate the AI ​​agent's performance and the support provided by the emotion engine, and provide feedback. The server uses this feedback to improve the performance of both the agent and the emotion engine.

[0340] As a result, advanced business support that adapts to the user's emotions becomes possible, and the present invention provides a more effective work environment.

[0341] (Example 2)

[0342] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0343] There is a need to provide an environment that effectively and efficiently utilizes individual skills and knowledge to support business operations using information processing equipment. However, current systems have the problem of not providing support optimized for individual needs because they do not take into account the emotional state of the user. In addition, selecting publicly available information processing equipment and adjusting it for different users is difficult, resulting in insufficient efficiency in business operations.

[0344] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0345] In this invention, the server includes means for training an information processing device using an individual's skills and knowledge and sharing that information processing device with others in a virtual space; means for analyzing the user's emotions and optimizing the information processing device based on the analysis results; and means for selecting an appropriate information processing device based on the analyzed emotional data and importing it to the terminal. This enables business support optimized for the user's emotional state, thereby achieving increased efficiency and automation of business processes.

[0346] "Skills" refer to the techniques and abilities necessary to effectively perform a specific task or job.

[0347] "Knowledge" is the understanding and memory of information acquired through education and experience, and is used for problem-solving and decision-making.

[0348] An "information processing device" is a device that includes computers and servers and is used for processing and analyzing data.

[0349] A "virtual space" is a computer simulation environment that does not have a physical existence and is constructed using digital technology.

[0350] "Emotion" refers to a person's feelings and mood, and is a concept that encompasses mental and psychological states such as joy, sadness, and stress.

[0351] "Analysis" is the act of breaking down data or events into smaller parts and then logically investigating and examining them to clarify their meaning and structure.

[0352] "Optimization" refers to adjusting a system or process to achieve maximum effectiveness and minimum cost under specific conditions.

[0353] A "terminal" refers to a device that connects to an information processing device and performs information input and output, and includes computers and smartphones.

[0354] "Import" refers to the operation of taking in data or information processing equipment from an external source, and adding new functions or information to a system or software.

[0355] This invention is a system for sharing information processing devices based on individual skills and knowledge within a virtual space to support users' work. Furthermore, it includes a function to analyze the user's emotions and optimize the information processing device based on the analysis results.

[0356] The server registers information processing devices created by individuals in a virtual space and manages them so that other users can share them. A common database system is used for this purpose. For example, MongoDB is used to manage and store data based on users' skills and knowledge.

[0357] The device captures the user's facial expressions and voice in real time and sends this data to an emotion analysis engine. It analyzes the user's emotions using facial recognition with OpenCV and a voice analysis API. Based on these analysis results, the operation of the information processing device is optimized to provide the user with the most suitable work support.

[0358] Users can review the content of their work support using the interface provided through their terminal and select options as needed. For example, if analysis reveals that the user is experiencing stress, the system will select an information processing device from the server that is effective in reducing stress, import it into the terminal, and use it. It is also possible to input prompts into the generating AI model to receive advice tailored to specific tasks. By entering prompts such as, "Please suggest ways to reduce the stress the user is currently experiencing," appropriate advice can be obtained.

[0359] This system enables flexible and effective work support tailored to the user's emotional state, thereby improving the efficiency of business processes.

[0360] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0361] Step 1:

[0362] The server registers the information processing devices trained by individuals in the virtual space. It receives data from the information processing devices entered by the user and stores this data in MongoDB. At this stage, the model based on the user's skills and knowledge is primarily managed. As a result, the virtual space is ready for others to access.

[0363] Step 2:

[0364] The device captures the user's facial expressions and voice in real time and inputs this data into an emotion analysis engine. OpenCV is used to analyze facial expressions from the video feed, and voice is processed by a voice analysis API. The output is the user's emotional state, which is sent to the server in JSON format. This information forms the basis for subsequent processing.

[0365] Step 3:

[0366] The server analyzes the received emotional state data and stores the information in a database. Machine learning algorithms are used in the analysis to compare the data with the user's past emotional history. As a result, a deeper understanding of the user's patterns is gained.

[0367] Step 4:

[0368] The terminal receives analysis results from the server and selects the appropriate information processing device based on them. Here, a Python script is used to perform the selection algorithmically. The appropriate information processing device is then presented to the user as output based on the input sentiment data and business needs.

[0369] Step 5:

[0370] The user reviews the presented information processing device and selects one as needed. The selected information processing device, through the user interface, can also send prompt messages to a generating AI model. A prompt message such as "Please provide suggestions to improve my current emotional state" is output, and the user receives appropriate countermeasures.

[0371] Step 6:

[0372] The server then saves the final user selection results back to the database for use in future analysis and optimization processes. By utilizing user interaction feedback for continuous improvement, it's possible to enhance the overall system performance.

[0373] (Application Example 2)

[0374] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0375] Conventional business support systems provide uniform support without considering the user's feelings or emotional state, which means they cannot adequately meet the individual needs of each user. Furthermore, because they cannot adjust work processes based on emotional states, they can lead to excessive stress and inefficient work operations.

[0376] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0377] This invention includes a server that trains a digital processing unit model using individual skills and knowledge and shares that digital processing unit model with others in the electrical space; a server that analyzes the user's emotional state, selects a digital processing unit model based on the analysis results, and adjusts the work process; and a server that utilizes the digital processing unit models of others to automate and streamline the work process. This enables optimal work support tailored to the user's emotional state, resulting in improved work efficiency and reduced stress.

[0378] "Individual skills and knowledge" refers to the unique abilities and information that an individual possesses, and is used in training the digital processing unit model.

[0379] A "digital processing unit model" refers to a program that runs on a computer or similar system, and is an algorithm trained to perform a specific task.

[0380] "Electrical space" refers to a computer network environment where digital information is exchanged and stored.

[0381] "Sharing with others" refers to making a trained digital processing unit model accessible to other users.

[0382] "User's emotional state" refers to the feelings and mental condition a user experiences at a particular time.

[0383] "Analysis" refers to the act of processing data to understand the emotional state of a user and deriving specific results or information.

[0384] "Adjusting the work process" refers to the act of changing the flow and procedures of work to the most optimal ones in accordance with the emotional state of the user.

[0385] "Automation and streamlining of business processes" refers to reducing manual operations and ensuring that tasks are performed with minimal time and effort.

[0386] The system that realizes this invention functions with the involvement of a server, terminals, and users. The server is responsible for training digital processing unit models based on the skills and knowledge of individual users and sharing those models with others in the electronic space. To analyze the user's emotional state, an emotion recognition engine is used, which processes voice and image data to understand the user's feelings in real time. The analyzed emotion data is then sent back to the server and used to select digital processing unit models and adjust work processes.

[0387] On the server, you can use "Microsoft Azure Emotion API" or "Amazon Rekognition" as your emotion recognition engine. These software programs can quickly process large amounts of emotion data and accurately determine the user's stress and relaxation levels. The processed emotion data serves as training data to optimize the algorithms of the digital processing unit model and provide the most effective work support for the user.

[0388] The device receives model and emotion data from the server and performs various actions on the user based on that information. For example, if the device analyzes that the user is feeling stressed, it may play relaxing music or adjust the room lighting to a calming level.

[0389] A concrete example would be a scenario where, upon returning home tired from work, the device starts playing "relaxing background music." In this case, a possible prompt message might be, "Please create a quiet environment so as not to distract you while you are concentrating on your work."

[0390] This invention enables more nuanced support tailored to the user's emotional state, leading to an expected improvement in the user experience.

[0391] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0392] Step 1:

[0393] The server collects skill and knowledge data provided by individual users. It then trains a digital processing model based on this data. The input is the user's skill and knowledge data, and the output is the trained digital processing model. This model includes algorithms optimized to support the user's specific tasks.

[0394] Step 2:

[0395] The server uses an emotion recognition engine to analyze the user's emotional state from audio and image input data. The input is the user's audio and image data, and the output is the analyzed emotional state data. The server processes this data in real time using the emotion recognition engine to identify the user's current emotional state.

[0396] Step 3:

[0397] The server selects the optimal digital processing model based on the analyzed emotional state data. The input is the user's emotional state data and a list of available models; the output is the selected model. The selected model provides the most appropriate work support for the user's current emotions.

[0398] Step 4:

[0399] The terminal receives a selected digital processing unit model and performs actions for the user based on that model. The input is the selected model, and the output is the performed action. The terminal makes suggestions based on the user's emotional state and takes specific actions, such as adjusting music or lighting.

[0400] Step 5:

[0401] Users utilize services provided by the terminal to obtain a comfortable work environment. User feedback is used to optimize the next digital processing unit model. The input is the services from the terminal, and the output is the user's work efficiency and stress reduction. Even if users do not provide direct feedback, sentiment data is saved as reference for selecting the next model.

[0402] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0403] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0404] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0405] [Third Embodiment]

[0406] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0407] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0408] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0409] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0410] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0411] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0412] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0413] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0414] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0415] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0416] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0417] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0418] The system according to the present invention generates a virtual computer model (hereinafter referred to as an AI agent) based on an individual's skills and knowledge, and makes it available in a virtual space, thereby providing an environment that can be used by others. This embodiment includes the processes of training, sharing, and using the AI ​​agent.

[0419] Server operation

[0420] The server registers user-generated AI agents within the virtual space. Here, the server receives the AI ​​agent's code and associated metadata (e.g., the agent's area of ​​expertise and intended use) and stores it in a database. After publication, the server manages the listing display to make it easier for other users to access those agents using the search function within the virtual space.

[0421] Terminal operation

[0422] The terminal provides the ability to search for and select AI agents through a user interface. Users retrieve AI agents from the server that meet their business needs and import them into the terminal. The terminal then uses these agents to automate specific business tasks. For example, to assist in creating marketing strategies, the terminal can deploy AI agents with appropriate marketing skills to help generate proposal materials.

[0423] User actions

[0424] Users prepare training data to model their expertise and use that data to customize an AI agent. The trained AI agent has the functionality to support specific business processes and tasks. Users publish the completed agent in a virtual space, making it available for use by other employees within the company. Furthermore, users can select AI agents created by other employees and use them to improve work efficiency and optimize processes.

[0425] Thus, the present invention provides a system and its embodiments for streamlining business processes while effectively utilizing individual knowledge and skills. Through mutual cooperation between servers, terminals, and users, knowledge sharing and business support are facilitated.

[0426] The following describes the processing flow.

[0427] Step 1:

[0428] Users collect their own expertise and skills as training data. This data is prepared for input into AI tools, and the necessary information is organized according to the nature of the work.

[0429] Step 2:

[0430] The user trains an AI agent based on training data to generate a model that aligns with their objectives. Here, the machine learning environment on the AI ​​system is used to fine-tune the algorithm, giving the agent the ability to perform specific tasks.

[0431] Step 3:

[0432] The user submits a registration request to the server for the completed AI agent. Based on the received data, the server saves the agent's metadata and code to a database and configures its public access settings within the virtual space.

[0433] Step 4:

[0434] The server displays and manages a list of publicly available AI agent information within the virtual space. This allows other users to easily search for and access available agents.

[0435] Step 5:

[0436] The terminal provides an AI agent search function via a user interface. Users select an AI agent based on their specific skills and objectives. Based on the selection, the terminal imports the appropriate agent from the server.

[0437] Step 6:

[0438] The device uses imported AI agents to perform and automate user-specified business processes. Examples include tasks such as data analysis, report generation, and schedule management.

[0439] Step 7:

[0440] Users evaluate the results of tasks performed by the AI ​​agent and provide feedback as needed to improve performance. This feedback may be used for subsequent training.

[0441] Through the steps described above, the system of the present invention enables the effective utilization of individual skills and knowledge and improves the efficiency of work.

[0442] (Example 1)

[0443] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0444] To facilitate information sharing and improve operational efficiency, there is a need for technology that provides an environment where individual expertise can be easily modeled and effectively shared with others.

[0445] In particular, there is a need for systems that enable the automation and optimization of business processes. In addition, there is a need for methods that allow users to select the most suitable computer model according to their individual needs and business content, and to maximize its utilization.

[0446] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0447] This invention includes a server that provides means for training a computer model based on an individual's expertise and sharing that model with others in an information space; means for selecting a computer model published in the information space and importing it into an information processing terminal to provide business support; means for utilizing the computer models of others to automate and optimize business procedures; means for creating prompt statements using a generated AI model and training an agent; and means for publishing the trained agent in a virtual space and managing an information list to make it easily accessible to others. This enables users to efficiently utilize their expertise and simultaneously achieve business process efficiency and knowledge sharing.

[0448] "Individual expertise" refers to a deep understanding and skills based on an individual's technical abilities and experience in a specific field.

[0449] A "computer model" is a computer program or algorithm built to perform a specific task based on data.

[0450] "Information space" refers to a virtual area where information is stored in digital format and can be accessed and manipulated by users.

[0451] An "information processing terminal" is a computing device used for inputting, processing, and outputting data, and includes personal computers and smartphones.

[0452] "Business support" refers to auxiliary functions and services provided to efficiently carry out specific tasks.

[0453] "Automating business procedures" means mechanizing processes to reduce manual operations by humans, thereby improving efficiency and accuracy.

[0454] "Optimization" is the process of adjusting a system or process to achieve the greatest effect under given conditions.

[0455] A "generative AI model" is an artificial intelligence system that learns patterns based on large amounts of data and generates output for new data.

[0456] A "prompt" is a form of instruction or question given to a generative AI model to elicit a specific output.

[0457] An "agent" is a software program designed to perform a specific task independently.

[0458] The system of this invention aims to generate AI agents, which are computer models based on an individual's expertise, and share them within a virtual space. This system functions with three main components: a server, a terminal, and a user.

[0459] First, the user digitizes their expertise and uses that data to train an AI agent using a generative AI model. The user creates a prompt sentence suitable for a specific purpose and inputs this prompt sentence into the generative AI model to generate an AI agent. As a concrete example, the user might create a prompt sentence such as, "Create an AI agent based on voice data to improve the sales process."

[0460] Next, the server receives the AI ​​agent code and associated metadata sent by the user. This metadata includes the agent's area of ​​expertise and intended use. The server stores this information in a database and then publishes the AI ​​agent in the virtual space. The published agents are managed by the server in an information list format, and care is taken to ensure that other users can easily access them.

[0461] The terminal navigates a virtual space through a user interface and provides functions for users to search for and select the necessary AI agents. The terminal has the ability to import selected agents from the server and utilize them for various business support purposes. For example, the terminal can use a marketing-adapted AI agent to assist in the automatic generation of materials proposing marketing strategies.

[0462] Through the above process, the system effectively models user expertise and provides an environment for automating and optimizing business processes. Furthermore, by utilizing the most suitable AI agent according to individual business needs within this environment, it is possible to promote the streamlining of business processes and the sharing of knowledge.

[0463] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0464] Step 1:

[0465] The user prepares their expertise as training data. Here, the user collects data related to specific tasks and organizes it in text, audio, or image format. The input includes existing business data and experience-based knowledge. This is then formatted into the form necessary for input into the generating AI model, resulting in a dataset that serves as the foundation for building the AI ​​agent.

[0466] Step 2:

[0467] The user creates a prompt and inputs it into a generative AI model to generate an AI agent. The input consists of the created prompt (e.g., "Create an AI agent based on voice data to improve the sales process.") and training data. The generative AI model trains the AI ​​agent based on this input and generates an AI agent that reflects expertise as output.

[0468] Step 3:

[0469] The server stores AI agents and their associated metadata received from users in a database. Input includes the AI ​​agent's code and metadata indicating its area of ​​expertise and intended use. The server combines and manages this information, then converts it into an output format that can be publicly shared in the virtual space.

[0470] Step 4:

[0471] The server exposes trained AI agents within a virtual space and manages a list of information accessible to other users. The input is the AI ​​agent data saved in the previous step. The server uses this data to configure access permissions and list displays, providing an environment where users can easily search for agents.

[0472] Step 5:

[0473] The terminal imports an AI agent selected from a virtual space via a user interface and uses it to support business operations. The input is information about the AI ​​agent chosen by the user. Based on this data, the terminal runs the agent in the execution environment and provides the user with functions that help improve work efficiency. Specifically, the agent automatically generates marketing strategy proposal materials, reducing work time.

[0474] (Application Example 1)

[0475] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0476] In modern cities, there is a need to efficiently solve various local problems while utilizing the individual expertise of residents. However, traditional methods lack sufficient mechanisms for effectively sharing individual knowledge and skills and putting them to practical use in problem-solving, thus necessitating more efficient and effective solutions.

[0477] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0478] This invention includes a server that provides means for training information processing models using individual skills and knowledge and sharing those information processing models with others in a virtual space; means for selecting publicly available information processing models in the virtual space, importing them into an information terminal, and providing business support; means for utilizing information processing models of others to automate and streamline business processes; and means for sharing information processing models within a community and using them to solve urban problems. This enables the efficient resolution of urban problems.

[0479] "Individual skills and knowledge" refers to the collection of specialized abilities and knowledge possessed by a particular person.

[0480] An "information processing model" is an artificial intelligence model built on an individual's skills and knowledge to analyze data and make decisions.

[0481] A "virtual space" is a simulation or virtual space on the internet that is generated using digital technology.

[0482] "Means of sharing with others" refers to methods for making certain information or technology accessible and usable by other users.

[0483] An "information terminal" refers to a device capable of processing and displaying digital information, specifically a smartphone or computer.

[0484] "Business support" refers to technical or knowledge-based assistance provided to efficiently carry out specific business activities.

[0485] "Automation" refers to the process of having machines or software perform tasks or processes that were previously done by humans.

[0486] "Efficiency improvement" means optimizing processes and methods to obtain the greatest possible results with limited resources.

[0487] A "community" is a group of people who share common interests or goals, and is a group associated with a particular region or field.

[0488] "Urban problem solving" refers to methods and means for resolving various social, environmental, and economic challenges that arise in cities.

[0489] The system for implementing this invention enables the generation and use of information processing models based on individual knowledge. Servers, terminals, and users each play their respective roles and work in coordination.

[0490] First, the server registers information processing models generated using an individual's skills and knowledge within a virtual space, making them accessible to others. To this end, the server uses a database such as Firebase Firestore to manage the model's code and metadata, displaying them as a searchable list. The server also controls user access and distributes the appropriate model to information terminals.

[0491] Next, users can access a virtual space using an information terminal equipped with a dedicated application, search for and select an information processing model that meets their needs. The selected model is downloaded to the information terminal and used to support business operations and solve urban problems. A concrete example would be an AI agent that assists in designing ecologically friendly transportation systems.

[0492] This application utilizes development environments such as Android Studio and Xcode and runs on information devices including smartphones and tablets. The information processing model is trained based on expertise provided by residents and is exposed to the virtual space via Firebase.

[0493] Furthermore, an example of a specific prompt that a user might use is, "Based on the following dataset, build an AI agent specializing in designing ecologically friendly transportation systems in urban areas." This prompt helps the information processing model provide the insights necessary to solve urban problems.

[0494] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0495] Step 1:

[0496] The server receives training data provided by the user and generates an information processing model. It receives training data and user skill information as input and constructs the information processing model using machine learning algorithms. The output is the information processing model registered in the virtual space.

[0497] Step 2:

[0498] The user accesses the virtual space using a dedicated application and searches for a list of publicly available information processing models. The user specifies search criteria (e.g., ecologically friendly) as input and retrieves the corresponding information processing models from the server. The output is a list of models displayed on the user's information terminal.

[0499] Step 3:

[0500] The user selects an appropriate information processing model and downloads it to their information terminal. The server encrypts and transmits the selected model, which is then decoded on the user's terminal and integrated into a business support application. The output is the integrated information processing model, ready for use in solving urban problems.

[0501] Step 4:

[0502] The information processing model executed on the terminal performs data calculations based on user prompts. It receives prompts as input and utilizes its internal knowledge to generate a predetermined analysis or proposal. The output might be, for example, a proposal for an optimal urban transportation plan.

[0503] Step 5:

[0504] The server collects user feedback and new data, and incorporates this information to improve the accuracy of the information processing model. It receives user feedback as input and retrains the model. The output is the improved new information processing model.

[0505] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0506] This invention combines a system that shares computer models (AI agents) based on individual skills and knowledge within a virtual space to enable business support and automation with an emotion engine that recognizes user emotions. In this configuration, the user's emotional state is analyzed in real time, enabling the adaptation and optimization of business processes based on that information.

[0507] Server operation

[0508] The server registers user-generated AI agents and emotion engines within the virtual space and manages the usage status of each agent. The server maintains a database for selecting agents and adjusting business processes based on user emotion data. It also utilizes the emotion analysis results obtained by the emotion engine as training data for AI agents, supporting the continuous optimization of the model.

[0509] Terminal operation

[0510] The terminal enhances user support through the collaboration of agents and an emotion engine. The terminal displays emotional data acquired from the emotion engine via the user interface and adjusts agent performance based on this information. It also provides a function to automatically select and import the appropriate AI agent according to the user's current emotional state. For example, if the user is experiencing stress, an agent specializing in stress reduction will be prioritized.

[0511] User actions

[0512] Users can utilize AI agents while considering their own emotional state. The agents work in conjunction with an emotion engine to automatically provide responses and handle tasks in a way that matches the user's mood. By selecting an agent based on their emotions, users can receive work support tailored to their individual needs. For example, if a project is deemed difficult to fulfill, an agent with optimization skills can be used to help resolve the project's challenges.

[0513] This invention enables a system that incorporates an emotion engine, expanding the possibilities for adapting to tasks based on the user's emotional state and further improving work efficiency. This mechanism provides users with a more comfortable and effective work environment.

[0514] The following describes the processing flow.

[0515] Step 1:

[0516] Users collect training data to generate AI agents tailored to their specific work needs. This data reflects the skills and knowledge required for particular tasks and operations.

[0517] Step 2:

[0518] Users train AI agents based on training data and register the models on the server. The trained AI agents have the ability to provide business support based on their skill sets.

[0519] Step 3:

[0520] The server stores registered AI agents and their metadata within a virtual space, making them accessible to other users when needed. The server also maintains the necessary infrastructure and databases to ensure the operation of the emotion engine.

[0521] Step 4:

[0522] The user activates the emotion engine in preparation for starting work. The emotion engine recognizes the user's emotional state in real time from their facial expressions, tone of voice, and input actions, and analyzes the data.

[0523] Step 5:

[0524] The emotion engine analyzes the user's emotions and displays the results on the device. Based on these results, the device selects a more supportive agent if the user is feeling stressed, and presents a more adaptable agent if work efficiency is declining.

[0525] Step 6:

[0526] The device selects an appropriate AI agent and imports it from the server into the device. The agent chosen is the one best suited to the user's emotional state.

[0527] Step 7:

[0528] The AI ​​agent starts operating on the device and provides instructions and work support tailored to the user's emotional state. This includes features such as making suggestions in a way that does not cause user dissatisfaction.

[0529] Step 8:

[0530] Users evaluate the AI ​​agent's performance and the support provided by the emotion engine, and provide feedback. The server uses this feedback to improve the performance of both the agent and the emotion engine.

[0531] As a result, advanced business support that adapts to the user's emotions becomes possible, and the present invention provides a more effective work environment.

[0532] (Example 2)

[0533] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0534] There is a need to provide an environment that effectively and efficiently utilizes individual skills and knowledge to support business operations using information processing equipment. However, current systems have the problem of not providing support optimized for individual needs because they do not take into account the emotional state of the user. In addition, selecting publicly available information processing equipment and adjusting it for different users is difficult, resulting in insufficient efficiency in business operations.

[0535] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0536] In this invention, the server includes means for training an information processing device using an individual's skills and knowledge and sharing that information processing device with others in a virtual space; means for analyzing the user's emotions and optimizing the information processing device based on the analysis results; and means for selecting an appropriate information processing device based on the analyzed emotional data and importing it to the terminal. This enables business support optimized for the user's emotional state, thereby achieving increased efficiency and automation of business processes.

[0537] "Skills" refer to the techniques and abilities necessary to effectively perform a specific task or job.

[0538] "Knowledge" is the understanding and memory of information acquired through education and experience, and is used for problem-solving and decision-making.

[0539] An "information processing device" is a device that includes computers and servers and is used for processing and analyzing data.

[0540] A "virtual space" is a computer simulation environment that does not have a physical existence and is constructed using digital technology.

[0541] "Emotion" refers to a person's feelings and mood, and is a concept that encompasses mental and psychological states such as joy, sadness, and stress.

[0542] "Analysis" is the act of breaking down data or events into smaller parts and then logically investigating and examining them to clarify their meaning and structure.

[0543] "Optimization" refers to adjusting a system or process to achieve maximum effectiveness and minimum cost under specific conditions.

[0544] A "terminal" refers to a device that connects to an information processing device and performs information input and output, and includes computers and smartphones.

[0545] "Import" refers to the operation of taking in data or information processing equipment from an external source, and adding new functions or information to a system or software.

[0546] This invention is a system for sharing information processing devices based on individual skills and knowledge within a virtual space to support users' work. Furthermore, it includes a function to analyze the user's emotions and optimize the information processing device based on the analysis results.

[0547] The server registers information processing devices created by individuals in a virtual space and manages them so that other users can share them. A common database system is used for this purpose. For example, MongoDB is used to manage and store data based on users' skills and knowledge.

[0548] The device captures the user's facial expressions and voice in real time and sends this data to an emotion analysis engine. It analyzes the user's emotions using facial recognition with OpenCV and a voice analysis API. Based on these analysis results, the operation of the information processing device is optimized to provide the user with the most suitable work support.

[0549] Users can review the content of their work support using the interface provided through their terminal and select options as needed. For example, if analysis reveals that the user is experiencing stress, the system will select an information processing device from the server that is effective in reducing stress, import it into the terminal, and use it. It is also possible to input prompts into the generating AI model to receive advice tailored to specific tasks. By entering prompts such as, "Please suggest ways to reduce the stress the user is currently experiencing," appropriate advice can be obtained.

[0550] This system enables flexible and effective work support tailored to the user's emotional state, thereby improving the efficiency of business processes.

[0551] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0552] Step 1:

[0553] The server registers the information processing devices trained by individuals in the virtual space. It receives data from the information processing devices entered by the user and stores this data in MongoDB. At this stage, the model based on the user's skills and knowledge is primarily managed. As a result, the virtual space is ready for others to access.

[0554] Step 2:

[0555] The device captures the user's facial expressions and voice in real time and inputs this data into an emotion analysis engine. OpenCV is used to analyze facial expressions from the video feed, and voice is processed by a voice analysis API. The output is the user's emotional state, which is sent to the server in JSON format. This information forms the basis for subsequent processing.

[0556] Step 3:

[0557] The server analyzes the received emotional state data and stores the information in a database. Machine learning algorithms are used in the analysis to compare the data with the user's past emotional history. As a result, a deeper understanding of the user's patterns is gained.

[0558] Step 4:

[0559] The terminal receives analysis results from the server and selects the appropriate information processing device based on them. Here, a Python script is used to perform the selection algorithmically. The appropriate information processing device is then presented to the user as output based on the input sentiment data and business needs.

[0560] Step 5:

[0561] The user reviews the presented information processing device and selects one as needed. The selected information processing device, through the user interface, can also send prompt messages to a generating AI model. A prompt message such as "Please provide suggestions to improve my current emotional state" is output, and the user receives appropriate countermeasures.

[0562] Step 6:

[0563] The server then saves the final user selection results back to the database for use in future analysis and optimization processes. By utilizing user interaction feedback for continuous improvement, it's possible to enhance the overall system performance.

[0564] (Application Example 2)

[0565] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0566] Conventional business support systems provide uniform support without considering the user's feelings or emotional state, which means they cannot adequately meet the individual needs of each user. Furthermore, because they cannot adjust work processes based on emotional states, they can lead to excessive stress and inefficient work operations.

[0567] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0568] This invention includes a server that trains a digital processing unit model using individual skills and knowledge and shares that digital processing unit model with others in the electrical space; a server that analyzes the user's emotional state, selects a digital processing unit model based on the analysis results, and adjusts the work process; and a server that utilizes the digital processing unit models of others to automate and streamline the work process. This enables optimal work support tailored to the user's emotional state, resulting in improved work efficiency and reduced stress.

[0569] "Individual skills and knowledge" refers to the unique abilities and information that an individual possesses, and is used in training the digital processing unit model.

[0570] A "digital processing unit model" refers to a program that runs on a computer or similar system, and is an algorithm trained to perform a specific task.

[0571] "Electrical space" refers to a computer network environment where digital information is exchanged and stored.

[0572] "Sharing with others" refers to making a trained digital processing unit model accessible to other users.

[0573] "User's emotional state" refers to the feelings and mental condition a user experiences at a particular time.

[0574] "Analysis" refers to the act of processing data to understand the emotional state of a user and deriving specific results or information.

[0575] "Adjusting the work process" refers to the act of changing the flow and procedures of work to the most optimal ones in accordance with the emotional state of the user.

[0576] "Automation and streamlining of business processes" refers to reducing manual operations and ensuring that tasks are performed with minimal time and effort.

[0577] The system that realizes this invention functions with the involvement of a server, terminals, and users. The server is responsible for training digital processing unit models based on the skills and knowledge of individual users and sharing those models with others in the electronic space. To analyze the user's emotional state, an emotion recognition engine is used, which processes voice and image data to understand the user's feelings in real time. The analyzed emotion data is then sent back to the server and used to select digital processing unit models and adjust work processes.

[0578] On the server, you can use "Microsoft Azure Emotion API" or "Amazon Rekognition" as your emotion recognition engine. These software programs can quickly process large amounts of emotion data and accurately determine the user's stress and relaxation levels. The processed emotion data serves as training data to optimize the algorithms of the digital processing unit model and provide the most effective work support for the user.

[0579] The device receives model and emotion data from the server and performs various actions on the user based on that information. For example, if the device analyzes that the user is feeling stressed, it may play relaxing music or adjust the room lighting to a calming level.

[0580] A concrete example would be a scenario where, upon returning home tired from work, the device starts playing "relaxing background music." In this case, a possible prompt message might be, "Please create a quiet environment so as not to distract you while you are concentrating on your work."

[0581] This invention enables more nuanced support tailored to the user's emotional state, leading to an expected improvement in the user experience.

[0582] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0583] Step 1:

[0584] The server collects skill and knowledge data provided by individual users. It then trains a digital processing model based on this data. The input is the user's skill and knowledge data, and the output is the trained digital processing model. This model includes algorithms optimized to support the user's specific tasks.

[0585] Step 2:

[0586] The server uses an emotion recognition engine to analyze the user's emotional state from audio and image input data. The input is the user's audio and image data, and the output is the analyzed emotional state data. The server processes this data in real time using the emotion recognition engine to identify the user's current emotional state.

[0587] Step 3:

[0588] The server selects the optimal digital processing model based on the analyzed emotional state data. The input is the user's emotional state data and a list of available models; the output is the selected model. The selected model provides the most appropriate work support for the user's current emotions.

[0589] Step 4:

[0590] The terminal receives a selected digital processing unit model and performs actions for the user based on that model. The input is the selected model, and the output is the performed action. The terminal makes suggestions based on the user's emotional state and takes specific actions, such as adjusting music or lighting.

[0591] Step 5:

[0592] Users utilize services provided by the terminal to obtain a comfortable work environment. User feedback is used to optimize the next digital processing unit model. The input is the services from the terminal, and the output is the user's work efficiency and stress reduction. Even if users do not provide direct feedback, sentiment data is saved as reference for selecting the next model.

[0593] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0594] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0595] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0596] [Fourth Embodiment]

[0597] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0598] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0599] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0600] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0601] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0602] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0603] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0604] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0605] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0606] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0607] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0608] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0609] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0610] The system according to the present invention generates a virtual computer model (hereinafter referred to as an AI agent) based on an individual's skills and knowledge, and makes it available in a virtual space, thereby providing an environment that can be used by others. This embodiment includes the processes of training, sharing, and using the AI ​​agent.

[0611] Server operation

[0612] The server registers user-generated AI agents within the virtual space. Here, the server receives the AI ​​agent's code and associated metadata (e.g., the agent's area of ​​expertise and intended use) and stores it in a database. After publication, the server manages the listing display to make it easier for other users to access those agents using the search function within the virtual space.

[0613] Terminal operation

[0614] The terminal provides the ability to search for and select AI agents through a user interface. Users retrieve AI agents from the server that meet their business needs and import them into the terminal. The terminal then uses these agents to automate specific business tasks. For example, to assist in creating marketing strategies, the terminal can deploy AI agents with appropriate marketing skills to help generate proposal materials.

[0615] User actions

[0616] Users prepare training data to model their expertise and use that data to customize an AI agent. The trained AI agent has the functionality to support specific business processes and tasks. Users publish the completed agent in a virtual space, making it available for use by other employees within the company. Furthermore, users can select AI agents created by other employees and use them to improve work efficiency and optimize processes.

[0617] Thus, the present invention provides a system and its embodiments for streamlining business processes while effectively utilizing individual knowledge and skills. Through mutual cooperation between servers, terminals, and users, knowledge sharing and business support are facilitated.

[0618] The following describes the processing flow.

[0619] Step 1:

[0620] Users collect their own expertise and skills as training data. This data is prepared for input into AI tools, and the necessary information is organized according to the nature of the work.

[0621] Step 2:

[0622] The user trains an AI agent based on training data to generate a model that aligns with their objectives. Here, the machine learning environment on the AI ​​system is used to fine-tune the algorithm, giving the agent the ability to perform specific tasks.

[0623] Step 3:

[0624] The user submits a registration request to the server for the completed AI agent. Based on the received data, the server saves the agent's metadata and code to a database and configures its public access settings within the virtual space.

[0625] Step 4:

[0626] The server displays and manages a list of publicly available AI agent information within the virtual space. This allows other users to easily search for and access available agents.

[0627] Step 5:

[0628] The terminal provides an AI agent search function via a user interface. Users select an AI agent based on their specific skills and objectives. Based on the selection, the terminal imports the appropriate agent from the server.

[0629] Step 6:

[0630] The device uses imported AI agents to perform and automate user-specified business processes. Examples include tasks such as data analysis, report generation, and schedule management.

[0631] Step 7:

[0632] Users evaluate the results of tasks performed by the AI ​​agent and provide feedback as needed to improve performance. This feedback may be used for subsequent training.

[0633] Through the steps described above, the system of the present invention enables the effective utilization of individual skills and knowledge and improves the efficiency of work.

[0634] (Example 1)

[0635] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0636] To facilitate information sharing and improve operational efficiency, there is a need for technology that provides an environment where individual expertise can be easily modeled and effectively shared with others.

[0637] In particular, there is a need for systems that enable the automation and optimization of business processes. In addition, there is a need for methods that allow users to select the most suitable computer model according to their individual needs and work content, and to maximize its utilization.

[0638] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0639] This invention includes a server that provides means for training a computer model based on an individual's expertise and sharing that model with others in an information space; means for selecting a computer model published in the information space and importing it into an information processing terminal to provide business support; means for utilizing the computer models of others to automate and optimize business procedures; means for creating prompt statements using a generated AI model and training an agent; and means for publishing the trained agent in a virtual space and managing an information list to make it easily accessible to others. This enables users to efficiently utilize their expertise and simultaneously achieve business process efficiency and knowledge sharing.

[0640] "Individual expertise" refers to a deep understanding and skills based on an individual's technical abilities and experience in a specific field.

[0641] A "computer model" is a computer program or algorithm built to perform a specific task based on data.

[0642] "Information space" refers to a virtual area where information is stored in digital format and can be accessed and manipulated by users.

[0643] An "information processing terminal" is a computing device used for inputting, processing, and outputting data, and includes personal computers and smartphones.

[0644] "Business support" refers to auxiliary functions and services provided to efficiently carry out specific tasks.

[0645] "Automating business procedures" means mechanizing processes to reduce manual operations by humans, thereby improving efficiency and accuracy.

[0646] "Optimization" is the process of adjusting a system or process to achieve the greatest effect under given conditions.

[0647] A "generative AI model" is an artificial intelligence system that learns patterns based on large amounts of data and generates output for new data.

[0648] A "prompt" is a form of instruction or question given to a generative AI model to elicit a specific output.

[0649] An "agent" is a software program designed to perform a specific task independently.

[0650] The system of this invention aims to generate AI agents, which are computer models based on an individual's expertise, and share them within a virtual space. This system functions with three main components: a server, a terminal, and a user.

[0651] First, the user digitizes their expertise and uses that data to train an AI agent using a generative AI model. The user creates a prompt sentence suitable for a specific purpose and inputs this prompt sentence into the generative AI model to generate an AI agent. As a concrete example, the user might create a prompt sentence such as, "Create an AI agent based on voice data to improve the sales process."

[0652] Next, the server receives the AI ​​agent code and associated metadata sent by the user. This metadata includes the agent's area of ​​expertise and intended use. The server stores this information in a database and then publishes the AI ​​agent in the virtual space. The published agents are managed by the server in an information list format, and care is taken to ensure that other users can easily access them.

[0653] The terminal navigates a virtual space through a user interface and provides functions for users to search for and select the necessary AI agents. The terminal has the ability to import selected agents from the server and utilize them for various business support purposes. For example, the terminal can use a marketing-adapted AI agent to assist in the automatic generation of materials proposing marketing strategies.

[0654] Through the above process, the system effectively models user expertise and provides an environment for automating and optimizing business processes. Furthermore, by utilizing the most suitable AI agent according to individual business needs within this environment, it is possible to promote the streamlining of business processes and the sharing of knowledge.

[0655] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0656] Step 1:

[0657] The user prepares their expertise as training data. Here, the user collects data related to specific tasks and organizes it in text, audio, or image format. The input includes existing business data and experience-based knowledge. This is then formatted into the form necessary for input into the generating AI model, resulting in a dataset that serves as the foundation for building the AI ​​agent.

[0658] Step 2:

[0659] The user creates a prompt and inputs it into a generative AI model to generate an AI agent. The input consists of the created prompt (e.g., "Create an AI agent based on voice data to improve the sales process.") and training data. The generative AI model trains the AI ​​agent based on this input and generates an AI agent that reflects expertise as output.

[0660] Step 3:

[0661] The server stores AI agents and their associated metadata received from users in a database. Input includes the AI ​​agent's code and metadata indicating its area of ​​expertise and intended use. The server combines and manages this information, then converts it into an output format that can be publicly shared in the virtual space.

[0662] Step 4:

[0663] The server exposes trained AI agents within a virtual space and manages a list of information accessible to other users. The input is the AI ​​agent data saved in the previous step. The server uses this data to configure access permissions and list displays, providing an environment where users can easily search for agents.

[0664] Step 5:

[0665] The terminal imports an AI agent selected from a virtual space via a user interface and uses it to support business operations. The input is information about the AI ​​agent chosen by the user. Based on this data, the terminal runs the agent in the execution environment and provides the user with functions that help improve work efficiency. Specifically, the agent automatically generates marketing strategy proposal materials, reducing work time.

[0666] (Application Example 1)

[0667] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0668] In modern cities, there is a need to efficiently solve various local problems while utilizing the individual expertise of residents. However, traditional methods lack sufficient mechanisms for effectively sharing individual knowledge and skills and putting them to practical use in problem-solving, thus necessitating more efficient and effective solutions.

[0669] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0670] This invention includes a server that provides means for training information processing models using individual skills and knowledge and sharing those information processing models with others in a virtual space; means for selecting publicly available information processing models in the virtual space, importing them into an information terminal, and providing business support; means for utilizing information processing models of others to automate and streamline business processes; and means for sharing information processing models within a community and using them to solve urban problems. This enables the efficient resolution of urban problems.

[0671] "Individual skills and knowledge" refers to the collection of specialized abilities and knowledge possessed by a particular person.

[0672] An "information processing model" is an artificial intelligence model built on an individual's skills and knowledge to analyze data and make decisions.

[0673] A "virtual space" is a simulation or virtual space on the internet that is generated using digital technology.

[0674] "Means of sharing with others" refers to methods for making certain information or technology accessible and usable by other users.

[0675] An "information terminal" refers to a device capable of processing and displaying digital information, specifically a smartphone or computer.

[0676] "Business support" refers to technical or knowledge-based assistance provided to efficiently carry out specific business activities.

[0677] "Automation" refers to the process of having machines or software perform tasks or processes that were previously done by humans.

[0678] "Efficiency improvement" means optimizing processes and methods to obtain the greatest possible results with limited resources.

[0679] A "community" is a group of people who share common interests or goals, and is a group associated with a particular region or field.

[0680] "Urban problem solving" refers to methods and means for resolving various social, environmental, and economic challenges that arise in cities.

[0681] The system for implementing this invention enables the generation and use of information processing models based on individual knowledge. Servers, terminals, and users each play their respective roles and work in coordination.

[0682] First, the server registers information processing models generated using an individual's skills and knowledge within a virtual space, making them accessible to others. To this end, the server uses a database such as Firebase Firestore to manage the model's code and metadata, displaying them as a searchable list. The server also controls user access and distributes the appropriate model to information terminals.

[0683] Next, users can access a virtual space using an information terminal equipped with a dedicated application, search for and select an information processing model that meets their needs. The selected model is downloaded to the information terminal and used to support business operations and solve urban problems. A concrete example would be an AI agent that assists in designing ecologically friendly transportation systems.

[0684] This application utilizes development environments such as Android Studio and Xcode and runs on information devices including smartphones and tablets. The information processing model is trained based on expertise provided by residents and is exposed to the virtual space via Firebase.

[0685] Furthermore, an example of a specific prompt that a user might use is, "Based on the following dataset, build an AI agent specializing in designing ecologically friendly transportation systems in urban areas." This prompt helps the information processing model provide the insights necessary to solve urban problems.

[0686] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0687] Step 1:

[0688] The server receives training data provided by the user and generates an information processing model. It receives training data and user skill information as input and constructs the information processing model using machine learning algorithms. The output is the information processing model registered in the virtual space.

[0689] Step 2:

[0690] The user accesses the virtual space using a dedicated application and searches for a list of publicly available information processing models. The user specifies search criteria (e.g., ecologically friendly) as input and retrieves the corresponding information processing models from the server. The output is a list of models displayed on the user's information terminal.

[0691] Step 3:

[0692] The user selects an appropriate information processing model and downloads it to their information terminal. The server encrypts and transmits the selected model, which is then decoded on the user's terminal and integrated into a business support application. The output is the integrated information processing model, ready for use in solving urban problems.

[0693] Step 4:

[0694] The information processing model executed on the terminal performs data calculations based on user prompts. It receives prompts as input and utilizes its internal knowledge to generate a predetermined analysis or proposal. The output might be, for example, a proposal for an optimal urban transportation plan.

[0695] Step 5:

[0696] The server collects user feedback and new data, and incorporates this information to improve the accuracy of the information processing model. It receives user feedback as input and retrains the model. The output is the improved new information processing model.

[0697] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0698] This invention combines a system that shares computer models (AI agents) based on individual skills and knowledge within a virtual space to enable business support and automation with an emotion engine that recognizes user emotions. In this configuration, the user's emotional state is analyzed in real time, enabling the adaptation and optimization of business processes based on that information.

[0699] Server operation

[0700] The server registers user-generated AI agents and emotion engines within the virtual space and manages the usage status of each agent. The server maintains a database for selecting agents and adjusting business processes based on user emotion data. It also utilizes the emotion analysis results obtained by the emotion engine as training data for AI agents, supporting the continuous optimization of the model.

[0701] Terminal operation

[0702] The terminal enhances user support through the collaboration of agents and an emotion engine. The terminal displays emotional data acquired from the emotion engine via the user interface and adjusts agent performance based on this information. It also provides a function to automatically select and import the appropriate AI agent according to the user's current emotional state. For example, if the user is experiencing stress, an agent specializing in stress reduction will be prioritized.

[0703] User actions

[0704] Users can utilize AI agents while considering their own emotional state. The agents work in conjunction with an emotion engine to automatically provide responses and handle tasks in a way that matches the user's mood. By selecting an agent based on their emotions, users can receive work support tailored to their individual needs. For example, if a project is deemed difficult to fulfill, an agent with optimization skills can be used to help resolve the project's challenges.

[0705] This invention enables a system that incorporates an emotion engine, expanding the possibilities for adapting to tasks based on the user's emotional state and further improving work efficiency. This mechanism provides users with a more comfortable and effective work environment.

[0706] The following describes the processing flow.

[0707] Step 1:

[0708] Users collect training data to generate AI agents tailored to their specific work needs. This data reflects the skills and knowledge required for particular tasks and operations.

[0709] Step 2:

[0710] Users train AI agents based on training data and register the models on the server. The trained AI agents have the ability to provide business support based on their skill sets.

[0711] Step 3:

[0712] The server stores registered AI agents and their metadata within a virtual space, making them accessible to other users when needed. The server also maintains the necessary infrastructure and databases to ensure the operation of the emotion engine.

[0713] Step 4:

[0714] The user activates the emotion engine in preparation for starting work. The emotion engine recognizes the user's emotional state in real time from their facial expressions, tone of voice, and input actions, and analyzes the data.

[0715] Step 5:

[0716] The emotion engine analyzes the user's emotions and displays the results on the device. Based on these results, the device selects a more supportive agent if the user is feeling stressed, and presents a more adaptable agent if work efficiency is declining.

[0717] Step 6:

[0718] The device selects an appropriate AI agent and imports it from the server into the device. The agent chosen is the one best suited to the user's emotional state.

[0719] Step 7:

[0720] The AI ​​agent starts operating on the device and provides instructions and work support tailored to the user's emotional state. This includes features such as making suggestions in a way that does not cause user dissatisfaction.

[0721] Step 8:

[0722] Users evaluate the AI ​​agent's performance and the support provided by the emotion engine, and provide feedback. The server uses this feedback to improve the performance of both the agent and the emotion engine.

[0723] As a result, advanced business support that adapts to the user's emotions becomes possible, and the present invention provides a more effective work environment.

[0724] (Example 2)

[0725] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0726] There is a need to provide an environment that effectively and efficiently utilizes individual skills and knowledge to support business operations using information processing equipment. However, current systems have the problem of not providing support optimized for individual needs because they do not take into account the emotional state of the user. In addition, selecting publicly available information processing equipment and adjusting it for different users is difficult, resulting in insufficient efficiency in business operations.

[0727] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0728] In this invention, the server includes means for training an information processing device using an individual's skills and knowledge and sharing that information processing device with others in a virtual space; means for analyzing the user's emotions and optimizing the information processing device based on the analysis results; and means for selecting an appropriate information processing device based on the analyzed emotional data and importing it to the terminal. This enables business support optimized for the user's emotional state, thereby achieving increased efficiency and automation of business processes.

[0729] "Skills" refer to the techniques and abilities necessary to effectively perform a specific task or job.

[0730] "Knowledge" is the understanding and memory of information acquired through education and experience, and is used for problem-solving and decision-making.

[0731] An "information processing device" is a device that includes computers and servers and is used for processing and analyzing data.

[0732] A "virtual space" is a computer simulation environment that does not have a physical existence and is constructed using digital technology.

[0733] "Emotion" refers to a person's feelings and mood, and is a concept that encompasses mental and psychological states such as joy, sadness, and stress.

[0734] "Analysis" is the act of breaking down data or events into smaller parts and then logically investigating and examining them to clarify their meaning and structure.

[0735] "Optimization" refers to adjusting a system or process to achieve maximum effectiveness and minimum cost under specific conditions.

[0736] A "terminal" refers to a device that connects to an information processing device and performs information input and output, and includes computers and smartphones.

[0737] "Import" refers to the operation of taking in data or information processing equipment from an external source, and adding new functions or information to a system or software.

[0738] This invention is a system for sharing information processing devices based on individual skills and knowledge within a virtual space to support users' work. Furthermore, it includes a function to analyze the user's emotions and optimize the information processing device based on the analysis results.

[0739] The server registers information processing devices created by individuals in a virtual space and manages them so that other users can share them. A common database system is used for this purpose. For example, MongoDB is used to manage and store data based on users' skills and knowledge.

[0740] The device captures the user's facial expressions and voice in real time and sends this data to an emotion analysis engine. It analyzes the user's emotions using facial recognition with OpenCV and a voice analysis API. Based on these analysis results, the operation of the information processing device is optimized to provide the user with the most suitable work support.

[0741] Users can review the content of their work support using the interface provided through their terminal and select options as needed. For example, if analysis reveals that the user is experiencing stress, the system will select an information processing device from the server that is effective in reducing stress, import it into the terminal, and use it. It is also possible to input prompts into the generating AI model to receive advice tailored to specific tasks. By entering prompts such as, "Please suggest ways to reduce the stress the user is currently experiencing," appropriate advice can be obtained.

[0742] This system enables flexible and effective work support tailored to the user's emotional state, thereby improving the efficiency of business processes.

[0743] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0744] Step 1:

[0745] The server registers the information processing devices trained by individuals in the virtual space. It receives data from the information processing devices entered by the user and stores this data in MongoDB. At this stage, the model based on the user's skills and knowledge is primarily managed. As a result, the virtual space is ready for others to access.

[0746] Step 2:

[0747] The device captures the user's facial expressions and voice in real time and inputs this data into an emotion analysis engine. OpenCV is used to analyze facial expressions from the video feed, and voice is processed by a voice analysis API. The output is the user's emotional state, which is sent to the server in JSON format. This information forms the basis for subsequent processing.

[0748] Step 3:

[0749] The server analyzes the received emotional state data and stores the information in a database. Machine learning algorithms are used in the analysis to compare the data with the user's past emotional history. As a result, a deeper understanding of the user's patterns is gained.

[0750] Step 4:

[0751] The terminal receives analysis results from the server and selects the appropriate information processing device based on them. Here, a Python script is used to perform the selection algorithmically. The appropriate information processing device is then presented to the user as output based on the input sentiment data and business needs.

[0752] Step 5:

[0753] The user reviews the presented information processing device and selects one as needed. The selected information processing device, through the user interface, can also send prompt messages to a generating AI model. A prompt message such as "Please provide suggestions to improve my current emotional state" is output, and the user receives appropriate countermeasures.

[0754] Step 6:

[0755] The server then saves the final user selection results back to the database for use in future analysis and optimization processes. By utilizing user interaction feedback for continuous improvement, it's possible to enhance the overall system performance.

[0756] (Application Example 2)

[0757] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0758] Conventional business support systems provide uniform support without considering the user's feelings or emotional state, which means they cannot adequately meet the individual needs of each user. Furthermore, because they cannot adjust work processes based on emotional states, they can lead to excessive stress and inefficient work operations.

[0759] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0760] This invention includes a server that trains a digital processing unit model using individual skills and knowledge and shares that digital processing unit model with others in the electrical space; a server that analyzes the user's emotional state, selects a digital processing unit model based on the analysis results, and adjusts the work process; and a server that utilizes the digital processing unit models of others to automate and streamline the work process. This enables optimal work support tailored to the user's emotional state, resulting in improved work efficiency and reduced stress.

[0761] "Individual skills and knowledge" refers to the unique abilities and information that an individual possesses, and is used in training the digital processing unit model.

[0762] A "digital processing unit model" refers to a program that runs on a computer or similar system, and is an algorithm trained to perform a specific task.

[0763] "Electrical space" refers to a computer network environment where digital information is exchanged and stored.

[0764] "Sharing with others" refers to making a trained digital processing unit model accessible to other users.

[0765] "User's emotional state" refers to the feelings and mental condition a user experiences at a particular time.

[0766] "Analysis" refers to the act of processing data to understand the emotional state of a user and deriving specific results or information.

[0767] "Adjusting the work process" refers to the act of changing the flow and procedures of work to the most optimal ones in accordance with the emotional state of the user.

[0768] "Automation and streamlining of business processes" refers to reducing manual operations and ensuring that tasks are performed with minimal time and effort.

[0769] The system that realizes this invention functions with the involvement of a server, terminals, and users. The server is responsible for training digital processing unit models based on the skills and knowledge of individual users and sharing those models with others in the electronic space. To analyze the user's emotional state, an emotion recognition engine is used, which processes voice and image data to understand the user's feelings in real time. The analyzed emotion data is then sent back to the server and used to select digital processing unit models and adjust work processes.

[0770] On the server, you can use "Microsoft Azure Emotion API" or "Amazon Rekognition" as your emotion recognition engine. These software programs can quickly process large amounts of emotion data and accurately determine the user's stress and relaxation levels. The processed emotion data serves as training data to optimize the algorithms of the digital processing unit model and provide the most effective work support for the user.

[0771] The device receives model and emotion data from the server and performs various actions on the user based on that information. For example, if the device analyzes that the user is feeling stressed, it may play relaxing music or adjust the room lighting to a calming level.

[0772] A concrete example would be a scenario where, upon returning home tired from work, the device starts playing "relaxing background music." In this case, a possible prompt message might be, "Please create a quiet environment so as not to distract you while you are concentrating on your work."

[0773] This invention enables more nuanced support tailored to the user's emotional state, leading to an expected improvement in the user experience.

[0774] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0775] Step 1:

[0776] The server collects skill and knowledge data provided by individual users. It then trains a digital processing model based on this data. The input is the user's skill and knowledge data, and the output is the trained digital processing model. This model includes algorithms optimized to support the user's specific tasks.

[0777] Step 2:

[0778] The server uses an emotion recognition engine to analyze the user's emotional state from audio and image input data. The input is the user's audio and image data, and the output is the analyzed emotional state data. The server processes this data in real time using the emotion recognition engine to identify the user's current emotional state.

[0779] Step 3:

[0780] The server selects the optimal digital processing model based on the analyzed emotional state data. The input is the user's emotional state data and a list of available models; the output is the selected model. The selected model provides the most appropriate work support for the user's current emotions.

[0781] Step 4:

[0782] The terminal receives a selected digital processing unit model and performs actions for the user based on that model. The input is the selected model, and the output is the performed action. The terminal makes suggestions based on the user's emotional state and takes specific actions, such as adjusting music or lighting.

[0783] Step 5:

[0784] Users utilize services provided by the terminal to obtain a comfortable work environment. User feedback is used to optimize the next digital processing unit model. The input is the services from the terminal, and the output is the user's work efficiency and stress reduction. Even if users do not provide direct feedback, sentiment data is saved as reference for selecting the next model.

[0785] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0786] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0787] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0788] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0789] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0790] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0791] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0792] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0793] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0794] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0795] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0796] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0797] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0798] 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.

[0799] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0800] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0801] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0802] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0803] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0804] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0805] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0806] The following is further disclosed regarding the embodiments described above.

[0807] (Claim 1)

[0808] A means of training computer models using individual skills and knowledge, and sharing those computer models with others in a virtual space,

[0809] A means of selecting a computer model published in a virtual space, importing it into the user's terminal, and using it to support business operations.

[0810] A means of automating and streamlining business processes by utilizing computer models from others,

[0811] A system that includes this.

[0812] (Claim 2)

[0813] The system according to claim 1, characterized by including means for managing the publication of computer models in a virtual space and controlling user access.

[0814] (Claim 3)

[0815] The system according to claim 1, characterized by having an algorithm for selecting different computer models according to the user and adapting them to specific business needs.

[0816] "Example 1"

[0817] (Claim 1)

[0818] A means of training computer models based on individual expertise and sharing those models with others in the information space,

[0819] A means of selecting a computer model published in the information space, importing it into an information processing terminal, and providing business support,

[0820] A means of automating and optimizing business procedures by utilizing computer models from others,

[0821] A method for creating prompt sentences using a generative AI model and training an agent,

[0822] A means of making trained agents publicly available in a virtual space and managing a list of their information so that others can easily access it,

[0823] A system that includes this.

[0824] (Claim 2)

[0825] The system according to claim 1, characterized by including means for managing the publication of computer models within an information space and controlling user access.

[0826] (Claim 3)

[0827] The system according to claim 1, characterized by having an algorithm for selecting different computer models according to the user and adapting them to specific business needs.

[0828] "Application Example 1"

[0829] (Claim 1)

[0830] A means of training an information processing model using an individual's skills and knowledge, and sharing that information processing model with others in a virtual space,

[0831] A means of selecting an information processing model published in a virtual space, importing it into an information terminal, and using it to support business operations,

[0832] A means of automating and streamlining business processes by utilizing the information processing models of others,

[0833] A means of sharing information processing models within a community and using them to solve urban problems,

[0834] A system that includes this.

[0835] (Claim 2)

[0836] The system according to claim 1, characterized by including means for managing the publication of information processing models within a virtual space and controlling user access.

[0837] (Claim 3)

[0838] The system according to claim 1, characterized by having a method for selecting different information processing models according to the user and adapting them to specific business needs.

[0839] "Example 2 of combining an emotion engine"

[0840] (Claim 1)

[0841] A means of training an information processing device using an individual's skills and knowledge, and sharing that information processing device with others in a virtual space,

[0842] A means of selecting an information processing device made publicly available in a virtual space, importing it into the user's terminal, and providing business support,

[0843] A means of automating and streamlining business processes by utilizing information processing equipment from other parties,

[0844] A means for analyzing the user's emotions and optimizing the information processing device based on the analysis results,

[0845] A means for selecting an appropriate information processing device based on the analyzed emotional data and importing it into a terminal,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, characterized by including means for managing the public access of information processing devices within a virtual space and controlling user access.

[0849] (Claim 3)

[0850] The system according to claim 1, characterized in that it includes a calculation procedure for selecting different information processing devices according to the user and adapting them to specific business needs.

[0851] "Application example 2 when combining with an emotional engine"

[0852] (Claim 1)

[0853] A means of training a digital processing unit model using individual skills and knowledge, and sharing that digital processing unit model with others in the electrical space,

[0854] A means of selecting a digital processing device model published in the electrical space, importing it into an information processing terminal, and supporting business operations.

[0855] A means of automating and streamlining business processes by utilizing the digital processing unit models of others,

[0856] A means of analyzing the user's emotional state, selecting a digital processing unit model based on the analysis results, and adjusting the work process,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, characterized by including means for managing the disclosure of digital processing device models in electrical space and controlling user access.

[0860] (Claim 3)

[0861] The system according to claim 1, characterized in that it selects different digital processing unit models according to the user, has calculation procedures to adapt to specific business requirements, and further utilizes analysis results based on the user's emotional state to provide appropriate support. [Explanation of symbols]

[0862] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of training computer models using individual skills and knowledge, and sharing those computer models with others in a virtual space, A means of selecting a computer model published in a virtual space, importing it into the user's terminal, and using it to support business operations. A means of automating and streamlining business processes by utilizing computer models from others, A system that includes this.

2. The system according to claim 1, characterized by including means for managing the publication of computer models in a virtual space and controlling user access.

3. The system according to claim 1, characterized in that it includes an algorithm for selecting different computer models according to the user and adapting them to specific business needs.

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