system

Abstract

Provide a system. 【Solution means】 Means for inputting the knowledge and ability of employees, Means for generating an artificial intelligence agent based on the input knowledge and ability, Means for creating an avatar that visually represents the generated artificial intelligence agent, Means for publishing the created avatar in a virtual space, Means for other employees to select the published artificial intelligence agent and resident it on their work terminals, Means for the work terminal to assist in business using the artificial intelligence agent, Means for collecting and storing the preference information of users, Means for the artificial intelligence agent to provide product information based on the collected preference information, A system including the above.

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, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern enterprises, the specialized knowledge and skills possessed by employees are often accumulated individually, and it is difficult for other employees to effectively utilize them. In addition, the complexity of sharing specialized knowledge and the shortage of personnel in efficient business operations have become problems. In such a situation, sharing of specialized knowledge and immediate utilization of technologies are required.

Means for Solving the Problems

[0005] This invention solves the above problem by providing a system that allows employees to reflect their own knowledge and abilities in an artificial intelligence agent and publish that agent as a visually represented avatar in a virtual space. This system provides a means for other employees to select an AI agent as needed and keep it resident on their work terminal, thereby realizing effective sharing of specialized knowledge and efficient support in performing work. Specifically, it includes various means that enable knowledge input and agent generation, avatarization and publication, and agent selection and use.

[0006] An "employee" refers to an individual who belongs to a company or organization and performs their duties with specialized knowledge and skills.

[0007] "Knowledge" refers to the system of information and understanding that employees possess in performing their duties and in their areas of expertise.

[0008] "Ability" refers to the skills and abilities that an employee possesses to perform specific tasks or duties.

[0009] An "artificial intelligence agent" refers to software that is programmed to autonomously perform tasks or act based on instructions.

[0010] An "avatar" refers to a graphical character used to visually represent an artificial intelligence agent in a virtual space.

[0011] A "virtual space" refers to a shared, computer-generated environment built on a digital network.

[0012] "Work terminals" refer to computers and devices that employees use on a daily basis to perform their work.

[0013] "Public" refers to the act of making specific information or resources accessible to other employees.

[0014] "Resident" refers to the state in which a specific software or program continuously operates on a work terminal.

[0015] "Assist in business" refers to providing support or assistance to make the performance of business more efficient.

Brief Description of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 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 Example 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

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] 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 a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] 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.

[0021] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention is a system designed to facilitate knowledge sharing and improve work efficiency among employees within a company. Each employee inputs their own expertise and skills, and an artificial intelligence agent is generated based on this input. This agent is then avatarized and made public in a virtual space. Other employees can select a publicly available agent and use it on their own work terminals.

[0038] User input of knowledge and skills

[0039] Users can input their individual knowledge and skills using a dedicated interface. The interface is intuitive and supports text input, multimedia uploads, and even the import of existing deliverables.

[0040] Generation of AI agents on the server

[0041] The server analyzes data received from the user and generates an artificial intelligence agent. Natural language processing technology is utilized to ensure that the input knowledge effectively functions as the agent. The agent is customized to reflect the user's expertise and conform to the company's specific specifications.

[0042] Agent avatarization and public release

[0043] The server assigns an avatar to the AI ​​agent. The avatar can be designed according to the employee's preferences and can be viewed by other employees in the virtual space.

[0044] User selection and utilization of AI agents

[0045] Other users access the virtual space and select the necessary agents from several publicly available agents. They install the selected agent on their work terminal and use it to assist with their tasks. The artificial intelligence agent supports users in solving problems and streamlining tasks that arise during their work.

[0046] Specific example

[0047] For example, if user A inputs discussion techniques in the sales field, the server develops an AI agent based on this information, creates an avatar of the agent, and makes it publicly available. Another user B can select this agent and integrate it into their work terminal, allowing them to receive the knowledge necessary for their sales activities from the agent. In this way, specialized knowledge is efficiently shared among employees, contributing to improved productivity throughout the company.

[0048] This system plays a crucial role in enhancing a company's competitiveness by enabling the sharing of specific knowledge and the smooth execution of tasks. In this way, it achieves the rapid response capabilities and improved efficiency required in today's information society.

[0049] The following describes the processing flow.

[0050] Step 1:

[0051] Users access a dedicated interface and input information about their knowledge and skills. Input methods include text input, speech recognition, and file uploads. After reviewing the information, users submit it.

[0052] Step 2:

[0053] The server receives information sent by the user and analyzes its content using natural language processing. The analysis then evaluates the importance and relevance of the information.

[0054] Step 3:

[0055] Based on the analysis results, the server generates an artificial intelligence agent that reflects the user's knowledge and skills. The agent's profile is configured with functions and characteristics that match the user's expertise.

[0056] Step 4:

[0057] The server automatically generates avatars to visualize the AI ​​agents that have been created. These avatars are customizable and designed according to the user's preferences.

[0058] Step 5:

[0059] The server publishes the completed avatar to the virtual public space. The agent list is then updated so that other employees can access it.

[0060] Step 6:

[0061] Users (other employees) access a virtual public space to search for and select the AI ​​agent they need for their work. The selection is made after reviewing the agent's description and evaluation.

[0062] Step 7:

[0063] The user downloads and installs the selected AI agent on their work terminal. After installation, the agent resides on the terminal and begins providing work support.

[0064] Step 8:

[0065] The terminal uses a resident AI agent to assist users with their work activities in real time. Based on specific instructions, the agent provides decision support and performs tasks on their behalf.

[0066] Step 9:

[0067] The server periodically collects agent usage data to inform improvements and updates. Feedback is used to enhance the performance of the AI ​​agent.

[0068] (Example 1)

[0069] 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."

[0070] Insufficient sharing of specialized knowledge and skills within a company can lead to decreased work efficiency for individual members. Furthermore, traditional systems often struggle to generate and implement intelligent entities tailored to individual needs, resulting in inefficient support. Therefore, there is a need to effectively and quickly share the knowledge and skills of team members to streamline operations.

[0071] 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.

[0072] In this invention, the server includes means for inputting the specialized knowledge and skills of its members, means for generating an intelligent entity based on the input specialized knowledge and skills, and means for a computer terminal to use the intelligent entity to assist in its work. This enables effective information sharing within the company and improves the work efficiency of each member.

[0073] "Member" refers to an individual who performs duties as part of a company or organization.

[0074] "Specialized knowledge" refers to information based on advanced information and skills in a specific field.

[0075] "Skills" refer to specific and practical abilities required to perform particular tasks or roles.

[0076] An "intelligent entity" refers to an artificial knowledge-based program or system that is generated based on the specialized knowledge and skills input by its members.

[0077] A "virtual personality" refers to a digital character or avatar created to visually represent an intelligent entity.

[0078] "Digital space" refers to a virtual environment created on a computer, which is accessible via a network.

[0079] A "computer terminal" refers to a digital device that a user can directly operate, and includes personal computers and tablets.

[0080] The embodiment of this invention relates to a system that facilitates the sharing of specialized knowledge and skills among members of a company to improve operational efficiency. This system primarily consists of three elements: a server, terminals, and users.

[0081] The server generates an intelligent entity based on the specialized knowledge and skills collected from its members. This process utilizes natural language processing technology to ensure that the input information is effectively used as the intelligent entity's function. A generative AI model is used to create an intelligent entity that reflects the expertise of each member. The generated intelligent entity is visualized as a virtual personality and made public in the digital space.

[0082] The terminal can access the digital space and select and install necessary virtual personalities from publicly available ones. Users use the installed AI entities on this terminal as work aids. These AI entities provide real-time support for problem-solving and task efficiency during work.

[0083] For example, if a user inputs discussion techniques for a specific sales area, the server uses this information to develop a relevant intelligence and publishes a visually represented virtual personality. Other users can then install this virtual personality on their devices to practically utilize the knowledge gained for sales activities.

[0084] As a concrete example of its use, the following prompt sentences can be provided to the AI ​​model:

[0085] "Please describe your area of ​​expertise. Also, please list specific skills and knowledge that are useful in that area."

[0086] In this way, efficient sharing of expertise among members and improvement of work efficiency are achieved.

[0087] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0088] Step 1:

[0089] Users input their professional knowledge and skills using a dedicated interface. Input includes written descriptions using text forms and uploading image and video files. The process is completed when the entered data is sent to the server. The server organizes the received data according to a specified format and stores it in a database.

[0090] Step 2:

[0091] The server performs natural language processing on user input data stored in the database. Specifically, it analyzes input text and extracts important themes and concepts. For image data, it performs visual information analysis and extracts relevant keywords. The information obtained here is used as the basis for generating intelligent entities. The output is organized information that reflects each user's expertise.

[0092] Step 3:

[0093] The server uses a generative AI model to generate an intelligent entity based on the analyzed information. During this process, extracted themes and skills are efficiently incorporated into the intelligent entity's response patterns. The final output is an intelligent entity that reflects the user's expertise. This intelligent entity can function effectively in specific tasks and scenarios.

[0094] Step 4:

[0095] The server assigns a virtual personality, a visual character, to the generated intelligent entity. The design of the virtual personality is customized based on user instructions and company guidelines. The completed virtual personality is uploaded to the digital space and made public. The output is a visually verifiable virtual personality.

[0096] Step 5:

[0097] Other users of the terminal can access the digital space and browse the publicly available virtual personalities. They then select the virtual personality necessary for their work and install it on their terminal. The selected virtual personality is downloaded to the terminal and becomes available through the interface. Once installed, the intelligent entity enters a standby state to support the user's daily tasks.

[0098] Step 6:

[0099] Users streamline their work by utilizing an intelligent system installed on their device. Specifically, the intelligent system provides real-time solutions to work problems the user faces and supports their work processes. The intelligent system has the functionality to improve the user's work efficiency and increase productivity. As an output, the user's work becomes more efficient, and the results are fed back as numerical data and evaluations.

[0100] (Application Example 1)

[0101] 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."

[0102] In today's information society, knowledge sharing and operational efficiency within companies and stores are essential. However, effectively integrating individual knowledge and preferences and providing information optimized for each user remains challenging. Furthermore, while there is a demand for personalized product information tailored to user needs and preferences, methods for achieving this are limited. Solving these problems and providing efficient operational support and an engaging user experience is crucial.

[0103] 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.

[0104] In this invention, the server includes means for inputting employees' knowledge and abilities, means for generating artificial intelligence agents based on the inputted knowledge and abilities, and means for collecting and storing user preference information. This enables knowledge sharing and operational efficiency within the company, as well as allowing customers to receive product information tailored to their individual preferences.

[0105] The term "employee" refers to an individual who belongs to an organization and performs specific duties or roles.

[0106] "Knowledge" refers to understanding and perception gained from information and experience, and includes all of an individual's specialized knowledge.

[0107] "Ability" refers to the skills, techniques, and aptitudes necessary to perform specific tasks or duties, and indicates an individual's capabilities.

[0108] An "artificial intelligence agent" refers to a software program designed to autonomously make decisions based on input information and assist in business operations.

[0109] An "avatar" refers to a digital icon or character used to visually represent an artificial intelligence agent in a virtual space.

[0110] A "virtual space" refers to a three-dimensional digital environment simulated on a computer, an area that users can access through an interface.

[0111] A "work terminal" refers to a computer or device used by a user to process work tasks or information.

[0112] "Preference information" refers to data about a specific user's preferences and interests, and is used to address individualized needs.

[0113] "Product information" refers to detailed information about a product, including price, specifications, performance, and usage instructions.

[0114] This system is designed to facilitate knowledge sharing and improve operational efficiency within a company, and to provide users with personalized product information. Its main components include an interface for inputting employee knowledge and skills, a server for generating artificial intelligence agents, and a platform for creating avatars that visually represent the agents.

[0115] The server uses Python and a natural language processing library (NLTK) to analyze the knowledge and abilities of the input employees. The analyzed data is passed to a generative AI model, which creates an artificial intelligence agent optimized for each piece of knowledge. Furthermore, this AI agent is visualized as an avatar in a virtual space using Unity.

[0116] Users (employees) can input their knowledge, skills, or market preference information using a dedicated interface. This information is sent to the server and forms the basis of the AI ​​agent generation process. In addition, the server utilizes the preference information to select and provide information tailored to each individual user, enabling the presentation of product information desired by the user's customers.

[0117] For example, if an employee inputs sales technique and preference information, an AI agent based on that information can be used by other employees in their sales activities. It can also suggest related new products based on products a customer has purchased in the past.

[0118] Examples of prompts from this system include, "Based on the electronic devices this customer has purchased in the past, what new products should we recommend?" and "Use your employees' sales techniques to provide advice on how to improve the closing rate."

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] Users input their knowledge and skills, or customer preference information, using a dedicated interface. This information is sent from the terminal to the server. Inputs include text data and past purchase history, and the output is an organized dataset.

[0122] Step 2:

[0123] The server uses a natural language processing library (NLTK) to process the received knowledge and preference information. In this step, the input data is classified by theme and keyword, and is ready to be used as parameters for the AI ​​generation model.

[0124] Step 3:

[0125] The server generates an artificial intelligence agent using a generative AI model based on the analyzed data. This process creates an AI agent that provides recommendation information based on input knowledge and customer preferences. The resulting agent functions as a business support algorithm.

[0126] Step 4:

[0127] The server uses Unity to create a visual avatar for the generated AI agent. This gives the agent a visually identifiable form when selected by other users in the virtual space. At this stage, the input is the generated AI agent, and the output is the avatarized digital character.

[0128] Step 5:

[0129] Users access a virtual space and select an AI agent that best suits their needs from among several publicly available agents. This selection is made on the terminal, and the selected agent resides permanently on the user's work terminal.

[0130] Step 6:

[0131] The terminal utilizes a resident AI agent to assist with tasks. The terminal presents recommended information and product information from the AI ​​agent, allowing users to receive suggestions for new tasks. The output consists of specific advice and product suggestions to streamline the user's tasks.

[0132] 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.

[0133] The system of this invention promotes knowledge sharing and operational efficiency within a company by reflecting employees' knowledge and abilities in an artificial intelligence agent. Furthermore, by combining this with an emotion engine, the system recognizes the user's emotional state and provides dynamic work support accordingly.

[0134] User input of knowledge and skills

[0135] Users can input their knowledge and skills through a dedicated interface. The interface supports text and voice input and allows for intuitive operation to enhance user convenience.

[0136] Generation of AI agents on the server

[0137] The server analyzes the data received from the user and understands the input using natural language processing technology. Based on this analysis, an artificial intelligence agent is generated that reflects the user's expertise. The agent is optimized for each individual user and responds to specific business needs.

[0138] Utilizing the Emotion Engine

[0139] The generated AI agent incorporates emotion recognition capabilities. The server analyzes the user's voice and text and uses an emotion engine to evaluate their emotional state. Based on this information, the agent autonomously adjusts its responses and level of support.

[0140] Agent avatarization and public release

[0141] The server generates avatars for the AI ​​agent and publishes them in the virtual space in a visually recognizable format for users and other employees. The avatars are customizable and can be designed to meet the user's requirements.

[0142] User selection and utilization of agents

[0143] Other users can select agents made available through the virtual space, install them on their work terminals, and use them in their daily tasks. Because they receive personalized support tailored to their individual needs, it's possible to further improve work productivity.

[0144] Specific example

[0145] For example, if User C is performing coordination tasks in a department that is causing them stress, the AI ​​agent uses its emotion engine to assess User C's emotions. Based on the emotion data obtained by the server, the agent suggests relaxing music and helps revise task priorities. This allows User C to perform their tasks efficiently while reducing their mental burden.

[0146] This system contributes to improving employees' work-life balance and the company's work environment by providing dynamic support based on emotion recognition.

[0147] The following describes the processing flow.

[0148] Step 1:

[0149] Users log in to a dedicated interface and input their expertise and skills via text and voice. This interface is designed to be user-friendly, allowing for concise input of complex knowledge.

[0150] Step 2:

[0151] The server receives data sent by the user and analyzes its content using natural language processing tools. The analysis identifies the user's knowledge domain and uses that information to create a profile for the AI ​​agent.

[0152] Step 3:

[0153] The server develops an AI agent based on the generated profile. This agent is designed to maximize the user's expertise and has the ability to adjust its response to specific tasks.

[0154] Step 4:

[0155] The server uses an emotion engine to add user emotion recognition capabilities to the agent. This capability analyzes the user's voice and text data to identify their emotional state.

[0156] Step 5:

[0157] The server generates an avatar that visually represents the AI ​​agent and applies the design chosen by the user. This avatar is then made public within the virtual space.

[0158] Step 6:

[0159] The user (or another employee) accesses the virtual space and selects which AI agent is needed. The selection is made after reviewing the agent's overview and evaluation information.

[0160] Step 7:

[0161] The user downloads the selected AI agent to their work terminal and completes the installation. After installation, the agent immediately begins operating on the terminal.

[0162] Step 8:

[0163] The terminal utilizes a resident agent to provide users with support for improving work efficiency and dynamic support tailored to their emotional state. Specific support includes suggestions based on emotional data and task prioritization.

[0164] Step 9:

[0165] The server regularly monitors agent usage and sentiment data, and uses the analysis results to update and improve the agents. This makes it possible to continuously provide optimized support to individual users.

[0166] (Example 2)

[0167] 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".

[0168] In modern businesses, effectively sharing the expertise and skills of team members and using that knowledge to streamline operations is crucial. However, traditional methods have struggled to accurately reflect each member's knowledge and perspectives and provide dynamic work support accordingly. Furthermore, there has been a lack of appropriate means to visually represent knowledge and abilities and promote collaboration among team members. This has resulted in limitations on knowledge sharing and improvements in work efficiency.

[0169] 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.

[0170] In this invention, the server includes means for inputting the expertise and skills of its members, means for generating an agent with learning capabilities based on the input expertise and skills, and means for performing emotion analysis on the generated agent and adjusting its behavior based on its state. This enables business support that takes into account the expertise and emotional state of its members.

[0171] "Members" refer to individual members who belong to an organization or group and contribute to its activities.

[0172] "Specialized knowledge" refers to a body of knowledge that has been deeply understood and acquired in relation to a specific field or job.

[0173] "Technology" refers to methods and skills used to achieve a specific purpose.

[0174] "Input means" refers to operations or devices used to supply information to a system.

[0175] An "agent with learning capabilities" refers to software that can analyze data and use that data to make autonomous decisions and perform tasks.

[0176] "Emotional analysis" refers to the process of collecting human emotions as data and evaluating those emotional states.

[0177] "Adjusting the operation" refers to optimizing the system's functions and responses according to the input data and circumstances.

[0178] "Visual elements" refer to visual media used to visually represent information or concepts.

[0179] A "virtual environment" refers to a digital space created using computers that mimics the real world.

[0180] "Work equipment" refers to devices or systems used to perform tasks or work.

[0181] This invention provides a system for sharing the expertise and skills of employees within a company and improving operational efficiency. To achieve this, it is primarily constructed using the following procedure.

[0182] Users communicate their expertise and skills to the system using a dedicated input device. The input device supports both text and voice input, allowing users to intuitively input information. For example, a user might input, "I have project management know-how."

[0183] The server analyzes information received from the user with high accuracy. The analysis uses Python as the programming language and leverages automated language processing libraries (e.g., spaCy). The server analyzes the input data, identifies keywords including "project management," and generates a learning agent. This agent is customized based on the user's expertise to support their work.

[0184] Next, the server collects the user's voice and text in real time and performs sentiment analysis. This analysis uses a sentiment recognition engine (e.g., IBM Watson® ToneAnalyzer) to evaluate the user's emotional state. Based on the sentiment data, the server adjusts the agent's behavior to provide assistance tailored to the user's needs.

[0185] Furthermore, the server adds visual elements to the generated agents. A 3D development platform (e.g., Unity) is used for this purpose, effectively creating visual elements within the virtual environment. These visual elements are customizable and can be shared with other members within the virtual environment.

[0186] Other users can select agents published in a virtual environment and utilize them on their own work devices. For example, they can improve work efficiency by sensing the user's emotions and providing appropriate support, such as "suggesting a short break to reduce stress."

[0187] An example of a prompt message might be, "The user is currently experiencing stress; please suggest ways to relax." This system utilizes a generative AI model and prompt messages to provide dynamic business support.

[0188] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0189] Step 1:

[0190] The user inputs their expertise and skills in text or voice using a dedicated input device. For example, they might input "I have experience in marketing analysis." The input data at this stage is information about the user's expertise and skills. The terminal formats this input data and sends it to the server.

[0191] Step 2:

[0192] The server receives user input data sent from the terminal and analyzes the data using a natural language processing library (e.g., spaCy). This extracts information about key concepts and technologies. For example, "marketing analytics" might be identified as a specialty. The output of the processing is the basic data needed to generate agents.

[0193] Step 3:

[0194] The server generates an agent with learning capabilities based on the extracted data. This agent utilizes the generated AI model to customize it to the user's expertise. The output is an agent specifically tailored to the user's business needs.

[0195] Step 4:

[0196] The server collects emotional data in real time from the user's voice and text, and evaluates their emotional state using an emotional analysis engine (e.g., IBM Watson Tone Analyzer). The input is voice or text data, and the output is the evaluation result of the user's emotional state. Based on this evaluation result, the agent dynamically adjusts its response and the level of support provided.

[0197] Step 5:

[0198] The server adds visual elements to the generated agents and places them in a virtual environment using a 3D development platform such as Unity. The input at this stage is configuration information regarding the agent's expertise and design. The output is a visually recognizable agent within the virtual environment.

[0199] Step 6:

[0200] Users select agents published in a virtual environment and install them on their work devices. This selection process filters the agents best suited to the user's tasks. Once selected, the agents assist the user's work on the work device, providing notifications and recommendations. The output is increased productivity through the agents' work support.

[0201] (Application Example 2)

[0202] 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".

[0203] In modern workplace and home environments, there is an increasing need for dynamic support based on individual knowledge, skills, and emotional states. However, conventional systems primarily rely on the reuse of static knowledge, making it difficult to respond flexibly while considering individual emotional states. Therefore, there is a demand for efficient support for work and daily life that reduces emotional burden.

[0204] 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.

[0205] In this invention, the server includes means for inputting the user's knowledge and skills, means for generating an intelligent agent based on the input knowledge and skills, and means for evaluating the user's emotional state using emotion recognition technology. This makes it possible to provide the user with dynamic support that takes both knowledge and emotions into consideration.

[0206] A "user" is an individual or group that uses the system to input knowledge and skills and receives support as a result.

[0207] "Knowledge" refers to the information and understanding that users possess, and is provided to the system through input terminals.

[0208] "Skills" refer to the practical abilities and techniques possessed by users, and are used for analysis by the system.

[0209] An "intelligent agent" is an artificial intelligence program that is generated based on the user's knowledge and skills, and provides dynamic support.

[0210] A "display character" is a virtual representation created to visually represent the generated intelligent agent.

[0211] A "virtual space" is a virtual area constructed within a digital environment, and it is the place where display characters are made public.

[0212] A "processing terminal" is a computer or electronic device used by a user, which is a device that houses an intelligent agent to provide support.

[0213] "Emotion recognition technology" refers to a technical method that analyzes a user's voice and text data to evaluate their emotional state.

[0214] To implement this invention, the cooperation of a server, terminal, and user is primarily required. First, the user utilizes a dedicated interface to input knowledge and skills. This interface supports various input formats, such as text and voice, and allows for intuitive operation. This enables the user to easily provide their expertise and experience to the system.

[0215] The server analyzes the received data using natural language processing technology. It then generates a customized intelligent agent based on the user's input. This agent incorporates emotion recognition technology, enabling it to evaluate the user's emotional state from the input voice and text. The generated agent is visually represented and displayed as a character within the virtual space.

[0216] The processing terminal serves as a platform for keeping this intelligent agent resident. On the terminal, the intelligent agent can dynamically provide support that takes into account the user's emotional state. For example, if the user is feeling stressed, the intelligent agent can suggest relaxing music.

[0217] As a concrete example, consider a support robot for use in the home. This robot can automatically adjust schedules and play music for relaxation based on the user's emotions and daily life circumstances. This entire process is provided seamlessly through the cooperation of a server and an agent.

[0218] An example of a prompt in a generative AI model might be: "Come up with an idea for a home support robot that suggests relaxing music when residents are stressed and readjusts their schedule priorities."

[0219] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0220] Step 1:

[0221] Users input their knowledge and skills as text or voice using a dedicated interface. The interface collects the input data and sends it to the server. This input consists of the user's expertise and technical information, which is then analyzed in subsequent processing.

[0222] Step 2:

[0223] The server receives the transmitted input data. Here, natural language processing techniques are used to analyze the data and understand the user's knowledge and skills. Through this analysis, the data is structured and used as foundational information for agent generation. The output of this analysis is digital information with unique characteristics for each user.

[0224] Step 3:

[0225] The server generates an intelligent agent based on the analysis results. This agent reflects the analyzed knowledge and skills and is optimized to meet specific business needs. In this process, the agent's operational guidelines are defined and emotion recognition technology is incorporated.

[0226] Step 4:

[0227] A display character is created to visually represent the generated intelligent agent. The server designs this character in a customizable format so that it can be easily recognized by the user or other users in the virtual space. The output here is executable display character data.

[0228] Step 5:

[0229] The server exposes the generated agent's display character to a virtual space. Other users can access the agent through this virtual space. This virtual space provides the agent's active area of ​​activity and forms the basis for interaction.

[0230] Step 6:

[0231] The terminal selects an intelligent agent exposed in the virtual space and makes it reside there. The terminal then downloads the agent and integrates it into its hardware environment. The agent runs on the terminal and is ready to support the user with their daily tasks.

[0232] Step 7:

[0233] The agent uses emotion recognition technology to assess the user's emotional state in real time. Through voice and text analysis, it quantifies the current emotional state and determines what kind of support is needed based on that data. The output here is evaluation data indicating the emotional state.

[0234] Step 8:

[0235] The agent dynamically adjusts its support based on the user's emotional state. For example, if it detects stress, it will suggest relaxing music. Through this action, the agent alleviates the user's mental burden and improves their efficiency in work and daily life. An example of a prompt using a generative AI model is: "Think of an idea for a home support robot that suggests relaxing music when residents are stressed and readjusts their schedule priorities."

[0236] 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.

[0237] Data generation model 58 is a type of 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.

[0238] 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.

[0239] [Second Embodiment]

[0240] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0241] 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.

[0242] 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).

[0243] 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.

[0244] 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.

[0245] 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).

[0246] 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.

[0247] 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.

[0248] 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.

[0249] 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.

[0250] 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.

[0251] 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".

[0252] This invention is a system designed to facilitate knowledge sharing and improve work efficiency among employees within a company. Each employee inputs their own expertise and skills, and an artificial intelligence agent is generated based on this input. This agent is then avatarized and made public in a virtual space. Other employees can select a publicly available agent and use it on their own work terminals.

[0253] User input of knowledge and skills

[0254] Users can input their individual knowledge and skills using a dedicated interface. The interface is intuitive and supports text input, multimedia uploads, and even the import of existing deliverables.

[0255] Generation of AI agents on the server

[0256] The server analyzes data received from the user and generates an artificial intelligence agent. Natural language processing technology is utilized to ensure that the input knowledge effectively functions as the agent. The agent is customized to reflect the user's expertise and conform to the company's specific specifications.

[0257] Agent avatarization and public release

[0258] The server assigns an avatar to the AI ​​agent. The avatar can be designed according to the employee's preferences and can be viewed by other employees in the virtual space.

[0259] User selection and utilization of AI agents

[0260] Other users access the virtual space and select the necessary agents from several publicly available agents. They install the selected agent on their work terminal and use it to assist with their tasks. The artificial intelligence agent supports users in solving problems and streamlining tasks that arise during their work.

[0261] Specific example

[0262] For example, if user A inputs discussion techniques in the sales field, the server develops an AI agent based on this information, creates an avatar of the agent, and makes it publicly available. Another user B can select this agent and integrate it into their work terminal, allowing them to receive the knowledge necessary for their sales activities from the agent. In this way, specialized knowledge is efficiently shared among employees, contributing to improved productivity throughout the company.

[0263] This system plays a crucial role in enhancing a company's competitiveness by enabling the sharing of specific knowledge and the smooth execution of tasks. In this way, it achieves the rapid response capabilities and improved efficiency required in today's information society.

[0264] The following describes the processing flow.

[0265] Step 1:

[0266] Users access a dedicated interface and input information about their knowledge and skills. Input methods include text input, speech recognition, and file uploads. After reviewing the information, users submit it.

[0267] Step 2:

[0268] The server receives information sent by the user and analyzes its content using natural language processing. The analysis then evaluates the importance and relevance of the information.

[0269] Step 3:

[0270] Based on the analysis results, the server generates an artificial intelligence agent that reflects the user's knowledge and skills. The agent's profile is configured with functions and characteristics that match the user's expertise.

[0271] Step 4:

[0272] The server automatically generates avatars to visualize the AI ​​agents that have been created. These avatars are customizable and designed according to the user's preferences.

[0273] Step 5:

[0274] The server publishes the completed avatar to the virtual public space. Here, the list of agents is updated so that other employees can access it.

[0275] Step 6:

[0276] The user (other employees) accesses the virtual public space and searches for and selects the AI agents required for work. The selection is made after checking the descriptions and evaluations of the agents.

[0277] Step 7:

[0278] The user downloads and installs the selected AI agent on their work terminal. After installation, the agent resides on the terminal and starts providing business support.

[0279] Step 8:

[0280] The terminal uses the resident AI agent to assist the user's business activities in real time. Based on specific instructions, the agent makes decisions and performs tasks on behalf of the user.

[0281] Step 9:

[0282] The server periodically collects the usage data of the agents for reference in improvement and updates. The performance of the AI agents is improved using the feedback.

[0283] (Example 1)

[0284] Next, 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] Within an enterprise, the sharing of expertise and skills may not be sufficient, which may lead to a decline in the work efficiency of each member. Also, in a conventional system, it may be difficult to generate and introduce intelligent entities that meet individual needs, and efficient support may not be obtained. Therefore, there is a need to effectively and quickly share the knowledge and skills of members and improve work efficiency.

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

[0287] In this invention, the server includes means for inputting the expertise and skills of members, means for generating an intelligent entity based on the input expertise and skills, and means for assisting the work by using the intelligent entity by a computer terminal. Thereby, effective information sharing within the enterprise and improvement of the work efficiency of each member become possible.

[0288] "Member" refers to an individual who performs work as part of an enterprise or organization.

[0289] "Expertise" refers to information based on advanced information and skills in a specific field.

[0290] "Skill" refers to a specific and practical ability for performing a specific task or role.

[0291] "Intelligent entity" refers to an artificial knowledge-based program or system generated based on the expertise and skills input by members.

[0292] "Virtual personality" refers to a digital character or avatar created to visually represent an intelligent entity.

[0293] "Digital space" refers to a virtual environment constructed on a computer and is accessible via a network.

[0294] A "computer terminal" refers to a digital device that a user can directly operate, and includes personal computers and tablets.

[0295] The embodiment of this invention relates to a system that facilitates the sharing of specialized knowledge and skills among members of a company to improve operational efficiency. This system primarily consists of three elements: a server, terminals, and users.

[0296] The server generates an intelligent entity based on the specialized knowledge and skills collected from its members. This process utilizes natural language processing technology to ensure that the input information is effectively used as the intelligent entity's function. A generative AI model is used to create an intelligent entity that reflects the expertise of each member. The generated intelligent entity is visualized as a virtual personality and made public in the digital space.

[0297] The terminal can access the digital space and select and install necessary virtual personalities from publicly available ones. Users use the installed AI entities on this terminal as work aids. These AI entities provide real-time support for problem-solving and task efficiency during work.

[0298] For example, if a user inputs discussion techniques for a specific sales area, the server uses this information to develop a relevant intelligence and publishes a visually represented virtual personality. Other users can then install this virtual personality on their devices to practically utilize the knowledge gained for sales activities.

[0299] As a concrete example of its use, the following prompt sentences can be provided to the AI ​​model:

[0300] "Please describe your area of ​​expertise. Also, please list specific skills and knowledge that are useful in that area."

[0301] In this way, efficient sharing of expertise among members and improvement of work efficiency are achieved.

[0302] The process of a specific process in Example 1 will be described with reference to FIG. 11.

[0303] Step 1:

[0304] The user inputs their own expertise and skills using a dedicated operation screen. The input includes descriptions using text forms, and file uploads of images and videos. This process is completed when the input data is sent to the server. The server organizes the received data according to the format and stores it in the database.

[0305] Step 2:

[0306] The server performs natural language processing on the input data from the user stored in the database. Specifically, it analyzes the input text and extracts important themes and concepts. For image data, it performs visual information analysis and extracts relevant keywords. The information obtained here is utilized as the basis for generating an intelligent entity. The output obtained is organized information reflecting the expertise of each user.

[0307] Step 3:

[0308] The server uses a generated AI model to generate an intelligent entity based on the analyzed information. In this process, the extracted themes and skills are efficiently incorporated as the response patterns of the intelligent entity. As the final output, an intelligent entity reflecting the user's expertise is generated. This intelligent entity can function effectively in specific tasks and scenarios.

[0309] Step 4:

[0310] The server assigns a virtual personality, a visual character, to the generated intelligent entity. The design of the virtual personality is customized based on user instructions and company guidelines. The completed virtual personality is uploaded to the digital space and made public. The output is a visually verifiable virtual personality.

[0311] Step 5:

[0312] Other users of the terminal can access the digital space and browse the publicly available virtual personalities. They then select the virtual personality necessary for their work and install it on their terminal. The selected virtual personality is downloaded to the terminal and becomes available through the interface. Once installed, the intelligent entity enters a standby state to support the user's daily tasks.

[0313] Step 6:

[0314] Users streamline their work by utilizing an intelligent system installed on their device. Specifically, the intelligent system provides real-time solutions to work problems the user faces and supports their work processes. The intelligent system has the functionality to improve the user's work efficiency and increase productivity. As an output, the user's work becomes more efficient, and the results are fed back as numerical data and evaluations.

[0315] (Application Example 1)

[0316] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0317] In today's information society, knowledge sharing and operational efficiency within companies and stores are essential. However, effectively integrating individual knowledge and preferences and providing information optimized for each user remains challenging. Furthermore, while there is a demand for personalized product information tailored to user needs and preferences, methods for achieving this are limited. Solving these problems and providing efficient operational support and an engaging user experience is crucial.

[0318] 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.

[0319] In this invention, the server includes means for inputting employees' knowledge and abilities, means for generating artificial intelligence agents based on the inputted knowledge and abilities, and means for collecting and storing user preference information. This enables knowledge sharing and operational efficiency within the company, as well as allowing customers to receive product information tailored to their individual preferences.

[0320] The term "employee" refers to an individual who belongs to an organization and performs specific duties or roles.

[0321] "Knowledge" refers to understanding and perception gained from information and experience, and includes all of an individual's specialized knowledge.

[0322] "Ability" refers to the skills, techniques, and aptitudes necessary to perform specific tasks or duties, and indicates an individual's capabilities.

[0323] An "artificial intelligence agent" refers to a software program designed to autonomously make decisions based on input information and assist in business operations.

[0324] An "avatar" refers to a digital icon or character used to visually represent an artificial intelligence agent in a virtual space.

[0325] A "virtual space" refers to a three-dimensional digital environment simulated on a computer, an area that users can access through an interface.

[0326] A "work terminal" refers to a computer or device used by a user to process work tasks or information.

[0327] "Preference information" refers to data about a specific user's preferences and interests, and is used to address individualized needs.

[0328] "Product information" refers to detailed information about a product, including price, specifications, performance, and usage instructions.

[0329] This system is designed to facilitate knowledge sharing and improve operational efficiency within a company, and to provide users with personalized product information. Its main components include an interface for inputting employee knowledge and skills, a server for generating artificial intelligence agents, and a platform for creating avatars that visually represent the agents.

[0330] The server uses Python and a natural language processing library (NLTK) to analyze the knowledge and abilities of the input employees. The analyzed data is passed to a generative AI model, which creates an artificial intelligence agent optimized for each piece of knowledge. Furthermore, this AI agent is visualized as an avatar in a virtual space using Unity.

[0331] Users (employees) can input their knowledge, skills, or market preference information using a dedicated interface. This information is sent to the server and forms the basis of the AI ​​agent generation process. In addition, the server utilizes the preference information to select and provide information tailored to each individual user, enabling the presentation of product information desired by the user's customers.

[0332] For example, if an employee inputs sales technique and preference information, an AI agent based on that information can be used by other employees in their sales activities. It can also suggest related new products based on products a customer has purchased in the past.

[0333] Examples of prompts from this system include, "Based on the electronic devices this customer has purchased in the past, what new products should we recommend?" and "Use your employees' sales techniques to provide advice on how to improve the closing rate."

[0334] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0335] Step 1:

[0336] Users input their knowledge and skills, or customer preference information, using a dedicated interface. This information is sent from the terminal to the server. Inputs include text data and past purchase history, and the output is an organized dataset.

[0337] Step 2:

[0338] The server uses a natural language processing library (NLTK) to process the received knowledge and preference information. In this step, the input data is classified by theme and keyword, and is ready to be used as parameters for the AI ​​generation model.

[0339] Step 3:

[0340] The server generates an artificial intelligence agent using a generative AI model based on the analyzed data. This process creates an AI agent that provides recommendation information based on input knowledge and customer preferences. The resulting agent functions as a business support algorithm.

[0341] Step 4:

[0342] The server uses Unity to create a visual avatar for the generated AI agent. This gives the agent a visually identifiable form when selected by other users in the virtual space. At this stage, the input is the generated AI agent, and the output is the avatarized digital character.

[0343] Step 5:

[0344] Users access a virtual space and select an AI agent that best suits their needs from among several publicly available agents. This selection is made on the terminal, and the selected agent resides permanently on the user's work terminal.

[0345] Step 6:

[0346] The terminal utilizes a resident AI agent to assist with tasks. The terminal presents recommended information and product information from the AI ​​agent, allowing users to receive suggestions for new tasks. The output consists of specific advice and product suggestions to streamline the user's tasks.

[0347] 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.

[0348] The system of this invention promotes knowledge sharing and operational efficiency within a company by reflecting employees' knowledge and abilities in an artificial intelligence agent. Furthermore, by combining this with an emotion engine, the system recognizes the user's emotional state and provides dynamic work support accordingly.

[0349] User input of knowledge and skills

[0350] Users can input their knowledge and skills through a dedicated interface. The interface supports text and voice input and allows for intuitive operation to enhance user convenience.

[0351] Generation of AI agents on the server

[0352] The server analyzes the data received from the user and understands the input using natural language processing technology. Based on this analysis, an artificial intelligence agent is generated that reflects the user's expertise. The agent is optimized for each individual user and responds to specific business needs.

[0353] Utilizing the Emotion Engine

[0354] The generated AI agent incorporates emotion recognition capabilities. The server analyzes the user's voice and text and uses an emotion engine to evaluate their emotional state. Based on this information, the agent autonomously adjusts its responses and level of support.

[0355] Agent avatarization and public release

[0356] The server generates avatars for the AI ​​agent and publishes them in the virtual space in a visually recognizable format for users and other employees. The avatars are customizable and can be designed to meet the user's requirements.

[0357] User selection and utilization of agents

[0358] Other users can select agents made available through the virtual space, install them on their work terminals, and use them in their daily tasks. Because they receive personalized support tailored to their individual needs, it's possible to further improve work productivity.

[0359] Specific example

[0360] For example, if User C is performing coordination tasks in a department that is causing them stress, the AI ​​agent uses its emotion engine to assess User C's emotions. Based on the emotion data obtained by the server, the agent suggests relaxing music and helps revise task priorities. This allows User C to perform their tasks efficiently while reducing their mental burden.

[0361] This system contributes to improving employees' work-life balance and the company's work environment by providing dynamic support based on emotion recognition.

[0362] The following describes the processing flow.

[0363] Step 1:

[0364] Users log in to a dedicated interface and input their expertise and skills via text and voice. This interface is designed to be user-friendly, allowing for concise input of complex knowledge.

[0365] Step 2:

[0366] The server receives data sent by the user and analyzes its content using natural language processing tools. The analysis identifies the user's knowledge domain and uses that information to create a profile for the AI ​​agent.

[0367] Step 3:

[0368] The server develops an AI agent based on the generated profile. This agent is designed to maximize the user's expertise and has the ability to adjust its response to specific tasks.

[0369] Step 4:

[0370] The server uses an emotion engine to add user emotion recognition capabilities to the agent. This capability analyzes the user's voice and text data to identify their emotional state.

[0371] Step 5:

[0372] The server generates an avatar that visually represents the AI ​​agent and applies the design chosen by the user. This avatar is then made public within the virtual space.

[0373] Step 6:

[0374] The user (or another employee) accesses the virtual space and selects which AI agent is needed. The selection is made after reviewing the agent's overview and evaluation information.

[0375] Step 7:

[0376] The user downloads the selected AI agent to their work terminal and completes the installation. After installation, the agent immediately begins operating on the terminal.

[0377] Step 8:

[0378] The terminal utilizes a resident agent to provide users with support for improving work efficiency and dynamic support tailored to their emotional state. Specific support includes suggestions based on emotional data and task prioritization.

[0379] Step 9:

[0380] The server regularly monitors agent usage and sentiment data, and uses the analysis results to update and improve the agents. This makes it possible to continuously provide optimized support to individual users.

[0381] (Example 2)

[0382] 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".

[0383] In modern businesses, effectively sharing the expertise and skills of team members and using that knowledge to streamline operations is crucial. However, traditional methods have struggled to accurately reflect each member's knowledge and perspectives and provide dynamic work support accordingly. Furthermore, there has been a lack of appropriate means to visually represent knowledge and abilities and promote collaboration among team members. This has resulted in limitations on knowledge sharing and improvements in work efficiency.

[0384] 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.

[0385] In this invention, the server includes means for inputting the expertise and skills of its members, means for generating an agent with learning capabilities based on the input expertise and skills, and means for performing emotion analysis on the generated agent and adjusting its behavior based on its state. This enables business support that takes into account the expertise and emotional state of its members.

[0386] "Members" refer to individual members who belong to an organization or group and contribute to its activities.

[0387] "Specialized knowledge" refers to a body of knowledge that has been deeply understood and acquired in relation to a specific field or job.

[0388] "Technology" refers to methods and skills used to achieve a specific purpose.

[0389] "Input means" refers to operations or devices used to supply information to a system.

[0390] An "agent with learning capabilities" refers to software that can analyze data and use that data to make autonomous decisions and perform tasks.

[0391] "Emotional analysis" refers to the process of collecting human emotions as data and evaluating those emotional states.

[0392] "Adjusting the operation" refers to optimizing the system's functions and responses according to the input data and circumstances.

[0393] "Visual elements" refer to visual media used to visually represent information or concepts.

[0394] A "virtual environment" refers to a digital space created using computers that mimics the real world.

[0395] "Work equipment" refers to devices or systems used to perform tasks or work.

[0396] This invention provides a system for sharing the expertise and skills of employees within a company and improving operational efficiency. To achieve this, it is primarily constructed using the following procedure.

[0397] Users communicate their expertise and skills to the system using a dedicated input device. The input device supports both text and voice input, allowing users to intuitively input information. For example, a user might input, "I have project management know-how."

[0398] The server analyzes information received from the user with high accuracy. The analysis uses Python as the programming language and leverages automated language processing libraries (e.g., spaCy). The server analyzes the input data, identifies keywords including "project management," and generates a learning agent. This agent is customized based on the user's expertise to support their work.

[0399] Next, the server collects the user's voice and text in real time and performs sentiment analysis. This analysis uses a sentiment recognition engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state. Based on the sentiment data, the server adjusts the agent's behavior to provide assistance tailored to the user's needs.

[0400] Furthermore, the server adds visual elements to the generated agents. A 3D development platform (e.g., Unity) is used for this purpose, effectively creating visual elements within the virtual environment. These visual elements are customizable and can be shared with other members within the virtual environment.

[0401] Other users can select agents published in a virtual environment and utilize them on their own work devices. For example, they can improve work efficiency by sensing the user's emotions and providing appropriate support, such as "suggesting a short break to reduce stress."

[0402] An example of a prompt message might be, "The user is currently experiencing stress; please suggest ways to relax." This system utilizes a generative AI model and prompt messages to provide dynamic business support.

[0403] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0404] Step 1:

[0405] The user inputs their expertise and skills in text or voice using a dedicated input device. For example, they might input "I have experience in marketing analysis." The input data at this stage is information about the user's expertise and skills. The terminal formats this input data and sends it to the server.

[0406] Step 2:

[0407] The server receives user input data sent from the terminal and analyzes the data using a natural language processing library (e.g., spaCy). This extracts information about key concepts and technologies. For example, "marketing analytics" might be identified as a specialty. The output of the processing is the basic data needed to generate agents.

[0408] Step 3:

[0409] The server generates an agent with learning capabilities based on the extracted data. This agent utilizes the generated AI model to customize it to the user's expertise. The output is an agent specifically tailored to the user's business needs.

[0410] Step 4:

[0411] The server collects emotional data in real time from the user's voice and text, and evaluates their emotional state using an emotional analysis engine (e.g., IBM Watson Tone Analyzer). The input is voice or text data, and the output is the evaluation result of the user's emotional state. Based on this evaluation result, the agent dynamically adjusts its response and the level of support provided.

[0412] Step 5:

[0413] The server adds visual elements to the generated agents and places them in a virtual environment using a 3D development platform such as Unity. The input at this stage is configuration information regarding the agent's expertise and design. The output is a visually recognizable agent within the virtual environment.

[0414] Step 6:

[0415] Users select agents published in a virtual environment and install them on their work devices. This selection process filters the agents best suited to the user's tasks. Once selected, the agents assist the user's work on the work device, providing notifications and recommendations. The output is increased productivity through the agents' work support.

[0416] (Application Example 2)

[0417] 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."

[0418] In modern workplace and home environments, there is an increasing need for dynamic support based on individual knowledge, skills, and emotional states. However, conventional systems primarily rely on the reuse of static knowledge, making it difficult to respond flexibly while considering individual emotional states. Therefore, there is a demand for efficient support for work and daily life that reduces emotional burden.

[0419] 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.

[0420] In this invention, the server includes means for inputting the user's knowledge and skills, means for generating an intelligent agent based on the input knowledge and skills, and means for evaluating the user's emotional state using emotion recognition technology. This makes it possible to provide the user with dynamic support that takes both knowledge and emotions into consideration.

[0421] A "user" is an individual or group that uses the system to input knowledge and skills and receives support as a result.

[0422] "Knowledge" refers to the information and understanding that users possess, and is provided to the system through input terminals.

[0423] "Skills" refer to the practical abilities and techniques possessed by users, and are used for analysis by the system.

[0424] An "intelligent agent" is an artificial intelligence program that is generated based on the user's knowledge and skills, and provides dynamic support.

[0425] A "display character" is a virtual representation created to visually represent the generated intelligent agent.

[0426] A "virtual space" is a virtual area constructed within a digital environment, and it is the place where display characters are made public.

[0427] A "processing terminal" is a computer or electronic device used by a user, which is a device that houses an intelligent agent to provide support.

[0428] "Emotion recognition technology" refers to a technical method that analyzes a user's voice and text data to evaluate their emotional state.

[0429] To implement this invention, the cooperation of a server, terminal, and user is primarily required. First, the user utilizes a dedicated interface to input knowledge and skills. This interface supports various input formats, such as text and voice, and allows for intuitive operation. This enables the user to easily provide their expertise and experience to the system.

[0430] The server analyzes the received data using natural language processing technology. It then generates a customized intelligent agent based on the user's input. This agent incorporates emotion recognition technology, enabling it to evaluate the user's emotional state from the input voice and text. The generated agent is visually represented and displayed as a character within the virtual space.

[0431] The processing terminal serves as a platform for keeping this intelligent agent resident. On the terminal, the intelligent agent can dynamically provide support that takes into account the user's emotional state. For example, if the user is feeling stressed, the intelligent agent can suggest relaxing music.

[0432] As a concrete example, consider a support robot for use in the home. This robot can automatically adjust schedules and play music for relaxation based on the user's emotions and daily life circumstances. This entire process is provided seamlessly through the cooperation of a server and an agent.

[0433] An example of a prompt in a generative AI model might be: "Come up with an idea for a home support robot that suggests relaxing music when residents are stressed and readjusts their schedule priorities."

[0434] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0435] Step 1:

[0436] Users input their knowledge and skills as text or voice using a dedicated interface. The interface collects the input data and sends it to the server. This input consists of the user's expertise and technical information, which is then analyzed in subsequent processing.

[0437] Step 2:

[0438] The server receives the transmitted input data. Here, natural language processing techniques are used to analyze the data and understand the user's knowledge and skills. Through this analysis, the data is structured and used as foundational information for agent generation. The output of this analysis is digital information with unique characteristics for each user.

[0439] Step 3:

[0440] The server generates an intelligent agent based on the analysis results. This agent reflects the analyzed knowledge and skills and is optimized to meet specific business needs. In this process, the agent's operational guidelines are defined and emotion recognition technology is incorporated.

[0441] Step 4:

[0442] A display character is created to visually represent the generated intelligent agent. The server designs this character in a customizable format so that it can be easily recognized by the user or other users in the virtual space. The output here is executable display character data.

[0443] Step 5:

[0444] The server exposes the generated agent's display character to a virtual space. Other users can access the agent through this virtual space. This virtual space provides the agent's active area of ​​activity and forms the basis for interaction.

[0445] Step 6:

[0446] The terminal selects an intelligent agent exposed in the virtual space and makes it reside there. The terminal then downloads the agent and integrates it into its hardware environment. The agent runs on the terminal and is ready to support the user with their daily tasks.

[0447] Step 7:

[0448] The agent uses emotion recognition technology to assess the user's emotional state in real time. Through voice and text analysis, it quantifies the current emotional state and determines what kind of support is needed based on that data. The output here is evaluation data indicating the emotional state.

[0449] Step 8:

[0450] The agent dynamically adjusts its support based on the user's emotional state. For example, if it detects stress, it will suggest relaxing music. Through this action, the agent alleviates the user's mental burden and improves their efficiency in work and daily life. An example of a prompt using a generative AI model is: "Think of an idea for a home support robot that suggests relaxing music when residents are stressed and readjusts their schedule priorities."

[0451] 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.

[0452] 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.

[0453] 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.

[0454] [Third Embodiment]

[0455] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0456] 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.

[0457] 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).

[0458] 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.

[0459] 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.

[0460] 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).

[0461] 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.

[0462] 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.

[0463] 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.

[0464] 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.

[0465] 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.

[0466] 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".

[0467] This invention is a system designed to facilitate knowledge sharing and improve work efficiency among employees within a company. Each employee inputs their own expertise and skills, and an artificial intelligence agent is generated based on this input. This agent is then avatarized and made public in a virtual space. Other employees can select a publicly available agent and use it on their own work terminals.

[0468] User input of knowledge and skills

[0469] Users can input their individual knowledge and skills using a dedicated interface. The interface is intuitive and supports text input, multimedia uploads, and even the import of existing deliverables.

[0470] Generation of AI agents on the server

[0471] The server analyzes data received from the user and generates an artificial intelligence agent. Natural language processing technology is utilized to ensure that the input knowledge effectively functions as the agent. The agent is customized to reflect the user's expertise and conform to the company's specific specifications.

[0472] Agent avatarization and public release

[0473] The server assigns an avatar to the AI ​​agent. The avatar can be designed according to the employee's preferences and can be viewed by other employees in the virtual space.

[0474] User selection and utilization of AI agents

[0475] Other users access the virtual space and select the necessary agents from several publicly available agents. They install the selected agent on their work terminal and use it to assist with their tasks. The artificial intelligence agent supports users in solving problems and streamlining tasks that arise during their work.

[0476] Specific example

[0477] For example, if user A inputs discussion techniques in the sales field, the server develops an AI agent based on this information, creates an avatar of the agent, and makes it publicly available. Another user B can select this agent and integrate it into their work terminal, allowing them to receive the knowledge necessary for their sales activities from the agent. In this way, specialized knowledge is efficiently shared among employees, contributing to improved productivity throughout the company.

[0478] This system plays a crucial role in enhancing a company's competitiveness by enabling the sharing of specific knowledge and the smooth execution of tasks. In this way, it achieves the rapid response capabilities and improved efficiency required in today's information society.

[0479] The following describes the processing flow.

[0480] Step 1:

[0481] Users access a dedicated interface and input information about their knowledge and skills. Input methods include text input, speech recognition, and file uploads. After reviewing the information, users submit it.

[0482] Step 2:

[0483] The server receives information sent by the user and analyzes its content using natural language processing. The analysis then evaluates the importance and relevance of the information.

[0484] Step 3:

[0485] Based on the analysis results, the server generates an artificial intelligence agent that reflects the user's knowledge and skills. The agent's profile is configured with functions and characteristics that match the user's expertise.

[0486] Step 4:

[0487] The server automatically generates avatars to visualize the AI ​​agents that have been created. These avatars are customizable and designed according to the user's preferences.

[0488] Step 5:

[0489] The server publishes the completed avatar to the virtual public space. The agent list is then updated so that other employees can access it.

[0490] Step 6:

[0491] Users (other employees) access a virtual public space to search for and select the AI ​​agent they need for their work. The selection is made after reviewing the agent's description and evaluation.

[0492] Step 7:

[0493] The user downloads and installs the selected AI agent on their work terminal. After installation, the agent resides on the terminal and begins providing work support.

[0494] Step 8:

[0495] The terminal uses a resident AI agent to assist users with their work activities in real time. Based on specific instructions, the agent provides decision support and performs tasks on their behalf.

[0496] Step 9:

[0497] The server periodically collects agent usage data to inform improvements and updates. Feedback is used to enhance the performance of the AI ​​agent.

[0498] (Example 1)

[0499] 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."

[0500] Insufficient sharing of specialized knowledge and skills within a company can lead to decreased work efficiency for individual members. Furthermore, traditional systems often struggle to generate and implement intelligent entities tailored to individual needs, resulting in inefficient support. Therefore, there is a need to effectively and quickly share the knowledge and skills of team members to streamline operations.

[0501] 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.

[0502] In this invention, the server includes means for inputting the specialized knowledge and skills of its members, means for generating an intelligent entity based on the input specialized knowledge and skills, and means for a computer terminal to use the intelligent entity to assist in its work. This enables effective information sharing within the company and improves the work efficiency of each member.

[0503] "Member" refers to an individual who performs duties as part of a company or organization.

[0504] "Specialized knowledge" refers to information based on advanced information and skills in a specific field.

[0505] "Skills" refer to specific and practical abilities required to perform particular tasks or roles.

[0506] An "intelligent entity" refers to an artificial knowledge-based program or system that is generated based on the specialized knowledge and skills input by its members.

[0507] A "virtual personality" refers to a digital character or avatar created to visually represent an intelligent entity.

[0508] "Digital space" refers to a virtual environment created on a computer, which is accessible via a network.

[0509] A "computer terminal" refers to a digital device that a user can directly operate, and includes personal computers and tablets.

[0510] The embodiment of this invention relates to a system that facilitates the sharing of specialized knowledge and skills among members of a company to improve operational efficiency. This system primarily consists of three elements: a server, terminals, and users.

[0511] The server generates an intelligent entity based on the specialized knowledge and skills collected from its members. This process utilizes natural language processing technology to ensure that the input information is effectively used as the intelligent entity's function. A generative AI model is used to create an intelligent entity that reflects the expertise of each member. The generated intelligent entity is visualized as a virtual personality and made public in the digital space.

[0512] The terminal can access the digital space and select and install necessary virtual personalities from publicly available ones. Users use the installed AI entities on this terminal as work aids. These AI entities provide real-time support for problem-solving and task efficiency during work.

[0513] For example, if a user inputs discussion techniques for a specific sales area, the server uses this information to develop a relevant intelligence and publishes a visually represented virtual personality. Other users can then install this virtual personality on their devices to practically utilize the knowledge gained for sales activities.

[0514] As a concrete example of its use, the following prompt sentences can be provided to the AI ​​model:

[0515] "Please describe your area of ​​expertise. Also, please list specific skills and knowledge that are useful in that area."

[0516] In this way, efficient sharing of expertise among members and improvement of work efficiency are achieved.

[0517] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0518] Step 1:

[0519] Users input their professional knowledge and skills using a dedicated interface. Input includes written descriptions using text forms and uploading image and video files. The process is completed when the entered data is sent to the server. The server organizes the received data according to a specified format and stores it in a database.

[0520] Step 2:

[0521] The server performs natural language processing on user input data stored in the database. Specifically, it analyzes input text and extracts important themes and concepts. For image data, it performs visual information analysis and extracts relevant keywords. The information obtained here is used as the basis for generating intelligent entities. The output is organized information that reflects each user's expertise.

[0522] Step 3:

[0523] The server uses a generative AI model to generate an intelligent entity based on the analyzed information. During this process, extracted themes and skills are efficiently incorporated into the intelligent entity's response patterns. The final output is an intelligent entity that reflects the user's expertise. This intelligent entity can function effectively in specific tasks and scenarios.

[0524] Step 4:

[0525] The server assigns a virtual personality, a visual character, to the generated intelligent entity. The design of the virtual personality is customized based on user instructions and company guidelines. The completed virtual personality is uploaded to the digital space and made public. The output is a visually verifiable virtual personality.

[0526] Step 5:

[0527] Other users of the terminal can access the digital space and browse the publicly available virtual personalities. They then select the virtual personality necessary for their work and install it on their terminal. The selected virtual personality is downloaded to the terminal and becomes available through the interface. Once installed, the intelligent entity enters a standby state to support the user's daily tasks.

[0528] Step 6:

[0529] Users streamline their work by utilizing an intelligent system installed on their device. Specifically, the intelligent system provides real-time solutions to work problems the user faces and supports their work processes. The intelligent system has the functionality to improve the user's work efficiency and increase productivity. As an output, the user's work becomes more efficient, and the results are fed back as numerical data and evaluations.

[0530] (Application Example 1)

[0531] 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."

[0532] In today's information society, knowledge sharing and operational efficiency within companies and stores are essential. However, effectively integrating individual knowledge and preferences and providing information optimized for each user remains challenging. Furthermore, while there is a demand for personalized product information tailored to user needs and preferences, methods for achieving this are limited. Solving these problems and providing efficient operational support and an engaging user experience is crucial.

[0533] 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.

[0534] In this invention, the server includes means for inputting employees' knowledge and abilities, means for generating artificial intelligence agents based on the inputted knowledge and abilities, and means for collecting and storing user preference information. This enables knowledge sharing and operational efficiency within the company, as well as allowing customers to receive product information tailored to their individual preferences.

[0535] The term "employee" refers to an individual who belongs to an organization and performs specific duties or roles.

[0536] "Knowledge" refers to understanding and perception gained from information and experience, and includes all of an individual's specialized knowledge.

[0537] "Ability" refers to the skills, techniques, and aptitudes necessary to perform specific tasks or duties, and indicates an individual's capabilities.

[0538] An "artificial intelligence agent" refers to a software program designed to autonomously make decisions based on input information and assist in business operations.

[0539] An "avatar" refers to a digital icon or character used to visually represent an artificial intelligence agent in a virtual space.

[0540] A "virtual space" refers to a three-dimensional digital environment simulated on a computer, an area that users can access through an interface.

[0541] A "work terminal" refers to a computer or device used by a user to process work tasks or information.

[0542] "Preference information" refers to data about a specific user's preferences and interests, and is used to address individualized needs.

[0543] "Product information" refers to detailed information about a product, including price, specifications, performance, and usage instructions.

[0544] This system is designed to facilitate knowledge sharing and improve operational efficiency within a company, and to provide users with personalized product information. Its main components include an interface for inputting employee knowledge and skills, a server for generating artificial intelligence agents, and a platform for creating avatars that visually represent the agents.

[0545] The server uses Python and a natural language processing library (NLTK) to analyze the knowledge and abilities of the input employees. The analyzed data is passed to a generative AI model, which creates an artificial intelligence agent optimized for each piece of knowledge. Furthermore, this AI agent is visualized as an avatar in a virtual space using Unity.

[0546] Users (employees) can input their knowledge, skills, or market preference information using a dedicated interface. This information is sent to the server and forms the basis of the AI ​​agent generation process. In addition, the server utilizes the preference information to select and provide information tailored to each individual user, enabling the presentation of product information desired by the user's customers.

[0547] For example, if an employee inputs sales technique and preference information, an AI agent based on that information can be used by other employees in their sales activities. It can also suggest related new products based on products a customer has purchased in the past.

[0548] Examples of prompts from this system include, "Based on the electronic devices this customer has purchased in the past, what new products should we recommend?" and "Use your employees' sales techniques to provide advice on how to improve the closing rate."

[0549] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0550] Step 1:

[0551] Users input their knowledge and skills, or customer preference information, using a dedicated interface. This information is sent from the terminal to the server. Inputs include text data and past purchase history, and the output is an organized dataset.

[0552] Step 2:

[0553] The server uses a natural language processing library (NLTK) to process the received knowledge and preference information. In this step, the input data is classified by theme and keyword, and is ready to be used as parameters for the AI ​​generation model.

[0554] Step 3:

[0555] The server generates an artificial intelligence agent using a generative AI model based on the analyzed data. This process creates an AI agent that provides recommendation information based on input knowledge and customer preferences. The resulting agent functions as a business support algorithm.

[0556] Step 4:

[0557] The server uses Unity to create a visual avatar for the generated AI agent. This gives the agent a visually identifiable form when selected by other users in the virtual space. At this stage, the input is the generated AI agent, and the output is the avatarized digital character.

[0558] Step 5:

[0559] Users access a virtual space and select an AI agent that best suits their needs from among several publicly available agents. This selection is made on the terminal, and the selected agent resides permanently on the user's work terminal.

[0560] Step 6:

[0561] The terminal utilizes a resident AI agent to assist with tasks. The terminal presents recommended information and product information from the AI ​​agent, allowing users to receive suggestions for new tasks. The output consists of specific advice and product suggestions to streamline the user's tasks.

[0562] 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.

[0563] The system of this invention promotes knowledge sharing and operational efficiency within a company by reflecting employees' knowledge and abilities in an artificial intelligence agent. Furthermore, by combining this with an emotion engine, the system recognizes the user's emotional state and provides dynamic work support accordingly.

[0564] User input of knowledge and skills

[0565] Users can input their knowledge and skills through a dedicated interface. The interface supports text and voice input and allows for intuitive operation to enhance user convenience.

[0566] Generation of AI agents on the server

[0567] The server analyzes the data received from the user and understands the input using natural language processing technology. Based on this analysis, an artificial intelligence agent is generated that reflects the user's expertise. The agent is optimized for each individual user and responds to specific business needs.

[0568] Utilizing the Emotion Engine

[0569] The generated AI agent incorporates emotion recognition capabilities. The server analyzes the user's voice and text and uses an emotion engine to evaluate their emotional state. Based on this information, the agent autonomously adjusts its responses and level of support.

[0570] Agent avatarization and public release

[0571] The server generates avatars for the AI ​​agent and publishes them in the virtual space in a visually recognizable format for users and other employees. The avatars are customizable and can be designed to meet the user's requirements.

[0572] User selection and utilization of agents

[0573] Other users can select agents made available through the virtual space, install them on their work terminals, and use them in their daily tasks. Because they receive personalized support tailored to their individual needs, it's possible to further improve work productivity.

[0574] Specific example

[0575] For example, if User C is performing coordination tasks in a department that is causing them stress, the AI ​​agent uses its emotion engine to assess User C's emotions. Based on the emotion data obtained by the server, the agent suggests relaxing music and helps revise task priorities. This allows User C to perform their tasks efficiently while reducing their mental burden.

[0576] This system contributes to improving employees' work-life balance and the company's work environment by providing dynamic support based on emotion recognition.

[0577] The following describes the processing flow.

[0578] Step 1:

[0579] Users log in to a dedicated interface and input their expertise and skills via text and voice. This interface is designed to be user-friendly, allowing for concise input of complex knowledge.

[0580] Step 2:

[0581] The server receives data sent by the user and analyzes its content using natural language processing tools. The analysis identifies the user's knowledge domain and uses that information to create a profile for the AI ​​agent.

[0582] Step 3:

[0583] The server develops an AI agent based on the generated profile. This agent is designed to maximize the user's expertise and has the ability to adjust its response to specific tasks.

[0584] Step 4:

[0585] The server uses an emotion engine to add user emotion recognition capabilities to the agent. This capability analyzes the user's voice and text data to identify their emotional state.

[0586] Step 5:

[0587] The server generates an avatar that visually represents the AI ​​agent and applies the design chosen by the user. This avatar is then made public within the virtual space.

[0588] Step 6:

[0589] The user (or another employee) accesses the virtual space and selects which AI agent is needed. The selection is made after reviewing the agent's overview and evaluation information.

[0590] Step 7:

[0591] The user downloads the selected AI agent to their work terminal and completes the installation. After installation, the agent immediately begins operating on the terminal.

[0592] Step 8:

[0593] The terminal utilizes a resident agent to provide users with support for improving work efficiency and dynamic support tailored to their emotional state. Specific support includes suggestions based on emotional data and task prioritization.

[0594] Step 9:

[0595] The server regularly monitors agent usage and sentiment data, and uses the analysis results to update and improve the agents. This makes it possible to continuously provide optimized support to individual users.

[0596] (Example 2)

[0597] 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."

[0598] In modern businesses, effectively sharing the expertise and skills of team members and using that knowledge to streamline operations is crucial. However, traditional methods have struggled to accurately reflect each member's knowledge and perspectives and provide dynamic work support accordingly. Furthermore, there has been a lack of appropriate means to visually represent knowledge and abilities and promote collaboration among team members. This has resulted in limitations on knowledge sharing and improvements in work efficiency.

[0599] 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.

[0600] In this invention, the server includes means for inputting the expertise and skills of its members, means for generating an agent with learning capabilities based on the input expertise and skills, and means for performing emotion analysis on the generated agent and adjusting its behavior based on its state. This enables business support that takes into account the expertise and emotional state of its members.

[0601] "Members" refer to individual members who belong to an organization or group and contribute to its activities.

[0602] "Specialized knowledge" refers to a body of knowledge that has been deeply understood and acquired in relation to a specific field or job.

[0603] "Technology" refers to methods and skills used to achieve a specific purpose.

[0604] "Input means" refers to operations or devices used to supply information to a system.

[0605] An "agent with learning capabilities" refers to software that can analyze data and use that data to make autonomous decisions and perform tasks.

[0606] "Emotional analysis" refers to the process of collecting human emotions as data and evaluating those emotional states.

[0607] "Adjusting the operation" refers to optimizing the system's functions and responses according to the input data and circumstances.

[0608] "Visual elements" refer to visual media used to visually represent information or concepts.

[0609] A "virtual environment" refers to a digital space created using computers that mimics the real world.

[0610] "Work equipment" refers to devices or systems used to perform tasks or work.

[0611] This invention provides a system for sharing the expertise and skills of employees within a company and improving operational efficiency. To achieve this, it is primarily constructed using the following procedure.

[0612] Users communicate their expertise and skills to the system using a dedicated input device. The input device supports both text and voice input, allowing users to intuitively input information. For example, a user might input, "I have project management know-how."

[0613] The server analyzes information received from the user with high accuracy. The analysis uses Python as the programming language and leverages automated language processing libraries (e.g., spaCy). The server analyzes the input data, identifies keywords including "project management," and generates a learning agent. This agent is customized based on the user's expertise to support their work.

[0614] Next, the server collects the user's voice and text in real time and performs sentiment analysis. This analysis uses a sentiment recognition engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state. Based on the sentiment data, the server adjusts the agent's behavior to provide assistance tailored to the user's needs.

[0615] Furthermore, the server adds visual elements to the generated agents. A 3D development platform (e.g., Unity) is used for this purpose, effectively creating visual elements within the virtual environment. These visual elements are customizable and can be shared with other members within the virtual environment.

[0616] Other users can select agents published in a virtual environment and utilize them on their own work devices. For example, they can improve work efficiency by sensing the user's emotions and providing appropriate support, such as "suggesting a short break to reduce stress."

[0617] An example of a prompt message might be, "The user is currently experiencing stress; please suggest ways to relax." This system utilizes a generative AI model and prompt messages to provide dynamic business support.

[0618] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0619] Step 1:

[0620] The user inputs their expertise and skills in text or voice using a dedicated input device. For example, they might input "I have experience in marketing analysis." The input data at this stage is information about the user's expertise and skills. The terminal formats this input data and sends it to the server.

[0621] Step 2:

[0622] The server receives user input data sent from the terminal and analyzes the data using a natural language processing library (e.g., spaCy). This extracts information about key concepts and technologies. For example, "marketing analytics" might be identified as a specialty. The output of the processing is the basic data needed to generate agents.

[0623] Step 3:

[0624] The server generates an agent with learning capabilities based on the extracted data. This agent utilizes the generated AI model to customize it to the user's expertise. The output is an agent specifically tailored to the user's business needs.

[0625] Step 4:

[0626] The server collects emotional data in real time from the user's voice and text, and evaluates their emotional state using an emotional analysis engine (e.g., IBM Watson Tone Analyzer). The input is voice or text data, and the output is the evaluation result of the user's emotional state. Based on this evaluation result, the agent dynamically adjusts its response and the level of support provided.

[0627] Step 5:

[0628] The server adds visual elements to the generated agents and places them in a virtual environment using a 3D development platform such as Unity. The input at this stage is configuration information regarding the agent's expertise and design. The output is a visually recognizable agent within the virtual environment.

[0629] Step 6:

[0630] Users select agents published in a virtual environment and install them on their work devices. This selection process filters the agents best suited to the user's tasks. Once selected, the agents assist the user's work on the work device, providing notifications and recommendations. The output is increased productivity through the agents' work support.

[0631] (Application Example 2)

[0632] 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."

[0633] In modern workplace and home environments, there is an increasing need for dynamic support based on individual knowledge, skills, and emotional states. However, conventional systems primarily rely on the reuse of static knowledge, making it difficult to respond flexibly while considering individual emotional states. Therefore, there is a demand for efficient support for work and daily life that reduces emotional burden.

[0634] 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.

[0635] In this invention, the server includes means for inputting the user's knowledge and skills, means for generating an intelligent agent based on the input knowledge and skills, and means for evaluating the user's emotional state using emotion recognition technology. This makes it possible to provide the user with dynamic support that takes both knowledge and emotions into consideration.

[0636] A "user" is an individual or group that uses the system to input knowledge and skills and receives support as a result.

[0637] "Knowledge" refers to the information and understanding that users possess, and is provided to the system through input terminals.

[0638] "Skills" refer to the practical abilities and techniques possessed by users, and are used for analysis by the system.

[0639] An "intelligent agent" is an artificial intelligence program that is generated based on the user's knowledge and skills, and provides dynamic support.

[0640] A "display character" is a virtual representation created to visually represent the generated intelligent agent.

[0641] A "virtual space" is a virtual area constructed within a digital environment, and it is the place where display characters are made public.

[0642] A "processing terminal" is a computer or electronic device used by a user, which is a device that houses an intelligent agent to provide support.

[0643] "Emotion recognition technology" refers to a technical method that analyzes a user's voice and text data to evaluate their emotional state.

[0644] To implement this invention, the cooperation of a server, terminal, and user is primarily required. First, the user utilizes a dedicated interface to input knowledge and skills. This interface supports various input formats, such as text and voice, and allows for intuitive operation. This enables the user to easily provide their expertise and experience to the system.

[0645] The server analyzes the received data using natural language processing technology. It then generates a customized intelligent agent based on the user's input. This agent incorporates emotion recognition technology, enabling it to evaluate the user's emotional state from the input voice and text. The generated agent is visually represented and displayed as a character within the virtual space.

[0646] The processing terminal serves as a platform for keeping this intelligent agent resident. On the terminal, the intelligent agent can dynamically provide support that takes into account the user's emotional state. For example, if the user is feeling stressed, the intelligent agent can suggest relaxing music.

[0647] As a concrete example, consider a support robot for use in the home. This robot can automatically adjust schedules and play music for relaxation based on the user's emotions and daily life circumstances. This entire process is provided seamlessly through the cooperation of a server and an agent.

[0648] An example of a prompt in a generative AI model might be: "Come up with an idea for a home support robot that suggests relaxing music when residents are stressed and readjusts their schedule priorities."

[0649] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0650] Step 1:

[0651] Users input their knowledge and skills as text or voice using a dedicated interface. The interface collects the input data and sends it to the server. This input consists of the user's expertise and technical information, which is then analyzed in subsequent processing.

[0652] Step 2:

[0653] The server receives the transmitted input data. Here, natural language processing techniques are used to analyze the data and understand the user's knowledge and skills. Through this analysis, the data is structured and used as foundational information for agent generation. The output of this analysis is digital information with unique characteristics for each user.

[0654] Step 3:

[0655] The server generates an intelligent agent based on the analysis results. This agent reflects the analyzed knowledge and skills and is optimized to meet specific business needs. In this process, the agent's operational guidelines are defined and emotion recognition technology is incorporated.

[0656] Step 4:

[0657] A display character is created to visually represent the generated intelligent agent. The server designs this character in a customizable format so that it can be easily recognized by the user or other users in the virtual space. The output here is executable display character data.

[0658] Step 5:

[0659] The server exposes the generated agent's display character to a virtual space. Other users can access the agent through this virtual space. This virtual space provides the agent's active area of ​​activity and forms the basis for interaction.

[0660] Step 6:

[0661] The terminal selects an intelligent agent exposed in the virtual space and makes it reside there. The terminal then downloads the agent and integrates it into its hardware environment. The agent runs on the terminal and is ready to support the user with their daily tasks.

[0662] Step 7:

[0663] The agent uses emotion recognition technology to assess the user's emotional state in real time. Through voice and text analysis, it quantifies the current emotional state and determines what kind of support is needed based on that data. The output here is evaluation data indicating the emotional state.

[0664] Step 8:

[0665] The agent dynamically adjusts its support based on the user's emotional state. For example, if it detects stress, it will suggest relaxing music. Through this action, the agent alleviates the user's mental burden and improves their efficiency in work and daily life. An example of a prompt using a generative AI model is: "Think of an idea for a home support robot that suggests relaxing music when residents are stressed and readjusts their schedule priorities."

[0666] 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.

[0667] 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.

[0668] 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.

[0669] [Fourth Embodiment]

[0670] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0671] 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.

[0672] 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).

[0673] 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.

[0674] 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.

[0675] 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).

[0676] 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.

[0677] 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.

[0678] 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.

[0679] 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.

[0680] 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.

[0681] 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.

[0682] 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".

[0683] This invention is a system designed to facilitate knowledge sharing and improve work efficiency among employees within a company. Each employee inputs their own expertise and skills, and an artificial intelligence agent is generated based on this input. This agent is then avatarized and made public in a virtual space. Other employees can select a publicly available agent and use it on their own work terminals.

[0684] User input of knowledge and skills

[0685] Users can input their individual knowledge and skills using a dedicated interface. The interface is intuitive and supports text input, multimedia uploads, and even the import of existing deliverables.

[0686] Generation of AI agents on the server

[0687] The server analyzes data received from the user and generates an artificial intelligence agent. Natural language processing technology is utilized to ensure that the input knowledge effectively functions as the agent. The agent is customized to reflect the user's expertise and conform to the company's specific specifications.

[0688] Agent avatarization and public release

[0689] The server assigns an avatar to the AI ​​agent. The avatar can be designed according to the employee's preferences and can be viewed by other employees in the virtual space.

[0690] User selection and utilization of AI agents

[0691] Other users access the virtual space and select the necessary agents from several publicly available agents. They install the selected agent on their work terminal and use it to assist with their tasks. The artificial intelligence agent supports users in solving problems and streamlining tasks that arise during their work.

[0692] Specific example

[0693] For example, if user A inputs discussion techniques in the sales field, the server develops an AI agent based on this information, creates an avatar of the agent, and makes it publicly available. Another user B can select this agent and integrate it into their work terminal, allowing them to receive the knowledge necessary for their sales activities from the agent. In this way, specialized knowledge is efficiently shared among employees, contributing to improved productivity throughout the company.

[0694] This system plays a crucial role in enhancing a company's competitiveness by enabling the sharing of specific knowledge and the smooth execution of tasks. In this way, it achieves the rapid response capabilities and improved efficiency required in today's information society.

[0695] The following describes the processing flow.

[0696] Step 1:

[0697] Users access a dedicated interface and input information about their knowledge and skills. Input methods include text input, speech recognition, and file uploads. After reviewing the information, users submit it.

[0698] Step 2:

[0699] The server receives information sent by the user and analyzes its content using natural language processing. The analysis then evaluates the importance and relevance of the information.

[0700] Step 3:

[0701] Based on the analysis results, the server generates an artificial intelligence agent that reflects the user's knowledge and skills. The agent's profile is configured with functions and characteristics that match the user's expertise.

[0702] Step 4:

[0703] The server automatically generates avatars to visualize the AI ​​agents that have been created. These avatars are customizable and designed according to the user's preferences.

[0704] Step 5:

[0705] The server publishes the completed avatar to the virtual public space. The agent list is then updated so that other employees can access it.

[0706] Step 6:

[0707] Users (other employees) access a virtual public space to search for and select the AI ​​agent they need for their work. The selection is made after reviewing the agent's description and evaluation.

[0708] Step 7:

[0709] The user downloads and installs the selected AI agent on their work terminal. After installation, the agent resides on the terminal and begins providing work support.

[0710] Step 8:

[0711] The terminal uses a resident AI agent to assist users with their work activities in real time. Based on specific instructions, the agent provides decision support and performs tasks on their behalf.

[0712] Step 9:

[0713] The server periodically collects agent usage data to inform improvements and updates. Feedback is used to enhance the performance of the AI ​​agent.

[0714] (Example 1)

[0715] 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".

[0716] Insufficient sharing of specialized knowledge and skills within a company can lead to decreased work efficiency for individual members. Furthermore, traditional systems often struggle to generate and implement intelligent entities tailored to individual needs, resulting in inefficient support. Therefore, there is a need to effectively and quickly share the knowledge and skills of team members to streamline operations.

[0717] 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.

[0718] In this invention, the server includes means for inputting the specialized knowledge and skills of its members, means for generating an intelligent entity based on the input specialized knowledge and skills, and means for a computer terminal to use the intelligent entity to assist in its work. This enables effective information sharing within the company and improves the work efficiency of each member.

[0719] "Member" refers to an individual who performs duties as part of a company or organization.

[0720] "Specialized knowledge" refers to information based on advanced information and skills in a specific field.

[0721] "Skills" refer to specific and practical abilities required to perform particular tasks or roles.

[0722] An "intelligent entity" refers to an artificial knowledge-based program or system that is generated based on the specialized knowledge and skills input by its members.

[0723] A "virtual personality" refers to a digital character or avatar created to visually represent an intelligent entity.

[0724] "Digital space" refers to a virtual environment created on a computer, which is accessible via a network.

[0725] A "computer terminal" refers to a digital device that a user can directly operate, and includes personal computers and tablets.

[0726] The embodiment of this invention relates to a system that facilitates the sharing of specialized knowledge and skills among members of a company to improve operational efficiency. This system primarily consists of three elements: a server, terminals, and users.

[0727] The server generates an intelligent entity based on the specialized knowledge and skills collected from its members. This process utilizes natural language processing technology to ensure that the input information is effectively used as the intelligent entity's function. A generative AI model is used to create an intelligent entity that reflects the expertise of each member. The generated intelligent entity is visualized as a virtual personality and made public in the digital space.

[0728] The terminal can access the digital space and select and install necessary virtual personalities from publicly available ones. Users use the installed AI entities on this terminal as work aids. These AI entities provide real-time support for problem-solving and task efficiency during work.

[0729] For example, if a user inputs discussion techniques for a specific sales area, the server uses this information to develop a relevant intelligence and publishes a visually represented virtual personality. Other users can then install this virtual personality on their devices to practically utilize the knowledge gained for sales activities.

[0730] As a concrete example of its use, the following prompt sentences can be provided to the AI ​​model:

[0731] "Please describe your area of ​​expertise. Also, please list specific skills and knowledge that are useful in that area."

[0732] In this way, efficient sharing of expertise among members and improvement of work efficiency are achieved.

[0733] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0734] Step 1:

[0735] Users input their professional knowledge and skills using a dedicated interface. Input includes written descriptions using text forms and uploading image and video files. The process is completed when the entered data is sent to the server. The server organizes the received data according to a specified format and stores it in a database.

[0736] Step 2:

[0737] The server performs natural language processing on user input data stored in the database. Specifically, it analyzes input text and extracts important themes and concepts. For image data, it performs visual information analysis and extracts relevant keywords. The information obtained here is used as the basis for generating intelligent entities. The output is organized information that reflects each user's expertise.

[0738] Step 3:

[0739] The server uses a generative AI model to generate an intelligent entity based on the analyzed information. During this process, extracted themes and skills are efficiently incorporated into the intelligent entity's response patterns. The final output is an intelligent entity that reflects the user's expertise. This intelligent entity can function effectively in specific tasks and scenarios.

[0740] Step 4:

[0741] The server assigns a virtual personality, a visual character, to the generated intelligent entity. The design of the virtual personality is customized based on user instructions and company guidelines. The completed virtual personality is uploaded to the digital space and made public. The output is a visually verifiable virtual personality.

[0742] Step 5:

[0743] Other users of the terminal can access the digital space and browse the publicly available virtual personalities. They then select the virtual personality necessary for their work and install it on their terminal. The selected virtual personality is downloaded to the terminal and becomes available through the interface. Once installed, the intelligent entity enters a standby state to support the user's daily tasks.

[0744] Step 6:

[0745] Users streamline their work by utilizing an intelligent system installed on their device. Specifically, the intelligent system provides real-time solutions to work problems the user faces and supports their work processes. The intelligent system has the functionality to improve the user's work efficiency and increase productivity. As an output, the user's work becomes more efficient, and the results are fed back as numerical data and evaluations.

[0746] (Application Example 1)

[0747] 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".

[0748] In today's information society, knowledge sharing and operational efficiency within companies and stores are essential. However, effectively integrating individual knowledge and preferences and providing information optimized for each user remains challenging. Furthermore, while there is a demand for personalized product information tailored to user needs and preferences, methods for achieving this are limited. Solving these problems and providing efficient operational support and an engaging user experience is crucial.

[0749] 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.

[0750] In this invention, the server includes means for inputting employees' knowledge and abilities, means for generating artificial intelligence agents based on the inputted knowledge and abilities, and means for collecting and storing user preference information. This enables knowledge sharing and operational efficiency within the company, as well as allowing customers to receive product information tailored to their individual preferences.

[0751] The term "employee" refers to an individual who belongs to an organization and performs specific duties or roles.

[0752] "Knowledge" refers to understanding and perception gained from information and experience, and includes all of an individual's specialized knowledge.

[0753] "Ability" refers to the skills, techniques, and aptitudes necessary to perform specific tasks or duties, and indicates an individual's capabilities.

[0754] An "artificial intelligence agent" refers to a software program designed to autonomously make decisions based on input information and assist in business operations.

[0755] An "avatar" refers to a digital icon or character used to visually represent an artificial intelligence agent in a virtual space.

[0756] A "virtual space" refers to a three-dimensional digital environment simulated on a computer, an area that users can access through an interface.

[0757] A "work terminal" refers to a computer or device used by a user to process work tasks or information.

[0758] "Preference information" refers to data about a specific user's preferences and interests, and is used to address individualized needs.

[0759] "Product information" refers to detailed information about a product, including price, specifications, performance, and usage instructions.

[0760] This system is designed to facilitate knowledge sharing and improve operational efficiency within a company, and to provide users with personalized product information. Its main components include an interface for inputting employee knowledge and skills, a server for generating artificial intelligence agents, and a platform for creating avatars that visually represent the agents.

[0761] The server uses Python and a natural language processing library (NLTK) to analyze the knowledge and abilities of the input employees. The analyzed data is passed to a generative AI model, which creates an artificial intelligence agent optimized for each piece of knowledge. Furthermore, this AI agent is visualized as an avatar in a virtual space using Unity.

[0762] Users (employees) can input their knowledge, skills, or market preference information using a dedicated interface. This information is sent to the server and forms the basis of the AI ​​agent generation process. In addition, the server utilizes the preference information to select and provide information tailored to each individual user, enabling the presentation of product information desired by the user's customers.

[0763] For example, if an employee inputs sales technique and preference information, an AI agent based on that information can be used by other employees in their sales activities. It can also suggest related new products based on products a customer has purchased in the past.

[0764] Examples of prompts from this system include, "Based on the electronic devices this customer has purchased in the past, what new products should we recommend?" and "Use your employees' sales techniques to provide advice on how to improve the closing rate."

[0765] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0766] Step 1:

[0767] Users input their knowledge and skills, or customer preference information, using a dedicated interface. This information is sent from the terminal to the server. Inputs include text data and past purchase history, and the output is an organized dataset.

[0768] Step 2:

[0769] The server uses a natural language processing library (NLTK) to process the received knowledge and preference information. In this step, the input data is classified by theme and keyword, and is ready to be used as parameters for the AI ​​generation model.

[0770] Step 3:

[0771] The server generates an artificial intelligence agent using a generative AI model based on the analyzed data. This process creates an AI agent that provides recommendation information based on input knowledge and customer preferences. The resulting agent functions as a business support algorithm.

[0772] Step 4:

[0773] The server uses Unity to create a visual avatar for the generated AI agent. This gives the agent a visually identifiable form when selected by other users in the virtual space. At this stage, the input is the generated AI agent, and the output is the avatarized digital character.

[0774] Step 5:

[0775] Users access a virtual space and select an AI agent that best suits their needs from among several publicly available agents. This selection is made on the terminal, and the selected agent resides permanently on the user's work terminal.

[0776] Step 6:

[0777] The terminal utilizes a resident AI agent to assist with tasks. The terminal presents recommended information and product information from the AI ​​agent, allowing users to receive suggestions for new tasks. The output consists of specific advice and product suggestions to streamline the user's tasks.

[0778] 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.

[0779] The system of this invention promotes knowledge sharing and operational efficiency within a company by reflecting employees' knowledge and abilities in an artificial intelligence agent. Furthermore, by combining this with an emotion engine, the system recognizes the user's emotional state and provides dynamic work support accordingly.

[0780] User input of knowledge and skills

[0781] Users can input their knowledge and skills through a dedicated interface. The interface supports text and voice input and allows for intuitive operation to enhance user convenience.

[0782] Generation of AI agents on the server

[0783] The server analyzes the data received from the user and understands the input using natural language processing technology. Based on this analysis, an artificial intelligence agent is generated that reflects the user's expertise. The agent is optimized for each individual user and responds to specific business needs.

[0784] Utilizing the Emotion Engine

[0785] The generated AI agent incorporates emotion recognition capabilities. The server analyzes the user's voice and text and uses an emotion engine to evaluate their emotional state. Based on this information, the agent autonomously adjusts its responses and level of support.

[0786] Agent avatarization and public release

[0787] The server generates avatars for the AI ​​agent and publishes them in the virtual space in a visually recognizable format for users and other employees. The avatars are customizable and can be designed to meet the user's requirements.

[0788] User selection and utilization of agents

[0789] Other users can select agents made available through the virtual space, install them on their work terminals, and use them in their daily tasks. Because they receive personalized support tailored to their individual needs, it's possible to further improve work productivity.

[0790] Specific example

[0791] For example, if User C is performing coordination tasks in a department that is causing them stress, the AI ​​agent uses its emotion engine to assess User C's emotions. Based on the emotion data obtained by the server, the agent suggests relaxing music and helps revise task priorities. This allows User C to perform their tasks efficiently while reducing their mental burden.

[0792] This system contributes to improving employees' work-life balance and the company's work environment by providing dynamic support based on emotion recognition.

[0793] The following describes the processing flow.

[0794] Step 1:

[0795] Users log in to a dedicated interface and input their expertise and skills via text and voice. This interface is designed to be user-friendly, allowing for concise input of complex knowledge.

[0796] Step 2:

[0797] The server receives data sent by the user and analyzes its content using natural language processing tools. The analysis identifies the user's knowledge domain and uses that information to create a profile for the AI ​​agent.

[0798] Step 3:

[0799] The server develops an AI agent based on the generated profile. This agent is designed to maximize the user's expertise and has the ability to adjust its response to specific tasks.

[0800] Step 4:

[0801] The server uses an emotion engine to add user emotion recognition capabilities to the agent. This capability analyzes the user's voice and text data to identify their emotional state.

[0802] Step 5:

[0803] The server generates an avatar that visually represents the AI ​​agent and applies the design chosen by the user. This avatar is then made public within the virtual space.

[0804] Step 6:

[0805] The user (or another employee) accesses the virtual space and selects which AI agent is needed. The selection is made after reviewing the agent's overview and evaluation information.

[0806] Step 7:

[0807] The user downloads the selected AI agent to their work terminal and completes the installation. After installation, the agent immediately begins operating on the terminal.

[0808] Step 8:

[0809] The terminal utilizes a resident agent to provide users with support for improving work efficiency and dynamic support tailored to their emotional state. Specific support includes suggestions based on emotional data and task prioritization.

[0810] Step 9:

[0811] The server regularly monitors agent usage and sentiment data, and uses the analysis results to update and improve the agents. This makes it possible to continuously provide optimized support to individual users.

[0812] (Example 2)

[0813] 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".

[0814] In modern businesses, effectively sharing the expertise and skills of team members and using that knowledge to streamline operations is crucial. However, traditional methods have struggled to accurately reflect each member's knowledge and perspectives and provide dynamic work support accordingly. Furthermore, there has been a lack of appropriate means to visually represent knowledge and abilities and promote collaboration among team members. This has resulted in limitations on knowledge sharing and improvements in work efficiency.

[0815] 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.

[0816] In this invention, the server includes means for inputting the expertise and skills of its members, means for generating an agent with learning capabilities based on the input expertise and skills, and means for performing emotion analysis on the generated agent and adjusting its behavior based on its state. This enables business support that takes into account the expertise and emotional state of its members.

[0817] "Members" refer to individual members who belong to an organization or group and contribute to its activities.

[0818] "Specialized knowledge" refers to a body of knowledge that has been deeply understood and acquired in relation to a specific field or job.

[0819] "Technology" refers to methods and skills used to achieve a specific purpose.

[0820] "Input means" refers to operations or devices used to supply information to a system.

[0821] An "agent with learning capabilities" refers to software that can analyze data and use that data to make autonomous decisions and perform tasks.

[0822] "Emotional analysis" refers to the process of collecting human emotions as data and evaluating those emotional states.

[0823] "Adjusting the operation" refers to optimizing the system's functions and responses according to the input data and circumstances.

[0824] "Visual elements" refer to visual media used to visually represent information or concepts.

[0825] A "virtual environment" refers to a digital space created using computers that mimics the real world.

[0826] "Work equipment" refers to devices or systems used to perform tasks or work.

[0827] This invention provides a system for sharing the expertise and skills of employees within a company and improving operational efficiency. To achieve this, it is primarily constructed using the following procedure.

[0828] Users communicate their expertise and skills to the system using a dedicated input device. The input device supports both text and voice input, allowing users to intuitively input information. For example, a user might input, "I have project management know-how."

[0829] The server analyzes information received from the user with high accuracy. The analysis uses Python as the programming language and leverages automated language processing libraries (e.g., spaCy). The server analyzes the input data, identifies keywords including "project management," and generates a learning agent. This agent is customized based on the user's expertise to support their work.

[0830] Next, the server collects the user's voice and text in real time and performs sentiment analysis. This analysis uses a sentiment recognition engine (e.g., IBM Watson Tone Analyzer) to evaluate the user's emotional state. Based on the sentiment data, the server adjusts the agent's behavior to provide assistance tailored to the user's needs.

[0831] Furthermore, the server adds visual elements to the generated agents. A 3D development platform (e.g., Unity) is used for this purpose, effectively creating visual elements within the virtual environment. These visual elements are customizable and can be shared with other members within the virtual environment.

[0832] Other users can select agents published in a virtual environment and utilize them on their own work devices. For example, they can improve work efficiency by sensing the user's emotions and providing appropriate support, such as "suggesting a short break to reduce stress."

[0833] An example of a prompt message might be, "The user is currently experiencing stress; please suggest ways to relax." This system utilizes a generative AI model and prompt messages to provide dynamic business support.

[0834] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0835] Step 1:

[0836] The user inputs their expertise and skills in text or voice using a dedicated input device. For example, they might input "I have experience in marketing analysis." The input data at this stage is information about the user's expertise and skills. The terminal formats this input data and sends it to the server.

[0837] Step 2:

[0838] The server receives user input data sent from the terminal and analyzes the data using a natural language processing library (e.g., spaCy). This extracts information about key concepts and technologies. For example, "marketing analytics" might be identified as a specialty. The output of the processing is the basic data needed to generate agents.

[0839] Step 3:

[0840] The server generates an agent with learning capabilities based on the extracted data. This agent utilizes the generated AI model to customize it to the user's expertise. The output is an agent specifically tailored to the user's business needs.

[0841] Step 4:

[0842] The server collects emotional data in real time from the user's voice and text, and evaluates their emotional state using an emotional analysis engine (e.g., IBM Watson Tone Analyzer). The input is voice or text data, and the output is the evaluation result of the user's emotional state. Based on this evaluation result, the agent dynamically adjusts its response and the level of support provided.

[0843] Step 5:

[0844] The server adds visual elements to the generated agents and places them in a virtual environment using a 3D development platform such as Unity. The input at this stage is configuration information regarding the agent's expertise and design. The output is a visually recognizable agent within the virtual environment.

[0845] Step 6:

[0846] Users select agents published in a virtual environment and install them on their work devices. This selection process filters the agents best suited to the user's tasks. Once selected, the agents assist the user's work on the work device, providing notifications and recommendations. The output is increased productivity through the agents' work support.

[0847] (Application Example 2)

[0848] 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".

[0849] In modern workplace and home environments, there is an increasing need for dynamic support based on individual knowledge, skills, and emotional states. However, conventional systems primarily rely on the reuse of static knowledge, making it difficult to respond flexibly while considering individual emotional states. Therefore, there is a demand for efficient support for work and daily life that reduces emotional burden.

[0850] 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.

[0851] In this invention, the server includes means for inputting the user's knowledge and skills, means for generating an intelligent agent based on the input knowledge and skills, and means for evaluating the user's emotional state using emotion recognition technology. This makes it possible to provide the user with dynamic support that takes both knowledge and emotions into consideration.

[0852] A "user" is an individual or group that uses the system to input knowledge and skills and receives support as a result.

[0853] "Knowledge" refers to the information and understanding that users possess, and is provided to the system through input terminals.

[0854] "Skills" refer to the practical abilities and techniques possessed by users, and are used for analysis by the system.

[0855] An "intelligent agent" is an artificial intelligence program that is generated based on the user's knowledge and skills, and provides dynamic support.

[0856] A "display character" is a virtual representation created to visually represent the generated intelligent agent.

[0857] A "virtual space" is a virtual area constructed within a digital environment, and it is the place where display characters are made public.

[0858] A "processing terminal" is a computer or electronic device used by a user, which is a device that houses an intelligent agent to provide support.

[0859] "Emotion recognition technology" refers to a technical method that analyzes a user's voice and text data to evaluate their emotional state.

[0860] To implement this invention, the cooperation of a server, terminal, and user is primarily required. First, the user utilizes a dedicated interface to input knowledge and skills. This interface supports various input formats, such as text and voice, and allows for intuitive operation. This enables the user to easily provide their expertise and experience to the system.

[0861] The server analyzes the received data using natural language processing technology. It then generates a customized intelligent agent based on the user's input. This agent incorporates emotion recognition technology, enabling it to evaluate the user's emotional state from the input voice and text. The generated agent is visually represented and displayed as a character within the virtual space.

[0862] The processing terminal serves as a platform for keeping this intelligent agent resident. On the terminal, the intelligent agent can dynamically provide support that takes into account the user's emotional state. For example, if the user is feeling stressed, the intelligent agent can suggest relaxing music.

[0863] As a concrete example, consider a support robot for use in the home. This robot can automatically adjust schedules and play music for relaxation based on the user's emotions and daily life circumstances. This entire process is provided seamlessly through the cooperation of a server and an agent.

[0864] An example of a prompt in a generative AI model might be: "Come up with an idea for a home support robot that suggests relaxing music when residents are stressed and readjusts their schedule priorities."

[0865] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0866] Step 1:

[0867] Users input their knowledge and skills as text or voice using a dedicated interface. The interface collects the input data and sends it to the server. This input consists of the user's expertise and technical information, which is then analyzed in subsequent processing.

[0868] Step 2:

[0869] The server receives the transmitted input data. Here, natural language processing techniques are used to analyze the data and understand the user's knowledge and skills. Through this analysis, the data is structured and used as foundational information for agent generation. The output of this analysis is digital information with unique characteristics for each user.

[0870] Step 3:

[0871] The server generates an intelligent agent based on the analysis results. This agent reflects the analyzed knowledge and skills and is optimized to meet specific business needs. In this process, the agent's operational guidelines are defined and emotion recognition technology is incorporated.

[0872] Step 4:

[0873] A display character is created to visually represent the generated intelligent agent. The server designs this character in a customizable format so that it can be easily recognized by the user or other users in the virtual space. The output here is executable display character data.

[0874] Step 5:

[0875] The server exposes the generated agent's display character to a virtual space. Other users can access the agent through this virtual space. This virtual space provides the agent's active area of ​​activity and forms the basis for interaction.

[0876] Step 6:

[0877] The terminal selects an intelligent agent exposed in the virtual space and makes it reside there. The terminal then downloads the agent and integrates it into its hardware environment. The agent runs on the terminal and is ready to support the user with their daily tasks.

[0878] Step 7:

[0879] The agent uses emotion recognition technology to assess the user's emotional state in real time. Through voice and text analysis, it quantifies the current emotional state and determines what kind of support is needed based on that data. The output here is evaluation data indicating the emotional state.

[0880] Step 8:

[0881] The agent dynamically adjusts its support based on the user's emotional state. For example, if it detects stress, it will suggest relaxing music. Through this action, the agent alleviates the user's mental burden and improves their efficiency in work and daily life. An example of a prompt using a generative AI model is: "Think of an idea for a home support robot that suggests relaxing music when residents are stressed and readjusts their schedule priorities."

[0882] 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.

[0883] 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.

[0884] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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."

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] The following is further disclosed regarding the embodiments described above.

[0904] (Claim 1)

[0905] A means of inputting employees' knowledge and abilities,

[0906] A means for generating an artificial intelligence agent based on input knowledge and abilities,

[0907] A means of creating an avatar that visually represents the generated artificial intelligence agent,

[0908] A means of making the created avatar publicly available in the virtual space,

[0909] A means for other employees to select a publicly available artificial intelligence agent and have it reside on their work terminal,

[0910] A means by which a work terminal uses an artificial intelligence agent to assist with tasks,

[0911] A system that includes this.

[0912] (Claim 2)

[0913] The system according to claim 1, characterized in that employees input knowledge and skills using a dedicated interface.

[0914] (Claim 3)

[0915] The system according to claim 1, characterized in that it uses natural language processing technology in generating an artificial intelligence agent.

[0916] "Example 1"

[0917] (Claim 1)

[0918] A means of inputting the specialized knowledge and skills of the members,

[0919] A means for generating an intelligent entity based on input specialized knowledge and skills,

[0920] A means of creating a virtual personality that visually represents the generated intelligent entity,

[0921] A means of making the created virtual personality public in the digital space,

[0922] A means by which other members can select a publicly available intelligent entity and install it into their own computer terminal,

[0923] A means by which computer terminals use intelligent entities to assist in tasks,

[0924] A system that includes this.

[0925] (Claim 2)

[0926] The system according to claim 1, characterized in that members input specialized knowledge and skills using a specific operation screen.

[0927] (Claim 3)

[0928] The system according to claim 1, characterized in that it uses natural language processing technology in the generation of an intelligent entity.

[0929] "Application Example 1"

[0930] (Claim 1)

[0931] A means of inputting employees' knowledge and abilities,

[0932] A means for generating an artificial intelligence agent based on input knowledge and abilities,

[0933] A means of creating an avatar that visually represents the generated artificial intelligence agent,

[0934] A means of making the created avatar publicly available in the virtual space,

[0935] A means for other employees to select a publicly available artificial intelligence agent and have it reside on their work terminal,

[0936] A means by which a work terminal uses an artificial intelligence agent to assist with tasks,

[0937] A means of collecting and storing user preference information,

[0938] A means by which an artificial intelligence agent provides product information based on collected preference information,

[0939] A system that includes this.

[0940] (Claim 2)

[0941] The system according to claim 1, characterized in that employees input knowledge and skills using a dedicated interface, and user preference information is also input at the same time.

[0942] (Claim 3)

[0943] The system according to claim 1, characterized in that it uses natural language processing technology in generating artificial intelligence agents, and also uses similar technology in providing product information based on user preference information.

[0944] "Example 2 of combining an emotion engine"

[0945] (Claim 1)

[0946] A means of inputting the expertise and skills of the members,

[0947] A means for generating an agent with learning capabilities based on input expertise and skills,

[0948] A means of performing emotional analysis on the generated agent and adjusting its behavior based on that state,

[0949] A means of creating video elements that visually represent the agent,

[0950] A means of placing the created video elements within a virtual environment,

[0951] A means by which other members select an agent to be placed and assign it to their own work device,

[0952] A means by which a work device uses an agent to assist in the work,

[0953] A system that includes this.

[0954] (Claim 2)

[0955] The system according to claim 1, characterized in that members transmit specialized knowledge and skills using a dedicated input device.

[0956] (Claim 3)

[0957] The system according to claim 1, characterized in that it uses lexical analysis technology in generating an agent with learning capabilities.

[0958] "Application example 2 when combining with an emotional engine"

[0959] (Claim 1)

[0960] A means of inputting the user's knowledge and skills,

[0961] A means for generating an intelligent agent based on input knowledge and skills,

[0962] A means for creating a display character that visually represents the generated intelligent agent,

[0963] A means of making the created display character publicly available in the virtual space,

[0964] A means for other users to select a publicly available intelligent agent and have it reside on their processing terminal,

[0965] A means by which a processing terminal uses an intelligent agent to support tasks,

[0966] A means of evaluating a user's emotional state using emotion recognition technology,

[0967] A means of dynamically adjusting the support content based on the user's emotional state,

[0968] A system that includes this.

[0969] (Claim 2)

[0970] The system according to claim 1, characterized in that the user inputs knowledge and skills using a dedicated interface.

[0971] (Claim 3)

[0972] The system according to claim 1, characterized in that it uses natural language processing technology in the generation of an intelligent agent. [Explanation of Symbols]

[0973] 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 inputting employees' knowledge and abilities, A means for generating an artificial intelligence agent based on input knowledge and abilities, A means of creating an avatar that visually represents the generated artificial intelligence agent, A means of making the created avatar publicly available in the virtual space, A means for other employees to select a publicly available artificial intelligence agent and have it reside on their work terminal, A means by which a work terminal uses an artificial intelligence agent to assist with tasks, A means of collecting and storing user preference information, A means by which an artificial intelligence agent provides product information based on collected preference information, A system that includes this.

2. The system according to claim 1, characterized in that employees input knowledge and skills using a dedicated interface, and user preference information is also input at the same time.

3. The system according to claim 1, characterized in that it uses natural language processing technology in generating artificial intelligence agents, and also uses similar technology in providing product information based on the user's preferences.

Images